Title :
Convexity of error probability in binary scalar detection
Author_Institution :
Dept. of Electr. Eng. & Comput. Sci., George Washington Univ., Washington, DC, USA
fDate :
27 Jun-1 Jul 1994
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;
Conference_Titel :
Information Theory, 1994. Proceedings., 1994 IEEE International Symposium on
Conference_Location :
Trondheim
Print_ISBN :
0-7803-2015-8
DOI :
10.1109/ISIT.1994.395084
