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首页> 外文期刊>Wireless personal communications: An Internaional Journal >Impact of Channel Estimation Error on the Performance of Relay Selection in Cognitive Radio Networks
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Impact of Channel Estimation Error on the Performance of Relay Selection in Cognitive Radio Networks

机译:信道估计误差对认知无线电网络中中继选择性能的影响

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摘要

Channel estimation error, which adversely affects the performance of any wireless communication system, is inevitably available in receivers. However, its impact on the bit error rate (BER) performance of relay selection in underlay cognitive networks has not been investigated analytically. This paper fills in this literature gap by firstly proposing an exact single-integral form BER formula for general network topology. Based on this proposal, we further analyze the diversity gain to have insights into asymptotic performance and system design. Secondly, we derive a closed-form approximate BER formula, which has been shown highly accurate, for a typical network topology where relays are closely positioned for reduced simulation time. Various results demonstrate that the channel estimation error significantly degrades the performance of the relay selection in underlay cognitive networks and completely destroys its diversity gain. In addition, increasing the number of involved relays drastically remedies its impact.
机译:不利于任何无线通信系统性能的信道估计误差在接收机中不可避免。但是,其对底层认知网络中中继选择的误码率(BER)性能的影响尚未进行分析研究。本文通过首先为通用网络拓扑提出一个精确的单积分形式BER公式来填补这一文献空白。基于此建议,我们将进一步分析多样性增益,以深入了解渐进性能和系统设计。其次,我们推导了一种闭合形式的近似BER公式,该公式已被证明具有很高的精确度,适用于将继电器紧密放置以减少仿真时间的典型网络拓扑。各种结果表明,信道估计误差会大大降低底层认知网络中中继选择的性能,并完全破坏其分集增益。另外,增加所涉及的继电器的数量可以极大地弥补其影响。

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