Dynamic Spectrum Access and Management in Cognitive Radio Networks

Cover......Page 1
Half-title......Page 3
Title......Page 5
Copyright......Page 6
Contents......Page 7
Preface......Page 15
Part I Introduction......Page 19
1 Wireless communications systems......Page 21
1.1.2 Spectrum management......Page 22
1.2 Wireless protocols......Page 24
1.3.1 Radio propagation......Page 27
Large-scale channel model......Page 29
Small-scale channel model and fading......Page 31
Integrating large-scale fading with small-scale fading......Page 34
Bluetooth......Page 37
1.4.2 Wireless LAN technologies......Page 38
Evolution of cellular wireless technology......Page 39
CDMA-based cellular wireless technologies......Page 40
1.4.4 Wireless MAN technologies......Page 41
1.4.5 Wireless RAN technology......Page 42
1.5.2 MIMO technology......Page 43
1.5.4 Ultra-wideband technology......Page 44
1.6 Multihop wireless networking......Page 45
1.6.1 Wireless sensor networks......Page 46
1.6.3 Wireless mesh networks......Page 47
1.7.1 Admission control......Page 48
1.7.2 Queue management......Page 50
1.7.4 Medium access control (MAC)......Page 51
1.7.6 Power control......Page 52
1.8 Next generation heterogeneous wireless access networks and cognitive radio......Page 53
1.9 Summary......Page 56
2 Introduction to cognitive radio......Page 57
2.1 Software-defined radio......Page 59
2.2.1 Cognitive radio architecture......Page 61
2.2.2 Functions of cognitive radio......Page 62
2.2.3 Dynamic spectrum access......Page 63
2.2.4 Components of cognitive radio......Page 64
2.2.5 Interference temperature......Page 65
Ideal interference temperature model......Page 66
Capacity under interference temperature......Page 67
Non-cooperative transmitter sensing......Page 68
Cooperative sensing......Page 69
2.2.7 Spectrum analysis and spectrum decision......Page 70
2.2.8 Potential applications of cognitive radio......Page 72
2.3.1 Issues in spectrum sensing......Page 73
Spectrum sensing in multichannel networks......Page 74
Issues in the spectrum access decision......Page 75
2.3.3 Spectrum mobility issues......Page 76
2.3.4 Network layer and transport layer issues......Page 77
2.3.5 Cross-layer design for cognitive radio networks......Page 78
2.3.6 Artificial intelligence approach for designing cognitive radio......Page 81
2.3.7 Location-aware cognitive radio......Page 82
2.4 Cognitive radio architectures for NeXt Generation (XG) networks......Page 84
2.5.1 IEEE SCC 41......Page 85
2.5.2 IEEE 802.22 for wireless regional area networks (WRANs)......Page 87
Physical layer in 802.22......Page 88
MAC layer in 802.22......Page 89
Channel sensing in IEEE 802.22......Page 90
2.6 Summary......Page 91
Part II Techniques for design, analysis, and optimization of dynamic spectrum access and management......Page 93
3 Signal processing techniques......Page 95
3.1.1 Interference temperature/channel estimation......Page 96
Maximum likelihood estimator......Page 97
Maximum a posteriori (MAP)/Bayesian estimator......Page 98
Periodogram estimator......Page 99
Subspace estimator......Page 100
Cramer–Rao lower bound......Page 101
3.1.2 Detection of spectrum holes......Page 103
3.1.3 Practical spectrum sensing approaches......Page 106
3.2 Collaborative sensing......Page 108
3.3 Replacement of sensing devices in secondary users......Page 109
3.3.1 New cognitive cycle with separate sensing devices......Page 110
3.4 Filtering and prediction......Page 113
3.4.1 AR, MA, and the ARMA model......Page 114
3.4.2 Wiener filter......Page 115
3.4.3 LMS filter......Page 117
3.4.4 RLS filter......Page 119
3.4.5 Kalman filter......Page 122
3.5.1 Basic technology......Page 124
3.5.2 Applications......Page 126
3.6 Summary......Page 127
4.1 Constrained optimization......Page 128
4.1.1 Basic definition......Page 129
4.1.2 Lagrangian method......Page 131
4.1.3 Optimality......Page 133
4.1.4 Primal-dual algorithm......Page 136
