Deep learning-based detection scheme for visible light communication with generalized spatial modulation.

Abstract

In this paper, a deep learning-based detection scheme is proposed for the visible light communication (VLC) systems using generalized spatial modulation (GenSM). In the proposed detection scheme, a deep neural network consisting of several neural layers is applied to detect the received signals. By integrating the signal processing modules of the conventional detection schemes into one deep neural network, the proposed scheme is able to extract the information bits from the received signals efficiently. After offline training, the proposed detection scheme can serve as a promising detection method for the VLC system with GenSM. Simulation results validate that the proposed detection scheme is capable of achieving superior detection error performance than conventional detection schemes at acceptable complexity.