Cross-Layer Resource Allocation in Cognitive Radio Networks: Models, Algorithms, and Applications - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Cross-Layer Resource Allocation in Cognitive Radio Networks: Models, Algorithms, and Applications write by Hang Qin. This book was released on 2017-04. Cross-Layer Resource Allocation in Cognitive Radio Networks: Models, Algorithms, and Applications available in PDF, EPUB and Kindle.
Cross-Layer Resource Allocation in Cognitive Radio Networks: Models, Algorithms, and Applications
Cross-Layer Resource Allocation in Cognitive Radio Networks: Models, Algorithms, and Applications - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Cross-Layer Resource Allocation in Cognitive Radio Networks: Models, Algorithms, and Applications write by Hang Qin. This book was released on 2017-04-30. Cross-Layer Resource Allocation in Cognitive Radio Networks: Models, Algorithms, and Applications available in PDF, EPUB and Kindle. 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.
Design of Cross-Layer Resource Allocation Algorithm with Multimedia Streams in Cognitive Radio Networks
Design of Cross-Layer Resource Allocation Algorithm with Multimedia Streams in Cognitive Radio Networks - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Design of Cross-Layer Resource Allocation Algorithm with Multimedia Streams in Cognitive Radio Networks write by 吳國瑋. This book was released on 2011. Design of Cross-Layer Resource Allocation Algorithm with Multimedia Streams in Cognitive Radio Networks available in PDF, EPUB and Kindle.
Cognitive Networks
Cognitive Networks - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Cognitive Networks write by Jaime Lloret Mauri. This book was released on 2014-12-09. Cognitive Networks available in PDF, EPUB and Kindle. A cognitive network makes use of the information gathered from the network in order to sense the environment, plan actions according to the input, and make appropriate decisions using a reasoning engine. The ability of cognitive networks to learn from the past and use that knowledge to improve future decisions makes them a key area of interest for anyone whose work involves wireless networks and communications. Cognitive Networks: Applications and Deployments examines recent developments in cognitive networks from the perspective of cutting-edge applications and deployments. Presenting the contributions of internationally renowned experts, it supplies complete and balanced treatment of the fundamentals of both cognitive radio communications and cognitive networks—together with implementation details. The book includes case studies and detailed descriptions of cognitive radio platforms and testbeds that demonstrate how to build real-world cognitive radio systems and network architectures. It begins with an introduction to efficient spectrum management and presents a survey on joint routing and dynamic spectrum access in cognitive radio networks. Next, it examines radio spectrum sensing and network coding and design. It explores intelligent routing in graded cognitive networks and presents an energy-efficient routing protocol for cognitive radio ad hoc networks. The book concludes by considering dynamic radio spectrum access and examining vehicular cognitive networks and applications. Presenting the latest standards and spectrum policy developments, the book’s strong practical orientation provides you with the understanding you will need to participate in the development of compliant cognitive systems.
Machine Learning for Future Wireless Communications
Machine Learning for Future Wireless Communications - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Machine Learning for Future Wireless Communications write by Fa-Long Luo. This book was released on 2020-02-10. Machine Learning for Future Wireless Communications available in PDF, EPUB and Kindle. A comprehensive review to the theory, application and research of machine learning for future wireless communications In one single volume, Machine Learning for Future Wireless Communications provides a comprehensive and highly accessible treatment to the theory, applications and current research developments to the technology aspects related to machine learning for wireless communications and networks. The technology development of machine learning for wireless communications has grown explosively and is one of the biggest trends in related academic, research and industry communities. Deep neural networks-based machine learning technology is a promising tool to attack the big challenge in wireless communications and networks imposed by the increasing demands in terms of capacity, coverage, latency, efficiency flexibility, compatibility, quality of experience and silicon convergence. The author – a noted expert on the topic – covers a wide range of topics including system architecture and optimization, physical-layer and cross-layer processing, air interface and protocol design, beamforming and antenna configuration, network coding and slicing, cell acquisition and handover, scheduling and rate adaption, radio access control, smart proactive caching and adaptive resource allocations. Uniquely organized into three categories: Spectrum Intelligence, Transmission Intelligence and Network Intelligence, this important resource: Offers a comprehensive review of the theory, applications and current developments of machine learning for wireless communications and networks Covers a range of topics from architecture and optimization to adaptive resource allocations Reviews state-of-the-art machine learning based solutions for network coverage Includes an overview of the applications of machine learning algorithms in future wireless networks Explores flexible backhaul and front-haul, cross-layer optimization and coding, full-duplex radio, digital front-end (DFE) and radio-frequency (RF) processing Written for professional engineers, researchers, scientists, manufacturers, network operators, software developers and graduate students, Machine Learning for Future Wireless Communications presents in 21 chapters a comprehensive review of the topic authored by an expert in the field.
