An Optimization-Based User Scheduling Framework for Multiuser MIMO Systems

TL;DR

This paper introduces a novel optimization-based user scheduling framework for multiuser MIMO systems that globally optimizes resource allocation, supporting various objectives and outperforming existing greedy algorithms in complex wireless scenarios.

Contribution

It proposes a flexible, optimization-driven scheduling framework that addresses the limitations of greedy algorithms by globally solving the resource allocation problem in MU-MIMO systems.

Findings

Outperforms existing scheduling algorithms in simulations.

Approaches the performance of exhaustive search methods.

Effective in millimeter-wave and sub-6-GHz massive MU-MIMO systems.

Abstract

Resource allocation is a key factor in multiuser (MU) multiple-input multiple-output (MIMO) wireless systems to provide high quality of service to all user equipments (UEs). In congested scenarios, UE scheduling enables UEs to be distributed over time, frequency, or space in order to mitigate inter-UE interference. Many existing UE scheduling methods rely on greedy algorithms, which fail at treating the resource-allocation problem globally. In this work, we propose a UE scheduling framework for MU-MIMO wireless systems that approximately solves a nonconvex optimization problem that treats scheduling globally. Our UE scheduling framework determines subsets of UEs that should transmit simultaneously in a given resource slot and is flexible in the sense that it (i) supports a variety of objective functions (e.g., post-equalization mean squared error, capacity, and achievable sum rate) and (ii) enables precise control over the minimum and maximum number of resources the UEs should occupy. We demonstrate the efficacy of our UE scheduling framework for millimeter-wave massive MU-MIMO and sub-6-GHz cell-free massive MU-MIMO systems, and we show that it outperforms existing scheduling algorithms while approaching the performance of an exhaustive search.