Result: Distributed Source-Channel Coding Based on Real-Field BCH Codes

Title:
Distributed Source-Channel Coding Based on Real-Field BCH Codes
Authors:
VAEZI, Mojtaba, LABEAU, Fabrice
Source:
IEEE transactions on signal processing. 62(5-8):1171-1184
Publisher Information:
New York, NY: Institute of Electrical and Electronics Engineers, 2014.
Publication Year:
2014
Physical Description:
print, 50 ref
Original Material:
INIST-CNRS
Subject Terms:
Telecommunications, Télécommunications, Sciences exactes et technologie, Exact sciences and technology, Sciences appliquees, Applied sciences, Telecommunications et theorie de l'information, Telecommunications and information theory, Théorie de l'information, du signal et des communications, Information, signal and communications theory, Théorie du signal et des communications, Signal and communications theory, Signal, bruit, Signal, noise, Détection, estimation, filtrage, égalisation, prédiction, Detection, estimation, filtering, equalization, prediction, Codage, codes, Coding, codes, Echantillonnage, quantification, Sampling, quantization, Gestion trafic, Traffic management, Gestión tráfico, Ajustement modèle, Model matching, Ajustamiento modelo, Canal transmission, Transmission channel, Canal transmisión, Codage canal, Channel coding, Codage source canal, Joint source channel coding, Codificación fuente canal, Codage source, Source coding, Code BCH, BCH code, Código BCH, Décodage, Decoding, Desciframiento, Erreur quadratique moyenne, Mean square error, Error medio cuadrático, Erreur quantification, Quantization error, Error cuantificuación, Evaluation performance, Performance evaluation, Evaluación prestación, Milieu dissipatif, Lossy medium, Medio dispersor, Méthode sous espace, Subspace method, Método subespacio, Méthode statistique, Statistical method, Método estadístico, Quantification signal, Signal quantization, Cuantificación señal, Régulation débit, Flow rate regulation, Regulación caudal, Régulation trafic, Traffic control, Regulación tráfico, Signal source réparti, Distributed source signal, Señal fuente distribuida, Temps retard, Delay time, Tiempo retardo, Traitement signal, Signal processing, Procesamiento señal, Transformation Fourier discrète, Discrete Fourier transformation, Transformación Fourier discreta, Télétrafic, Teletraffic, Teletráfico, BCH-DFT codes, distributed source coding, joint source-channel coding, parity, real-number codes, syndrome
Document Type:
Academic journal Article
File Description:
text
Language:
English
Author Affiliations:
Department of Electrical and Computer Engineering, McGill University, Montreal, QC H3A 0E9, Canada
ISSN:
1053-587X
Access URL:
http://pascal-francis.inist.fr/vibad/index.php?action=search&terms=28403643
Rights:
Copyright 2015 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Telecommunications and information theory
Accession Number:
edscal.28403643
Database:
PASCAL Archive

Further Information

We use real-number codes to compress statistically dependent sources and establish a new framework for distributed lossy source coding in which we compress sources before, rather than after, quantization. This change in the order of binning and quantization blocks makes it possible to model the correlation between continuous-valued sources more realistically and compensate for the quantization error partially. We then focus on the asymmetric case, i.e., lossy source coding with side information at the decoder. The encoding and decoding procedures are described in detail for a class of real-number codes called discrete Fourier transform (DFT) codes, both for the syndrome- and parity-based approaches. We leverage subspace-based decoding to improve the decoding and by extending it we are able to perform distributed source coding in a rate-adaptive fashion to further improve the decoding performance when the statistical dependency between sources is unknown. We also extend the parity-based approach to the case where the transmission channel is noisy and thus we perform distributed joint source-channel coding in this context. The proposed system is well suited for low-delay communications, as the mean-squared reconstruction error (MSE) is shown to be reasonably low for very short block length.