A Deployment Strategy for Reconfigurable Intelligent Surfaces with Joint Phase and Position Optimization

The actual implementation of fifth-generation (5G) and beyond networks faces persistent challenges, including environmental interference and limited coverage, which compromise transmission stability and network feasibility. Reconfigurable Intelligent Surfaces (RISs) have emerged as a promising technology to dynamically reconfigure wireless propagation environments and enhance communication quality. To fully unlock the potential of RIS, this paper proposes a novel deployment strategy based on Double Deep Q-Networks (DDQNs) that jointly optimizes the RIS placement and phase shift configuration to maximize the system sum-rate. Specifically, the coverage area is discretized into a grid, and at each candidate location, a DDQN-based method is developed to solve the corresponding non-convex phase optimization problem. Simulation results reveal that our proposed strategy significantly surpasses conventional benchmark schemes, resulting in a sum-rate improvement of up to 38.41%. The study provides a practical and efficient pre-deployment framework for RIS-enhanced wireless networks.