Performance Evaluation of Finite Sparse Signals for Compressed Sensing Frameworks

Jin-Taek SEONG  

Publication
IEICE TRANSACTIONS on Information and Systems   Vol.E101-D   No.2   pp.531-534
Publication Date: 2018/02/01
Online ISSN: 1745-1361
DOI: 10.1587/transinf.2017EDL8166
Type of Manuscript: LETTER
Category: Fundamentals of Information Systems
Keyword: 
compressed sensing,  finite fields,  signal recovery,  probabilistic decoding,  

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Summary: 
In this paper, we consider to develop a recovery algorithm of a sparse signal for a compressed sensing (CS) framework over finite fields. A basic framework of CS for discrete signals rather than continuous signals is established from the linear measurement step to the reconstruction. With predetermined priori distribution of a sparse signal, we reconstruct it by using a message passing algorithm, and evaluate the performance obtained from simulation. We compare our simulation results with the theoretic bounds obtained from probability analysis.