Stochastic Geometry And Markov Chain Model Based Throughput Analysis In Dense Wlans

This paper analyzes the dense IEEE 802.11 wireless local area networks (WLANs) with random topologies using stochastic geometry and Markov chain model. Since Markov chain model for WLANs only focuses on 802.11 MAC layer performance and stochastic geometry model mainly focuses on physical layer effects, our mathematical models take both of these two layers into consideration. The locations of access points (Al's) and stations (STAs) are distributed according to two independent homogeneous Poisson point process (PPP) models. Then, an algorithm is proposed for systematically constructing the continuous time Markov chain (CTMC) corresponding to dense WLANs with random topologies. We use a Markov chain model to analyze the throughput performance of dense WLANs based on the CTMC model. The accuracy of our mathematical models is validated by simulations.