Title: An improved compressed sensing reconstruction algorithm used in sparse channel estimation
Abstract:Compressed sensing is a new method of data acquisition and processing, which can accurately restore the original data from a few observation samples. In this paper, based on this theoretical framework...Compressed sensing is a new method of data acquisition and processing, which can accurately restore the original data from a few observation samples. In this paper, based on this theoretical framework, the compressed sensing reconstruction algorithm named Discrete Fourier transform Matching Pursuit algorithm (DFT-MP) were proposed for sparse channel estimation. It is suitable for sparse underwater acoustic channels. We analyzed and compared our proposed algorithm with other signal reconstruction algorithms, such as Matching Pursuit algorithm (MP), Orthogonal Matching Pursuit algorithm (OMP), and Sparse Bayesian Learning algorithm (SBL). From the simulation results, the Discrete Fourier transform Matching Pursuit algorithm outperforms other algorithms which we mentioned above.Read More
Publication Year: 2016
Publication Date: 2016-08-01
Language: en
Type: article
Indexed In: ['crossref']
Access and Citation
Cited By Count: 4
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