Abstract
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.
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