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CHARISMA – D2.1 – final of 79

Converged Heterogeneous Advanced 5G Cloud-RAN Architecture for Intelligent and Secure Media Access

Project no. 671704

Research and Innovation Action

Co-funded by the Horizon 2020 Framework Programme of the European Union

Call identifier: H2020-ICT-2014-1

Topic: ICT-14-2014 - Advanced 5G Network Infrastructure for the Future Internet

Start date of project: July 1st, 2015

Deliverable D2.1

CHARISMA Initial Architecture Design and Interfaces

Due date: 30/06/2016

Submission date: 13/07/2016

Deliverable leader: Kai Habel (HHI)

Dissemination Level

PU: Public

PP: Restricted to other programme participants (including the Commission Services)

RE: Restricted to a group specified by the consortium (including the Commission Services)

CO: Confidential, only for members of the consortium (including the Commission Services)

Ref. Ares(2016)3361046 - 13/07/2016


List of Contributors

Participant Short Name Contributor

Fraunhofer HHI HHI Kai Habel, Volker Jungnickel

Innoroute INNO Marian Ulbricht, Andreas Foglar

JCP-Connect JCP-C Yaning Liu, Jean-Charles Point

University of Essex UESSEX Geza Koczian, Mike Parker, Terry Quinlan, Stuart Walker

Altice Labs ALB Victor Marques

Ethernity ETHER Eugene Zetserov, David Levy


Table of Contents 1. Introduction ...................................................................................................................... 8

2. Physical layer architecture for 5G ....................................................................................... 9

3. CHARISMA link technologies – design, interfaces, and 1st results .......................................12

3.1. PHY Security .....................................................................................................................................12 3.1.1. Quantum PHY Technologies.....................................................................................................12 3.1.2. Stokes-encrypted secure communication ...............................................................................13 3.1.3. 60-GHz Orbital Angular Momentum Wireless Communications .............................................13 3.1.4. Geometric Optical Phase Encryption .......................................................................................17

3.2. PON Introduction .............................................................................................................................21

3.3. New PON solutions ..........................................................................................................................22 3.3.1. XG-PON1 ..................................................................................................................................22 3.3.2. NG-PON2 ..................................................................................................................................23 3.3.3. NG-PON2 OLT and ONU optics [17] .........................................................................................26

3.4. OFDM-PON ......................................................................................................................................31 3.4.1. OFDM modulation....................................................................................................................31 3.4.2. OFDM transmitter and receiver ...............................................................................................31 3.4.3. OFDM-PON architecture ..........................................................................................................32 3.4.4. OFDM-MAC ..............................................................................................................................33 3.4.5. OFDM-PHY ...............................................................................................................................34 3.4.6. OFDM-Control ..........................................................................................................................34 3.4.7. Hardware realisation and targeted parameters ......................................................................35 3.4.8. OLT measurements ..................................................................................................................38 3.4.9. ONU measurements .................................................................................................................39

3.5. Wireless links ...................................................................................................................................41 3.5.1. Wireless standards and recent advances ................................................................................41 3.5.2. Recent work on 60 GHz ............................................................................................................44 3.5.3. Future 60-GHz integration .......................................................................................................46 3.5.4. Point-to-multipoint 60 GHz ......................................................................................................46 3.5.5. 60 GHz 802.11ad band experimental work .............................................................................48

4. Design of Network Elements .............................................................................................54

4.1. SmartNIC and virtual CPE ................................................................................................................54 4.1.1. HW Related Features: ..............................................................................................................55 4.1.2. Technical Specifications: ..........................................................................................................57 4.1.3. Virtual CPE Concept .................................................................................................................58

4.2. TrustNode ........................................................................................................................................63 4.2.1. TrustNode Concept – an Overview ..........................................................................................63 4.2.2. TrustNode Architecture ...........................................................................................................65 4.2.3. FlowEngine Basics ....................................................................................................................66 1.1.1. 6Tree Concept ..........................................................................................................................66

4.3. Network Caching Device ..................................................................................................................68

5. Conclusion ........................................................................................................................71

References ............................................................................................................................72

Acronyms ..............................................................................................................................74


List of Figures Figure 2-1: 5G architecture as proposed from the 5G-PPP Architecture Work Group ......................................9 Figure 2-2: Physical layer description of converged aggregation levels (CALs) [3] ......................................... 11 Figure 3-1: Poincaré sphere showing: (a) The constellation setup for 128 equidistant bases; and (b) the

effect of adding depolarized noise (approx. ~25% DOP). ....................................................................... 13 Figure 3-2: OAM state simulation, (a) L = 0 (no OAM), (b) L = 1, (c) L = 2, (d) L = 3. ....................................... 14 Figure 3-3: Horizontally separated HP for L = 1, 3, and 5; (a–c) mask simulation, (d–f) far-field diffraction

pattern. ................................................................................................................................................... 14 Figure 3-4: (a) HP superimposed mask for L = 3 vertically separated and L = 1 horizontally separated, (b) HP

superimposed far-field diffraction pattern of (a), (c) far-field diffraction with OAM representation. .. 15 Figure 3-5: Spiral phase plate for L = 3, 4, and 6; (a–c) phase mask simulation, (d–f) far-field diffraction

pattern. ................................................................................................................................................... 16 Figure 3-6: A 4-Gb/s uncompressed wireless OAM experimental setup. ....................................................... 17 Figure 3-7: Measured number of good packets with SPP in use for L = 4. ...................................................... 17 Figure 3-8: Poincaré Sphere representation of higher-order HG and LG modes in Stokes-space. ................. 18 Figure 3-9: Use of pairs of parallel cylindrical lenses and Dove prisms to achieve mode transformations

between LG and HG modes, and closed contour loop on Poincaré Sphere surface for geometric phase modulation. ............................................................................................................................................. 18

Figure 3-10: Round-loop system set-up allowing Alice to transmit cryptographic data to Bob using differential geometric phase. ................................................................................................................. 19

Figure 3-11: General PON architecture ........................................................................................................... 21 Figure 3-12: PON Standards evolution ............................................................................................................ 22 Figure 3-13: ITU-T G.987 wavelength plan ...................................................................................................... 23 Figure 3-14: Coexistence Element (ITU-T G.989) ............................................................................................ 25 Figure 3-15: TWDM-PON ................................................................................................................................. 26 Figure 3-16: NG-PON2 OLT line cards .............................................................................................................. 27 Figure 3-17: NG-PON2 XFPs types ................................................................................................................... 28 Figure 3-18: NG-PON2 ONU ............................................................................................................................ 28 Figure 3-19: PIC for NG-PON2. Chip received from the foundry. .................................................................... 30 Figure 3-20: PIC for NG-PON2. Detail of packaging with wire bonding for the electronic circuit ................... 30 Figure 3-21: OFDM signal generation (principle) ............................................................................................ 31 Figure 3-22: Generic OFDM transmitter .......................................................................................................... 32 Figure 3-23: Generic OFDM receiver ............................................................................................................... 32 Figure 3-24: Setup of OLT and ONU ................................................................................................................ 32 Figure 3-25: OFDM-PON Layered architecture ............................................................................................... 33 Figure 3-26: OFDM-MAC (Implemented VHDL blocks for OLT transmitter) ................................................... 33 Figure 3-27: OFDM-PON-PHY (Implemented VHDL blocks for OLT transmitter) ............................................ 34 Figure 3-28: OFDM-PON-PHY (ONU receiver) ................................................................................................. 34 Figure 3-29: OFDM-Control architecture ........................................................................................................ 35 Figure 3-30: Planned OFDM-PON hardware for trials ..................................................................................... 36 Figure 3-31: FPGA platform for OFDM-PON: OLT(a), ONU(b) ......................................................................... 37 Figure 3-32: Block diagram of OFDM-PON ONU platform .............................................................................. 37 Figure 3-33: Measurement setup OLT-PON (Tx) ............................................................................................. 38 Figure 3-34: Received spectrum (blue: unfiltered, red: filtered) .................................................................... 38 Figure 3-35: Estimated SNR (for training symbols) for all subcarriers ............................................................ 39 Figure 3-36: Constellation diagrams (for training symbols) ............................................................................ 39 Figure 3-37: ONU test setup ............................................................................................................................ 40 Figure 3-38: OFDM-PON ONU: partial reception of OFDM spectrum ............................................................. 40 Figure 3-39: Example of downlink MU-MIMO ................................................................................................ 42 Figure 3-40: Specific attenuation for atmospheric oxygen and water vapour ................................................ 42


Figure 3-41: Worldwide frequency allocation at 60 GHz band. ...................................................................... 43 Figure 3-42: Active antenna and wireless card ............................................................................................... 44 Figure 3-43: Omnidirectional antenna basic characterisations, left: 90° azimuth directivity for docking

station; right: 330° azimuth directivity for laptop. ................................................................................. 45 Figure 3-44: Live streaming of 4K UHDTV signals over 802.11ad.................................................................... 45 Figure 3-45: 60 GHz D2I integration in the proposed CHARISMA architecture .............................................. 46 Figure 3-46: TP Link 802.11ad router [30] ....................................................................................................... 47 Figure 3-47: 60 GHz beam-steering technology [30] ....................................................................................... 47 Figure 3-48: Throughput and latency measurement experimental setup ...................................................... 47 Figure 3-49: RF port wire bonds ...................................................................................................................... 49 Figure 3-50: Detail of RF Line Model ............................................................................................................... 49 Figure 3-51: RF port S11 Return Loss ................................................................................................................ 50 Figure 3-52: RF port S11 Impedance Smith Chart ............................................................................................. 50 Figure 3-53: S11 E-Plane Showing Radiation Confinement ............................................................................... 51 Figure 3-54: Detail of LO Line Model ............................................................................................................... 51 Figure 3-55: LO Port S11 Return Loss ................................................................................................................ 52 Figure 3-56: LO Port S11 Impedance Smith Chart ............................................................................................ 52 Figure 3-57: S21 E-Plane Showing Radiation Confinement .............................................................................. 53 Figure 3-58: 10 Gb/s DQPSK eye diagrams ...................................................................................................... 53 Figure 4-1: Traditional (left) vs. Cloud based (right) CPE implementations .................................................... 54 Figure 4-2: ACE-NIC: Block Diagram ................................................................................................................ 56 Figure 4-3: ACE-NIC: HW Block Diagram ......................................................................................................... 57 Figure 4-4: vE-CPE Location Examples ............................................................................................................. 58 Figure 4-5: Non-Virtualized CPE and vE-CPE ................................................................................................... 59 Figure 4-6: No Home Virtualization ................................................................................................................. 60 Figure 4-7: Home V-function ........................................................................................................................... 61 Figure 4-8: Smart NIC....................................................................................................................................... 62 Figure 4-9: TrustNode Concept ....................................................................................................................... 64 Figure 4-10: Direct Flows and Default Flow .................................................................................................... 64 Figure 4-11: TrustNode Architecture ............................................................................................................... 66 Figure 4-12: Hierarchical routing with 3 example paths ................................................................................. 67 Figure 4-13: MoBcache prototype ................................................................................................................... 68 Figure 4-14: MoBcache block diagram ............................................................................................................ 69 Figure 4-15: Networking of MoBcaches .......................................................................................................... 69 Figure 4-16: physical architecture and channels arrangement ....................................................................... 70


List of Tables Table 3-1: Main features of XG-PON1 ITU-T G.987 ......................................................................................... 23 Table 3-2: NG-PON2 XFPs Characteristics ....................................................................................................... 27 Table 3-3: NG-PON2 XFPs models ................................................................................................................... 27 Table 3-4: Planned parameter for OFDM-PON (OLT and ONU) ...................................................................... 36 Table 3-5: Basic technology parameters for 802.11ac and 802.11ad ............................................................. 41 Table 3-6: 60 GHz Band Channel Plan ............................................................................................................. 43 Table 4-1: technical specification .................................................................................................................... 57 Table 4-2: Performance comparison ............................................................................................................... 61 Table 4-3: Smart NIC server requirements ...................................................................................................... 62 Table 4-4: Flow acceleration methods ............................................................................................................ 65


Executive Summary

This deliverable discusses the initial results achieved during the first year of the CHARISMA project of the activities performed within WP2, including the PHY layer design, link technologies, intelligent nodes, and security technologies.

In particular, following the introduction of the converged aggregation layer (CAL) nodes into the CHARISMA hierarchical 5G network, the CAL-based hierarchical approach has been adopted by the 5G-PPP architecture group within its 5G Architectures White Paper [1], and has had an important influence on the design and specifications technologies associated with the each of the CAL nodes of the 5G architecture. This is discussed in Chapter 2, where the low latency, open access, and security aspects of the PHY layer design, virtualised functional architecture, and individual equipment at each CAL (including CPE) have provided the context to the work performed in WP2 thus far.

CHARISMA has focussed on those 5G networking technologies located behind the final radio link, and these are discussed in Chapter 3. Particular PHY layer link aspects include a discussion of physical layer security based on three main technologies: namely Stokes-encrypted secure communication, orbital angular momentum (OAM) wireless communications, and geometric optical phase encryption. In addition, initial results on the research into PON technologies (for the backhaul) are discussed. For OFDM-PON the initial design is described and first experimental results are shown. Fronthaul and final-drop technologies based on 60 GHz wireless links are also presented, with the initial design and first measurements given.

A key aspect of the research in CHARISMA is the intelligent CAL nodes, which are described in the following chapter. For the three main CAL node technologies: SmartNIC, TrustNode and MoBcache, the initial design for each of these technology solutions is described and the first hardware examples illustrated. The SmartNIC is a FPGA-based network interface card that allows the acceleration of network functions in a virtualized network infrastructure for 5G. The TrustNode router is also FPGA-based at the CAL network node, and allows routing with low latency using the 6Tree algorithm. The MoBcache devices for hierarchical network caching, enable mobile but also fixed applications to be integrated at all levels of the CHARISMA network hierarchy and can significantly reduce the service access time latency for cached content.

The results reported in this deliverable will feed into the demonstrator/field-trial work being conducted in WP4, as well as inform the on-going architecture refinements taking place in WP1, and will also be used for the design of the associated control, management and orchestration (CMO) plane in WP3. In addition, the on-going research in WP2 means that the results reported in this deliverable will be updated by means of the following WP2 deliverables (D2.2 and D2.3) in the second and third years of the CHARISMA project.


1. Introduction

This deliverable provides the initial architecture design and interfaces for the CHARISMA project, and focuses on the initial outcome of the activities performed within the various current WP2 tasks, including the PHY layer design, link technologies, intelligent nodes and security technologies. The work described in this deliverable will then be updated by means of the following WP2 deliverables in the second and third year.

The deliverable is organized as follows. It starts with a chapter describing the two-way interaction of the 5G-PPP Architecture Work Group and the architectural design work performed within CHARISMA, with a focus on the physical layer representation of the architecture. The introduction by the CHARISMA project of the Converged Aggregation Layer (CAL) nodes to create a hierarchical 5G network has been adopted by the 5G-PPP architecture group, which has been setup in order to facilitate sharing and discussing architecture aspects developed and considered in different 5G-PPP projects. CHARISMA has had a large influence on the associated 5G Architecture White Paper [1]. The CAL hierarchy of the CHARISMA architecture has been designed to support the low latency, open access, and security aspects of the PHY layer design, as well as the virtualised functional architecture. These architectural aspects have provided the background context to the WP2 work reported in this deliverable.

This deliverable characterizes CHARISMA’s initial 5G research on link technologies for the network behind the final radio link. Three main PHY security technologies, namely Stokes-encrypted secure communication, orbital angular momentum (OAM) wireless communications, and geometric optical phase encryption are discussed. These techniques can be employed and integrated into the overall CHARISMA end-to-end v-security solution. Further on, the latest research is presented on different passive optical networks (PON) solutions providing bitrates of 100 Gb/s or more. For the PON based on Orthogonal Frequency Division Multiplexing (OFDM) an initial design is given and the first experimental results are shown. The initial design and first measurements are also given for the wireless link technology using the 60 GHz band. A key aspect of research in CHARISMA is the concept of intelligent nodes, with some of the technologies and functionalities (including virtualisation) associated with such distributed intelligence described in the following chapter. For the three main node technologies, SmartNIC, TrustNode and MoBcache the initial design is described and the first hardware results illustrated. The SmartNIC is a FPGA-based network interface card (NIC) that allows the acceleration of network functions in a virtualized network infrastructure for 5G. The TrustNode is also a FPGA-based network node, and allows low latency routing using the 6Tree algorithm. The MoBcache devices for mobile but also fixed applications can be integrated in all level of the network hierarchy and can significantly reduce the access time latency for cached content.


2. Physical layer architecture for 5G

5G not only represents the next generation of wireless networking, but rather, the term 5G has been also broadly used recently in the telecommunications networking community to represent the new evolution of mobile broadband networks, which includes fixed and wireless, and the fixed access network interfaces between the radio link and the core network. The research in CHARISMA is mainly focused on the access network behind the radio link, while other projects in the 5G-PPP programme are more focused on the radio link. The 5G-PPP Architecture Work Group has also produced a white paper document [1] that provides a consolidated view of the physical layer architecture among all the various 5G-PPP projects.

Radio heads and base stations have been typically connected via heterogeneous transport technologies like fibre or copper lines together with micro-wave, mm-wave, and optical wireless links. Depending on the actual technology, all traffic is aggregated at the regional/metro networks. A consolidated overview of these different technologies is shown in Figure 2-1.

