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AuthorAlouini, Mohamed-Slim (2)

Kammoun, Abla (2)

Rached, Nadhir B. (2)

Tempone, Raul (2)Ben Issaid, Chaouki (1)DepartmentApplied Mathematics and Computational Science Program (2)Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division (2)Electrical Engineering Program (2)Center for Uncertainty Quantification in Computational Science and Engineering (SRI-UQ) (1)Statistics Program (1)JournalIEEE Transactions on Communications (2)PublisherInstitute of Electrical and Electronics Engineers (IEEE) (2)Subject
importance sampling (2)

outage probability (2)

bounded relative error (1)covariance matrix scaling (1)Gamma-Gamma (1)View MoreTypeArticle (2)Year (Issue Date)
2017 (2)

Item AvailabilityOpen Access (2)

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On the Efficient Simulation of Outage Probability in a Log-normal Fading Environment

Rached, Nadhir B.; Kammoun, Abla; Alouini, Mohamed-Slim; Tempone, Raul (IEEE Transactions on Communications, Institute of Electrical and Electronics Engineers (IEEE), 2017-02-15) [Article]

The outage probability (OP) of the signal-to-interference-plus-noise ratio (SINR) is an important metric that is used to evaluate the performance of wireless systems. One difficulty toward assessing the OP is that, in realistic scenarios, closed-form expressions cannot be derived. This is for instance the case of the Log-normal environment, in which evaluating the OP of the SINR amounts to computing the probability that a sum of correlated Log-normal variates exceeds a given threshold. Since such a probability does not admit a closed-form expression, it has thus far been evaluated by several approximation techniques, the accuracies of which are not guaranteed in the region of small OPs. For these regions, simulation techniques based on variance reduction algorithms is a good alternative, being quick and highly accurate for estimating rare event probabilities. This constitutes the major motivation behind our work. More specifically, we propose a generalized hybrid importance sampling scheme, based on a combination of a mean shifting and a covariance matrix scaling, to evaluate the OP of the SINR in a Log-normal environment. We further our analysis by providing a detailed study of two particular cases. Finally, the performance of these techniques is performed both theoretically and through various simulation results.

On the Efficient Simulation of the Distribution of the Sum of Gamma-Gamma Variates with Application to the Outage Probability Evaluation Over Fading Channels

Ben Issaid, Chaouki; Rached, Nadhir B.; Kammoun, Abla; Alouini, Mohamed-Slim; Tempone, Raul (IEEE Transactions on Communications, Institute of Electrical and Electronics Engineers (IEEE), 2017-01-26) [Article]

The Gamma-Gamma distribution has recently emerged in a number of applications ranging from modeling scattering and reverberation in sonar and radar systems to modeling atmospheric turbulence in wireless optical channels. In this respect, assessing the outage probability achieved by some diversity techniques over this kind of channels is of major practical importance. In many circumstances, this is related to the difficult question of analyzing the statistics of a sum of Gamma- Gamma random variables. Answering this question is not a simple matter. This is essentially because outage probabilities encountered in practice are often very small, and hence the use of classical Monte Carlo methods is not a reasonable choice. This lies behind the main motivation of the present work. In particular, this paper proposes a new approach to estimate the left tail of the sum of Gamma-Gamma variates. More specifically, we propose robust importance sampling schemes that efficiently evaluates the outage probability of diversity receivers over Gamma-Gamma fading channels. The proposed estimators satisfy the well-known bounded relative error criterion for both maximum ratio combining and equal gain combining cases. We show the accuracy and the efficiency of our approach compared to naive Monte Carlo via some selected numerical simulations.

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