presentation onfuture mobile networks

Department of Communications Engineering

TLT – 6507 Advanced Course on Wireless Communications

Presentation onFuture Mobile Networks

Dipesh PaudelHuseyin OgePratik JoshiSemanta NeupaneTugrul Acikgöz


Flow of presentation

o Introductiono Current scenarioo Future Mobile Networkso Cognitive Radio Network (CRN)o Applications of CRNo Conclusion

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TLT-6507 Advanced Course on Wireless Communications


Introduction

o Mobile Network is a wireless service, or wireless carrier that provides network, voice, and data services

o A set of towers which a cell phone can communicate with Switch to the nearest possible tower

o Company that operates a mobile network is Mobile Network Operator (MNO)

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Introduction

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Classified based on the distance they are meant to cover.


Current Scenario

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Current Scenario

o GSM – the most popularo Used to carry voice traffic and some datao Available to almost 90% of world populationo Mobile Data Explosiono Introduction of 3G Mobile System

Wideband CDMA, HSPA, HSPA+o Introduction of HSPA transformed voice dominated to packet

dominatedo LTE (4G): improving end-user throughput, cell capacity and user

plane latency

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Future Mobile Network

o Increasing demand Mobile internet access, Social networking, navigation,

location based service and so ono 3rd Generation Partnership Project (3GPP)

Brings together a number of telecommunications standards bodies.

Produce globally applicable Technical Specifications and Reports for a 3rd Gen Mobile System based on GSM core networks and the radio access technologies that they support

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Future Mobile Network scenarios

o Heterogeneous Networks and Homogeneous Networks Current wireless cellular networks Typically deployed as homogeneous networks. Using a macro centric planning process. Collection of user terminals, all the base stations have similar

transmit power levels, antenna patterns, receiver noise level Similar connectivity to the (packet) data network

oHeterogeneous NetworksoCloud RAN (C-RAN)

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Future Mobile Network Scenarios

o Current wireless cellular networks BSs are deployed for wide area coverage. The footprint of a BS varies depending on traffic demand. In Het-Nets, existing macrocells and microcells remain,

providing essential coverage. Additionally, large macrocells hold advantages in supporting

high-mobility users for reduced handover frequency.

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Heterogeneous Networks

a.k.a "HetNets” o Expanding mobile

network capacity. o Composed of multiple

radio access technologies, architectures, transmission solutions, and base stations of varying transmission power.

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o Heterogeneous Networks Heterogeneous Network utilizes mix of macro, pico, femto and

relay base stations

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o Heterogeneous Networks: an example



o Heterogeneous Networks: Disadvantages Network Management Complexity Increasing number and variety of managed cells Location of Home eNBs (Femto eNBs) Coordination of operation of network domains The cost structure of heterogeneous networks is much lower.

Since low power devices serve much smaller areas with minimal functionality.

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o Cloud RAN A new distributed architecture Aims to reduce the number of cell sites while increasing the

base station deployment density.o The concept of the Cloud RAN

Breaks down the base station into a Base Unit (BU) Converts digital signals to analog, amplifies the power, and

sends the actual transmission

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FUTURE MOBILE NETWORK SCENARIOS

o Network Architecture Evolution: Cloud RAN

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o The advantages of C-RAN over a conventional RAN architectureo Reduction of the Total Cost of Ownershipo Simplifies operationso Enables the distribution of traffic loado Improves load balancing and mobilityo Increased data rates can be achieved

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o Cloud RAN challenges Technical and economic challenges due to the required

optical fiber connection between the central location and antenna sites

Optical Fiber Connections is very expensive Connection imposes challenging requirements concerning

data rates, latency jitter and latency asymmetry For redundancy reasons, one antenna will likely be linked to

the central location through several connections in order to avoid a single point of failure

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o The emergence of C-RAN will pose new requirements on network management, thus if an operator decides to introduce C-RAN, this will proceed in a gradual way

o Requirements for future OAM Systems Researched Mobile Network Technologies like HetNet or C-

RAN add to the complexity of Mobile Network Management by increasing network elements

Complexity is challenging and leads to human-induced errors, however customers aren’t willing to suffer from poor quality of service due to these network-internal issues

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o According to foresights, revenue per bit in mobile network will continue to decline, thus Operation Expenditure (OPEX) will be more dramatically reduced than with SON

o Due to these reasons, future OAM Systems have to aid humans by reducing the complexity, reduce the OPEX and improve the availability of the mobile network through more automation

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COGNITIVE RADIO NETWORKS

o Fundamentals of Cognitive Radioo Frameworko Artificial Intelligence (AI)

