In this paper, we propose an orthogonal frequency division multiplexing (OFDM)-based generalized optical quadrature spatial modulation (GOQSM) technique for multiple-input multiple-output optical wireless communication (MIMO-OWC) systems. Considering the error propagation and noise amplification effects when applying maximum likelihood and maximum ratio combining (ML-MRC)-based detection, we further propose a deep neural network (DNN)-aided detection for OFDM-based GOQSM systems. The proposed DNN-aided detection scheme performs the GOQSM detection in a joint manner, which can efficiently eliminate the adverse effects of both error propagation and noise amplification. The obtained simulation results successfully verify the superiority of the deep learning-aided OFDM-based GOQSM technique for high-speed MIMO-OWC systems.
@article{arxiv.2106.12770,
title = {Deep Learning-Aided OFDM-Based Generalized Optical Quadrature Spatial Modulation},
author = {Chen Chen and Lin Zeng and Xin Zhong and Shu Fu and Min Liu and Pengfei Du},
journal= {arXiv preprint arXiv:2106.12770},
year = {2021}
}