Missing Spectrum-Data Recovery in Cognitive Radio Networks Using Piecewise Constant Nonnegative Matrix Factorization
Abstract
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.
Cite
@article{arxiv.1508.07269,
title = {Missing Spectrum-Data Recovery in Cognitive Radio Networks Using Piecewise Constant Nonnegative Matrix Factorization},
author = {Alireza Zaeemzadeh and Mohsen Joneidi and Behzad Shahrasbi and Nazanin Rahnavard},
journal= {arXiv preprint arXiv:1508.07269},
year = {2017}
}
Comments
6 pages, 6 figures, Accepted for presentation in MILCOM'15 Conference