We present SpeckSense, an interference detector that distinguishes between different types of interference using a unsupervised learning technique.
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. However, existing approaches to interference detection are not able to handle multiple concurrent sources of interference. To enable effective interference mitigation, a sensor network needs to know the type of interference it is exposed to. Sensor networks operating in the 2.4 GHz band often face cross-technology interference from co-located WiFi and Bluetooth devices.
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