16QAM-OFDM VLC system Based on Frequency Domain Pre-Compensation and DNN Post-Equalization

Visible light communication (VLC) technology utilizes LEDs as light sources, offering several benefits such as the use of license-free spectrum, green and safe. However, conventional LED devices face challenges due to their restricted bandwidth and nonlinearity under different current levels. These issues lead to signal distortion and inter-symbol interference (ISI), which are particularly problematic in high-order modulation schemes. In this work, we propose a low complexity scheme combining S21 pre-compensation and shallow hidden layer deep neural networks (DNN)-based post-equalization in a VLC system. At the transmitter, S21 pre-compensation is used to suppress the influence of high-frequency power fading. The post-equalization at the receiver side uses the least square (LS)-DNN cascaded equalization algorithm, where LS performs linear equalization and DNN performs nonlinear equalization. Since the S21 pre-compensation and LS algorithm have completed partial equalization, it can provide a good initial state for DNN training, thus speeding up the convergence of DNN. To better capture the dependency between symbols, we preprocess the dislocation filling before the data is sent to the input layer of DNN. In the experiment, a VLC system with the 3-dB bandwidth of 9MHz is used. With S21 pre-compensation, its 3-dB bandwidth is expanded to about 43MHz. The two hidden layer DNN is used to carry nonlinear equalization. If an 80Mbps 16QAM OFDM signal is transmitted in a 3m VLC system, the scheme proposed can expand the available peak-to-peak voltage (Vpp) range by 30% compared with pre-compensation LS algorithm and achieve transmission over 9 meters under 7% hard-decision forward error correction (HD-FEC) BER threshold of 3.8e-3. The comparison with LSTM-DNN based scheme shows that the proposed scheme can improve the performance of VLC system in terms of BER and EVM, while the training complexity is 2-order of magnitude lower.