• Chinese Optics Letters
  • Vol. 17, Issue 10, 100011 (2019)
Nan Chi* and Fangchen Hu
Author Affiliations
  • Shanghai Institute for Advanced Communication and Data Science, Key Laboratory for Information Science of Electromagnetic Waves (MoE), Fudan University, Shanghai 200433, China
  • show less
    DOI: 10.3788/COL201917.100011 Cite this Article Set citation alerts
    Nan Chi, Fangchen Hu, "Nonlinear adaptive filters for high-speed LED based underwater visible light communication [Invited]," Chin. Opt. Lett. 17, 100011 (2019) Copy Citation Text show less
    Nonlinear response of the UVLC system in the time domain and frequency domain.
    Fig. 1. Nonlinear response of the UVLC system in the time domain and frequency domain.
    Schematic diagram of the RLS-based Volterra filter.
    Fig. 2. Schematic diagram of the RLS-based Volterra filter.
    Schematic diagram of the LMS-based DP filter.
    Fig. 3. Schematic diagram of the LMS-based DP filter.
    Schematic diagram of the LMS-based Volterra filter.
    Fig. 4. Schematic diagram of the LMS-based Volterra filter.
    Computational complexity versus number of taps.
    Fig. 5. Computational complexity versus number of taps.
    Block diagram of the UVLC system.
    Fig. 6. Block diagram of the UVLC system.
    BER performance versus bandwidth and number of taps for different nonlinear adaptive filters in the UVLC system.
    Fig. 7. BER performance versus bandwidth and number of taps for different nonlinear adaptive filters in the UVLC system.
    Time-domain waveform comparison of the transmitted signal and received signal after the nonlinear adaptive filter and the DNN proposed by Ref. [3].
    Fig. 8. Time-domain waveform comparison of the transmitted signal and received signal after the nonlinear adaptive filter and the DNN proposed by Ref. [3].
    Spectral response of (a) transmitted signal, (b) received signal without nonlinear equalization, (c) signal with RLS–Volterra nonlinear equalization, (d) signal with LMS–Volterra nonlinear equalization, (e) signal with LMS–DP nonlinear equalization, and (f) signal with the DNN proposed by Ref. [3].
    Fig. 9. Spectral response of (a) transmitted signal, (b) received signal without nonlinear equalization, (c) signal with RLS–Volterra nonlinear equalization, (d) signal with LMS–Volterra nonlinear equalization, (e) signal with LMS–DP nonlinear equalization, and (f) signal with the DNN proposed by Ref. [3].
    Error convergence curve of the RLS–Volterra and LMS–Volterra filters.
    Fig. 10. Error convergence curve of the RLS–Volterra and LMS–Volterra filters.
    BER versus bandwidth for the VLC and UVLC systems.
    Fig. 11. BER versus bandwidth for the VLC and UVLC systems.
    AlgorithmOutputUpdate
    RLS–VolterraNlinear+Nnonlinear(Nnonlinear+1)2·24Nlinear+3Nlinear2+3NlinearNnonlinear+6NlinearNnonlinear2+6NlinearNnonlinear3+6NlinearNnonlinear4+4Nlinear3+6Nlinear2Nnonlinear+6Nlinear2Nnonlinear2+2Nnonlinear+114Nnonlinear2+2Nnonlinear3+94Nnonlinear4+32Nnonlinear5+12Nnonlinear6
    LMS–DPNlinear+Nnonlinear·2Nlinear+1+Nnonlinear+1
    LMS–VolterraNlinear+Nnonlinear(Nnonlinear+1)2·2Nlinear+1+Nnonlinear(Nnonlinear+1)2+1
    Table 1. Computational Complexity
    Nan Chi, Fangchen Hu, "Nonlinear adaptive filters for high-speed LED based underwater visible light communication [Invited]," Chin. Opt. Lett. 17, 100011 (2019)
    Download Citation