Long Short-Term Memory Neural Network to Enhance the Data Rate and Performance for Rolling Shutter Camera Based Visible Light Communication (VLC)

Abstract

We propose and demonstrate using Long-Short-Term-Memory neural-network (LSTM-NN) to mitigate inter-symbol-interference (ISI) in 4-level pulse-amplitude-modulation (PAM4) camera based visible-light-communication (VLC) system. Data-rate of 14.4-kbit/s with 3-m free-space transmission is achieved.

Neural Network Equalizer in Visible Light Communication: State of the Art and Future Trends

“…used to solve nonlinear problems (Khan et al, 2017). Among these methods, using neural networks as equalizers to compensate for signal impairment is one of the most important aspects of physical layer communication, especially for VLC (Haigh et al, 2014;Lin et al, 2021;Peng et al, 2022). In 5G, channel equalization is achieved through zero-forcing equalization based on pilot sequences.…”