Sudharman K. Jayaweera - Signal Processing for Cognitive Radios

1. Chapter 06
2. Chapter 11
3. Appendix C

1. Chapter 01
2. Chapter 02
3. Chapter 03
4. Chapter 04
5. Chapter 06
6. Chapter 07
7. Chapter 08
8. Chapter 09
9. Chapter 10
10. Chapter 11
11. Chapter 12
12. Chapter 13
13. Chapter 14
14. Chapter 15
15. Chapter 16
16. Appendix A

SUDHARMAN K. JAYAWEERA

University of New Mexico

Copyright 2015 by John Wiley & Sons, Inc. All rights reserved

Published by John Wiley & Sons, Inc., Hoboken, New Jersey
Published simultaneously in Canada

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Library of Congress Cataloging-in-Publication Data:

Jayaweera, Sudharman K., 1972
Signal processing for cognitive radios / Sudharman K. Jayaweera.
pages cm
Includes index.

ISBN 978-1-118-82493-1 (hardback)
1. Cognitive radio networks. 2. Signal processing. I. Title.
TK5103.4815.J39 2015
621.3822dc23

2015020555

To my mother (Amma) Mulin
and my son
Milidu

Arguably, it is signal processing that makes a cognitive radio cognitive. Its predecessor, software-defined radio (SDR) technology, already provides a software-reconfigurable device platform by implementing most baseband radio operations in software instead of in hardware. Cognitive radios are meant to be SDRs that are cognitive and intelligent. Acquisition of knowledge through learning is a common aspect of both cognition and intelligence, while self-awareness and reasoning (application of acquired knowledge) are perhaps distinctive features of cognition and intelligence, respectively. A cognitive radio, thus, is supposed to possess all these features: self-awareness, learning, and reasoning. Clearly, these are attributes that a radio can possess mostly through signal processing. It is the signal processing algorithms, implemented on an SDR platform, that will endow a radio with self-awareness, learning, and reasoning abilities.

There are many books devoted to cognitive radios. However, none are devoted to signal processing in cognitive radios. This book is an attempt to highlight the fundamental role of signal processing in cognitive radios. One may identify two types of signal processing within a cognitive radio: signal processing for gaining spectrum awareness and signal processing for achieving efficient communications. Many processing algorithms that fall under the latter are already present in all wireless communications systems and devices. However, signal processing for spectrum awareness is unique to cognitive radios. These are aimed at providing the cognitive radio with self-awareness, a necessary ingredient of cognition. Attempting to comprehensively cover signal processing of both these types in a single book is perhaps an unrealistic goal. Moreover, it is unnecessary given the fact that there are many excellent books devoted to signal processing in wireless communications systems. Hence, the focus of this book is on signal processing that is unique to a cognitiveradio. Not surprisingly, signal processing for gaining spectrum awareness constitutes a bulk of this focus. Still though, there are certain advanced signal processing techniques aimed at achieving efficient communications that are realistically well suited for implementations on sophisticated devices such as cognitive radios, thus deserving to be included in a book on signal processing for cognitive radios. An example is the advanced cooperative communications and processing techniques.

Any radio that is simply cognitive and intelligent can be considered as a cognitive radio. Hence, the notion of cognitive radios is a broad concept. Depending on the application context and the type of communications network in question, cognition and intelligence in a cognitive radio may be directed at achieving different objectives. One such widely pursued objective is the development of radios that may coexist with licensed spectrum users through dynamic spectrum sharing (DSS). However, there are other useful objectives as well, including, among others, multiband/multimode operation and antijamming. In general, such cognitive radios may be taken to be wideband radios in the sense that they may be able to operate over a wide span of non-contiguous spectrum. By default, the cognitive radios in this book are such wideband radios whose cognition and intelligence are aimed at arbitrary performance objectives. The DSS cognitive radios are treated as an important special case.

I would like to thank my former graduate students Mario Bkassiny, Yang Li, and Tianming Li whose pursuit of graduate research on the topic of cognitive radios led to much of the new results in this book. In particular, this book would not have been possible without the help of Mario, Yang, and Ding Li (another former graduate student of mine), who helped me in preparing many diagrams and figures for the book. I cannot thank them enough. I would also like to thank Prof. Christos Christodoulou, my colleague at the ECE Department of UNM, for the opportunity to collaborate with him on cognitive radio research as well as his encouragement during this book writing project. I am grateful for Prof. Carlos Mosquera of the University of Vigo, Spain, and his wife Vicky for their friendship and support during the times that I spent in Vigo. You gave me much needed distraction to get through the tough times while still keeping the interest in working on CR research. I must mention Prof. Hyuck Kwon's help with some of the proof-reading and my friend Thusitha Liyanage for checking on me time-to-time when I was too absorbed in work to keep in touch with any friends.