Binary Block Codes for Noisy Channels with Unknown Offset

Journal article (2020)

Authors

J.H. Weber Discrete Mathematics and Optimization - EEMCS
R. Bu Discrete Mathematics and Optimization - EEMCS
Kui Cai Singapore University of Technology and Design
Kees A. Schouhamer Immink Turing Machines Inc.
Research Group
Discrete Mathematics and Optimization (EEMCS) (TU Delft)
Copyright: © 2020 J.H. Weber, R. Bu, Kui Cai, Kees A. Schouhamer Immink
DOI: https://doi.org/10.1109/TCOMM.2020.2986200
Offset Noise Performance evaluation Binary block codes Decoding criteria
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Published Date

2020-7

Language

English

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Faculty

Electrical Engineering, Mathematics and Computer Science

Department

Delft Institute of Applied Mathematics

Research Group

Discrete Mathematics and Optimization

Abstract

Decoders minimizing the Euclidean distance between the received word and the candidate codewords are known to be optimal for channels suffering from Gaussian noise. However, when the stored or transmitted signals are also corrupted by an unknown offset, other decoders may perform better. In particular, applying the Euclidean distance on normalized words makes the decoding result independent of the offset. The use of this distance measure calls for alternative code design criteria in order to get good performance in the presence of both noise and offset. In this context, various adapted versions of classical binary block codes are proposed, such as (i) cosets of linear codes, (ii) (unions of) constant weight codes, and (iii) unordered codes. It is shown that considerable performance improvements can be achieved, particularly when the offset is large compared to the noise.