@TechReport{	  it:2014-023,
  author	= {Venkatraman Iyer and Frederik Hermans and Thiemo Voigt},
  title		= {Detecting and Avoiding Multiple Sources of Interference in
		  the 2.4 {GHz} Spectrum},
  institution	= {Department of Information Technology, Uppsala University},
  department	= {Division of Computer Systems},
  year		= {2014},
  number	= {2014-023},
  month		= dec,
  abstract	= {Sensor networks operating in the 2.4 GHz band often face
		  cross-technology interference from co-located WiFi and
		  Bluetooth devices. To enable effective interference
		  mitigation, a sensor network needs to know the type of
		  interference it is exposed to. However, existing approaches
		  to interference detection are not able to handle multiple
		  concurrent sources of interference. In this paper, we
		  address the problem of identifying multiple channel
		  activities impairing a sensor network~s communication, such
		  as simultaneous WiFi traffic and Bluetooth data transfers.
		  We present SpeckSense, an interference detector that
		  distinguishes between different types of interference using
		  a unsupervised learning technique. Additionally, SpeckSense
		  features a classifier that distinguishes between moderate
		  and heavy channel traffic, and also identifies WiFi
		  beacons. In doing so, it facilitates interference avoidance
		  through channel blacklisting. We evaluate SpeckSense on
		  common mote hardware and show how it classifies concurrent
		  interference under real-world settings. We also show how
		  SpeckSense improves the performance of an existing
		  multichannel data collection protocol by 30\%.}
}