Cognitive Rrm Dasilva

Embed Size (px)

Citation preview

  • 8/22/2019 Cognitive Rrm Dasilva

    1/27

    06/ 05/ 2012

    1

    Cognitive Radio Resource

    Management

    Prof. Luiz DaSilva

    Theory and Practice of Cognitive Radio

    Aalborg University

    May 9-11, 2012

    About me...

  • 8/22/2019 Cognitive Rrm Dasilva

    2/27

    06/ 05/ 2012

    2

    Objectivesof

    Cognitive

    Radio

    ResourceManagement

    ApproachesforAllocationof

    WirelessResources

    FunctionalArchitecturesfor

    CognitiveRRM

    RadioResourceManagement(RRM)

    Efficientallocationofresourcesinawirelessnetwork

    Orthogonalchannels,throughfrequency,time,code

    oratleastallocationsthatresultintolerableamountof

    interference

    Achievedthrough

    Transmitpowercontrol

    Spectrum/channelallocation

    Accesstothemedium/scheduling

    Multiantennause(beamforming,MIMO)

    Multitransceiveruse

  • 8/22/2019 Cognitive Rrm Dasilva

    3/27

    06/ 05/ 2012

    3

    Goals

    Goalsoftheindividualradio

    MaximizeSINR,datarate,throughput

    Mitigatetheeffectsofnoise,interference

    Maximizeaccesstothemedium

    Maximizebatterylife

    Goalsofthenetwork

    Ensureefficientuseofspectrumresources

    Maximizeaggregatethroughput

    Avoidunduecontentionforresources

    Ensureappropriatecoverage

    WhatisdifferentinCognitive RRM?

    Greaterabilityoftheterminaltoreconfigure(softwaredefinedradio)

    RadiosmaybecapableofworkingwithmultipleRadio

    AccessTechnologies

    (RATs)

    Frequencyagility

    Opportunisticuseofspectrum,ordynamicspectrummanagement

    User

    Service

    Terminal

    Network

    RRM

  • 8/22/2019 Cognitive Rrm Dasilva

    4/27

    06/ 05/ 2012

    4

    CognitiveRadioResourceManagement

    Dynamicallocationofresources(e.g.,spectrum)whenradioshaveincreasedabilitytoadaptandreconfigure(frequencyagility,multipleRATs,etc.)

    Higherdegreeofautonomyfromtheradios(radiosmayparticipateintheresourcemanagementdecisions)

    Coexistence:competitionandcooperationintheuseofresources

    Allocationof

    traffic

    to

    different

    RATs

    that

    are

    supported

    in

    thenetwork

    FlexibleSpectrumManagement

    Coordinated

    Verticalhandovers

    Spectrumsharing/pooling

    Spectrumbroker

    Virtualoperators

    Realtimespectrumauctions

    Autonomous

    Sharedbands Opportunisticmultiband

    randomaccess

    Cooperativeaccess,

    coalition

    formation

    Licensedbands Secondaryaccess,interruptible

    byprimaryuser

    Femto/macrocellcoexistence

    Dynamicmultihoming

  • 8/22/2019 Cognitive Rrm Dasilva

    5/27

    06/ 05/ 2012

    5

    CoordinatedExample

    Spectrumbrokercontrols

    accesstopartofthespectrum

    Grantsatimeboundlease

    tooperators,specifying

    spatialregion,maximum

    power,exclusiveornon

    exclusiveusagerights

    Regionunderbroker

    controlmayhavebase

    stationsofseveral

    providers

    d

    a

    f

    c

    Autonomous,NonCooperative

    Example1

    Topologycontrolinadhoc

    networks

    Eachnodesetsits

    transmissionpowerand

    channelofoperationto

    achievesome

    connectivity

    objective

    Accesstothemediumis

    random(unscheduled)

  • 8/22/2019 Cognitive Rrm Dasilva

    6/27

    06/ 05/ 2012

    6

    Autonomous,NonCooperative

    Example2

    Opportunisticspectrumaccess

    Secondaryuserdetects

    whitespaceandshapesits

    signaltofitintoit

    Noexplicitcooperation

    withincumbentisrequired,

    aslongandinterference

    doesnotexceedpre

    determinedlimit 2.4096 2.4097 2.4098 2.4099 2.41 2.4101 2.4102 2.4103 2.4104x 109

    60

    50

    40

    30

    20

    10

    0

    Frequency (Hz)

    Magnitude(dB)