4.2 Linear programming and the simplex algorithm......Page 137
4.3.1 Quadratic, geometric, and semi-definite programming......Page 140
4.3.2 Gradient method, Newton method, and their variations......Page 142
4.4 Non-linear programming......Page 145
4.4.1 Barrier/interior-point method......Page 146
4.4.2 Monte Carlo method......Page 147
4.4.3 Simulated annealing......Page 148
4.5 Integer programming......Page 149
4.5.1 General formulation......Page 150
Network, routing, and graph problems......Page 151
Assignment problem......Page 152
4.5.2 Knapsack problem......Page 153
4.5.3 Relaxation and decomposition......Page 156
4.5.4 Enumeration technique: branch-and-bound......Page 157
4.5.5 Cutting plane algorithms based on polyhedral combinatorics......Page 160
4.6.1 General definition of dynamic programming......Page 162
4.6.2 Markov decision process......Page 164
4.6.3 Examples in wireless networks......Page 166
4.7 Stochastic programming......Page 167
4.7.1 Problem definition......Page 168
4.7.2 Recourse......Page 170
4.8 Summary......Page 171
5 Game theory......Page 173
5.1 Basics of game theory......Page 174
5.2 Non-cooperative static game......Page 177
5.2.1 Normal form of static game......Page 178
5.2.2 Nash equilibrium, Pareto optimality, and mixed strategy......Page 179
5.2.3 Social optimum: price of anarchy and referee-based game......Page 181
5.3 Dynamic/repeated game......Page 182
5.3.1 Sequential game and extensive form......Page 183
5.3.2 Tit-for-tat and trigger-price strategy......Page 185
5.3.3 Stochastic game......Page 187
5.4.1 Solution of bargaining games......Page 188
5.4.2 Applications of bargaining games......Page 190
5.5.1 Characteristic function and core......Page 192
5.5.2 Fairness......Page 193
5.5.3 Merge/split algorithm......Page 195
5.6 Game with imperfect information......Page 196
5.6.1 Bayesian game in normal form......Page 197
5.6.2 Bayesian game in extensive form......Page 199
5.7.1 Zero-sum game......Page 201
5.7.2 Potential game......Page 203
5.7.3 Super-modular game......Page 204
5.7.4 Correlated equilibrium......Page 206
5.8 Summary......Page 207
6.1 Machine learning......Page 209
6.1.1 Supervised learning......Page 210
Regression technique......Page 211
Classification technique......Page 212
Neural network......Page 213
6.1.2 Unsupervised learning......Page 215
6.2 Reinforcement learning models and algorithms......Page 216
6.2.1 Value function......Page 218
6.2.2 Dynamic programming......Page 219
6.2.3 Monte Carlo methods......Page 221
6.2.4 Temporal-difference learning......Page 222
6.2.5 Learning in games......Page 223
Q-learning and game......Page 224
6.3.1 Neural network and cognitive radio......Page 226
6.3.2 Q-learning and dynamic channel assignment......Page 227
6.3.3 Q-learning and pricing in cognitive radio......Page 228
6.3.4 Radio environment map and learning algorithms......Page 229
6.4 Genetic algorithms......Page 231
6.5.1 Fuzzy set......Page 234
6.5.4 Fuzzy logic control......Page 235
Network access selection......Page 236
Transmit power control......Page 237
6.6 Summary......Page 238
Part III Dynamic spectrum access and management......Page 239
7.1 Spectrum access models......Page 241
7.1.1 Exclusive-use model......Page 242
Dynamic exclusive-use model......Page 243
Spectrum overlay......Page 244
Uncontrolled-commons sub-model......Page 245
Private-commons sub-model......Page 246
7.2.1 Infrastructure-based versus infrastructureless cognitive radio network......Page 247
7.2.2 Centralized versus distributed dynamic spectrum access......Page 248
7.2.3 Inter- and intra-RAN dynamic spectrum allocation......Page 249
7.3 Spectrum sensing......Page 250
7.3.1 Design tradeoff in spectrum sensing......Page 253
7.3.2 Cooperative centralized spectrum sensing......Page 255
7.3.3 Cooperative distributed spectrum sensing......Page 256
Sensor network to detect passive licensed users......Page 257
