基础认知网络中主动中继选择的误码率分析

H. Khuong, V. Son, L. Tra, P. Liên
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引用次数: 0

摘要

针对信道信息不完善(CII)、最大发射功率约束、干扰功率约束、独立非同瑞利衰落分布和任意调制水平的认知网络中主动中继选择(PRS)问题,提出了一种误码率分析框架。该分析提供了精确和渐近的误码率表达式,这有助于快速评估系统性能,而无需耗时的模拟,并提供重要的性能指标,如分集顺序。大量结果表明,CII显著提高了PRS的误码率,并完全消除了PRS的分集顺序。然而,CII的影响可以通过增加继电器的数量来显著减轻。
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 proactive relay selection in underlay cognitive networks
This paper proposes a BER (bit error rate) analysis framework for proactive relay selection (PRS) in underlay cognitive networks with channel information imperfection (CII), maximum transmit power constraint, interference power constraint, independent non-identical (i.n.i) Rayleigh fading distributions, and arbitrary modulation level. The analysis provides exact and asymptotic BER expressions, which facilitate in promptly evaluating system performance without time-consuming simulations and providing important performance metrics such as diversity order. Numerous results illustrate that CII considerably increases the BER of the PRS and completely eliminates its diversity order. However, the effect of CII can be significantly mitigated by increasing the number of relays.
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