信道信息不完全条件下具有中继选择的底层协同认知网络性能研究

Khuong Ho‐Van
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引用次数: 2

摘要

在考虑主中断约束、最大发射功率约束和信道估计误差的情况下,研究了底层协同认知网络中无功中继选择方案的中断性能。为了消除耗时的模拟,我们为未授权用户提出了一个精确的闭式中断概率表达式。几个结果验证了它的有效性,并说明了相对于继电器数量的增加,由于信道信息不完善而导致的显着性能下降以及系统性能饱和,显著的性能增强。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
On the performance of underlay cooperative cognitive networks with relay selection under imperfect channel information
This paper studies the outage performance of the reactive relay selection scheme in underlay cooperative cognitive networks, taking into account primary outage constraint, maximum transmit power constraint, and channel estimation error. To eliminate time-consuming simulations, we propose an exact closed-form outage probability expression for unlicensed users. Several results verify its validity and illustrate considerable performance enhancement with respect to the increase in the number of relays, significant performance degradation due to imperfect channel information, as well as system performance saturation.
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