Titlebook: Developments in Cognitive Radio Networks; Future Directions fo Bodhaswar TJ Maharaj,Babatunde Seun Awoyemi Book 2022 The Editor(s) (if appl

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Resource Optimisation Problems in Cognitive Radio Networks them as optimisation problems. A general representation of resource optimisation problems in cognitive radio networks is then provided. Some classical examples of resource allocation problems and problem formulations in cognitive radio networks are presented. Thereafter, the unique characteristics

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Deep Learning Opportunities for Resource Management in Cognitive Radio Networkss posed by the environment. The chapter explores and investigates deep architecture being applied in addressing spectrum management problems in the cognitive radio networks. The most integral part of this chapter is the discussion on how these deep architecture are orchestrated or tailored to solve

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Book 2022 modern cognitive radio networks on other emerging technologies -- such as 5G, Internet of Things, and advanced wireless sensor networks -- and discusses the role that cognitive radio networks play in the evolution of smart cities and in the realization of a highly interconnected world. In discussin

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Introduction to Cognitive Radio Networksrich history and establishes that the radio-frequency spectrum is the most important base in the overall cognitive radio network scheme. The recently-proposed concept of dynamic spectrum access and allocation is portrayed as the preferred mechanism for sharing and administering the spectrum, especia

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Spectrum Resource for Cognitive Radio Networksr further establishes that, by simply improving spectrum sensing, the challenge of spectrum scarcity and underutilisation can be significantly mitigated in modern wireless communications. Traditional approaches to spectrum sensing, such as energy detection and matched filter detection are discussed,

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