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Ubiquitous, yet Deceptive: Hardware-Based Channel Metrics on Interfered WSN Links
Mid Sweden University, Faculty of Science, Technology and Media, Department of Information and Communication systems. (IKS)
Mid Sweden University, Faculty of Science, Technology and Media, Department of Information and Communication systems. (ABB CRC)
Mid Sweden University, Faculty of Science, Technology and Media, Department of Information and Communication systems.
2015 (English)In: IEEE Transactions on Vehicular Technology, ISSN 0018-9545, E-ISSN 1939-9359, Vol. 64, no 5, p. 1766-1778Article in journal (Refereed) Published
Abstract [en]

The ease of acquiring hardware-based link quality indicators is an alluring property for fast channel estimation in time- and safety-critical Wireless Sensor Network (WSN) applications, such as closed-loop control and interlocking. The two rudimentary hardware-based channel quality metrics, Received Signal Strength (RSS) and Link Quality Indicator (LQI), are the key constituents of channel estimation and a plethora of other WSN functionalities, from routing to transmit power control. Nevertheless, this study highlights three deficient aspects of these two indicators: 1) overall deceptiveness, i.e. the inability to reveal the presence of interference, falsely indicating excellent channel conditions in an unacceptably high fraction of cases; 2) the burstiness of missed detections, which compromises the attempts to eliminate the deceptiveness by averaging; 3) high mutual discrepancy of the two indicators, observed in 39-73% of packets, throughout different scenarios. The ability of RSS and LQI to indicate IEEE 802.11 interference is scrutinized in a variety of scenarios in typical industrial environments, using commercialoff- the-shelf hardware and realistic network topologies, giving the findings of this study a high general validity and practical relevance.

Place, publisher, year, edition, pages
2015. Vol. 64, no 5, p. 1766-1778
Keywords [en]
IEEE 802.15.4, industrial wireless sensor network (WSN), interference, link quality, link quality indicator (LQI), received signal strength (RSS)
National Category
Telecommunications
Identifiers
URN: urn:nbn:se:miun:diva-22908DOI: 10.1109/TVT.2014.2334494ISI: 000354472800010Scopus ID: 2-s2.0-84929340066Local ID: STCOAI: oai:DiVA.org:miun-22908DiVA, id: diva2:745972
Projects
COINS
Funder
Knowledge Foundation
Note

Publ online Jul 2014

Available from: 2014-09-11 Created: 2014-09-11 Last updated: 2017-12-05Bibliographically 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: 2018-01-10Bibliographically approved

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Barac, FilipGidlund, MikaelZhang, Tingting

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