csp-net breakout session...em-propagation-software/ benefits of ray tracing • can capture diffuse...

CSP-NET Breakout Session

NSF-RCN mmWave WorkshopJuly 2017

Goals

• Identify the most critical aspects of mmW PHY-abstraction

• WISHLIST: simulation/emulation capabilities for mmW networking research

• Opportunity for a white paper?

Agenda

• Introductions (25’)

• Open discussion (60’)

• Wrap-up (5’)

Introductions

• Haitham Hassanieh (U Illinois)

• Ismail Guvenc (U North Carolina)

• Tom Henderson (U Washington)

• Marco Mezzavilla (NYU)

• Jing Zhu (Intel)

• Matthew Andrews (Nokia)

• Rui Yang (Interdigital)

• Yuichi Kakishima (NTT DOCOMO)

Pasternack 60 GHz Evaluation Kit:

Cost ≈ 14,000 USD+Full PHY Control+Can Synchronize −Only Radio Front End!−Horn Antenna −Unidirectional

Haitham Hassanieh (UIUC)

TP-Link Talon AD7200Cost ≈ 380 USD

Dell Latitude Series

Acer Travelmate Series

Intel 18260 WiGig Cards

Qualcomm QCA WiGig Cards

Cost ≈ 1000 USD Cost = ?+Phased Array (4 ant.) 64 antennas+802.11ad stack 802.11ad+Bidirectional+Beam Selection−Rang ≈ 2m ≈ 100m

Tensorcom 60 GHz: Products

Cost ≈ 142K–314K USD +PHY Control, 2GHz+MIMO+Uni/Bidirectional−Cost−Horn Antennas

NI Transceiver (28,70 GHz):

PicoCell PlatformEvaluation Kit

Cost ≈ 10s of USD

−Designed mainly for laptop docking stations

Cost > 700 USD

Analog Devices 60 GHzEvaluation Kit

Cost ≈ 3700 USD x2

+/−Same as Pasternack

Millimeter Wave Platforms

Build 24 GHz mmWave Front-End from components: Cost ≈ 10,000 USD

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dB

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256 QAM

16 QAM

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256 QAM

16 QAM

Millimeter Wave PlatformsHaitham Hassanieh (UIUC)

+Full PHY Control+Can Synchronize +Phased Array (8 element)+Range−Unidirectional−RF Front End Only

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Phased Array Calibration

Range (>90m)

Challenge: All components available and can be found at other frequencies

except: Phase Shifters

Phase Shifters we used:+Analog Phase Shifters+3𝑜Accuracy−Discontinued!−Need Calibration−High Loss 6dB

Ray Tracing (RT) Simulations for mmWave PropagationIsmail Guvenc, North Carolina State University

Altair WinProp RT Software Remcom Wireless Insite RT Software

• Urban/indoor multipath simulations• Prediction of maximum 5G data rate• mmWave propagation simulation up to 75 GHz • Considers oxygen absorption at 60 GHz• Built-in graphical editors for buildings, tunnels

stadiums, antenna pattern, etc.• Website:

http://www.altairhyperworks.com/product/FEKO/WinProp-Propagation-Modeling

• Urban/indoor multipath simulations• Massive MIMO support• mmWave propagation simulation up to 100 GHz • Considers oxygen absorption at 60 GHz, diffuse

scatterring• Built-in graphical editors • Website: https://www.remcom.com/wireless-insite-

em-propagation-software/

Benefits of Ray Tracing• Can capture diffuse scattering and spatial consistency

(important for mobility studies)• Convenient and quick way to generate data for specific

environments when compared to experiments

Drawbacks of Ray Tracing• May not fully characterize subtle details of real world

environments• Precise modeling of an environment requires modeling

of scatterer locations/material (time consuming)

Use of Ray Tracing Tools in the Recent Literature• # of papers in Google Scholar with the query (Winprop

mmWave): ~25• # of papers in Google Scholar with the query (Remcom

mmWave): ~88• Example: ICC 2016 paper by Qualcomm [1]

• Winprop is used for studying RMS delay spread with omni and beamformed links, results compared with real world experimental data

