Precoding Optimization Algorithm for Visible Light Communication Based on Lattice Reduction

To tackle the issue of strong spatial correlation among sub-channels caused by the implementation of multiple-input multiple-output (MIMO) technology in indoor visible light communication (VLC) systems, which consequently leads to inter-channel interference, a comprehensive solution is proposed. This solution aims to jointly enhance channel transmission quality by seamlessly integrating the lattice reduction algorithm with the minimum mean square error (MMSE) algorithm. Through the application of lattice reduction, the channel matrix is transformed into an equivalent form with significantly improved orthogonality. Additionally, the utilization of the MMSE criterion effectively reduces spatial correlation within the MIMO channel, resulting in superior bit error rate (BER) performance compared to the traditional MMSE precoding approach. Simulation results reveal that this scheme effectively mitigates spatial correlation within the channel. Notably, the BER performance of a 2×2 system surpasses that of a 4×4 system. Specifically, for the 4×4 system, when the BER attains a level of 10–3, the signal-to-noise ratio (SNR) is reduced by approximately 3 dB in comparison to the conventional MMSE precoding technique.