Unified Importance Sampling Schemes for Efficient Simulation of Outage Capacity over Generalized Fading Channels

Handle URI:
http://hdl.handle.net/10754/582497
Title:
Unified Importance Sampling Schemes for Efficient Simulation of Outage Capacity over Generalized Fading Channels
Authors:
Rached, Nadhir B.; Kammoun, Abla ( 0000-0002-0195-3159 ) ; Alouini, Mohamed-Slim ( 0000-0003-4827-1793 ) ; Tempone, Raul ( 0000-0003-1967-4446 )
Abstract:
The outage capacity (OC) is among the most important performance metrics of communication systems operating over fading channels. Of interest in the present paper is the evaluation of the OC at the output of the Equal Gain Combining (EGC) and the Maximum Ratio Combining (MRC) receivers. In this case, it can be seen that this problem turns out to be that of computing the Cumulative Distribution Function (CDF) for the sum of independent random variables. Since finding a closedform expression for the CDF of the sum distribution is out of reach for a wide class of commonly used distributions, methods based on Monte Carlo (MC) simulations take pride of price. In order to allow for the estimation of the operating range of small outage probabilities, it is of paramount importance to develop fast and efficient estimation methods as naive Monte Carlo (MC) simulations would require high computational complexity. In this line, we propose in this work two unified, yet efficient, hazard rate twisting Importance Sampling (IS) based approaches that efficiently estimate the OC of MRC or EGC diversity techniques over generalized independent fading channels. The first estimator is shown to possess the asymptotic optimality criterion and applies for arbitrary fading models, whereas the second one achieves the well-desired bounded relative error property for the majority of the well-known fading variates. Moreover, the second estimator is shown to achieve the asymptotic optimality property under the particular Log-normal environment. Some selected simulation results are finally provided in order to illustrate the substantial computational gain achieved by the proposed IS schemes over naive MC simulations.
KAUST Department:
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Citation:
Unified Importance Sampling Schemes for Efficient Simulation of Outage Capacity over Generalized Fading Channels 2015:1 IEEE Journal of Selected Topics in Signal Processing
Publisher:
Institute of Electrical and Electronics Engineers (IEEE)
Journal:
IEEE Journal of Selected Topics in Signal Processing
Issue Date:
13-Nov-2015
DOI:
10.1109/JSTSP.2015.2500201
Type:
Article
ISSN:
1932-4553; 1941-0484
Additional Links:
http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=7328688
Appears in Collections:
Articles; Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

Full metadata record

DC FieldValue Language
dc.contributor.authorRached, Nadhir B.en
dc.contributor.authorKammoun, Ablaen
dc.contributor.authorAlouini, Mohamed-Slimen
dc.contributor.authorTempone, Raulen
dc.date.accessioned2015-11-22T12:12:44Zen
dc.date.available2015-11-22T12:12:44Zen
dc.date.issued2015-11-13en
dc.identifier.citationUnified Importance Sampling Schemes for Efficient Simulation of Outage Capacity over Generalized Fading Channels 2015:1 IEEE Journal of Selected Topics in Signal Processingen
dc.identifier.issn1932-4553en
dc.identifier.issn1941-0484en
dc.identifier.doi10.1109/JSTSP.2015.2500201en
dc.identifier.urihttp://hdl.handle.net/10754/582497en
dc.description.abstractThe outage capacity (OC) is among the most important performance metrics of communication systems operating over fading channels. Of interest in the present paper is the evaluation of the OC at the output of the Equal Gain Combining (EGC) and the Maximum Ratio Combining (MRC) receivers. In this case, it can be seen that this problem turns out to be that of computing the Cumulative Distribution Function (CDF) for the sum of independent random variables. Since finding a closedform expression for the CDF of the sum distribution is out of reach for a wide class of commonly used distributions, methods based on Monte Carlo (MC) simulations take pride of price. In order to allow for the estimation of the operating range of small outage probabilities, it is of paramount importance to develop fast and efficient estimation methods as naive Monte Carlo (MC) simulations would require high computational complexity. In this line, we propose in this work two unified, yet efficient, hazard rate twisting Importance Sampling (IS) based approaches that efficiently estimate the OC of MRC or EGC diversity techniques over generalized independent fading channels. The first estimator is shown to possess the asymptotic optimality criterion and applies for arbitrary fading models, whereas the second one achieves the well-desired bounded relative error property for the majority of the well-known fading variates. Moreover, the second estimator is shown to achieve the asymptotic optimality property under the particular Log-normal environment. Some selected simulation results are finally provided in order to illustrate the substantial computational gain achieved by the proposed IS schemes over naive MC simulations.en
dc.language.isoenen
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en
dc.relation.urlhttp://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=7328688en
dc.rights(c) 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.en
dc.subjectImportance Samplingen
dc.subjectOutage capacityen
dc.subjectasymptotic optimalityen
dc.subjectbounded relative erroren
dc.subjecthazard rate twistingen
dc.subjectnaive Monte Carloen
dc.titleUnified Importance Sampling Schemes for Efficient Simulation of Outage Capacity over Generalized Fading Channelsen
dc.typeArticleen
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Divisionen
dc.identifier.journalIEEE Journal of Selected Topics in Signal Processingen
dc.eprint.versionPost-printen
dc.contributor.affiliationKing Abdullah University of Science and Technology (KAUST)en
kaust.authorRached, Nadhir B.en
kaust.authorKammoun, Ablaen
kaust.authorAlouini, Mohamed-Slimen
kaust.authorTempone, Raulen
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