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3 results on '"Hugo Andre Lopes"'

1. Efficient Recovery Algorithm for Discrete Valued Sparse Signals Using an ADMM Approach

Author

Nuno M. B. Souto and Hugo Andre Lopes

Subjects
Sparse signal recovery, discrete signal reconstruction, compressed sensing, generalized spatial modulations (GSM), large scale MIMO (LS-MIMO), Electrical engineering. Electronics. Nuclear engineering, TK1-9971
Abstract

Motivated by applications in wireless communications, in this paper we propose a reconstruction algorithm for sparse signals whose values are taken from a discrete set, using a limited number of noisy observations. Unlike conventional compressed sensing algorithms, the proposed approach incorporates knowledge of the discrete valued nature of the signal in the detection process. This is accomplished through the alternating direction method of the multipliers which is applied as a heuristic to decompose the associated maximum likelihood detection problem in order to find candidate solutions with a low computational complexity order. Numerical results in different scenarios show that the proposed algorithm is capable of achieving very competitive recovery error rates when compared with other existing suboptimal approaches.

Published
2017
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3. Efficient recovery algorithm for discrete valued sparse signals using an ADMM approach

Author

Nuno Souto and Hugo Andre Lopes

Subjects
Mathematical optimization, Discrete signal reconstruction, General Computer Science, Computational complexity theory, Generalized spatial modulations (GSM), Heuristic (computer science), Engenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática [Domínio/Área Científica], 02 engineering and technology, Sparse signal recovery, discrete signal reconstruction, Large scale MIMO (LS-MIMO), 0202 electrical engineering, electronic engineering, information engineering, Wireless, General Materials Science, compressed sensing, Mathematics, Noise measurement, business.industry, General Engineering, Ciências Naturais::Ciências da Computação e da Informação [Domínio/Área Científica], generalized spatial modulations (GSM), 020206 networking & telecommunications, Reconstruction algorithm, large scale MIMO (LS-MIMO), Compressed sensing, 020201 artificial intelligence & image processing, Algorithm design, lcsh:Electrical engineering. Electronics. Nuclear engineering, business, Convex function, lcsh:TK1-9971, Algorithm
Abstract

Motivated by applications in wireless communications, in this paper we propose a reconstruction algorithm for sparse signals whose values are taken from a discrete set, using a limited number of noisy observations. Unlike conventional compressed sensing algorithms, the proposed approach incorporates knowledge of the discrete valued nature of the signal in the detection process. This is accomplished through the alternating direction method of the multipliers which is applied as a heuristic to decompose the associated maximum likelihood detection problem in order to find candidate solutions with a low computational complexity order. Numerical results in different scenarios show that the proposed algorithm is capable of achieving very competitive recovery error rates when compared with other existing suboptimal approaches. info:eu-repo/semantics/publishedVersion

Published
2017

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