2009 IEEE Wireless Communications and Networking Conference 2009
DOI: 10.1109/wcnc.2009.4917849
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On the Approximation of the Generalized-K PDF by a Gamma PDF Using the Moment Matching Method

Abstract: Abstract-Using the Nakagami probability density function (PDF) to model multipath fading and the Gamma PDF to model shadowing, in a wireless channel, has led to a closed-form expression for the composite fading PDF, known as the generalized-K PDF (also called Gamma-Gamma PDF). However, further derivations have shown that the cumulative distribution function (CDF) and the characteristic function of the generalized-K PDF contain special functions that are involved to handle. In this paper, an approximation of th… Show more

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Cited by 37 publications
(25 citation statements)
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“…1) Our analysis can also approximate fading correlation scenarios by performing moment matching to simplify to a single Gamma distribution [29].…”
Section: Interference Modelmentioning
confidence: 99%
“…1) Our analysis can also approximate fading correlation scenarios by performing moment matching to simplify to a single Gamma distribution [29].…”
Section: Interference Modelmentioning
confidence: 99%
“…Due to space limitations we will study only the MGF of the Gamma composite fading case, i.e., we consider a scenario in which shadowing and fading statistics are modeled by a Gamma and Nakagami distribution (also referred as Generalized-K [10]), respectively. Recently, in [10] an accurate approximation of the Generalized-K RV using moment matching method has been proposed to increase its analytical tractability, i.e., the Generalized-K distribution can be approximated by a simple Gamma distribution [10]. Therefore in this case M X (t)) can be derived as follows:…”
Section: Mgf Of the Cumulative Icimentioning
confidence: 99%
“…In this case, the composite distribution has a closed form which is known as generalized-K or Gamma-Gamma distribution [11]. In order to avoid the computational difficulties, while dealing with the generalized-K RV, the authors in [12] proposed an accurate approximation of the generalized-K RV using moment matching method, i.e., the generalized-K distribution can be approximated by a simple Gamma distribution using moment matching method [12]. Therefore in this case, using (20), f X (x) can be written as follows:…”
Section: Distribution Of the Allocated User Locationsmentioning
confidence: 99%