15,724 research outputs found

    The Intensity Matching Approach: A Tractable Stochastic Geometry Approximation to System-Level Analysis of Cellular Networks

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    The intensity matching approach for tractable performance evaluation and optimization of cellular networks is introduced. It assumes that the base stations are modeled as points of a Poisson point process and leverages stochastic geometry for system-level analysis. Its rationale relies on observing that system-level performance is determined by the intensity measure of transformations of the underlaying spatial Poisson point process. By approximating the original system model with a simplified one, whose performance is determined by a mathematically convenient intensity measure, tractable yet accurate integral expressions for computing area spectral efficiency and potential throughput are provided. The considered system model accounts for many practical aspects that, for tractability, are typically neglected, e.g., line-of-sight and non-line-of-sight propagation, antenna radiation patterns, traffic load, practical cell associations, general fading channels. The proposed approach, more importantly, is conveniently formulated for unveiling the impact of several system parameters, e.g., the density of base stations and blockages. The effectiveness of this novel and general methodology is validated with the aid of empirical data for the locations of base stations and for the footprints of buildings in dense urban environments.Comment: Submitted for Journal Publicatio

    Feature selection for modular GA-based classification

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    Genetic algorithms (GAs) have been used as conventional methods for classifiers to adaptively evolve solutions for classification problems. Feature selection plays an important role in finding relevant features in classification. In this paper, feature selection is explored with modular GA-based classification. A new feature selection technique, Relative Importance Factor (RIF), is proposed to find less relevant features in the input domain of each class module. By removing these features, it is aimed to reduce the classification error and dimensionality of classification problems. Benchmark classification data sets are used to evaluate the proposed approach. The experiment results show that RIF can be used to find less relevant features and help achieve lower classification error with the feature space dimension reduced

    On the low energy brane/anti-brane dynamics

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    We study the dynamical behavior of a pair of Dp-brane and anti Dp-brane (0p60 \leq p \leq 6) moving parallel to each other in the region where the brane and anti-brane annihilation will not occur and the low energy description is valid. Given this, we perform a general analysis, in the center of mass frame, of the behavior of the effective potential with respect to the relative brane separation and find that the classical orbits of this system are in general unbound except for p=6p = 6 case for which classical bound orbits exist. The non-linearity of the low energy DBI action for D-brane is important for the underlying dynamics. We solve also the explicit orbits for p=6p = 6 case.Comment: 15 pages, 2 figures; shorten version published in Phys. Lett
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