Visible Light Communication Using Deep Learning Techniques

Abstract

Deep learning (DL) techniques have the potential of making communication systems more efficient and solving many problems in the physical layer. In this paper, an optical wireless communications (OWC) system based on visible light communications (VLC) technology is implemented using an autoencoder (AE). The proposed system is tested in different scenarios using various AE parameters and applied on an indoor VLC model. Bit error rate (BER) is evaluated with respect to the signal-to-noise-ratio (SNR) values at different locations within the room. To validate the proposed system, theoretical results are compared to the simulated values. The bit-error performance demonstrates the viability of DL techniques in VLC systems.