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Paper IDM.6.4
Paper Title Maximum Likelihood Decoding for Channels with Uniform Noise and Signal Dependent Offset
Authors Renfei Bu, Jos H. Weber, Delft University of Technology, Netherlands; Kees A. Schouhamer Immink, Turing Machines Inc., Netherlands
Session M.6: Coding for Storage and Memories II
Presentation Lecture
Track Coding for Storage and Memories
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Abstract Maximum likelihood (ML) decision criteria have been developed for channels suffering from signal independent offset mismatch. Here, such criteria are considered for signal dependent offset, which means that the value of the offset may differ for distinct signal levels rather than being the same for all levels. An ML decision criterion is derived, assuming uniform distributions for both the noise and the offset. In particular, for the proposed ML decoder, bounds are determined on the standard deviations of the noise and the offset which lead to a word error rate equal to zero. Simulation results are presented confirming the findings.

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2021 IEEE International Symposium on Information Theory

11-16 July 2021 | Melbourne, Victoria, Australia

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