Figure 2-1: 5G architecture as proposed from the 5G-PPP Architecture Work Group

The two major access technologies, namely Passive Optical Networks (PONs) and active networks with a central Active Remote Node (ARN) are connected to metropolitan networks here. The active networks, connected e.g. via a dedicated wavelength with the metro network, have an ARN, which aggregates the traffic from homes, SMEs, macro cell sites, or other customers.

The second access technology - the PON consists of:

a Central Node – the Optical Line Terminal (OLT) at the central office;

2MP MP

2MP MP

Elastic Frame-based MetroWDM

FlexGridROADM

FlexGridROADM

FlexGridROADM

FlexGridROADM

2MP MP

2MP MP


an Optical Distribution Network (ODN) including a passive power splitter (or an arrayed-waveguide grating, AWG) at a Remote Node; and

Optical Network Units (ONUs) connected via individual fibres, which connect themselves customer premises, SMEs, etc. to the PON.

The general PON architecture is also discussed in section 3.2. The available bandwidth of a PON is shared by means of time-division multiplexed access (TDMA) and/or wavelength-division multiplexed access (WDMA). In this context, next-generation (NG)-PON2 has introduced wavelength-division multiplexing (WDM) as a means to multiply capacity to Nx10 Gb/s in the downstream [2]. However, one of the key research topics of CHARISMA is to exploit orthogonal frequency division multiplexing (OFDM)-PON technology, which promises to reach multiple 100 Gb/s per wavelength by a more efficient usage of the optical spectrum and efficient utilisation of frequency modulation techniques.

The discussion in CHARISMA about the location of the computing, storage or networking functions (physical and virtual) has also generated increased interest within the 5G-PPP forum, and the associated discussions have also been taking place in the 5G-PPP architecture work group. As a result, a new and consolidated architecture for 5G has been proposed and summarized below. For a more detailed description of the architecture it is recommended to read the original white paper from the 5G-PPP architecture work group [1].

The physical deployment opportunities offered by the current fixed network architectures to 5G suggests a hierarchy of five different computing resource categories as shown in Figure 2-1:

Central cloud;

Regional cloud;

Edge cloud;

Nano cloud (cloudlet nodes); and

Physical network functions (PNFs).

All these computation resource categories (which therefore also include possible locations for virtualisation of physical resources and networking functions) map well with the CHARISMA architecture as depicted in Figure 2-2 ([3]).

The central and regional clouds can be considered to be located in the core and metro (regional) network domains, and are described in greater detail in the following paragraphs:

A central cloud node lives in a centrally located data centre (DC). Such a DC centre hosts a large collection of processing, storage, networking, and other fundamental computing resources. Tenants are allowed to deploy and run arbitrary software, e.g., operating systems and applications etc., on such node. Typically in the current context, only a few central cloud nodes are to be found in a nationwide operator network.

A regional cloud node is available in densely populated metropolitan, urban, and suburban areas. Besides hosting network functions, these nodes also host software deployed functions and run on behalf of a consumer, again including operating systems or applications. The number of regional cloud nodes is at least one order of magnitude greater than the number of central cloud nodes.

In the access network domain, which is within the scope of the CHARISMA project, are to be found the locations of the edge and the nano clouds:

An edge cloud node is implemented inside an access branch of the fixed network, serving, e.g. a city quarter, and thus is even closer to the end-user. In a typical deployment, it would be situated inside the CO and would be referred to as a CAL3 node as defined in CHARISMA.


A cloudlet (nano cloud) is a mobility-enhanced small-scale cloud data centre (micro data centre, or

DC) that is located at the edge of the network collocated with the macro cell sites. In the case of an active deployment based on the ARN, both the cloudlet and the macro-cell sites would be co-located with the ARN. The main purpose of the cloudlet is supporting resource-intensive and interactive mobile applications by providing powerful computing resources to mobile devices and Internet of Things (IoT) devices with lower latency. This nano cloud has connectivity with the CAL2, CAL1 and CAL0 nodes (or devices) in CHARSIMA, which describe the initial available aggregation levels, and are closer to the end-users as compared to legacy networks.

Figure 2-2: Physical layer description of converged aggregation levels (CALs) [3]

Of particular relevance to this deliverable, is to point out that CHARISMA envisions a 100G OFDM-PON as providing the backhaul connectivity between CAL3 and CAL2, as indicated in the Figure 2-2. Likewise, mm-wave (i.e. 60-GHz) links can also be employed to provide the required connectivity between CAL2 and CAL1 (i.e. the front-haul), as well as between CAL1 and CAL0 for the final drops (i.e. which can be considered as the perimetric-haul) in the CHARISMA context. In addition, although described already in greater detail in the reference [3], the Figure 2-2 also highlights the Intelligent Management Unit (IMU) located at each of the CALs, and containing the required computation resources, e.g. for storage (i.e. hierarchical caching), and security functions etc.

CAL: Converged Aggregation Level


3. CHARISMA link technologies – design, interfaces, and 1st results

This chapter gives an overview of the link technologies developed in CHARISMA’s WP2 during the first year. It includes PHY security, PON research, and results for wireless links using the 60 GHz frequency band.

3.1. PHY Security

The issue of security applies to all levels of the communications stack, with each level needing to appropriately address security, independently of the other stacks. However, being the fundamental level of the stack, it could be argued that the physical (PHY) layer could be considered to play a particularly important role, since any failure at the PHY level will almost certainly impact the upper layers, either from a security point of view, or indeed in their ability to successfully play their roles in the communications stack.

Issues of security of particular relevance to 5G networking include: Authentication (personal ID), confidentiality & privacy (including encryption, key distribution etc.), and anonymity; Authorisation – e.g. for Access rights to the 5G network; Network resilience (including DoS & DDoS attacks, reliability, and restoration; Virtualisation of network functions (particularly with regard to issues of impersonation, and hijacking of and signalling functions); Transparency (i.e. low latency, and unobtrusiveness of security features, including QoS/E and SLAs etc.) Here, we present an overview of the latest PHY layer technologies being developed, with particular regard to encryption and key distribution. The other PHY issues related to network resilience and transparency are dealt with in other parts of the CHARISMA project (i.e. WP1, in the architecture design), whilst the issue of network functions virtualisation (NFV) while being strongly related to the actual architecture hardware being virtualised is considered within WP3. In that context, virtualised security (v-security) via the use of virtual security functions (VSFs) are also being investigated within WP3. A successful end-to-end CHARISMA security solution will require coherent integration of the PHY security and v-security solutions to provide the required secure end-to-end link security. These integration aspects will be investigated in the second and final years of the CHARISMA project.

3.1.1. Quantum PHY Technologies

At the PHY level, it could be argued that the issues of privacy and encryption are essentially solved. For example, quantum key distribution (QKD) is now a well-established technology, for fibre-optic networking, offering fundamental quantum-based security. Quantum cryptography has attracted considerable research interest [4][5][6][7] since the BB84 proposal by Bennett and Brassard [7]. However, the same no-cloning theorem that guarantees their security renders them incompatible with amplified optical networks and their use is limited to secure low data rate quantum key distribution (QKD). Another quantum technique [5][6] makes use of coherent states and uses inherent quantum noise to encrypt the data stream. However again, optical amplification destroys the quantum states and hence the basis of inherent security, which limits the distance of the method.

Indeed, the quantum technologies have the principle weaknesses of distance, and jamming, both of which are arguably intrinsic to the quantum nature of the technology; hence, the extent of the security is limited. In addition, related to its relatively low distance, due to the low intensity of the light, is its relatively low bit-rate. But once a QKD link is established, then it is secure. In the 5G networking context, where there is a converged fixed and wireless aspect to the overall communications link, it is clear that the fibre optic component of the link can therefore be made essentially secure; however, the application of QKD technology into the wireless domain is less obvious. First of all QKD employs photons at optical frequencies; and secondly


the very low intensities (i.e. individual photons are counted in the QKD procedure) make optical fibre an optimum means to conserve the number of photons being conducted. In the free-space environment, the effects of diffraction mean that the intensity is quickly attenuated, and the useful effectiveness of the method is rapidly lost. In addition, with the wireless radiation essentially diffracting away from the receiver location, interception of such misdirected radiation offers alternative eavesdropping opportunity. Another issue with the mm-wave and microwave domains is that the QKD method intrinsically is based upon the production of entangled photons via non-linear optical effects; the achievement of such entangled photons at mm-wave frequencies via appropriate non-linear processes is not yet in practical sight. As an alternative, there have been other schemes proposed, which while not offering the same degree of security as QKD, still offer a very secure key distribution possibility.

3.1.2. Stokes-encrypted secure communication

Stokes-encrypted secure communication [8] offers one solution where the key is hidden within a highly noisy landscape. The method also offers full data rate that allows optical amplification without degrading the security level. It therefore offers opportunities for secure communication over long distances. In particular, the signal of interest is hidden within an equidistant constellation of bases on the surface of the Poincaré sphere; i.e. the representation of polarization states in Stokes space.

Figure 3-1: Poincaré sphere showing: (a) The constellation setup for 128 equidistant bases; and (b) the effect of adding depolarized noise (approx. ~25% DOP).

The plaintext is encoded as a binary polarisation shift-keying (PolSK) signal encrypted through implementation of a full Poincaré occupancy M-PoISK signal using a Polarization Modulator as the transmitter and a self-correcting Stokes analyser as the receiver. Fully depolarized noise (ASE from EDFA) is added to the polarization encrypted data to hide the data and the key. The encrypted data stream has been transmitted over 50km of G.652 fibre. With knowledge of the key, Bob only has to make a decision on two levels, and hence the error rate is extremely low. Experimental measurements show error-less (BER<10-9) transmission up to 14% DOP. A potential eavesdropper, conversely, has to make a decision on N levels (actually 2N levels, including the antipodes), and hence the data stream is close to a random guess.

3.1.3. 60-GHz Orbital Angular Momentum Wireless Communications

Related to the use of Stokes space and polarization shift keying, is the use of orbital angular momentum (OAM) states for the transmission of data, and also as a means for cryptographic and secure data transmission [9]. OAM is a higher-order state of polarization, which can also be represented on the surface of a Poincaré sphere, and hence the same cryptographic techniques as used for the Stokes-encrypted optical fibre case (above) can be employed, but in the wireless domain. The latest research results on 60-GHz (mm-wave) communications systems are described later in this document in section 3.5. Applying the use of OAM for mm-wave communication has already been demonstrated [9], but the exploitation of OAM technology for cryptographic transmission is now an area of on-going research within the CHARISMA project. We first provide some background context to the use of OAM states (Figure 3-2) in a mm-wave communications system, before describing a method for using geometric phase modulation based on OAM states as the basis for cryptographic transmission.


Figure 3-2: OAM state simulation, (a) L = 0 (no OAM), (b) L = 1, (c) L = 2, (d) L = 3.

Amplitude OAM is achieved by placing a holographic plate (HP) directly in front of a 60-GHz radio wave. The main elements of holographic masks are observable in a fork-grating dislocation of HP (Figure 3-3(a)–(c)), where the plane input wave is transformed through this area. The shape and behaviour of fork grating is controlled by topological charge (L) [10] that is the number of phase twists around the vortex. A radio vortex beam is the product of the phase-only interference of an indirect plane reference wave.

Figure 3-3: Horizontally separated HP for L = 1, 3, and 5; (a–c) mask simulation, (d–f) far-field diffraction pattern.

L is the topological charge of the radio vortex to be created and K is the number of grating lines per unit length.

1) Holographic Plate (HP)

Corresponding to the L value of each OAM state, HP masks are created with a central dislocation as a phase grating in horizontally separated patterns (Figure 3-3 (a)–(c)). After the input signal passes through the


disturbance in the middle of the horizontally/vertically separated HP mask, the optical signal diffracts and in the far field generates the OAM state (Figure 3-3 (d)–(f)).

2) Superimposed HP

A complex HP configuration (Figure 3-4 (a)) is created by superimposing horizontally and vertically separated HP masks in order to increase the number of OAM states from an input beam.

Figure 3-4: (a) HP superimposed mask for L = 3 vertically separated and L = 1 horizontally separated, (b) HP superimposed far-field diffraction pattern of (a), (c) far-field diffraction with OAM representation.

Phase OAM

Changing the phase of an incoming radio signal around a 2π circle is an alternative way of generating an OAM; in theory, an infinite number of OAMs are possible. The power of the incoming radio signal is not reduced by utilizing the phase plate instead of HP hence, after the entering transmitter signal has passed through the phase plate, most of the signal energy is maintained. Phase OAM is created by inserting a SPP directly in line with the 60-GHz beam.

1) Spiral Phase Plate (SPP)

SPP was simulated corresponding to the L value, which determines each OAM state (Figure 3-5 (a)–(c)). After the input signal passes through the phase variation on each plate, an OAM state is generated by forming the relevant far-field diffraction of the input signal. As the step height of the SPP is raised, the OAM intensity decreases and the “black hole” in the middle of the OAM state expands apart. Therefore, a larger area in a doughnut-shaped ring is created because more OAM states are compacted in a single radio beam.


Figure 3-5: Spiral phase plate for L = 3, 4, and 6; (a–c) phase mask simulation, (d–f) far-field diffraction pattern.

In order to demonstrate the practicality of a 4-Gb/s uncompressed OAM radio channel, an OFDM wireless 60-GHz mm-wave reference system (Figure 3-6) was set up as a test bed in order to perform experimental measurements. The transmitter antenna was set to ‘lock straight beam’ mode using GUI controlling software. The transmitted 60-GHz signal was further localized utilizing a brass aperture with 5 mm gap in the middle before it was radiated on to HP or SPP surface. The size of the gap was chosen so that it corresponded directly with the 60-GHz wavelength. The output data of the Matlab1 simulation was utilized to create realistic HP masks by controlling a printed circuit board router to drill the required shapes on copper plates. In addition, a realistic model of SPP (Figure 3-5 (a)) with adjustable step height was manufactured using Polytetrafluoroethylene (PTFE), known as Teflon. The L value is chosen by modifying the step height. The received power was measured along a horizontal line scan as various OAM modes were generated in the far-field region utilizing HP or SPP techniques.

1 https://mathworks.com/products/matlab/index.html


Figure 3-6: A 4-Gb/s uncompressed wireless OAM experimental setup.

The measured amplitude (HP method) and phase (SPP method) OAM signal, as shown in Figure 3-6 were determined by measuring the far-field diffraction patterns when utilizing HP and SPP. In both cases, the input plane beam is a 60-GHz signal and the experimental results were obtained by measuring the signal strength across a horizontal scan. As shown in Figure 3-7 using the SPP technique with L = 4, the number of good packets per second was also measured and plotted across the distance of horizontal scan. The OAM mode effect on the transmission of 4-Gb/s uncompressed video is clearly visible.

Figure 3-7: Measured number of good packets with SPP in use for L = 4.

OAM is associated with angular momentum that is dependent on field spatial distribution for transmission, unlike multiple-input multiple-output (MIMO) that utilizes multiple antennas approach. As the use of 60-GHz technology becomes more widespread with the advent of IEEE 802.11ad-based modules, for example, its suitability for spatial multiplexing based on OAM and holographic beamforming offers opportunities for further increases in capacity.

3.1.4. Geometric Optical Phase Encryption

The Poincaré sphere also offers the possibility of geometric phase encryption, via a novel cryptographic differential topological phase protocol for secure photonic networking. Eavesdropping is detected when the geometric (or Berry [11]) phase of higher-order modal transmission is perturbed by the presence of an eavesdropper. The method relies on the multiplexing of higher-order modes of light onto a single optical fibre such that only one mode is sensitive to geometric phase variation. At the transmitter side, the higher-order mode sensitive to geometric phase variation is modulated with the data to be encrypted, while the second, zero-order, insensitive mode passes through the same modulator, but with no effect. Instead, the lowest (zero) order mode (i.e. the conventional basic mode of SMF) acts as a phase reference for comparison with the modulated first mode. After transmission through the network physical layer, the signal is retrieved from the inter-modal phase. Any attempt to eavesdrop onto the signal, e.g. through tapping or evanescent coupling of light out of the optical fibre etc., causes the path topology to change between transmitter and


receiver, with the associated differential geometric phase shift being detected at the receiver. Security of the signal is thus guaranteed in an analogous manner to that of quantum cryptography, i.e. eavesdropping is automatically detected, but will also tend to corrupt the signal. However, in contrast to quantum cryptography, the geometric phase cryptography described here has no power limitation, so that distance and bit-rates are not as constrained.

Figure 3-8: Poincaré Sphere representation of higher-order HG and LG modes in Stokes-space.

Figure 3-8 shows a Stokes-space Poincaré Sphere representation of the higher-order Laguerre-Gaussian (LG) and Hermite-Gaussian (HG) fibre-optic waveguide modes [12]. Together, the LG and HG modes are not only analogous to the conventional polarisation (spin) states of light, but are phenomenologically linked by their orbital angular momentum (OAM). Any closed path trajectories on the surface of the Poincaré Sphere lead

to geometric phase accumulation, indicated by the solid angle subtended by the closed contour path at the centre of the sphere [13], see Figure 3-8.

Figure 3-9: Use of pairs of parallel cylindrical lenses and Dove prisms to achieve mode transformations between LG and HG modes, and closed contour loop on Poincaré Sphere surface for geometric phase

modulation.

