Joint Optimization of URLLC Parameters and Beamforming Design for Multi-RIS-Aided MU-MISO URLLC System

This letter focuses on a novel resource allocation design for a multi-reconfigurable intelligent surface (RIS)-aided multi-input and single-output (MISO) ultra-reliable low-latency communication (URLLC) system. In particular, we formulate the sum-rate maximization problem for joint optimization of block-length and packet-error probability for each user, precoder design at the base-station (BS) and passive beamforming at the RIS. To solve it, we provide an alternating optimization framework which involves the decoupling of original problem into the sub-problems of beamforming design and block-length optimization, and later solving them using general convex approximations. Numerical results validate the fast convergence of the proposed solution. Moreover, the proposed solution achieves upto 40% better performance when compared to random resource allocation and each RIS deployment boost the rate performance by 3-5%.

Automated summary

This letter proposes a novel resource allocation design for a multi-RIS-aided MISO URLLC system. An alternating optimization framework is provided to solve the sum-rate maximization problem by decoupling it into two sub-problems and using convex approximations. Numerical results show the fast convergence and superior performance of the proposed solution, with up to 40% improvement compared to random resource allocation and 3-5% rate performance boost for each RIS deployment.