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CrossZig: Combating Cross-Technology Interference in Low-power Wireless Networks
ETH Zurich, Switzerland.
EPFL Swiss Federal Institute of Technology in Lausanne, Switzerland.
ETH Zurich, Switzerland.
KTH Royal Institute of Technology, Sweden.
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2016 (Engelska)Ingår i: 2016 15th ACM/IEEE International Conference on Information Processing in Sensor Networks, IPSN 2016 - Proceedings, 2016, artikel-id 7460663Konferensbidrag, Publicerat paper (Refereegranskat)
Abstract [en]

Low-power wireless devices suffer notoriously from Cross- Technology Interference (CTI). To enable co-existence, researchers have proposed a variety of interference mitigation strategies. Existing solutions, however, are designed to work with the limitations of currently available radio chips. In this paper, we investigate how to exploit physical layer properties of 802.15.4 signals to better address CTI. We present CrossZig, a cross-layer solution that takes advantage of physical layer information and processing to improve low-power communication under CTI. To this end, CrossZig utilizes physical layer information to detect presence of CTI in a corrupted packet and to apply an adaptive packet recovery which incorporates a novel cross-layer based packet merging and an adaptive FEC coding. We implement a prototype of CrossZig for the low-power IEEE 802.15.4 in a software-defined radio platform. We show the adaptability and the performance gain of CrossZig through experimental evaluation considering both micro-benchmarking and system performance under various interference patterns. Our results demonstrate that CrossZig can achieve a high accuracy in error localization (94.3% accuracy) and interference type identification (less than 5% error rate for SINR ranges below 3 dB). Moreover, our system shows consistent performance improvements under interference from various interfering technologies.

Ort, förlag, år, upplaga, sidor
2016. artikel-id 7460663
Nyckelord [en]
Interference, Physical layer, IEEE 802.15 Standard, Wireless communication, Wireless sensor networks, Signal to noise ratio, Diversity reception
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Identifikatorer
URN: urn:nbn:se:ri:diva-26212DOI: 10.1109/IPSN.2016.7460663ISBN: 9781509008025 (tryckt)OAI: oai:DiVA.org:ri-26212DiVA, id: diva2:1050934
Konferens
15th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN 2016), April 11-14, 2016, Vienna, Austria
Tillgänglig från: 2016-11-30 Skapad: 2016-11-30 Senast uppdaterad: 2019-06-19Bibliografiskt granskad

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Duquennoy, Simon

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Computer Systems Laboratory
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