Aiming at the problem of optical intensity fluctuation under strong turbulence in underwater visible light communication, a beamforming algorithm based on maximum ratio combining is proposed. Through space diversity, the received signals are combined through different paths, and a beamforming optimization model with the goal of maximizing the signal-to-noise ratio is established to solve the optimal beamforming vector to form the target beam and overcome the influence of strong turbulence channel fading. The simulation results show that at a bit error rate of 10−6 , compared with a system without use the beamforming algorithm, the signal-to-noise ratio of the system is reduced by about 5dB.
Aiming at the problem that the great spatial correlation between sub-channels of the underwater visible light MIMO system affects the system's error performance, a precoding algorithm based on lattice reduction is proposed. The lattice reduction algorithm makes the channel matrix more orthogonal through iterative reduction operations. The transformation matrix is used as the precoding matrix to precode the transmitted signal, which is equivalent to transmit the original signal on the channel with less correlation. It can be used for transmission to improve the signal detection performance of the system. The lattice reduction algorithm is further combined with the linear precoding algorithm to compensate for the amplification of noise caused by linear detection at the receiving end, so that the system has better error performance. The simulation results show that at a bit error rate of 10-4, compared with a system without precoding, the required signal-to-noise ratio of the system using the lattice reduction precoding algorithm is reduced by about 10dB, compared with the traditional minimum mean square error precoding, the required signal-to-noise ratio of the system using the minimum mean square error precoding based on lattice reduction is reduced by about 6dB.
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