Multiuser Cognitive Networks with Nth-Best User Selection and Imperfect Channel Estimation

Abstract

The Nth-best user selection scheme is efficient in outdated channel information conditions where the user that was the best at the selection time instant could not be the best at the transmission time instant. Also, this scheme is useful when the scheduling unit fails in error in selecting the best user among all the available users. Furthermore, the Nth-best user selection scheme is efficient in situations where, while the best user is waiting to be scheduled by a certain base station or a scheduling unit, it gets scheduled by other unit. In the proposed scheme, the secondary user with the Nth-best end-to-end signal-to-noise ratio (SNR) is scheduled the system resources. In our paper, closed-form expressions are derived for the outage probability, average symbol error probability, and ergodic channel capacity assuming imperfect estimation of channel state information and Rayleigh fading channels. Furthermore, to further analyze the system performance, the system is studied at 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 multiuser cognitive Nth-best user selection network is the same as its non-cognitive counterpart. Also, findings show that with perfect channel estimation of secondary users, the diversity order of the system linearly increases with decreasing the order of the scheduled user, and vice versa, whereas a zero diversity gain is achieved by the system and a noise floor appears in the results when the channels of secondary users are imperfectly estimated assuming constant estimation error variance. Finally, results illustrate that the imperfect estimation of the secondary cell-primary cell channel affects only the coding gain of the system without affecting the diversity order.