Throughput Analysis of Dense WLANs Using Continuous-Time Markov Chain Model
Tao Lei, Shan Jiang, Xiangming Wen, Zhaoming Lu, Lingchao Guo · 2017
This paper analyzes the throughput performance of dense Wireless Local Area Networks (WLANs) with random topologies using the continuous time Markov chain (CTMC) model. Because the main factor that affects the accuracy of throughput analysis of dense WLANs is the interference caused by the simultaneous transmitting access points (APs). The accuracy decreases as the interference becomes increasingly significant. Therefore, we introduce coverage probability model into the CTMC model, thus capturing the effects of interference on the transmission process. In order to capture all the feasible CTMC states of different network topologies, we present a Feasible State Searching Algorithm (FSSA) which can calculate the number of states that each basic service set (BSS) belongs to and the total number of states in a CTMC model. Simulation results indicate that the proposed CTMC based throughput analysis method can capture the throughput properties of dense WLANs with random topologies.