7.3.5 Spectrum sensing and prediction......Page 258
Bluetooth......Page 260
7.4 Medium access control for dynamic spectrum access......Page 261
Optimization of joint spectrum sensing and spectrum access......Page 263
Optimal sensing for hardware-constrained cognitive radio......Page 264
Optimal discovery of spectrum opportunities......Page 265
Learning-based optimal channel selection......Page 267
7.4.2 Multichannel and multiuser MAC......Page 268
Ad hoc secondary-system MAC (AS-MAC) for spectrum sharing......Page 269
Slotted-beaconing period and rendezvous channel......Page 270
MAC protocol for cluster-based cognitive radio networks and CogMesh......Page 271
Dynamic open spectrum sharing (DOSS) protocol......Page 273
Multichannel MAC protocol with collaborative channel sensing......Page 274
Dynamic frequency hopping MAC for IEEE 802.22......Page 275
Cognitive radio MAC with rate and power adaptation......Page 277
Statistical channel allocation MAC (SCA-MAC) for cognitive radio......Page 278
Enhancements to the IEEE 802.22 air interface and MAC protocol......Page 279
MAC-layer scheduling in cognitive radio networks......Page 281
Rental protocol for dynamic channel allocation......Page 282
Centralized cognitive MAC protocol for coordinated spectrum access......Page 283
Queueing analysis......Page 284
Latency analysis......Page 285
Blocking analysis......Page 287
Throughput analysis......Page 288
7.5 Open issues in dynamic spectrum access......Page 290
7.6 Summary......Page 291
8.2.1 Quality of service (QoS)-constrained dynamic spectrum access......Page 292
8.2.2 Primary-prioritized dynamic spectrum access......Page 294
8.2.3 Dynamic control of open spectrum management......Page 296
8.2.4 Joint admission control and power allocation for dynamic spectrum access......Page 298
8.2.5 Power and rate control for dynamic spectrum access......Page 299
8.2.6 Coordinated dynamic spectrum access in cellular networks......Page 301
8.2.7 Collaboration and fairness in spectrum allocation......Page 303
8.2.8 Spatio-temporal dynamic spectrum allocation......Page 304
8.2.9 Dynamic spectrum allocation among network service providers......Page 306
8.2.10 Coordinated dynamic spectrum access......Page 307
8.2.11 Cooperative game for dynamic spectrum access......Page 309
8.2.12 Transmission scheduling via spectrum server......Page 310
8.2.13 Spectrum sensing and access scheduling......Page 312
8.2.14 Joint spectrum allocation and routing......Page 314
8.3 Auction-based approach......Page 315
8.3.1 General framework of spectrum auction......Page 316
8.3.2 Multibid auction for dynamic spectrum allocation......Page 318
8.3.3 Dynamic spectrum allocator knapsack auction......Page 319
8.3.4 Weighted proportional fair spectrum allocation......Page 320
8.3.5 Bilateral bargain in spectrum access......Page 321
8.4 Summary......Page 323
9 Distributed dynamic spectrum access: cooperative and non-cooperative approaches......Page 324
9.1.1 Power and admission control of cognitive radio with antenna arrays......Page 326
9.1.2 Genetic algorithm to optimize distributed dynamic spectrum access......Page 330
9.1.3 Distributed spectrum sharing based on cooperative game......Page 331
9.1.4 Optimal channel sensing and allocation in cognitive radio mesh network......Page 333
9.1.5 Cooperative spectrum sharing using repeated game......Page 336
9.1.6 Cooperative strategy for distributed spectrum sharing......Page 338
9.2.1 Decentralized channel selection for QoS-sensitive cognitive radio networks......Page 340
9.2.2 Joint distributed power control and channel selection in CDMA cognitive radio networks......Page 341
9.2.3 Random access and interference channel in cognitive radio networks......Page 343
9.2.4 Dynamic channel selection in multihop networks......Page 346
9.2.5 Genetic algorithm-based competitive power allocation for dynamic spectrum access......Page 347
