Minimizing Power Consumption under SINR Constraints for Cell-Free Massive MIMO in O-RAN

TL;DR

This paper proposes a novel optimization method for minimizing power consumption in cell-free massive MIMO systems under SINR constraints, suitable for implementation in O-RAN architectures.

Contribution

It introduces a penalized convex-concave procedure to solve a complex binary quadratic optimization problem for joint precoding and AP selection.

Findings

Effective power minimization while maintaining SINR constraints.

Potential for real-time implementation in O-RAN systems.

Improved joint precoding and access point selection performance.

Abstract

This paper deals with the problem of energy consumption minimization in Open RAN cell-free (CF) massive Multiple-Input Multiple-Output (mMIMO) systems under minimum per-user signal-to-noise-plus-interference ratio (SINR) constraints. Considering that several access points (APs) are deployed with multiple antennas, and they jointly serve multiple users on the same time-frequency resources, we design the precoding vectors that minimize the system power consumption, while preserving a minimum SINR for each user. We use a simple, yet representative, power consumption model, which consists of a fixed term that models the power consumption due to activation of the AP and a variable one that depends on the transmitted power. The mentioned problem boils down to a binary-constrained quadratic optimization problem, which is strongly non-convex. In order to solve this problem, we resort to a novel approach, which is based on the penalized convex-concave procedure. The proposed approach can be implemented in an O-RAN cell-free mMIMO system as an xApp in the near-real time RIC (RAN intelligent Controller). Numerical results show the potential of this approach for dealing with joint precoding optimization and AP selection.