• RMS-DS measurements with WinProp: ~60-100ns (omni) and ~20ns (beamformed)

• Beamformed measurements: 50ns (NYU), 30ns (Samsung) – higher in practice

• Diffuse scattering critical at higher frequency

[1] Zhang, Zhenliang, Jung Ryu, Sundar Subramanian, and Ashwin Sampath, “Coverage and channel characteristics of millimeter wave band using ray tracing,” in Proc. IEEE Int. Conf. Commun. (ICC), pp. 1380-1385, 2015.

http://www.altairhyperworks.com/product/FEKO/WinProp-Propagation-Modeling

https://www.remcom.com/wireless-insite-em-propagation-software/

Case Study: Ray Tracing for UAV mmWave Propagation ChannelsUsing RemCom Wireless Insite [2]

RSS at 28 GHz

RMS-DS at 28 GHz

[2] W. Khwaja, O. Ozdemir, and I. Guvenc, “UAV Air-to-Ground Channel Characterization for mmWaveSystems”, to appear in IEEE VTC Workshops, Sep. 2017.

Sub-urban scenario

Urban scenario

Over sea Rural

Suburban Urban

Over sea Rural

Suburban Urban

Received Signal Strength (RSS):• Over sea: Closely follows a two ray model• Rural/suburban: Fluctuation from scatterers• Urban areas: Fluctuations become higher• Fluctuation rate of the two ray propagation

model increases with UAV height• Fluctuation rate higher for 60 GHz (not shown)

versus 28 GHz• Rate of RSS decay with respect to distance at 60

GHz is higher than at 28 GHz indicating higher path loss

Root mean Square Delay Spread (RMS-DS):• RMS-DS largest for urban environment for most

of UAV heights (high scatterer density)• RMS-DS increases as a function of the UAV

height in the urban environment (can observe larger scattering at higher UAV heights)

• For suburban, rural environments, RMS-DS reduces with UAV altitude (buildings are not as tall, and hence less scattering)

• RMS-DS is lower at 60 GHz compared to 28 GHz

ns-3 wireless challenges

Thomas R. Henderson and Sumit Roy

CSP-NET Interface Breakout Session

NSF-RCN Millimeter-Wave Workshop, July 2017

ns-3 overview

• ns-3 is a leading open source, packet-level network simulator oriented towards network research, featuring a high-performance core enabling parallelization across a cluster (for large scenarios), ability to run real code, and interaction with testbeds

Runsonasinglemachine

orpartitionedacrossacluster

Challenges for 5G wireless simulations

• Largely categorized as scope and scale• Scope issues: pace of standards development, level of detail, implementation

issues, scenario support

• Scope approaches: federated development, common scenario support, vendor assistance

• Scale issues: managing abstractions, parallel wireless simulations

• Scale approaches: link-to-system mapping, simple wireless models

NSF-RCN Millimeter-Wave Workshop July 2017

Recent work on Phy abstractions for ns-3

• ns-3 implementation of TR 38.900 channel model above 6 GHz [1]• including MIMO beamforming architecture, spatial consistency and blockage models, integration with

ns-3 buildings module

• Wi-Fi OFDM error models for TGn fading channels • leveraging MATLAB WLAN System Toolbox

• maps link system simulation results into AWGN tables in the ns-3 simulator

NSF-RCN Workshop July 2017

[1] Zhang et al., NYU Wireless, arXiv: 1702.04822v1, Feb 2017[2] Patidar et al., Univ. Washington, WNS3 2017, June 2017

End-to-end mmWaveDr. Marco mezzavilla, research scientist, NYU

University OF WISCONSIN-MADISON, JULY 19 2017

End-to-end Network Simulator

14

Open source

Indoor/outdoor, urban macro/micro, rural scenarios

Mobility (including vehicular / hi-speed transportation)

Traffic and channel models (including real measurements)

Customizable frame structures, frequency bands, schedulers

Core network (S1/X2) latency

TCP/IP protocols and other technologies (e.g., IEEE 802.11)

© 2017 NYU WIRELESS

mmWave Channel

15© 2017 NYU WIRELESS

• Pathloss (3GPP channel models, NYU, QUADRIGA, ..)

