Artificial Intelligence Application to Cognitive Radio Networks

Author(s):  
Badr Benmammar ◽  
Asma Amraoui
Author(s):  
Shikha Singhal ◽  
Shashank Gupta ◽  
Adwitiya Sinha

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.


Author(s):  
Preetjot Kaur ◽  
Roopali Garg

This chapter provides a-state-of-art of artificial intelligence (AI) techniques applied to cognitive radio networks. Cognitive radio (CR) is an empowering innovation for various new opportunities, for example, spectrum sensing, access, markets, and self-organizing networks. Its target is to enable the system to exploit the available resources through self-learning and to adapt itself accordingly to the sensed environment. To understand this plethora of applications, CR researchers often make use of several types of AI techniques. By utilizing AI, the network system can immediately complete self-awareness learning, structure association, and scheduling several tasks. To help researchers obtain a healthier knowledge of AI techniques along with CR, this chapter presents several such implementations that have already been applied. Finally, the literature review of the best accomplishments in applying AI techniques to CRs is presented and classified according to the major techniques of artificial intelligence.


Author(s):  
Badr Benmammar

Cognitive radio is a form of wireless communication that makes decisions about allocating and managing radio resources after detecting its environment and analyzing the parameters of its radio frequency environment. Decision making in cognitive radio can be based on optimization techniques. In this context, machine learning and artificial intelligence are to be used in cognitive radio networks in order to reduce complexity, obtain resource allocation in a reasonable time and improve the user's quality of service. This article presents recent advances on artificial intelligence in cognitive radio networks. The article also categorizes the techniques presented according to the type of learning—supervised or unsupervised—and presents their applications and challenges according to the tasks of the cognitive radio.


2014 ◽  
Vol 1 ◽  
pp. 652-655
Author(s):  
Takumi.Matsui Takumi.Matsui ◽  
Mikio.Hasegawa Mikio.Hasegawa ◽  
Hiroshi.Hirai Hiroshi.Hirai ◽  
Kiyohito.Nagano Kiyohito.Nagano ◽  
Kazuyuki.Aihara Kazuyuki.Aihara

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