Title :
Efficiency of optimal conditional importance sampling
Author_Institution :
Res. Sch. Inf. & Sci. Eng., Australian Nat. Univ., Canberra, ACT, Australia
fDate :
8/3/1995 12:00:00 AM
Abstract :
Optimal conditional importance sampling (OCIS) provides the unique optimal conditional estimator for error probabilities. The OCIS method essentially obtains a Monte Carlo average over conditional error probabilities. The efficiency of OCIS is studied for a binary symmetric ISI channel with AWGN. The results show that the technique is at least twice as efficient as that of the linearly shifted method
Keywords :
Gaussian noise; Monte Carlo methods; digital radio; error statistics; intersymbol interference; mobile radio; probability; signal sampling; telecommunication channels; white noise; AWGN; Monte Carlo average; binary symmetric ISI channel; conditional error probabilities; error probabilities; optimal conditional estimator; optimal conditional importance sampling;
Journal_Title :
Electronics Letters
DOI :
10.1049/el:19950906
