Coordinated beamforming (Co-BF) is a key multi-access-point coordination (MAPC) technique for dense Wi-Fi deployments, but its performance can be hindered by the large channel state information (CSI) feedback required through channel sounding across overlapping basic service sets (OBSS). This work proposes an autoencoder (AE)-based CSI compression mechanism integrated into a standards-aligned IEEE 802.11bn MAC design. Using an event-driven simulator with realistic channels generated through Sionna RT, we evaluate the tradeoff between AE reconstruction accuracy and feedback size by measuring their impact on channel sounding overhead and data latency. Our results show that AE-based compression reduces channel sounding overhead by more than 50% compared to IEEE 802.11 CSI compression, with a compression ratio of 1/4 providing the best accuracy/feedback-size tradeoff for lowest data latency. Compared to legacy transmissions without MAPC, IEEE 802.11 CSI compression limits Co-BF due to high channel sounding overhead, causing it to underperform the legacy in some situations. However, AE-based CSI compression enables better Co-BF performance with substantial gains in throughput and data latency compared to legacy, demonstrating its promise as an enabler of efficient MAPC operation in future Wi-Fi systems.

翻译：协调波束成形（Co-BF）是密集Wi-Fi部署中关键的多接入点协调（MAPC）技术，但其性能可能受到跨重叠基本服务集（OBSS）信道探测所需的大量信道状态信息（CSI）反馈的制约。本文提出一种基于自编码器（AE）的CSI压缩机制，该机制集成于符合标准的IEEE 802.11bn MAC设计中。通过使用基于Sionna RT生成真实信道的事件驱动仿真器，我们测量AE重构精度与反馈大小对信道探测开销和数据延迟的影响，以此评估二者间的权衡。结果表明，与IEEE 802.11 CSI压缩相比，基于AE的压缩能减少超过50%的信道探测开销，其中压缩比为1/4时可在最低数据延迟下实现最佳的精度/反馈大小权衡。相较于未采用MAPC的传统传输，IEEE 802.11 CSI压缩因信道探测开销过高而限制了Co-BF性能，导致其在某些情况下表现不及传统方案。然而，基于AE的CSI压缩能实现更优的Co-BF性能，并在吞吐量和数据延迟方面较传统方案获得显著提升，这证明了其作为未来Wi-Fi系统中高效MAPC操作使能技术的潜力。