Cognitive Radio Communication and Networking (eBook)

Principles and Practice

Robert Caiming Qiu, Zhen Hu, Husheng Li, Michael C. Wicks (Autoren)

eBook Download: EPUB

2012
John Wiley & Sons (Verlag)
9781118376294 (ISBN)

Infos

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
• Companion website hosting MATLAB codes, and supplementary material including exercises

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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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.

Autor

Robert C. Qiu, Department of Electrical and Computer Engineering, Tennessee Technological University, USA Professor Qiu is currently Director of the Wireless Networking System Laboratory at Tennessee Technological University, USA. He was Founder-CEO and President of Wiscom Technologies, Inc., manufacturing and marketing WCDMA chipsets. Wiscom was acquired by Intel in 2003. Prior to Wiscom, he worked for GTE Labs, Inc. (now Verizon), Waltham, MA, and Bell Labs, Lucent, Whippany, NJ. He holds 5 U.S. patents (another two pending) in WCDMA. He is co-editor of Ultra-Wideband Wireless Communications and Networks (Wiley), and? has authored over 80 technical (journal/conference) papers and contributed 6 book chapters. Professor Qiu has contributed to 3GPP and IEEE standards bodies, and delivered invited seminars to institutions including Princeton University and the U.S. Army Research Lab. Dr. Qiu serves as Associate Editor, IEEE Transaction on Vehicular Technology, International Journal of Sensor Networks and Wireless Communication and Mobile Computing.

Textauszug

Preface

The idea of writing this book began at least five years ago when the first author taught a one first-year graduate course, on communications/wireless communications. After this course, some students pursued advanced topics such as convex optimization prior to their PhD research. MS students wanted to know more about the field before they began to design wireless systems. The first author taught such advanced courses regularly, and part of these materials provided the starting point for this book. After this book project began, additional authors were added so that we could meet with our deadlines and before the topics become outdated. Another title of this book could be Advanced Wireless Communications.

The most difficult part was to decide what to exclude. The wireless industry is still expanding rapidly after two decades of growth. The first author studied the second generation (2G) system—CDMA and GSM—during his university days. Now, 3G (WCDMA) and 4G (LTE) systems are available. Each system has its central concept and demands unique analytical skills. Generally professors find that their most significant responsibilities are to teach students the most difficult mathematical tools required to analyze and design fundamental system concepts. For example, in a GSM (TDMA) system, the equalizers are central to the system. For a CDMA system, a RAKE receiver is central (as is power control). For an LTE system, a multiple-input, multiple-output (MIMO) system combined with an orthogonal frequency division multiplexing (OFDM) is central.

This approach is adopted in our book. We cover the system concepts that are central to the next generation cognitive radio network (CRN). We claim that the following three analytical tools are central to the CRN: (1) large random matrices; (2) convex optimization; (3) game theory. The unified view is the so-called “Big Data”—high-dimensional data processing. Due to the unique nature of cognitive radio, we have an unparalleled challenge—having too much data at our disposal. In today's digital age, making sense of the data in real-time is central not only to major players like Facebook, Google and Amazon, but also to our telecommunication vendors. To successfully solve the Big Data problem however, there are still many hurdles. For one thing, the current tools are inadequate. Scientist and engineers with the skills to analyze the data are scarce. Future ECE students must learn the analytical skills obtained from studying Big Data. In addition to traditional fields, this book contains results from multi disciplinary fields: machine learning, financial engineering, statistics, quantum computing, etc. Social networking and the Smart Grid command more resources. Researchers must become more cost-conscious. Investments in other fields mentioned above can reduce the costs of solving these problems. Abstract mathematical connections are the best starting point toward this goal. This justifies our belief in teaching students the most difficult analytical skills that are not readily obtained after leaving schools. By studying this book, practical engineers will understand system concepts, and may make connections with other fields. Peer researchers can use this book as a reference.

Compared with previous systems, the CRN contains radios that are highly programmable; their modulation waveforms are changing rapidly and their frequencies are agile; their radio frequency (RF) front-ends are wideband (up to several GHz). In addition to the highly programmable nature of their physical layer functions, a CRN radio senses the spectrum at an unprecedentedly low signal-to-noise-ratio (SNR) (e.g., −21 dB required by the FCC). To support this fundamental spectrum sensing function, the system allocates computing resources with the ultimate goal of real-time operations. From another viewpoint, this radio is a powerful sensor with almost unlimited computing and networking capabilities. Through the combination of these two views, communications and sensing are merged into one function that transmits, receives, and processes programmable modulated waveforms. Real-time distributed computing is embedded in these two functions.

It is believed that we lack a coherent network theory that is valid for numerous applications. Rather, the state-of-the-art network is designed for special needs; when a new need arises, the network must be redesigned. Costs are wasteful due to the lack of a network theory. The cognitive radio poses unique challenges in networking.

