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Distributed Spectrum Estimation for Small Cell Networks Based on Sparse Diffusion Adaptation

delete2013-12-01
delete44
PRE
AI
P
Paolo Di Lorenzo *
S
Sergio Barbarossa
A
Ali H. Sayed
DOI:10.1109/LSP.2013.2287373delete
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Abstract

Abstract

En 中文
The goal of this letter is to propose an adaptive and distributed approach to cooperative sensing for wireless small cell networks. The method uses a basis expansion model of the power spectral density (PSD) to be estimated, and exploits spectral sparsity to improve estimation accuracy and adaptation capabilities. An estimator of the model coefficients is developed based on sparse diffusion strategies, which are able to exploit and track sparsity while at the same time processing data in real-time and in a fully decentralized manner. Simulation results illustrate the advantages of the proposed sparsity-aware strategies for cooperative spectrum sensing applications.
Keywords:
Distributed spectrum estimation
small-cell networks
sparse diffusion adaptation

Journal

IEEE Signal Processing Magazine cover
IEEE Signal Processing Magazine
IF:
9.6
Papers:
1.1W
Citations:
1.7W

Organization

University of California System cover
University of California System
Scholars:
37.5W
Papers: 33.7W
Citations: 6.6K
S
sapienza university rome
Scholars:
6.3W
Papers: 4.7W
Citations: 381
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