Channel Characterization and Link Quality Assessment of IEEE 802.15.4-Compliant Radio for Factory Environments

Tang, Lei; Wang, Kuang-Ching; Huang, Yong; Gu, Fangming

doi:10.1109/tii.2007.898414

Cited by 166 publications

(129 citation statements)

References 15 publications

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“…To facilitate the design of error control mechanisms, a better understanding of the error characteristics of IEEE 802.15.4-compliant transceivers in industrial environments will be useful [108], [109].…”

Section: Research Issues For Ieee 802154 In Industrial Environmentsmentioning

confidence: 99%

“…The precise error characteristics depend on the specific wireless technology, the carrier frequency, the distance and propagation environment between transmitter and receiver, and other factors. Measurements of the error characteristics in industrial environments have been presented in a number of studies and for different types of wireless technologies: Bluetooth [136], IEEE 802.11b [135], IEEE 802.11a [31] or IEEE 802.15.4 [109].…”

Section: Combating Channel Fading With Spatial/cooperative Diversmentioning

confidence: 99%

“…A necessary precondition for this is to collect detailed measurements about wireless industrial channels (for example [31], [109], [135], and [136]). To support this, community initiatives for collecting wireless traces, similar to the CRAWDAD initiative at the University of Dartmouth might be useful.…”

Section: Quality Of Service Provisioning and Analysismentioning

confidence: 99%

See 2 more Smart Citations

Recent and Emerging Topics in Wireless Industrial Communications: A Selection

Willig

2008

IEEE Trans. Ind. Inf.

567

329

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Abstract-In this paper we discuss a selection of promising and interesting research areas in the design of protocols and systems for wireless industrial communications. We have selected topics that have either emerged as hot topics in the industrial communications community in the last few years (like wireless sensor networks), or which could be worthwhile research topics in the next few years (for example cooperative diversity techniques for error control, cognitive radio/opportunistic spectrum access for mitigation of external interferences).Index Terms-Cognitive radio, IEEE 802154, industrial-QoS, spatial and cooperative diversity, ultra-wideband, wireless sensor networks, ZigBee.

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Section: Research Issues For Ieee 802154 In Industrial Environmentsmentioning

confidence: 99%

Section: Combating Channel Fading With Spatial/cooperative Diversmentioning

confidence: 99%

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Recent and Emerging Topics in Wireless Industrial Communications: A Selection

Willig

2008

IEEE Trans. Ind. Inf.

567

329

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“…It combines (i) a static component ℓ characterized by a distance-dependent LOS term 0 ( , ) and an excess attenuation that accounts for the building blockage; (ii) a zeromean random term accounting for the fluctuations of the received power with typical standard deviation around √ E[ 2 ] = 3 ÷ 5 dB in static environments [6]. In what follows, it is derived a model for the static RSS component ℓ .…”

Section: Channel Modelingmentioning

confidence: 99%

Wireless Sensor Network Modeling and Deployment Challenges in Oil and Gas Refinery Plants

Savazzi

Guardiano

Spagnolini

2013

International Journal of Distributed Sensor Networks

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Wireless sensor networks for critical industrial applications are becoming a remarkable technological paradigm. Large-scale adoption of the wireless connectivity in the field of industrial monitoring and process control is mandatorily paired with the development of tools for the prediction of the wireless link quality to mimic network planning procedures similar to conventional wired systems. In industrial sites, the radio signals are prone to blockage due to dense metallic structures. The layout of scattering objects from the existing infrastructure influences the received signal strength observed over the link and thus the quality of service (QoS). This paper surveys the most promising wireless technologies for industrial monitoring and control and proposes a novel channel model specifically tailored to predict the quality of the radio signals in environments affected by highly dense metallic building blockage. The propagation model is based on the diffraction theory, and it makes use of the 3D model of the plant to classify the links based on the number and density of the obstructions surrounding each individual radio device. Accurate link classification opens the way to the optimization of the network deployment to guarantee full end-to-end connectivity with minimal on-site redesign. The link-quality prediction method based on the classification of propagation conditions is validated by experimental measurements in two oil refinery sites using industry standard ISA SP100.11a compliant devices operating at 2.4 GHz.

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“…In the past, the RSSI has been exploited for nodes localization [2], [3], distance estimation [4], [5], and link quality assessment purposes [6], [7]. However, it has also proved to be useful for detecting the movements of individuals found inside the monitored area [8], [9], [10].…”

Section: Introductionmentioning

confidence: 99%

Real-Time Intrusion Detection and Tracking in Indoor Environment through Distributed RSSI Processing

Kaltiokallio

Bocca

2011

2011 IEEE 17th International Conference on Embedded and Real-Time Computing Systems and Applications

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Abstract-In the context of wireless sensor networks, the received signal strength indicator has been traditionally exploited for localization, distance estimation, and link quality assessment. Recent research has shown that, in indoor environments where nodes have been deployed, variations of the signal strength can be exploited to detect movements of persons. Moreover, the time histories of the received signal strength indicator of multiple links allow reconstructing the paths followed by the persons inside the monitored area. This approach, though effective, requires the transmission of multiple, raw received signal strength indicator time histories to a central sink node for off-line analysis. This consistently increases the latency and power consumption of the system. This work aims at applying distributed processing of the received signal strength indicator for indoor surveillance purposes. Through distributed processing, the nodes are able to autonomously detect and localize moving persons. The latency and power consumption of the system are minimized by transmitting to the sink node only the alerts related to significant events. Moreover, power consumption is further reduced through a high accuracy time synchronization protocol, which allows the nodes to keep the radio off for 60 % of the time. During the tests, the system was able to detect the intrusion of a person walking inside the monitored area and to correctly track his movements in real-time with a 0.22 m average error. Possible applications of this application include surveillance of critical areas in buildings, enhancement of workers safety in factories, support to emergency workers or police forces in locating people e.g. during fires, hostage situations or terrorist attacks.

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Channel Characterization and Link Quality Assessment of IEEE 802.15.4-Compliant Radio for Factory Environments

Cited by 166 publications

References 15 publications

Recent and Emerging Topics in Wireless Industrial Communications: A Selection

Recent and Emerging Topics in Wireless Industrial Communications: A Selection

Wireless Sensor Network Modeling and Deployment Challenges in Oil and Gas Refinery Plants

Real-Time Intrusion Detection and Tracking in Indoor Environment through Distributed RSSI Processing

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