Field trial with a GSM/DCS1800 smart antenna base station

Kuchart, A.; Taferner, Manfred; Tangemann, M.; Hoek, Cornelis

doi:10.1109/vetecf.1999.797037

Cited by 5 publications

(7 citation statements)

References 3 publications

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“…• Downlink beamforming. Knowledge of the directions and average powers of the multipath components is used for the downlink of FDD systems with smart antennas [23]. Signals propagating via different clusters can be used for "beam diversity".…”

Section: B Influence On System Designmentioning

confidence: 99%

Clustering of scatterers in mobile radio channels-evaluation and modeling in the COST259 directional channel model

Asplund

Molisch²,

Steinbauer³

et al.

2002 IEEE International Conference on Communications. Conference Proceedings. ICC 2002 (Cat. No.02CH37333)

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We analyze the clustering of scatterers in mobile radio channels, i.e, the fact that scatterers are usually not located uniformly in the whole coverage area, but tend to occur in clusters. While this has been recognized for some time, a realistic model for this phenomenon has been lacking up to now. We first analyze measurements to extract the distribution of the number of observed clusters. We then present a model that reflects not only this distribution, but also reproduces the appearance and disappearance of clusters as the mobile station moves through the cell. Our approach has been adopted as an important part of the COST259 Directional Channel Model, a standard model for directional mobile radio channels. Finally, we discuss the implications of the model for the system performance of CDMA and SDMA systems.

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Section: B Influence On System Designmentioning

confidence: 99%

Clustering of scatterers in mobile radio channels-evaluation and modeling in the COST259 directional channel model

Asplund

Molisch²,

Steinbauer³

et al.

2002 IEEE International Conference on Communications. Conference Proceedings. ICC 2002 (Cat. No.02CH37333)

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“…Compared to [20], here the set of measurement results is limited to seven scenarios that are described in [21,[42][43][44][45][46]. Out of all unimodal, empirical PDFs that are included in [20], the measurement data from [47] are not contained in this paper. For this case, the correction changing position of transmitter (Tx) is not included in AAOA averaging procedure.…”

Section: Measurement Scenariosmentioning

confidence: 99%

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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“…For each scenario, the empirical data is not a uniform set. For [1,28,33] scenarios, PDS is the basis for DBMM parameters, so all of them take statistically constant values. PDP is used with respect to [26,29,30,34] scenarios.…”

Section: Verification and Comparison Of Modelsmentioning

confidence: 99%

“…Therefore, for these scenarios, the same parameter values of other models are adopted in [23]. Also, in [28,33], the propagation properties of environments are not described. For these scenarios, DBMM parameters are defined on the basis of descriptions of the measurement conditions.…”

Section: Verification and Comparison Of Modelsmentioning

confidence: 99%

Estimation of the Reception Angle Distribution Based on the Power Delay Spectrum or Profile

Ziółkowski

Kelner

2015

International Journal of Antennas and Propagation

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The paper presents an estimation of the reception angle distribution based on temporal characteristics such as the power delay spectrum (PDS) or power delay profile (PDP). Here, we focus on such wireless environment, where the propagation phenomenon predominates in azimuth plane. As a basis to determine probability density function (PDF) of the angle of arrival (AOA), a geometrical channel model (GCM) in form of the multielliptical model for delayed scattering components and the von Mises’ PDF for local scattering components are used. Therefore, this estimator is called the distribution based on multielliptical model (DBMM). The parameters of GCM are defined on the basis of the PDS or PDP and the relative position of the transmitter and the receiver. In contrast to the previously known statistical models, DBMM ensures the estimation PDF of AOA by using the temporal characteristics of the channel for differing propagation conditions. Based on the results of measurements taken from the literature, DBMM verification, assessment of accuracy, and comparison with other models are shown. The results of comparison show that DBMM is the only model that provides the smallest least-squares error for different environments.

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Field trial with a GSM/DCS1800 smart antenna base station

Cited by 5 publications

References 3 publications

Clustering of scatterers in mobile radio channels-evaluation and modeling in the COST259 directional channel model

Clustering of scatterers in mobile radio channels-evaluation and modeling in the COST259 directional channel model

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

Estimation of the Reception Angle Distribution Based on the Power Delay Spectrum or Profile

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