Worst-case power-constrained noise for binary-input channels

1 September 1992

journal article
Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Information Theory

Vol. 38 (5) , 1494-1511
https://doi.org/10.1109/18.149501

Abstract

Additive noise channels with binary-valued inputs and real-valued outputs are considered. The maximum error probability and the minimum channel capacity achieved by any power-constrained noise distribution are obtained. A general framework which applies to a variety of performance measures shows that the least-favorable noise distribution is, in general, a mixture of two lattice probability mass functions. The framework holds for m-ary input constellations on finite-dimensional lattices.

Keywords

This publication has 20 references indexed in Scilit:

On the capacity of channels with unknown interference
IEEE Transactions on Information Theory, 1989
On the capacity of channels with block memory
IEEE Transactions on Information Theory, 1988
Gaussian arbitrarily varying channels
IEEE Transactions on Information Theory, 1987
Minimax Robust Discrete-Time Matched Filters
IEEE Transactions on Communications, 1983
Coding Theorems of Information Theory
Published by Springer Nature ,1978
An upper bound on the probability of error due to intersymbol interference for correlated digital signals
IEEE Transactions on Information Theory, 1972
Convex Analysis
Published by Walter de Gruyter GmbH ,1970
Coding for a class of unknown channels
IEEE Transactions on Information Theory, 1966
Signal detection under noise interference in a game situation
IEEE Transactions on Information Theory, 1962
Communications through unspecified additive noise
Information and Control, 1961