Free-space optical communication employing subcarrier modulation and spatial diversity in atmospheric turbulence channel

An expression for the bit error rate of a multiple subcarrier intensity-modulated atmospheric optical communication system employing spatial diversity is derived. Spatial diversity is used to mitigate scintillation caused by atmospheric turbulence, which is assumed to obey lognormal distribution. Optimal but complex maximum ratio, equal gain combining (EGC) and relatively simple selection combining spatial diversity techniques in a clear atmosphere are considered. Each subcarrier is modulated using binary phase shift keying. Laser irradiance is subsequently modulated by a subcarrier signal, and a direct detection PIN receiver is employed (i.e. intensity modulation/direction detection). At a subcarrier level, coherent demodulation is used to extract the transmitted data/information. The performance of on–off-keying is also presented and compared with the subcarrier intensity modulation under the same atmospheric conditions

On the Multivariate Gamma-Gamma (ΓΓ\Gamma \Gamma) Distribution with Arbitrary Correlation and Applications in Wireless Communications

The statistical properties of the multivariate Gamma-Gamma ($\Gamma \Gamma$) distribution with arbitrary correlation have remained unknown. In this paper, we provide analytical expressions for the joint probability density function (PDF), cumulative distribution function (CDF) and moment generation function of the multivariate $\Gamma \Gamma$ distribution with arbitrary correlation. Furthermore, we present novel approximating expressions for the PDF and CDF of the sum of $\Gamma \Gamma$ random variables with arbitrary correlation. Based on this statistical analysis, we investigate the performance of radio frequency and optical wireless communication systems. It is noteworthy that the presented expressions include several previous results in the literature as special cases.Comment: 7 pages, 6 figures, accepted by IEEE Transactions on Vehicular Technolog

On the Sum of Order Statistics and Applications to Wireless Communication Systems Performances

We consider the problem of evaluating the cumulative distribution function (CDF) of the sum of order statistics, which serves to compute outage probability (OP) values at the output of generalized selection combining receivers. Generally, closed-form expressions of the CDF of the sum of order statistics are unavailable for many practical distributions. Moreover, the naive Monte Carlo (MC) method requires a substantial computational effort when the probability of interest is sufficiently small. In the region of small OP values, we propose instead two effective variance reduction techniques that yield a reliable estimate of the CDF with small computing cost. The first estimator, which can be viewed as an importance sampling estimator, has bounded relative error under a certain assumption that is shown to hold for most of the challenging distributions. An improvement of this estimator is then proposed for the Pareto and the Weibull cases. The second is a conditional MC estimator that achieves the bounded relative error property for the Generalized Gamma case and the logarithmic efficiency in the Log-normal case. Finally, the efficiency of these estimators is compared via various numerical experiments