ErrorSense: Characterizing WiFi Error Patterns for Detecting ZigBee Interference

Abstract

Recent years have witnessed the increasing adoption of heterogeneous wireless networks working in unlicensed ISM bands, thus creating serious problems of spectrum overcrowding. Although ZigBee, Bluetooth and WiFi networks have been natively designed for working in presence of interference, it has been observed that several performance impairments may occur because of heterogeneous sensitivity to detect or react to the presence of other technologies. In this paper we focus on the WiFi capability to detect interfering ZigBee links. Despite of the narrowband transmissions performed by ZigBee, in emerging scenarios ZigBee interference can have a significant impact on WiFi performance. Therefore, interference detection is essential for improving coexistence strategies in heterogeneous networks. In our work we show how such a detection can be performed on commodity cards working on time and frequency domain and also analysing data in the error domain. Errors are monitored and classified into error patterns observed in the network in terms of occurrence probability and temporal clustering of different error events. Through statistical analysis we are able to detect the presence of ZigBee transmissions measuring the errors raised by the WiFi card.