With the rapid growth of new wireless devices and applications over the past decade, the demand for wireless radio spectrum is increasing relentlessly. The development of cognitive radio networking provides a framework for making the best possible use of limited spectrum resources, and it is revolutionising the telecommunications industry. This book presents the fundamentals of designing, implementing, and deploying cognitive radio communication and networking systems. Uniquely, it focuses on game theory and its applications to various aspects of cognitive networking. It covers in detail the core aspects of cognitive radio, including cooperation, situational awareness, learning, and security mechanisms and strategies. In addition, it provides novel, state-of-the-art concepts and recent results. This is an ideal reference for researchers, students and professionals in industry who need to learn the applications of game theory to cognitive networking. Presenting the fundamentals of designing, implementing, and deploying cognitive radio networks, this book provides a unique focus on game theory and its applications. Cooperation, situational awareness, learning, and security are all covered in detail, in addition to novel, state-of-the-art concepts and recent results.
Author(s): K. J. Ray Liu, Beibei Wang
Edition: 1
Publisher: Cambridge University Press
Year: 2010
Language: English
Pages: 619
Cover......Page 1
Half-title......Page 3
Title......Page 5
Copyright......Page 6
Dedication......Page 7
Contents......Page 9
Preface......Page 15
Part I Cognitive radio communications and cooperation......Page 19
1.1 Introduction......Page 21
1.2.1 Cognitive radio characteristics......Page 23
1.2.2 Cognitive radio functions......Page 24
1.2.3 Network architecture and applications......Page 25
1.3.1 Interference temperature......Page 27
1.3.2 Spectrum sensing......Page 30
1.3.2.1 Energy detector......Page 31
1.3.2.2 Feature detectors......Page 33
1.3.2.3 Matched filtering and coherent detection......Page 35
1.3.2.4 Other techniques......Page 37
1.3.3 Cooperative sensing......Page 38
1.3.3.1 User selection......Page 39
1.3.3.2 Decision fusion......Page 40
1.3.3.4 Interference diversity......Page 41
1.4 Dynamic spectrum allocation and sharing......Page 42
1.4.1 Medium-access control in CR networks......Page 44
1.4.2 Spectrum handoff......Page 46
1.4.3 Cognitive relaying......Page 48
1.4.4 Spectrum sensing and access......Page 49
1.4.5 Power control in CR networks......Page 50
1.4.6 Control-channel management......Page 51
1.4.8 Spectrum sharing games......Page 52
1.4.9 Routing in CR networks......Page 54
1.5 Cognitive radio platforms......Page 57
1.5.2 The Center for Wireless Telecommunications at Virginia Tech......Page 58
1.5.3 WINLAB at Rutgers University......Page 59
1.5.4 Others......Page 60
1.5.5 Industry......Page 62
1.5.6 Standards......Page 63
2.1 Introduction......Page 64
2.2 Non-cooperative games and Nash equilibrium......Page 67
2.2.1 Nash equilibrium......Page 68
2.2.2 Uniqueness of equilibrium......Page 70
2.2.2.1 Potential games......Page 71
2.2.2.2 Standard functions......Page 73
2.2.3.1 Pareto optimality......Page 74
2.2.3.2 Equilibrium refinement......Page 75
2.2.3.3 Evolutionary equilibrium......Page 77
2.2.4.1 Pricing......Page 78
2.2.4.2 Repeated-game and folk theorems......Page 80
2.2.4.3 Correlated equilibrium......Page 83
2.3 Economic games, auction games, and mechanism design......Page 85
2.3.1 Oligopolistic competition......Page 86
2.3.2 Auction games......Page 91
2.3.3 Mechanism design......Page 94
2.4 Cooperative games......Page 95
2.4.1 Bargaining games......Page 96
2.4.2 Coalitional games......Page 98
2.5 Stochastic games......Page 101
2.6 Summary......Page 104
3.1 Introduction......Page 105
3.2 The system model......Page 106
3.3.1.1 CTMC without queuing......Page 109
3.3.1.2 Multiuser CTMC without queuing......Page 111
3.3.2.1 CTMC with queuing......Page 113
3.4 Primary-prioritized dynamic spectrum access......Page 115
3.5 Simulation results and analysis......Page 120
3.5.1 CTMC-8 for the symmetric-interference case......Page 121
