Energy Efficiency Optimization for URLLC in RIS-Aided User-Centric Networks

User-centric networking is expected to be a promising technology to implement ultra-reliable and low-latency communication (URLLC). However, the densely deployed access points (APs) in a user-centric network (UCN) will involve significant hardware costs and energy consumption. To address this issue, we propose a reconfigurable intelligent surface (RIS)-aided UCN for URLLC. Then, a joint optimization problem with consideration of active beamforming at APs and passive beamforming at RISs is formulated to achieve optimal energy efficiency (EE). Since the problem is intractable and non-convex, we develop an alternating optimization algorithm based on the inner approximation framework to solve it efficiently. Numerical results verify that the proposed algorithm outperforms baseline algorithms regarding EE. Particularly, with the proposed algorithm, our RIS-aided UCN achieves up to 147% performance gains in terms of EE compared to traditional UCN.