Estimation of Interference in Wi-Fi Networks

Interference is a troublesome issue that affects the throughput performance of Wi-Fi networks. Therefore it becomes crucial to estimate the interference between nodes and links of a wireless network. This approach includes passive monitoring of traffic which consists of placing multiple sniffers near network nodes to capture the wireless traffic. This traffic is analyzed to conclude about the carrier-sense relationship between nodes by using a machine learning approach. This combined with an estimation of collision probabilities helps us to arrive at the interference relation-ships. The main focus of work is to 1) identify instances when the two nodes attempt to simultaneously transmit, and 2) conclude the deferral behaviors during such instances. This paper offers an overview of the different techniques of measurement-based modeling and estimation of interference associated with wireless networks.