AUTHOR=Zhao Yiheng , Yu Shaohua , Chi Nan TITLE=Transfer Learning–Based Artificial Neural Networks Post-Equalizers for Underwater Visible Light Communication JOURNAL=Frontiers in Communications and Networks VOLUME=2 YEAR=2021 URL=https://www.frontiersin.org/journals/communications-and-networks/articles/10.3389/frcmn.2021.658330 DOI=10.3389/frcmn.2021.658330 ISSN=2673-530X ABSTRACT=
In this article, we demonstrate two transfer learning–based dual-branch multilayer perceptron post-equalizers (TL-DBMLPs) in carrierless amplitude and phase (CAP) modulation-based underwater visible light communication (UVLC) system. The transfer learning algorithm could reduce the dependence of artificial neural networks (ANN)–based post-equalizer on big data and extended training cycles. Compared with DBMLP, the TL-DBMLP is more robust to the jitter of the bias current (