3.5.2 CTMC-8 for the asymmetric-interference case......Page 123
3.5.3 Comparison with a CSMA-based scheme......Page 125
3.5.5 Spectrum sharing among multiple secondary users......Page 126
3.6 Summary and bibliographical notes......Page 127
4.1 Introduction......Page 129
4.2 The system model......Page 130
4.3.1 The one-shot game......Page 131
4.3.2 The repeated game......Page 133
4.4 Cooperation with optimal detection......Page 136
4.4.1 Cooperation criteria......Page 137
4.4.2 Optimal detection......Page 139
4.5 Cheat-proof strategies......Page 140
4.5.1 Mechanism-design-based strategy......Page 141
4.5.2 Statistics-based strategy......Page 144
4.6 Simulation results......Page 145
4.7 Summary and bibliographical notes......Page 150
5.1 Introduction......Page 151
5.2 The system model......Page 152
5.3.1 Game settings for dynamic spectrum allocation......Page 153
5.3.2 Static pricing games and competitive equilibrium......Page 154
5.3.3 Multi-stage dynamic pricing games for spectrum allocation......Page 156
5.4.1 User collusion in auction-based spectrum allocation......Page 157
5.4.2 MSOP and OSMP scenarios......Page 159
5.4.3 MSMP scenarios......Page 163
5.4.4 Performance lower bounds for MSMP scenarios......Page 166
5.4.5 Dynamic pricing with budget constraints......Page 167
5.5 Simulation results......Page 169
5.6 Summary and bibliographical notes......Page 172
6.1 Introduction......Page 173
6.2 The system model......Page 175
6.3.1 The optimal allocation......Page 178
6.3.2 Collusion-resistant pricing strategies......Page 179
6.3.3 Interference matrix disclosure......Page 181
6.3.4 Complexity issues......Page 183
6.3.5 The physical interference model......Page 185
6.4.1 Multi-band auction mechanisms......Page 186
6.4.2 The SDP relaxation for the multi-band auction......Page 187
6.5 Simulation results......Page 189
6.6 Summary......Page 194
7.1 Introduction......Page 195
7.2.1 The hypothesis of channel sensing......Page 197
7.2.2 The throughput of a secondary user......Page 198
7.2.3 Spectrum sensing games......Page 199
7.3.2 Evolution dynamics of the sensing game......Page 202
7.3.3 Analysis of sensing games with homogeneous players......Page 204
7.3.4.1 Two-player games......Page 208
7.3.5 A learning algorithm for the ESS......Page 210
7.4.1 A sensing game with homogeneous players......Page 212
7.4.3 Comparison of ESS and full cooperation......Page 214
7.5 Summary and bibliographical notes......Page 217
8.1 Introduction......Page 218
8.2.2 Anti-jamming defense in cognitive radio networks......Page 220
8.3.1 States and actions......Page 223
8.3.2 State transitions and stage payoff......Page 226
8.4 Solving optimal policies of the stochastic game......Page 229
8.5 Simulation results......Page 233
8.5.1.1 Anti-jamming defense in one licensed band......Page 234
8.5.1.2 Anti-jamming defense in two licensed bands......Page 238
8.5.2 Comparison of different strategies......Page 239
8.6 Summary and bibliographical notes......Page 243
9.1 Introduction......Page 244
9.2 Network and channel models......Page 246
9.2.1 The channel model......Page 247
9.2.2 The queuing model......Page 248
9.3.1 The cooperation protocol......Page 249
9.3.2 Maximum stable throughput analysis......Page 250
9.3.3 Relay selection......Page 252
9.3.3.2 Maximum success probability......Page 253
9.3.4 Numerical results......Page 254
9.4 Opportunistic multiple access for secondary nodes......Page 255
9.4.1.1 Case I: maximum interference......Page 256
9.4.1.3 Numerical results......Page 259
9.4.2 Secondary nodes with relaying capability......Page 261
9.5 Summary and bibliographical notes......Page 263
Part II Resource awareness and learning......Page 265
10.1 Introduction......Page 267
10.2 The Markov decision process and dynamic programming......Page 269
10.3 Reinforcement learning......Page 270
10.4.1 Reward functions......Page 272
10.4.3 The optimal dynamic programming solution......Page 274
10.4.3.1 The finite-state Markov channel (FSMC)......Page 275
10.4.3.2 Construction of the state-transition probability......Page 276
10.4.4 Numerical results......Page 277