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Why Cognitive Radio Networks?o Briefly, SON is a set of automated operations and management

processes for Mobile Networkso The behaviour of SON operations are configured through high-

level parameters which is determined by human operators.o Due to depending on human operators, this turns out to be

cumbersome if the context changes regularly.o From here Cognitive Radio steps in, because mobile networks

must adapt themselves to changes in the operational context

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o Cognitive radios could provide a paradigm shift in the way that spectra is regulated and used

o Cognitive Radios are able to sense the spectrum to see whether it is being used by the Primary User.

o Quick look to IEEE 802.22 Working Group

o Frequency reuse is typically done through frequency planning, resulting in an inefficient utilization of frequencies across different geographical regions



Cognitive Radio Networko SON introduced framework with closed loop automation. o Automate the management by defining SON functions o Functions perform their task without human intervention.o CRN extends this vision by substituting SON functions and

workflows with Cognitive Processes controlled by goals.o Thus, SON network management loop is replaced by a cognitive

network management loop.

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The cognitive network management loop



o Proposed by Fortuna and Mohorcic in 2009.o Cognitive Process continuously monitors the environment i.e. sense

through Network Status Sensors.o This information is used to create several strategies how the network

configuration should be changed i.e. plan based on goalso Sensor Information is used for learning to build up knowledge of the

effects of actions i.e. learno The system has to decide which plan to implement based on goal i.e.

decideo This strategy is then enacted using Network API i.e. act

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Cognitive loop



o As Cognitive loop is very complex, some steps can be bypassed.o It is possible to declare a sensor output as critical and ssign an

action which causes the system to skip the plan and decide phase and act immediately.

o CRN do not assume any specific architecture of the network. o Thus, Functionality of the process can be distributed same way

as SON.o i.e. centralised, decentralised and hybrid.

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o CRN relies on sophisticated AI technologies to fulfill the challenging vision.

o Special Interest for cognitive loop: Knowledge Representations Planning and decision algorithms Learning technology

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Application of CRN

o CRN can sense the surrounding environment and without the intervention of the user can adapt to the users communication needs.

o CRN has capability for efficient spectrum utilization since it can intelligently detect whether any portion of the spectrum is in use or not.

o The main application of CRN is to solve the shortcomings of SON and ease the functions of network operators more.

o SON concepts can be improved in areas of self-configuration, self-optimization, self-healing and operation using CRN concept.

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Application of CRN

Self-Configurationo SON involves loading initial configuration parameters to new

base stations.o This involves hectic and complex manual planning procedures.o In CRN initial configuration is loaded in the base stations

automatically by OAM systems(operations, administration and maintenance).

o The configuration parameters are obtained by measurements of environment from new base station, location of new base station and operator policies.

o These obtained parameters are loaded into the base-station using SON algorithms.

o The efficiency of this configuration is continuously evaluated by the base-station and its neighbors. This knowledge is then used for loading configurations in other base stations.

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Application of CRN

Self-optimizationo Self-optimization algorithms in SON are static and do not change

with the change in operational environment.o These algorithms cannot handle uncertainty problems which

requires probabilistic reasoning.o CRN improves the self-optimization process by employing

inference based algorithms.o The network performance is measured from which the current

system state and performance issues are inferred using uncertain knowledge representation.

o The cognitive process continuously monitors the performance to gather information for making the self-optimization process more effective.

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Application of CRN

Self-healingo SON self-healing involves two phases. o 1st phase: problem detection and diagnosis using predefined

knowledge.o 2nd phase: action for healing done by compensation of a cell

outage by neighboring cells. requires extensive manual work which will increase with the

increase in number of nodes.o CRN self-healing process involves automated detection and

diagnosis of network failures and automated advisory process determining which recovery actions to execute.

o The automated advisory process should give the most optimal solution for the problem.

o The whole process is continuously monitored as a part of learning, so that the solutions for different situations can be used in the future.

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Application of CRN

Operationo SON has defined the co-ordination function for controlling

different SON functions.o The implementation of these functions is time consuming, costly

and error prone.o Changes in certain parameters forces change in operational

behavior. To address these changes considerable human effort is needed.

o CRN uses knowledge representation which is used to represent semantics of operational goals, network properties and network status.

o The information is now used for automated reasoning for obtaining coordination function at run time.

o Any change in the goals can be reflected in the knowledge Base of the system.

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Conclusion

o Future mobile technology has many challenges. The system should be reliable, cheap and fast with the ability to adapt to the changing environment and integrating diverse devices.

o To meet these requirements we have to go beyond SON concept.o SON has been extended to include automation in the network

leading the way for CRN concept.o CRN extensively uses theory and algorithms of Artificial

Intelligence. o CRN is in the initial phase of development. With the integration of

machine intelligence and communication technologies, CRN is certainly the future of mobile communication.

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THANK YOU

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presentation onfuture mobile networks

Engineering

wireless communications

advanced course

communications engineering8tlt

communications engineering7tlt

introductiono mobile

wireless service

future mobile networko

gen mobile system