    Autonomous,Cooperative

    Example

    Cooperativespectrumsharing

    Multiplesecondaryusersin

    amultichannel

    environmentnegotiate

    spectrumusage

    Informationdissemination

    regardingprobabilityof

    incumbentactivityand

    economicincentivesmay

    bepartofthenegotiation

  • 8/22/2019 Cognitive Rrm Dasilva

    7/27

    06/ 05/ 2012

    7

    Approaches

    Classicaloptimization

    Gametheory

    Heuristics

    Metaheuristics

    Multiobjectiveapproaches

    andcombinationsofthese

    Parameters

    Physical

    MAC

    Network

    Application

    Transmitpower,modulation,channel

    codingrate,channelselection,resource

    blocks,

    Transmissiontimeandchannel,service

    rate,priority,

    Routeselection,costmetric,cooperation,

    Sourcecodingrate,priority,packetarrival

    rate,

  • 8/22/2019 Cognitive Rrm Dasilva

    8/27

    06/ 05/ 2012

    8

    OptimizationGoals

    Physical

    MAC

    Network

    Application

    Minaggregate

    power,

    max

    throughput,

    maxrate/Joule,maxspectralefficiency,

    minBER,

    Maxaggregatethroughput,minbuffer

    overflowprobability,mindelay,

    Minroutelength,minenergyexpended,

    Mindistortion,mindelay,

    Constraints

    Physical

    MAC

    Network

    Application

    Maxtransmitpowerpernodeand/or

    channel,availablemodulation

    constellation, availablechannelcoding

    rate,

    Limitedtime/frequencyslots,limited

    informationaboutothermobiles,

    Maxnumberofhops,

    Limitedsourcerate,strictdelay

    requirements,

  • 8/22/2019 Cognitive Rrm Dasilva

    9/27

    06/ 05/ 2012

    9

    ClassicalOptimization

    Findanoptimalallocationofresourcestomeetacertaingoal

    Linear/nonlinear/integer/MILP

    Mayassumecentralizeddecisionmakingand/orfull

    information

    Complexityissues

    S

    ,,2,10)(

    ,,2,10)(

    )(min

    =

    ==

    x

    x

    x

    x

    rjg

    mihtosubject

    f

    j

    i

    K

    K

    ClassicalOptimizationExample

    Given

    Asetofsourcedestinationpairsinthenetworkand

    associateraterequirements

    Findtheoptimal

    Assignmentoffrequencybandstoeachpair

    Schedulingofsubbandsfortransmissionandreception

    Multihoprouting

    Thatminimizes

    Thetotalbandwidthusedinthenetwork

  • 8/22/2019 Cognitive Rrm Dasilva

    10/27

    06/ 05/ 2012

    10

    ClassicalOptimizationExample:Formulation

    Y.T.Hou,Y.Shi,andH.Sherali,Spectrum

    SharingforMultihop Networkingwith

    CognitiveRadios,IEEEJSAC, Jan.2008.

    DistributedOptimization

    Optimizationproblemswhereeachvariableandconstraintis

    ownedbyanagent

    Consideranetworkofnagents:

    Agentswanttocooperativelyfind:

    Objectivefunction isknowntoagenti

    Agentsperiodicallyexchangeinformationandestimatetheir

    impactontheobjectivefunction

    Moretailoredtodistributedscenarioswithincomplete

    information

    },,1{ nN K=

    )(min1

    xx =n

    i

    iR fm

    RRf m

    i :)(x

  • 8/22/2019 Cognitive Rrm Dasilva

    11/27

    06/ 05/ 2012

    11

    GameTheory

    Mathematicalmodelsofconflictandcooperationamong

    intelligent,rationaldecisionmakers

    Canbeusedtostudythedistributedresourceallocation

    decisionsmadebydecisionmakers(networknodes,radio

    providers)toachievesomegoal(maximizeperformance,

    minimizeresourceutilization)

    Agameconsistsof

    Asetoftwoormoreplayers

    Setsof

    possible

    actions

    for

    each

    player

    Asetofpreferencerelationshipsforeachplayerovereach

    actiontuple

    CooperativeandNonCooperativeGameTheory

    Noncooperative

    Playersmakedecisionsindependently

    Cooperative

    Playersareallowedtoenterintoagreements,form

    coalitions,etc.

