TY - GEN

T1 - A unified simulation approach for the fast outage capacity evaluation over generalized fading channels

AU - Rached, Nadhir B.

AU - Kammoun, Abla

AU - Alouini, Mohamed-Slim

AU - Tempone, Raul

N1 - KAUST Repository Item: Exported on 2020-10-01

PY - 2015/10/1

Y1 - 2015/10/1

N2 - The outage capacity (OC) is among the most important performance metrics of communication systems over fading channels. The evaluation of the OC, when Equal Gain Combining (EGC) or Maximum Ratio Combining (MRC) diversity techniques are employed, boils down to computing the Cumulative Distribution Function (CDF) of the sum of channel envelopes (equivalently amplitudes) for EGC or channel gain (equivalently squared enveloped/amplitudes) for MRC. Closed-form expressions of the CDF of the sum of many generalized fading variates are generally unknown and constitute open problems. In this paper, we develop a unified hazard rate twisting Importance Sampling (IS) based approach to efficiently estimate the CDF of the sum of independent arbitrary variates. The proposed IS estimator is shown to achieve an asymptotic optimality criterion, which clearly guarantees its efficiency. Some selected simulation results are also shown to illustrate the substantial computational gain achieved by the proposed IS scheme over crude Monte-Carlo simulations.

AB - The outage capacity (OC) is among the most important performance metrics of communication systems over fading channels. The evaluation of the OC, when Equal Gain Combining (EGC) or Maximum Ratio Combining (MRC) diversity techniques are employed, boils down to computing the Cumulative Distribution Function (CDF) of the sum of channel envelopes (equivalently amplitudes) for EGC or channel gain (equivalently squared enveloped/amplitudes) for MRC. Closed-form expressions of the CDF of the sum of many generalized fading variates are generally unknown and constitute open problems. In this paper, we develop a unified hazard rate twisting Importance Sampling (IS) based approach to efficiently estimate the CDF of the sum of independent arbitrary variates. The proposed IS estimator is shown to achieve an asymptotic optimality criterion, which clearly guarantees its efficiency. Some selected simulation results are also shown to illustrate the substantial computational gain achieved by the proposed IS scheme over crude Monte-Carlo simulations.

UR - http://hdl.handle.net/10754/579722

UR - http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=7282474

UR - http://www.scopus.com/inward/record.url?scp=84969866301&partnerID=8YFLogxK

U2 - 10.1109/ISIT.2015.7282474

DO - 10.1109/ISIT.2015.7282474

M3 - Conference contribution

SN - 9781467377041

SP - 346

EP - 350

BT - 2015 IEEE International Symposium on Information Theory (ISIT)

PB - Institute of Electrical and Electronics Engineers (IEEE)

ER -