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Improved Cyclostationarity based sensing algorithms

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Presentation on theme: "Improved Cyclostationarity based sensing algorithms"— Presentation transcript:

1 Improved Cyclostationarity based sensing algorithms
July 2007 Improved Cyclostationarity based sensing algorithms IEEE P Wireless RANs Date: Authors: Notice: This document has been prepared to assist IEEE It is offered as a basis for discussion and is not binding on the contributing individual(s) or organization(s). The material in this document is subject to change in form and content after further study. The contributor(s) reserve(s) the right to add, amend or withdraw material contained herein. Release: The contributor grants a free, irrevocable license to the IEEE to incorporate material contained in this contribution, and any modifications thereof, in the creation of an IEEE Standards publication; to copyright in the IEEE’s name any IEEE Standards publication even though it may include portions of this contribution; and at the IEEE’s sole discretion to permit others to reproduce in whole or in part the resulting IEEE Standards publication. The contributor also acknowledges and accepts that this contribution may be made public by IEEE Patent Policy and Procedures: The contributor is familiar with the IEEE 802 Patent Policy and Procedures including the statement "IEEE standards may include the known use of patent(s), including patent applications, provided the IEEE receives assurance from the patent holder or applicant with respect to patents essential for compliance with both mandatory and optional portions of the standard." Early disclosure to the Working Group of patent information that might be relevant to the standard is essential to reduce the possibility for delays in the development process and increase the likelihood that the draft publication will be approved for publication. Please notify the Chair Carl R. Stevenson as early as possible, in written or electronic form, if patented technology (or technology under patent application) might be incorporated into a draft standard being developed within the IEEE Working Group. If you have questions, contact the IEEE Patent Committee Administrator at > Hou-Shin Chen and Wen Gao, Thomson Inc.

2 Spectrum of the ATSC DTV Signal
July 2007 Spectrum of the ATSC DTV Signal DTV data are VSB modulated. Before VSB modulation, a constant of 1.25 is added to the 8-level pulse amplitude modulated signal (8-PAM). Therefore, there is a strong pilot tone on the power spectrum density (PSD) of the ATSC DTV signal. Hou-Shin Chen and Wen Gao, Thomson Inc.

3 Signal Model The received signal contains the signal where
July 2007 Signal Model The received signal contains the signal where w(t) is the additive white Gaussian noise (AWGN) P and are the power and the initial phase of the sinusoidal function respectively The function h(t) is the channel impulse response The parameter is the amount of frequency offset in the unit of Hz Hou-Shin Chen and Wen Gao, Thomson Inc.

4 Cyclic Spectrum of the Pilot Signal
July 2007 Cyclic Spectrum of the Pilot Signal The cyclic spectrum of the received signal must contain the cyclic spectrum of x(t) which is given by Hou-Shin Chen and Wen Gao, Thomson Inc.

5 Cyclic Spectrum of the Pilot Signal
July 2007 Cyclic Spectrum of the Pilot Signal Hou-Shin Chen and Wen Gao, Thomson Inc.

6 Spectrum Sensing Algorithm
July 2007 Spectrum Sensing Algorithm Use a proper narrow band-pass filter to filter received signal and obtain a small frequency bands which contains the pilot tone Hou-Shin Chen and Wen Gao, Thomson Inc.

7 Spectrum Sensing Algorithm
July 2007 Spectrum Sensing Algorithm Down-converted to lower central frequency Decimate the signal by a proper factor to reduce data rate Note that we will do Step 2 and 3 for multiple times in order to perform cyclic spectrum estimation Hou-Shin Chen and Wen Gao, Thomson Inc.

8 Spectrum Sensing Algorithm
July 2007 Spectrum Sensing Algorithm The cyclic spectrum is computed by where and zlD[n] which has central frequency fIF+lfΔis down-converted and D-decimated samples of the narrow band-pass signal around the pilot. N is the size of FFT. The decision statistic is Hou-Shin Chen and Wen Gao, Thomson Inc.

9 Simulation Parameters
July 2007 Simulation Parameters The band-pass filter used to filter the pilot tone has a bandwidth of 40 KHz The band-pass signal is down-converted to fIF equaling to 17 KHz The decimation factor is 200 and the decimation filter is a ±50 KHz low-pass filter The size of FFT is N = 2048 The parameter L is 2 and fΔ is set to be half of the carrier spacing divided by 2L+1. The false alarm rate is set to be 0.1 Hou-Shin Chen and Wen Gao, Thomson Inc.

10 July 2007 Simulation Results Simulations are run over 12 reference ATSC DTV ensembles and their corresponding symbols are listed below : A : WAS_3_27_ _REF B : WAS_311_36_ _REF C : WAS_06_34_ _REF D : WAS_311_48_ _REF E : WAS_51_35_ _REF F : WAS_68_36_ _REF G : WAS_86_48_ _REF H : WAS_311_35_ _REF I : WAS_47_48_ _opt J : WAS_32_48_ _OPT K : WAS_49_34_ _opt L : WAS_49_39_ _opt Hou-Shin Chen and Wen Gao, Thomson Inc.

11 July 2007 Simulation Results Hou-Shin Chen and Wen Gao, Thomson Inc.


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