Characterizing the impact of interference through spectral analysis on commercial 802.11 devices

Performance experienced by end-users supporting the popular 802.11 protocol is significantly degraded in densely populated urban areas, mainly due to the extensive spectrum sharing and the resulting 802.11 impairments such as ”hidden-terminals”, overlapping channel interference, etc. Moreover, as the unlicensed spectrum is also home for other wireless technologies and a large range of RF devices, the experienced channel conditions further deteriorate due to cross-technology interference. While the various resulting phenomena can be efficiently mitigated by isolating affected links from interference sources over spectrum, 802.11 networks currently lack unified mechanisms for characterizing the impact of different interference sources across the available channel configurations. In this work, we take advantage of spectral measurements available at the PHY-layer of commercial 802.11 equipment, in order to develop a highly accurate spectral analysis mechanism that is able to quantify the impact of interference on WLAN performance. The developed distributed mechanism concurrently operates on all network nodes and characterizes the band of interest with minimal overhead. Through the implementation of our approach on commercial 802.11n chipsets and its detailed experimental evaluation, we showcase its applicability in characterizing the impact of spectrum congestion and interference in a unified way, towards driving efficient spectrum adaptation decisions.