In this paper, a two-stage intelligent scheduler is proposed to minimize the packet-level delay jitter while guaranteeing delay bound. Firstly, Lyapunov technology is employed to transform the delay-violation constraint into a sequential slot-level queue stability problem. Secondly, a hierarchical scheme is proposed to solve the resource allocation between multiple base stations and users, where the multi-agent reinforcement learning (MARL) gives the user priority and the number of scheduled packets, while the underlying scheduler allocates the resource. Our proposed scheme achieves lower delay jitter and delay violation rate than the Round-Robin Earliest Deadline First algorithm and MARL with delay violation penalty.

翻译：本文提出了一种两阶段智能调度器，旨在保证时延上限的同时最小化分组级时延抖动。首先，采用李雅普诺夫技术将时延违规约束转化为序列化的时隙级队列稳定性问题。其次，提出一种分层方案以解决多基站与用户间的资源分配问题：其中多智能体强化学习（MARL）负责确定用户优先级及调度分组数量，而底层调度器则执行资源分配。与轮询最早截止时间优先算法及带有时延违规惩罚的MARL方法相比，本文所提方案实现了更低的时延抖动与更低的时延违规率。