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Tic-tac: TV White Space Testbed with Robust Spectrum Sensing Algorithms for M2M Communications
Antennafor aWSD Client• CompactandLowProfile‒ Dimension:231mm×35mm×0.8mm
• Ultra-wideband‒ Bandwidth:474MHz-1212MHz
• Excellent Performance‒ Radiationpattern:omnidirectional‒ Averagegain:1.68dBioverTVWS‒ Radiationefficiency:over80%
RobustSensingAlgorithms• SpectrumUsage‒ Spectrumshortageandspectrumwaste‒ OpeningoflicenceexemptuseofTVWS
• CognitiveRadio‒ Widebandspectrumsensing:highsamplingrate‒ Compressivespectrumsensing:sub-Nyquistsampling
• ProposedAlgorithms‒ Robustcompressivespectrumsensingwithlowcomplexity‒ Geolocationdatabaseassistedcompressivespectrum
sensingwithlowcomplexity‒ Malicioususerdetectionbasedonmatrixcompletion
• MeasurementonReal-TimeTVWSSignals
• NumericalResults
Yue Gao, Clive Parini, Zhijin Qin, Qianyun [email protected] Twitter: @WMCLab
TVWStestbed• SystemSetup‒ Basestationwithsectorantenna‒ Clientwiththedevelopedantenna
• MeasurementLocations‒ Movingclienttodifferentlocations,7linksrepresenting
variouscommunicationscenariosaretested
• MeasurementResults
‒ Proposedalgorithmshavebeenverifiedbyreal-timesignalscollectedbyRFeye node
Fig.7.MeasurementsetupwithRFeye nodeatQMUL
Fig.6.CompressiveSpectrumSensingModelFig.1.AntennaforWSD client
Fig.2.WSD Client Fig.3.Basestation
Fig.4.In-buildingandbetween-buildingsTVWScommunications
ContributionsThisprojectgoesbeyondstate-of-the-artanddeveloped:• Robustcompressivesensingalgorithms[1][2]• Acompactantenna for white space devices (WSDs)[3]• Areal-timeTVwhitespace(TVWS) testbedforM2M/IoT [4][5]
Fig.8.Simulationresultsofproposedcompressivespectrumsensingalgorithms
Fig.5.Measurementsignal-to-interference-plus-noiseratios(SINRs) oflink1,4,and7withclientantennafacingdifferentdirections.SINRofuplinksignalisnotedby’o’andthatofdownlinkisnotedby’+’
(a).DetectionprobabilitycomparisonofproposedrobustcompressivespectrumsensingalgorithmunderdifferentcompressionratiosandSNRvalues
(c).Detectionprobabilitycomparisonofproposedgeolocationdatabaseassistedcompressivespectrumsensingalgorithmunderdifferentcompressionratios
(d).Detectionprobabilitycomparisonofproposedmalicioususerdetectionframeworkunderdifferentcompressionratios
TV Database
DTV1 coverage area channels
20,21,39
DTV2 coverage area
channels 25,26,40
CR coverage area channels 20,21,25,26,39,40
Maximum Allowable Transmission Power
0.1w,0.07w,2.3w,0.5w,3w,0.2w
Geo-locationdatabase
FusioncenterSU1
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SpectrumofinterestSpectrumsensing
TVwhitespacedatadissemination(webportal)
TVwhitespacerecordingLowNoise
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RFsignallogger
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widebandantennas
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ExistingGeo-locationdatabasemodels
UHF470-790MHz
DTT
WSDs
PMSE
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Proposedsolution
Existingsolution
Validationandintegration
Hybridapproach
Overview
TV White Space Testbed with Robust Spectrum Sensing Algorithms For M2M Communications (Tic-tac) Yue Gao, Zhijin Qin, Qianyun Zhang
Antenna for slave WSDs • Compact and Low Profile
‒ Dimension: 231mm×35mm×0.8mm • Ultra-wideband
‒ Bandwidth: 474MHz-1212MHz • Good Performance
‒ Radiation pattern: omnidirectional ‒ Average gain: 1.68dBi over TVWS ‒ Radiation efficiency: over 80%
Robust Sensing Algorithms • Spectrum Usage
‒ Spectrum shortage and spectrum waste. ‒ Opening of licence exempt use of TVWS.
