This cutting-edge resource offers practical overview of cognitive radio, a paradigm for wireless communications in which a network or a wireless node changes its transmission or reception parameters. The alteration of parameters is based on the active monitoring of several factors in the external and internal radio environment. This book offers a detailed description of cognitive radio and its individual parts. Practitioners learn how the basic processing elements and their capabilities are implemented as modular components. Moreover, the book explains how each component can be developed and tested independently, before integration with the rest of the engine. Practitioners discover how cognitive radio uses artificial intelligence to achieve radio optimization. The book also provides an in-depth working example of the developed cognitive engine and an experimental scenario to help engineers understand its performance and behavior.
Introduction to Cognitive Radio - Brief Concept of Cognitive Radio. Very Brief Cognitive Radio History. Definition. Contributions. Contents. ; The Cognitive Engine: Artificial Intelligence for Wireless Communications - Cognitive Radio Design. Cognitive Engine Design. Component Descriptions. Artificial Intelligence in Wireless Communications. Artificial Intelligence Techniques. Conclusions. ; Overview and Basics of Software Defined Radios - Background. Benefits of Using SDR. Problems Faced by SDR. GNU Radio Design. Conclusions. ; Optimization of Radio Resources - Objective Space. Multiobjective Optimization: Objective Functions. Multiobjective Optimization: A Different Perspective. Multiobjective Analysis. Conclusion. ; Genetic Algorithms for Radio Optimization - A Brief Review. Simple Example: The Knapsack Problem. Multiobjective GA. Wireless System Genetic Algorithm. Conclusions. ; Decision Making with Case-Based Learning - Case-Based Decision Theory. Cognitive Engine Architecture with CBDT. Cognitive Engine Case-Based Decision Theory Implementation. Simple CBDT Example. Cognitive Radio Example Problem. Conclusion. ; Cognitive Radio Networking and Rendezvous - Waveform Distribution and Rendezvous. Cognitive Radio Networks. Distributed AI. Conclusions. ; Example Cognitive Engine - Functional System Design. Simple Simulations. Interference Environment. Case-Based Decision Theory Example. Over-the-Air Results. Conclusions. ; Conclusions - Application to Multicarrier Waveforms. Strategies, Not Waveforms. Enhanced Learning Systems. Final Thoughts. ; Appendice. Acronyms. About the Authors. Index ;
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Charles W. Bostian
Charles W. Bostian is an alumni distinguished professor in the Bradley Department of Electrical and Computer Engineering at the Virginia Polytechnic Institute and State University. He holds an M.S. and Ph.D. in electrical engineering from North Carolina State University.
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Thomas W. Rondeau
Thomas W. Rondeau is a research scientist at IDA CCR-P in Princeton, New Jersey. He holds and M.S. and Ph.D. in electrical engineering from the Virginia Polytechnic and State University.