认知无线电网络中基于混合IWOPSO算法的协同频谱感知

D. Das, Susmita Das
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引用次数: 2

摘要

认知无线电(CR)是一种解决频谱稀缺问题的新兴技术。这是通过持续地感知频谱和检测未充分利用的频段而不会对主用户(PU)造成不当干扰来实现的。但是,恶意用户/攻击者的存在会降低系统的性能。为此,提出了一种改进的基于软决策融合(SDF)的协同频谱感知(CSS)方案,该方案采用入侵杂草混合优化和粒子群混合优化(hybrid IWOPSO)算法作为全局优化方法,对权系数进行优化,使主用户仿真攻击(PUEA)存在时的检测概率最大化。通过与现有的基于SDF的CSS方案进行比较,验证了本文算法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Cooperative spectrum sensing using hybrid IWOPSO algorithm in cognitive radio networks
Cognitive Radio (CR) is an emerging technology to combat the spectrum scarcity issues. This is achieved by consistently sensing the spectrum, and detecting the under-utilized frequency bands without causing undue interference to the primary user (PU). However, the presence of malicious users/attackers degrades the system performance. So, we propose an improved soft decision fusion (SDF) based cooperative spectrum sensing (CSS) scheme in which the hybrid invasive weed optimization and particle swarm optimization (hybrid IWOPSO) algorithm is used as global optimization method to optimize the weight coefficients to maximize the detection probability in the presence of primary user emulation attack (PUEA). The efficacy of our proposed algorithm is validated by comparing with the other existing SDF based CSS schemes.
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