Hybrid Active-Passive Reconfigurable Intelligent Surface-Assisted URLLC Services for Energy Efficiency Optimization

This paper investigates a hybrid reconfigurable intelligent surface (RIS) architecture incorporating both passive and active elements, to enhance the ultra-reliable and low-latency communication (URLLC) services between a central controller (CC) and remote devices in mission-critical scenarios. Specifically, with the objective of maximizing the energy efficiency (EE) of the system under target reliability, an optimization problem in terms of the transmit precoding of CC, the reflecting coefficients of hybrid RIS, and the allocated blocklength is proposed. To deal with the intractability of the non-convex problem considering the various quality of service (QoS) issues of remote devices such as transmission latency and rate constraints, Dinkelbach's method is invoked to transform the original problem into a parameterized concave-convex function. Subsequently, efficient algorithms are developed based on alternating optimization, successive convex approximation, and Big-M formulation methods. In addition, the effects of several vital parameters on the performance of the proposed scheme are investigated. Numerical results show that compared to conventional full-passive/active RIS and no-RIS systems, the proposed hybrid RIS offers significant performance advantages. Furthermore, the optimal number and distribution of active/passive elements allocation are demonstrated. It is observed that the proposed hybrid RIS with only a few active elements can achieve higher EE than conventional passive RIS even with infinite blocklength, sufficiently revealing the potential of hybrid RIS to reduce transmission latency, guarantee rewarding reliability, and enhance EE for URLLC services.