As an emerging technology, reconfigurable intelligent surfaces (RISs) have been investigated to apply to visible light communication (VLC) systems to enhance the transmission capability of the systems, recently. However, the optimization of RIS location in VLC has not been studied. In this study, we first investigated RIS positioning design in VLC. Specifically, we set two indoor VLC scenarios with a VLC RIS composed of a mirror array. We set the achievable rates in different scenarios as the utility functions to optimize the position of the RIS array according to the placement of the access point (AP) and user. We found that the problems are nondeterministic polynomial (NP)-hard. Aiming at the different optimization problems, the particle swarm optimization (PSO) algorithm was used to confirm the optimal position of the RIS array. Unlike the traditional algorithm, we added an adaptive mutation mechanism to the algorithm to guarantee the randomness of the particle to search for the optimal solution. Finally, our simulation results showed that the proper position design of the RIS array can improve the communication performance to a greater degree, while the computational complexity required to solve the position optimization problems through the PSO algorithm can be significantly reduced compared with that required for the exhaustive search method in the case where both of the algorithms find the optimal solution.

中文翻译：

---

可重构智能表面辅助室内可见光通信系统的定位设计

作为一种新兴技术，可重构智能表面（RIS）最近被研究应用于可见光通信（VLC）系统，以增强系统的传输能力。然而，尚未研究 VLC 中 RIS 位置的优化。在这项研究中，我们首先研究了 VLC 中的 RIS 定位设计。具体来说，我们设置了两个室内 VLC 场景，其中 VLC RIS 由镜像阵列组成。我们将不同场景下的可实现速率设置为效用函数，以根据接入点 (AP) 和用户的位置优化 RIS 阵列的位置。我们发现这些问题是非确定性多项式 (NP) 难的。针对不同的优化问题，采用粒子群优化（PSO）算法确定RIS阵列的最优位置。与传统算法不同的是，我们在算法中加入了自适应变异机制，以保证粒子搜索最优解的随​​机性。最后，我们的仿真结果表明，RIS阵列的适当位置设计可以更大程度地提高通信性能，而通过PSO算法解决位置优化问题所需的计算复杂度相比于穷举搜索在两种算法都找到最优解的情况下。