Power-efficient Joint Resource Allocation and Decoding Error Probability for Multiuser Downlink MISO with Finite Block Length Codes

In this paper, we study a multiuser multiple-input single-output (MISO) ultra-reliable low-latency (URLLC)-enabled intelligent reflecting surface (IRS) system, where a multi-antenna access point (AP) transmits information symbols to a set of URLLC users by taking into account short packet transmission and low-latency wireless communication. In particular, the total system transmits power is minimized by jointly optimizing active and passive beamformers at the AP and the IRS, respectively. An efficient algorithm based on alternating optimization (AO) is proposed to solve the main optimization problem iteratively. Firstly, we adopt the difference of convex functions (DC) and successive convex approximation (SCA) to obtain a sub-optimal solution for the active beamformers at the AP. Secondly, a penalty-based approach is adopted together with the SCA technique to handle the unit-modulus constraints at the IRS. Moreover, an explicit objective is proposed to provide a better convergence. Simulation results exhibit the performance of the proposed algorithm compared to other baseline schemes.