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Deep Learning-Aided OFDM-Based Generalized Optical Quadrature Spatial Modulation

2021-06-24 · Chen Chen, Lin Zeng, Xin Zhong, Shu Fu, Min Liu, Pengfei Du

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.

📄 PDF Abstract BibTeX arXiv:2106.12770

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Deep Learning

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