Power Control in Cell-Free Massive MIMO Networks for UAVs URLLC under the Finite Blocklength Regime

TL;DR

This paper investigates power control strategies in cell-free massive MIMO networks to enhance ultra reliable low latency communication for UAVs and ground users, using novel optimization approximations.

Contribution

It introduces two successive convex optimization methods for nonconvex URLLC rate maximization problems in UAV-assisted CFmMIMO networks.

Findings

SCO-IIA outperforms other schemes in minimum user rate.

CFmMIMO with SCO-IIA achieves higher URLLC rates than colocated MIMO.

Proposed methods effectively handle nonconvex optimization in URLLC scenarios.

Abstract

In this paper, we employ a user-centric (UC) cell-free massive MIMO (CFmMIMO) network for providing ultra reliable low latency communication (URLLC) when traditional ground users (GUs) coexist with unmanned aerial vehicles (UAVs). We study power control in both the downlink and the uplink when partial zero-forcing (PZF) transmit/receive beamforming and maximum ratio transmission/combining are utilized. We consider optimization problems where the objective is to maximize either the users' sum URLLC rate or the minimum user's URLLC rate. The URLLC rate function is both complicated and nonconvex rendering the considered optimization problems nonconvex. Thus, we propose two approximations for the complicated URLLC rate function and employ successive convex optimization (SCO) to tackle the considered optimization problems. Specifically, we propose the SCO with iterative concave lower bound approximation (SCO-ICBA) and the SCO with iterative interference approximation (SCO-IIA). We provide extensive simulations to evaluate SCO-ICBA and SCO-IIA and compare UC CFmMIMO deployment with traditional colocated massive MIMO (COmMIMO) systems. The obtained results reveal that employing the SCO-IIA scheme to optimize the minimum user's rate for CFmMIMO with MRT in the downlink, and PZF reception in the uplink can provide the best URLLC rate performances.