Convex-optimization-based precoding for MIMO downlinks

In this paper, the design of linear leakage-based precoders is considered for multiple-input multiple-output (MIMO) downlinks. Our proposed scheme minimizes total transmit power under each user's signal-to-leakage-plus-noise ratio (SLNR) constraint. When the base station knows perfect channel state information (CSI), suitable reformulation of design problem allows the successful application of semidefinite relaxation (SDR) techniques. When the base station knows imperfect CSI with limited estimation errors, the design problem can be solved using semidefinite program (SDP). At the same time, it can dynamically allocate each user's SLNR threshold according to each user's channel state, so it is more feasible than other similar SINR-based precoding methods. Simulation results show that using large SLNR thresholds, the proposed design has better bit error rate (BER) performance than maximal-SLNR precoding method at high signal-to-noise ratio (SNR). Moreover, when the base station knows imperfect channel state information, the proposed precoder is robust to channel estimation errors, and has better BER preformance than other similar SINR-based precoding methods.