In interfering WLANs, clients are usually non-uniformly distributed. Therefore, their throughput can be improved by association control. WLANs adopt DCF (Distributed Coordinating Function) for media access control. The transmit probability of an AP is governed by its CW (Contention Window). Random Access control is to determine the CW size and hence the transmit probability of each AP. Client association control and random access control are coupled. APs associated with more clients require higher channel access opportunities. On the other hand, APs with higher transmit probability should serve more clients. We study the novel problem of maximizing the proportional fairness of client throughput by joint association control and random access control. As the joint problem is non-convex, we first consider that client association is given and propose an optimal policy for random access control. Given the CWs of APs, we propose a factor-2 approximation algorithm, Greedy-Asso to address the client association problem. Inspired by the optimal access control policy and Greedy-Asso, we further propose a distributed algorithm, termed CARA to tackle the joint optimization problem. Extensive simulation and experimental studies show that it outperforms comparison schemes by a wide margin in terms of throughput and fairness.

中文翻译：

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MU-MIMO WLAN 的联合客户端关联和随机访问控制

在干扰 WLAN 中，客户端通常是非均匀分布的。因此，它们的吞吐量可以通过关联控制来提高。WLAN 采用​​ DCF（分布式协调功能）进行媒体访问控制。AP 的传输概率由其 CW（竞争窗口）控制。随机接入控制用于确定 CW 大小，从而确定每个 AP 的传输概率。客户端关联控制和随机访问控制是耦合的。与更多客户端关联的 AP 需要更多的信道访问机会。另一方面，具有更高传输概率的 AP 应该为更多客户端提供服务。我们研究了通过联合关联控制和随机访问控制最大化客户端吞吐量的比例公平的新问题。由于联合问题是非凸的，我们首先考虑给定客户端关联并提出随机访问控制的最佳策略。鉴于 AP 的 CW，我们提出了一个因子 2 近似算法 Greedy-Asso 来解决客户端关联问题。受最优访问控制策略和 Greedy-Asso 的启发，我们进一步提出了一种分布式算法，称为 CARA 来解决联合优化问题。大量的模拟和实验研究表明，它在吞吐量和公平性方面大大优于比较方案。称为 CARA 来解决联合优化问题。大量的模拟和实验研究表明，它在吞吐量和公平性方面大大优于比较方案。称为 CARA 来解决联合优化问题。大量的模拟和实验研究表明，它在吞吐量和公平性方面大大优于比较方案。