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Summary: On Decoding Binary Quasi-Perfect Codes
Over Markov Noise Channels
Haider Al-Lawati and Fady Alajaji
Department of Mathematics and Statistics
Queen's University, Kingston, ON K7L 3N6, Canada
Email: {haider,fady}@mast.queensu.ca
Abstract-- We study the decoding problem when a binary
linear quasi-perfect code is transmitted over a binary channel
with additive Markov noise. After examining the properties
of the channel block transition distribution, we show a near
equivalence relationship between strict maximum likelihood and
strict minimum Hamming distance decoding for a range of
channel parameters and the code's minimum distance. As a
result, an improved minimum distance decoder is proposed and
simulations illustrating its benefits are provided.
I. INTRODUCTION
Conventional communication systems employ coding
schemes that are designed for memoryless channels. However,
since most real world channels have memory, interleaving is
used in an attempt to spread the channel noise in a uniform
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