Wireless technology is proliferating rapidly; the vision of pervasive wireless computing, communication, sensing and control offers the promise of many societal and individual benefits. Cognitive radios, through dynamic spectrum access, offer the promise of being a disruptive technology. Cognitive radios are fully programmable wireless devices that can (1) sense their environment and (2) dynamically adapt their transmission waveform, channel access method, spectrum use and networking protocols. It is anticipated that cognitive radio technology will become a general-purpose programmable radio that will serve as a universal platform for wireless system development, as microprocessors have served a similar role for computation. There is, however, a big gap between having a flexible cognitive radio, effectively a building block, and the large-scale deployment of cognitive radio networks that dynamically optimize spectrum use. Testbeds are critical but totally ignored since the materials become outdated when the book is published. We want to focus on the materials that can last.

One goal is aimed toward a large-scale cognitive radio network; in particular, we need to study novel cognitive algorithms using quantum information and machine learning techniques, to integrate FPGA, CPU and graphics processing unit (GPU) technology into state-of-the-art radio platforms, and to deploy these networks as testbeds in the real-world university environment. Our applications range from communications to radar/sensing and Smart Grid technologies. Cognitive radio networking/sensing for unmanned aerial vehicles (UAVs) is also very interesting and challenging due to its high mobility. Synchronization is critical. UAVs can be replaced with robots.

One task will pursue a new initiative of CRN as sensors and explore the vision of a dual-use sensing/communication system based on CRN. The motivation is to push the convergence of sensing and communication systems into a unified cognitive networking system. CRN is a cyber-physical system with the integrated capabilities of control, communications, and computing.

Due to the embedded function of cooperative spectrum sensing in CRN, rich information about the radio environment may be obtained. This information unique to CRN can be exploited to detect, indicate, recognize, or track the target or intruder in the covered area of a CRN. The data for this kind of information system are intrinsically high-dimensional and random. Hence, we can employ quantum detection, quantum state estimation, and quantum information theory in our new initiative using CRN as sensors. In this way, the sensing capability of CRN can be explored together with great improvement in performance.

Very often one views a cognitive radio as two fundamental functions: (1) spectrum sensing; (2) spectrum-aware resources allocation. In this second function, convex optimization plays a central role. Optimization stems from human instinct. We always like to do something in the best way. Optimization theory gives us a way to realize this kind of human instinct. With the enhancement of computing capability, optimization theory, especially convex optimization, is a powerful signal processing tool to handle Big Data. If the data mining problem can be formulated as a convex optimization problem, the global optimum can be achieved. There is no doubt about the results or performances. However, there is still a challenge to make optimization algorithms scalable on the data sets of millions or trillions of elements. Thus, more effort is needed to explore optimization theory before we gain the benefit of it.

A collection of nodes are studied. These nodes, in analogy with human beings, can both collaborate and compete. Game theory captures the fundamental role of competition for resources. Of course, many algorithms in game theory can be formulated as convex optimization problems. For the games in CRN, we have provided plenty of working knowledge of generic games such that the readers can begin the research without reading specific books on game theory. Several typical examples in CRN are given to illustrate how to use game theory to analyze cognitive radio. Moreover, many unique concerns of games in cognitive radio are explained in order to motivate new research directions.

We will explain the networking issues in CRN in a layer by layer manner. Only challenges specific to CRN are explained in order to distinguish from traditional communication networks. We hope that the corresponding chapter not only explains the state-of-the-art of CRN, but also motivates new ideas in the design of CRN.

The overall picture of this book is presented in Figure P.1. Novel applications of the CRN include:

1. The Smart Grid; Security is a challenge.

2. Wireless networking for for unmanned aerial vehicles. Synchronization is a challenge.

3. Cloud computing is integrated with the CRN.

4. The CRN is used as distributed sensing.

Figure P.1 Connections of different chapters in this book.

Chapter 1 overviews the book. Twelve chapters are...

Produkt-Details

• Erscheint lt. Verlag: 10.9.2012
• Sprache: englisch
• Themenwelt: Technik ► Elektrotechnik / Energietechnik
• Themenwelt: Technik ► Nachrichtentechnik
• Schlagworte: Cognitive Radio Communication and Networking, Robert Caiming Qiu, Zhen Hu, Husheng Li, Spectrum Sensing, Cooperative Spectrum Sensing Wideband Spectrum Sensing, Agile Transmission Techniques, Orthogonal Frequency Division • Communication Technology - Networks • Drahtlose Kommunikation • Electrical & Electronics Engineering • Elektrotechnik u. Elektronik • Kommunikationsnetz • Kommunikationsnetze • Mobile & Wireless Communications
• ISBN-13: 9781118376294 / 9781118376294