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Channel Diagnostics for Wireless Sensor Networks in Harsh Industrial Environments
Mid Sweden University, Faculty of Science, Technology and Media, Department of Information and Communication systems. (IKS)
Natl Instruments Italy, I-20090 Milan, Italy.
Mid Sweden University, Faculty of Science, Technology and Media, Department of Information and Communication systems. (ABB CRC)ORCID iD: 0000-0003-0873-7827
Univ Brescia, Dept Informat Engn, I-25123 Brescia, Italy.
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2014 (English)In: IEEE Sensors Journal, ISSN 1530-437X, E-ISSN 1558-1748, Vol. 14, no 11, p. 3983-3995Article in journal (Refereed) Published
Abstract [en]

Wireless sensor network communication in industrial environments is compromised by interference, multipath fading, and signal attenuation. In that respect, accurate channel diagnostics is imperative to selecting the adequate countermeasures. This paper presents the lightweight packet error discriminator (LPED) that infers the wireless link condition by distinguishing between errors caused by multipath fading and attenuation, and those inflicted by interfering wideband single-channel communication systems (e.g., IEEE 802.11b/g), based on the differences in their error footprints. The LPED uses forward error correction in a novel context, namely, to determine the symbol error density, which is then fed to a discriminator for error source classification. The classification criteria are derived from an extensive set of error traces collected in three different types of industrial environments, and verified on a newly collected set of error traces. The proposed solution is evaluated both offline and online, in terms of classification accuracy, speed of channel diagnostics, and execution time. The results show that in ≥91% of cases, a single packet is sufficient for a correct channel diagnosis, accelerating link state inference by at least 270%, compared with the relevant state-of-the-art approaches. The execution time of LPED, for the worst case of packet corruption and maximum packet size, is below 30 ms with ≤3% of device memory consumption. Finally, live tests in an industrial environment show that LPED quickly recovers from link outage, by losing up to two packets on average, which is only one packet above the theoretical minimum.

Place, publisher, year, edition, pages
2014. Vol. 14, no 11, p. 3983-3995
Keywords [en]
IWSN, interference recognition, error discrimination, FEC, bit error traces
National Category
Telecommunications
Identifiers
URN: urn:nbn:se:miun:diva-22909DOI: 10.1109/JSEN.2014.2356972ISI: 000343610500001Scopus ID: 2-s2.0-84923182066Local ID: STCOAI: oai:DiVA.org:miun-22909DiVA, id: diva2:745976
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Knowledge FoundationAvailable from: 2014-09-11 Created: 2014-09-11 Last updated: 2022-04-06Bibliographically approved
In thesis
1. Error mitigation in industrial wireless sensor networks: Corrupted packet forensics and recovery
Open this publication in new window or tab >>Error mitigation in industrial wireless sensor networks: Corrupted packet forensics and recovery
2016 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Wireless sensor networks (WSN) are gradually penetrating the industrial automation domain. This process is, however, inhibited by a number of challenges that need to be considered and addressed before WSN can serve the most demanding industrial applications. In the context of process automation, existing technology can only serve the three least critical application classes related to non-critical monitoring of slowly-changing physical variables. The main issue in that respect is the insufficient communication timeliness and reliability, caused by the influence of harsh radio environment and the infeasibility of applying advanced communication techniques, due to the poor computational power of low-cost specialized hardware. The goal of this work is to improve wireless communication reliability in industrial environments, where the proposed solutions are generally applicable to other WSN domains as well as radio environments. This research is based on the notion that corrupt packets contain valuable channel state information that can be leveraged to improve communication robustness. The research methodology used in this work is rather unconventional, compared to existing research, but also highly intuitive, bearing in mind that counteracting a phenomenon requires a thorough knowledge of its properties. In order to rectify the aforementioned challenges, this work makes the following three contributions. The first contribution is a comprehensive analysis of communication errors recorded in practically relevant scenarios in a number of industrial environments. The related literature is seemingly rich, but essentially poor, due to inadequate measurement objectives, environments, and scenarios. The main research outcome of this measurement campaign is a set of practically relevant conclusions, which can be used for the design of coding, interleaving and packet recovery schemes. The second contribution is the design of two packet recovery schemes, based on the knowledge about error patterns obtained in the industrial measurement campaign. The first scheme is a proposal for redefinition of the IEEE 802.15.4 physical layer, where digital errors are counteracted at the earliest stage in the receiver chain. The second scheme exploits the determinism in packet structure inherent to industrial communication. Both schemes significantly improve the correctability of corrupted packets received. The third contribution is a channel diagnostics algorithm that determines whether a packet was corrupt by multipath fading and attenuation or by wireless local area network interference. The algorithm is derived from the error traces collected in three industrial environments and tested at a fourth, previously unused, industrial site. The results of live tests verify the ability of the proposed algorithm to promptly reestablish communication after a sudden deterioration of channel quality.

Place, publisher, year, edition, pages
Sundsvall: Mittuniversitetet, 2016. p. 158
Series
Mid Sweden University doctoral thesis, ISSN 1652-893X ; 239
National Category
Computer and Information Sciences
Identifiers
urn:nbn:se:miun:diva-28759 (URN)STC (Local ID)978-91-88025-54-8 (ISBN)STC (Archive number)STC (OAI)
Public defence
2016-03-02, Sundsvall, 10:15 (English)
Opponent
Supervisors
Available from: 2016-09-12 Created: 2016-09-12 Last updated: 2022-04-06Bibliographically approved

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Barac, FilipGidlund, MikaelZhang, Tingting

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