    Externalentityassumedtoexisttoenforcecontracts

    Itispossibletomodel/predicttheoutcomeofabargaining

    processwithoutmodelingtheprocessitself

  • 8/22/2019 Cognitive Rrm Dasilva

    12/27

    06/ 05/ 2012

    12

    NonCooperativeGameTheoryExample

    SINRmaximizingpowercontrolgame

    Setofplayers:cognitiveradiosinacertainregion

    Setofactions:eachradio setsitstransmitpower to

    maximizeitsutilityfunction

    whereMisthestatisticalcrosscorrelationofthesignals

    }{,, iuAN=

    Ni ip

    +=

    }\{

    )1()(

    iNk

    kk

    iii

    phM

    phu

    p

    J.O.Neel,J.H.Reed,andR.P.Gilles,GameModelsfor

    CognitiveRadioAlgorithmAnalysis,SDRForumTechnicalConf., Nov.2004.

    CooperativeGameTheoryExample

    Cooperativespectrumsharinggame

    Setofplayers:cognitiveradiosinagivenregion

    Setofactions:eachplayerselectsasubsetofatotalofK

    channelstooccupy(eachwithbandwidthB/K),andthepower

    allocationoneachofthosechannelstomaximizeutility

    function

    Radioscanbargainwithoneanothertoachieveanefficient

    solutionJ.E.Suris,L.A.DaSilva,Z.Han,A.B.MacKenzie,andR.

    Komali,AsymptoticOptimalityforDistributedSpectrum

    SharingUsingBargainingSolutions,IEEETrans.WirelessCommunications,vol.8,no.10,Oct.2009.

    2log (1 )i kk

    Bu SINR

    K= +

  • 8/22/2019 Cognitive Rrm Dasilva

    13/27

    06/ 05/ 2012

    13

    TypicalResultsofGameTheoreticAnalysis

    Equilibria

    Stableoperatingpointsforthenetworkfromwhich,once

    reached,noplayerhasanincentivetodeviate

    Convergenceproperties(noncooperativegames)

    Indicationofwhetherthroughanadaptiveprocessplayers

    willarriveatanequilibrium

    Expectedoutcomeofbargaining(cooperativegames)

    Indicationofwhetheramoreefficientoutcomecanbe

    arrivedat

    through

    cooperation

    Designofincentives/disincentives

    Examples:auctions,mechanismdesign

    Heuristics

    Approximationsthatseekagoodenough,ratherthanan

    optimal,solutionfortheproblem

    Appropriatewhen

    Problemistoocomplexforanoptimizationsolutiontobe

    foundinreasonableamountoftime

    Environmentchanges

    too

    rapidly

    Adaptationsandresourceallocationdecisionsmustbe

    madeunderpartialinformation

    Heuristicsolutioncanbeshowntodonotmuchworse

    thantheoptimum

  • 8/22/2019 Cognitive Rrm Dasilva

    14/27

    06/ 05/ 2012

    14

    HeuristicsExamples

    Linearorparameterizedapproximationstoobjective

    functions

    Mayallownonconvexproblemstobetreatedasconvex

    Maybereasonableapproximationsundersomeconditions

    (highSNR,largenumberofchannels,etc.)

    Simpleadaptationsthatcanbeshowntogivegoodresults

    withhighprobability

    Adaptationsbasedonlocalconditions,withouttakinginto

    accountglobal

    state

    of

    the

    network

    MetaHeuristics

    Heuristicmethodsforsolvingaclassofcomputational

    problemsforwhichthereisnopractical(e.g.,polynomial

    time)solution

    Usesomeblackboxproceduresthatarethemselves

    heuristics

    Examples

    HillClimbingorgreedyAlgorithm

    Tabu search

    Simulatedannealing

    Geneticalgorithms

  • 8/22/2019 Cognitive Rrm Dasilva

    15/27

    06/ 05/ 2012

    15

    MetaHeuristicsExample

    Islandgeneticalgorithmappliedtothechannelallocation

    problemincognitivenetworks

    Protocolmodelofinterference

    Anislandgeneticalgorithmdividesthepopulationinto

    subpopulations,orislands,thatinteractthroughthemigration

    ofindividualstootherislands

    Seekchannelassignmentthatmaximizessumcapacity

    Startwithavalidchannelassignment,performmutationand

    crossover

    of

    individuals

    with

    high

    fitness

    function

    D.Friend,M.ElNainay,Y.Shi,andA.B.MacKenzie,

    Architectureand PerformanceofanIslandGenetic

    AlgorithmBasedCognitiveNetwork,Proc.IEEEConsumerComm.AndNetworkingConf.,pp.993997,2008.

