Role of Artificial Intelligence in Cognitive Radio Networks

Role of Artificial Intelligence in Cognitive Radio Networks

Shikha Singhal, Shashank Gupta, Adwitiya Sinha
Copyright: © 2019 |Pages: 22
DOI: 10.4018/978-1-5225-5354-0.ch014
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Abstract

The role of artificial intelligence techniques and its impact in context of cognitive radio networks has become immeasurable. Artificial intelligence redefines and empowers the decision making and logical capability of computing machines through the evolutionary process of leaning, adapting, and upgrading its knowledge bank accordingly. Significant functionalities of artificial intelligence include sensing, collaborating, learning, evolving, training, dataset, and performing tasks. Cognitive radio enables learning and evolving through contextual data perceived from its immediate surrounding. Cognitive science aims at acquiring knowledge by observing and recording externalities of environment. It allows self-programming and self-learning with added intelligence and enhanced communicational capabilities over wireless medium. Equipped with cognitive technology, the vision of artificial intelligence gets broadened towards optimizing usage of radio spectrum by accessing spectrum availability, thereby reducing channel interferences while communication among licensed and non-licensed users.
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Artificial Intelligence

Artificial Intelligence is fundamentally a computer, software or computer controlled machine which thinks intelligently same as like human brain works. These computers do not use a fixed programmed to solve real-world problems. They are based on learning, training, reasoning, planning, and decision making aspects. The foundation of AI is based on how human brain works intelligently towards solving the problem i.e., how human brain thinks, sense, learn, decide, take actions to try to address any issue. On the basis of these studies, researchers developed some intelligent software so as to reduce manual efforts. The engineering science makes intelligent machine possible which behaves like as human brain (Russell, Norvig, Canny, Malik, & Edwards, 1995; He, Bae, Newman, Gaeddert, Kim, Menon, Morales-Tirado, Neel, Zhao, Reed, & Tranter, 2010).

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