LEADER 06670nam 22008055 450 001 9910254194403321 005 20200629220235.0 010 $a981-10-0024-7 024 7 $a10.1007/978-981-10-0024-9 035 $a(CKB)3710000000501350 035 $a(EBL)4089251 035 $a(SSID)ssj0001584630 035 $a(PQKBManifestationID)16265385 035 $a(PQKBTitleCode)TC0001584630 035 $a(PQKBWorkID)14865567 035 $a(PQKB)11302285 035 $a(DE-He213)978-981-10-0024-9 035 $a(MiAaPQ)EBC4089251 035 $a(PPN)190523328 035 $a(EXLCZ)993710000000501350 100 $a20151109d2016 u| 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aGame-theoretic Interference Coordination Approaches for Dynamic Spectrum Access /$fby Yuhua Xu, Anpalagan Alagan 205 $a1st ed. 2016. 210 1$aSingapore :$cSpringer Singapore :$cImprint: Springer,$d2016. 215 $a1 online resource (100 p.) 225 1 $aSpringerBriefs in Electrical and Computer Engineering,$x2191-8112 300 $aDescription based upon print version of record. 311 $a981-10-0022-0 320 $aIncludes bibliographical references at the end of each chapters. 327 $aPreface; Contents; Acronyms; 1 Introduction; 1.1 Interference Coordination in Dynamic Spectrum Access; 1.1.1 Preliminaries; 1.1.2 Challenges and Problems; 1.2 Game-Theoretic Solutions for Interference Coordination; 1.2.1 Motivation of Applying Game Models; 1.2.2 A General Framework of Game-Theoretic Solutions; 1.3 Organization and Summary; References; 2 Distributed Interference Mitigation in Time-Varying Radio Environment; 2.1 Introduction; 2.2 System Model and Problem Formulation; 2.2.1 System Model; 2.2.2 Problem Formulation; 2.3 Interference Mitigation Game in Time-Varying Environment 327 $a2.3.1 Game Model2.3.2 Analysis of Nash Equilibrium; 2.4 Achieving NE Using Stochastic Learning Automata; 2.4.1 Algorithm Description; 2.4.2 Convergence Analysis; 2.5 Simulation Results and Discussion; 2.5.1 Convergence Behavior; 2.5.2 Performance Evaluation; 2.6 Concluding Remarks; References; 3 Game-Theoretic MAC-Layer Interference Coordination with Orthogonal Channels; 3.1 Introduction; 3.2 Motivation, Definition, and Discussion of MAC-Layer Interference; 3.2.1 Motivation and Definition; 3.2.2 Discussion on the Impact of Channel Fading; 3.3 System Model and Problem Formulation 327 $a3.3.1 Bilateral Interference Networks3.3.2 MAC-Layer Interference Minimization; 3.4 MAC-Layer Interference Minimization Game; 3.4.1 Graphical Game Model; 3.4.2 Analysis of Nash Equilibrium; 3.5 The Binary Log-Linear Learning Algorithms for Achieving Best NE; 3.5.1 Algorithm Description; 3.5.2 Convergence Analysis; 3.6 Simulation Results and Discussion; 3.6.1 Scenario Setup; 3.6.2 Scenario with No Fading; 3.6.3 Scenario with Fading; 3.7 Extension to Unilateral Interference CRNs; 3.7.1 System Model; 3.7.2 Simulation Results; 3.8 Concluding Remarks; References 327 $a4 Game-Theoretic MAC-Layer Interference Coordination with Partially Overlapping Channels4.1 Introduction; 4.2 Interference Models and Problem Formulation; 4.2.1 MAC-Layer Interference Model with Partially Overlapping Channels; 4.2.2 Problem Formulation; 4.3 Graphical Game Model ; 4.3.1 Graphical Game Model; 4.3.2 Analysis of Nash Equilibrium; 4.4 Simultaneous Log-Linear Learning Algorithm with Heterogeneous Rates; 4.4.1 Algorithm Description; 4.4.2 Convergence Analysis; 4.5 Simulation Results and Discussion; 4.5.1 Scenario Setup; 4.5.2 Convergence Behavior; 4.5.3 Performance Evaluation 327 $a4.6 Concluding RemarksReferences; 5 Robust Interference Coordination with Dynamic Active User Set; 5.1 Introduction; 5.2 System Model and Problem Formulation; 5.2.1 System Model; 5.2.2 Problem Formulation; 5.3 Channel Sensing Order Selection Games; 5.3.1 State-Based Order Selection Game; 5.3.2 Robust Order Selection Game; 5.3.3 Distributed Learning Algorithm with Dynamic Active User Set; 5.4 Simulation Results and Discussion; 5.4.1 Convergence Behavior; 5.4.2 Throughput Performance; 5.5 Concluding Remarks; References; 6 Future Direction and Research Issues 327 $a6.1 Hierarchical Games for Small Cell Networks 330 $aWritten by experts in the field, this book is based on recent research findings in dynamic spectrum access for cognitive radio networks. It establishes a game-theoretic framework and presents cutting-edge technologies for distributed interference coordination. With game-theoretic formulation and the designed distributed learning algorithms, it provides insights into the interactions between multiple decision-makers and the converging stable states. Researchers, scientists and engineers in the field of cognitive radio networks will benefit from the book, which provides valuable information, useful methods and practical algorithms for use in emerging 5G wireless communication. 410 0$aSpringerBriefs in Electrical and Computer Engineering,$x2191-8112 606 $aElectrical engineering 606 $aComputer organization 606 $aInformation theory 606 $aMicrowaves 606 $aOptical engineering 606 $aCommunications Engineering, Networks$3https://scigraph.springernature.com/ontologies/product-market-codes/T24035 606 $aComputer Systems Organization and Communication Networks$3https://scigraph.springernature.com/ontologies/product-market-codes/I13006 606 $aInformation and Communication, Circuits$3https://scigraph.springernature.com/ontologies/product-market-codes/M13038 606 $aMicrowaves, RF and Optical Engineering$3https://scigraph.springernature.com/ontologies/product-market-codes/T24019 615 0$aElectrical engineering. 615 0$aComputer organization. 615 0$aInformation theory. 615 0$aMicrowaves. 615 0$aOptical engineering. 615 14$aCommunications Engineering, Networks. 615 24$aComputer Systems Organization and Communication Networks. 615 24$aInformation and Communication, Circuits. 615 24$aMicrowaves, RF and Optical Engineering. 676 $a621.38215 700 $aXu$b Yuhua$4aut$4http://id.loc.gov/vocabulary/relators/aut$0762253 702 $aAlagan$b Anpalagan$4aut$4http://id.loc.gov/vocabulary/relators/aut 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910254194403321 996 $aGame-theoretic Interference Coordination Approaches for Dynamic Spectrum Access$92514058 997 $aUNINA