Optimizing Optical Wireless Communication Sender Alignment Using Extended Gene Density Genetic Algorithm for Minimizing SNR Fluctuation

Abstract

Optical wireless communication (OWC) systems utilize light-emitting diode (LED) lamps as transmitters to encode data into light, while photo-detectors act as receivers to collect the transmitted data. However, improper alignment of LED lamps can lead to non-uniform signal-to-noise ratio (SNR) distribution across the application area, with SNR power being significantly lower in the corners compared to other sub-areas of the room. To address this issue, this work employs the extended gene density genetic algorithm (EGDGA) to minimize SNR fluctuation in indoor OWC applications. Unlike traditional fixed geometry LED alignment, the EGDGA dynamically adjusts the positions of the LED lamps to achieve optimal alignment with minimal SNR fluctuation. The EGDGA leverages real-value encoding to minimize processing overhead and enable continuous representation of LED lamp locations. It initializes a pool of genes and chromosomes to ensure solutions remain within the feasible region. The algorithm employs a binary tournament selection (TS) technique to maintain population diversity, allowing even low-fitness chromosomes to participate in subsequent generations. Additionally, a death penalty mechanism eliminates duplicate chromosomes, promoting more consistent and effective solutions. This approach enhances illumination, channel gain, and SNR distribution across the application plane, including the corners, and significantly reduces SNR fluctuation compared to fixed geometry alignment. Simulation results demonstrate that the EGDGA outperforms fixed alignment by achieving higher uniformity and fairer distribution of SNR across the application area. For a four-LED setup, the SNR uniformity values were 0.22 for fixed alignment and 0.70 for the EGDGA optimization. Similarly, for a sixteen-LED setup, the SNR uniformity values were 4.24 for fixed alignment and 5.07 for the EGDGA optimization. Ultimately, the EGDGA methodology improves the characteristics of the OWC channel, offering superior transmission performance compared to fixed alignment techniques.