Cognitive Wireless Communication Networks

Cognitive Wireless Communication Networks by Ekram Hossain, published by Springer US on November 4, 2010, is a softcover reprint of the hardcover first edition from 2007, comprising 440 pages. This book explores the technology of cognitive radio, which aims to optimize the use of limited radio bandwidth while accommodating a growing array of services and applications in wireless networks. It discusses the adaptability of cognitive radio transceivers to dynamic radio environments and network parameters, emphasizing their ability to maximize resource utilization and provide flexibility in wireless access.
Readers will find an in-depth examination of the key features of cognitive radio transceivers, including their awareness of the radio environment and their intelligence, which is developed through adaptive learning. The book addresses both technical and practical considerations related to cognitive radio technology, highlighting the multidisciplinary nature of the field. It also covers enabling techniques such as wideband signal processing, advanced wireless communication methods, and machine learning approaches, making it relevant for researchers in telecommunications, networking, and artificial intelligence.
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A Brief Journey through “Cognitive Wireless Communication Networks” Ekram Hossain, University of Manitoba, Winnipeg, Canada Vijay Bhargava, University of British Columbia, Vancouver, Canada Introduction Cognitive radio has emerged as a promising technology for maximizing the utili- tion of the limited radio bandwidth while accommodating the increasing amount of services and applications in wireless networks. A cognitive radio (CR) transceiver is able to adapt to the dynamic radio environment and the network parameters to maximize the utilization of the limited radio resources while providing ?exibility in wireless access. The key features of a CR transceiver are awareness of the radio en- ronment (in terms of spectrum usage, power spectral density of transmitted/received signals, wireless protocol signaling) and intelligence. This intelligence is achieved through learning for adaptive tuning of system parameters such as transmit power, carrier frequency, and modulation strategy (at the physical layer), and higher-layer protocol parameters. Development of cognitive radio technology has to deal with technical and pr- tical considerations (which are highly multidisciplinary) as well as regulatory – quirements. There is an increasing interest on this technology among the researchers in both academia and industry and the spectrum policy makers. The key enabling techniques for cognitive radio networks (also referred to as dynamic spectrum – cess networks) are wideband signal processing techniques for digital radio, advanced wireless communications methods, arti?cial intelligence and machine learning te- niques, and cognitive radio-aware adaptive wireless/mobile networking protocols.
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