NDLI: Wideband spectrum sensing by compressed measurements

Content Provider	IEEE Xplore Digital Library
Author	Najafabadi, D.M. Tadaion, A.A. Sahaf, M.R.A.
Copyright Year	2012
Description	Author affiliation: Department of Electrical Engineering, Yazd University, Yazd, Iran (Najafabadi, D.M.; Tadaion, A.A.; Sahaf, M.R.A.)
Abstract	In this paper we introduce a new method for wideband spectrum sensing which uses the received signal compressed measurements to determine the occupancy status of each subchannel. In the cognitive radio systems, wideband spectrum sensing in high utilization regimes increases the speed of the access to the spectrum holes. In order to send data, the primary users employ different modulation types in each sub-channel; therefore, the transmitted signal is chosen among a signal space. Since just a few numbers of sub-channels are occupied by the primary user signals in each time instant, the received wideband signal has a sparse representation on the sub-channel signal space bases; then, the secondary user can compress the received signal samples. Knowing about the modulation types and therefore, the signal spaces, the information in each subchannel is separated using a projection matrix applied to the compressed measurements, directly. The separated compressed measurements are employed to derive a Generalized Likelihood Ratio detector and determine the presence or absence of the primary user signal in each sub-channel. We try to determine the sensing matrix so that the filtering and detection steps and, therefore, wideband spectrum sensing have low error.
Starting Page	000667
Ending Page	000671
File Size	673561
Page Count	5
File Format	PDF
ISBN	9781467327121
ISSN	15301346
e-ISBN	9781467327138
e-ISBN	9781467327114
DOI	10.1109/ISCC.2012.6249374
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-07-01
Publisher Place	Turkey
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Wideband Detectors Vectors Cognitive radio Discrete Fourier transforms Pollution measurement Compressive sensing Spectrum sensing Sparsity
Content Type	Text
Resource Type	Article
Subject	Signal Processing Mathematics Computer Networks and Communications Computer Science Applications Software

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