Passive Wi-Fi Link Capacity Estimation on Commodity Access Points

Diego Neves da Hora (1) , Karel van Doorselaer (2) , Koen van Oost (2) , Renata Teixeira (1) , Christophe Diot (3)

1 MUSE - Measuring networks for enhancing USer Experience
2 Technicolor
3 SAFRAN Group

Wi-Fi is the preferred way of accessing the internet for many devices at home, but it is vulnerable to performance problems. In this work, we propose a method to estimate the link capacity of a Wi-Fi link using physical layer metrics passively sampled on commodity access points. We build a model that predicts the maximum UDP throughput a device can sustain, which extends previous models to consider IEEE 802.11n optimizations such as frame aggregation. We validate our model through controlled experiments in an anechoic chamber. Over 95% of the link capacity predictions present errors below 5% when using our model with reference data. We show how link capacity estimation enables Wi-Fi diagnosis in two case studies where we predict the available bandwidth under microwave interference and in an office environment.

Domaines: Réseaux et télécommunications [cs.NI]

Diego Neves da Hora, Karel van Doorselaer, Koen van Oost, Renata Teixeira, Christophe Diot. Passive Wi-Fi Link Capacity Estimation on Commodity Access Points. Traffic Monitoring and Analysis Workshop (TMA) 2016, Apr 2016, Louvain-la-Neuve, Belgium. ⟨hal-01292633⟩