A Lightweight Classification Algorithm for External Sources of Interference in IEEE 802.15.4-Based Wireless Sensor Networks Operating at the 2.4 GHz
Author(s) -
Sven Zacharias,
Thomas Newe,
Sinéad O’Keeffe,
Elfed Lewis
Publication year - 2014
Publication title -
international journal of distributed sensor networks
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.324
H-Index - 53
eISSN - 1550-1477
pISSN - 1550-1329
DOI - 10.1155/2014/265286
Subject(s) - computer science , bluetooth , ieee 802.11 , wireless , interference (communication) , wireless sensor network , neurfon , channel (broadcasting) , ieee 802.15 , frequency band , energy (signal processing) , demodulation , computer network , real time computing , wireless network , key distribution in wireless sensor networks , antenna (radio) , telecommunications , statistics , mathematics
peer-reviewedIEEE 802.15.4 is the technology behind wireless sensor networks (WSNs) and ZigBee. Most of the IEEE 802.15.4 radios operate in the crowded 2.4 GHz frequency band, which is used by many technologies. Since IEEE 802.15.4 is a low power technology, the avoidance of interference is vital to conserve energy and to extend the lifetime of devices. A lightweight classification algorithm is presented to detect the common external sources of interference in the 2.4GHz frequency band, namely, IEEE 802.11-based wireless local area networks (WLANs), Bluetooth, and microwave ovens. This lightweight algorithm uses the energy detection (ED) feature (the feature behind received signal strength indication (RSSI)) of an IEEE 802.15.4-compliant radio. Therefore, it classifies the interferers without demodulation of their signals. As it relies on time patterns instead of spectral features, the algorithm has no need to change the channel. Thus, it allows the radio both to stay connected to the channel and to receive while scanning. Furthermore, it has a maximum runtime of merely one second. The algorithm is extensively tested in a radio frequency anechoic chamber and in real world scenarios. These results are presented here.PUBLISHEDpeer-reviewe
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