Figure 3-9 indicates how the azimuthal and elevation angle changes may be achieved in practice. Here,

the elevation angle can be changed by use of a pair of parallel cylindrical lenses (or their integrated optics

alternatives). Axial rotation of the pair of cylindrical lenses by an angle /4 introduces the required /2 phase

change in the elevation angle and conversion between LG and HG modes. A spatial rotation by /2 of a

pair of Dove prisms is used to accomplish the required azimuthal phase change , whilst also causing an

angular variation of 2 in the associated Stokes space.


Figure 3-10: Round-loop system set-up allowing Alice to transmit cryptographic data to Bob using differential geometric phase.

Figure 3-10 shows how the two modes of light are multiplexed. At Bob (the receiver), a computer-generated hologram (CGH) exhibiting a single phase line dislocation [12] (i.e. equivalent to Figure 3-2 (a)) is placed

before a collimated lowest-order Gaussian beam of light, i.e. a LG00 mode. The CGH acts to diffract the light

into multiple orders, with the 0th-order (undiffracted) light emerging as a lowest order LG00 mode. First-

order diffracted light modes are respectively the LG0+1 and LG0

-1 modes, and constitute the +1st and -1st

orders; possessing oppositely-handed OAM respectively. These diffracted orders are passed into a power beam splitting cube BS1, and spatial filters (iris stops #1 and #2) used to select the desired orders in each of the consequent two optical paths. 0th-order light is allowed through the bottom path, whilst only the +1st-order diffracted light is selected in the upper path. A second power beam splitting cube (BS2) acts to combine

the two selected modes LG00 and LG0

+1 together. The two modes can now be passed through the

appropriate pairs of cylindrical lenses and Dove prisms as shown, with the LG00 mode experiencing no

geometric phase modulation, whereas the higher OAM mode LG0+1 undergoes the appropriate topological

phase modulation. Geometric phase on a closed contour trajectory on the surface of the Poincaré Sphere is assessed by considering the whole round-loop transmission link between Alice and Bob. In this case, the

geometric phase associated with the LG0+1 mode is only accumulated once the LG0

+1mode arrives back at

Bob. Considering the trajectory along the Poincaré sphere (Figure 3-8), the LG0+1mode starts at the south

pole, and the combination of cylindrical lens pair and Dove prism at Bob causes the trajectory to reach a point on the equator.

The resulting HG01 cosq + HG10 sinq mode is then transmitted along the fibre, where the Hermite-

Gaussian mode mix (i.e. as described by the angle ) is varied in a random fashion due to fibre perturbations such as refractive index variations and fibre kinks, twists etc. Twisting effects have to be systematic (and extreme) over extended lengths of fibre for the two Hermite-Gaussian modes to becoming significantly out of phase with each other, e.g. to reach 90 degrees out of phase so as to convert into a Laguerre-Gaussian mode. On reaching back to the receiver (Bob), the cylindrical lens pair causes the mode to be transformed

back to the LG0+1mode at the south pole, and the contour is closed.

The LG0+1mode thus accumulates a geometric phase, which varies according to the overall geometry of its

trajectory on the Poincaré sphere surface, and the associated solid angle. The HG01 cosq + HG10 sinq

mode accumulates an additional path-dependent phase as it traverses the optical fibre link B-A-B; but the

co-propagating LG00 mode also accumulates the same path-dependent phase, since it follows exactly the

same in-fibre variation. In which case, the phase difference between the two modes on arrival at the receiver is purely the geometric phase. At its simplest, the differential geometric phase is detected by imaging the


fibre end onto a CCD camera, and noting the relative rotations of the resulting interference pattern from the

superposition of the LG0+1 and LG0

0 modes [14].

The protocol for secure data communication is accomplished as follows:

i) Bob is the original source of the reference LG00 mode and LG0

+1mode and transmits them both

along the fibre to Alice at A. However, Bob additionally adds a pseudo-random (e.g. binary phase,

0 or bit stream) differential phase qrand between the LG0

0 and LG0+1 modes using the Dove

prism (Figure 3-10).

ii) When the light signals of the two modes reach Alice at A, she initially simply sends them back to Bob again down a parallel optical fibre – alternatively, a fully reflective alternative may be possible, using optical circulators between Alice and Bob.

iii) Bob receives the return signal from Alice, and due to the random fibre perturbations discussed

earlier, there will be additional phase differences between the LG00 and LG0

+1 modes, over and

above the pseudo-random phase differences that Bob originally imposed. Using a suitable feedback system (which also has as a feed-forward input the stream of pseudo-random phase

differences qrand that Bob earlier imposed) Bob automatically adjusts the Dove prism at the

receiving end by a further phase qFB 2 to dynamically change the overall geometric phase

associated with the LG0+1 mode, to compensate for the combination of both the pseudo-random

phase stream he imposed and the accumulated path-dependent phase differences between the

LG00 and LG0

+1 modes, so as to equalize the phase between the two modes. Phase equalization

between the modes is straightforwardly checked and measured at a CCD detector, with an electrical feed-back signal send to the control unit to provide suitable feedback for the additional

phase angle qFB 2 applied to the Dove prism.

iv) Alice can now start transmitting the encrypted data to Bob by imposing an additional "data"

differential (geometric) phase onto the LG0+1 mode using the Dove prism in her set-up and

rotating it by the angle qData 2 , prior to passing the two modes back to Bob.

v) Only Bob knows the original random differential phase qrand he imposed onto the LG0

+1 mode,

and also the light has to complete the full journey B-A-B with its random perturbations along the length for there to be the correct balance/equalization between the path-dependent accumulated phase and the overall geometric phase due to the feedback. From the received phase difference between the two modes, Bob can therefore "subtract" his imposed random phase and the random phase due to the fibre path perturbations from the received differential signal phase, and hence successfully extract the data signal from Alice.

If there is an eavesdropper Eve somewhere between Alice and Bob then, even with a receiver identical to Bob’s, when she diverts a proportion of the signal, the full B-A-B path will no longer be accomplished by that proportion of light, and there will be no balance between the geometric phase and the path-dependent fibre-

perturbation phase. In which case, in addition to the pseudo-random phases qrand imposed by Bob onto the

signal, Eve is not in a position to be able to distinguish the "data" phases from all the other random phases. Advantageously, the more perturbations that the two modes experience along the path B-A-B, then the better is the protection due to the accumulated phase noise which will mask both the "data" phase and the random phases imposed by Bob. With higher-order modal multiplexing [15], and orbital angular momentum [16] transmission to more fully exploit fibre optical spectral capacity attracting ever-greater research attention, the PHY level cryptographic method is becoming more practicable for experimental demonstration.


3.2. PON Introduction

A passive optical network (PON) consists of a central node, where the OLT is located at the central office (CO), and many ONUs located at customer premises or at a radio network site (Figure 3-11). The OLT connects the PON with a metro network over an aggregated upstream link. ONUs are connected with the OLT over an optical distribution network (ODN), which is divided into feeder and distribution parts. A power splitter at the distribution point (DP) splits the optical signals, which are passed to each of the ONUs via individual fibres. The ONU itself is connected with a SME, macro cell site, home, or other customers. In most of the cases the ODN is passive, hence the name PON. In some cases an optical amplifier can be integrated with the DP in order to improve the optical signal-to-noise ratio (OSNR), and to increase either the reach or the split ratio.

Figure 3-11: General PON architecture

Access technologies, especially those based on PONs are evolving rapidly, especially in the context of 5G networking. Most commercial deployments nowadays are based on GPON technology that provides 2.5 Gb/s bandwidth in the downstream direction, and 1.24 Gb/s in the upstream, shared amongst, typically, 32, 64 or 128 customers.

The ITU has, and continues to be very active in standardizing new technologies that are able to coexist with GPON, while offering more bandwidth, and are able to compete with point-to-point solutions for business users and as a viable alternative for cellular backhaul.

In 2010, ITU-T Recommendation G.987 (referred to as XG-PON) was defined, based on a TDM-PON architecture. This technology is able to provide 10Gb/s in the downstream (4x more than GPON) and 2.5 Gb/s in the upstream (2x more than GPON).

In 2015, ITU-T released G.989 (NG-PON2) which is expected to be a long-term solution with an entirely new optical network type, based on what is called TWDM-PON technology, which stands for time- and wavelength-division multiplexing (TWDM). NG-PON2 typically provides 40 Gb/s bidirectional but may also provide up to 80 Gb/s bidirectional.

Regarding configuration, operation and maintenance, generic OMCI (Optical network unit management and control interface specification ITU-T G.988) applies to both GPON and XG-PON1, and also to NG-PON2.

CO DP

Distribution network

Feedernetwork

http://en.wikipedia.org/wiki/ITU-T


Figure 3-12: PON Standards evolution

The next section 3.3 presents the advances for XG-PON1and NG-PON2 technologies. Afterwards in section 3.4 new research on OFDM-PON is presented.

3.3. New PON solutions

We will begin with XG-PON1 due to the fact that NG-PON2 is strongly based upon “stacking” up to 8x XG-PON over the same fibre.

3.3.1. XG-PON1

As stated before, XG-PON1 provides 10 Gb/s of shared downstream capacity, combined with 2.5 Gb/s of upstream capacity. XG-PON1 uses the same framing and management of GPON. Full-service operation is provided via higher data rates and larger splits. This way, more capacity is added to the optical access network, without an increase in complexity. GPON and XG-PON systems may coexist on the same PON by using a wavelength coupler located at the central office. FSAN has selected the wavelengths for downstream as 1575-1580 nm and for upstream as 1260-1280 nm, mostly driven by the 10G optical transceivers market and the available bands, assuring legacy compatibility.

Most modern GPON ONUs have an integrated filter to eliminate interference from XG-PON1 wavelengths, which could be a barrier to the deployment of GPON and XG-PON1 on the same PON. However, older installed ONUs may not have such a filter, which has to be externally added to guarantee network compatibility. The wavelength plan for different PON technologies is depicted in Figure 3-13.


Figure 3-13: ITU-T G.987 wavelength plan

The main features of the XG-PON technology are compiled in the following table (Table 3-1).

Table 3-1: Main features of XG-PON1 ITU-T G.987

Optical fibre Single fibre transmission, compliant with ITU-T G.652

Wavelength plan Upstream 1260 nm to 1280 nm / Downstream 1575 nm to 1580 nm

Capacity Downstream: 10 Gb/s / Upstream: 2.5 Gb/s Support for dynamic bandwidth allocation (DBA) Full QoS and Traffic Managements

Nominal Line rate Upstream: 2.48832 Gb/s / Downstream: 9.95328 Gb/s

Media Access Control Layer

Upstream: TDMA / Downstream: TDM Forward Error Correction with Scrambled NRZ Line Encoding

Optical Power budget

Between 29 dB and 35 dB

Split Ratio 1:32, 1:64, scalable up to 1:256

Fibre Distance Differential distance of 20 km or 40 km. Logical Distance of up to 60 km.

Synchronization Enhanced timing and time of day synchronization for mobile backhaul applications

Enhanced security Strong mutual authentication; Authentication to protect the integrity of the PON management messages and the PON encryption keys.

Power saving Reduces the load during power failures (so that batteries last longer), by turning off those user network interfaces (UNI) that are not actively used Deactivating the transmitter for routine PON transmissions (“dozing”) Sleep mode, in which the ONU deactivates both its transmitter and receiver when the user has no activity (“sleeping”)

3.3.2. NG-PON2

NG-PON2 benefits from the latest high-speed laser technology and usage of multiple wavelengths. NG-PON2 provides up to 10 Gb/s downstream and up to 10 Gb/s upstream for one pair of wavelengths alone, further allowing combining of up to 4 (or even 8) such wavelength pairs onto one physical fibre using a Wavelength Multiplexer. This thus makes it the first symmetrical 40/80 Gb/s fibre access technology. The technology requires that the optical receiver and transmitter on the ONUs must be tuneable; that is, the selection of the wavelength channel must be performed automatically (that is, they must be able to send and receive signals on any of the specified wavelengths).


Beyond that, NG-PON2 runs each of multiple pairs of wavelengths as a single TDMA PON, each carrying, typically, up to 10 Gb/s down- and 2.5 Gb/s upstream; so that it is called a Time and Wavelength Division Multiplexed (TWDM) PON. In addition, NG-PON2 can optionally support point-to-point (PtP) Wavelength-Division-Multiplexing (WDM)-PON for even higher per user speeds (up to 10 Gb/s down- and 10 Gb/s upstream).

NG-PON2 can use up to 8 wavelengths for each direction, increasing the overall speed by up to a factor of x8 (downstream) and up to a factor of x32 (upstream), as compared to XG-PON.

Besides TWDM-PON, other technologies proposals were also under study to support the requirement of 40 Gb/s capacity:

WDM-PON

Coherent ultra-dense WDM-PON (UDWDM PON)

Orthogonal Frequency Division Multiplexing (OFDM) PON (see section 3.4)

40Gb/s TDM PON

The TWDM-PON approach was considered to be less risky, less disruptive and less expensive than the other considered approaches because it reuses existing components and technologies.

TWDM-PON has been chosen to have less impact (or no impact at all) on the network provider outside plant. Changes are confined to the PON's end equipment: the central office's optical line terminal (OLT) and the home or building's optical networking unit (ONU). Operators yet to adopt PON technology may use NG-PON2's extended reach to consolidate their network by reducing the number of central offices (COs) they manage.

NG-PON2 allows operators to place the different technologies – GPON, XG-PON1 and NG-PON2 – onto the same optical distribution network. Coexistence is ensured by a passive element, called the coexistence element (CE), which combines / splits the various wavelengths associated with each technology. When implementing NG-PON2, the main challenges are the spectrum allocation (compatibility with sensitive radio frequency services is essential).

Four topologies are currently being considered by the ITU-T, for NG-PON2:

Basic: 40 Gb/s downstream and 10 Gb/s upstream, using 4 wavelengths

Extended: 80 Gb/s downstream and 20 Gb/s upstream, using 8 wavelengths

Business: Symmetrical services, 40/40 Gb/s to 80/80 Gb/s

Mobile Fronthaul: PtP WDM

With NG-PON2 the providers may use a pay-as-you-grow approach. When deploying NG-PON2 it is unlikely that all 8 or even 4 wavelength pairs per ODN will be required from day 1. NG-PON2 allows for wavelengths to be added individually per fibre tree as they are required.

Using service-specific wavelength pairs allows service separation, avoiding potential performance or security issues associated with shared TDM / TDMA systems.


Figure 3-14: Coexistence Element (ITU-T G.989)

NG-PON2 devices support Mobile Backhaul (MBH) timing applications (IEEE 1588v2 Boundary Clock and Transparent Clock) to support accurate frequency and phase time requirements. NG-PON2 also offers a clear path to higher capacities, and therefore is expected to address the needs of network providers in the future. Indeed, some providers are targeting a direct migration from GPON to NG-PON2, skipping XG-PON1.

Figure 3-15 presents a TWDM-PON architecture example. Here, four 10 Gb/s wavelengths are multiplexed on the CO sent downstream. Each ONU will select its own wavelength, by using tuneable optical filters in front of the receiver.

On the upstream, each ONU operates on one of the 4 available wavelengths, previously selected by the OLT. Additionally, more ONUs may share a wavelength, just like in a GPON deployment.


Figure 3-15: TWDM-PON

3.3.3. NG-PON2 OLT and ONU optics [17]

3.3.3.1.NG-PON2 Products During CHARISMA, Altice Labs will have both NG-PON2 OLT line cards and NG-PON2 ONUs. The first OLT line cards will have 8 or 4 TWDM-PON interfaces, on which a single band XFP is used. The current NG-PON2 OLT optics are based on Bi-directional Optical Subassemblies (BOSAs) integrated on XFP form factor.

They are suitable for TWDM-PON, 10 Gb/s downstream, 2.5 Gb/s or 10 Gb/s upstream. The XFP integrates an electro-absorption integrated laser diode with semiconductor optical amplifier (SOA) in order to reach the type A N1 class (+5~+9 dBm at the output of the XFP) NG-PON2 optical requirements. A high sensitivity burst mode avalanche photodiode (APD), a pre-amplifier and a limiting amplifier as receiver components are mounted into a package integrated in single mode fibre-stub with a sensitivity equal to -28.5 dBm at 10 Gb/s; and -32 dBm at 2.5Gb/s).

The NG-PON2 ONU optics are based on BOSA on board. The BOSA integrates a burst mode tuneable distributed feedback lasers (DFB) at 10 Gb/s or 2.5 Gb/s emitting high optical power in a N1 type A link, +4 ~9 dBm capable of doing 4 upstream channels.

On the receiver side, a high sensitivity 4 channel tuneable APD a pre-amplifier and a limiting amplifier are able to operate at a sensitivity of -28 dBm at 10 Gb/s.

In a TWDM-PON system, multiple 10G optical transceiver modules are stacked and connected through an external passive optical multiplexer/demultiplexer. Such an encapsulated module is big in size and results in low integration at the OLT side. The industry generally favours using hybrid integration technology based on silicon photonics to replace the traditional discrete component assembly. The new technology can effectively reduce encapsulation size and increase optical module integration at the OLT side, as it will be explained on section 3.3.3.2.

