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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.
References
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Proceedings ArticleDOI

Artificial Mapping for Dynamic Resource Management of Cognitive Radio Networks

TL;DR: Recognizing that fuzzy logic inference can better handle uncertainty, fuzziness, and incomplete information in node convergence report, FuzzyConvergence is developed as a novel approach to aggregate wireless node control with affordable message overload.
Proceedings ArticleDOI

The Design of Scheduling Algorithm for Cognitive Radio Networks Based on Genetic Algorithm

TL;DR: Simulation results show that, by adjusting the proportion factor in the fitness function, the Genetic Algorithm for Cognitive Radio Scheduler (GACRS) algorithm can guarantee the fairness among users while reaching the upper limit of the spectrum utilization.
Proceedings ArticleDOI

Fuzzy cognitive Vehicular Ad hoc Networks

TL;DR: This paper suggests a system that employs a fuzzy logic system (FLS) to dynamically assign additional spectrum from the ISM band to the CCH by the IEEE 802.11p amendment, which succeeds to relieve contention by reducing delay and the number of un-transmitted packets.
Proceedings ArticleDOI

Reasoning through fuzzy logical for reconfiguration in cognitive radio network

TL;DR: The fuzzy logical based reconfiguration algorithm of CRN is studied, which is accomplished by introducing the reasoning process in reconfigured decision making, and the simulation results with detailed analysis are shown to enforce the effectiveness of the proposed algorithms.
Proceedings ArticleDOI

Fuzzy logic based channel selection for mobile secondary users in cognitive radio networks

TL;DR: In this work, a new approach for channel assignment to mobile secondary users by means of fuzzy logic is proposed by using input parameters of density, mobility, and noise, channel selection probability is obtained.
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