Dr. JOSEPH MITOLA III is a Consulting Scientist with The MITRE Corporation. A pioneer in telecommunications, Dr. Mitola published the first paper on software radios in 1992 and continues to write and teach extensively on this technology. His current research interests center on enhancing the computational intelligence of software radios to develop cognitive radios.

• Preface ixAcknowledgments xi1 Introduction 11.1 Perception 31.2 Aware, Adaptive, or Cognitive? 51.3 Adaptation 81.4 Cognition 101.5 Cognitive Radio and Public Policy 151.6 Are We There Yet? 161.7 Key Questions 181.8 Organization of the Text 191.9 Exercises 20I Foundations2 Technical Overview 252.1 The iCR Has Seven Capabilities 252.2 Sensing and Perception: What and Whom to Perceive 272.3 Ideal Cognitive Radio (iCR) Platform Evolution 412.4 The serModel of Machine Learning for iCR 472.5 Architecture 512.6 Synoptic iCR Functional Definition 562.7 Exercises 563 Evolving From Aware and Adaptive to Cognitive Radio 583.1 Revolution or Evolution? 583.2 Moving Day 593.3 Developing AML for Genie 623.4 Learning Etiquette 733.5 Value Proposition for AML in AACR 753.6 Exercises 794 Autonomous Machine Learning for AACR 804.1 Machine Learning Framework 804.2 Histogram as a Discovery Algorithm 854.3 User-Domain Learning 884.4 Radio-Domain Learning 974.5 Reinforcement, Extension, and Constraint Discovery 1084.6 Learning Strategies 1184.7 Exercises 1215 Cognitive Radio Architecture 1235.1 CRA I: Functions, Components, and Design Rules 1245.2 CRA II: The Cognition Cycle 1345.3 CRA III: The Inference Hierarchy 1385.4 CRA IV: Architecture Maps 1435.5 CRA V: Building the CRA on SDR Architectures 1445.6 Cognition Architecture Research Topics 1525.7 Exercises 152II Radio-Domain Competence6 Radio-Domain Use Cases 1576.1 Radio Use-Case Metrics 1576.2 FCC Unused TV Spectrum Use Case 1636.3 Demand Shaping Use Case 1706.4 Military Market Segment Use Cases 1766.5 RF Knowledge That Saves Lives 1776.6 Prognostication 1806.7 Exercises 1807 Radio Knowledge 1837.1 Radio-Domain Overview 1837.2 Knowledge of the HF Radio Band 1957.3 Knowledge of the LVHF Radio Band 2087.4 Radio Noise and Interference 2247.5 Knowledge of the VHF Radio Band 2287.6 Knowledge of the UHF Radio Band 2377.7 Knowledge of the SHF Radio Band 2467.8 Knowledge of EHF, Terahertz, and Free Space Optics 2567.9 Satellite Communications Knowledge 2607.10 Cross-Band/Mode Knowledge 2678 Implementing Radio-Domain Skills 2758.1 Cognitive Radio Architecture Structures Radio Skills 2768.2 Embedded Databases Enable Skills 2818.3 Production Systems Enable Skills 2888.4 Embedded Inference Enables Skills 2918.5 Radio Knowledge Objects (RKOs) 2968.6 Evolving Skills Via RKO and RDH 3038.7 Implementing Spatial Skills 3058.8 Generalized 3188.9 Microworlds 3238.10 Radio Skills Conclusions 3258.11 Exercises 326III User-Domain Competence9 User-Domain Use Cases 3319.1 Emergency Companion Use Case 3319.2 Office Assistant Use Case 3339.3 Cognitive Assistants for Wireless 3349.4 User Skill Enhancements 3439.5 Exercises 34610 User-Domain Knowledge 34710.1 Users’ Natural Language Expression 34810.2 Acoustic Sensory Perception 35210.3 Visual Sensory Perception 35910.4 Audio-Visual Integration 36310.5 Lexical Conceptual Semantics (LCS) 36610.6 Other Sensors 36910.7 Architecture Implications 36910.8 Exercises 36911 Implementing User-Domain Skills 37211.1 Integrating Cognition 37311.2 Autonomous Extensibility 38211.3 Supervised Extensibility 40111.4 Uncertainty 40711.5 Learning Requires Grounding 41711.6 Sleep Cycles 42311.7 Pitfalls and Opportunities 42411.8 Exercises 42612 Semantic Radio 42812.1 CYC, eBusiness Solutions, and the Semantic Web 42812.2 CYC Case Study 42912.3 CYC Implications 43712.4 Web Languages 43912.5 Radio XML 43912.6 Conclusions 443Glossary 444References 451Index 467

Dr. JOSEPH MITOLA III is a Consulting Scientist with The MITRE Corporation. A pioneer in telecommunications, Dr. Mitola published the first paper on software radios in 1992 and continues to write and teach extensively on this technology. His current research interests center on enhancing the computational intelligence of software radios to develop cognitive radios.

