Optimal spectrum allocation in Cognitive Radio using Genetic Algorithm

P. Varade, Y. Ravinder
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引用次数: 11

Abstract

Modern developments in wireless technologies lead to scarcity of spectrum due to fixed spectrum allocation policy. Cognitive Radio which uses Dynamic spectrum allocation is proposed to utilize spectrum efficiently. In a given wireless scenario optimization of transmission parameters for cognitive radio become complex due to many transmission parameters and large number of values it can have. In this paper we have proposed a cognitive radio decision engine that determines the optimal values of radio transmission parameters using Genetic Algorithm (GA) for optimal spectrum allocation in cognitive radio. Initially we have strived to achieve subset of parameters and evolve them till the optimal value is achieved for given performance objective. To control the evolution process for GA we have defined fitness measures for different performance objective. Simulation results clearly show that optimization of transmission parameters is achieved with the overall efficiency of 94% for fitness measures.
基于遗传算法的认知无线电频谱优化分配
随着现代无线技术的发展,由于固定的频谱分配政策,导致频谱资源短缺。为了有效地利用频谱,提出了动态频谱分配的认知无线电。在给定的无线场景中,由于认知无线电的传输参数众多且可能具有大量的值,因此传输参数的优化变得非常复杂。本文提出了一种认知无线电决策引擎,利用遗传算法确定无线电传输参数的最优值,实现认知无线电的最优频谱分配。最初,我们努力实现参数的子集,并不断进化,直到达到给定性能目标的最优值。为了控制遗传算法的进化过程,我们针对不同的性能目标定义了适应度度量。仿真结果清楚地表明,传输参数的优化达到了94%的适应度度量的总效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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