    MultiObjectiveOptimization

    Alternatives

    Combineallobjectivefunctionsintoanaggregateobjective

    function,suchasaweightedsum(buthowtoassign

    weights?)

    LookforsolutionsintheParetofrontier

    [ ]

    S

    ,,2,10)(

    ,,2,10)(

    )()()(min 21

    =

    ==

    x

    x

    x

    xxx

    rjg

    mihtosubject

    j

    i

    T

    p

    K

    K

    K

  • 8/22/2019 Cognitive Rrm Dasilva

    16/27

    06/ 05/ 2012

    16

    TheParetoFrontier

    Givenanallocationofresourcesinvolvingsometradeoff,say

    performanceandcost,aParetoimprovementisamovementfromoneallocationtoanotherthatcanmakeatleastone

    individualbetteroffwithoutmakinganyindividualworseoff

    AsolutionisParetooptimalorParetoefficientifnoParetoimprovementispossible

    Thesetofallsolutionstoamultiobjectiveoptimizationthat

    areParetooptimalistheParetofrontier No

    objective

    can

    be

    further

    improved

    without

    making

    at

    leastoneotherobjectiveworseoff

    ParetoFrontier:Visualization

  • 8/22/2019 Cognitive Rrm Dasilva

    17/27

    06/ 05/ 2012

    17

    ConsiderationsintheSelectionofanApproach

    Timescaleinwhichresourceallocationmustbemadeand

    timescaleinwhichenvironmentchanges

    Fairlystatic(optimization)versusdynamic(heuristics)

    Centralized(optimization)versusdecentralized(gametheory,

    distributedoptimization,heuristics)

    Processingcomplexity

    Realtimeadaptations(heuristics)versusestablishmentof

    baselineidealresults(optimization)

    IEEE1900.4

    ArchitectureandEnablersforOptimizedRadioandSpectrumResourceUsage

    DefinesamanagementsystemthatdecidesactionsrequiredtooptimizeradioresourceusageandQoS inheterogeneouswirelessenvironments

    Spectrumassignment(carrierfrequency,signalbandwidth,

    radiointerface

    used

    in

    the

    assigned

    spectrum)

    to

    radio

    accessnetworks(RANs)canbedynamicallychanged OrspectrumassignmenttoRANsisfixed,butaRANcan

    operateconcurrentlyinmultiplebands Terminalsarereconfigurableandmayormaynotbecapable

    ofmultihoming Multihoming =capabilitytosimultaneouslymaintain

    morethanoneactiveconnectionwithRANs

  • 8/22/2019 Cognitive Rrm Dasilva

    18/27

    06/ 05/ 2012

    18

    IEEE1900.4Resource

    Management

    Reconfigurationdecisionsare

    madebytheterminal(TRM)

    andbythenetwork(NRM)

    Logicalcommunicationchannel

    betweenTRMandNRMcanbe

    realizedinband(usingan

    existingRANalsousedfordata)

    oroutofband(specifyinga

    dedicatedphysicalchannelfor

    thiscommunication)

    S.Buljoreetal.,ArchitectureandEnablersforOptimizedRadioResourceUsageinHeterogeneousWirelessAccess

    Networks,IEEECommunicationsMagazine, Jan.2009.

    IEEE1900.4ReferenceUsage

    Cases

    Dynamicspectrumassignmentexample:aspectrumbandisshifted

    from802.16eto802.11n

    duetoshiftsindemand

    Dynamicspectrumsharingexample:802.22systems

    usingVHF/UHFbands

    opportunistically

    Distributedradioresourceusageoptimizationexample:jointoptimization

    ofresourceassignmentby

    terminalsandnetwork

    S.Buljoreetal.,ArchitectureandEnablersforOptimizedRadioResourceUsageinHeterogeneousWirelessAccess

    Networks,IEEECommunicationsMagazine, Jan.2009.

  • 8/22/2019 Cognitive Rrm Dasilva

    19/27

    06/ 05/ 2012

    19

    IEEE1900.4SystemArchitecture

    Terminal context

    information

    (terminal

    capabilities,

    user preferences,

    required QoS,

    measurements,

    geo-location

    info, )

    RAN context

    information(optimization

    objectives,

    radio

    capabilities,

    measurements,)

    Radio resource

    selection

    policies

    IEEE1900.4FunctionalArchitecture

  • 8/22/2019 Cognitive Rrm Dasilva

    20/27

    06/ 05/ 2012

    20

    BringingDynamicSpectrum

    Accessto

    4G

    (LTE+)

    and

    Beyond

    Licensedspectrumis

    augmentedwithdynamic

    accesstoadditionalbands

    CoordinatedbySpectrum

    AccountabilityServer(SAS)

