Joint Power and User Grouping Optimization in Cell-Free Massive MIMO Systems

TL;DR

This paper proposes a joint power and user grouping optimization method for cell-free massive MIMO systems, reducing power consumption and increasing user capacity without added complexity.

Contribution

It introduces a novel joint power and user grouping framework under QoS constraints, with an efficient GBD-based algorithm for optimal solutions.

Findings

User grouping allows serving as many users as APs without extra complexity.

Power consumption is reduced by 2-3 dB compared to existing strategies.

Total transmit power decreases by 7 dB with the proposed grouping.

Abstract

To relieve the stress on channel estimation and decoding complexity in cell-free massive multiple-input multiple-output (MIMO) systems, user grouping problem is investigated in this paper, where access points (APs) based on time-division duplex (TDD) are considered to serve users on different time resources and the same frequency resource. In addition, when quality of service (QoS) requirements are considered, widely-used max-min power control is no longer applicable. We derive the minimum power constraints under diverse QoS requirements considering user grouping. Based on the analysis, we formulate the joint power and user grouping problem under QoS constraints, aiming at minimizing the total transmit power. A generalized benders decomposition (GBD) based algorithm is proposed, where the primal problem and master problem are solved iteratively to approach the optimal solution. Simulation results demonstrate that by user grouping, the number of users served in cell-free MIMO systems can be as much as the number of APs without increasing the complexity of channel estimation and decoding. Furthermore, with the proposed user grouping strategy, the power consumption can be reduced by 2-3 dB compared with the reference user grouping strategy{, and by 7 dB compared with the total transmit power without grouping.