Improving Performance for DCO-OFDM Based VLC via Convolutional Coding and Viterbi Decoding

The reliability of Visible Light Communication (VLC) is affected by several parameters, the most significant being high peak-to-average power ratio(PAPR) and nonlinear distortion. This study presents an adaptive direct current O-OFDM (DCO-OFDM) based VLC system as a solution, which integrates error correction the Convolutional coding and Viterbi decoding (by hard and soft decision methods) with a PAPR reduction technique that combines Vandermonde-like Matrix (VLM) precoding with a nonlinear companding transform (NCT). This proposed system enhances resistance to channel impairments, thereby reducing BER while maintaining the gains of PAPR reduction. Moreover, examined the system under realistic VLC propagation conditions both Line Of Site (LOS) and nonline Of Site (NLOS) channel, with Rapps model that employed to represent the linear and nonlinear behavior of LED. The simulation results confirm that the proposed system gives improved BER performance compared to conventional systems by achieving in the beast case under LOS channel an SNR gain of approximately 6.5 dB at a target BER of 10-4 represents the highest improvement with soft decision Viterbi decoding and about 4.5 dB at a target BER of 10-4 with hard decision Viterbi decoding,and approximately the same coding gain under NLOS channel, result indicate soft decision outperforming hard decision decoding under both linear and nonlinear LED behavior by achieves approximately 1 dB greater coding gain and System under NLOS channel have worst BER performance due to multipath reflections. however, This proposed system effectively maintains the advantages of PAPR reduction techniques, thereby achieving a balance between efficiency and reliability.