    Signallingtocontrolaccessto

    additionalbandsusesthe

    licensedcarriers

    Datatransportedoverlicensed

    anddynamicallyallocated

    carriers

    J.Deaton,R.IrwinandL.A.DaSilva,TheEffectsofa

    DynamicSpectrumAccessOverlayinLTEAdvanced

    Networks,Proc.ofIEEEDySPAN,2011

    SAS

    cBS

    Spectr umAuct i on

    Li censed Car r i er

    BCCHCCCHDCCHDTCHPCCH

    DCCHDTCHPCCH

    CONNCONNCONNCONN IDLEIDLEIDLEIDLE

    CONNCONNCONNCONN

    BCCH: Broadcast Control Channel

    CCCH: Common Control Channel

    DCCH: Dedicated Control Channel

    DTCH: Dedicated Traffic Channel

    PCCH: Paging Control Channel

    ArchitectureforDSAinLTE+

    HSS

    PDG

    ( SGW+PGW)

    I nter net

    MME

    UE

    E- UTRAN

    eNBeNB

    eNB

    eNB

    eNB

    eNB

    eNB

    GDB

    cUE

    SAS

    cRAN

    S1- U

    S1- MME

    S1- U

    S1- MME

    S11

    Di amet er ( RFC 3588)

    eNB: Evolved Node B

    E-UTRAN: Evolved Universal Terrestrial Radio Access

    HSS: Home Subscriber Server

    MME: Mobility Management Entity

    PDG: Packet Data Gateway

    PGW: Packet Gateway

    SGW: Signaling Gateway

    LTE Net wor k El ement s

    cBS: cognitive Base Station

    cRAN: cognitive Radio Access Network

    cUE: cognitive User Equipment

    GDB: Geolocation Data Base

    SAS: Spectrum Accountability Server

    SA Net wor k El ement s

    cBS

    cBScBS

    cBS

    cBS

    cBS

    cBS

  • 8/22/2019 Cognitive Rrm Dasilva

    21/27

    06/ 05/ 2012

    21

    ArchitecturalComponents

    cBS

    I P Reachabl eSpect r umTrendi ngTr af f i c Trendi ng

    Spect r umAgi l e Radi oRRC Spect r umSensi ng

    SAP: Spect r umAccount i ng Prot ocol

    X2e- Cooperat i ve SenseX2e- Spectr umTradi ng

    PDG

    I P Gat ewayI P Tunnel i ng t o cUE

    SAS

    Spect r umPol i cy &Leasi ng

    SAP: Spect r umAccount i ng Protocol

    Spectr umAccount abi l i t y

    I nter f erence Al arms

    cUE

    Spect r um Agi l e Radi oRRC - Spect r umSensi ng

    I RI P Connect TVSer vi ce Loss

    Detect i onSer vi ce Loss

    Repor t i ng

    SignallingEndpoints

    H- PDGH- cBS

    I R

    I nt ernet

    GDB

    SAS

    N- PDGN- cBS

    I R

    I R

    OPERATOR A

    OPERATOR B

    Networ k Operat orsRegul ator Agenci es

    DSA Stat i st i cs

    H- cUE

    H- cUE

    N- cUE

    N- cUE

    X2e: Cooper at i ve Sensi ngX2e: Spectr um Tradi ng

    H- : HomeN-: Nei ghborI R: I nt egrat ed Recei verSAP: Spect r umAccountabi l i t y Pr ot ocol

  • 8/22/2019 Cognitive Rrm Dasilva

    22/27

    06/ 05/ 2012

    22

    cBS RegistrationandNeighbourDiscovery

    Update Local DB

    SAP: cBS Registration Request

    IP Addr., Geolocation

    SAP: cBS Registration Response

    Registration Successful

    SAP: cBS Neighbor Request

    cBS Neighbors Not Known

    SAP: cBS Neighbor Response

    Request Successful

    SASH-cBS

    Create Spectrum Account for H-cBS

    Find cBS Neighbors

    N-cBS

    Update Neighbor Tables

    X2e: Link Setup Request

    Sent to each neighbor

    X2e: Link Setup Response

    Request Successful

    SpectrumLeaseRequestProcedure

    SAScBScUE

    SAP: Spectrum Lease Request

    Calculate Lease Request

    Evaluate Spectrum Availability

    SAP: Spectrum Release Order

    SAP: Spectrum Release ACK

    Update Spectrum Account with Lease

    information

    Service Requests

    SAP: Spectrum Lease Response

    Spectrum available

    Procedure Note:

    This process could be executed during the maintenance window or on demand on a call by call basis.