• Real measurements + raytracing (U Bristol)

mmWave Beamforming


• For each TX-RX pair we store the following variables

MultiModelSpectrumChannel

MmWaveSpectrumPhy MmWaveSpectrumPhy

MmWaveEnbPhy MmWaveUePhy

MmWaveUeNetDeviceMmWaveEnbNetDevice

LteRlcAm/UmLtePdcpLteEnbRrc

MmWave

Beamforming

MmWavePropagationLossModel

AntennaArrayModel

MiErrorModel

IPTCP/UDPApplication

EpcEnbApplication

UDPIP

MmWaveEnbMacScheduler

MmWaveUeMac


mmWave eNodeB mmWave UE

UDPIP

IP

EpcPgwSgwApp

PGW/SGW


RemoteHost

ns3/LENA

built-incustommmW

PHY/MACcustommmW

channelmodel

MultiModelSpectrumChannel

MmWaveSpectrumPhy MmWaveSpectrumPhy

MmWaveEnbPhy MmWaveUePhy

MmWaveUeNetDeviceMmWaveEnbNetDevice


MmWave

Beamforming

MmWavePropagationLossModel

AntennaArrayModel

MiErrorModel


EpcEnbApplication

UDPIP

MmWaveEnbMacScheduler

MmWaveUeMac


mmWave eNodeB mmWave UE

UDPIP

IP

EpcPgwSgwApp

PGW/SGW


RemoteHost

ns3/LENA

built-incustommmW

PHY/MACcustommmW

channelmodel

Research Platform


Dynamic channel sounder Channel emulator End-to-end network simulator

TCP Optimization over mmWave* Jing Zhu

Senior Staff Research Scientist

Wireless Communication Research / Intel Lab In collaboration with NYU Wireless (Menglei Zhang; Marco Mezzavilla)

Research Interest / Areas• Multi Radio Network / Convergence

• WLAN/WPAN/WWAN coexistence (e.g. 802.11, 802.16, LTE, etc.)

• Multi-RAT convergence & integration (e.g. LTE WiFi Aggregation, MP-TCP, etc.)

• Interference Mitigation & Spatial Reuse in Ultra-Dense Wi-Fi Networks

• Adaptive Carrier Sensing & TX Power Control

• Cross-Layer Optimization & QoS for Real-Time Internet Apps (e.g. Skype)

• Intra-Flow Prioritization & Scheduling

• 5G/5G+ mmWave Network current focus

• MAC protocol /System Design: mobility management/handover & multi-connectivity/multi-hop relay & beam management

• TCP/cross-layer optimization (bufferbloat, linkoutage)

• Edge Computing & Mobile Compute Offload

TCP over 5G mmWave: Problems• Packet Loss over wireless link is NO longer the

main problem, thanks to advanced link-layer retransmission scheme, e.g. LTE RLC AM.

• Bufferbloat/Overfow [1]: when the link speed drops suddenly (e.g. LOSNLOS), RLC buffer occupancy may increase significantly leading to long latency, packet loss

• Long Link Outage [1] [2]: if link outage is too long (say 1 second), TCP sender may trigger RTO.

• ACK Congestion [3]: the UL congestion (“TCP ACKs”) may limit the maximum DL throughput of a TCP flow

>200ms RTT due to bufferbloat

[1] L. Zhang, et al., Transport Layer Performance in 5G mmWave Cellular, http://arxiv.org/abs/1603.02701[2] R2-1701686, Impact of blockage on TCP performance in high frequency scenarios, MTK, RAN2#97[3] R2-168036, Potential hurdle in maximizing DL TCP throughput NTT DOCOMO, INC., Fujitsu, RAN2#96

http://arxiv.org/abs/1603.02701

Solutions & Preliminary Results

• Active Queue Management [1]: AQM detects congestion by monitoring the instantaneous or average queue size. When the average queue size exceeds a certain threshold but is still less than the capacity of the queue, AQM algorithms infer congestion on the link and notify the end systems to back off by proactively dropping some of the packets arriving at a router. How effective will AQM solve the bufferbloat/overflow problem in 5G mmWave?

