Artificial Intelligence in Wireless Communications

by Rondeau, Thomas W.; Bostian, Charles W.

• ISBN13: 9781607832348
• ISBN10: 1607832348
• Edition: 1st
• Format: Hardcover
• Copyright: 2009-06-30
• Publisher: Artech House

Summary

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.

Author Biography

Thomas W. Rondeau is a research scientist at IDA CCR-P in Princeton, New Jersey. He holds an M.S. and a Ph.D. in electrical engineering from the Virginia Polytechnic Institute and State University. 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 a Ph.D. in electrical engineering from North Carolina State University.

Table of Contents

Acknowledgments	p. xiii
Introduction to Cognitive Radio	p. 1
Brief Concept of Cognitive Radio	p. 2
Very Brief Cognitive Radio History	p. 3
Definition	p. 5
Contributions	p. 6
Contents	p. 8
References	p. 8
The Cognitive Engine: Artificial Intelligence for Wireless Communications	p. 11
Cognitive Radio Design	p. 12
Cognitive Engine Design	p. 14
Component Descriptions	p. 16
Sensors	p. 16
Optimizer	p. 19
Decision Maker	p. 20
Policy Engine	p. 20
Radio Framework	p. 21
User Interface	p. 23
Cognitive Controller Configuration	p. 23
Artificial Intelligence in Wireless Communications	p. 24
Artificial Intelligence Techniques	p. 25
Neural Networks	p. 26
Hidden Markov Models (HMM)	p. 27
Fuzzy Logic	p. 28
Evolutionary Algorithms	p. 28
Case-Based Reasoning	p. 28
Conclusions	p. 29
References	p. 30
Overview and Basics of Software Defined Radios	p. 33
Background	p. 34
Benefits of Using SDR	p. 36
Problems Faced by SDR	p. 38
GNU Radio Design	p. 39
The Universal Software Radio Peripheral	p. 40
The USRP Version 2	p. 41
Flow Graphs	p. 41
Parallel Programming in GNU Radio	p. 44
Flow Graph for Simulation and Experimentation	p. 45
Available Knobs and Meters	p. 47
Conclusions	p. 50
References	p. 51
Optimization of Radio Resources	p. 53
Objective Space	p. 53
Multiobjective Optimization: Objective Functions	p. 55
Bit Error Rate (BER)	p. 56
Bandwidth (Hz)	p. 61
Spectral Efficiency (bits/Hz)	p. 62
Interference	p. 63
Signal to Interference Plus Noise Ratio (SINR)	p. 64
Throughput	p. 65
Power	p. 66
Computational Complexity	p. 67
Multiobjective Optimization: A Different Perspective	p. 68
Multiobjective Analysis	p. 68
Utility Functions	p. 68
Population-Based Analysis	p. 71
Conclusion	p. 73
References	p. 74
Genetic Algorithms for Radio Optimization	p. 77
A Brief Review	p. 77
Simple Example: The Knapsack Problem	p. 78
Multiobjective GA	p. 84
Wireless System Genetic Algorithm	p. 86
Details of Chromosome Structure	p. 88
Objective Function Definition	p. 90
Optimal Individual Selection	p. 91
Conclusions	p. 93
References	p. 94
Decision Making with Case-Based Learning	p. 97
Case-Based Decision Theory	p. 98
Cognitive Engine Architecture with CBDT	p. 99
Memory and Forgetfulness	p. 101
Cognitive Engine Case-Based Decision Theory Implementation	p. 102
Simple CBDT Example	p. 105
Cognitive Radio Example Problem	p. 113
Conclusion	p. 117
References	p. 118
Cognitive Radio Networking and Rendezvous	p. 119
Waveform Distribution and Rendezvous	p. 120
Cognitive Radio Networks	p. 121
Distributed AI	p. 122
Conclusions	p. 123
References	p. 123
Example Cognitive Engine	p. 125
Functional System Design	p. 126
Simple Simulations	p. 129
BER-only	p. 129
BER and Power (1)	p. 131
BER and Power (2)	p. 132
Throughput	p. 134
Waveform Efficiency	p. 134
Interference Environment	p. 137
Interference (1): Simple BER Tests	p. 138
Interference (2): Sensor Problems	p. 140
Interference (3): Correcting for Sensors	p. 141
Interference (4): Throughput with Low Spectral Footprint	p. 146
Case-Based Decision Theory Example	p. 148
Over-the-Air Results	p. 149
Conclusions	p. 155
References	p. 156
Conclusions	p. 157
Application to Multicarrier Waveforms	p. 158
Strategies, Not Waveforms	p. 159
Enhanced Learning Systems	p. 160
Final Thoughts	p. 161
References	p. 161
Analysis of GNU Radio Simulation	p. 163
Bit Error Rate Plots	p. 163
Additional BER Formulas	p. 169
References	p. 171
OProfile and Results of Profiling GNU Radio	p. 173
Introduction to OProfile	p. 173
OProfile Results of GNU Radio Modulators	p. 173
References	p. 176
XML and DTD Representation of the Cognitive Components	p. 181
Waveform Representation	p. 181
Objectives Sensor	p. 185
Meters Sensor	p. 186
PSD Sensor	p. 187
Cognitive Controller Configuration	p. 187
Optimal Solutions of Knapsack Problems	p. 191
Simulation of an SINR Sensor	p. 195
Sensor Design	p. 195
Simulation	p. 196
MATLAB Code	p. 198
SINR Calculation Function	p. 198
Plotting SINR with No Interference Power	p. 200
Plotting SINR with Varying Interference Power	p. 201
Acronyms	p. 203
About the Authors	p. 207
Index	p. 211
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