MAC

TWDM PON O T

ONU

ONU

ONU

ONU

M

EM

s litter


Figure 3-16: NG-PON2 OLT line cards

The NG-PON2 OLT line card features the following main characteristics:

• Symmetrical (10G/10G)/Asymmetrical (10G/2.5G)

• 4 or 8xTWDM-PON physical ()OLT interfaces

• Common functionalities:

• Compliant with G.989.1, G.989.2, G.989.3

• XFP based optical interfaces: N1(29 dB), N2(31 dB)

• Management via generic OMCI (G.988)

• Wavelength control accordingly to G.989.3

• Bit rate per NG-PON2 :

• DS/US: 10/2.5 Gb/s or 10/10 Gb/s

• Configuration done per port

The current NG-PON2 OLT optics are based on Bi-directional Optical Subassemblies (BOSAs) integrated on

XFP form factor. To be able to use all the NG-PON2 s, the XFPs have different frequency bands, according to the channel they use (Table 3-2).

Table 3-2: NG-PON2 XFPs Characteristics

Channel No.

Transmitter wavelength Receiver wavelength Unit

Min. Typ. Max. Min. Typ. Max.

1 1596.18 1596.34 1596.50 1522 1532.68 1544 Nm

2 1597.03 1597.19 1597.35 1522 1533.47 1544 Nm

3 1597.88 1598.04 1598.20 1522 1534.25 1544 Nm

4 1598.73 1598.89 1599.05 1522 1535.04 1544 Nm

Table 3-3: NG-PON2 XFPs models

XFP Models Channel Descriptiom

Symmetric 10/10 1 XFP Sym TWDM N1A 1596.34/1532.68 nm

2 XFP Sym TWDM N1A 1597.19/1533.47 nm

3 XFP Sym TWDM N1A 1598.04/1534.25 nm

4 XFP Sym TWDM N1A 1598.89/1535.04 nm

Asymmetric 10/2.5

1 XFP Asym TWDM N1A 1596.34/1532.68 nm





Figure 3-17: NG-PON2 XFPs types

In Figure 3-17 are shown the two XFP types – the symmetric type for 10 Gb/s up- and downstream, and the asymmetric type for 10 Gb/s downstream and 2.5 Gb/s upstream.

The XFP for NG-PON2 are single fibre transceivers using SC connectors with:

L band EML laser diode as 9.95 Gb/s continuous-mode transmitter

C band APD as 2.488 Gb/s or 9.95 Gb/s burst-mode receiver The modules comply with ITU-T G.989 N1 Class, support Digital Diagnostic Monitoring (DDM) functions, and feature a burst mode received signal strength indication (RSSI) output.

Figure 3-18: NG-PON2 ONU

The ONU as depicted in Figure 3-18 have the following main characteristics:

TWDM-PON; Downstream: 10 Gb/s / Upstream: 10 or 2.5 Gb/s

Optical via embedded BOSA module: N1 (29 dB), N2(31 dB), E1(33 dB) and E2(32 dB)

G.989 compliant, full coexistence with GPON ITU-T G.984 and XG-PON G.987

Tx Wavelengths: 1524-1544 nm; Rx Wavelength: 1600-1610 nm; Wavelength tuning accordingly to G.989.3

4x GbE Interfaces, 2x FXS, Wi-Fi IEEE 802.11b/g/n/ac 2.4 GHz/5 GHz

USB 2.0, TR-247 and TR-069, Management via OMCI ITU-T G.988

Redundant power supply

3.3.3.2.Closing the gap between Photonic Integrated Circuits (PICs) and PONs Altice Labs is currently investigating the use of photonic integrated circuits (PICs) in order to be able to have a future OLT line card, where it will be possible to have 4 NG-PON2 channels on a single OLT card port. The PIC will be integrated on a Q-XFP form factor. This section describes the ongoing work on this area.


The road to commercial PICs Affordable, efficient integration is now starting to occur in photonics. Photonic Integrated Circuits (PICs) are the dual of electronic integrated circuits in the optical domain as they perform integrated computing and signal processing functions that are based on light. Their main application is fibre-optic communications but they can also be used in biomedicine, photonic computing and sensing.

Photonic integration emerged at the end of the 1960s [18], but the era of high-complexity PICs started in 1988 when Smit published the invention of the Arrayed Waveguide Grating [19]. Almost 20 years after, Infinera launched the first truly complex PIC in a commercial telecommunications system [20].

Research context, objectives and work plan PICs may be used in countless applications, however their fast development has been due to their applications for systems based on fibre optics communications. In the telecommunications industry the goal is to reach as much clients as possible at the least cost providing the best service. The demand for bandwidth and the number of users has been increasing constantly, and the technology that can keep up with these demands is that of fibre optic communications, because it is the only technology that can supply the requisite high data rates and reach the necessary large distances. PONs are networks that do not need amplification or regeneration of the signal from the central office to the users, due to the optical fibre properties that can reach up to at least 40 km. Although first generation PONs have been a success, the bitrates that are provided do not take full advantage of the fibre capabilities, and thus new standards such as NG-PON2 are now ready to be deployed. It can quadruple (or even x8) the bandwidth and uses the optical spectrum more efficiently. With these improvements, the complexity of the networks and the components also increases, which translates into greater difficulty in controlling the components, more room (i.e. a greater footprint) being needed in the CO, and a higher power consumption. In order to tackle the problems that arise with this evolution, PICs are needed. With the integrated version of the discrete implementation, the associated control complexity, floor space (footprint), and power consumption are all decreasing. Integration also means a decrease in costs, which makes these networks more affordable. However research still needs to take place to turn PICs into a fully competitive technology.

To increase the competitiveness of PICs, several projects have been developed so that generic foundry models were created and different users can contribute to the design of a single wafer in the same process; i.e. the so-called Multi Project Wafer (MPW) run [18][21]. The cost of a MPW run when compared with a normal commercial run can be one to two orders of magnitude cheaper, thus leveraging the increase of research in the field. The idea of generic integration is that the user is agnostic to the way the foundry implements the technology and sees the components as building blocks, which means that if different foundries have the same building block (e.g. amplifier) it is very easy to translate from one foundry to another. Currently, there are three main platforms to develop PICs: Silicon (Si), Indium Phosphide (InP) and TriPleX (combination of Silicon Nitride – Si3N4, and Silicon Dioxide – SiO2). Each platform has different characteristics and main applications; the major difference is that with Indium Phosphide it is possible to have active elements (e.g. lasers) that are needed for the telecommunications applications.

Altice Labs and Instituto de Telecomunicações partnered in the field of PICs three years ago in the scope of NG-PON2. A complex PIC, able to transmit and receive NG-PON2 signals, with more than 40 components inside was designed produced and tested [22] (see Figure 3-19). For non-standardized networks that used advanced modulation formats and coherent detection an integrated circuit was also designed [23]. The latter case was designed to operate in 100 Gigabit/s networks.


Figure 3-19: PIC for NG-PON2. Chip received from the foundry.

Figure 3-20: PIC for NG-PON2. Detail of packaging with wire bonding for the electronic circuit

Despite the achievements that were obtained so far in the design and testing of PICs, there are still major difficulties in the process, which are mainly due to the novelty of the technology. One of the problems that the researchers currently face when designing for an MPW is the lack of information about the building blocks that the foundry provide. Despite the fact that there are design manuals with information about the process and building blocks, the information is insufficient to perform the most accurate simulations before the design and production, which can lead to errors that are found only in a later stage. To solve this, optical simulations software is starting to integrate the models from the foundries, and the foundries are encouraging the users to develop their own blocks of simulations [24].

With the first steps already given towards maturing the process of the design and production of PICs, CHARISMA is also working towards keeping up with the evolutions that occur in the field and properly contribute to this topic. In 2016 the first commercial solutions of NG-PON2 are planned to be deployed, and they are based on discrete components. Their scalability depends on the appearance of integrated solutions and thus it is important that PIC research focus on this trend. As the demand for PIC production is increasing, foundries are also providing more options for MPW runs which will ease the whole process.

Optical communications and PIC are fields of science that are under constant fast development. New standards are created every year and the PIC technologies are still in maturation. In order to follow the trends, focus and investment must be appropriately complementary in this field. This is the only way to guarantee growing and novelty in the fast changing world of innovation.

The first NG-PON2 photonic integrated circuit prototype totally compliant with ITU-T G.989 is expected in 4Q of 2016 and its mass production is expected in 2017.


3.4. OF M-PON

As already stated OFDM-PONs have been proposed as the technology of choice for NG-PON2, but among the different proposals TWDM-PON has been chosen and has been standardized in the G.989 series by IEEE [2]. Nevertheless an OFDM-PON continues to be an interesting solution for the next generation of PON systems, i.e. NG-PON3, because it provides high spectral efficiency and high flexibility in assigning the bandwidth resources.

3.4.1. OFDM modulation

An analogue representation of an OFDM modulator is shown in Figure 3-21. A serial binary sequence b is converted into N parallel sequences, representing the N subcarriers of the OFDM signal. The modulation format for each subcarrier (e.g. BPSK, QPSK, QAM-16, etc.) is independent of each other and can be chosen according to the channel properties in order to maximize the overall bitrate. The complex data symbols ck are then up-converted to a (complex) subcarrier at frequency fk. Finally all subcarriers are summed up in order to generate the OFDM signal. The OFDM symbol s can be expressed by the following formula

Equation 3-1

Here we have that N is the principal Nth root of unity exp(j 2 π/N), and ck are the data symbols.

Figure 3-21: OFDM signal generation (principle)

The OFDM scheme is just illustrative and is not being used for a practical implementation, because many subcarriers would also require a large number (N) of oscillators and filters. In practice this operation is performed by means of a discrete Fourier transform (DFT) or more specifically by the fast Fourier transform (FFT). In this case the equation to calculate an OFDM symbol then can be given as the inverse DFT:

Equation 3-2

That means the signal in the time domain is the inverse discrete Fourier transform (IDFT) of the data symbols of all subcarriers.

3.4.2. OFDM transmitter and receiver

While the FFT/IFFT is the core operation for an OFDM transmitter or receiver respectively, other digital signal processing (DSP) functions are required for a fully-functional OFDM system. An overview of a generic OFDM transmitter and receiver are shown in Figure 3-22 and Figure 3-23.

S/P

b1

b2

b3

bN-1

bN

exp(j2π·f1)

exp(j2π·f2)

exp(j2π·f3)

exp(2π·fN-1)

exp(j2π·fN)

c1

c2

c3

cN-1

cN

Σ

binarysequence

OFDMsignal

4

4

2

2

2


Figure 3-22: Generic OFDM transmitter Figure 3-23: Generic OFDM receiver

Additional information is added to the data stream at the OFDM transmitter, in order to improve the overall signal quality or to allow certain estimation techniques at the receiver. A few of these techniques are outlined below; a complete discussion about OFDM can be found e.g. in [25]. Training symbols (TS) or more general training information is inserted into the data stream in order to estimate the transmission channel later at the receiver. In order to avoid inter-symbol interference (ISI) a cyclic prefix (CP) is added, where the last few samples of an OFDM symbol are copied and put in front of each symbol. Power loading can be applied to amplify or attenuate certain subcarriers, in order to enhance the overall performance.

The first DSP function of an OFDM receiver is to synchronize the data stream by means of a correlation algorithm. Then, the CP must be removed before the FFT is applied. Afterwards the various effects of the transmission channel are corrected, and the original data is then recovered.

3.4.3. OFDM-PON architecture

While subsection 3.4.2 describes a generic OFDM transmission link, an OFDM-PON (downlink) requires additional components. The setup of an OFDM-PON OLT (a) and ONU (b) are shown in Figure 3-24.

a) OLT setup

b) ONU setup

Figure 3-24: Setup of OLT and ONU

The OLT transmitter contains an OFDM-Tx for the downstream, which generates the complex OFDM signal. A common method to generate a real-valued signal for transmission is an I/Q modulator, which upconverts the in-phase and quadrature component onto an RF carrier. This can be realized either in the digital domain – direct digital synthesis (DDS), or by discrete RF components. The frequency band is shown with the blue colour.

The entire upconverted spectrum is then conveyed to all ONUs by the ODN. An interesting approach for a simplified ONU has been described in reference [26], which will be implemented in CHARISMA. Using this approach only the shaded part of the spectrum is actually sampled by the analogue-to-digital converter (ADC) at the receiver. This reduces the costs, energy consumption, and the DSP requirements significantly.

For the upstream of an OFDM-PON different options are being discussed. An OFDM transmission in upstream is the most challenging one, because of the strict synchronisation requirements for a joint detection at the OLT. An easier approach for the upstream could be the usage of TDMA as in NG-PON2 with a upstream rate of 10 Gb/s.

Datasource

MapperM-QAM

TSinsert

Powerloading

IFFTCP

insert

In-phase

Bitloading

quadr-ature

real

imaginary

FrameSYNC

CPremoval

FFTChannel

est. +corr.

I/Qest. + corr.

Fine corr.

EVMBER

In-phase

quadr-ature

real

imaginary

Delay

I/Q Mod

(DDS)

clock

DAC-AIfc

LO (tx)

OFDMTx

32GSa/s

DAC-BIfc

DAC-A(6bit)

DAC-B(6bit)

16GHz8GHz

Dig.LO

Pol-MUX Tx

LO (tx)

16GHz8GHz

PINTIA

I/QDemod

LP

LP

Tun.LORx

ADC

ADC

LO (tx)

LO (rx)

OFDMRx

e.g. 200MHz e.g. 1GSa/s


The layered OFDM-PON architecture has already been briefly described in the CHARISMA deliverable D1.1 [3]. Its main parts are the OFDM-MAC and OFDM-PHY layers as shown below in Figure 3-25. The physical layer medium is planned to be a standard single mode fibre (SSMF). Both major blocks will be described in the following subchapters.

Figure 3-25: OFDM-PON Layered architecture

3.4.4. OFDM-MAC

The main function of the OFDM-MAC layer is to process incoming Ethernet frames and to distribute them to the respective OFDM subcarrier. An overview of the functional blocks is given in Figure 3-26. Ethernet frames reach the OFDM-MAC unit via an optical SFP+-pluggable.

Figure 3-26: OFDM-MAC (Implemented VHDL blocks for OLT transmitter)

In the first DSP blocks the processing of Ethernet frames is performed. The standard conforming Ethernet IP-cores, namely Ethernet-PCS/PMA and Ethernet-MAC handle all incoming frames. They are checked after leaving the Ethernet-MAC block. Bad frames with an invalid cyclic redundancy code (CRC) are discarded here, and in addition the frame header is modified by inserting a field containing the Ethernet frame length.

In the second stage the Ethernet frames are switched to the subcarrier, which are passed further on to the respective ONU. The scheduler distributes the frames according to their destination address. A MAC table in

OFDM MAC

SFP+PCS/PMA

MACETH

checkCarrierSwitch

Buffer FEC Buffer

IP-Cores10G Ethernet

• Remove badETH frames

• ETH length

Buffer FEC

Buffer FEC

1

2

128

„MAC subcarrier“

Carrierscheduler

Bit-Loading

Buffer

Buffer

to PHY

1

8

9

16

1017

1024

to PHY

to PHY

10GEthernet


the scheduler holds information about connected devices and respective ONU id information. To save FPGA resources 8xOFDM subcarriers are grouped together and form a “MAC subcarrier”.

In the third stage, right after distributing the frames to the MAC subcarriers a forward error correction (FEC) is applied in order to gain sensitivity for the detection process. The bitloading information gained from a PON control entity (not shown here) is applied at this stage. Finally the information is formatted to generate a continuous data stream, which is passed via an internal interface to the OFDM-PHY.

3.4.5. OFDM-PHY

The main function of the OFDM-PHY layer is the generation of the physical OFDM signal from incoming data received from the OFDM-MAC instance at the transmitter side and vice versa at the receiving end. In order to guarantee the correct operation of the OFDM-PHY additional information to estimate the channel and to perform the synchronisation is required.

A block diagram of an OFDM transmitter is depicted in Figure 3-27.

Figure 3-27: OFDM-PON-PHY (Implemented VHDL blocks for OLT transmitter)

The incoming data from the MAC is modulated using the bitloading mask, which gives the modulation format for each subcarrier. In the next step training information is inserted. This is used at the receiver in order to provide an estimate of the channel. To shape the amplitude of the signal spectrum, a power loading is applied. In the next step the core function of the OFDM transmitter is the application of the IFFT, which transforms the subcarrier symbols from the frequency into the time domain. Afterwards, the cyclic prefix is inserted, so as to help avoid OFDM symbol interference.

The block diagram of an OFDM-PHY receiver is depicted in Figure 3-28. The incoming information from the optical/electrical (O/E) conversion is down-converted by means of an I/Q-demodulator. In the next block the OFDM symbols are synchronized in order to find the start of each of the OFDM frames. Afterwards, the cyclic prefix is removed and the data is passed to the FFT block. After transforming back into the frequency domain there, the data symbols are available for each subcarrier. Now the channel effects and I/Q imbalance, if present, can be removed. Finally the corrected data can be evaluated or passed onto the next subsystem.

Figure 3-28: OFDM-PON-PHY (ONU receiver)

3.4.6. OFDM-Control

A simplified system for control of the OFDM-PON has been established on the currently used development platform (Virtex6-based). An overview of the hardware and software for the OFDM-PON management interface is given in Figure 3-29. The central controller (PC-based) provides the connectivity to the server running the orchestrator and to the OFDM-PON itself. The interface is realized using GbE/IP and the interface to the OFDM-PON is implemented using a programming device via JTAG.

