  Wi-Fi in the enterprise - characterized by overlapping Wi-Fi cells -
constitutes the design challenge for next-generation networks. Standardization
for recently started IEEE 802.11be (Wi-Fi 7) Working Groups has focused on
significant medium access control layer changes that emphasize the role of the
access point (AP) in radio resource management (RRM) for coordinating channel
access due to the high collision probability with the distributed coordination
function (DCF), especially in dense overlapping Wi-Fi networks. This paper
proposes a novel multi-AP coordination system architecture aided by a
centralized AP controller (APC). Meanwhile, a deep reinforcement learning
channel access (DLCA) protocol is developed to replace the binary exponential
backoff mechanism in DCF to enhance the network throughput by enabling the
coordination of APs. First-Order Model-Agnostic Meta-Learning further enhances
the network throughput. Subsequently, we also put forward a new greedy
algorithm to maintain proportional fairness (PF) among multiple APs. Via the
simulation, the performance of DLCA protocol in dense overlapping Wi-Fi
networks is verified to have strong stability and outperform baselines such as
Shared Transmission Opportunity (SH-TXOP) and Request-to-Send/Clear-to-Send
(RTS/CTS) in terms of the network throughput by 10% and 3% as well as the
network utility considering proportional fairness by 28.3% and 13.8%,
respectively.
