Two-Agent DRL for Power Allocation and IRS Orientation in Dynamic NOMA-based OWC Networks

Intelligent reflecting surfaces (IRSs) technology has been considered a promising solution in visible light communication (VLC) systems due to its potential to overcome the line-of-sight (LoS) blockage issue and enhance coverage. Moreover, integrating IRS with a downlink non-orthogonal multiple access (NOMA) transmission technique for multi-users is a smart solution to achieve a high sum rate and improve system performance. In this paper, a dynamic IRS-assisted NOMA-VLC system is modeled, and an optimization problem is formulated to maximize sum energy efficiency (SEE) and fairness among multiple mobile users under power allocation and IRS mirror orientation constraints. Due to the non-convex nature of the optimization problem and the non-linearity of the constraints, conventional optimization methods are impractical for real-time solutions. Therefore, a two-agent deep reinforcement learning (DRL) algorithm is designed for optimizing power allocation and IRS orientation based on centralized training with decentralized execution to obtain fast and real-time solutions in dynamic environments. The results show the superior performance of the proposed DRL algorithm compared to standard DRL algorithms typically used for resource allocation in wireless communication. The results also show that the proposed DRL algorithm achieves higher performance compared to deployments without IRS and with randomly oriented IRS elements.

Intelligent Reflecting Surfaces assisted Laser-based Optical Wireless Communication Networks

The increasing demand for wireless networks of higher capacity requires key-enabling technologies. Optical wireless communication (OWC) arises as a complementary technology to radio frequency (RF) systems that can support high aggregate data rates. However, OWC systems face some challenges including beam-blockage. Intelligent reflecting surfaces (IRSs) can offer alternative pathways for the optical signal, ensuring continuous connectivity. In this work, we investigate the potential of using IRS in an indoor OWC network. In particular, we define a system model of indoor OWC that employs IRS in conjunction with angle diversity transmitters (ADT) using vertical-cavity surface-emitting laser (VCSEL) arrays. The VCSEL beam is narrow, directed, and easy to block, however, it can deliver high data rates under eye safety regulations. Simulation results show that the deployment of IRS can significantly improve the achievable data rates of Laser-based OWC systems.