On the OFDM-PON controller (PC-based) runs a Tcl2 interpreter, which allows easy access to the OFDM-PON parameters. Currently a predefined set of bitloading masks can be selected using a Tcl script. This means the

2 Tcl is a scripting language (https://www.tcl.tk/)


modulation format for each of the 1024 subcarriers is set to the predefined value of that mask. In a later stage the script is modified to set the modulation format for each subcarrier individually. An example of the respective script is shown below.

xtclsh.exe ..\..\cse\tcl\csevio_ofdmBL.tcl -usb -bl 3

Here, the USB interface is selected and the 3rd (predefined) bitloading mask is chosen, which sets the modulation format to 16-QAM on all subcarriers.

In the second stage a Virtex7-based FPGA platform together with a Power PC controller is used. (The availability of this platform is planned for M15 in the 2nd year of the CHARISMA project.) The main modification is the replacement of the PC-based controller by the on-board Power PC. The use of Linux as the OS, and Python to program the interfaces is planned; however, complete platform documentation has not yet been provided, such that modifications might therefore be required after availability.

Figure 3-29: OFDM-Control architecture

3.4.7. Hardware realisation and targeted parameters

3.4.7.1.System considerations With regards to the design of the actual hardware, two main elements have had to be considered: first, the plan to demonstrate the key aspects of a 100G-capable OFDM-PON system; second, using the resources to build such a system in the most effective manner. Therefore, we have decided that the demonstration system will provide 100 Gb/s data rate on the physical layer in the downstream direction, but 10 Gb/s at the Ethernet level.

In order to achieve a bitrate rB of 100 Gb/s at the physical layer two parameters can be adjusted – the bandwidth B and the spectral efficiency η.

𝑟𝐵 = 𝐵 ∙ 𝜂 Equation 3-3

Since the sample rate of the D/A converter is limited to 34 GSa/s currently (see [28]), the maximum signal bandwidth is 17 GHz. On the other hand, the resolution for the mentioned DAC is 6 bits. In which case, a maximum spectral efficiency of 6 bit/s/Hz is reasonable (see reference [27]).

Using these numbers a maximum bitrate of 102 Gb/s can be reached, which is in line with the target set. In order to increase the rate further, both optical polarisations can also be used. This would give an overall maximum rate on the physical layer of 204 Gb/s. An overview of the planned system parameters is given in Table 3-4.

HardwareSoftware

Controller(PC-based)

Programmer

OFDM-PON(Virtex 6 FPGA)

Tcl-Script

VIO Controller(FPGA)

USB

JTAG

virtualI/O

GbETCP/IP

ServerCHARISMA

Orchestrator


Table 3-4: Planned parameter for OFDM-PON (OLT and ONU)

Parameter Value

OLT-Tx

Sample rate 34 GSa/s

FFT length 1024

Modulation formats Off, BPSK, QPSK,8-QAM,16-QAM, 32-QAM, 64-QAM

DDS LO frequency 8.5 GHz

OFDM spectrum <=17 GHz

ONU-Rx

Sample rate 1.25/2.5 GSa/s (t.b.d)

Maximum received bandwidth 1 GHz (1/16 from Tx spectrum)

To keep the resources within the planned limits it is planned to equip the test system with 10G Ethernet interfaces. An overview of the Ethernet connectivity of the OFDM-PON link is shown in Figure 3-30.

Figure 3-30: Planned OFDM-PON hardware for trials

100GOLT

SFP+ ONUE/O O/E SFP+

SFP+SFP+

100G OFDM

10G ETH uplink


3.4.7.2.Planned Hardware on physical layer

(a)

(b)

Figure 3-31: FPGA platform for OFDM-PON: OLT(a), ONU(b)

The hardware planned for the OFDM-PON is shown in Figure 3-31. The FPGA platform for the OLT is designed by Nokia Bell Labs and provides two sockets for MICRAM DAC-II modules ([28]). In addition it contains a Virtex7-class FPGA and an on-board PowerPC as control processor. Since the board does not contain a 10G Ethernet interface, some high-speed lines to the FPGA will be used to adapt to a SFP+ cage.

The ONU hardware will be based on an established hardware design (Figure 3-32). It provides a 10G Ethernet interface, 4 DAC outputs, and 4 ADC inputs. With respect to the OFDM-PON ONU (Rx), only the input lines use 10 bit resolution ADC with a maximum sample rate of 2.5 GSa/s.

Figure 3-32: Block diagram of OFDM-PON ONU platform

The hardware holds both OFDM-PON layers: the OFDM-PHY and the OFDM-MAC layers.

FPGA #1Virtex-7 690T

FMC to

2xSFP+

2xDAC

Ch.2

10 Gb

Ethernet

FPGA #2Virtex-7 690T

2xDAC

Ch.1

2xADC

Ch.1

FMC

(HPC)

FMC

(HPC)

FMC

(HPC) 14 bit @ 2.5 GS/s

1.25 GBd

10 bit @ 2.5 GS/s

1.25 GBd

2xADC

Ch.2

FMC

(HPC)

10 bit @ 2.25 GS/s

1.25 GBd

14 bit @ 2.5 GS/s

1.25 GBd

FMC

(HPC)

FMC to

2xSFP+

FMC

(HPC)

Board to board

(SFP+)

10 bit @ 2.5 GS/s1.25 Gbd

10 bit @ 2.5 GS/s1.25 Gbd


3.4.8. OLT measurements

As already indicated, as part of the CHARISMA backhauling technology solution, HHI is currently using an OFDM-PON OLT-Tx design, which runs on a Virtex6-based FPGA platform. This platform is limited to a sample rate of 16 GSa/s, while the planned final design will run at 34 GSa/s in order to achieve the targeted 100 Gb/s data rate (see paragraph 3.4.7.1). Nevertheless the complete OFDM-PON transmitter as described in Figure 3-24 and Figure 3-27 is already running on this platform.

The OFDM-PON OLT-Tx on this platform has been tested, mainly to confirm the operation of the newly implemented functions, namely IQ-modulator (DDS), delay element, upsampling block. The test setup is shown in Figure 3-33. Here an IXIA 10G protocol analyser is connected to the OFDM-PON OLT-Tx via a pair of optical fibres.

Figure 3-33: Measurement setup OLT-PON (Tx)

The output, the upconverted OFDM signal is captured by an oscilloscope and processed by a Matlab-based offline OFDM receiver. The sampling rate of the Tx is set to the current maximum of 16 GSa/s, while the scope runs at 40 GSa/s. The local oscillator (LO) frequency and the spectral width of the OFDM signal are both set to 4 GHz. The received spectrum is shown in Figure 3-34. The blue colour indicates the unfiltered signal, while in red the filtered OFDM spectrum occupying the range from 2 to 6 GHz is shown.

Figure 3-34: Received spectrum (blue: unfiltered, red: filtered)

Further signal processing verifies the correct generation of the OFDM signal. In Figure 3-35 and Figure 3-36 are shown the signal quality of the known training information. The estimated SNR (from the error vector magnitude, EVM) after correction shows a SNR from 20 to 25 dB depending on the individual subcarrier. Since a power loading with an increased power for the outer subcarriers was applied, the SNR is higher for those in a back-to-back configuration.

IXIA10G

OFDM-PON

(OLT-Tx)Scope

Offline-DSP


Figure 3-35: Estimated SNR (for training symbols) for all subcarriers

Figure 3-36: Constellation diagrams (for training symbols)

A constellation diagram for all 1024 subcarriers of the training symbols plotted over each other is shown in Figure 3-36. The QPSK constellation, marked in red before and blue after correction demonstrates the correct operation of the transmitter. The Ethernet frames send by the IXIA protocol analyser could be recovered and were received correctly.

3.4.9. ONU measurements

The DSP algorithms are currently being tested for the planned OFDM-PON ONU. For this purpose, a setup as shown in Figure 3-37 has been implemented. It consists of an arbitrary waveform generator (AWG), which is fed by a Matlab-based offline OFDM-Tx. The ONU receiver itself down-converts a part of the received spectrum by means of an I/Q demodulator, and passes both the in-phase and quadrature parts to their respective channels of an oscilloscope. It should be noted that the sample rate of the scope is just 1 GSa/s. The captured signals are then processed by an off-line receiver.


Figure 3-37: ONU test setup

The transmitted OFDM spectrum ranging from 9 to 11 GHz is shown in the top inset. In the results shown in Figure 3-38 the LO was set in a way it could receive the central quarter of the transmitted OFDM spectrum.

Figure 3-38: OFDM-PON ONU: partial reception of OFDM spectrum

It can be seen that the carriers at the edge of the received spectrum (114,115 and 16,17) see a strong degradation, which can be explained by the low pass (LP) characteristic of the I/Q demodulator. On the other hand the central 28 subcarriers can be detected by the ONU. In this configuration the LO of the receiver was detuned by 10 ppm with respect to the transmitter oscillator. The DSP algorithm could recover the transmitted 16-QAM constellations and a mean EVM of -17 dB was achieved for those. This is also in line with error-free reception of a 16-QAM signal. More investigations are required to complete the ONU design.

AWG

24GSa/s

OfflineOFDM-

TxIQ

LO

Scope

1 GSa/s

10MHz Frequencydetuninge.g. 10ppm

OfflineOFDM-

Rx

9 GHz 11 GHz

10 GHz

Central carriers

Edge carriers

SC usedby this ONU

mean EVM: -17dB

SC forother ONUs

SC forother ONUs


3.5. Wireless links

3.5.1. Wireless standards and recent advances

Converged 5G networking is emerging as an important research area in next-generation access architectures. Critical aspects of 5G research are high data rates available to wireless end-users (e.g. 1 Gb/s to mobile devices and 10 Gb/s to fixed premises, residential or SME locations), service level latency (with a target of 1 ms delay), and lower energy consumption. Towards these targets, the introduction of mm-wave technologies into 5G access network architectures is attracting considerable interest, since they act as an enabler for many of the technical solutions to these 5G-PPP KPI requirements. The mm-wave bands around 60 GHz have become the major option for shorter-range high-speed communication systems, with these bands offering multi-Gb/s throughput as required by multimedia consumer-oriented applications, such as uncompressed video streaming and device-to-device (D2D) and device-to-infrastructure (D2I) functionalities.

The IEEE 802.11ad standard was formed in January 2009 to address the newly developing 60 GHz market, with initial applications of 60 GHz technology envisaged to include HDMI cable replacement by transmitting uncompressed HDMI. The WiGig specification, which aims to achieve multi-gigabit wireless communication in the 60 GHz band, has since been used to contribute into the new 802.11ad amendment. This builds on the existing 802.11 standard where interoperability with the 2.4-GHz and 5-GHz bands are based on the existing 802.11b/a/g/n and the 802.11ac standards. Wilocity and Qualcomm have already demonstrated IEEE 802.11ad based chipsets, and it is anticipated that by 2017, IEEE 802.11ad will be an integral part of many consumer electronic devices such as personal computers, tablets and mobile phones. 802.11ad access points operate at the 60 GHz, which is an unlicensed band available worldwide. The basic technology features of the 802.11ac and 802.11ad standards are laid out in Table 3-5.

Table 3-5: Basic technology parameters for 802.11ac and 802.11ad

802.11ac operates strictly in the 5-GHz band, but supports backwards compatibility with other 802.11 technologies operating in the same band. As an evolution to 802.11n, 802.11ac adds 80 MHz, 160 MHz and non-contiguous 160 MHz (80 + 80 MHz) channel bandwidths. Another major throughput enhancement feature is multi-user capability in the form of downlink multi-user MIMO (DL MU-MIMO). Furthermore, 802.11ac increases the modulation constellation size from 64 QAM to 256 QAM.

Most wireless networks have multiple active clients that share the available bandwidth. The overall throughput can only be increased by increasing the link rate for all clients. Many clients cannot transmit at


the highest 802.11ac rates though, because they only have one or two antennas. For such clients, MU-MIMO is the solution to get significant network throughput gains. A MU-MIMO capable transmitter can transmit multiple packets simultaneously to multiple clients as shown in Figure 3-39 below.

Figure 3-39: Example of downlink MU-MIMO

The advantage of MU-MIMO is that client devices with limited capability (few or one antenna) do not degrade the network capacity by occupying too much time on air due to their lower data rates. With downlink (DL) MU-MIMO, network capacity is based on the aggregate of the clients of the simultaneous transmission.

At 60 GHz (802.11ad), radio signals suffer from higher propagation and atmospheric losses (as compared to 5 GHz) as shown in Figure 3-40. Transmission in the 60 GHz range is subject to greater free-space loss than in the 2.4-GHz or 5-GHz range, with channel conditions able to change dramatically during a connection. This can be managed in real time by the use of beamforming. 60 GHz chipsets can exploit the shorter carrier wavelength by incorporating antennas or antenna arrays directly on-chip or in-package. Because the antenna size in the 60 GHz band is very compact, small and competitive antenna arrays can be used, with the 802.11ad standard supporting real-time beamforming.

Figure 3-40: Specific attenuation for atmospheric oxygen and water vapour

Because of the amount of bandwidth available in the 60-GHz band, four 2.16-GHz wide channels can be used. Transmitting in the 60-GHz band enables WiGig and 802.11ad to offer significantly higher data rates than previous standards. Unlike 802.11ac, WiGig and 802.11ad use beamforming to enable communications over longer distances, even though signal attenuation is high in the 60 GHz band, such that link budgeting is a challenging issue. However, in this case high-gain antennas are deployed to improve the signal strength at the receiver. Such high gain antennas, mostly phased-array antennas, utilize beamforming to create beams in a particular direction allowing the transmitted power to be focused.

Figure 3-41 shows the spectrum allocations across the world for unlicensed operation at 60 GHz. In this band, typically 7 GHz of spectrum is available for unlicensed usage, as compared to only 83.5 MHz in the 2.4-GHz


band. 802.11ad also defines both single carrier (SC) modulation and orthogonal frequency division multiplexing (OFDM) modulation.

Figure 3-41: Worldwide frequency allocation at 60 GHz band.

According to the ITU Radio Regulations, the 60-GHz band extending from 57-66 GHz is available for fixed and mobile services amongst others. The channelization of the 57-66 GHz band emerged by consensus from the technical specification developed by the IEEE, ECMA, the WirelessHD Consortium and the Wireless Gigabit Alliance. This channelization and a corresponding spectrum mask for the occupying signal was approved in November 2011 by ITU-R WP 5A for global standardization. The band is split into 4 channels, each with a bandwidth of 2.16 GHz as seen below in Table 3-6.

Table 3-6: 60 GHz Band Channel Plan

Frequency (GHz)

Channel Min Max Centre

1 57.24 59.40 58.32

2 59.40 61.56 60.48

3 61.56 63.72 62.64

4 63.72 65.88 64.80

802.11ad PHY data rates range from 385 Mb/s to 6.7 Gb/s, achieved through combinations of modulation scheme and code rate. Four channels are defined for the 60 GHz band, but they are not universally available. Channel 2 is available in all regions and is therefore used as the default channel. 802.11ad transceivers are currently more costly than 802.11ac transceivers.

Summary

802.11ac is suitable for longer-range high-throughput applications, such as in-home wireless LAN and compressed multimedia wireless display; whereas 802.11ad appears more appropriate for higher throughput applications. The regulatory transmitter power and power consumption requirements limit applicability of the two standards to different use cases. Since the obstruction loss at 5 GHz is lower than at 60 GHz, multi-gigabit 802.11ac is more appropriate for both line-of-sight (LoS) and non-line-of-sight (NLoS) wireless applications where portability is not a bottleneck. 802.11ac chipsets are already being deployed in mobile phones, PCs, laptops, and mobile devices, where smart phones use the technology for high-speed networking, HD video, and videoconferencing. 802.11ad is therefore appropriate for LoS, room-scale, low-cost, short-range, and very high throughput applications, such as in-room uncompressed and lightly compressed multimedia wireless displays, sync data/file transfer, etc. Low cost 60 GHz high gain antennas featuring small sizes can also be realized for point-to-point applications, such as small-cell backhaul networking, as indicated already in the CHARISMA use cases ([3]).


3.5.2. Recent work on 60 GHz

UEssex has several examples of 60 GHz technology as part of the Dell Latitude laptop offering. Data rates of ~3 Gb/s are possible over distances of about 40 m. All standard interfaces are provided, so uncompressed 4k UHDTV signals have been able to be transmitted using the technology over these distances.

Figure 3-42: Active antenna and wireless card

Figure 3-42 shows the 210 active antenna array module and the 60-GHz half mini-card used in the docking station implementation. The functionality of the antenna and radio card is documented in a series of patents;

granted and pending [29]. As can be seen, a technically advanced 210 beam steering antenna is present, featuring sophisticated functionality.

60 GHz omnidirectional and line of sight (LoS) antenna characteristics

The technical performance of the 60-GHz Dell Latitude laptop and its associated docking station has been assessed in a number of laboratory tests. In the first experiment the compatible Dell Latitude laptop was placed at a constant distance of 2 m away from the Dell wireless dock 802.11ad access point (AP) placed at the centre with an angular (azimuthal) variation of 0 to 360 degrees, as shown in Figure 3-43.


Figure 3-43: Omnidirectional antenna basic characterisations, left: 90° azimuth directivity for docking station; right: 330° azimuth directivity for laptop.

The connection was maintained when the laptop was moved around the dock, although the linkspeed (<2.4Gb/s) and the maximum wired 1GbE throughput (<980 Mbps) was not constant due to the characteristics of the omnidirectional antennas in both the dock and in the laptop. As might be expected, the docking station, which would normally be in a fixed position, has been optimised to have a 90 degree acceptance angle for connectivity. In contrast, the laptop (being a mobile device) has been designed to exhibit a more flexible acceptance angle with directivity found to be almost omnidirectional at 330 degrees.

