Implementation of GSM channel estimation using open-source SDR environment

Bhatta, Abhishek; Mishra, Amit Kumar

doi:10.1109/icmoce.2015.7489757

Cited by 7 publications

(6 citation statements)

References 6 publications

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“…In some of the previous reports from our work on CommSense we have shown some encouraging results using both GSM and LTE telecommunication standards ( [7], [8], [20], [21]). However, we have not done a formal analysis of the performances of this newly proposed instrument.…”

Section: Introductionmentioning

confidence: 57%

Performance Evaluation of LTE-CommSense System for Discriminating the Presence of Multiple Objects in Outdoor Environment

Sardar

Mishra

Khan

2020

IEEE Trans. Instrum. Meas.

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Section: Introductionmentioning

confidence: 57%

Performance Evaluation of LTE-CommSense System for Discriminating the Presence of Multiple Objects in Outdoor Environment

Sardar

Mishra

Khan

2020

IEEE Trans. Instrum. Meas.

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“…The Naive Nearest Neighbour classifier is selected in this feasibility analysis. Previous works on CommSense have shown promising results using both GSM and LTE telecommunication standards ( [6], [7], [11], [8]). Our proposed hypothesis in this work is that, using extracted CSI values of LTE downlink signal, vehicle can be detected and multiple vehicle can be classified.…”

Section: Lte-commsense Systemmentioning

confidence: 99%

“…Main principle of these systems are to transmit a signal and analyse corresponding reflected signal from the vehicle. Passive Radar or commensal Radar [1, 2, 6, 7] enjoys benefit from each other without any detrimental effect on each other. The efforts of coexistence using commensal Radar principle have many real‐world applications [7, 8].…”

Section: Introductionmentioning

confidence: 99%

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Vehicle detection and classification using LTE‐CommSense

Sardar

Mishra²,

Khan

2019

IET Radar, Sonar & Navigation

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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 environment. For vehicle detection and subsequent classification, our setup is similar to a passive radar in forward scattering radar (FSR) mode. Instead of performing the radio frequency (RF) signals directly, we take advantage of the processing that happens in a LTE receiver user equipment (UE). We tap into the channel estimation and equalization block and extract the CSI value. CSI value reflects the property of the communication channel between communication base station (eNodeB) and UE. We use CSI values for with and vehicle and without vehicle case in outdoor open road environment. Being a receiver only system, there is no need for any transmission and related regulations. Therefore, this system is low cost, power efficient and difficult to detect. Also, most of its processing will be done by the existing LTE communication receiver (UE). In this paper, we establish our claim by analyzing field-collected data. Live LTE downlink (DL) signal is captured using modeled LTE UE using software defined radio (SDR). The detection analysis and classification performance shows promising results and ascertains that, LTE-CommSense is capable of detection and classification of different types of vehicles in outdoor road environment.

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“…These interferences are proportional to the properties of the channel itself. In communication systems this type of interference causes degradation of the information and thus various channel equalization techniques are used to minimize the channel effects [6,14,15]. In case of a GSM system the transmitter transmits a known bit stream referred to as a training sequence which is used at the receiver to equalize the effects of the channel.…”

Section: Gsm-commsense: a Short Reviewmentioning

confidence: 99%

GSM–CommSense-based through-the-wall sensing

Bhatta

Mishra

2017

Remote Sensing Letters

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We have recently proposed a scheme to use the channel equalization blocks of telecommunication systems to sense changes in an environment. We call this communication-sensing, CommSense for short.After some initial positive results we tried to use our global system for mobile communication (GSM)based CommSense system for a through-the-wall sensing application. As the system was inherently highly under-determined we used statistical machine learning techniques to help us sense environmental changes in the behind-the-wall experiments. We observed that with limited amount of data per GSM frame of 577 µs a person can be detected across a wall to an accuracy of 77.458% and a person carrying a weapon can be detected to an accuracy of 95.208%. We present details of the experiments and the encouraging results that we have obtained in this article.

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Implementation of GSM channel estimation using open-source SDR environment

Cited by 7 publications

References 6 publications

Performance Evaluation of LTE-CommSense System for Discriminating the Presence of Multiple Objects in Outdoor Environment

Performance Evaluation of LTE-CommSense System for Discriminating the Presence of Multiple Objects in Outdoor Environment

Vehicle detection and classification using LTE‐CommSense

GSM–CommSense-based through-the-wall sensing

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