Error Exponents for Dimension-Matched Vector Multiple Access Channels With Additive Noise
| Autor: | Venkat Anantharam, François Baccelli |
|---|---|
| Přispěvatelé: | Department of Electrical Engineering and Computer Science [Berkeley] (EECS), University of California [Berkeley] (UC Berkeley), University of California (UC)-University of California (UC), Dynamics of Geometric Networks (DYOGENE), Département d'informatique - ENS Paris (DI-ENS), École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Inria de Paris, Institut National de Recherche en Informatique et en Automatique (Inria), University of California [Berkeley], University of California-University of California, Inria de Paris, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Département d'informatique - ENS Paris (DI-ENS), Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche en Informatique et en Automatique (Inria)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL), Département d'informatique de l'École normale supérieure (DI-ENS), École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Paris (ENS Paris) |
| Rok vydání: | 2019 |
| Předmět: |
Independent and identically distributed random variables
02 engineering and technology Positive-definite matrix Multiple access channels Library and Information Sciences Noise (electronics) Point process symbols.namesake Dimension (vector space) Poltyrev capacity Random coding 0202 electrical engineering electronic engineering information engineering Computer Science::Information Theory Mathematics Discrete mathematics Covariance matrix Error exponents [MATH.MATH-IT]Mathematics [math]/Information Theory [math.IT] 020206 networking & telecommunications Computer Science Applications Stationary point processes Gaussian noise symbols Palm calculus Decoding methods Information Systems |
| Zdroj: | IEEE Transactions on Information Theory IEEE Transactions on Information Theory, 2019, 65 (5), pp.2808-2823. ⟨10.1109/TIT.2018.2875541⟩ IEEE Transactions on Information Theory, Institute of Electrical and Electronics Engineers, 2019, 65 (5), pp.2808-2823. ⟨10.1109/TIT.2018.2875541⟩ |
| ISSN: | 1557-9654 0018-9448 |
| DOI: | 10.1109/tit.2018.2875541 |
| Popis: | International audience; We analyze a class of vector multiple access channels with additive noise, where the sum of the dimensions of the transmitted signals matches that of the received signal. We first focus on the case without power constraints, in the Poltyrev sense, using point process techniques. We find the Poltyrev capacity region for noise processes that are independent and identically distributed over channel uses. For each rate vector strictly in the Poltyrev capacity region, we study, for each subset of the transmitters, the exponent of the decay in block length of the smallest possible probability that decoding results in error for each transmitter in that subset. In the case of independent and identically distributed Gaussian noise, with arbitrary positive definite covariance matrix, we derive random coding exponents for each type of error event-these are lower bounds to the true error exponents. This also leads to random coding error exponents in the traditional power-constrained case, where the power constraint at each transmitter is defined by an arbitrary positive definite matrix. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|