IST-TRUST: a perspective on the reconfiguration of future mobile terminals using software download

Farnham, Tim; Clemo, Gary; Haines, Russell; Seidel, E.; Benamar, A.; Billington, S.; Greco, Nancy; Drew, N.J.; Le, Truong Hong; Arram, B.; Mangold, Paul

doi:10.1109/pimrc.2000.881582

Cited by 26 publications

(17 citation statements)

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“…Detectors extract signal features such as channel bandwidth and cycle frequencies, and use machine learning techniques to classify the technology being used [53], [58], [59].…”

Section: ) Feature Based Detectionmentioning

confidence: 99%

Using Cognitive Radio for Interference-Resistant Industrial Wireless Sensor Networks: An Overview

Chiwewe

Mbuya

Hancke

2015

IEEE Trans. Ind. Inf.

138

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Abstract-Industrial wireless sensor networks have to contend with environments that are usually harsh and time varying. Industrial wireless technology, such as WirelessHART and ISA 100.11a, also operates in a frequency spectrum utilised by many other wireless technologies, and with wireless applications rapidly growing it is possible that multiple heterogeneous wireless systems would need to operate in overlapping spatiotemporal regions. Interference such as noise or other wireless devices affects connectivity and reduces communication link quality. This negatively affects reliability and latency, which are core requirements of industrial communication. Building wireless networks that are resistant to noise in industrial environments and can coexist with competing wireless devices in an increasingly crowded frequency spectrum is challenging. To meet these challenges, we need to consider the benefits that approaches finding success in other application areas can offer industrial communication. Cognitive radio methods offer a potential solution to improve resistance of industrial wireless sensor networks to interference. Integrating cognitive radio principles into the lower layers of industrial wireless sensor networks can enable devices to detect and avoid interference and potentially opens the possibility of utilising free radio spectrum for additional communication channels. This improves resistance to noise and increases redundancy in terms of channels per network node or adding additional nodes. In this paper, we summarise cognitive radio methods relevant to industrial applications, covering cognitive radio architecture, spectrum access and interference management, spectrum sensing, dynamic spectrum access, game theory and cognitive radio network security.Index Terms-Cognitive radio, industrial wireless sensor networks, Internet of Things, spectrum management, spectrum sensing.

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“…Detectors extract signal features such as channel bandwidth and cycle frequencies, and use machine learning techniques to classify the technology being used [53], [58], [59].…”

Section: ) Feature Based Detectionmentioning

confidence: 99%

Using Cognitive Radio for Interference-Resistant Industrial Wireless Sensor Networks: An Overview

Chiwewe

Mbuya

Hancke

2015

IEEE Trans. Ind. Inf.

138

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“…In the radio identification stage of the method, several features of the received signal are exploited and then classified to determine if the signal demonstrates the PU signal technology [26]. Fundamentally, the feature extraction and classification techniques are used in the context of European Transparent Ubiquitous Terminal (TRUST) project [27]. For collecting the signal features, the radio identification method may use one of the known sensing techniques, such as the energy detection method [9].…”

Section: Radio Identification Based Sensingmentioning

confidence: 99%

Spectrum Sensing in Cognitive Radio Networks : QoS Considerations

Giweli

Shahrestani

Cheung

2015

Computer Science &Amp; Information Technology ( CS &Amp; IT )

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“…For radio identification, feature extraction and classification techniques are used in the context of European transparent ubiquitous terminal (TRUST) project [33]. The goal is to identify the presence of some known transmission technologies and achieve communication through them.…”

Section: Radio Identification Based Sensingmentioning

confidence: 99%

Performance Analysis and Comparative Study of Cognitive Radio Spectrum Sensing Schemes

Singh¹

2013

IOSR-JECE

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IST-TRUST: a perspective on the reconfiguration of future mobile terminals using software download

Cited by 26 publications

References 0 publications

Using Cognitive Radio for Interference-Resistant Industrial Wireless Sensor Networks: An Overview

Using Cognitive Radio for Interference-Resistant Industrial Wireless Sensor Networks: An Overview

Spectrum Sensing in Cognitive Radio Networks : QoS Considerations

Performance Analysis and Comparative Study of Cognitive Radio Spectrum Sensing Schemes

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