摘要
This Letter proposes a post-equalizer for underwater visible light communication(UVLC) systems that combines channel estimation and joint time-frequency analysis, named channel-estimation-based bandpass variable-order time-frequency network(CBV-TFNet). By utilizing a bandpass variable-order loss function with communication prior knowledge, CBVTFNet enhances communication performance and training stability. It enables lightweight implementation and faster convergence through a channel estimation-based mask. The superior performance of the proposed equalization method over Volterra and deep neural network(DNN)-based methods has been studied experimentally. Using bit-power loading discrete multitone (DMT) modulation, the proposed method achieves a transmission bitrate of 4.956 Gbps through a 1.2 m underwater channel utilizing only 38.15% of real multiplication calculations compared to the DNN equalizer and achieving a bitrate gain of440 Mbps and a significantly larger dynamic range over the LMS-Volterra equalizer. Results highlight CBV-TFNet's potential for future post-equalization in UVLC systems.
作者
Haoyu Zhang
Li Yao
Chaoxu Chen
Yuan Wei
Chao Shen
Jianyang Shi
Junwen Zhang
Ziwei Li
Nan Chi
张昊宇;姚力;陈超旭;魏圆;沈超;施剑阳;张俊文;李子薇;迟楠(Key Laboratory for Information Science of Electromagnetic Waves(MoE),Department of Communication Science and Engineering,School of Information Science and Technology,Fudan University,Shanghai 200433,China;Shanghai CIC of LEO Satellite Communication Technology,Fudan University,Shanghai 200433,China;Shanghai ERC of LEO Satellite Communication and Application,Fudan University,Shanghai 200433,China)
基金
supported by the National Key Research and Development Program of China (No. 2022YFB2802803)
the National Natural Science Foundation of China (Nos. 61925104, 62031011, and 62201157)。
