基于粒子群优化的频谱共享

Tareq M. Shami, Ayman A. El-Saleh, M. Y. Alias
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引用次数: 0

摘要

与静态频谱策略不同,频谱共享采用动态频谱接入技术,有效利用频谱资源。本工作的主要目标是使认知无线电网络中允许的次要链路与主链路和平共存的总吞吐量最大化。将二元粒子群算法应用于这一认知无线电优化问题。我们还研究了限制主链路和从链路的链路距离对总吞吐量的影响。结果证明了利用粒子群算法实现总吞吐量最大化的可行性。主、次链路之间的距离越短,总吞吐量越高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Spectrum sharing using particle swarm optimization
Unlike the static spectrum policy, spectrum sharing uses dynamic spectrum access techniques in order to utilize the spectrum efficiently. The main objective of this work is to maximize the sum throughput for the allowed secondary links that can coexist peacefully with primary links in a cognitive radio network. A binary particle swarm optimization (BPSO) is applied to solve this cognitive radio optimization problem. We also investigate the effect of limiting the link distance of both primary and secondary links on the sum throughput. The results prove the viability of using BPSO to maximize the sum throughput. Moreover, it is shown that the shorter the distance of primary and secondary links the higher the sum throughput.
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