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.

翻译：在多用户（MU）多输入多输出（MIMO）无线系统中，资源分配是为所有用户设备（UE）提供高质量服务的关键因素。在拥塞场景下，UE调度能够将UE在时间、频率或空间上进行分布，以减轻UE间干扰。许多现有的UE调度方法依赖于贪心算法，这些算法无法全局性地处理资源分配问题。本文提出了一种用于MU-MIMO无线系统的UE调度框架，该框架通过近似求解一个非凸优化问题来实现全局调度。我们的UE调度框架确定在给定资源时隙中应同时传输的UE子集，并具有以下灵活性：（i）支持多种目标函数（例如后均衡均方误差、容量和可达和速率）；（ii）能够精确控制UE应占用的资源数量的最小值和最大值。我们证明了该UE调度框架在毫米波大规模MU-MIMO和6GHz以下无蜂窝大规模MU-MIMO系统中的有效性，并表明其性能优于现有调度算法，且接近穷举搜索的性能。