Probability Distribution of Rician &lt;formula formulatype="inline"&gt; &lt;tex Notation="TeX"&gt;$K$&lt;/tex&gt;&lt;/formula&gt;-Factor in Urban, Suburban and Rural Areas Using Real-World Captured Data

Zhu, S.; Ghazaany, T. S.; Jones, S. M. R.; Abd-Alhameed, R. A.; Noras, J. M.; Buren, Tyler Van; Wilson, James P.; Suggett, T.; Marker, S.

doi:10.1109/tap.2014.2318072

Cited by 65 publications

(37 citation statements)

References 12 publications

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“…Therefore, the relative error of RMSE is about 1/16. It shows that (14) introduces about 16 times smaller error in relation to (10). This fact justifies the adaptation of (14) to approximate the relationship between r h and j for the von Mises PDF.…”

Section: Adaptation Of the Empirical Models To Propagation Scenariossupporting

confidence: 55%

“…Part I of this paper [1] is focused on a comparative analysis of empirical and geometrical (theoretical) models of the probability density function (PDF) of azimuth AOA (AAOA) for different environmental conditions. Empirical models are based on standard distributions such as Gaussian [2][3][4][5], Laplacian [2,3,[6][7][8][9][10][11][12], logistic [13][14][15][16], and von Mises [3,[17][18][19][20][21], which are being modified due to limited support of PDF of AAOA. The theoretical models are defined by the geometrical structures that describe the spatial position of scattering elements.…”

Section: Introductionmentioning

confidence: 99%

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Empirical Models of the Azimuthal Reception Angle—Part II: Adaptation of the Empirical Models in Analytical and Simulation Studies

Ziółkowski

Kelner

2016

Wireless Pers Commun

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This paper focuses on modeling of the statistical reception angle properties that are the result of the environmental influence on transmitted signals. Numerous measurements have shown that the statistical properties of angle of arrival (AOA) significantly depend on the type of propagation environment. In practice, this means that in the analytical and simulation studies, the use of statistical models of AOA required their adaptation to propagation conditions in research scenario. Despite the large number of papers that are devoted to the AOA modeling, the method of fitting models to the environment is not presented in any of the publications. This paper fills this gap. For the assessment of the propagation properties and environment type classification, the basis is the rms delay spread (DS). Therefore, the presented method of the model adaptation to the environment type consists of determining the relationship between the model parameter and DS of environment. Here, the probability density function (PDF) of models such as the modified Gaussian, modified Laplacian, modified logistic, and von Mises distribution are considered as the statistical models of azimuth AOA. For seven different propagation environments, the measurement results are used as a reference data. A comparative analysis shows that the modified Laplacian PDF provides the smallest error fit to measurement data. However, in theoretical analysis and simulation studies, other empirical models can be used due to relatively low approximation errors. The presented results are the basis for the adaptation error assessment of the empirical model for any of the research scenario.

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Section: Adaptation Of the Empirical Models To Propagation Scenariossupporting

confidence: 55%

Section: Introductionmentioning

confidence: 99%

Empirical Models of the Azimuthal Reception Angle—Part II: Adaptation of the Empirical Models in Analytical and Simulation Studies

Ziółkowski

Kelner

2016

Wireless Pers Commun

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“…3(b). The mean μ and variance 2 of the normal and logistic distributions follow the measurement data from urban, suburban, and rural areas [4], as shown in Fig. 3(a).…”

Section: Numerical Resultsmentioning

confidence: 87%

“…The joint probability density function (PDF) and joint cumulative distribution function (CDF) of the Rician distributed instantaneous signal-to-noise ratio (SNR) i;j and the random K-factor is denoted as p i;j ð i;j ; K i;j Þ and F i;j ð i;j ; K i;j Þ ¼ F i;j ð i;j jK i;j Þp K i;j ðK i;j Þ, respectively. The PDF of K-factor p K i;j ðK i;j Þ is represented by either logistic distribution p log ðKÞ or normal distribution p nor ðKÞ, which are found to be well-fit models in [4].…”

Section: System Modelmentioning

confidence: 99%

“…In this paper, we study a TW relaying transmission network, where the LF relaying is performed at the relay node, referred to as (TW-LF) relaying. The channels experience the Rician fading with random K-factor following the probability distributions estimated in [4] based on measurement data. The outage probability upper bound of the TW-LF relaying is theoretically derived by a multi-fold integral over the achievable rate region determined by the theorem of source coding with side information.…”

Section: Introductionmentioning

confidence: 99%

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Performance analysis for two-way lossy-forward relaying with random Rician K-factor

Qian

Juntti

et al. 2017

IEICE ComEX

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A novel lossy-forward (LF) cooperative communication scheme based on the decode-and-forward (DF) protocol allowing source-relay link errors is proposed recently. The LF relaying scheme always allows the relay to forward the decoded information to the destination even though it may contain errors. The knowledge of the correlation between received information sequences is exploited in the decoding process at the destination to improve the system performance. In this paper, we derive exact expressions of the outage probability upper bound for a two-way LF relay system over Rician fading channels with random K-factor. The K-factor follows empirical distributions derived from measurement data. It is found that the two-way relaying with LF is superior to that with DF scheme in terms of the outage performance. Keywords: outage probability, two-way relaying, lossy-forward, random K-factor, multiple access channel (MAC) Classification: Wireless Communication Technologies References[1] M. Chen and A. Yener, "Power allocation for F/TDMA multiuser two-way relay networks," IEEE Trans.

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Empirical Models of the Azimuthal Reception Angle—Part I: Comparative Analysis of Empirical Models for Different Propagation Environments

Ziółkowski

Kelner

2016

Wireless Pers Commun

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Statistical properties of the reception angle have a significant impact on the choice of the antenna system patterns and decide on the received signal-processing methods. For angle of arrival in azimuth plane, comparative analysis of the empirical models and the approximation error evaluation are the purpose of this paper. Here, the presented analysis is focused on models such as the von Mises, modified Gaussian, modified Laplacian, and modified logistic. For each model, the approximation accuracy is determined with respect to measurement data for seven different propagation scenarios. The measures such as the least-squares error, difference of standard deviations, Kolmogorov-Smirnov statistic, and Cramer-von Mises statistic are used for evaluation of the approximation errors. Comparative analysis for four empirical models, differentiation of propagation environments, multi-criterial evaluation of approximation errors in significant degree fill a gap in the previous analysis presented in the literature. The obtained results show that the empirical models provide a better fit to the measurement data than the geometrical models, and the smallest errors of approximation are for the modified Laplacian and logistic distributions.

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Probability Distribution of Rician <formula formulatype="inline"> <tex Notation="TeX">$K$</tex></formula>-Factor in Urban, Suburban and Rural Areas Using Real-World Captured Data

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Cited by 65 publications

References 12 publications

Empirical Models of the Azimuthal Reception Angle—Part II: Adaptation of the Empirical Models in Analytical and Simulation Studies

Empirical Models of the Azimuthal Reception Angle—Part II: Adaptation of the Empirical Models in Analytical and Simulation Studies

Performance analysis for two-way lossy-forward relaying with random Rician K-factor

Empirical Models of the Azimuthal Reception Angle—Part I: Comparative Analysis of Empirical Models for Different Propagation Environments

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