The next experiment focused on increasing the range of the wireless link. Figure 3-44 shows the Dell docking station to Latitude laptop wireless setup at 60GHz frequency for a delivery of 4K uncompressed video stream from the 4K camera to the UHDTV display.

Figure 3-44: Live streaming of 4K UHDTV signals over 802.11ad

It was found that the wireless link can be maintained for much longer than the 10 metres distance as prescribed by the 802.11ad standard. Indeed, the operation of the wireless link was extended to about 40 m in an outdoor environment, where a line of sight connection was achieved. The results presented here show


that for full signal strength and maximum throughput (~2.3 Gb/s) the docking station must be in the line of sight with the Latitude. It was also found as might be expected that polarization plays a critical role during multi-channel transmission at 60 GHz wave band, which can therefore be also considered in the context of possible aggregation of 802.11ad links.

3.5.3. Future 60-GHz integration

We have already successfully demonstrated device-to-device (D2D) connectivity up to 40 m distance, with a maximum throughput of 2.4 Gb/s (full-duplex). Ad-hoc mesh networking between multiple devices, and mobile distributed caching (MDC) has also been achieved up to Gigabit speeds.

With regard to device-to-infrastructure (D2I), we have recently focused on integrating the 60-GHz (802.11ad) system into the overall CHARISMA network architecture. To that end, Figure 3-45 below shows a front-hauling scenario for the CHARISMA architecture, with a 60-GHz wireless link between the CAL0 and CAL1 intelligent active nodes, with wireless D2I functionality at 5-GHz also enabled.

Figure 3-45: 60 GHz D2I integration in the proposed CHARISMA architecture

To verify the above CHARISMA architecture, a test bed has been constructed where the 60-GHz module (laptop with RF modem) receives data from a device (mobile phone or tablet) and retransmits it wirelessly upstream over 60 GHz to the Base Station (docking station). Measurements (reported in the accompanying CHARISMA deliverable D4.1 “Demonstrators design and prototyping”) additionally conform the overall (low) end-to-end latency from the UE to the Cloud Server, and also observe the latencies between any two points along the link.

3.5.4. Point-to-multipoint 60 GHz

Background As the number of Wi-Fi devices steadily rises, consumers are requiring faster, most reliable Wi-Fi connections to access the high necessary bandwidths across the network. So far, 802.11ad vendors have only offered point-to-point solutions as described previously. The recently announced TP Link Talon AD7200 router (powered by 802.11ac and 802.11ad chipsets from Qualcomm) runs multiple bands aggregated at 7.2 Gb/s to provide complete coverage for all devices. This 802.11ad solution provides speeds of up to 800 Mb/s on the 2.4-GHz band, 1733 Mb/s on the 5-GHz band, and 4600 Mb/s on the 60-GHz band, thus creating an interesting wireless technology solution that supports multiple simultaneous connections without interference.


The Talon AD7200 uses eight high-gain antennas (seven external, one internal) as well as an external 60-GHz antenna array (Figure 3-46) to create strong Wi-Fi connections. Beamforming helps the router to locate Wi-Fi devices and to focus its wireless signal in their direction [30].

Figure 3-46: TP Link 802.11ad router [30]

As has been mentioned earlier, the 60-GHz band uses beamsteering technology to detect objects and direct the 60-GHz wireless signals along the clearest path to devices. If there is something between the router and a wireless device, beamsteering sends Wi-Fi around it for a stronger connection, as is shown in Figure 3-47.

Figure 3-47: 60 GHz beam-steering technology [30]

MU-MIMO allows simultaneous communication with multiple devices on its 2.4-GHz and 5-GHz bands, reducing wait times and speeding up connections. With MU-MIMO, more users can be connected at once without affecting the router’s performance. Transmit power at 60 GHz is 24 dBm EIRP. 32 patch antennas form an active antenna array for the 60-GHz band to ensure that Wi-Fi signals are concentrated towards the user equipment.

Point-to-multipoint wireless at 60 GHz So far, only point-to-point throughput and end-to-end latency measurements have been possible with maximum speeds of 950 Mb/s when connected to backhaul infrastructure. After the most recent announcement from TP Link described above, the on-going work at UEssex on 60 GHz is now focusing on investigating point-to-multipoint wireless networking. This offers the opportunity to examine true wireless speeds and latency measurements at 60 GHz.

Figure 3-48: Throughput and latency measurement experimental setup


Figure 3-48 above shows a schematic of the laboratory topology for proposed on-going 802.11ad performance and characterization testing. In this case, only wireless connectivity is established between the laptops and the 60 GHz access point (AP) as compared to previous experiments where the network consisted of a mixture of both 60 GHz wireless and Gigabit Ethernet connections. Successful outcome of the proposed experiment will also provide an enhanced understanding of the performance of mm waves at 60 GHz.

3.5.5. 60 GHz 802.11ad band experimental work

Introduction Initial work based around Gotmic transmitter and receiver die chips [32] and an in-house printed circuit board (PCB) design has produced credible baseband data transmission results of up 3 Gb/s as well as demonstrating an antenna compatibility with commercial IEEE 802.11ad based devices. These first generation PCB designs provide an excellent starting point in that they allowed for the identification of a number of issues in the interfacing of the Gotmic chips. As might be expected, at these mm wavelength frequencies the LO and RF port designs are not straightforward and the traditional use of a 50 Ω micro strip line has proved inadequate. To alleviate this both these lines have been the subject of some intensive modelling with the aim of improving system sensitivity. Further, in order to facilitate the manufacturing constraints necessary to support the previously identified performance enhancing PCB modifications an increased track thickness may be required. The model was therefore modified to accommodate a track thickness of 70 microns. Also an alternative method of manufacture that includes a pre-etching procedure is to be investigated. This allows greater control over PCB track thickness to be implemented. This approach also permits greatly increased control of the track sections, reducing the “undercutting” problem previously experienced and increases the track resistance to mechanical damage.

PCB modelling With the fundamental functionality of the PCBs established and many of the fabrication techniques involved now understood and characterised, we now seek to improve the performance of the layouts. It was decided to construct CST models of both the RF and LO PCB tracks in order to analyse in detail the electromagnetic behaviour associated with each line. As no modelling information was available for the terminating sockets these were not included in the modelling and we rely on the manufacturers specifications as being accurate. The aim is to design feed lines and wire bonds that have a combined return loss of -10dB or better across the required frequency range. It was found early on in the process of modelling both tracks that there were four distinct areas where refinement had an effect. These being the wire bond I/O area, the taper, the transmission line and the terminating socket area. Whilst the most sensitive sections were found to be the wire bond area and the area around the terminating socket, all were interactive and could not be treated in isolation, for this reason a holistic approach was taken with the bond wire integral to the overall design.

RF model modifications included the use of 25 micron bond wires a compensation network that included the provision of a 0.15 pF inductance cancelling pad, close coupled grounding pads a modified taper multi point grounded output port. Detail of the model construction can be seen in Figure 3-49. This shows the port assignments and details and shows the direction of signal propagation and bond wire shapes. These bond wires were now specified as 0.3 mm in length with a mid-point max height of 0.1 mm.


Figure 3-49: RF port wire bonds

It should be noted that the predicted S11 plots were not symmetrical and differed according to the direction of propagation. The plots that follow are for the indicated forward direction of signal propagation as indicated by the accompanying illustrations. Figure 3-50 shows the assigned direction of propagation for the 60 GHz RF signal.

Figure 3-50: Detail of RF Line Model

As can be seen in Figure 3-51 the target return loss was accomplished with values of -16.5 dB at 57 GHz rising to -10.5 dB at 64 GHz which gave rise to a predicted flat transmission loss function (S21) across the range. Complementing this, Figure 3-52 shows the associated Smith chart impedance prediction. Whilst not indicating the ideal 50 Ω impedance this shows that there is little variation across the frequency range and, importantly, no sign of wasteful resonance effects that would absorb the radiating signal prematurely.


Figure 3-51: RF port S11 Return Loss

Figure 3-52: RF port S11 Impedance Smith Chart

Reinforcing this assumption Figure 3-53 shows the E-plane radiation due to wire bonds and track structure. It can be seen that the micro-strip line does not show excessive radiation of the propagating signal and there is no sign of excessive reflection activity associated with the wire bonds with significant energy being coupled into the capacitive compensation pad. These behaviours indicate that improved RF output levels can be expected when these design features are incorporated into the next PCB designs.


Figure 3-53: S11 E-Plane Showing Radiation Confinement

LO model modifications also include the use of 25 micron bondwires. A compensation network that now included the provision of a 0.18 pF inductance cancelling pad and the use of close coupled grounding pads. The taper was once again modified and multi point grounding deployed at the SMA input port. As before, these bond wires were specified as 0.3 mm in length with a mid-point max height of 0.1 mm. Shown below in Figure 3-54 is the detail and assigned direction of propagation for the 10-GHz LO signal.

Figure 3-54: Detail of LO Line Model

Figure 3-55 indicates S11 return loss values ranging from better than -12 dB at the upper end of the frequency range down to in excess of -20 dB at the lowest point, indicating that good signal coupling can be expected from the SMA socket to the input pad of the die chip.


Figure 3-55: LO Port S11 Return Loss

The Smith chart plot, Figure 3-56 shows little impedance variation across the band and again there is no indication of resonant activity being present.

Figure 3-56: LO Port S11 Impedance Smith Chart

Predicted E-plane radiation behaviour of the micro-strip line structure and wire bond section as shown in Figure 3-57 again indicates little stray radiation beyond confines of the line. The wire bonds and associated network also indicates a good level of coupling into the chip, which leads to lower drive levels being required.


Figure 3-57: S21 E-Plane Showing Radiation Confinement

Transmission results The resulting designs have now been fabricated and incorporated into both the transmitter and receiver designs and are currently being evaluated. Preliminary results are encouraging and indicate an increase in transmitter power of the order of 10 dB. Although yet to be confirmed, indications are that a corresponding increase in system SNR can be expected along with improved receiver performance. As an initial experiment the Gotmic devices were connected in differential QPSK mode to two co-located 5 Gb/s baseband data sources using antennas at a range of 2 metres. The resulting combined 10 Gb/s was then transferred with the subsequent eye diagram shown in Figure 3-58.

Figure 3-58: 10 Gb/s DQPSK eye diagrams


4. esign of Network Elements

This chapter gives an overview of the technologies for intelligent CAL nodes developed in CHARISMA’s WP2 within the first year. It includes the SmartNIC accelerator, the TrustNode, and the MoBcache.

4.1. SmartNIC and virtual CPE

Broadband Service Providers (SP) are taking a page from the software-defined networking (SDN) and NFV world to allow the new services and to keep up with a fast changing consumer demands around interactive services, social networks, smart devices and IoT. The new devices installed to deliver the connected home are all required the web-based services to much greater degree than before, and with the current route based customer premises equipment (CPE) it is very complicated to enable these innovative new services, taking into assumption that managing these services in an operator’s network is already complicated operational task.

Today subscribers want to remove the boundaries and limitation to create a better personalized experience that leverages all that the internet and the consumer electronic industry. This includes:

Consume, control and share content and the internet connection on any device from PC to gaming console, to tablet to big screen TV.

Replicate the home experience outside the home at Wi-Fi hotspots in stadiums, coffee shops, shopping malls and airports.

Attain optimal value through customized high speed internet plans that reflect each subscriber’s unique application and content consumption needs.

Transform content consumption into an interactive experience, with sidebar content and suggestions, social media integration, and interacting ads and content.

There are two types of CPE: Enterprise (E) and Residential (R). They have different functions and sometimes approaches of network function (NF) migration, but both have to virtualize complex functions of Router, Gateway, Firewall, media distribution and intrusion detection systems (IDS) on server side to improve not only operating expense (OPEX), but providing more opportunities for Telco’s to implement value-added services (VASs) and improve user experience.

The solution is a combination of a bridge installed in the residence physical CPE (pCPE) and a remote hosted virtual CPE (vCPE) supporting thousands of CPEs, compared with the legacy residential gateway that perform on the routing functions at the residential home.

Figure 4-1: Traditional (left) vs. Cloud based (right) CPE implementations

physical CPE / HGWArchitecture LimitationsOperational Contraints

Architectur AgilityBest of breed plattforms and vendors

Independent HW & SW upgradesOperational Ease

Location of virtual CPE


The virtual CPE is the set of application or VNFs developed to address the above problem and will:

Help service providers to save expenses on operating and managing the residential CPE

Enable service providers to differentiate their service, by offering fast introduction of innovative and personalized services

Offer granular control of service to specific types of smart devices

Provide an ability to design and monetize personalized service

Reduce operational cost of new customer subscription

Use low cost devices that have a lower risk of failure such as L2 bridges

Provide cloud services, such as WAN optimization applications and policy control, can enable more efficient use of bandwidth, reducing connectivity costs

Gain an efficient network usage through a network real-time analysis

Avoid frequent field replacement by using simple device at customer premises

Help operators to ease support for new home device based on IPv6 to run over IPv4 Networks, together with support for home IoT protocols

Provide network flexibility by placement of virtual CPE, at different network positions: access node, central office or cloud based service

The figure below shows a residence with bridge device and Virtual CPE in the cloud. The Virtual CPE sends requests to the SDN controller and the SDN controller sends traffic to the appropriate services. For more details, see Section 4.3.1 of this document

In a new SDN/NFV world, VNFs migrate from the customer premises to the cloud. This migration raises few issues with NFs performance and latency. When the application responsible for a CPE will run on a server, this will cause high load and high latency processing. Our aim is offload network throughput and reduce latency by running data processing in the network adaptor. 5G network are going to address lot of issues and use cases, such as health care, safety events IoT solutions for smart cites and smart environment monitoring. Robust solution with fast failover detection and support of time critical application is the most important for society.

For the CHARISMA project, and especially to solve vCPE latency and performance problem, Ethernity has proposed a 40G Ethernet PCI Express server adapter designed to enhance flow processing of network applications. The idea has been to adopt an existing network interface card (NIC), with a variety of different functions as defined by ITU, IEEE, and IETF ([34]) and described in section 4.1.3. In addition it is foreseen to apply the ETSI NFV models and specifically to create a flexible and convenient API for network functions to handle the acceleration on NIC. This design is based on a standard Intel controller and an in-line FPGA networking accelerator engine.

Ethernity’s Flow Processing acceleration adapter (SmartNIC) offers the smooth integration into any network application device due to their use of the standard Intel controllers with all of their features as market-leading controllers, while also boosting application performance through their on-board hardware packet buffers and FPGA-leveraging acceleration.

4.1.1.HW Related Features:

In the following subchapter the hardware related features of the SmartNIC are described, whilst its VNF are listed and described in section 4.1.3. The block diagram is depicted in Figure 4-2. The two main elements are: a FPGA with Ethernity’s Flow Processor responsible for VNFs data forwarding offload, packet editing, and performance monitoring and second an Intel XL710 controller responsible for host connectivity and virtualization.


Figure 4-2: ACE-NIC: Block Diagram

The SmartNIC has a large on-board DDR3 memory for buffering received data packets. It supports up to 100 ms buffering time to enable caching of received packets on board, and eliminating packet drop when the host CPU/Server is busy ([33]). The on-board DDR3 memory supports search and filtering of millions of flows, together with extended counters. The card can be used with standard Intel drivers or the Intel DPDK and supports SRIOV functions. An oscillator has been integrated on-board to enhance the time stamping technology solution. The flow processing engine integrated on Xilinx Kintex-7 family FPGA is equipped with:

o 100 ms buffering with per VM queue;

o Millions of search entries, implementing search through external DDR3, eliminating the need for expensive TCAM;

o 16K virtual ports utilizing QoS , rate limiting and multicasting;

o IEEE/IETF/ITU Carrier grade features.

A detailed hardware block diagram is shown for information only below in the Figure 4-3.

PCIe

SFP

SFP

SFP

SFP

ENE ACE-NIC

ilinx intex

1M flows 2/ /MP S

Time stamping

100ms buffer Routing/NAPT/FW

Intel 1

Fortville

40G MAC

SRIOV

DDR

buffer DDR

search

DDR

counter

OSC


Figure 4-3: ACE-NIC: HW Block Diagram

4.1.2.Technical Specifications:

The following Table 4-1 lists the technical specification of the interfaces and the on-board logic for the SmartNIC.

Table 4-1: technical specification

SFP+ 10Gigabit Ethernet Technical Specifications Adapters

SFP+ (Small Form Factor Pluggable) supports:

SFI interfaces supports 10GBase-R PCS and 10 Gigabit PMA in order to connect with SFP+ to 10GBase-SR/LR

Copper Gigabit Ethernet Technical Specifications (PTP Port)

IEEE Standard / Network topology

Gigabit Ethernet, 1000Base-T Fast Ethernet, 100Base-TX Ethernet, 10Base-T

Operating Systems Support

Operating system support: Linux FreeBSD Windows

General Technical Specifications

Interface Standard: PCI-Express Base Specification Revision 3.0 (5GT/s)

Board Size: Standard height : 241. x 111.15mm (9.5” x 4. 76”)

PCI Express Card Type: X8 Lane

PCI Connector: X8 Lane

Controller: Intel FTX710AM1, Intel WGI210AT


On Board Memory packet buffer DDR3: 2GByte on HP ( packet data), 1.5 GB on HR. ( search, counter, and user application)

Holder: Metal Bracket

Power Consumption (PE310G4TSF4I71-SR):

32.1W 2.675A at 12V: Typical, all ports operate at 10Gb/s. 24.5W 2.040A at 12V: Typical, No link.

