| Summary: | In visible light communication (VLC) systems based on light emitting diodes (LEDs), the nonlinearity of LEDs often leads to a high bit error rate (BER), which limits the system’s performance. While artificial neural networks (ANNs) have been used as predistorters to mitigate LED nonlinearity, their effectiveness is hampered by overfitting. This paper proposes an adaptive predistorter based on amplitude time-delay twin support vector regression (ATD-TSVR) to address the nonlinearity of LEDs in orthogonal frequency division multiplexing (OFDM)-based VLC systems. The authors demonstrate through experiments that LED nonlinearity is the primary source of signal distortion in nonlinear VLC systems. Simulation results show that the proposed ATD-TSVR predistorter achieves superior BER, Inputs/Outputs curves, power spectral density (PSD), and constellation plots in an 80Mbit/s OFDM nonlinear VLC system. Meanwhile, as compared to the traditional SVR approach, the CPU training time of ATD-TSVR can be reduced by more than four times. The adaptive pre-distortion method herein is generally applicable to broadband VLC systems and also proves the application prospect and effectiveness of TSVR in VLC system.
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