Design of PAM-8 VLC Transceiver System Employing Neural Network-Based FFE and Post-Equalization

Wireless communication technology adopting electromagnetic waves in an unlicensed spectrum, such as visible light, for has attracted wide research efforts. Visible light (VLC) utilizes a medium to transmit signals but faces limited bandwidth and low data rate, which is caused by the intrinsic characteristics of LEDs. This paper first studies mathematical model its effect on transmitted then analyzes free space underwater channel loss. With theoretical analysis, VLC transceiver system presented solving limitation utilizing pulse-amplitude modulation-8 (PAM-8) scheme hybrid equalization method. The proposed combined passive equalizer, neural network (NN)-based feed-forward (FFE), radial basis function (RBF-NN). feasibility this was verified through co-simulation platform with both free-space channels. Compared deep (DNN)-based post-equalization method, could achieve rate 3.6 Gbps bit error (BER) 3.8 × 10−3 over 3 m channel. RBF-NN achieved reduced training time 10 min, 86.7% lower than conventional DNN-based