9.2.6 Cognitive medium access and coexistence with WLAN......Page 349
9.2.7 Time domain spectrum allocation......Page 353
9.3 Summary......Page 355
10.1.1 Distributed resource management in multihop cognitive radio networks......Page 356
10.1.2 Opportunistic channel selection based on the fuzzy learning algorithm......Page 359
10.1.3 Distributed dynamic spectrum access based on no-regret learning......Page 362
10.1.4 Agent-based dynamic spectrum access......Page 364
10.1.5 Biologically inspired dynamic spectrum access......Page 367
10.1.6 Secondary spectrum access......Page 369
10.1.7 Distributed rule-regulated spectrum sharing......Page 372
10.1.8 Game theory-based spectrum etiquette......Page 374
10.1.9 Opportunistic channel selection in cooperative mobility networks......Page 377
10.2.1 Channel evacuation protocol......Page 378
10.2.2 Distributed channel management in uncoordinated wireless environment......Page 380
10.2.3 Spectrum-aware on-demand routing protocol......Page 383
10.2.4 Optimization of the transmission period......Page 384
10.3 Summary......Page 386
11.1 Introduction to spectrum trading......Page 387
11.1.1 Classification and taxonomy of spectrum trading......Page 391
11.1.2 Radio resource pricing......Page 393
11.1.3 Authentication, authorization, and accounting in spectrum trading......Page 394
Utility and preference......Page 396
Application of utility in wireless networks......Page 398
Transmission rate......Page 399
Connection blocking probability......Page 400
Application-related utility......Page 401
Subjective survey of utility......Page 402
11.2.2 Market-equilibrium......Page 403
11.2.3 Oligopoly market......Page 404
Cournot model......Page 405
Bertrand game......Page 407
Stackelberg model......Page 409
11.2.4 Auction theory......Page 411
Single-side auction......Page 412
Double auction......Page 413
11.3.1 Double auction-based pricing for dynamic spectrum access......Page 415
11.3.2 Sequential and concurrent auction for dynamic spectrum access......Page 416
11.3.3 Dynamic spectrum allocation via spectrum server......Page 418
11.3.4 Techno-economic model for dynamic spectrum access......Page 420
11.3.5 Spectrum leasing through cooperation......Page 421
11.3.6 Improving the efficiency of spectrum access by using pricing......Page 423
11.3.7 Spectrum pricing competition based on Hotelling's model......Page 425
11.3.8 Pricing and admission control......Page 426
11.4 Summary......Page 427
12.1 Dynamic competitive spectrum sharing: Cournot model......Page 428
12.1.1 System model......Page 429
Static game......Page 430
12.1.3 Dynamic game model......Page 431
12.1.4 Performance evaluation results......Page 434
12.2 Bertrand competition, market-equilibrium pricing, and cooperative spectrum pricing......Page 436
12.2.1 System model and pricing schemes......Page 437
12.2.2 Utility and spectrum demand of secondary users......Page 439
12.2.4 Spectrum supply, spectrum demand, and market-equilibrium......Page 440
12.2.5 Non-cooperative game formulation for Bertrand competition......Page 441
12.2.6 Cooperative spectrum pricing based on optimization......Page 442
Distributed algorithm for Bertrand pricing competition......Page 443
Distributed algorithm for cooperative pricing......Page 444
12.2.8 Information exchange protocol......Page 445
12.2.9 Performance evaluation results......Page 446
12.3.1 Formulation of a repeated game......Page 448
12.3.2 Performance evaluation results......Page 450
12.4 Economic model for spectrum sharing in IEEE 802.22 WRANs......Page 451
12.4.1 System model for spectrum trading in IEEE 802.22 WRANs......Page 452
12.4.2 Selection of service providers......Page 453
12.4.3 Non-cooperative game formulation of joint spectrum bidding and service pricing......Page 455
12.4.4 Performance evaluation results......Page 456
12.6 Summary......Page 458
References......Page 460
Index......Page 502