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Software-defined white-spacecognitive systems:Implementation of the spectrum sensing unitCastelldefels, October 6th 2011Sergio Benco,Floriana Crespi, Andrea Ghittino, Alberto PerottiIntegrated Networks Laboratory (INLAB),CSP s.c.a r.l. - ICT innovation,TURIN (ITALY)

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Outline TV White-Spaces Spectrum Sensing IEEE 802.22 Spectrum Sensing model DVB-T CP autocorrelation Spectrum Sensing Threshold calculation Performance Conclusions and future work Software-defined white-space cognitive systems 2

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Spectrum sensing for TV White-SpacesTV White-Spaces represent the area (space domain) andthe portion of the spectrum (VHF and UHF bands) wherethe broadcast signal strength falls below the sensitivitylevel of Primary User (PU) receiversRegulatory bodies are currently discussing aboutSecondary User (SU) spectrum sensing requirements inorder to avoid interference to DVB-T receiversInterference issues can be faced through: SU geo-location and PU database queries Cognitive Pilot Channel (CPC) SU autonomous sensing (cooperative or not) Software-defined white-space cognitive systems 3

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IEEE 802.22 Spectrum Sensing model PU protection contour (Dkm) Sensitivity range of the PU Rx PU ITU-R: PRPU = -92dBm @ 132km (RX) ERP TX = +90dBm, height: 500m, 615MHz)SU PU (TX) Keep-out region (Rkm) Range at wich the Desired/Undesired SU (D/U) ratio falls below 23 dB SU spectrum sensing requirements: ● PU Rx characteristics: F/B = 14 dB; D/U = 23 dB ● At PU Rx: PRSU ≤ PRPU – D/UdB + F/BdB ● At PU Rx: PRSU ≤ -101 dBm At SU Rx: Sens. ≤ -115 dBm A SU must detect a PU Tx at a range of: Rkm + Dkm Software-defined white-space cognitive systems 4

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DVB-T spectrum sensing: CP autocorrelationNs Symbol samplesNCP CP samples N0CP N0 d N1CP N1dNd Data samplesK Number of symbols Ns K −1 i+kN s +N cp −1CP correlator:See R xx (i) = ∑ ∑ x (n) x (n+ N d ) ˙ k=0 n=i+kN sReferences (1)(2)CP correlator test: DVB-T sensing module parameters max∣R xx (i)∣ Modes 8k (6817 subcarriers) T CP = i ⩾ γ 2k (1705 subcarriers) Avg∣R xx (i)∣ < CP lengths 1/4, 1/8, 1/16, 1/32 i∈J Channel bandwidth 8 MHz Sampling rate 12.5 MS/s (12.5 MHz) Software-defined white-space cognitive systems 5

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DVB-T spectrum sensing: applied threshold False Alarm max∣R xx (i)∣ Probability (PFA ) i ̂ θ ⩾ γT CP = = obtained through Avg∣R xx (i)∣ ∣R xx∣ < ̄ i∈J Monte-Carlo simulations over 1000 trialsγ = γ ⋅ Avg∣R xx (i)∣ ⇒̂ P FA ⩽ 0.1 i ∈JJ =N ∖QN ={n∈ℕ : 0 ⩽ n < N s } ̂ ̂Q={q∈ℕ : θ− N CP ⩽ q < θ+N CP }The threshold is adaptive w.r.t. the actual averagecorrelation level plus a fixed margin that depends on PFA Software-defined white-space cognitive systems 6

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DVB-T spectrum sensing over K symbolsSymbol synchronization permits to obtain a coherentcombining and average over K subsequent DVB-Tsymbols thus achieving a processing gain of about 5 dBfor each 10 dB increase in K 1 symbol 10 symbols 100 symbols SNR = -15dB SNR = -15dB SNR = -15dBAWGN channel AWGN channel AWGN channel Software-defined white-space cognitive systems 7

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DVB-T OFDM sensing: performanceThe detection time Tdet of this real-time module is calculated at thetarget sensing performance (PFA=0.1, PD=0.9) for a given SNR: SNR (PD=0.9) = -17 dB Symbols = 100 Tdet = 112.00 ms + Tproc SNR (PD=0.9) = -12 dB Symbols = 10 Tdet = 11.20 ms + Tproc Tch move time = 2000 ms Tsensing = Tch move time – 2Tdet Software-defined white-space cognitive systems 8

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Conclusions and future work● The DVB-T spectrum sensing based on CP autocorrelation offers a good trade-off between complexity and effectiveness● The first attempts to exploit TV white space have raised the problem of high sensitivity requirements for the SU spectrum sensing unit● We have developed a real-time module for OFDM spectrum sensing that approaches the requirements for the IEEE 802.22 WRAN spectrum sensing unit● Future work will provide a SU network able to continuously monitor the TV White-Spaces through a CP-based spectrum sensing module using the GNURadio/USRP2 platform Software-defined white-space cognitive systems 9

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References(1) D. Danev, E. Axell, and E. G. Larsson, “Spectrum Sensing Methods for Detection of DVB-T Signals in AWGN and Fading Channels”, In Proc. IEEE PIMRC, pp. 2721-2726, Dec. 2010(2) V. Gaddam, M. Ghosh, “Robust Sensing of DVB-T Signals”, New Frontiers in Dynamic Spectrum, 2010 IEEE Symposium on , vol., no., pp.1-8, 6-9 April 2010(3) S. Shellhammer, V. Tawil, G. Chouinard, M. Muterspaugh, M. Ghosh, “Spectrum sensing simulation model”, IEEE 802.22-06/0028r10, Sept. 2006(4) C.R. Stevenson, C. Cordeiro, E. Sofer, G. Chouinard, “Functional Requirements for the 802.22 WRAN Standard”, IEEE 802.22- 05/0007r46, September 2005 Software-defined white-space cognitive systems 10

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ContactsSergio BencoConsulting Engineer,Integrated Networks Laboratory (INLAB)R&D dept.mail: sergio.benco@csp.itcell: +39 329 0118356tel. +39 011-4815164CSP innovation in ICTRegistered and Central OfficesEnvironment Park - Laboratori A1via Livorno 60 - 10144 TorinoOperational OfficesVilla Gualino - Viale Settimio Severo 6310133 TorinoTel +39 011 4815111Fax +39 011 4815001E-mail: marketing@csp.itwww.csp.itSoftware-defined white-space cognitive systems 11