Preface
Published online by Cambridge University Press: 26 February 2010
Summary
Frequency spectrum is a limited resource for wireless communications and may become congested owing to a need to accommodate the diverse types of air interface used in next generation wireless networks. To meet these growing demands, the Federal Communications Commission (FCC) has expanded the use of the unlicensed spectral band. However, since traditional wireless communications systems also utilize the frequency bands allocated by the FCC in a static manner, they lack adaptability. Also, many studies show that while some frequency bands in the spectrum are heavily used, other bands are largely unoccupied most of time. These potential spectrum holes result in the under-utilization of available frequency bands.
The concepts of software-defined radio and cognitive radio have been recently introduced to enhance the efficiency of frequency spectrum usage in next generation wireless and mobile computing systems. Software radio improves the capability of a wireless transceiver by using embedded software to enable it to operate in multiple frequency bands using multiple transmission protocols. Cognitive ratio, which can be implemented through software-defined radio, is able to observe, learn, optimize, and intelligently adapt to achieve optimal frequency band usage. Through dynamic spectrum access, a cognitive wireless node is able to adaptively and dynamically transmit and receive data in a changing radio environment. Therefore, techniques for channel measurement, learning, and optimization are crucial in designing dynamic spectrum access schemes for cognitive radio under different communication requirements.
In fact, cognitive radio based on dynamic spectrum access has emerged as a new design paradigm for next generation wireless networks. Cognitive radio aims at maximizing the utilization of the limited radio bandwidth while accommodating the increasing number of services and applications in wireless networks.
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- Dynamic Spectrum Access and Management in Cognitive Radio Networks , pp. xiii - xviPublisher: Cambridge University PressPrint publication year: 2009