• Preface ixAcknowledgments xi1 Introduction 11.1 Perception 31.2 Aware, Adaptive, or Cognitive? 51.3 Adaptation 81.4 Cognition 101.5 Cognitive Radio and Public Policy 151.6 Are We There Yet? 161.7 Key Questions 181.8 Organization of the Text 191.9 Exercises 20I Foundations2 Technical Overview 252.1 The iCR Has Seven Capabilities 252.2 Sensing and Perception: What and Whom to Perceive 272.3 Ideal Cognitive Radio (iCR) Platform Evolution 412.4 The serModel of Machine Learning for iCR 472.5 Architecture 512.6 Synoptic iCR Functional Definition 562.7 Exercises 563 Evolving From Aware and Adaptive to Cognitive Radio 583.1 Revolution or Evolution? 583.2 Moving Day 593.3 Developing AML for Genie 623.4 Learning Etiquette 733.5 Value Proposition for AML in AACR 753.6 Exercises 794 Autonomous Machine Learning for AACR 804.1 Machine Learning Framework 804.2 Histogram as a Discovery Algorithm 854.3 User-Domain Learning 884.4 Radio-Domain Learning 974.5 Reinforcement, Extension, and Constraint Discovery 1084.6 Learning Strategies 1184.7 Exercises 1215 Cognitive Radio Architecture 1235.1 CRA I: Functions, Components, and Design Rules 1245.2 CRA II: The Cognition Cycle 1345.3 CRA III: The Inference Hierarchy 1385.4 CRA IV: Architecture Maps 1435.5 CRA V: Building the CRA on SDR Architectures 1445.6 Cognition Architecture Research Topics 1525.7 Exercises 152II Radio-Domain Competence6 Radio-Domain Use Cases 1576.1 Radio Use-Case Metrics 1576.2 FCC Unused TV Spectrum Use Case 1636.3 Demand Shaping Use Case 1706.4 Military Market Segment Use Cases 1766.5 RF Knowledge That Saves Lives 1776.6 Prognostication 1806.7 Exercises 1807 Radio Knowledge 1837.1 Radio-Domain Overview 1837.2 Knowledge of the HF Radio Band 1957.3 Knowledge of the LVHF Radio Band 2087.4 Radio Noise and Interference 2247.5 Knowledge of the VHF Radio Band 2287.6 Knowledge of the UHF Radio Band 2377.7 Knowledge of the SHF Radio Band 2467.8 Knowledge of EHF, Terahertz, and Free Space Optics 2567.9 Satellite Communications Knowledge 2607.10 Cross-Band/Mode Knowledge 2678 Implementing Radio-Domain Skills 2758.1 Cognitive Radio Architecture Structures Radio Skills 2768.2 Embedded Databases Enable Skills 2818.3 Production Systems Enable Skills 2888.4 Embedded Inference Enables Skills 2918.5 Radio Knowledge Objects (RKOs) 2968.6 Evolving Skills Via RKO and RDH 3038.7 Implementing Spatial Skills 3058.8 Generalized 3188.9 Microworlds 3238.10 Radio Skills Conclusions 3258.11 Exercises 326III User-Domain Competence9 User-Domain Use Cases 3319.1 Emergency Companion Use Case 3319.2 Office Assistant Use Case 3339.3 Cognitive Assistants for Wireless 3349.4 User Skill Enhancements 3439.5 Exercises 34610 User-Domain Knowledge 34710.1 Users’ Natural Language Expression 34810.2 Acoustic Sensory Perception 35210.3 Visual Sensory Perception 35910.4 Audio-Visual Integration 36310.5 Lexical Conceptual Semantics (LCS) 36610.6 Other Sensors 36910.7 Architecture Implications 36910.8 Exercises 36911 Implementing User-Domain Skills 37211.1 Integrating Cognition 37311.2 Autonomous Extensibility 38211.3 Supervised Extensibility 40111.4 Uncertainty 40711.5 Learning Requires Grounding 41711.6 Sleep Cycles 42311.7 Pitfalls and Opportunities 42411.8 Exercises 42612 Semantic Radio 42812.1 CYC, eBusiness Solutions, and the Semantic Web 42812.2 CYC Case Study 42912.3 CYC Implications 43712.4 Web Languages 43912.5 Radio XML 43912.6 Conclusions 443Glossary 444References 451Index 467

Dr. JOSEPH MITOLA III is a Consulting Scientist with The MITRE Corporation. A pioneer in telecommunications, Dr. Mitola published the first paper on software radios in 1992 and continues to write and teach extensively on this technology. His current research interests center on enhancing the computational intelligence of software radios to develop cognitive radios.

