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dc.contributor.authorBen Rached, Nadhir
dc.contributor.authorBotev, Zdravko
dc.contributor.authorKammoun, Abla
dc.contributor.authorAlouini, Mohamed-Slim
dc.contributor.authorTempone, Raul
dc.date.accessioned2019-01-13T06:44:06Z
dc.date.available2019-01-13T06:44:06Z
dc.date.issued2018-09-21
dc.identifier.citationRached, N. B., Botev, Z., Kammoun, A., Alouini, M.-S., & Tempone, R. (2018). Importance Sampling Estimator of Outage Probability under Generalized Selection Combining Model. 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). doi:10.1109/icassp.2018.8462177
dc.identifier.doi10.1109/ICASSP.2018.8462177
dc.identifier.urihttp://hdl.handle.net/10754/630800
dc.description.abstractWe consider the problem of evaluating outage probability (OP) values of generalized selection combining diversity receivers over fading channels. This is equivalent to computing the cumulative distribution function (CDF) of the sum of order statistics. Generally, closed-form expressions of the CDF of order statistics are unavailable for many practical distributions. Moreover, the naive Monte Carlo method requires a substantial computational effort when the probability of interest is sufficiently small. In the region of small OP values, we propose instead an efficient, yet universal, importance sampling (IS) estimator that yields a reliable estimate of the CDF with small computing cost. The main feature of the proposed IS estimator is that it has bounded relative error under a certain assumption that is shown to hold for most of the challenging distributions. Moreover, an improvement of this estimator is proposed for the Pareto and the Weibull cases. Finally, the efficiency of the proposed estimators are investigated through various numerical experiments.
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.relation.urlhttps://ieeexplore.ieee.org/abstract/document/8462177
dc.titleImportance Sampling Estimator of Outage Probability under Generalized Selection Combining Model
dc.typeConference Paper
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.identifier.journal2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
dc.conference.date15-20 April 2018
dc.conference.name2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
dc.conference.locationCalgary, AB, Canada
dc.eprint.versionPost-print
dc.contributor.institutionUniversity of New South Wales (UNSW), Sydney, NSW, Australia
dc.source.beginpage3909
dc.source.endpage3913
refterms.dateFOA2019-01-13T06:44:07Z
dc.date.published-online2018-09-21
dc.date.published-print2018-04


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