## 6 Experiment Setup and Results
### Experiment Results of Predistortion Modeling with Coefficient Approximation  
We simulated the QAM performances of two predistortion schemes using (1) the inverse function and (2) coefficient approximation along with the conventional scheme without predistortion. Note that we set the simulation threshold as the BER reached to \(10^{-5}\).  
Figure 8 shows OFDM's BER performance using 256 subcarriers in 16 QAM and 64 QAM for the white LED. The results showed a 3.5 dB performance gain for all predistortion schemes at BER \(10^{-4}\) in 16 QAM. For BER \(10^{-4}\) at 64 QAM modulation, each predistortion required us to set SNR values at 16.5 dB in the inverse function scheme and 17 dB in the coefficient modification scheme. In addition, the BER performance were deteriorated when QAM levels were increased since symbols were closer in the constellation diagram.  
Figure 7: An Initial design of Bidirectional LSTM in predistortion module from OFDM transmitter. Note that, for training model, we consider input data as 2�Figure 9 shows OFDM's BER performances using 256 subcarriers in 16 QAM and 64 QAM. In these simulations, we used the infrared LED. In this case, we also observed that both predistortion schemes gained 1.5 dB performance at BER = \(10^{-4}\) with 16 QAM compared to the scheme without predistortion. For 64 QAM modulation to meet target BER \(10^{-4}\), both predistortion schemes needed to set SNR values up to 16.5 dB.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Properties and Settings** & **Types and Values** \\ \hline OS & Ubuntu 20.04.3 LTS \\ Python & 3.8.10 \\ Tensorflow (incl. Keras) & 2.7.0 \\ CUDA & 11.2 \\ \hline CPU & Intel Xeon Silver 4208 Processor \\ GPU & NVIDIA GeForce RTX 3080 \\ \hline LED Type & White LED \\ FFT size & 32 \\ Modulation & 16 QAM \\ Channel condition & Rician fading channel \\ Rician K factor (dB) & 4, 8, 12, 16, 20 \\ Batch size & 32, 64, 128, 256, 512 \\ Data size (per 10,000 samples) & 2560, 5120, 7680, 10,240, 20,480, 25,600, 51,200 \\ Epoch & 1, 2, 3, 5 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Experiment properties and settings for VLC BLSTM experiments.  
Figure 8: BER performances of the predistortion in 16/64 QAM modulation for white LED.  
To summarize the results from Figures 8 and 9, the white LED performance was substantially improved compared to the infrared LED performance. However, the overall BER performances of the white LED with predistortion schemes were still inferior to infrared LED performance since the infrared LED operates on a lower frequency spectrum than the white LED does. In addition, infrared LED performance without predistortion had 2 dB more SNR gain than the white LED performance without predistortion.  
Given the Rician fading conditions, our performance results showed that the Rician fading might alter the performance. As shown on the Rician fading results in Figure 10, the performance of the coefficient approximation predistortion method was still better than that without any predistortion in low SNRs. Our results may conclude that the predistortion modeling may mitigate the distortion matter but still can be affected by other conditions in terms of Rician fading impacts.