Cognitive Radio Networks: Efficient Resource Allocation in Cooperative Sensing, Cellular Communications, High-Speed Vehicles, and Smart Grid PDF
Preview Cognitive Radio Networks: Efficient Resource Allocation in Cooperative Sensing, Cellular Communications, High-Speed Vehicles, and Smart Grid
Digital & Wireless Communication Ji Cognitive Radio a n g Resource allocation is an important issue in wireless communication networks. In • recent decades, cognitive radio-based networks have garnered increased attention W and have been well studied to overcome the problem of spectrum scarcity in future a n Networks wireless communications systems. Many new challenges in resource allocation g appear in cognitive radio-based networks. This book focuses on effective resource • C allocation solutions in several important cognitive radio-based networks, including a o opportunistic spectrum access networks, cooperative sensing networks, cellular networks, high-speed vehicle networks, and smart grids. Efficient Resource Allocation Cognitive radio networks are composed of cognitive, spectrum-agile devices capable of changing their configuration on the fly based on the spectral environment. This capability makes it possible to design flexible and dynamic spectrum access strategies in Cooperative Sensing, Cellular with the purpose of opportunistically reusing portions of the spectrum temporarily C vacated by licensed primary users. Different cognitive radio-based networks focus on Communications, High-Speed O different network resources, such as transmission slots, sensing nodes, transmission power, white space, and sensing channels. G Vehicles, and Smart Grid N This book introduces several innovative resource allocation schemes for different I T cognitive radio-based networks according to their network characteristics: I V • Opportunistic spectrum access networks – Introduces a probabilistic slot E allocation scheme to effectively allocate the transmission slots to secondary Tao Jiang R users to maximize throughput A • Cooperative sensing networks – Introduces a new adaptive collaboration D Zhiqiang Wang sensing scheme in which the resources of secondary users are effectively I utilized to sense the channels for efficient acquisition of spectrum opportunities O Yang Cao • Cellular networks – Introduces a framework of cognitive radio-assisted N cooperation for downlink transmissions to allocate transmission modes, relay E stations, and transmission power/sub-channels to secondary users to maximize T throughput W • High-speed vehicle networks – Introduces schemes to maximize the utilized O TV white space through effective allocation of white space resources to secondary users R K • Smart grids – Introduces effective sensing channel allocation strategies for S acquiring enough available spectrum channels for communications between utility and electricity consumers K25569 6000 Broken Sound Parkway, NW Suite 300, Boca Raton, FL 33487 ISBN: 978-1-4987-2113-4 711 Third Avenue New York, NY 10017 90000 an informa business 2 Park Square, Milton Park www.crcpress.com Abingdon, Oxon OX14 4RN, UK 9 781498 721134 w w w. c r c p r e s s . c o m K25569 cvr mech.indd 1 2/25/15 11:50 AM Cognitive Radio Networks Efficient Resource Allocation in Cooperative Sensing, Cellular Communications, High-Speed Vehicles, and Smart Grid OTHER COMMUNICATIONS BOOKS FROM AUERBACH Analytical Evaluation of Nonlinear Distortion Network Innovation through OpenFlow and SDN: Effects on Multicarrier Signals Principles and Design Theresa Araújo Edited by Fei Hu ISBN 978-1-4822-1594-6 ISBN 978-1-4665-7209-6 Architecting Software Intensive Systems: Neural Networks for Applied Sciences and A Practitioners Guide Engineering: From Fundamentals to Complex Anthony J. 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Visit the Taylor & Francis Web site at http://www.taylorandfrancis.com and the CRC Press Web site at http://www.crcpress.com Contents Preface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ix Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xi AbouttheAuthors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xiii 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1.1 CognitiveRadio-BasedNetworks . . . . . . . . . . . . . . . . . . 1 1.2 OpportunisticSpectrumAccessNetworks . . . . . . . . . . . . . . 4 1.3 CognitiveRadioNetworkswithCooperativeSensing . . . . . . . . 6 1.4 CognitiveRadioNetworksforCellularCommunications . . . . . . 8 1.5 CognitiveRadioNetworksforHigh-SpeedVehicles . . . . . . . . 10 1.6 CognitiveRadioNetworksforaSmartGrid . . . . . . . . . . . . . 11 1.7 ContentandOrganization . . . . . . . . . . . . . . . . . . . . . . 