• AQM (e.g. CoDel) will trigger TCP congestion avoidance, causing underutilization (low TPT) when the link recovers

• TCP retransmissions may be delayed or lost during the bufferbloat period

• TCP Receiver Window Adjustment seems to be more effective than AQM, but today’s UE-based solution is hard managed, and may not have all the info, e.g. RTT, available bandwidth

• Splitting TCP/TCP Proxy[3] [4]: split the TCP connection at BS/AP into two parts: wireless and wired; Base Station (BS) to mitigate impact of link outage & bufferbloat. How effective will “split TCP” (e.g. TCP proxy) solve the link outage problem and bufferbloat in 5G mmWave?

[1]: https://en.wikipedia.org/wiki/Active_queue_management[2]: Menglei Zhang, et al., The Bufferbloat Problem over Intermittent Multi-Gbps mmWave Links, https://arxiv.org/pdf/1611.02117.pdf[3]: K. Brown and S. Singh, “M-TCP: TCP for Mobile Cellular Networks,” ACM Computer Communications Review (CCR), vol. 27, no. 5, 1997[4]: Jing Zhu, et al. Performance Modelling of TCP Enhancements in Terrestrial-Satellite Hybrid Networks, IEEE/ACM Transactions on Networking, Aug. 2006.

E2E Simulator (like NS3) is essential for cross-layer research (PHY/MAC/NET) in mmWavenetwork

Source: [2]

22

New Real-time Services are envisioned by 2020~2025!

Autonomous Services enabled by ultra-responsive and reliable 5G network

Remote Controlled Drones Self-Driving Cars

Augmented/Virtual Reality Autonomous Robots

Compute and Communication Frameworks

Intelligent, learning-enabled wireless platforms

and networks that can reliably sense, interpret

and act in real-time (<1 ms).

Source: ITU Watch Report on Tactile Internet

Experimental Trials for5G and Beyond

DOCOMO Innovations, Inc.

Yuichi Kakishima

Biography

• Yuichi Kakishima

• Received the B.S. and M.S. degrees from Tokyo Institute of Technology in 2005 and 2007, respectively.

• Joined NTT DOCOMO, INC. in 2007• Engaged in R&D of wireless access technologies

including MIMO technologies for LTE and LTE-Advanced.

• Currently a Manager in DOCOMO Innovations, Inc., California, USA.• Involved in research of 5G cellular network.

• Involved in 3GPP standardization as a delegate to 3GPP RAN1.

Collaborations with Global Vendors• Experimental trials are being started since 2014/Q4

• Including wide frequency band up to 70GHz

• Expanding collaborations to vertical industries

• E.g., Advanced driving support, virtual reality (VR), security systems, etc.

Outdoor Trial • LoS: 2Gbps at 480m away from BS

• N-LoS (in front of building): around 3Gbps

Frequency band: 14.9 GHz

System bandwidth: 730 .5MHz

Radio access: OFDM

BS: 4Tx/Rx (Max 4 streams)

MS: 8Tx/Rx

Indoor Trial

High-Mobility Test in Poster Session• Achieved more than 3Gbps with MS speed over 150km/h

Please visit our booth after this break out session for details!!

Interesting MmWave Networking Issues

Matthew Andrews

19 July 2017

vs

PPP Structured

Traffic Multihop

Half duplex constraints and dynamic TDD

interference

channel

GoB, Interference Modeling, Beam Coordination

vs

Antenna Abstraction

Important Standards for mm Wave Communications

• 3GPP• The global standard body that has defined 3G UMTS and 4G LTE cellular

technologies

• It’s where all of the wireless companies (terminal and infrastructure vendors, operators, …) meet to define how to connect devices to networks

• 3GPP is currently developing 5G cellular networks – the New Radio (NR)

• IEEE 802.11• 802.11 is the de facto Wireless LAN Standard

• Wi-Fi is based on 802.11, implemented in nearly all mobile devices

• Wi-Fi will be a key component of 5G • More than half of all traffic from mobile-connected devices will be offloaded to the fixed

network by means of Wi-Fi


3GPP 5G Standardization Activities and Timeline


20212017 2018 2019 2020

LTE Release 16

New Radio WIs (R16) New Radio WIs (R17)

