Summary: 668 IEEE TRANSACTIONS ON COMMUNICATIONS, VOL. 45, NO. 6, JUNE 1997
Quantization of Memoryless and Gauss­Markov
Sources Over Binary Markov Channels
Nam Phamdo, Member, IEEE, Fady Alajaji, Member, IEEE, and Nariman Farvardin, Senior Member, IEEE
Abstract-- Joint source­channel coding for stationary memo-
ryless and Gauss­Markov 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 4­5 dB in signal-to-noise ratio are possible.
Index Terms-- Channels with memory, joint source­channel

Source: Alajaji, Fady - Department of Mathematics and Statistics, Queen's University (Kingston)

Collections: Engineering