24,670 research outputs found
Selective Combining for Hybrid Cooperative Networks
In this study, we consider the selective combining in hybrid cooperative
networks (SCHCNs scheme) with one source node, one destination node and
relay nodes. In the SCHCN scheme, each relay first adaptively chooses between
amplify-and-forward protocol and decode-and-forward protocol on a per frame
basis by examining the error-detecting code result, and () relays will be selected to forward their received signals to the
destination. We first develop a signal-to-noise ratio (SNR) threshold-based
frame error rate (FER) approximation model. Then, the theoretical FER
expressions for the SCHCN scheme are derived by utilizing the proposed SNR
threshold-based FER approximation model. The analytical FER expressions are
validated through simulation results.Comment: 27 pages, 8 figures, IET Communications, 201
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
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