Optimal Design of Energy-Efficient Cell-Free Massive MIMO: Joint Power Allocation and Load Balancing

TL;DR

This paper presents an optimal and energy-efficient design for cell-free massive MIMO systems by jointly optimizing power allocation and load balancing, significantly reducing power consumption.

Contribution

It introduces a globally optimal solution and a low-complexity algorithm for minimizing power use in cell-free massive MIMO, considering APs' on/off states.

Findings

Significant power savings by turning off unnecessary APs

Global optimal solution via mixed-integer second-order cone programming

Low-complexity algorithm exploiting group-sparsity

Abstract

A large-scale distributed antenna system that serves the users by coherent joint transmission is called Cell-free Massive MIMO (multiple input multiple output). For a given user set, only a subset of the access points (APs) is likely needed to satisfy the users' performance demands. To find a flexible and energy-efficient implementation, we minimize the total power consumption at the APs in the downlink, considering both the hardware and transmit powers, where APs can be turned off. Even though this is a non-convex optimization problem, a globally optimal solution is obtained by solving a mixed-integer second-order cone program. We also propose a low-complexity algorithm that exploits group-sparsity in the problem formulation. Numerical results manifest that our optimization framework can greatly reduce the power consumption compared to keeping all APs turned on and only minimizing the transmit powers.