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Journal ArticleDOI

Research on Soft Computing Techniques for Cognitive Radio

TLDR
A critical review on different soft computing approaches applied over the cognitive radio issues is presented & also points out different research directions over it.
Abstract
Presently, the world of wireless communication is going under some crucial challenges, which attracts the attention of several researchers. Cognitive radio is defined as a multidimensional aware, autonomous radio system that learns from its experiences to reason, plan & decide future actions to meet user needs. Such a highly varied radio environment calls on intelligent management, allocation & usage of scarce resources. Issues like spectrum sensing & allocation, environmental learning i.e., adaptability & capability to learn attracts the attention of several soft computing learning & optimization techniques like neural networks, fuzzy logic, genetic algorithm & swarm intelligence. The cognitive engine behind the radio combines the sensing, learning, switching, and optimization algorithms to control & adapt the radio system from the physical layer to the top of the communication stack. This paper presents a critical review on different soft computing approaches applied over the cognitive radio issues & also points out different research directions over it.

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Citations
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Book ChapterDOI

A PMOGA-Based Approach for Efficient Spectrum Utilization in Cognitive Radio

TL;DR: A parallel multi-objective genetic algorithm (PMOGA)-based approach for efficient spectrum utilization in cognitive radio (CR) addresses multiple objective issues in spectrum utilization like minimization of bit error rate and interference with maximization of throughput by considering the constraints likemaximum value of interference level on primary user and maximum value of BER of the secondary user.
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Proceedings ArticleDOI

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Proceedings ArticleDOI

Research on Cognitive Radio Engine Based on Genetic Algorithm and Radial Basis Function Neural Network

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Proceedings ArticleDOI

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