LTE Release 17LTE Release 15R14

Phase 2 of R15 Specifications

Release 16 Specifications

Phase 1 of R15 - Early Freeze

Today

New Radio SIs (R15) New Radio Study beyond R16 IMT-2020 Submission

New Radio WIs (R15)

5G LTE + NB-IoT(required for

mMTC use cases for IMT-2020)

5G New Radio (NR)…

WRC-19 mmW bands (>6GHz)

eMBB, Low Latency Ultra Reliable, Satellite, mMTC, NOMA, V2X, …

Ch

ann

el M

od

el a

bo

ve 6

GH

z

Non standalone (depend on LTE) NR standalone

Proof of Concept Design e.g., Beam centric operations (< 52.6GHz)

Road to WRC-19


Studies carried out by ITU on above 6 GHz Bands Technical feasibility of IMT in bands above 6 GHz are being studied by ITU-R WP-5D

The ITU report describes a number of channel measurement campaigns by industry and academia

Investigation aimed at the propagation channel characteristics under different propagation condition in these bands: 10, 18, 28, 38, 60, and 72 GHz

ITU & 3GPP plans for future studies on above 6 GHz Bands 3GPP RAN has completed a channel modelling project for above 6 GHz (< 52.6GHz)

New candidate bands will be proposed in the First Conference Preparatory Meeting for the WRC-19

The earliest opportunity for allocation of any band above 6 GHz is in 2019 at WRC-2019

A joint task group within ITU-R of existing license holders from other industries has been formed to closely examine the reallocation of above-6GHz band to mobile communications.

Mm Wave Communications in IEEE 802 Standards• IEEE802.15.3c

• Published in Sept 2009• 57-66GHz frequencies and short range (10m)

• PHY and MAC for WPAN• Single carrier (up to 5.3 Gbps) and OFDM (up to 3.8 Gbps)

• Use Cases • High speed stream content download and wireless data bus

• IEEE 802.11ad (WiGig)• Published in 2012 and has become part of 802.11-2016 (SC part only)• Peak data rate 6.7Gbps• Enabling a set of comprehensive beam selection, refinement, and tracking

procedures• Support multiple antennas and Relay


Mm Wave Communications in IEEE 802 Standards• IEEE 802.11ay

• Currently being developed by TGay• Working on specification draft D0.3 (D1.0 in Nov17, and D2.0 in Mar18)

• Supporting a maximum throughput of at least 20 gigabits per second• Backward compatible to 802.11ad• To include channel bonding (up to 8.64GHz), SU/MU MIMO (up to 8 SSs), analogue and

digital baseband hybrid beamforming, higher order and non-uniform modulation • Use cases: Indoor, Outdoor, Backhaul/front haul/Mesh network,…

• IEEE802.11aj• Chinese mm Wave frequency bands including the 59-64 GHz and the 45 GHz frequency

bands to enable multi-Gbps throughput and lower power• Peak data rate 14.175Gbps (4x4 SU MIMO)• Plan to be published at the end of 2017


Open discussion1. Channel abstraction. The main challenges are (i) directional time-dynamics and (ii) blockage: traces or

statistical models?

2. Are there components of the channel models that we still need to understand to perform reasonable simulations? If so, what?

3. Antenna abstraction: how much should we simplify the antenna pattern? What's the impact on interference characterization, MAC, et cetera?

4. What are the appropriate tools for networking research? What simplifications are reasonable at the physical layer to scale up the number of nodes?

5. Some PHY-MAC layer procedures may be centralized. What is the appropriate interface to the coordinator? What are the bandwidth / delay requirements?

6. What traffic models should we use, in order to capture the key 5G requirements?

7. Network discovery / tracking. How do we model this at a network layer in order to model handover / cell selection?

8. Similarly, how are we going to design and test PHY/MAC for new use cases like vehicular and aerial communications?

9. More in general – what will be the next big PHY-abstraction challenge 5-10 years from now?

csp-net breakout session...em-propagation-software/ benefits of ray tracing • can capture diffuse...

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