10.5 Multi-node energy-aware optimization......Page 280
10.5.1 The channel model for multi-node communication and problem formulation......Page 281
10.5.3 Simulation results: multi-node scenarios......Page 282
10.6 Discussion......Page 284
10.7 Summary and bibliographical notes......Page 286
11.1 Introduction......Page 288
11.2 The system model and design challenge......Page 289
11.3.1 Design of punishment scheme under perfect observability......Page 293
11.3.2 The design of a punishment scheme under imperfect local observability......Page 298
11.4.1 Self-learning under perfect observability......Page 303
11.4.2.1 Learning through flooding......Page 304
11.4.2.2 Learning with utility prediction......Page 305
11.5 Simulation results......Page 308
11.6 Summary and bibliographical notes......Page 314
12.1 Introduction......Page 315
12.2 The system model......Page 317
12.3 Pricing game models......Page 320
12.3.1 The static pricing game......Page 321
12.3.2 The dynamic pricing game......Page 322
12.4.1 The optimal auction for static pricing-based routing......Page 324
12.4.2 The optimal dynamic auction for dynamic pricing-based routing......Page 325
12.4.3 Mechanism design......Page 330
12.4.4 Profit sharing among the nodes on a selected route......Page 331
12.5 Simulation studies......Page 335
12.6 Summary and bibliographical notes......Page 341
13.1 Introduction......Page 343
13.2.2 Definitions of network lifetime......Page 345
13.2.3 Problem formulation......Page 346
13.3.1 Eigenvalues of a Laplacian matrix......Page 347
13.3.2 The Fiedler value and vector......Page 348
13.4 Keep-connect algorithms......Page 349
13.4.1 Routing algorithms......Page 350
13.4.2 Minimum total energy while keeping connectivity (MTEKC) routing......Page 352
13.5 The upper bound on the energy consumption......Page 353
13.6 The distributed implementation and learning algorithm......Page 358
13.6.1 Improvement on the distributed algorithm......Page 359
13.7 Simulation results......Page 360
13.8 Summary......Page 367
14.1 Introduction......Page 368
14.2 The system model......Page 370
14.3.1 The SDP-based network maintenance algorithm......Page 373
14.4 Lifetime-maximization strategies......Page 375
14.4.1 The weighted minimum-power routing (WMPR) algorithm......Page 376
14.4.2 An adaptive network maintenance algorithm......Page 377
14.5 Network repair......Page 378
14.6 Simulation results......Page 379
14.6.1 Interference-based transmission scenario......Page 382
14.6.2 Network repair......Page 385
14.7 Summary and bibliographical notes......Page 386
Part III Securing mechanism and strategies......Page 389
15.1 Introduction......Page 391
15.2.1 Trust concepts in social networks and computer networks......Page 393
15.2.2 Notation of trust......Page 394
15.2.4 Trust metrics......Page 395
15.2.5 Fundamental axioms of trust......Page 396
15.2.6.2 The probability-based model......Page 398
15.3.1 Bad-mouthing attacks......Page 401
15.3.2 On–off attack......Page 402
15.3.3 Conflicting-behavior attack......Page 404
15.3.4 Sybil attacks and newcomer attacks......Page 405
15.4.1 Design of trust-management systems......Page 406
15.4.2.1 Obtaining trust recommendations......Page 407
15.4.2.2 Trust-record maintenance and updating......Page 408
15.5 Simulations......Page 409
15.5.1 Effects of trust management......Page 410
15.5.2 Bad-mouthing attack......Page 411
15.5.3 On–off attack......Page 412
15.5.4 Conflicting-behavior attack......Page 413
15.6 Summary and bibliographical notes......Page 415
16.1 Introduction and background......Page 417
16.2.2 Dynamic source routing......Page 419
16.2.4 Security and key-setup assumptions......Page 420
16.3.1 Route-traffic observers......Page 421
16.3.2 Cheating records and honesty scores......Page 423
16.3.4 Route diversity......Page 424
16.3.6 Implementation of HADOF......Page 425
16.4 Security analysis......Page 426
16.5.1 Simulator and simulation parameters......Page 428
16.6 Performance evaluation......Page 430
16.6.1.2 Gray-hole plus frame-up attacks......Page 431
16.6.1.3 The effectiveness of friendship......Page 433
16.6.2 Overhead comparisons......Page 434
