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.     

Pragmatic physical layer abstraction method based on bit-LLR-wise exponential effective SNR mapping for bit interleaved coded orthogonal frequency division multiplexing system

In this paper, we analyze the physical layer abstraction for bit interleaved coded orthogonal frequency division multiplexing （BIC-OFDM） system from a parallel bit channel perspective. By combining the exponential effective SNR （signal-to-noise ratio） mapping （EESM） with the maximum a posteriori （MAP） algorithm, a bit LLR （log-likelihood ratio） wise EESM （BL-EESM） method is proposed. This method can abstract the link performance with high accuracy, especially for the case when channel estimation is imperfect. Afterward, the BL-EESM method is simplified by utilizing the non-linear quantization idea, which can reduce the times of exponential operation by two orders of magnitude at wide system bandwidth, yet shows little loss in accuracy. Our proposal can be applied to both system level simulations to save the time consumption and to practical terminals to facilitate the adaptive modulation and coding （AMC） procedure, bringing about throughput improvement at low hardware cost.