Performance of Transmit Optimization for Two-Input Multiple-Output Spatial Multiplexing

A two-input multiple-output (TIMO) system represents an important special case of multiple-input multiple-output (MIMO) systems. In this paper, performance of transmit optimization for TIMO spatial multiplexing systems is investigated. Efforts to optimize TIMO transmission have involved minimum mean squared-error (MMSE) precoding and decoding, minimum bit error rate (MBER) precoding for zero-forcing (ZF) receiver, minimum distance (MD) precoding for maximum-likelihood (ML) receiver, approximate MBER transmit power allocation, and approximate MBER transmit beamforming. It is shown both analytically and by simulations that power allocation together with interference cancellation and detection ordering outperforms both linear MMSE and ZF-MBER precoding, and ML-MD precoding and transmit beamforming eliminate error floors in ill-conditioned channels and offer superior performance over both power allocation and linear precoding/decoding methods