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Missing Spectrum-Data Recovery in Cognitive Radio Networks Using Piecewise Constant Nonnegative Matrix Factorization
In this paper, we propose a missing spectrum data recovery technique for
cognitive radio (CR) networks using Nonnegative Matrix Factorization (NMF). It
is shown that the spectrum measurements collected from secondary users (SUs)
can be factorized as product of a channel gain matrix times an activation
matrix. Then, an NMF method with piecewise constant activation coefficients is
introduced to analyze the measurements and estimate the missing spectrum data.
The proposed optimization problem is solved by a Majorization-Minimization
technique. The numerical simulation verifies that the proposed technique is
able to accurately estimate the missing spectrum data in the presence of noise
and fading.Comment: 6 pages, 6 figures, Accepted for presentation in MILCOM'15 Conferenc
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