Multi-Access Point Coordination (MAPC) will be a key feature in next generation Wi-Fi 8 networks. MAPC aims to improve the overall network performance by allowing Access Points (APs) to share time, frequency and/or spatial resources in a coordinated way, thus alleviating inter-AP contention and enabling new multi-AP channel access strategies. This paper introduces a framework to support periodic MAPC transmissions on top of current Wi-Fi operation. We first focus on the problem of creating multi-AP groups that can transmit simultaneously to leverage Spatial Reuse opportunities. Then, once these groups are created, we study different scheduling algorithms to determine which groups will transmit at every MAPC transmission. Two different types of algorithms are tested: per-AP, and per-Group. While per-AP algorithms base their scheduling decision on the buffer state of individual APs, per-Group algorithms do that taking into account the aggregate buffer state of all APs in a group. Obtained results -- targetting worst-case delay -- show that per-AP based algorithms outperform per-Group ones due to their ability to guarantee that the AP with a) more packets, or b) with the oldest waiting packet in the buffer is selected.

翻译：多接入点协调（MAPC）将成为下一代Wi-Fi 8网络的关键特性。MAPC通过允许接入点以协调方式共享时间、频率和/或空间资源，从而缓解接入点间竞争并支持新型多AP信道接入策略，旨在提升整体网络性能。本文提出一种在现有Wi-Fi运行机制之上支持周期性MAPC传输的框架。我们首先聚焦于创建可同时传输的多AP群组问题，以利用空间复用机会；随后，在群组建立后，研究不同调度算法以确定每次MAPC传输中哪些群组进行传输。测试包含两类算法：每AP型与每群组型。每AP型算法基于单个AP的缓冲状态进行调度决策，而每群组型算法则综合考虑群组内所有AP的聚合缓冲状态。针对最差时延的优化结果表明，每AP型算法因能确保选择具有a）更多数据包或b）缓冲中最旧等待数据包传输的AP，其性能优于每群组型算法。