Table of Contents
Preface ix Acknowledgments xi
1 Introduction 1
1.1 Perception 3
1.2 Aware, Adaptive, or Cognitive? 5
1.3 Adaptation 8
1.4 Cognition 10
1.5 Cognitive Radio and Public Policy 15
1.6 Are We There Yet? 16
1.7 Key Questions 18
1.8 Organization of the Text 19
1.9 Exercises 20
I Foundations
2 Technical Overview 25
2.1 The iCR Has Seven Capabilities 25
2.2 Sensing and Perception: What and Whom to Perceive 27
2.3 Ideal Cognitive Radio (iCR) Platform Evolution 41
2.4 The serModel of Machine Learning for iCR 47
2.5 Architecture 51
2.6 Synoptic iCR Functional Definition 56
2.7 Exercises 56
3 Evolving From Aware and Adaptive to Cognitive Radio 58
3.1 Revolution or Evolution? 58
3.2 Moving Day 59
3.3 Developing AML for Genie 62
3.4 Learning Etiquette 73
3.5 Value Proposition for AML in AACR 75
3.6 Exercises 79
4 Autonomous Machine Learning for AACR 80
4.1 Machine Learning Framework 80
4.2 Histogram as a Discovery Algorithm 85
4.3 User-Domain Learning 88
4.4 Radio-Domain Learning 97
4.5 Reinforcement, Extension, and Constraint Discovery 108
4.6 Learning Strategies 118
4.7 Exercises 121
5 Cognitive Radio Architecture 123
5.1 CRA I: Functions, Components, and Design Rules 124
5.2 CRA II: The Cognition Cycle 134
5.3 CRA III: The Inference Hierarchy 138
5.4 CRA IV: Architecture Maps 143
5.5 CRA V: Building the CRA on SDR Architectures 144
5.6 Cognition Architecture Research Topics 152
5.7 Exercises 152
II Radio-Domain Competence
6 Radio-Domain Use Cases 157
6.1 Radio Use-Case Metrics 157
6.2 FCC Unused TV Spectrum Use Case 163
6.3 Demand Shaping Use Case 170
6.4 Military Market Segment Use Cases 176
6.5 RF Knowledge That Saves Lives 177
6.6 Prognostication 180
6.7 Exercises 180
7 Radio Knowledge 183
7.1 Radio-Domain Overview 183
7.2 Knowledge of the HF Radio Band 195
7.3 Knowledge of the LVHF Radio Band 208
7.4 Radio Noise and Interference 224
7.5 Knowledge of the VHF Radio Band 228
7.6 Knowledge of the UHF Radio Band 237
7.7 Knowledge of the SHF Radio Band 246
7.8 Knowledge of EHF, Terahertz, and Free Space Optics 256
7.9 Satellite Communications Knowledge 260
7.10 Cross-Band/Mode Knowledge 267
8 Implementing Radio-Domain Skills 275
8.1 Cognitive Radio Architecture Structures Radio Skills 276
8.2 Embedded Databases Enable Skills 281
8.3 Production Systems Enable Skills 288
8.4 Embedded Inference Enables Skills 291
8.5 Radio Knowledge Objects (RKOs) 296
8.6 Evolving Skills Via RKO and RDH 303
8.7 Implementing Spatial Skills 305
8.8 Generalized 318
8.9 Microworlds 323
8.10 Radio Skills Conclusions 325
8.11 Exercises 326
III User-Domain Competence
9 User-Domain Use Cases 331
9.1 Emergency Companion Use Case 331
9.2 Office Assistant Use Case 333
9.3 Cognitive Assistants for Wireless 334
9.4 User Skill Enhancements 343
9.5 Exercises 346
10 User-Domain Knowledge 347
10.1 Users’ Natural Language Expression 348
10.2 Acoustic Sensory Perception 352
10.3 Visual Sensory Perception 359
10.4 Audio-Visual Integration 363
10.5 Lexical Conceptual Semantics (LCS) 366
10.6 Other Sensors 369
10.7 Architecture Implications 369
10.8 Exercises 369
11 Implementing User-Domain Skills 372
11.1 Integrating Cognition 373
11.2 Autonomous Extensibility 382
11.3 Supervised Extensibility 401
11.4 Uncertainty 407
11.5 Learning Requires Grounding 417
11.6 Sleep Cycles 423
11.7 Pitfalls and Opportunities 424
11.8 Exercises 426
12 Semantic Radio 428
12.1 CYC, eBusiness Solutions, and the Semantic Web 428
12.2 CYC Case Study 429
12.3 CYC Implications 437
12.4 Web Languages 439
12.5 Radio XML 439
12.6 Conclusions 443
Glossary 444
References 451
Index 467
