Missing Spectrum-Data Recovery In Cognitive Radio Networks Using Piecewise Constant Nonnegative Matrix Factorization

Keywords

Cognitive Radio Network; Missing Data Estimation; Nonnegative Matrix Factorization; Spectrum Sensing

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.

Publication Date

12-14-2015

Publication Title

Proceedings - IEEE Military Communications Conference MILCOM

Volume

2015-December

Number of Pages

238-243

Document Type

Article; Proceedings Paper

Personal Identifier

scopus

DOI Link

https://doi.org/10.1109/MILCOM.2015.7357449

Socpus ID

84959275313 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/84959275313

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