Simulation and Comparison of Lightweight Channel Coding Schemes for Low-Cost Indoor Visible Light Communication Systems

Abstract

Indoor visible light communication (VLC) systems for Internet of Things (IoT) applications face stringent computational constraints, which render high-complexity channel coding impractical, leaving these networks highly vulnerable to channel noise. To address this limitation, this study proposes a lightweight cascaded coding scheme that strikes a practical balance between interference resilience and computational efficiency. The scheme incorporates an inner convolutional code for random noise, an outer Hamming code for correction of random code errors, and an interleaver to scatter burst errors. End-to-end physical layer simulations are conducted at data rates from 1 to 100 Mbps. Results indicate that indoor VLC channels are mainly dominated by additive noise rather than multipath, as the line-of-sight component accounts for 98.51% of total signal energy. The proposed scheme achieves 8.7 dB coding gain relative to the uncoded baseline at a bit error rate of 10~ 5 . By increasing computational overhead slightly, its performance is largely higher than that of independent lightweight coding schemes. Overall, the cascaded coding scheme overcomes the limited error-correction capability of single coding schemes while ensuring reliable transmission even under extremely low signal-to-noise ratios, thus providing a feasible transmission framework for indoor IoT applications.