Citation:
IEEE International Symposium on Information Theory (ISIT 2018), 17-22 June 2018, Vail, Colorado, USA. [Proceedings], 5 p.
ISBN:
978-1-5386-4780-6
ISSN:
2157-8117
Sponsor:
This work has been funded in part by the European Research Council (ERC) under grants 714161 and 725411, by the Spanish Ministry of Economy and Competitiveness under grants TEC2013-41718-R, RYC-201416332, IJCI-2015-27020 and TEC2016-78434-C3 (AEI/FEDER, EU), by the Madrid Autonomous Community under grant S2103/ICE-2845 and by the Spanish
Ministry of Education, Culture and Sport under grant FPU14/01274.
Project:
info:eu-repo/grantAgreement/EC/H2020/714161 info:eu-repo/grantAgreement/EC/H2020/725411 Gobierno de España. TEC2013-41718-R Gobierno de España. RYC-2014-16332 Gobierno de España. IJCI-2015-27020 Gobierno de España. TEC2016-78434-C3 (AEI/FEDER, EU) Gobierno de España. FPU14/01274 Comunidad de Madrid. S2103/ICE-2845
Keywords:
Error probability
,
Testing
,
Random variables
,
AWGN channels
,
Laplace equations
,
Gaussian distribution
We propose a saddlepoint approximation of the error probability of a binary hypothesis test between two i.i.d. distributions. The approximation is accurate, simple to compute, and yields a unified analysis in different asymptotic regimes. The proposed formulatWe propose a saddlepoint approximation of the error probability of a binary hypothesis test between two i.i.d. distributions. The approximation is accurate, simple to compute, and yields a unified analysis in different asymptotic regimes. The proposed formulation is used to efficiently compute the meta-converse lower bound for moderate block-lengths in several cases of interest.[+][-]