16.7 Summary and bibliographical notes......Page 435
17.1 Introduction......Page 438
17.2 Traffic-injection attacks......Page 439
17.3 Defense mechanisms......Page 441
17.3.1 Route discovery and packet delivery......Page 442
17.3.2 Traffic monitoring......Page 443
17.3.3 Detection of traffic-injection attacks......Page 444
17.3.4 Overhead analysis......Page 445
17.4 Theoretical analysis......Page 446
17.5 Centralized detection with decentralized implementation......Page 455
17.6 Simulation studies......Page 457
17.7 Summary and bibliographical notes......Page 461
18.1 Introduction......Page 462
18.2 The system model and problem formulation......Page 463
18.3.1 The cooperation degree......Page 466
18.3.2 Route selection......Page 467
18.3.3.1 Forwarding the data packet......Page 469
18.3.3.2 Submitting receipts......Page 470
18.3.4 Updating records......Page 471
18.3.6 Resolving inconsistent record updates......Page 473
18.3.7 Parameter selection......Page 474
18.4.1 Packet-dropping attacks......Page 475
18.4.2 Attacks emulating link breakage......Page 476
18.4.4 Collusion attacks......Page 477
18.5.1 The simulation configuration......Page 478
18.5.2 Simulation results......Page 480
18.6 Summary and bibliographical notes......Page 484
19.1 Introduction......Page 486
19.2.1 The game model......Page 487
19.2.2 Nash-equilibrium refinements......Page 489
19.2.3 Optimal and cheat-proof packet-forwarding strategies......Page 493
19.3 System description and the game model......Page 495
19.4 Attack-resistant and cheat-proof cooperation-stimulation strategies......Page 497
19.5 Strategy analysis under no attacks......Page 501
19.6 Strategy analysis under attacks......Page 503
19.7 Discussion......Page 505
19.8.1 Simulation studies with different credit lines......Page 507
19.8.2 Simulation studies under different networks......Page 509
19.8.3 Simulation studies under attacks......Page 510
19.9 Summary......Page 513
20.1 Introduction......Page 514
20.2.1 System model......Page 515
20.2.2 The static and repeated packet-forwarding game model......Page 516
20.3 Vulnerability analysis......Page 518
20.4.1 Two-player belief-based packet forwarding......Page 520
20.4.2 Efficiency analysis......Page 522
20.4.3.1 The multi-node multi-hop game model......Page 527
20.4.3.2 The design of the belief-evaluation system......Page 528
20.5 Simulation studies......Page 530
20.6 Summary and bibliographical notes......Page 535
21.1 Introduction......Page 537
21.2.1 System description......Page 538
21.2.2 The game model......Page 539
21.3 Defense strategies with statistical attacker detection......Page 543
21.3.1 Statistical detection of packet-dropping attacks......Page 545
21.3.2 Statistical detection of traffic-injection attacks......Page 546
21.3.3 A secure-routing and packet-forwarding strategy......Page 547
21.3.4 Attacking strategy......Page 548
21.4 Optimality analysis......Page 551
21.5 Performance evaluation......Page 556
21.6 Summary......Page 562
22.1 Introduction......Page 563
22.2.1 System description and design challenges......Page 564
22.2.2 The multi-stage secure-routing and packet-forwarding game......Page 567
22.3.1 Statistical detection of packet-dropping attacks......Page 569
22.3.2.1 The route-participation stage......Page 570
22.3.2.2 The route-selection stage......Page 571
22.3.2.3 The packet-forwarding stage......Page 572
22.4.1 Strategy analysis under no attacks......Page 573
22.4.2 Attacking strategy and damage analysis......Page 574
22.5 Simulation studies......Page 575
22.5.1 Mobile ad hoc networks vs. static ad hoc networks......Page 576
22.5.3 The effect of a negative cooperation level......Page 578
22.5.4 The effect of cooperation level on cooperation stimulation......Page 579
22.5.5 The effect of inhomogeneous request rates......Page 580
22.5.6 Effects of different types of packet-dropping attack......Page 582
22.5.7 The effect of the number of attackers......Page 583
22.5.8 Cooperation level vs. damage......Page 584
22.6 Discussion......Page 585
22.7 Summary and bibliographical notes......Page 587
References......Page 588
Index......Page 616
