Achievable rates and error exponents for a class of mismatched compound channels
This paper investigates achievable information rates and error exponents of mismatched decoding when the channel belongs to the class of channels that are close to the decoding metric in terms of relative entropy. For both discrete- and continuous-alphabet channels, we derive approximations of the w...
| Autores: | , , |
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| Formato: | artículo |
| Fecha de publicación: | 2025 |
| País: | España |
| Recursos: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/444814 |
| Acesso em linha: | https://hdl.handle.net/2117/444814 https://dx.doi.org/10.1109/TIT.2025.3574460 |
| Access Level: | acceso abierto |
| Palavra-chave: | Information theory Mismatched decoding Achievable rates Error exponents Relative entropy Channel uncertainty Discrete and continuous channels Imperfect channel estimation Modulo-additive noise Nearest neighbor decoding |
| Resumo: | This paper investigates achievable information rates and error exponents of mismatched decoding when the channel belongs to the class of channels that are close to the decoding metric in terms of relative entropy. For both discrete- and continuous-alphabet channels, we derive approximations of the worst-case achievable information rates and error exponents as a function of the radius of a small relative entropy ball centered at the decoding metric, allowing the characterization of the loss incurred due to imperfect channel estimation. We provide a number of examples including symmetric metrics and modulo-additive noise metrics for discrete systems, and nearest neighbor decoding for continuous-alphabet channels, where we derive the approximation when the channel admits arbitrary statistics and when it is assumed noise-additive with unknown finite second-order moment. |
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