In next generation of Wi-Fi networks Multiple Access Point Coordination (MAPC) is poised to significantly enhance the network performance by enabling a set of Access Points (APs) to coordinate with each other through advanced coordinating schemes so that to reduce inter-AP contention and congestion. This paper focuses on defining a framework to facilitate the coordination across multi-APs when these employ Coordinated Spatial Reuse (C-SR). In this case, the coordinating APs may need to reciprocally adjust their scheduling strategy, power control and link adaptation to meet specific Quality of Service (QoS) requirements, which by using classical approaches leads to high overhead due to negotiations needed across APs, and requires complex solutions in order to properly optimize the network across all the parameters in play. In this matter, a two layer Multi-Armed Bandit (MAB) algorithm has been proposed to optimize such a network while preserving the fair use of resources across all nodes. The validity of this holistic approach is confirmed by system level simulations, which show that the proposed algorithm not only improves the network in terms of sum-throughput, but also allows to enhance fairness, making this a robust solution for next-generation of Wi-Fi networks.

翻译：在下一代Wi-Fi网络中，多接入点协调（MAPC）通过先进协调机制使一组接入点（AP）相互协作以减少AP间竞争与拥塞，有望显著提升网络性能。本文聚焦于定义一种框架，以促进采用协调空间复用（C-SR）的多AP间的协同。在此场景下，协调AP可能需相互调整其调度策略、功率控制及链路自适应，以满足特定的服务质量（QoS）要求。采用传统方法会导致AP间协商开销过高，且需要复杂的解决方案才能对网络中所有参数进行优化。为此，本文提出了一种两层多臂赌博机（MAB）算法，在保障各节点资源公平使用的前提下实现网络优化。系统级仿真验证了该整体方案的有效性：所提算法不仅能提升网络的总吞吐量，还能增强公平性，为下一代Wi-Fi网络提供了稳健的解决方案。