Quantization of memoryless and Gauss-Markov sources over binary Markov channels

Author

Phamdo, Nam ; Alajaji, Fady ; Farvardin, Nariman

Author_Institution

Dept. of Electr. Eng., State Univ. of New York, Stony Brook, NY, USA

Volume

45

Issue

6

fYear

1997

fDate

6/1/1997 12:00:00 AM

Firstpage

668

Lastpage

675

Abstract

Joint source-channel coding for stationary memoryless and Gauss-Markov sources and binary Markov channels is considered. The channel is an additive-noise channel where the noise process is an Mth-order Markov chain. Two joint source-channel coding schemes are considered. The first is a channel-optimized vector quantizer-optimized for both source and channel. The second scheme consists of a scalar quantizer and a maximum a posteriori detector. In this scheme, it is assumed that the scalar quantizer output has residual redundancy that can be exploited by the maximum a posteriori detector to combat the correlated channel noise. These two schemes are then compared against two schemes which use channel interleaving. Numerical results show that the proposed schemes outperform the interleaving schemes. For very noisy channels with high noise correlation, gains of 4-5 dB in signal-to-noise ratio are possible

Keywords

Gaussian processes; Markov processes; channel coding; correlation methods; maximum likelihood detection; maximum likelihood estimation; memoryless systems; source coding; vector quantisation; Gauss-Markov sources; Markov chain; SNR; additive noise channel; binary Markov channels; channel interleaving; channel optimized vector quantizer; correlated channel noise; gains; high noise correlation; joint source-channel coding; maximum a posteriori detector; noisy channels; quantization; residual redundancy; scalar quantizer; signal-to-noise ratio; stationary memoryless sources; Channel coding; Communications Society; Delay; Detectors; Gain; Gaussian channels; Gaussian distribution; Interleaved codes; Signal to noise ratio; Vector quantization;

fLanguage

English

Journal_Title

Communications, IEEE Transactions on

Publisher

ieee

ISSN

0090-6778

Type

jour

DOI

10.1109/26.592605

Filename

592605