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.