Abstract

In this paper, we propose a low complexity lattice reduction aided (LRA) minimum mean square error (MMSE) precoding design for multiple input multiple output (MIMO) systems. We exploit the extended channel to implement the MMSE approach and obtain an optimal tradeoff between noise amplification and residual interference. Three schemes with linear and nonlinear processing are provided based on the lattice reduction method. Simulation results show the proposed schemes significantly outperform the conventional MMSE Tomlinson- Harashima precoding (THP) and the LRA zero-forcing (ZF) precoding. Interestingly, higher diversity order than the LRA ZF precoding is achieved. Moreover, our schemes perform not worse than the LRA MMSE vector precoding (VP) schemes.

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