4.5 Article

3.2 Gbps underwater visible light communication system utilizing dual-branch multi-layer perceptron based post-equalizer

期刊

OPTICS COMMUNICATIONS
卷 460, 期 -, 页码 -

出版社

ELSEVIER
DOI: 10.1016/j.optcom.2019.125197

关键词

Artificial neural network; LED; Visible light communication; Underwater

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资金

  1. National Key Research and Development Program of China [2017YFB0403603]
  2. NSFC [61925104]

向作者/读者索取更多资源

In this paper, we demonstrate a novel dual-branch multi-layer perceptron (DBMLP) based post-equalizer(PE). Since the two branches of the DBMLP can compensate linear and nonlinear distortion in the received signal, respectively, the complexity of the neural network is reduced and the performance of the post-equalizer is improved. Compared with multi-layer perceptron (MLP) based PE the space complexity of DBMLP based PE reduces 59.5%, and the bit error rate (BER) at 3.1 Gbps reduces 45.5%. The reduction of spatial complexity helps the application of post-equalizer based on neural network algorithms in practical communication systems. Meanwhile, increased BER performance helps underwater visible light communication (UVLC) systems reach higher rates. We achieved 3.2Gbps in the 64 quadrature amplitude modulation (64QAM)-carrierless amplitude and phased modulation (CAP) modulated UVLC system using DBMLP based PE. To the best of our knowledge, this is the highest record of data rate in the field of one single chip blue LED based UVLC system.

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