2019
DOI: 10.1049/iet-rsn.2018.5231
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Vehicle detection and classification using LTE‐CommSense

Abstract: We demonstrated a vehicle detection and classification method based on Long Term Evolution (LTE) communication infrastructure based environment sensing instrument, termed as LTE-CommSense by the authors. This technology is a novel passive sensing system which focuses on the reference signals embedded in the sub-frames of LTE resource grid. It compares the received signal with the expected reference signal, extracts the evaluated channel state information (CSI) and analyzes it to estimate the change in the envi… Show more

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Cited by 9 publications
(4 citation statements)
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“…The description and working principle of an USRP N200 SDR platform can be obtained from [6,7]. The SDR was modelled as the CommSense prototype containing LTE receiver.…”
Section: Lte-commsense Systemmentioning
confidence: 99%
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“…The description and working principle of an USRP N200 SDR platform can be obtained from [6,7]. The SDR was modelled as the CommSense prototype containing LTE receiver.…”
Section: Lte-commsense Systemmentioning
confidence: 99%
“…The concept of Comm-Sense was proposed and verified by the authors in simulation and with field-collected data for various indoor applications like indoor object detection, indoor localization and indoor occupancy estimation [6]. The system was also tested for outdoor vehicle detection and classification [7]. These give the confidence to apply the CommSense principle to perform outdoor crowd size measurement.…”
Section: Introductionmentioning
confidence: 99%
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“…In addition, radio jammers could be used to explicitly attack those systems. Sardar et al [45] furthermore present an unique approach, which implements the general idea of radiofingerprinting for long-range communication via Long Term Evolution (LTE). Their proposed Software Defined Radio (SDR)-based method entitled LTE-CommSense monitors the received downlink CSI the User Equipment (UE) side.…”
Section: B Vehicle Detection and Classification Systemsmentioning
confidence: 99%