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Channel Optimized Vector Quantization Based on Maximum a Posteriori Hard Decision Demodulation
 

Summary: Channel Optimized Vector Quantization Based
on Maximum a Posteriori Hard Decision Demodulation
Hamidreza Ebrahimzadeh Saffar, Fady Alajaji and Tam´as Linder
Department of Mathematics and Statistics
Queen's University, Kingston, Ontario, Canada, K7L 3N6
{hamid, fady, linder}@mast.queensu.ca
Abstract-- We design a Maximum a Posteriori hard-decision
demodulated channel optimized vector quantizer (COVQ) that
exploits the non-uniformity of the quantized source. We con-
sider memoryless Gaussian and Gauss-Markov sources trans-
mitted over a binary phase-shift keying modulated additive
white Gaussian noise channel. Our scheme which has less
decoding complexity than soft decoded COVQ systems, is
shown to provide a notable signal-to-distortion ratio gain (up
to 0.4 dB for memoryless Gaussian sources and up to 0.8 dB for
Gauss-Markov sources) over the conventional COVQ designed
for hard-decision demodulated channels.
I. INTRODUCTION
Communication systems designed on the basis of Shan-
non's separation theorem are called tandem source-channel

  

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

 

Collections: Engineering