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

Vaishnavi Kasuluru, Luis Blanco, Miguel Angel Vazquez, Cristian J. Vaca-Rubio, Engin Zeydan

TL;DR

The paper tackles energy minimization in Open RAN CF-mMIMO under per-user SINR constraints by jointly optimizing precoding and AP selection. It recasts the problem as a binary-constrained, non-convex program due to fixed AP power terms and SINR requirements, and solves it via a penalized convex-concave procedure (PCCP) that linearizes concave components and enforces AP activation through binary variables. The proposed PCCP-based approach can be implemented as an xApp in the near-real-time RIC, enabling dynamic AP on/off decisions alongside beamforming. Numerical results demonstrate meaningful power savings and quantify the AP activation tradeoffs as SINR targets and user counts vary, highlighting practical feasibility limits and the method’s usefulness for real deployments.

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.

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

TL;DR

The paper tackles energy minimization in Open RAN CF-mMIMO under per-user SINR constraints by jointly optimizing precoding and AP selection. It recasts the problem as a binary-constrained, non-convex program due to fixed AP power terms and SINR requirements, and solves it via a penalized convex-concave procedure (PCCP) that linearizes concave components and enforces AP activation through binary variables. The proposed PCCP-based approach can be implemented as an xApp in the near-real-time RIC, enabling dynamic AP on/off decisions alongside beamforming. Numerical results demonstrate meaningful power savings and quantify the AP activation tradeoffs as SINR targets and user counts vary, highlighting practical feasibility limits and the method’s usefulness for real deployments.

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.
Paper Structure (9 sections, 25 equations, 5 figures, 1 algorithm)

This paper contains 9 sections, 25 equations, 5 figures, 1 algorithm.

Table of Contents

  1. Introduction
  2. Cell-Free O-RAN Architecture
  3. System Model
  4. Channel Model
  5. Uplink training and channel estimation
  6. SINR computation
  7. Problem Statement
  8. Numerical Results
  9. Conclusions

Figures (5)

  • Figure 1: Cell-free O-RAN Architecture.
  • Figure 2: Mean number active APs and average transmit power as a function of SINR.
  • Figure 3: Effect of changing the number of users on active APs and transmit power.
  • Figure 4: Empirical Cumulative Distribution Function of the number of active APs for different SINRs.
  • Figure 5: Feasibility of finding an optimal solution for various SINRs.