Robust optimization for the correlated MIMO downlink with imperfect channel state information

To reduce the performance deterioration induced by imperfect channel state information (CSI) in cor-related multiple input multiple output(MIMO) downlink, the linear transmit/receive filters should be optimized to be robust to imperfect CSI. A sub-optimization algorithm based on minimizing sum MSE conditional on available imperfect CSI estimates subject to a per-user power constraint is proposed. The algorithm adapts the existing MMSE algorithm from uncorrelated single-user MIMO system with perfect CSI to correlated MIMO downlink with imperfect CSI. Simulation shows that the suboptimal algorithm can effectively mitigate the performance loss induced by imperfect CSI and has a good convergence performance. In addition, the effect of spatial correlation on the performance of the proposed algorithm is also simulated.     

Lattice reduction aided MMSE Tomlinson-Harashima precoding based on VBLAST algorithm for MIMO systems

A lattice reduction aided （LRA） minimum mean square error （MMSE） Tomlinson-Harashima precoding （THP） was proposed based on vertical Bell Labs layered space time （VBLAST） algorithm for multiple input multiple output （MIMO） systems. The extended channel was used to provide optimal tradeoff between residual interference and noise amplification. The processing based on lattice reduction method helps achieve maximal diversity order. The VBLAST algorithm was applied to get the optimal processing ordering for successive interference cancellation （SIC） at transmitter. Simulation results show that the proposed algorithm outperforms conventional THP and the LRA zero-forcing （ZF） THP with full diversity order.     

A Novel Iterative Receiver Based on Extrinsic Information Update for MIMO Systems

A novel iterative receiver for multiple input multiple output (MIMO) systems was introduced. Its basis concept is that the reliability of extrinsic information will be strengthened with continuous iterations. Extrinsic information of present iteration is added with prior information of last iteration to obtain performance gain. The simulation results show that the improved iterative receiver can approach the 5th iteration performance of conventional soft interference cancellation (SIC)-minimum mean square error (MMSE) iterative receiver after the 2nd iteration with less computational complexity. Compared with conventional iterative receiver, the improved iterative receiver has 1dB performance gain at bit error rate (BER) of 10~ -5 , with four transmit antennas and four receive antennas system.