Future Mobile Communications
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Machine Learning for Future Wireless Communications
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.
Future Mobile Networks
Contributors from the British company BT Wireless describe new technologies and services that they predict the growing throng of mobile communications consumers will demand over the next few years. Among their topics are a virtual center of excellence in mobile and personal communications, what the technology will enable, architecture evolution to support multimedia, services through mobility portals, the future of radio access, and the company's airwave service. Annotation copyrighted by Book News, Inc., Portland, OR
Spectrum Requirement Planning in Wireless Communications
Presents the model and methodology, applied by ITU-R WRC’07, to calculate the spectrum requirement Spectrum Requirement Planning in Wireless Communications: Model and Methodology for IMT-Advanced is a self-contained “handbook” of the models and methodologies used for the spectrum requirement calculation for IMT-Advanced systems, as well as for the predecessor IMT-2000 systems. The reader will learn how the spectrum requirement is calculated for real systems that prevail worldwide. The book also provides the basis on which to develop advanced methodologies for yet future systems, as the spectrum regulation will continue in the future. Spectrum Requirement Planning in Wireless Communications: Model and Methodology for IMT-Advanced Provides the reader with information on how the spectrum requirement is calculated for real systems that prevail worldwide Contains useful tables and examples such as flowchart of the methodology Introduces definitions of service category and radio environment, the process of distributing traffic to radio environments, and the method to calculate the required spectrum Applies queueing and loss models for the calculation of required system capacity Covers utilization of radio frequencies, market data, spectrum requirement calculation methods for IMT-2000 and for IMT-Advanced systems Instructs how to use the calculation tool package Comes with an accompanying website with the downloadable tool applied by ITU-R WRC’07 for making decisions on spectrum regulation for mobile systems This book serves as an invaluable guide to engineers in mobile phone companies, system design engineers, operator system engineers and other specialists dealing with mobile system planning and development. It is also of great interest to researchers and graduate students in the fields of applied probability theory, operations research, telecommunications, and mobile networks engineering.