Search results for "Wireless fidelity"

showing 6 items of 6 documents

Error-Based Interference Detection in WiFi Networks

2017

In this paper we show that inter-technology interference can be recognized by commodity WiFi devices by monitoring the statistics of receiver errors. Indeed, while for WiFi standard frames the error probability varies during the frame reception in different frame fields (PHY, MAC headers, payloads) protected with heterogeneous coding, errors may appear randomly at any point during the time the demodulator is trying to receive an exogenous interfering signal. We thus detect and identify cross-technology interference on off-the-shelf WiFi cards by monitoring the sequence of receiver errors (bad PLCP, bad PCS, invalid headers, etc.) and develop an Artificial Neural Network (ANN) to recognize t…

Artificial Neural NetworkNeuronsMonitoringComputer scienceSettore ING-INF/03 - Telecomunicazioni05 social sciencesReal-time computingComputerSystemsOrganization_COMPUTER-COMMUNICATIONNETWORKS050801 communication & media studies020206 networking & telecommunicationsWireless LAN02 engineering and technologySpectrum managementReceiversZigBee0508 media and communicationsComputer Networks and CommunicationPHYHardware and Architecture0202 electrical engineering electronic engineering information engineeringLong Term EvolutionDemodulationWireless fidelitySafety Risk Reliability and QualityInterference
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Impact of LTE’s Periodic Interference on Heterogeneous Wi-Fi Transmissions

2018

The problem of Wi-Fi and LTE coexistence has been significantly debated in the last years, with the emergence of LTE extensions enabling the utilization of unlicensed spectrum for carrier aggregation. Rather than focusing on the problem of resource sharing between the two technologies, in this paper, we study the effects of LTE's structured transmissions on the Wi-Fi random access protocol. We show how the scheduling of periodic LTE transmissions modifies the behavior of 802.11's distributed coordination function (DCF), leading to a degradation of Wi-Fi performance, both in terms of channel utilization efficiency and in terms of channel access fairness. We also discuss the applicability and…

FOS: Computer and information sciencesComputer scienceThroughput02 engineering and technologyDistributed coordination functionSpectrum managementAnalytical modelScheduling (computing)Computer Science - Networking and Internet ArchitectureC.2.0C.2.50202 electrical engineering electronic engineering information engineeringLong Term EvolutionWireless fidelityElectrical and Electronic EngineeringProbabilitySensorNetworking and Internet Architecture (cs.NI)business.industrySettore ING-INF/03 - TelecomunicazioniComputerSystemsOrganization_COMPUTER-COMMUNICATIONNETWORKS020206 networking & telecommunicationsComputer Science Applications1707 Computer Vision and Pattern RecognitionThroughput91A06 91A10 91A80Computer Science ApplicationsShared resourceModeling and SimulationbusinessC.2.0; C.2.5InterferenceRandom accessComputer networkCommunication channel
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Learning From Errors: Detecting Cross-Technology Interference in WiFi Networks

2018

In this paper, we show that inter-technology interference can be recognized using commodity WiFi devices by monitoring the statistics of receiver errors. Indeed, while for WiFi standard frames the error probability varies during the frame reception in different frame fields (PHY, MAC headers, and payloads) protected with heterogeneous coding, errors may appear randomly at any point during the time the demodulator is trying to receive an exogenous interfering signal. We thus detect and identify cross-technology interference on off-the-shelf WiFi cards by monitoring the sequence of receiver errors (bad PLCP, bad FCS, invalid headers, etc.) and propose two methods to recognize the source of in…

MonitoringComputer Networks and CommunicationsComputer scienceReal-time computingheterogeneous network050801 communication & media studies02 engineering and technologySpectrum managementZigBee0508 media and communicationsArtificial IntelligencePHY0202 electrical engineering electronic engineering information engineeringLong Term EvolutionDemodulationWireless fidelityHidden Markov modelsHidden Markov modelCross technology interferenceArtificial neural networkSettore ING-INF/03 - Telecomunicazioni05 social sciencesComputerSystemsOrganization_COMPUTER-COMMUNICATIONNETWORKScoexistenceunlicensed bands020206 networking & telecommunicationsThroughputLearning from errorsHardware and ArchitectureInterferenceCoding (social sciences)
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Exploring Training Options for RF Sensing Using CSI

2018

This work analyzes human behavior recognition approaches using WiFi channel state information from the perhaps less usual point of view of training and calibration needs. With the help of selected literature examples, as well as with more detailed experimental insights on our own Doppler spectrum-based approach for physical motion/presence/cardinality detection, we first classify the diverse forms of training so far employed into three main categories (trained, trained-once, and training-free). We further discuss under which conditions it is possible to move toward lighter forms of calibration or even succeed in devising fully untrained model-based solutions. Our take home messages are main…

Point (typography)Settore ING-INF/03 - TelecomunicazioniComputer Networks and CommunicationsCalibration (statistics)Computer sciencebusiness.industry010401 analytical chemistryBehavioural sciences020206 networking & telecommunications02 engineering and technologyMachine learningcomputer.software_genreTraining Wireless fidelity Calibration Doppler effect Behavioral sciences Radio frequency Sensors Channel state estimation01 natural sciencesTraining (civil)Motion (physics)0104 chemical sciencesComputer Science ApplicationsPersonalization0202 electrical engineering electronic engineering information engineeringArtificial intelligenceElectrical and Electronic EngineeringbusinesscomputerIEEE Communications Magazine
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SHARP: Environment and Person Independent Activity Recognition with Commodity IEEE 802.11 Access Points

2022

In this article we present SHARP, an original approach for obtaining human activity recognition (HAR) through the use of commercial IEEE 802.11 (Wi-Fi) devices. SHARP grants the possibility to discern the activities of different persons, across different time-spans and environments. To achieve this, we devise a new technique to clean and process the channel frequency response (CFR) phase of the Wi-Fi channel, obtaining an estimate of the Doppler shift at a radio monitor device. The Doppler shift reveals the presence of moving scatterers in the environment, while not being affected by (environment-specific) static objects. SHARP is trained on data collected as a person performs seven differe…

Signal Processing (eess.SP)Networking and Internet Architecture (cs.NI)FOS: Computer and information scienceshuman activity recognitionMobile computingComputer Science - Machine LearningCFRMonitoringSensorsComputer Networks and CommunicationsIEEE 802.11acneural networksWi-Fi sensingMachine Learning (cs.LG)Computer Science - Networking and Internet ArchitectureCSIActivity recognitionFOS: Electrical engineering electronic engineering information engineeringPerformance evaluationFeature extractionWireless fidelityElectrical and Electronic EngineeringElectrical Engineering and Systems Science - Signal Processingcontactless indoor monitoringSoftware
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Exploring User Acceptance of Free Wireless Fidelity Public Hot Spots : An Empirical Study

2008

Research regarding commercial and free wireless fidelity (Wi-Fi) public hot spots acceptance and adoption is sketchy. Therefore, it has become imperative to understand the critical factors that affect their acceptance. The focus of this study is free Wi-Fi public hot spot users, with the objective to better understand their user acceptance. In doing so, this study integrated two well-established initial acceptance models, specifically, the technology acceptance model and the diffusion of innovation theory. This study was conducted using an on-line survey that collected data from 129 users. It uses the Partial Least Square (PLS) technique to examine the relationship between variables. The re…

technology acceptance modelpartial least squarediffusion of innovationfree Wi-Fiwireless fidelitypublic hot spots
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