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Maximum-Minimum Eigen Value Based Spectrum Scanner

Maximum-Minimum Eigen Value Based Spectrum Scanner. Mohamed Hamid and Niclas Björsell Center for RF measurement Technology, University of Gävle , Sweden Communications Systems Lab, Royal Institute of Technology, Stockholm, Sweden @RFMTC 2011, Gävle , October, 2011. Outlines. Introduction

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Maximum-Minimum Eigen Value Based Spectrum Scanner

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  1. Maximum-Minimum Eigen Value Based Spectrum Scanner Mohamed Hamid and Niclas Björsell Center for RF measurement Technology, University of Gävle, Sweden Communications Systems Lab, Royal Institute of Technology, Stockholm, Sweden @RFMTC 2011, Gävle, October, 2011

  2. Outlines Introduction Spectrum Detection Techniques Maximum-MinimumEigenValueDetection (MMEVD) RectangularFiltering for sub-bandsspectrum scanning with MMEVD MeasurementsResults Conclusions

  3. Introduction Currentspectrumregulation policy relies on Staticspectrum access Wireless services and technologies are growingrapidly Lack of radio resources Radio Spectrum is under-utilized DynamicSpectrum access (DSA) policy

  4. Introduction(Cont.) What is the spectrumopportuinty?! A free of usechannel (band) subject to the recieved power in a specific time at a specificlocation How to find a spectrumOpportuity SpectrumSensing and/or GeolocationDatabse Beacon based Spectrum Opportunities

  5. Spectrum Detection Techniques Energy Detector Requires a prior knowledge of the system backgroundnoise Matched Filtering Auto-correlation Detection Require a prior knowledge of the primary system signal Maximum-MinimumEigenValueDetection

  6. Maximum-MinimumEigenValueDetection (MMEVD) λmax Signal frequency components α Eigen values of the auto correlation Matrix of the signal 2 λmin = σn

  7. Maximum-MinimumEigenValueDetection (MMEVD) Recieved Signal r(t) Uponpredefinedthresholdγ of the ratioλmax/ λmin the decission is madeif it is a signal or just noise MMEVD tests the extent of the flatnessof the spectrum Filtering is a problimaticwhen scanning for sub-bands is to takeplace

  8. RectangularFiltering for sub-bandsspectrum scanning with MMEVD Solution: Rectangular Filtering , i.e. talking the spectrum lines lie inside the sub-band of interest and throw away the rest Time Domain Signals Do MMEVD

  9. Measured BW : 10 MHz • # Sub-channels: 5 (2MHz each) MeasurementsResults

  10. Conclusions • Sub-bands spectrum scanning is feasible with rectangular filtering and MMEVD • MMEVD introduces probability of false alarm much less than the one introduced by Energy Detection

  11. THANKS FOR YOUR ATTENTION QUESTIONS AND COMMENTS ARE WELCOME

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