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 (Ibias) of light-emitting diode (LED), which indicates that TL-DBMLP does not require further training in Ibias varying UVLC system. In terms of voltage peak-to-peak (Vpp) varying VLC system, DBMLP requires a training set with a size of more than 105 and 50 training epochs, which quantitatively prove the effectiveness of DBMLP in reducing reliance on large amount of training epochs. On the counterpart, the TL-DBMLP only requires a training set with a size of less than 2×104 and 10 training epochs, which quantitatively prove the effectiveness of DBMLP in reducing reliance on big data. Finally, we experimentally demonstrate that transfer learning can effectively reduce ANN dependence on extensive size training data and large amount of training epochs, whether in VLC systems with varying Ibias and varying Vpp.
Highlights
The limited bandwidth of traditional communication systems has always been a major problem that hinders human exploration and marine resources development
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
In this article, based on preliminary work, we propose two transfer learning–based artificial neural networks (ANN) post-equalizers named as TLDBMLPs (TL-DBMLP-I and TL-DBMLP-V) (Zhao et al, 2019a; Zhao et al, 2019b)
Summary
The limited bandwidth of traditional communication systems has always been a major problem that hinders human exploration and marine resources development. With the in-depth research of scientific research organizations in visible light communication (VLC), many scientists have noticed the potential of VLC in underwater applications (Chi et al, 2018; Oubei, 2018; Zhao et al, 2020). Because of the skin effect of wireless communication in the underwater environment, long-distance high-speed wireless communication cannot be realized. Green and blue light is just located in the transmission window of seawater, which indicates the potential of VLC to realize long-distance and high speed UVLC. To achieve Gbps-level wireless communication at a distance greater than 100 m underwater, it is necessary to introduce UVLC into the field of underwater wireless communication. To improve the efficiency of spectrum utilization and increase the system data rate, we have adopted high-order modulation, CAP64. High-order modulated signals have higher requirements for signal-to-noise ratio (SNR), which poses challenges to the performance of post-equalization algorithms
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