    Demand Trigger:

  • 8/22/2019 Cognitive Rrm Dasilva

    23/27

    06/ 05/ 2012

    23

    SpectrumSharingProcedure

    H-cBScUE

    SAP: Spectrum Lease Response

    Spectrum unavailable

    Evaluate Spectrum Availability

    SAP: Spectrum Lease Request

    X2e-ST: Spectrum Release Order

    X2e-ST: Spectrum Release ACK

    Add Spectrum to Available Pool

    SAS N-cBS

    X2e-ST: Spectrum Lease Request

    Evaluate Spectrum Availability

    X2e-ST: Spectrum Lease Response

    Spectrum available

    Service Request

    Procedure Notes:

    This process could be done during the maintenance window or on demand

    Calculate Lease Request

    Demand Trigger:

    ServiceRequestandReportingProcedure

    RRC Carrier Optimization

    RRC: Connection Request

    Licensed spectrum

    SAScBSIDLE_cUE

    Determine Carrier for Use

    Service Response

    Carrier Assignment Available

    cUE Service

    Change Carrier

    Report Service KPI

    Successful/Dropped/Lost/BlockedService

    Record and Report Statistics

    CONN_cUEs

    RRC: Carrier Handoff Order

    Channel reassignment

    RRC: Carrier Handoff Complete

    Determine Carrier Use and

    Availability

    Procedure Notes:

    This process is done on

    demand.

    The RRC optimization

    procedure is one of the first

    open issues.

    Reporting Service Usage could

    also be combined in the

    spectrum lease release

    SAP: Report Service KPI

    Piggybacked on Spectrum ReleaseACK or Periodic

  • 8/22/2019 Cognitive Rrm Dasilva

    24/27

    06/ 05/ 2012

    24

    PerformanceAnalysis:Scenario

    cBS

    cBS

    cBS

    Demand

    Demand

    Demand

    10MHzLicensedCarrier

    10MHzLicensedCarrier

    10MHzLicensedCarrier

    10MHzSharedDSACarrier

    Service

    Service

    Service

    OverflowTraffic

    PoissonArrivals

    With

    ParetoSessionDemand

    DSAChannelAvailability

    BetaDistribution

    Ti me

    Packet

    Size

    Par et o Demand

    Poi sson Ar r i val s

    PerformanceAnalysis:SpectrumAvailability

    Ti me

    Spectrum

    200 kHz

    1 sec

    Spect r umAvai l abi l i ty Prof i l e

    OFF ON

    Modi f i ed Beta Di st r i but i on

  • 8/22/2019 Cognitive Rrm Dasilva

    25/27

    06/ 05/ 2012

    25

    PerformanceAnalysis:Results

    HeterogeneousNetworks

    Operatordeployedand/oruserdeployedsmallcells

    Significantimprovementinoverallcapacity

    SmallcellsaddcomplexitytoRRMproblem

    Verticalhandover

    Femto

    femto and

    macro

    femto channel

    allocation

    and

    interference

    TheRRMtaskalsobecomesincreasinglydecentralized

    Lessplanningofinfrastructuredeployment

  • 8/22/2019 Cognitive Rrm Dasilva

    26/27

    06/ 05/ 2012

    26

    J.Deaton,R.Irwin,andL.DaSilva,Supporting

    DynamicSpectrumAccessinHeterogeneousLTE+

    Networks,underreview,2012.

    IncorporatingIndoorSmallCells

    Radioresourcemanagementreferstothe

    allocationofwirelessresourcestofulfill

    networkanduserobjectives

    Incognitiveradionetworks,musttakeinto

    accountincreasedreconfiguration

    capabilitiesoftheradios,frequencyagility,

    coexistence

    between

    primary

    and

    secondary

    users,multipleradioaccesstechnologies

    Essentially,anoptimizationproblem

    Functionalarchitecturesbeingstandardized

    (IEEE1900)andproposedintheliteraturefor

    4Gnetworksandbeyond

  • 8/22/2019 Cognitive Rrm Dasilva

    27/27

    06/ 05/ 2012

    About CTVR www.ctvr.ie

    On email [email protected]

    Papers luizdasilva.wordpress.com

    Wireless @ Virginia Tech wireless.vt.edu

    Ontheinterwebs