The $\kappa$– $\mu$ Shadowed Fading Model: Unifying the $\kappa$– $\mu$ and $\eta$– $\mu$ Distributions

Moreno-Pozas, Laureano; López‐Martínez, F. Javier; Paris, José F.; Martos-Naya, Eduardo

doi:10.1109/tvt.2016.2525721

Cited by 90 publications

(39 citation statements)

References 27 publications

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“…denotes the Kummer confluent hypergeometric function [15]. In [14], [5] the authors have shown how popular fading distributions such as Rayleigh, Rician, Rician shadowed, Nakagami, κ-µ, η-µ, one sided Gaussian, Hoyt etc. can be obtained as special cases of κ-µ shadowed fading.…”

Section: System Modelmentioning

confidence: 99%

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Error Vector Magnitude Analysis in Generalized Fading With Co-Channel Interference

Parthasarathy

Kumar

Ganti

et al. 2018

IEEE Trans. Commun.

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In this paper, we derive the data-aided Error Vector Magnitude (EVM) in an interference limited system when both the desired signal and interferers experience independent and non identically distributed κ-µ shadowed fading. Then it is analytically shown that the EVM is equal to the square root of number of interferers when the desired signal and interferers do not experience fading. Further, EVM is derived in the presence of interference and noise, when the desired signal experiences κ-µ shadowed fading and the interferers experience independent and identical Nakagami fading. Moreover, using the properties of the special functions, the derived EVM expressions are also simplified for various special cases.

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Section: System Modelmentioning

confidence: 99%

“…Secondly, they fit experimentally measured mobile radio propagation statistics better as compared to the other channel models [4]. Recently, Paris has proposed κ-µ shadowed fading and in [5] it has been shown that both κ-µ and η-µ fading are the special cases of κ-µ shadowed fading.…”

Section: Introductionmentioning

confidence: 96%

Error Vector Magnitude Analysis in Generalized Fading With Co-Channel Interference

Parthasarathy

Kumar

Ganti

et al. 2018

IEEE Trans. Commun.

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“…Without loss of generality, we will consider a normalized bandwith B = 1 in the following derivations. Even though the average capacity is known for most popular fading channels distributions (see [23] and the references therein), this is not the case for the SOSF channel. Substituting f γ (γ) by (10) in (35), the capacity is obtained in a double integral form.…”

Section: B Application Example: Average Capacitymentioning

confidence: 99%

Statistical Characterization of Second-Order Scattering Fading Channels

López-Fernández

López‐Martínez

2018

IEEE Trans. Veh. Technol.

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We present a new approach to the statistical characterization of the second order scattering fading (SOSF) channel model, which greatly simplifies its analysis. Exploiting the unadvertised fact that the SOSF channel can be seen as a continuous mixture of Rician fading channels, we obtain expressions for its probability density function and cumulative density function that are numerically better-behaved than those available in the literature. Our approach allows for obtaining new results for the SOSF model, such as a closed-form expression for its momentgenerating function, as well as the characterization of the average channel capacity. Relevantly, and somehow counterintuitively, we observe that in the presence of a strong line-of-sight (LOS) component, the channel capacity of a LOS plus double-Rayleigh scattered diffuse component is larger than its LOS plus Rayleigh (i.e Rician-like) counterpart.

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“…The model considers the received signal as formed by one or several groups of multipath signals, each being able to have a main component whose amplitude can fluctuate. It includes Rayleigh, Rice, Rice shadowed, Nakagami-m, κ-µ and η-µ as particular cases [6,7]. Changing its fading parameters (κ, µ and m), the model can study non-line-of-sight scenarios (NLoS) and line-of-sight scenarios (LoS) with different characteristics.…”

Section: Introductionmentioning

confidence: 99%

Understanding the Impact of Line-of-Sight in the Ergodic Spectral Efficiency of Cellular Networks

García-Corrales

Martín-Vega

López‐Martínez

et al. 2018

2018 IEEE 23rd International Workshop on Computer Aided Modeling and Design of Communication Links and Networks (CAMAD)

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In this paper we investigate the impact of lineof-sight (LoS) condition in the ergodic spectral efficiency of cellular networks. To achieve this goal, we have considered the κ-µ shadowed model, which is a general model that provides an excellent fit to a wide set of propagation conditions. To overcome the mathematical complexity of the analysis, we have split the analysis between large and small-scale effects. Building on the proposed framework, we study a number of scenarios that range from heavily-fluctuating LoS to deterministic-LoS. Finally, we shed light on the interplay between fading severity and spectral efficiency by means of the amount of fading.Index Terms-Wireless communications, average spectral efficiency, κ-µ shadowed fading model, amount of fading

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The $\kappa$– $\mu$ Shadowed Fading Model: Unifying the $\kappa$– $\mu$ and $\eta$– $\mu$ Distributions

Cited by 90 publications

References 27 publications

Error Vector Magnitude Analysis in Generalized Fading With Co-Channel Interference

Error Vector Magnitude Analysis in Generalized Fading With Co-Channel Interference

Statistical Characterization of Second-Order Scattering Fading Channels

Understanding the Impact of Line-of-Sight in the Ergodic Spectral Efficiency of Cellular Networks

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