Power Consumption

(PE310G4TSF4I71-LR):

32.4W 2.7A at 12V: Typical, all ports operate at 10Gb/s.

27.38W 2.282A at 12V: Typical, No link

4.1.3. Virtual CPE Concept

The virtual customer premises equipment (vCPE) is the counterpart of a physical CPE (pCPE) with reduced functionality located at customer premises and connected through wire or wireless infrastructure to the central office. Two models of field deployment of vCPE are discussed as follows: i) The models of vCPE for Enterprise (vE-CPE) with specific functions, zone of responsibility of virtual IT (vIT), which makes it easier for the deployment of new services without upgrading local IT; ii) vCPE for Home network, with different types of service enable faster new technologies adoption without customer involvement in the process (for example HD TV upgrade).

Services provided by the vE-CPE may include a router providing QoS and other high-end services such as L7 stateful firewall3, intrusion detection and prevention and more ([35]). Application accelerators are also deployed either as standalone appliances or as router integrated services.

Figure 4-4 and Figure 4-5 below provide a view of a typical large enterprise, where the vE-CPE functionality may be located in various locations.

Figure 4-4: vE-CPE Location Examples

3A stateful firewall is a firewall that keeps track of the state of network connections.


Figure 4-5: Non-Virtualized CPE and vE-CPE

The main features of a vE-CPE are listed below:

AR - Enterprise Access Router / Enterprise CPE

FW - Enterprise Firewall

NG-FW - Enterprise NG-FW

WOC - Enterprise WAN optimization Controller

DPI - Deep Packet Inspection (Appliance or a function)

IPS - Intrusion Prevention System and other Security appliances

Network Performance Monitoring

Network separation

The solution can be different for a residential (home) CPE (ref [3]). Figure 4-6 below depicts a legacy network without home virtualization. In this example, each home is equipped with a residential gateway (RGW) and IP set-top box (STB). All services are received by the RGW, converted to private IP address and delivered inside the home network. The RGW is connected (via a PPPoE Tunnel or IPoE) to the BNG (sometimes called BRAS), which provides connectivity to the Internet or data centre. Video (IPTV) and phone (VoIP) services bypass the BNG in this scenario.


Figure 4-6: No Home Virtualization

An example of virtualized CPEs is given in Figure 4-7. The main features for connectivity, security, and management are listed below.

Connectivity functions:

DHCP server - Provide private IP addresses to home devices.

NAT router - Provide routing capabilities to the home. Convert the home addresses to one public IP per home (IPv4/6).

PPPoE client - Client for connectivity to the BRAS.

ALG - Application level gateway to allow Application Specific routing behaviour.

Security functions:

Firewall, Antivirus, IPS - Provide protection to the home environment.

Parental control - Allows control of consumed web content to device level. Port mapping.

VPN Server - Provide remote accesses to the user LAN.

Management functions:

Web GUI - to allow subscriber management.

TR-69 - To allow operator's control.

uPnP comparable technology with augmented security - Discovery of vRGW by home applications. Statistics & Diagnostics

Most of both eCPE and rCPE features of layers 3-7 can be moved to a vCPE (also known as VNF) in the cloud and has to be implemented by software there.


Figure 4-7: Home V-function

Implementation of VNFs at the server requires the solution of some problems. First of all, performance, which is usually solved by adding more computing power (CPU cores), which sometimes is expensive. Second latency, since some of those functions are time sensitive, and where the server NIC (Network Adapter) usually plays a passive role and forwards data to CPU-applications only. In CHARISMA the NIC located at a CAL node is smart, and does not only have to forward data to the CPU, but can also optimize, and process it. Using this approach, the load on CPU applications is thereby removed and latency in the µs range is reached.

Table 4-2 shows a comparison of CPU vs flow processor data forwarding:

Table 4-2: Performance comparison

Throughput x86 CPU

Kernel OVS DPDK OVS ENET ACE-NIC

L2/L3 1MPPS4 8MPPS 17 MPPS

Tunnel 0.5MPPS 4MPPS 17 MPPS

SLA Performance monitoring

1MPPS 8MPPS 64MPPS

The latency varies from 5 to 10 µs, and depends on application, and particularly those applications that have to be accelerated. But in the comparison of CPU processing where differences are measured to be of the order of one tenth of ms, acceleration has reduced value. Virtual CPE functions can also be divided between end users for multi-tenancy operation. In this case, one smart NIC is able to support up to 16K tenants.

In addition, one of main challenges is not only to design and build such a system, but also to make it a plug&play solution for OpenStack. This requires a smart approach for integration with tools and applications like OVS, vRouter, and etc.

4 Million packets per second


Figure 4-8: Smart NIC

The SmartNIC is depicted in Figure 4-8, and a list of the associated server requirement is shown in Table 4-3.

Table 4-3: Smart NIC server requirements

Server Type

Type: Any ATX Server with PCIe for NIC

Memory (RAM): > 500MB

Storage Disk: > 256GB

Operating Systems Support

Operating system support: Can be any Linux/UNIX/Win


4.2. rustNode

4.2.1. TrustNode Concept – an Overview

InnoRoute's TrustNode is a hardware accelerated Router platform designed for fast IPv6 processing and rapid network prototyping, addressing research applications. TrustNode is designed so that it can be located at each of the CALs in the hierarchy of the CHARISMA architecture, so as to assist in minimising end-to-end latency as data are routed via the lowest common aggregation node. In addition, the TrustNode supports the 6Tree high-speed hierarchical IPv6 routing as a means for flow acceleration, so that a routing latency of less than 3 µs can be achieved. In addition, the 6Tree routing provides deterministic (predicable) routes, such that remote manipulation is not possible and so prevents man-in-middle attacks. Hence, 6Tree also assists in providing support to the security objective of the CHARISMA architecture. The KPIs of the TrustNode technology that are of particular relevance to the CHARISMA architecture are listed below:

Low-latency, low-jitter routing

12 Gigabit Ethernet ports

2 x SyncE-Master/Slave

10 x SyncE-Slave

Hardware based routing using Xilinx Artix

Modular routing & routing acceleration

1-step Precision Time Protocol-Support according to PTP 1588v2

3 Forwarding Modes:

o 6Tree -- highspeed hierarchical IPv6 routing

o Ethernet switching

o Standard routing (using Intel Atom)

Support of OpenFlow for SDN application

Intel ATOM quad-core processor

Hosting Linux (OpenWrt5)

Optional user modification/ extension of FPGA-based data path

SNMP and OpenFlow management endpoints The TrustNode consists of two main parts, the FlowEngine implemented in an FPGA and the control processor (Intel ATOM) as shown in Figure 4-9. Packets enter and leave the TrustNode via gigabit Ethernet ports at the FPGA and are processed by the FPGA and optionally also by the CPU. The connection between FPGA and CPU subsystem is implemented as a high bandwidth PCIe interface.

5 https://openwrt.org/


Figure 4-9: TrustNode Concept

The idea is that most of the packets (80-90%) are forwarded by the FPGA only, i.e. packets enter the FPGA via the Gigabit Ethernet port and are forwarded to another Gigabit Ethernet port directly, without passing the control processor. Hence the FlowEngine acts as an offloading engine for the CPU.

The routing software runs on the Control Processor, whose main task is to process packets which have not been processed by the FPGA. Typically, control packets such as from the ARP, ICMP, STP, SNMP etc. protocols are processed by the Control Processor, while voice and video streams are forwarded by the FlowEngine only. Special exceptions are time stamp packets from SYNCE protocol, which are looped by the FlowEngine with an automatic time stamp update.

The TrustNode supports 4 different flow types, with 3 of them forwarded by the FlowEngine only, as shown in Figure 4-10. The default flow is processed by the Control Processor.

Figure 4-10: Direct Flows and Default Flow

The acceleration flow types are listed in Table 4-4. The Flow Cache is controlled by the Control Processor, while 6Tree is a hardwired mechanism and MAC Table forwarding is autonomously learning and aging6 out according to Ethernet switching standard. Obviously accelerated flows are much faster forwarded; the lowest latency of less than 3 µs is achieved by accelerated flows only.

6 When the aging time for an address in the MAC table expires, the address is removed


Table 4-4: Flow acceleration methods

Method Description Type

6Tree Hardwired algorithm, destination extracted from packet Static

Flow Cache Configured by user via control processor Dynamic

Flow Cache Learned MAC address according to IEEE 802.1 Autonomous

From the three acceleration methods only the Flow Cache can be controlled by the user. There are two basic operation modes, transparent mode and automatic mode:

In Direct Control Mode the user has full control over the Flow Cache entries. User software running on the Control Processor decides if a flow is accelerated or not. This is the default mode of the TrustNode.

In Automatic Mode a daemon7 running on the Control Processor automatically decides if a flow is to be accelerated. The decisions depend on configurable parameters such as flow rate, flow persistence, protocol type etc.

The Flow Cache is a basic mechanism needed to make an OpenFlow Switch with the TrustNode. The automatic daemon can be configured to act as an extension to the software OpenVSwitch running on the CPU.

4.2.2. TrustNode Architecture

TrustNode architecture is shown in Figure 4-11, with InnoRoute's packet processor "FlowEngine" in the upper part and the processor subsystem containing the Control Processor below. The FlowEngine is basically a data pipe which forwards packets from left to right and modifies them on the fly. All packets are stored in the Shared Buffer from where they can be sent out to any destination. Rx and Tx in Figure 4-11 denotes the receive and transmit parts of the Gigabit Ethernet PHYs.

The Control Processor is attached like an additional PHY, but with a high throughput PCIe interface. With 4 lanes running at 5 Gb/s a total throughput of 20 Gb/s is achieved, so that all received packets can be transferred without losses to the Control Processor and stored there in the DRAM. For the internal data path interfaces the AXI-S bus from ARM is used. The MUX and DeMUX blocks convert to and from the common internal data path. Ingress, Egress Processing and Scheduler blocks contain InnoRoute specific blocks with the option to include customer specific functions. The Queuing block administers a scalable number of queues.

7 A daemon is a computer program that runs as a background process.


Figure 4-11: TrustNode Architecture

4.2.3. FlowEngine Basics

The idea of the FlowEngine is to assign each packet to a flow. Further processing of the packet within the FlowEngine is done on a per-flow basis. Each packet is assigned by a Classification mechanism to a flow by attaching a Flow-ID to the packet. The Flow-ID determines the output port of a packet, QoS class, output queue and its further processing, counting, shaping, colour marking etc.

The Flow Cache of FlowEngine version 1.0 is a table of 512 entries (this number could be increased in future versions). Each entry can be one of 4 types described here:

Type 1 is a Layer 2 entry with all relevant Ethernet header fields, MAC, VLAN and Ethertype. It can be used for example to define VLAN specific forwarding.

Type 2 is a Layer 3 entry for IPv4. It can be used for example to detect TCP/IP flows. The search pattern includes the 5-tuple (IPv4 addresses, Protocol and Ports) and the DiffServ Code Point field DSCP.

Type 3 is a Layer 3 entry for IPv6. It makes use of the fact that according to RFC6437 [36] the Flow Label is a hash of packet's 5-tuple (IPv6 address prefixes, DSCP field and Ports). According to RFC7136 [37] the Interface Identifier should be treated as opaque (by the network) and therefore only the 64-bit prefixes of the IPv6 addresses are used. This entry is used for prioritization of a flow.

Type 4 is reserved for user specific function. For constructing the entry several fields are provided by the parser.

Each entry in the flow table can be mapped to several chained entries of the rule table, which includes the actions to be applied to the flow. So the FlowEngine is able to accelerate a subset of OpenFlow rules managed by the software OpenVSwitch.

1.1.1. 6Tree Concept

This routing concept is based on IPv6. The basic idea is that in a hierarchically structured network (segment) the IPv6 address prefix is evaluated gradually by the routers [38]. A similar concept is described in [39]. The 6Tree concept will speed-up the routing process dramatically, hence there is no need for a lookup-table, which is the most time intensive operation during IP-routing. Reference [40] shows the potential of this improvement when tested under scientific conditions.

Figure 4-12 shows an example of a routing network with three hierarchy levels. Each router (rectangular box) gets assigned an address by manual configuration. The top-level router gets the empty address < >, the second highest hierarchy router gets a one-digit address <1>, <2> or <3> and the third hierarchy level routers


get 2-digit addresses assigned. Each of the lowest level routers has up to three terminals (rounded boxes) attached, which get 3-digit addresses assigned.

Figure 4-12: Hierarchical routing with 3 example paths

The 6Tree mechanism built into the TrustNode has several advantages:

Implementation in hardware; works without processor interaction and with minimum latency

Deterministic, predictable routes, depending on local router configuration only; no remote manipulation possible; this prevents man-in-the-middle attacks, and so enhances security.

Thus the 6tree concept is consistent with the CHARISMA hierarchically network topology, the TrustNode-device can be easily integrated into the projects structure and controlled using the OpenFlow-protocol.


4.3. Network Caching evice

Deploying caching [41] in the network can efficiently improve service access time latency, which is another one of the main CHARISMA objectives. In addition, aligned with another CHARISMA objective (multi-tenancy) is that the CHARISMA content delivery system is designed to provide an open access [42], highly configurable, efficient and transparent in-network caching service to improve the content distribution efficiency by distributing the content in the different Converged Aggregation Levels (CALs) in the network as defined in D1.1 ([3]). One of the main difficulties is to provide continuous service with low latency in a mobile scenario where user equipment switches from different wireless/mobile networks. For example, in the automotive – bus/tram use case presented in Section 4.2.3 of D1.1, some intelligence like caching, switching and routing closer to end users has been defined to assist in reducing network latency. However, providing intelligence in a wireless/mobile scenario requires a sophisticated design for the hardware device.

The MoBcache (MB) described in this section is a mobile router-server prototype with autonomous battery, and auto-configuration within a tree radio network. It is specially designed for mobile scenarios in the CHARISMA system to keep service continuity while a user moves about and requires hand-overs between base stations within the network. The MB prototype has the following radio interfaces:

1 GB Ethernet Port

1 Wi-Fi 5 GHz interface

1 Wi-Fi 2.4 GHz interface

1 optional LTE interface (to be added during the project)

A 60 GHz interface is currently being evaluated The first MoBcache prototype design is quite compact, allowing the prototype to be placed in pilot demonstrator trials, or in the carriages of public transport systems (provided it is in some protected environment).

Figure 4-13: MoBcache prototype

Comparing to other cache solutions, MoBcache has been specially designed for mobile scenarios in the CHARISMA system to keep the service continuity while a user moves about and requires hand-overs between different CALs in the network. The MoBcache prototype has the following features:

With Wi-Fi, LTE modules, internal battery equipped and relatively small size (16 cm 8 cm 4 cm),

MoBcache can be used as wireless portable equipment;

Disconnection predictor is designed to predict the eventuality of a network disconnection of the MB and optimize the seamless handover for MB between Wi-Fi and LTE, or different MBs;

The self-organized ad-hoc network among MBs through Wi-Fi 802.11ac allows it to achieve an optimal local CDN network solution;

Pre-fetching module has been designed into the MB to allow pre-fetching the required content in the following scenarios:


o In a live-streaming video scenario like the World Cup, prefetching the live-streaming by pushing the live video content onto the caches where multiple requests are potential initiated in the network;

o In a mobile scenario, the user requested content can be pre-fetched in some MBs according to the anticipated user movements and/or socially based requirements.

The block diagram of the MoBcache prototype shown in Figure 4-14 is mobile (battery powered) and can have different RF interfaces. Two possible configurations are shown; one with 2 Wi-Fi interfaces, and one with 2 Wi-Fi and one 4G interface (which can evolve to 5G). It contains a SSD for content storage and RAM for content caching and pre-fetching.

Figure 4-14: MoBcache block diagram

In a system configuration, the MoBcache can be configured in a tree network as shown below, usually using the 5 GHz Wi-Fi as a backbone between the MoBcache devices, and 2.4 GHz Wi-Fi for user device or M2M connectivity. Connection to the Internet can be ensured through the Ethernet or 4-5G links.

Besides the classical networking functions, in-network caching and NAT/NAPT and DHCP server can also be activated in the MoBcache.

Figure 4-15: Networking of MoBcaches


Concerning ad-hoc networking capabilities, MoBcaches can configure themselves automatically in a tree configuration, with a 5 GHz Wi-Fi backbone and 2.4 GHz Wi-Fi distribution. Configuration can be done on different 5 GHz and 2.4 GHz channels respectively, according to the network planning constraints such as shown below (Figure 4-16).

Figure 4-16: physical architecture and channels arrangement

The device is controlled by two software appliances:

A manager which controls the device connectivity and can configure the wireless mesh network;

A cache controller, which interfaces with the network operator or OTT/content provider, and controls the caching and pre-fetching strategy of the MoBcache device, within an SDN framework. Caching and pre-fetching strategies can be set in a D2D manner (managed by the MoBcache themselves) or network-to-device configurations (controlled by the cache controller in that case).

Figure 4-16 presents a physical tree architecture with a logical mesh overlay and a single connection to the Internet. Hierarchical content caching can be performed upstream and downstream according to strategies which can be configured by the Cache Controller. Additionally, fetching or pre-fetching strategies can be set:

Content fetching between 2 MBs, according to appropriate criteria (e.g. social distance, etc.)

