Hang Qin
Published: 2017-04-30
Total Pages: 194
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This book is about cognitive radio (CR), a revolution in radio technology and an enabling technology for dynamic spectrum access. Due to the unique characteristics of the wireless networks, it is essential to address the approach of multiple layers (e.g., physical, link, and network) to maximize the network performance. The formulation of this cross-layer problem is usually complicated and challenging, while wireless resource allocation is a vital way to handle the race condition of the limited wireless resources. However, given the intrinsic characteristics of cognitive radio networks (CRN), none of the existing analytical approach could be a direct fit. Therefore, innovative theoretical results, along with the corresponding mathematical techniques, are necessary. In this book, we aim to develop some novel algorithmic design and optimization techniques that provide optimal or near-optimal solutions. Although cross-layer design has been introduced to CRN for many years, there are rarely any books for researchers, engineers, and students, from the engineering perspective. From one hand, most of the existing books primarily focus on the mathematical and economic aspects, which are considerably different from the engineering. On the other hand, all of the books mainly aim to system optimization or control techniques, while the cross-layer algorithm design in the distributed environment is usually ignored. As the result, there is an urgent demand for a reference source, which can provide complete information on how to fully adopt cross-layer resource allocation to the CRN. In this regard, this book not only focuses on the description of the main aspects of cross-layer resource allocation over CRN, but also provides a review of the application solutions. In a nutshell, it provides a specific treatment of cross-layer design in CRN. The topics range from the basic concepts of cross-layer resource allocation, to the state-of-the-art analyses, modelings, and optimizations for CRN.