Cooperative wideband spectrum sensing based on sequential compressed sensing |
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Authors: | Bin Gu Zhen Yang Haifeng Hu |
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Affiliation: | (1) School of Electronic and Information Engineering, South China University of Technology, Guangzhou, People’s Republic of China;(2) Guangdong University of Technology, Guangzhou, People’s Republic of China;(3) Simula Research Laboratory, Norway; Department of Informatics, University of Oslo, Oslo, Norway;(4) Department of Electrical and Computer Engineering, The University of British Columbia, Canada |
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Abstract: | Compressed sensing offers a new wideband spectrum sensing scheme in Cognitive Radio (CR). A major challenge of this scheme
is how to determinate the required measurements while the signal sparsity is not known a priori. This paper presents a cooperative sensing scheme based on sequential compressed sensing where sequential measurements are
collected from the analog-to-information converters. A novel cooperative compressed sensing recovery algorithm named Simultaneous
Sparsity Adaptive Matching Pursuit (SSAMP) is utilized for sequential compressed sensing in order to estimate the reconstruction
errors and determinate the minimal number of required measurements. Once the fusion center obtains enough measurements, the
reconstruction spectrum sparse vectors are then used to make a decision on spectrum occupancy. Simulations corroborate the
effectiveness of the estimation and sensing performance of our cooperative scheme. Meanwhile, the performance of SSAMP and
Simultaneous Orthogonal Matching Pursuit (SOMP) is evaluated by Mean-Square estimation Errors (MSE) and sensing time. |
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