Enhanced Fairness and Scalability of Power Control Schemes in Multi-Cell Massive MIMO

TL;DR

This paper introduces a scalable power control scheme for multi-cell massive MIMO systems that balances fairness and spectral efficiency, overcoming limitations of existing schemes in large networks.

Contribution

A novel power control method maximizing the geometric mean of per-cell max-min spectral efficiency, formulated as a convex optimization problem for scalability.

Findings

The proposed scheme is provably scalable for large networks.

Simulation results show improved fairness and spectral efficiency balance.

The method effectively overcomes the scalability issues of existing schemes.

Abstract

This paper studies the transmit power optimization in multi-cell massive multiple-input multiple-output (MIMO) systems. Network-wide max-min fairness (NW-MMF) and network-wide proportional fairness (NW-PF) are two well-known power control schemes in the literature. The NW-MMF focus on maximizing the fairness among users at the cost of penalizing users with good channel conditions. On the other hand, the NW-PF focuses on maximizing the sum SE, thereby ignoring fairness, but gives some extra attention to the weakest users. However, both of these schemes suffer from a scalability issue which means that for large networks, it is highly probable that one user has a very poor channel condition, pushing the spectral efficiency (SE) of all users towards zero. To overcome the scalability issue of NW-MMF and NW-PF, we propose a novel power control scheme that is provably scalable. This scheme maximizes the geometric mean (GM) of the per-cell max-min SE. To solve this new optimization problem, we prove that it can be rewritten in a convex optimization form and then solved using standard tools. The simulation results highlight the benefits of our model which is balancing between NW-PF and NW-MMF.