Improved Low-Complexity Demodulation: Integrating Minimum-Mean-Square-Error and Maximum-Likelihood Detection for Image-Sensor-Based Visible Light Communication

Abstract

This study proposes an improved low-complexity signal demodulation method for a visible light communication (VLC) system with an image sensor as a receiver and light-emitting diode (LED) transmitters. Signal demodulation by VLC systems is challenging when image sensors are used as receivers because of defocusing. The traditional maximum likelihood detection (MLD)-based demodulation, although effective, incurs high computational costs, restricting its use in real-time applications. To address these limitations, this study introduces an improved error signal candidate selection algorithm that focuses on residual signals and channel matrix characteristics to refine the signal estimation result. Through iterative refinement using low-complexity detectors such as those based on zero-forcing (ZF), and minimum-mean-square error (MMSE), our method substantially narrows the search space for the MLD, thus striking a balance between demodulation performance and computational efficiency. The proposed method was validated through laboratory experiments to demonstrate substantial performance gains over existing techniques. Thus, this method advances the field of VLC demodulation, particularly for systems with image sensors.