A new concept for wireless reconfigurable receivers

Palicot, Jacques; Roland, Christian

doi:10.1109/mcom.2003.1215649

Cited by 63 publications

(33 citation statements)

References 4 publications

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“…Some works in the literature [6,7,8] consider spectrum sensing as a method for distinguishing between two or more different types of signals or technologies in operation. Since this is not a question of detection (determining whether a given frequency band is being used), these types of signal identification issues such as [9] are not addressed in this chapter.…”

Section: Characteristics Of Spectrum Sensingmentioning

confidence: 99%

Spectrum Sensing for Cognitive Radio

2009

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Section: Characteristics Of Spectrum Sensingmentioning

confidence: 99%

Spectrum Sensing for Cognitive Radio

2009

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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.

135

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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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“…These features include amount of energy detected and its distribution across the spectrum. Channel bandwidth and its shape are used in [35] as reference features. Channel bandwidth is found to be the most discriminating parameter among others.…”

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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A new concept for wireless reconfigurable receivers

Cited by 63 publications

References 4 publications

Spectrum Sensing for Cognitive Radio

Spectrum Sensing for Cognitive Radio

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

Performance Analysis and Comparative Study of Cognitive Radio Spectrum Sensing Schemes

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