• Cognitive Radio ‒ Wideband spectrum sensing: high sensing rate ‒ Compressive spectrum sensing: sub-Nyquist sampling
• Proposed Algorithms ‒ Robust compressive spectrum sensing with low complexity. ‒ Geolocation database assisted compressive spectrum
sensing with low complexity. ‒ Malicious user detection based on matrix completion.
• Measurements on Real-Time TV Signals
• Numerical Results
http://tic-tac.eecs.qmul.ac.uk
TVWS testbed • System Setup
‒ Base station with sector antenna ‒ Client with home-made antenna
• Measurement Locations ‒ Moving client to different locations, seven links represents
various communication scenarios are tested
• Measurement Results
‒ All proposed algorithms have been verified by real-time TV signals RFeye node.
Fig. 2. Measurement setup with RFeye node at QMUL
Fig. 1. Compressive Spectrum Sensing Model
Fig. 4. Antenna for slave WSDs
Fig. 5. Client Fig. 6. Base station
Fig. 7. In-building and between-buildings TVWS communications
Contributions: This project goes beyond state-of-the-art and developed:
• Robust compressive sensing algorithms • Develop novel compact and wideband antennas • A real-time TV white space testbed for M2M/IoT
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Fig. 3. Simulation results of proposed compressive spectrum sensing algorithms
Fig. 8. Measurement signal-to-interference-plus-noise ratios (SINRs) of link 1, 4, and 7 with client antenna facing different directions. SINR of uplink signal is noted by ’o’ and that of downlink is noted by ’+’.
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ANTENNAS & ELECTROMAGNETICS RESEARCH GROUP
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(a). Detection probability comparison of proposed robust compressive spectrum sensing algorithm under different compression ratios and SNR values
(b). Detection probability comparison of proposed robust compressive spectrum sensing algorithm with different sparsity levels and compression ratios
(c). Detection probability comparison of proposed geolocation database assisted compressive spectrum sensing algorithm under different compression ratios
(d). Detection probability comparison of proposed malicious user detection framework under different compression ratios
Up
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EE hub
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(b).Detectionprobabilitycomparisonofproposedrobustcompressivespectrumsensingalgorithmwithdifferentsparsitylevelsandcompressionratios
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[1]Z.Qin,Y.Gao,M.Plumbley andC.Parini,“WidebandSpectrumSensingonReal-timeSignalsatSub-NyquistSamplingRatesinSingleandCooperativeMultipleNodes,”IEEETrans.SignalProcess.,vol.64,no.12,pp.3106– 3117,Jun.2016.[2]Z.Qin,Y.Gao,andC.G.Parini,“Data-assistedlowcomplexitycompressivespectrumsensingonreal-timesignalsundersub-nyquist rate,”IEEETrans.WirelessCommun.,vol.15,no.2,pp.1174–1185,Feb.2016.[3]Q.Zhang,Y.GaoandC.Parini,“CompactU-shapeUltra-widebandAntennawithCharacteristicModeAnalysisforTVWhiteSpaceCommunications,” TheIEEEInternationalSymposiumonAntennasandPropagation,Jun.2016.[4]Y.Gao,Z.Qin,Z.Feng,Q.Zhang,O.Holland,M.Dohler,“Scalable&ReliableIoT EnabledByDynamicSpectrumManagementforM2MinLTE-A”,IEEEInternetofThingsJournal,2016.(Inpress)[5]Q.Zhang,X.Zhang,Y.Gao,O.Holland,M.Dohler,P.Chawdhry,J.Chareau,“TVWhiteSpaceNetworkProvisioningwithDirectionalandOmni-directionalTerminalAntennas,”theIEEEVehicularTechnologyConference,VTC2016-FallinMontréal,Canada,Sept.2016.