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Performance Analysis of Relay Subset Selection for Amplify-and-Forward Cognitive Relay Networks

机译:放大和前进认知继电器网络中继子集选择的性能分析

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Cooperative communication is regarded as a key technology in wireless networks, including cognitive radio networks (CRNs), which increases the diversity order of the signal to combat the unfavorable effects of the fading channels, by allowing distributed terminals to collaborate through sophisticated signal processing. Underlay CRNs have strict interference constraints towards the secondary users (SUs) active in the frequency band of the primary users (PUs), which limits their transmit power and their coverage area. Relay selection offers a potential solution to the challenges faced by underlay networks, by selecting either single best relay or a subset of potential relay set under different design requirements and assumptions. The best relay selection schemes proposed in the literature for amplify-and-forward (AF) based underlay cognitive relay networks have been very well studied in terms of outage probability (OP) and bit error rate (BER), which is deficient in multiple relay selection schemes. The novelty of this work is to study the outage behavior of multiple relay selection in the underlay CRN and derive the closed-form expressions for the OP and BER through cumulative distribution function (CDF) of the SNR received at the destination. The effectiveness of relay subset selection is shown through simulation results.
机译:协作通信时,通过复杂的信号处理允许分布式终端合作视为在无线网络,包括认知无线电网络(CRNS),这增加了信号的分集以对抗衰落信道的不利影响的关键技术。底衬CRNS有活性的主要用户(PUS)的频带,这限制了它们的发射功率和它们的覆盖区域朝向所述次要用户(SUS)严格干扰约束。中继选择提供了可能的解决方案,以通过底层网络面临的,通过选择单个最佳中继器或潜在的中继器的在不同的设计要求和假设的一个子集的挑战。在文献中提出的最佳中继器选择方案的放大和转发(AF)的底层认知中继网络已经在中断概率(OP)和误码率(BER),这是在多个中继不足的方面非常出色的研究选择方案。这项工作的新颖之处是研究底层CRN多个中继选择的中断行为,并通过累积分布函数(CDF)推导出OP和BER的封闭形式表达在目的地收到的SNR。中继子集选择的有效性是通过仿真结果示出。

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