• Preface ixAcknowledgments xi1 Introduction 11.1 Perception 31.2 Aware, Adaptive, or Cognitive? 51.3 Adaptation 81.4 Cognition 101.5 Cognitive Radio and Public Policy 151.6 Are We There Yet? 161.7 Key Questions 181.8 Organization of the Text 191.9 Exercises 20I Foundations2 Technical Overview 252.1 The iCR Has Seven Capabilities 252.2 Sensing and Perception: What and Whom to Perceive 272.3 Ideal Cognitive Radio (iCR) Platform Evolution 412.4 The serModel of Machine Learning for iCR 472.5 Architecture 512.6 Synoptic iCR Functional Definition 562.7 Exercises 563 Evolving From Aware and Adaptive to Cognitive Radio 583.1 Revolution or Evolution? 583.2 Moving Day 593.3 Developing AML for Genie 623.4 Learning Etiquette 733.5 Value Proposition for AML in AACR 753.6 Exercises 794 Autonomous Machine Learning for AACR 804.1 Machine Learning Framework 804.2 Histogram as a Discovery Algorithm 854.3 User-Domain Learning 884.4 Radio-Domain Learning 974.5 Reinforcement, Extension, and Constraint Discovery 1084.6 Learning Strategies 1184.7 Exercises 1215 Cognitive Radio Architecture 1235.1 CRA I: Functions, Components, and Design Rules 1245.2 CRA II: The Cognition Cycle 1345.3 CRA III: The Inference Hierarchy 1385.4 CRA IV: Architecture Maps 1435.5 CRA V: Building the CRA on SDR Architectures 1445.6 Cognition Architecture Research Topics 1525.7 Exercises 152II Radio-Domain Competence6 Radio-Domain Use Cases 1576.1 Radio Use-Case Metrics 1576.2 FCC Unused TV Spectrum Use Case 1636.3 Demand Shaping Use Case 1706.4 Military Market Segment Use Cases 1766.5 RF Knowledge That Saves Lives 1776.6 Prognostication 1806.7 Exercises 1807 Radio Knowledge 1837.1 Radio-Domain Overview 1837.2 Knowledge of the HF Radio Band 1957.3 Knowledge of the LVHF Radio Band 2087.4 Radio Noise and Interference 2247.5 Knowledge of the VHF Radio Band 2287.6 Knowledge of the UHF Radio Band 2377.7 Knowledge of the SHF Radio Band 2467.8 Knowledge of EHF, Terahertz, and Free Space Optics 2567.9 Satellite Communications Knowledge 2607.10 Cross-Band/Mode Knowledge 2678 Implementing Radio-Domain Skills 2758.1 Cognitive Radio Architecture Structures Radio Skills 2768.2 Embedded Databases Enable Skills 2818.3 Production Systems Enable Skills 2888.4 Embedded Inference Enables Skills 2918.5 Radio Knowledge Objects (RKOs) 2968.6 Evolving Skills Via RKO and RDH 3038.7 Implementing Spatial Skills 3058.8 Generalized 3188.9 Microworlds 3238.10 Radio Skills Conclusions 3258.11 Exercises 326III User-Domain Competence9 User-Domain Use Cases 3319.1 Emergency Companion Use Case 3319.2 Office Assistant Use Case 3339.3 Cognitive Assistants for Wireless 3349.4 User Skill Enhancements 3439.5 Exercises 34610 User-Domain Knowledge 34710.1 Users’ Natural Language Expression 34810.2 Acoustic Sensory Perception 35210.3 Visual Sensory Perception 35910.4 Audio-Visual Integration 36310.5 Lexical Conceptual Semantics (LCS) 36610.6 Other Sensors 36910.7 Architecture Implications 36910.8 Exercises 36911 Implementing User-Domain Skills 37211.1 Integrating Cognition 37311.2 Autonomous Extensibility 38211.3 Supervised Extensibility 40111.4 Uncertainty 40711.5 Learning Requires Grounding 41711.6 Sleep Cycles 42311.7 Pitfalls and Opportunities 42411.8 Exercises 42612 Semantic Radio 42812.1 CYC, eBusiness Solutions, and the Semantic Web 42812.2 CYC Case Study 42912.3 CYC Implications 43712.4 Web Languages 43912.5 Radio XML 43912.6 Conclusions 443Glossary 444References 451Index 467