Recently, visible light communication (VLC) has become a hot topic owing to its advantages, such as high security, high capacity, and antielectromagnetic interference. VLC has become a potential candidate for indoor access networks due to the feasibility of combining illumination and communication. However, intersymbol interference and random phase rotation induced by the transmission channel will decrease the system performance. Traditional constant modulus algorithm (CMA) performs well in converging constellation, but random phase rotation still exists since CMA is insensitive to phase. We demonstrate an optical fiber and visible light integrated communication system. 960-Mbps multiband geometrically shaping (GS) quadrature amplitude modulation (QAM)-8 transmission is realized. Modified learning vector quantization is employed after CMA equalization to mitigate the impairment induced by both optical fiber and visible light channel. Experimental results indicate the feasibility of the proposed method. The Q factor of GS QAM-8 could be enhanced by 5.98 dB with the proposed method.
We proposed an adaptive two-stage nonlinear feedforward equalizer and decision feedback equalizer to minimize the negative influence of nonlinear distortions. A data rate of 960 Mbit/s is experimentally achieved on the guided visible-light transparent transmission over a 100-m ultra-large effective area pure silica fiber. The experimental results verified the effectiveness and improvement of the proposed method compared with the traditional feedforward post-equalizers.
We have proposed a frequency reshaping and compensation scheme for FTN (Faster-Than-Nyquist) CAP (Carrierless Amplitude and Phase modulation) signal based on machine learning for the first time in this paper. The cascaded post equalizer consists of 2 stages. The first stage digital signal processing (DSP) is a Deep Neural Network (DNN), then LMS post-equalization is conducted as the second stage offline DSP. Through this method, we successfully demonstrated a data rate of 1.12Gbit/s FTN CAP 9QAM modulation over 1meter free space transmission with bit error rate (BER) below 7% FEC threshold of 3.8×10-3. Compared to the traditional FTN CAP modulation without DNN, the proposed method would increase the data rate by approximately 100 Mbps, leading to an improvement of system capacity of 9.8%. The experimental results clearly validate the proposed cascaded two stage DNN-LMS (C2S DNNLMS) can be a promising solution for future high speed VLC system.
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