Content pre-fetching taking into account user mobility [43] and disconnection-connection to a new MB; or MB mobility. The pre-fetching strategy is set by the cache controller and monitoring by the disconnection predictor.


5. Conclusion

This CHARISMA deliverable D2.1 “Initial Architecture Design and Interfaces” has given an overview of the initial research results arising in WP2 of CHARISMA during the first year of the project. The link technologies and the intelligent nodes as discussed in this document are in line with the CHARISMA architecture already defined in WP1 and described in the earlier deliverable D1.1 [3] and the physical layer aspects of the 5G-PPP architecture [1]. The initial results reported here include the PHY layer design, link technologies, intelligent nodes, and security technologies, that have been developed in WP2 in conjunction with the other parallel work packages of the project. In addition, the CAL architecture approach of CHARISMA has been taken up in the 5G Architecture work group White Paper.

The initial results for the backhaul OFDM-PON already demonstrate that key DSP algorithms have been implemented and are working as expected. The current hardware of the OFDM-PON OLT is already processing real Ethernet traffic, with the estimated SNR for that configuration being ~20 dB, which enables transmission using 16-QAM or more per subcarrier. For NG-PON2 new technologies like photonic integrated circuits have been investigated and promise significant gains in terms of reduces footprint due to higher integration. The research on 60 GHz RF links for fronthaul and final-drop deployments has used early prototypes for consumer devices as well as newly designed transmitter and receiver components. Using 60 GHz prototypes from Dell up to 40 m reach has been shown transmitting an uncompressed UHDTV video stream at 2.4 Gb/s. First prototypes using a new RF design already show very promising results. A combined data rate of 10 Gb/s for two data sources has been reached. For the physical layer security three technologies (Stokes-encrypted secure communication, orbital angular momentum (OAM) wireless communications, and geometric optical phase encryption) have been presented.

For the intelligent CAL nodes developed in CHARISMA early prototype components (SmartNIC, TrustNode and MoBcache) of the intelligent management units (IMUs) have been built and tested. A throughput measurement using the SmartNIC, which is a FPGA-based network interface card that allows the acceleration of network functions in a virtualized network infrastructure for 5G, has shown an improvement by a factor of 17-64 depending on the application. For the TrustNode a new routing algorithm has been presented, which

promises a very low latency (of the order of 3s) as compared to established routing algorithms. In addition, the TrustNode router allows routing with low latency using the 6Tree algorithm. The MoBcache device for hierarchical network caching (i.e. directed content delivery) represents a caching technology solution for fixed and mobile applications. It can significantly reduce the service access time latency for cached content, and integration into the CAL nodes has been described in this report.

The results reported in this deliverable will feed into the pilot field and lab demonstrators being developed in WP4. The architectural design of the CHARISMA network is continuing to be refined in WP1, and these refinements will continue to be informed by the WP2 technology developments reported here and anticipated to occur in the on-going progress of WP2. In addition, the architecture technology designs and interfaces are also required in WP3 to assist in the on-going design of the CHARISMA CMO plane. As the various technologies described here continue to be developed, this deliverable will be updated by means of the following WP2 deliverables (D2.2 and D2.3) in the second and third years of the CHARISMA project.


References

[1] 5G PPP Architecture Working Group: “View on 5G Architecture”, (to be published) https://5g-ppp.eu/white-papers, 2016

[2] G.989.1, “40-Gigabit-capable passive optical networks (NG-PON2): General requirements”, 0 /201

[3] M. Parker, et al. “D1.1 Architecture Definition & Requirements based on Use-case Scenarios”, CHARISMA, 2016M. Dusek, N. Lutkenhaus, and M. Hendrych, “Quantum Cryptography”, Progress in Optics, 49, 381-454 (2006).

[4] V.S. Grigoryan, G.S. Kanter, P. Kumar, “Quantum-Noise-Randomized Data Encryption: Comparative Analysis of M-ary PSK and M-ary ASK Protocols for Long-Haul Optical Communications”, Proc. OFC 2007, Paper OWT3, Anaheim, CA (2007)

[5] V.S. Grigoryan et al., ECOC 2004, We4.P.121 (2004)

[6] C Liang et al., IEEE Photonics Technology Letters, 17(7), p.1573-1575 (2005)

[7] C. H. Bennett et al., IEEE International Conference on Computers, Systems and Signal Processing, p175-179, (1984)

[8] T. Ajmal, J.J. epley, and S.D. Walker, “Stokes Encrypted Secure Communication over Optically Amplified inks”, ECOC 2006, p.1-3, (2006)

[9] F.E. Mahmouli, S.D. Walker, “4-Gbps Uncompressed Video Transmission over a 60-GHz Orbital

Angular Momentum Wireless Channel”, IEEE Wireless Communications etters, 2(2), p22 (201 )

[10] J. P. Torres and . Torner, “Twisted Photons: Applications of ight with Orbital Angular Momentum”, Wiley-VCH, (2011)

[11] M.V. Berry, “Quantal Phase Factors Accompanying Adiabatic Changes”, Proc. R. Soc. A 392, p. 45, (1984)

[12] M.J. Padgett, J. Courtial, “Poincaré-sphere equivalent for light beams containing orbital angular momentum”, Optics Letters, 24(7), p430, (1999)

[13] E.J. Galvez et al., “Geometric phase associated with mode transformation of optical beams bearing orbital angular momentum”, Physical Review Letters, 90(20), 203901 (2003)

[14] G.F. Calvo, “Wigner representation and geometric transformations of optical orbital angular momentum spatial modes”, Optics Letters, 30(10), p1207 (2005)

[15] N.K. Fontaine, R. Ryf, S.G. Leon-Saval, J. Bland-Hawthorn, “Evaluation Of Photonic anterns For Lossless Mode-Multiplexing”, Proc. ECOC 2012, Paper Th2D6, Amsterdam, Netherlands (2012)

[16] N. Bozinovic , Y. Yue, Y. Ren, M. Tur, P. Kristensen, A.E. Willner, S. Ramachandran, “Orbital Angular Momentum (OAM) based Mode Division Multiplexing (MDM) over a Km-length Fiber”, Proc. ECOC 2012, Paper PDP Th3C6, Amsterdam, Netherlands (2012)

[17] Cláudio Rodrigues, Tiago Miguel Mendes, Francisco Manuel Ruivo, Paulo Mão-Cheia, José Salgado, NG-PON2, Revista Saber e Fazer, PT Inovação e Sistemas S.A., 2015

[18] Miller, S.E.: ‘Integrated Optics : an introduction’, Bell Syst. Tech. J., 1969,488, pp. 2059-2069

[19] Smit M K: ‘New focusing and dispersive planar component based on an optical phased array’, Electronic Letters, 1988, 24 385-6

[20] Nagarajan, R., Joyner, C. H., Schneider, R. P., et al.: ‘ arge-scale photonic integrated circuits’, IEEE J. Sel. Top. Quant. Electron. JSTQE, 2005, 11,(1), pp 50-65

https://5g-ppp.eu/white-papers

https://5g-ppp.eu/white-papers


[21] Smit, M., eijtens, X., Ambrosius H., et al: ‘An Introduction to InP-based generic integration technology’, Semiconductor Science Technology, 2014, 41 pp

[22] Tavares,A. , opes, A., Rodrigues, C. et al :’Photonic integrated transmitter and receiver for NG-PON2’, AOP , 2014

[23] Rodrigues, F., Tavares, A., opes,A. Et al : ‘Photonic integrated transceiver for Hybrid PONs’, IEEE proceedings from Networks 2014,2014

[24] Richter, A., Mingaleev,S., Koltchanov,I. : ‘Automated design of large-scale photonic integrated circuits’, SPIE Newsroom, 2015

[25] Weinstein, Stephen B., "The history of orthogonal frequency-division multiplexing", IEEE Communications Magazine, 2009.

[26] J. von Hoyningen-Huene, et al.: „Experimental IM/DD OFDMA Transmission with Scalable Receiver Frontend for PON Scenarios“, Optical Fiber Communication Conference, 2012

[27] M. Bernhard: “Analytical and numerical studies of quantization effects in coherent optical OFDM transmission with 100Gbit/s and beyond”, ITG Photonische Netze, eipzig, 2012

[28] http://micram.net/products/dac-board-systems/dac7202/

[29] http://www.faqs.org/patents/assignee/wilocity-ltd/

[30] http://www.tp-link.com/en/products/details/cat-9_AD7200.html#overview

[31] http://www.tp-link.com/res/pmpo/files/AD7200/Talon%20AD7200%20Datasheet%201.0.pdf

[32] http://www.gotmic.se/txrx.html

[33] http://www.ethernitynet.com/products/ace-nic/

[34] https://tools.ietf.org/pdf/draft-fu-dmm-vcpe-models-01.pdf

[35] http://www.etsi.org/deliver/etsi_gs/nfv/001_099/001/01.01.01_60/gs_nfv001v010101p.pdf

[36] S. Amante and B. Carpenter and S. Jiang and J. Rajahalme, RFC 64 7 “IPv6 Flow abel Specification”, 2011

[37] B. Carpenter and S. Jiang, “RFC 71 6: Significance of IPv6 Interface Identifiers”, 2014

[38] A. Foglar, S. Sonntag: “Router IP port for an IP router”, Google Patents, 2009

[39] Choi, H. G. et al., “Internet addressing architecture and hierarchical routing method thereof”, Google Patents, 2005

[40] M. Ulbricht, J. Wagner: “ Accelerated Processing Delay Optimization in Hierarchical Networks Using Lowcost Hardware”, 2016 10th International Symposium on Communication Systems, Networks and Digital Signal Processing (CSNDSP) (CSNDSP16)

[41] Zhe Li, Jean-Charles Point, Selami Ciftci, Onur Eker, Giulia Mauri, Marco Savi, Giacomo Verticale, “CN based shared caching in future converged fixed and mobile network”, HPSR: International Conference on High Performance Switching and Routing, 1-4 July, 2015.

[42] Zhe Li, Yaning Liu, Jean-Charles Point, Selami Ciftci, Onur Eker, Marco Savi, Massimo, Tornatore, Giacomo Verticale, “Shared cache as a service in future converged fixed and mobile network”, EuCNC: European Conference on Networks and Communications, Paris, France, 29 June – 2 July, 2015. (Poster)

[43] Joost Geurts, Zhe Li, Yaning Liu, Jean-Charles Point, “Transparent handover using Wi-Fi network prediction for mobile video streaming”, rd World Conference on Information Systems and Technologies, Portugal, 1-3 April 2015.

http://www.gotmic.se/txrx.html

http://www.ethernitynet.com/products/ace-nic/

https://tools.ietf.org/pdf/draft-fu-dmm-vcpe-models-01.pdf

http://www.etsi.org/deliver/etsi_gs/nfv/001_099/001/01.01.01_60/gs_nfv001v010101p.pdf


Acronyms

5G 5th generation mobile network

ACE Accelerated

ADC Analog-to-Digital-Converter

ALG Application Level Gateway

AP Access Point

APD Avalanche Photodiode

API Application Programming Interface

AR Access Router

ARN Active Remote Node

ARP Address Resolution Protocol

ASE Amplified Spontaneous Emission

ATX Advanced Technology eXtended

AWG Arbitrary Waveform Generator/ Arrayed Waveguide Grating

BER Bit Error Rate

BPSK Binary Phase Shift Keying

BNG Broadband Network Gateway

BOSA Bi-directional Optical Sub-assembly

BRAS Broadband Remote Access Server

BS Base Station

CAL Converged Aggregation Layer

CCD Charge-Coupled Device

CDN Content Delivery Network

CE Coexistence Element

CGH Computer-Generated Hologram

CO Central Office

CP Cyclic Prefix

CPE Customer Premise Equipment

CPU Central Processing Unit

CRC Cyclic Redundancy Check

CST Computer Simulation Technology (AG)

D2D Device to Device

D2I Device to Infrastructure

DAC Digital-to-Analog-Converter

DC Data Centre

DDM Digital Diagnostic Monitoring

DDoS Distributed DoS

DDR Double Data Rate


DDS Direct Digital Synthesis

DFB Distributed Feedback Lasers

DFT Discrete Fourier Transform

DHCP Dynamic Host Configuration Protocol

DL Downlink

DOP Degree of Polarisation

DPDK Data Plane Development Kit

DPI Deep Packet Inspection

DoS Denial of Service

DoW Description of Work

DP Distribution Point

DQPSK Differential Quadrature Phase Shift Keying

DRAM Dynamic RAM

DSCP Differentiated services code point

DSP Digital Signal Processing

EC European Commission

ECMA European Computer Manufacturers Association

EDFA Erbium Doped Fibre Amplifier

EIRP Equivalent isotropically radiated power

EML Externally Modulated Laser

ETH Ethernet

EVM Error-Vector-Magnitude

FEC Forward Error Correction

FFT Fast Fourier Transform

FMC FPGA Mezzanine Card

FPGA Field-Programmable Gate Array

FSAN Full Service Access Network

FSO Free Space Optics

FW Firewall

GbE Gigabit Ethernet

GPON Gigabit Passive Optical Network

GUI Graphical User Interface

HD High-Definition

HDMI High-Definition Multimedia Interface

HDTV High Definition TV

HG Hermite-Gaussian

HGI Home Gateway Initiative

HGW Home Gateway

HP Holographic Plate

HW Hardware


I/Q In-phase/Quadrature

ICMP Internet Control and Management Protocol

ID Identification Data

IDFT Inverse Discrete Fourier Transform

IEEE Institute of Electrical and Electronics Engineers

IETF The Internet Engineering Task Force

Ifc Interface

IFFT Inverse Fast Fourier Transform

IMU Intelligent Management Unit

IoT Internet of things

IP Internet Protocol

IPTV IP Television

IPoE IP over Ethernet

IPS Intrusion Protection System

ISI Inter-Symbol-Interference

ITU International Telecommunication Union

JTAG Joint Test Action Group

KPI Key Performance Indicators

LG Laguerre-Gaussian

LO Local Oscillator

LOS Line of Sight

LP Low-Pass

LTE Long Term Evolution

MAC Media Access Control

MB MoBcache

MBH Mobile Backhaul

MDC Mobile Distributed Caching

MIMO Multiple-Input Multiple-Output

MPLS Multiprotocol Label Switching

MPPS Million Packets per second

MPW Multi Project Wafer

MU Multi-User

MUX Multiplexer

MVNO Mobile Virtual Network Operator

NAPT Network Address Port Translation

NAT Network Address Translation

NFV Network Function Virtualisation

NG-PON2 Next Generation Passive Optical Network 2

NIC Network Interface Card

NLOS None Line of Sight


O/E Optical-to-Electrical

OAM Orbital Angular Momentum

ODN Optical distribution Network

OFDM Orthogonal Frequency Division Multiplexing

OLT Optical Line Terminal

OMCI Optical Network Unit Management and Control Interface

ONT Optical Network Termination

ONU Optical Network Unit

OPEX Operating Expense

OS Operating System

OSNR Optical Signal to Noise Ratio

OTT Over-The-Top content

OVS Open vSwitch

PC Personal Computer

PCB Printed Circuit Board

PCI Peripheral Component Interconnect

PCIe Peripheral Component Interconnect Express

pCPE Physical CPE

PCS Physical Coding Sublayer

PHY Physical Layer

PIC Photonic Integrated Circuits

PIN Positive-intrinsic-Negative

PMA Physical Medium Attachment

PNF Physical Network Functions

PolSK Polarisation Shift Keying

PON Passive Optical Network

PPP Public Private Partnership/

PPPoE PPP over Ethernet

PtP Point-to-Point

PTP Precision Time Protocol

QAM Quadrature Amplitude Modulation

QPSK Quadrature Phase Shift Keying

QKD Quantum Key Distribution

QoS Quality of Service

RAM Random Access Memory

RF Radio Frequency

RFC Request For Comment

RGW Residential Gateway

RN Remote Node

RSSI Received Signal Strength Indication


SC Small Cell

SDN Software Defined Networks

SFI SerDes Framer Interface

SFP+ Small Form Factor Pluggable

SLA Service level Agreement

SMA Sub-Miniature version A (connector)

SMF Single Mode Fibre

SNMP Simple Network Management Protocol

SNR Signal to Noise Ratio

SOA Semiconductor Optical Amplifier

SP Service Provider

SPP Spiral Phase Plate

SRIOV single root input/output virtualization

SSD Solid State Disk

SSMF Standard Single Mode Fibre

STB Set Top Box

STP Spanning Tree Protocol

syncE Synchronous Ethernet

TCAM Ternary Content Addressable Memory

Tcl Tool command language

TCP Transmission Control Protocol

TDMA Time Division Multiple Access

TIA Trans-Impedance-Amplifier

TS Training Symbol(s)

TWDM Time and Wavelength Division Multiplex

Tx Transmitter

UHDTV Ultra HDTV

UNI User Network Interfaces

UPnP Universal Plug-and-Play

USB Universal Serial Bus

VAS Value-added Service

vCPE Virtual CPE

vE-CPE Virtual Enterprise CPE

vIT Virtual IT

VLAN Virtual LAN

VM Virtual Machine

VNF Virtual Network Function

VPN Virtual Private Network

VoIP Voice over IP

WDM Wavelength Division Multiplexing


WOC WAN Optimization Controller

WP Work Package

XFP 10 Gigabit Small Form Factor Pluggable

XG-PON 10 Gb/s PON

<END OF DOCUMENT>

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