不完全Nakagami-m衰落信道信息下中继认知网络的误码分析

Khuong Ho‐Van
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引用次数: 0

摘要

在考虑最大发射功率约束(MTPC)和干扰功率约束(IPC)的情况下,研究了不完全Nakagami-m衰落信道信息对任意跳数中继认知网络(URCNs)误码率性能的影响。为了消除耗时的模拟,我们提出了一个精确的封闭形式的误码率表达式。各种结果证明了该方法的有效性,并显示了URCNs的性能饱和。此外,信道信息不完全性(CII)、不同最大发射功率(MTP)水平的辅助用户的定位顺序以及辅助中继的最佳位置对其性能有显著影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
BER analysis of underlay relay cognitive networks with imperfect Nakagami-m fading channel information
This paper studies the effect of imperfect Nakagami-m fading channel information on the bit error rate (BER) performance of underlay relay cognitive networks (URCNs) with arbitrary number of hops, taking into account both maximum transmit power constraint (MTPC) and interference power constraint (IPC). To eliminate time-consuming simulations, we propose an exact closed-form BER expression. Various results demonstrate its validity and show the performance saturation of URCNs. Additionally, channel information imperfection (CII), the order of locating secondary users of different maximum transmit power (MTP) levels, and optimum positions of secondary relays dramatically affect their performance.
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