Paper Info
Title
Reconstruction Of Finite-Alphabet Block-Sparse Signals From Map Support Detection
Abstract
This paper addresses finite-alphabet block-sparse signal recovery by considering support detection and data estimation separately. To this aim, we propose a maximum a posteriori (MAP) support detection criterion that takes into account the finite alphabet of the signal as a constraint. We then incorporate the MAP criterion in a compressed sensing detector based on a greedy algorithm for support estimation. We also propose to consider the finite-alphabet property of the signal in the bound-constrained least-squares optimization algorithm for data estimation. The MAP support detection criterion is investigated in two different contexts: independent linear modulation symbols and dependent binary continuous phase modulation (CPM) symbols. The simulations are carried out in the context of sporadic multiuser communications and show the efficiency of proposed algorithms compared to selected state-of-the-art algorithms both in terms of support detection and data estimation.
Year
DOI
Venue
2019
10.1109/ACCESS.2019.2914349
IEEE ACCESS
Keywords
Field
DocType
Compressed sensing, finite alphabet, support detection, orthogonal matching pursuit, Gaussian mixture distribution
Computer science,Algorithm,Continuous phase modulation,Greedy algorithm,Optimization algorithm,Maximum a posteriori estimation,Detector,Compressed sensing,Binary number,Distributed computing,Alphabet
Journal
Volume
ISSN
Citations 
7
2169-3536
0
PageRank 
References 
Authors
0.34
0
4
Name
Order
Citations
PageRank
Malek Messai1205.01
Karine Amis27517.77
Frédéric Guilloud3348.66
Abdeldjalil Aïssa-El-Bey416225.10