Abstract
In free space optical (FSO) communication system, the maximum likelihood (ML) is the optimum detector considering perfect channel state information (CSI) at receiver. However, the ML does not provide a proper performance in imperfect CSI scenario. Therefore, a deep learning based detection method is proposed in this paper. In this paper, we use deep neural network to get a mapping function of a received signal and transmitted symbol streams. Moreover, the end-to-end approach using deep learning with the conventional ML method is compared for both perfect and imperfect scenarios. Simulation results show that our method presents a better performance compared to the conventional ML method in imperfect CSI. Moreover, our proposed method reaches the same performance as the ML detector in perfect CSI.
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