Print Email Facebook Twitter Maximum Likelihood Decoding for Gaussian Noise Channels with Gain or Offset Mismatch Title Maximum Likelihood Decoding for Gaussian Noise Channels with Gain or Offset Mismatch Author Weber, J.H. (TU Delft Discrete Mathematics and Optimization) Schouhamer Immink, Kees A. (Turing Machines Inc.) Date 2018 Abstract Besides the omnipresent noise, other important inconveniences in communication and storage systems are formed by gain and/or offset mismatches. In the prior art, a maximum likelihood (ML) decision criterion has already been developed for Gaussian noise channels suffering from unknown gain and offset mismatches. Here, such criteria are considered for Gaussian noise channels suffering from either an unknown offset or an unknown gain. Furthermore, ML decision criteria are derived when assuming a Gaussian or uniform distribution for the offset in the absence of gain mismatch. Subject Maximum likelihood decodingEuclidean distanceGaussian noiseReceiversMaximum likelihood detectionStandards To reference this document use: http://resolver.tudelft.nl/uuid:442c4c2c-c07a-4112-a05d-d72dfda699d1 DOI https://doi.org/10.1109/LCOMM.2018.2809749 ISSN 1089-7798 Source IEEE Communications Letters, 22 (6), 1128-1131 Bibliographical note Accepted Author Manuscript Part of collection Institutional Repository Document type journal article Rights © 2018 J.H. Weber, Kees A. Schouhamer Immink Files PDF 42589728_FINAL_VERSION.pdf 178.58 KB Close viewer /islandora/object/uuid:442c4c2c-c07a-4112-a05d-d72dfda699d1/datastream/OBJ/view