This book discusses in-depth the concept of distributed artificial intelligence (DAI) and its application to cognitive communications
Table of Contents
Part One: Introduction
Chapter 1 Introduction to Cognitive Communications
Part Two: Wireless Communications
Chapter 2 Cognitive Radio and Networks for Heterogeneous Networking
Chapter 3 Channel Assignment and Power Allocation Algorithms in Multi-Carrier-Based Cognitive Radio Environments
Chapter 4 Filter Bank Techniques for Multi-Carrier Cognitive Radio Systems
Chapter 5 Distributed Clustering of Cognitive Radio Networks: A Message-Passing Approach
Part Three: Application of Distributed Artificial Intelligence
Chapter 6 Machine Learning Applied to Cognitive Communications
Chapter 7 Reinforcement Learning for Distributed Power Control and Channel Access in Cognitive Wireless Mesh Networks
Chapter 8 Reinforcement Learning-Based Cognitive Radio for Open Spectrum Access
Chapter 9 Learning Techniques for Context Diagnosis and Prediction in Cognitive Communications
Chapter 10 Social Behavior in Cognitive Radio
Part Four: Regulatory Policy and Economics
Chapter 11 Regulatory Policy and Economics of Cognitive Radio for Secondary Spectrum Access
Part Five: Implementation
Chapter 12 Cognitive Radio Networks in TV White Spaces
Chapter 13 Cognitive Femtocell Networks
Chapter 14 Cognitive Acoustics: A Way to Extend the Lifetime of Underwater Acoustic Sensor Networks
Chapter 15 CMOS RF Transceiver Considerations for DSA
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