Cognitive Radio Communication and Networking: Principles and Practice

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John Wiley & Sons, Sep 10, 2012 - Technology & Engineering - 536 pages
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The author presents a unified treatment of this highly interdisciplinary topic to help define the notion of cognitive radio. The book begins with addressing issues such as the fundamental system concept and basic mathematical tools such as spectrum sensing and machine learning, before moving on to more advanced concepts and discussions about the future of cognitive radio. From the fundamentals in spectrum sensing to the applications of cognitive algorithms to radio communications, and discussion of radio platforms and testbeds to show the applicability of the theory to practice, the author aims to provide an introduction to a fast moving topic for students and researchers seeking to develop a thorough understanding of cognitive radio networks.

  • Examines basic mathematical tools before moving on to more advanced concepts and discussions about the future of cognitive radio
  • Describe the fundamentals of cognitive radio, providing a step by step treatment of the topics to enable progressive learning
  • Includes questions, exercises and suggestions for extra reading at the end of each chapter

Topics covered in the book include: Spectrum Sensing: Basic Techniques; Cooperative Spectrum Sensing Wideband Spectrum Sensing; Agile Transmission Techniques: Orthogonal Frequency Division Multiplexing Multiple Input Multiple Output for Cognitive Radio; Convex Optimization for Cognitive Radio; Cognitive Core (I): Algorithms for Reasoning and Learning; Cognitive Core (II): Game Theory; Cognitive Radio Network IEEE 802.22: The First Cognitive Radio Wireless Regional Area Network Standard, and Radio Platforms and Testbeds.


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MachineLearning 7 1 Unsupervised Learning 7 2 Supervised Learning
Agile Transmission Techniques
Multiple Output 8 1 Benefits ofMIMO 8 2 Space TimeCoding 8 3 MultiUser MIMO 8 4 MIMO Network 8 5 MIMO CognitiveRadio Network
Signal through Machine Learning
Hypothesis Detectionof Noncommutative Random
Convex Optimization

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About the author (2012)

Michael C. Wicks holds a Ph.D. from Syracuse University. Mr. Wicks is a principal engineer at the US Air Force Research Laboratory in the Sensor Directorate, Radar Signal Processing Branch. He is a fellow of the IEEE. He is on the Board of Governors for IEEE Aerospace and Electronic Systems and is the Chairman of the IEEE Radar Systems Panel.

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