Most intelligent reflecting surface (IRS)-aided indoor visible light communication (VLC) studies ignore the time delays introduced by reflected paths, even though these delays are inherent in practical wideband systems. In this work, we adopt a realistic assumption of IRS-induced time delay for physical layer security (PLS) enhancement. We consider an indoor VLC system where an IRS is used to shape the channel so that the reflected signals add constructively at the legitimate user and create intersymbol interference at eavesdroppers located inside the coverage area. The resulting secrecy capacity maximisation over the IRS element allocation is formulated as a complex combinatorial optimisation problem and is solved using deep reinforcement learning with proximal policy optimisation (PPO). The approach is evaluated for both colluding eavesdroppers, which combine their received signals, and non-colluding eavesdroppers, which act independently. Simulation results are shown for various simulation setups, which demonstrate significant secrecy capacity gains. In a worst-case scenario, where the eavesdroppers have stronger channels than the legitimate user, the proposed PPO-based IRS allocation improves secrecy capacity by 107\% and 235\% in the colluding and non-colluding cases, respectively, compared with allocating all IRS elements to the legitimate user. These results demonstrate that time-delay-based IRS control can provide a strong secrecy advantage in practical indoor VLC scenarios.

翻译：大多数智能反射面（IRS）辅助的室内可见光通信（VLC）研究忽略了反射路径引入的时间延迟，尽管这些延迟在实际宽带系统中是固有的。在本工作中，我们采用IRS引入时间延迟这一现实假设来增强物理层安全（PLS）。我们考虑一个室内VLC系统，其中使用IRS来塑造信道，使得反射信号在合法用户处相干叠加，并在覆盖区域内的窃听者处产生码间干扰。由此产生的、基于IRS单元分配的安全容量最大化问题被表述为一个复杂的组合优化问题，并使用基于近端策略优化（PPO）的深度强化学习进行求解。该方法针对合谋窃听者（它们合并其接收信号）和非合谋窃听者（它们独立行动）两种情况进行了评估。针对多种仿真设置的仿真结果表明了显著的安全容量增益。在最坏情况下，即窃听者信道强于合法用户时，与将所有IRS单元分配给合法用户的方案相比，所提出的基于PPO的IRS分配方案在合谋与非合谋场景下分别将安全容量提高了107%和235%。这些结果表明，基于时间延迟的IRS控制能够在实际室内VLC场景中提供强大的安全优势。