Nonlinear adaptive filters for high-speed LED based underwater visible light communication [Invited]

Nan Chi; Fangchen Hu

doi:doi:10.3788/COL201917.100011

Chinese Optics Letters, 2019, 17 (10): 100011, Published Online: Oct. 15, 2019

Nonlinear adaptive filters for high-speed LED based underwater visible light communication [Invited] Download： 799次

Nan Chi ^*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

Figures & Tables

Fig. 1. Nonlinear response of the UVLC system in the time domain and frequency domain.

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Fig. 7. BER performance versus bandwidth and number of taps for different nonlinear adaptive filters in the UVLC system.

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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].

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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].

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Fig. 10. Error convergence curve of the RLS–Volterra and LMS–Volterra filters.

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Fig. 11. BER versus bandwidth for the VLC and UVLC systems.

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Table1. Computational Complexity

Algorithm	Output	Update
RLS–Volterra	$N_{linear} + \frac{N_{nonlinear} (N_{nonlinear} + 1)}{2} \cdot 2$	$4 N_{linear} + 3 {N_{linear}}^{2} + 3 N_{linear} N_{nonlinear} + 6 N_{linear} {N_{nonlinear}}^{2} + 6 N_{linear} {N_{nonlinear}}^{3} + 6 N_{linear} {N_{nonlinear}}^{4} + 4 {N_{linear}}^{3} + 6 {N_{linear}}^{2} N_{nonlinear} + 6 {N_{linear}}^{2} {N_{nonlinear}}^{2} + 2 N_{nonlinear} + \frac{11}{4} {N_{nonlinear}}^{2} + 2 {N_{nonlinear}}^{3} + \frac{9}{4} {N_{nonlinear}}^{4} + \frac{3}{2} {N_{nonlinear}}^{5} + \frac{1}{2} {N_{nonlinear}}^{6}$
LMS–DP	$N_{linear} + N_{nonlinear} \cdot 2$	$N_{linear} + 1 + N_{nonlinear} + 1$
LMS–Volterra	$N_{linear} + \frac{N_{nonlinear} (N_{nonlinear} + 1)}{2} \cdot 2$	$N_{linear} + 1 + \frac{N_{nonlinear} (N_{nonlinear} + 1)}{2} + 1$

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Nan Chi, Fangchen Hu. Nonlinear adaptive filters for high-speed LED based underwater visible light communication [Invited][J]. Chinese Optics Letters, 2019, 17(10): 100011.

Nonlinear adaptive filters for high-speed LED based underwater visible light communication [Invited] Download： 799次

Fig. 1. Nonlinear response of the UVLC system in the time domain and frequency domain.

Fig. 2. Schematic diagram of the RLS-based Volterra filter.

Fig. 3. Schematic diagram of the LMS-based DP filter.

Fig. 4. Schematic diagram of the LMS-based Volterra filter.

Fig. 5. Computational complexity versus number of taps.

Fig. 6. Block diagram of the UVLC system.

Fig. 7. BER performance versus bandwidth and number of taps for different nonlinear adaptive filters in the UVLC system.

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].

Fig. 10. Error convergence curve of the RLS–Volterra and LMS–Volterra filters.

Fig. 11. BER versus bandwidth for the VLC and UVLC systems.

Table1. Computational Complexity

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Nonlinear adaptive filters for high-speed LED based underwater visible light communication [Invited] Download： 799次

Fig. 1. Nonlinear response of the UVLC system in the time domain and frequency domain.

Fig. 2. Schematic diagram of the RLS-based Volterra filter.

Fig. 3. Schematic diagram of the LMS-based DP filter.

Fig. 4. Schematic diagram of the LMS-based Volterra filter.

Fig. 5. Computational complexity versus number of taps.

Fig. 6. Block diagram of the UVLC system.

Fig. 7. BER performance versus bandwidth and number of taps for different nonlinear adaptive filters in the UVLC system.

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].

Fig. 10. Error convergence curve of the RLS–Volterra and LMS–Volterra filters.

Fig. 11. BER versus bandwidth for the VLC and UVLC systems.

Table1. Computational Complexity

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