Publications

Abstract : We develop a scalable cell-level analytical model for multi-cell infrastructure IEEE 802.11 WLANs under a so-called Pairwise Binary Dependence (PBD) condition. The PBD condition is a geometric property under which the relative locations of the nodes inside a cell do not matter and the network is free of hidden nodes. For a given number of cells, the computational complexity of our cell-level model remains constant even if the number of nodes per cell increases. For the cases of saturated nodes and TCP-controlled long-file downloads, we provide accurate predictions of cell throughputs. Similar to Bonald et al. (Sigmetrics, 2008), we model a multi-cell WLAN under short-file downloads as “a network of processor-sharing queues with state-dependent service rates.” Whereas the state-dependent service rates proposed by Bonald et al. are based only on the number of contending neighbors, we employ state-dependent service rates that incorporate the impact of the overall topology of the network. We propose an effective service rate approximation technique and obtain good approximations for the mean flow transfer delay in each cell. For TCP-controlled downloads where the Access Points (APs) transmit for a much larger fraction of time than the stations (STAs), we consider the case when the APs can sense all the nodes in the neighboring cell, but ≈50% of the STAs in each cell can sense only a subset of STAs in the other cell. Our cell-level model can predict the throughputs quite accurately in this case as well even though the PBD condition does not strictly hold.