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Error Exponents for Dimension-Matched Vector Multiple Access Channels With Additive Noise

Venkat Anantharam 1 François Baccelli 2
2 DYOGENE - Dynamics of Geometric Networks
Inria de Paris, CNRS - Centre National de la Recherche Scientifique : UMR 8548, DI-ENS - Département d'informatique de l'École normale supérieure
Abstract : 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.
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Submitted on : Friday, December 20, 2019 - 8:56:25 PM
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Venkat Anantharam, François Baccelli. Error Exponents for Dimension-Matched Vector Multiple Access Channels With Additive Noise. IEEE Transactions on Information Theory, Institute of Electrical and Electronics Engineers, 2019, 65 (5), pp.2808-2823. ⟨10.1109/TIT.2018.2875541⟩. ⟨hal-02422196⟩



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