Convexity of error probability in binary scalar detection

Author

Azizoglu, Murat

Author_Institution

Dept. of Electr. Eng. & Comput. Sci., George Washington Univ., Washington, DC, USA

fYear

1994

fDate

27 Jun-1 Jul 1994

Firstpage

469

Abstract

This paper obtains results on the convexity of error probability in the detection of binary-valued scalar signals corrupted by additive noise. It is shown that the error probability of the maximum likelihood receiver is a convex function of the signal-to-noise ratio (SNR) when the noise has a unimodal, differentiable probability density function. This result has some interesting implications on the optimum strategies of the transmitter and the jammer, as well as the optimal use of multiple channels

Keywords

error statistics; jamming; maximum likelihood detection; noise; telecommunication channels; additive noise; binary scalar detection; binary-valued scalar signals; convex function; differentiable probability density function; error probability convexity; jammer; maximum likelihood receiver; multiple channels; optimum strategies; signal-to-noise ratio; transmitter; Additive noise; Communication systems; Constraint theory; Error probability; Jamming; Maximum likelihood detection; Probability density function; Signal to noise ratio; Time sharing computer systems; Transmitters;

fLanguage

English

Publisher

ieee

Conference_Titel

Information Theory, 1994. Proceedings., 1994 IEEE International Symposium on

Conference_Location

Trondheim

Print_ISBN

0-7803-2015-8

Type

conf

DOI

10.1109/ISIT.1994.395084

Filename

395084