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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

Real-coded genetic algorithm parameter setting for cognitive radio adaptation

TL;DR: This paper proposes a new algorithm based on a real-coded genetic algorithm, based on De Jong's standard parameter settings and binary coding, used for optimizing QoS for cognitive radio, which gives better performance in terms of convergence speed.
Proceedings ArticleDOI

A Mini-Slot Sensing with Selective Coordinator in Cognitive Radio System

TL;DR: It is proved that in mini-slot sensing, not all slots do benefits to CR system, and a Greedy based two stage assignment method is proposed as the sub-optimal solution.
Proceedings ArticleDOI

Genetic fuzzy scheduler for spectrum sensing in cognitive radio networks

TL;DR: Genetic Algorithm (GA) is used to give the proposed FIS scheduler the ability to evolve and adapt to new environment conditions, and heuristic-based scheduling algorithm is used as supporting mechanism for the genetic FIS Scheduler.
Proceedings ArticleDOI

Fuzzy channel ranking estimation in cognitive wireless networks

TL;DR: A FL-based channel ranking algorithm exploiting fuzzy logic (FL) theory is proposed that leads to more efficient communications that traditional crisp value based approaches.
Proceedings ArticleDOI

A novel spectrum sensing scheduler algorithm for Cognitive Radio Networks

TL;DR: A novel sensing scheduler algorithm is proposed, the idea is to utilize the CRN by fairly distribute the sensing task among the sensors, then utilizing the radio spectrum shared with the primary networks.
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