Cognitive beamforming exploiting spatial opportunity is an attractive technique for secondary users to coexist with primary users in cognitive radio environments. If perfect channel state information of the interfering link is available, interference from a secondary transmitter to a primary receiver can be perfectly pre-nulled by choosing the ideal transmit beam. In practice, however, there is channel estimation error due to noise and the time-varying channels. To minimize the residual interference due to those channel estimation errors, channel prediction based on auto regressive (AR) model is introduced in this paper. Further, to cope with extremely rapidly-varying channels, a cognitive transmit power control technique is proposed as well. By combining channel prediction and transmit power control in cognitive beamforming, the cognitive users can share the spectrum with the primary users with a limited interference level in time-varying channels.

This paper proposes an opportunistic feedback and user selection method for a multiuser two-way relay channel (MU-TWRC) in a time-varying environments where a base station (BS) and a selected mobile station (MS), one of K moving MSs, exchange messages during two time slots via an amplify-and-forward relay station. Specifically, under the assumption of perfect channel reciprocity, we analyze the outage probabilities of several channel feedback scenarios, including the proposed scheme. Based on the analysis, the transmission rates are optimized and the optimal user selection method is proposed to maximize the expected sum throughput. The simulation results indicate that, with opportunistic feedback, the performance can be significantly improved compared to that without feedback. Moreover, the performance is nearly identical to that with full feedback, and close to the case of perfect channel state information at BS for low mobility MSs.