13 2 TransmissionSlotAllocationinanOpportunisticSpectrumAccess Network. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 2.1 Single-UserSingle-ChannelSystemModel . . . . . . . . . . . . . 16 2.2 ProbabilisticSlotAllocationScheme . . . . . . . . . . . . . . . . 18 2.3 OptimalProbabilisticSlotAllocation . . . . . . . . . . . . . . . . 21 2.3.1 BaselinePerformance . . . . . . . . . . . . . . . . . . . . 21 2.3.2 ExponentialDistribution . . . . . . . . . . . . . . . . . . . 21 2.3.3 Hyper-ErlangDistribution . . . . . . . . . . . . . . . . . . 22 2.4 PerformanceAnalysisandEvaluation . . . . . . . . . . . . . . . . 23 2.4.1 ImpactofSensingErrors . . . . . . . . . . . . . . . . . . . 23 2.4.2 ImpactofUnknownPrimaryUserIdlePeriodDistribution . 26 2.4.3 PerformanceComparisons . . . . . . . . . . . . . . . . . . 27 2.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34 Appendix2-A:DerivationofT . . . . . . . . . . . . . . . . . . . . . . 34 k Appendix2-B:DerivationofPC1,1 . . . . . . . . . . . . . . . . . . . . . 35 k v vi (cid:4) Contents Appendix2-C:DerivationofT1 . . . . . . . . . . . . . . . . . . . . . . 36 k 3 SensingNodeAllocationinaCognitiveRadioNetworkwith CooperativeSensing . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37 3.1 Multi-UserMulti-ChannelSystemModel . . . . . . . . . . . . . . 38 3.2 AdaptiveCollaborationSensingScheme . . . . . . . . . . . . . . 41 3.2.1 BasicIdea . . . . . . . . . . . . . . . . . . . . . . . . . . . 41 3.2.2 SequentialProbabilityRatioTest. . . . . . . . . . . . . . . 42 3.2.3 OptimalSensingNodeAllocation . . . . . . . . . . . . . . 43 3.3 PerformanceEvaluationandAnalysis . . . . . . . . . . . . . . . . 47 3.4 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52 Appendix3-A:ProofofL(t ) . . . . . . . . . . . . . . . . . . . . . . . 52 ik Ui Appendix3-B:DerivationofP ∑ Tik<lnη0 ξi . . . . . . . . . . . 53 − (cid:18)k=1 (cid:19) 4 TransmissionPowerAllocationinaCognitiveRadioNetwork. . . . . 57 4.1 CognitiveRadio-AssistedCooperationFramework . . . . . . . . . 58 4.2 OptimalTransmissionPowerAllocation . . . . . . . . . . . . . . . 64 4.2.1 Cross-LayerOptimization . . . . . . . . . . . . . . . . . . 64 4.2.2 PowerConstraintElimination . . . . . . . . . . . . . . . . 65 4.2.3 ThroughputMaximization . . . . . . . . . . . . . . . . . . 66 4.3 PerformanceAnalysisandEvaluation . . . . . . . . . . . . . . . . 68 4.3.1 SimulationScenario . . . . . . . . . . . . . . . . . . . . . 68 4.3.2 PerformanceComparisons . . . . . . . . . . . . . . . . . . 69 4.3.3 ImpactoftheCellPopulation . . . . . . . . . . . . . . . . 70 4.3.4 ImpactofthePrimaryUserTrafficLoad . . . . . . . . . . . 70 4.4 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73 5 WhiteSpaceAllocationinaCognitiveRadio-BasedHigh-SpeedVehicle Network. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75 5.1 ACognitiveRadio-BasedHigh-SpeedVehicleNetwork . . . . . . 76 5.1.1 SystemModel . . . . . . . . . . . . . . . . . . . . . . . . 76 5.1.2 PathLossModel . . . . . . . . . . . . . . . . . . . . . . . 80 5.1.3 AvailableChannelList . . . . . . . . . . . . . . . . . . . . 82 5.1.4 SpectrumSharingList . . . . . . . . . . . . . . . . . . . . 83 5.2 MaximizationofUtilizedWhiteSpace . . . . . . . . . . . . . . . 83 5.2.1 SeparationComputing . . . . . . . . . . . . . . . . . . . . 85 5.2.2 BranchandBoundSearchMethod . . . . . . . . . . . . . . 87 5.2.3 Single-ChannelMethodwithLowComplexity . . . . . . . 89 5.2.4 LinearProgrammingMethodwithLowComplexity . . . . 90 5.3 PerformanceAnalysisandEvaluation . . . . . . . . . . . . . . . . 92 5.4 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 98 Contents (cid:4) vii 6 Sensing ChannelAllocationinaCognitiveRadioNetworkforaSmart Grid . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99 6.1 ElectricityLoadShapingFramework . . . . . . . . . . . . . . . . 100 6.1.1 SmartGridModel . . . . . . . . . . . . . . . . . . . . . . 100 6.1.2 TheCognitiveRadioNetworkModel . . . . . . . . . . . . 104 6.2 SensingChannelAllocationandLoadShapingStrategies . . . . . . 106 6.2.1 SensingChannelAllocationStrategies . . . . . . . . . . . . 106 6.2.2 LoadShapingStrategy . . . . . . . . . . . . . . . . . . . . 107 6.3 PerformanceAnalysisandEvaluation . . . . . . . . . . . . . . . . 109 6.3.1 PerformanceofSensingChannelAllocation . . . . . . . . . 109 6.3.2 PerformanceofElectricityLoadShaping . . . . . . . . . . 111 6.4 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 116 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 117 Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 127
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