## 5 Conclusions  
Energy efficiency is an important indicator to measure the energy consumption of communication systems. In this paper, the VLC system via mirror array-based IRS for parallel vehicles is designed first, and the calculation formula of channel gain is given. Then, the achievable rate and power consumption of the system are analyzed, and the calculation method of EE is given. On this basis, considering the non-negative and real of the transmitted signal, the maximum power consumption satisfied luminous ability and eye safety, the minimum achievable rate, and the required BER, the optimization problem of the number of mirrors under EE maximization is proposed. Under the existing constraints, it is proved that \(EE(N)\) is a unimodal function. To quickly find the optimal value of the number of mirrors, the bsci algorithm is proposed. By comparing the optimal number  
Figure 6: EE versus N with different \(y_{s}\). \begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{\(y_{s}\) (m)} & \multirow{2}{*}{\(N_{opt}\)} & \multirow{2}{*}{\(EE_{max}\)(N) (Mbits/J)} & \multicolumn{2}{c}{**Iterations of Bubble**} & **Iterations of Bsci** \\  & & & **Sort Method** & **Algorithm** \\ \hline
10 & 168 & 1.7049 & 6363528 & 12 \\
20 & 264 & 1.0795 & 6098778 & 12 \\
30 & 378 & 0.7442 & 566661 & 12 \\
40 & 510 & 0.5422 & 5089645 & 11 \\
50 & 661 & 0.4108 & 4394130 & 11 \\ \hline \hline \end{tabular}
\end{table} 
Table 5: \(N_{opt}\) and iterations with different \(y_{s}\). of mirrors corresponding to different \(R_{min}\), \(\sigma^{2}\), \(y_{s}\), we can know that different parameter changes will bring the different iterative range of the number of mirrors, and effect the optimal number of mirrors. Compared with the Bubble Sort method, the BSCI algorithm reduces the amount of computation by \(10^{5}\) orders of magnitude, and can quickly find the optimal number of mirrors and the maximum value of EE, which is an effective algorithm. The numerical results show that when the EE corresponding to \(R_{min}\) is less than the \(EE_{max}(N)\), \(EE(N)\) increases first and then decreases. Otherwise, \(EE(N)\) decreases monotonically, and the \(EE_{max}(N)\) obtained at this time is smaller than that in the previous case. Therefore, it is necessary to select an appropriate \(R_{min}\) according to the actual communication needs of the vehicle. This requires consideration of the tradeoff between the EE and achievable rate. When noise power increases, \(EE(N)\) becomes smaller with the same number of mirrors. Therefore, it is necessary to reduce noise power to obtain a smaller number of optimized mirrors and higher EE, especially background light noise. The use of optical elements, such as optical filters, can be considered. As \(y_{s}\) increases, the distance between the vehicle and IRS is longer, resulting in the optimal number of mirrors increasing and \(EE(N)\) decreasing. To solve this problem, it can be considered to install multiple IRSs that the distance between the vehicle and the IRS is within a controllable range, which can improve the efficiency of the mirrors in the IRS and the performance of EE. Conceptualization, L.Z. and H.Z. ; methodology, L.Z. ; validation, L.Z., H.Z. and J.L. ; formal analysis, W.Z. ; investigation, L.Z. ; data curation, H.Z. ; writing--original draft preparation, L.Z. ; writing--review and editing, J.L. ; visualization, L.Z. ; supervision, J.L. ; project administration, J.L. ; funding acquisition, J.L. All authors have read and agreed to the published version of the manuscript.