Resource Allocation for Cell-free Massive MIMO enabled URLLC Downlink Systems

Abstract

Ultra-reliable and low-latency communication (URLLC) is a crucial technique for enabling the wireless control over industrial Internet-of-Things (IIoT) devices. By enhancing the path gain, cell-free massive multiple-input and multiple-output (CF mMIMO) has great potential to provide the URLLC service for the IIoT devices. In this paper, we investigate the CF mMIMO-enabled URLLC in a smart factory. The lower bounds (LBs) of downlink ergodic data rate under finite channel blocklength (FCBL) with imperfect channel state information (CSI) are derived for the full-pilot zero-forcing (FZF) precoding scheme. Meanwhile, the weighted sum rate is maximized by jointly optimizing the pilot power and transmission power based on the derived LB by considering the devices' requirements of reliability and data rate. To solve this optimization problem, we first provide the globally optimal solution of the pilot power, and then introduce some approximations to transform the original problems into a series of subproblems, which can be expressed in a geometric programming (GP) form that can be readily solved. Finally, an iterative algorithm is proposed to optimize the power allocation. Simulation results demonstrate that our proposed algorithm is superior over the conventional method and CF mMIMO systems significantly improves the average weighted sum rate (AWSR) over the centralized mMIMO system.