A generative MIMO channel model: Encompassing single satellite and satellite diversity cases

Carrie, G.; Pérez-Fontán, F.; Lacoste, F.; Lemorton, J.

doi:10.1109/eucap.2012.6206627

Cited by 6 publications

(12 citation statements)

References 15 publications

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“…Since dual polarization MIMO configurations were included in these experiments, the SISO model has been extended into a MIMO version. This MIMO extension is an upgrade of the approach presented in [4].…”

Section: Introductionmentioning

confidence: 97%

“…A first version was published in [3], still based on the same experimental datasets as the 3-state Markov (with measurements carried out in the 90's). Then, upgraded versions of the enhanced 2-state model ( [4], [5] and [6]) have been developed using recent L-, S-band and C-band experiments with better dynamic ranges and/or longer travelled distances [4] [7]. In 2011 and 2012, the France Space Agency (CNES) has carried out new measurements at 2.2 GH and 3.8 GHz for various elevation angles, environments and antennas configurations.…”

Section: Introductionmentioning

confidence: 99%

“…In 2011 and 2012, the France Space Agency (CNES) has carried out new measurements at 2.2 GH and 3.8 GHz for various elevation angles, environments and antennas configurations. These new experimental datasets have been used to slightly improve the enhanced 2-state model presented in [4] and [5] and to fully parameterize it. Since dual polarization MIMO configurations were included in these experiments, the SISO model has been extended into a MIMO version.…”

Section: Introductionmentioning

confidence: 99%

“…During this activity, additional features were introduced with respect to [4] and [5] and the model outputs have been verified for various configurations in terms of fading, Rice factor, level crossing late (LCR) and average fade duration (AFD) statistics.…”

Section: Introductionmentioning

confidence: 99%

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SISO and MIMO enhanced 2-state modelling of the Land Mobile satellite channel for various frequencies, environments and elevation angles

Lacoste

Villacieros

Prieto-Cerdeira

et al. 2014

The 8th European Conference on Antennas and Propagation (EuCAP 2014)

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The design and assessment of air interfaces for modern Land Mobile satellite systems between 1 and 4 GHz require the use of reference generative propagation channel models. Among possible generative modeling approaches, the empirical stochastic method has been widely used in the past two decades for its simplicity, reduced number of input parameters and efficiency in terms of computation time. A model based on 3-state Markov chain approach for SISO links in particular was used in various standardization groups whereas available input parameters generally were affected by measurements biases and uncertainties. Recently, an evolution of such model with more flexibility, the so-called enhanced 2-state SISO model, has been developed. New experimental datasets collected at 2 and 4 GHz in different environments and for various elevation angles have been used to slightly improve this initial enhanced 2-state model and to fully parameterize it. A dual polarization MIMO extension has also been developed from these new experimental results. This paper aims at presenting the upgraded enhanced 2-state channel model and at providing testing results.Index Terms-SISO, MIMO, Land Mobile Satellite, generative chanel model.

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Section: Introductionmentioning

confidence: 97%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

SISO and MIMO enhanced 2-state modelling of the Land Mobile satellite channel for various frequencies, environments and elevation angles

Lacoste

Villacieros

Prieto-Cerdeira

et al. 2014

The 8th European Conference on Antennas and Propagation (EuCAP 2014)

View full text Add to dashboard Cite

show abstract

“…This has a strong influence on the corresponding satellite-to-Earth propagation channel as, based on user surroundings, the signal may be shadowed differently determined by the direction of the incoming signal. To predict such behavior, a number of various propagation channel models for different scenarios can be found in the literature, see for example [1][2][3][4][5][6][7][8]. Generally, such models need to be based on available experimental data; however, obtaining suitable experimental data is demanding.…”

Section: Introductionmentioning

confidence: 99%

First-Order Statistics Prediction for a Propagation Channel of Arbitrary Non-Geostationary Satellite Orbits

Kvičera¹,

Pechač²

2015

RADIOENGINEERING

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MIMOSA–a dual approach to detailed land mobile satellite channel modeling

Burkhardt

Eberlein

Jaeckel

et al. 2014

Satell Commun Network

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As multiple-input-multiple-output (MIMO) transmission technologies are common in terrestrial mobile communications and getting attention for mobile broadcasting satellite systems, the need for a comprehensive MIMO channel model for the dual-polarized land mobile satellite (LMS) channel arises. In the course of the Characterisation of the MIMO Channel for Mobile Satellite Systems (MIMOSA) project, two complementary modeling approaches have been developed that form a dual model. They provide a scalable modeling solution, which permits a user selectable level of simulation complexity and detail. The models have been evaluated by comparing their results with data gathered from the extensive field trials carried out within the MIMOSA project. This paper describes the dual wideband-modeling and narrowband-modeling approaches, provides examples of the usage and provides some evaluation results.

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A generative MIMO channel model: Encompassing single satellite and satellite diversity cases

Cited by 6 publications

References 15 publications

SISO and MIMO enhanced 2-state modelling of the Land Mobile satellite channel for various frequencies, environments and elevation angles

SISO and MIMO enhanced 2-state modelling of the Land Mobile satellite channel for various frequencies, environments and elevation angles

First-Order Statistics Prediction for a Propagation Channel of Arbitrary Non-Geostationary Satellite Orbits

MIMOSA–a dual approach to detailed land mobile satellite channel modeling

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