## 5 Simulation Results and Discussions
### Results Without Ambient Light Noise  
In this subsection, we evaluate the performance of the considered systems in terms of BER, Q-factor, and received power, excluding the effects of ambient light noise. Figure 7 presents the BER performance as a function of distance for both MIMO and SISO-based VLC systems. It is evident that both QPSK and NRZ techniques outperform the RZ technique in both SISO and MIMO systems. Furthermore, the MIMO-based VLC system outperforms the SISO-VLC system due to spatial multiplexing achieved by using multiple light sources and detectors. Based on Figure 7, the RZ modulation briefly outperforms QPSK in terms of BER performance within the narrow distance range of 1000 to 1025 m. The temporary performance advantage of RZ modulation in this specific range is attributed to its better temporal signal separation, which reduces ISI at moderate transmission distances. In this region, the benefits of the shorter pulse duration in RZ help maintain clearer symbol distinction, especially under reduced noise influence, compared to QPSK, which, while spectrally efficient, is more sensitive to phase noise and ambient distortion under certain conditions. However, as the distance increases further, the higher spectral efficiency and robustness of QPSK allow it to outperform RZ in terms of BER and coverage, as stated above. Figures 8 and 9 depict the Q-factor and received power as a function of distance for both systems without considering ambient light noise, respectively, further supporting the observations from Figure 7. Table 3 presents the achievable link distance in both SISO and MIMO systems that achieve the acceptable BER limit, which must be greater than 1 per data rate. \begin{table}
\begin{tabular}{c c} \hline \hline
**Parameters** & **Value** \\ \hline Data rate & 1 Gbps \\ \hline Power of LASER & (10–30) dBm \\ \hline Wavelength of LASER & 700 nm \\ \hline Frequency of LASER & 428 THz \\ \hline Channel attenuation & 25 dB/km \\ \hline Optical amplifier gain & 20 dB \\ \hline Optical amplifier noise figure & 4 dB \\ \hline Wavelength of ambient noise & 550 nm \\ \hline Cutoff freq. of low-pass Bessel filter & 0.75 \(\times\) data rate \\ \hline Communication distance & Up to 1.35 Km \\ \hline Receiver field of view (FOV) & \(\pm 60^{\circ}\) \\ \hline Photodetector responsivity \(R\) & 0.6 A/W \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Simulation parameters. Figure 8: Q-factor as a function of distance for both MIMO- and SISO-based VLC systems without considering ambient light noise. Figure 7: BER performance versus distance for both MIMO- and SISO-based VLC systems without considering ambient light noise. As demonstrated in Table 3, the MIMO system achieves greater transmission distances compared to the SISO system. The results show that MIMO systems, particularly with NRZ and QPSK modulation, achieve longer distances, while RZ performs the worst in both systems. It is important to note that minor inconsistencies between Q-factor and BER results may occur, particularly near the performance degradation threshold. This is due to the nonlinear relationship between the Q-factor and BER, especially when modulation schemes are subjected to complex channel conditions, such as ISI. While the Q-factor provides a statistical measure of signal quality based on the separation between logic levels and noise margins, BER is a direct measure of bit errors over time. As a result, transient effects, such as variations in noise, phase distortions, or symbol misalignments, may cause short-range discrepancies between the two metrics (as in SISO scenario 1000 to 1025 m). These effects are more pronounced at the edge of the communication range, where signal degradation accelerates, and different modulation schemes respond differently to distortion. Such variations are expected and do not imply fundamental contradictions but rather reflect the sensitivity of each metric to different aspects of signal quality.