Research on Vehicle-to-Vehicle 2×n MIMO-VLC System Based on an Improved Genetic Algorithm

This paper proposes a vehicle-to-vehicle
$2 \times n$
MIMO-VLC system model based on an improved genetic algorithm to achieve the purpose of improving the bit error rate (BER) performance of vehicle-to-vehicle visible light commutations systems in the presence of interfering vehicles. The model uses two headlights of the car as transmitters and
$n$
photoelectric detectors (PD) as receivers. In the presence of interfering vehicles, the improved genetic algorithm was used to optimize the light sensitive area parameters and the half angle of field of view parameters of the
$n$
PDs, and then the signal-to-noise ratios received by the
$n$
PDs with optimized structural parameters were processed using the maximum ratio merging method to finalize the data reception. The results of the study show that the vehicle-to-vehicle MIMO-VLC system model using improved genetic algorithm to optimize the PD structural parameters has a positive effect in reducing the system BER and the degree of BER fluctuation.