An efficient switching threshold-based scheduling protocol for multiuser cognitive AF relay networks

The multiuser switched diversity (MUSwiD) selection scheme is useful in reducing the required amount of channel estimations and system complexity in wireless networks. In this paper, we propose and evaluate the performance of cognitive amplify-and-forward (AF) MUSwiD relay networks where a cognitive user is selected among a set of users for data reception. The selection process is performed such that the end-to-end (e2e) signal-to-noise ratio (SNR) of the selected user satisfies a predetermined switching threshold. An upper bound on the e2e SNR of a user is used in deriving closed-form approximations for the outage probability and average symbol error probability (ASEP) of the studied system. To get more insights about the system performance, the behavior is studied in the high SNR regime. The derived analytical and asymptotic expressions are verified by Monte-Carlo simulations. Main results illustrate that the diversity order of the studied cognitive AF multiuser switched diversity relaying network is the same as its non cognitive counterpart. Also, findings show that the asymptotic results tightly converge to the derived bounds and the analytical bounds are indeed very tight, validating the accuracy of our methodology. Finally, results show the effectiveness of the proposed MUSwiD scheduling scheme in reducing the channel estimation load compared to the opportunistic scheduling where the best user is always assigned the system resources.