# Deep Learning-Based Next-Generation Waveform for Multiuser VLC Systems
## 4 Results and Discussions  
The aforementioned multiplexing techniques, OFDM-IM and OAM-IM are implemented for four users in MIMO configuration in the MATLAB simulation program. For the simulations, the 4-PSK modulator and 4 \(\times\) 4 MIMO configuration are used. For the sake of comparison, the modulation order is kept the same for the LOS and NLOS VLC channels. Figure 8: Proposed CNN-based NOMA-SIC multiuser system. The simulation parameters are given in Table 1. It is worth noting that two modes are activated, and the mode combination matrix is shown in (23). \[\mathcal{L}=\left[ \begin{array}{cc}0&1\\ 2&3\\ 0&2\\ 1&3\end{array} \right], \tag{23}\]  
where the elements of the matrix, \(\mathcal{L}\), show the index of vector \(x\), which has nonzero information. For example, the first row, which contains [0, 1] in the matrix \(\mathcal{L}\), shows that the nonzero information will be stored at indices 0 and 1 of the vector. The data of both users are suppressed via NOMA techniques with power ratios of 0.3, 0.4, 0.6, and 0.8 for user 4, user 3, user 2, and user 1, respectively. Figure 9 illustrates the Bit Error Rate (BER) performance of the VLC system based on OAM-IM and OFDM-IM for user 1 and user 2. It should be noted that both systems are evaluated with an equal number of activated modes. For both users, OAM-IM outperforms OFDM-IM, at least for the low SNR region, irrespective of the detection scheme used. For the high SNR region, the diversity gain becomes relatively more comparable for both schemes. Moreover, the coding gain of OAM-IM is reduced in the high SNR region. Further exploration of OAM-IM based on some parameters such as the rotation angle can lead to better performance in the high SNR region. There are myriad reasons for this enhanced performance of OAM-IM: First, the multiplexing efficient performance of OAM-IM with PD-NOMA is clearly evident. Second, the decoding of OAM-IM is better, which shows it is less effected when transmitted with low transmitted power compared to OFDM-IM symbols. This point is especially valid for the NLOS scenario where the performance of OFDM-IM is notably worse than that of OAM-IM. Third, ML decoding is best suited to OAM-IM in terms of BER performance under PD-NOMA multiplexing. \begin{table}
\begin{tabular}{c c} \hline \hline
**Parameter** & **Value** \\ \hline Configuration & \(4\times 4\) \\ Average transmission power & 1 W \\ Photodetector’s area & 0.1 mm\({}^{2}\) \\ Angle of incidence & 20\({}^{\circ}\) \\ Distance between LED and photodetector & 10 ft \\ Field of view & 120\({}^{\circ}\) \\ Activated modes & 2 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Simulation parameters. Figure 9: User 1 and user 2 BER of OFDM-IM and OAM-IM for LoS/NLoS VLC channel. As far as the selection of decoding is concerned, CNN-based receiver design performs very well for all ranges of SNR values. The overall dominance of the CNN-based detection method can be observed, as it has low complexity and better results than those of maximum likelihood [18; 38]. The BER performance of the ML-based system is good for user 1; however, as the number of users is increased in the system, its performance starts to degrade. It shows that the ML-based method is not as good as CNN due to CNN-based models' inherent feature of learning the system on the go. The simulation parameters are shown in Table 1[18]. It should be highlighted that the current work considers a rotation angle of zero for simplicity. However, it is to be noted that the performance of the system can be improved by changing the rotation angles (\(\theta_{2}\)) for different modulation modes for M-PSK. Figure 10 shows very interesting results for user 3 and user 4. Above all, these curves imply that the superior performance of OAM-IM is consistent and is not affected by the increase in the number of users by and large. It can be seen that the difference between OAM-IM and OFDM-IM for a low SNR in Figure 10 is comparatively low; however, as the SNR values are increased, OFDM-IM performance starts to decrease.