# Massive MIMO Optimization with Compatible Sets

## TL;DR

This paper develops optimization models for massive MIMO systems using compatible sets, enabling joint device scheduling and power control to improve energy efficiency and reduce complexity in 5G networks.

## Contribution

It introduces new mixed-integer programming models for massive MIMO that incorporate compatible sets and applies them to heterogeneous device scenarios.

## Key findings

- Significant energy savings without throughput loss.
- Reduced signaling overhead and device complexity.
- Efficient scheduling eliminates need for uplink power control.

## Abstract

Massive multiple-input multiple-output (MIMO) is expected to be a vital component in future 5G systems. As such, there is a need for new modeling in order to investigate the performance of massive MIMO not only at the physical layer, but also higher up the networking stack. In this paper, we present general optimization models for massive MIMO, based on mixed-integer programming and compatible sets, with both maximum ratio combing and zero forcing precoding schemes. We then apply our models to the case of joint device scheduling and power control for heterogeneous devices and traffic demands, in contrast to existing power control schemes that consider only homogeneous users and saturated scenarios. Our results show substantial benefits in terms of energy usage can be achieved without sacrificing throughput, and that both signalling overhead and the complexity of end devices can be reduced by abrogating the need for uplink power control through efficient scheduling.