Extended two-state narrowband LMS propagation model for S-Band

Arndt, Daniel; Heyn, Thomas; Konig, Jonas; Ihlow, Alexander; Heuberger, Albert; Prieto-Cerdeira, R.; Eberlein, Ernst

doi:10.1109/bmsb.2012.6264301

Cited by 18 publications

(22 citation statements)

References 7 publications

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“…By analysing the extensive SDARS measurement data in terms of slow-and fast signal variations within MiLADY, some modifications of the two-state model from [4] are indicated. Recently, modifications were proposed in [15]. A validation of these new concepts for a multi-satellite model is topic of ongoing work.…”

Section: Discussionmentioning

confidence: 99%

State modelling of the land mobile propagation channel for dual-satellite systems

Arndt

Ihlow

Heyn

et al. 2012

J Wireless Com Network

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The quality of service of mobile satellite reception can be improved by using multi-satellite diversity (angle diversity). The recently finalised MiLADY project targeted therefore on the evaluation and modelling of the multi-satellite propagation channel for land mobile users with focus on broadcasting applications. The narrowband model combines the parameters from two measurement campaigns: In the U.S. the power levels of the Satellite Digital Audio Radio Services were recorded with a high sample rate to analyse fast and slow fading effects in great detail. In a complementary campaign signals of Global Navigation Satellite Systems (GNSS) were analysed to obtain information about the slow fading correlation for almost any satellite constellation. The new channel model can be used to generate time series for various satellite constellations in different environments. This article focuses on realistic state sequence modelling for angle diversity, confining on two satellites. For this purpose, different state modelling methods providing a joint generation of the states 'good good', 'good bad', 'bad good' and 'bad bad' are compared. Measurements and re-simulated data are analysed for various elevation combinations and azimuth separations in terms of the state probabilities, state duration statistics, and correlation coefficients. The finally proposed state model is based on semi-Markov chains assuming a log-normal state duration distribution.

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Section: Discussionmentioning

confidence: 99%

State modelling of the land mobile propagation channel for dual-satellite systems

Arndt

Ihlow

Heyn

et al. 2012

J Wireless Com Network

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“…By using the Loo generator according to [6], Loo distibuted samples with various Loo parameter triplets were generated. In the following re-estimation, it was found that the algorithm converges to the correct Loo triplet in most cases, depending on the set of initial values.…”

Section: Estimation Algorithm On Synthetic Datamentioning

confidence: 99%

“…2. Generic model architecture based on [6] for generating timeseries of the land mobile satellite (LMS) propagation channel, extended for two satellites. A correlation is considered in each stage of the model.…”

Section: Introductionmentioning

confidence: 99%

Estimation of fading parameter correlation for modeling the land mobile satellite channel

Konig

Arndt

Ihlow

et al. 2012

IEEE International Symposium on Broadband Multimedia Systems and Broadcasting

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This paper addresses the correlation of fading signal parameters for dual-satellite land mobile satellite (LMS) channels. We use Loo's model to describe the slow and fast variations that occur due to varying shadowing conditions and multipath fading, respectively. Loo's parameters (mean power of direct signal component, standard deviaton of direct signal component, and average multipath power) are estimated segment-by-segment from fading signals of two simultaneously measured geostationary satellites using a curve-fitting approach. The parameter correlation between the signals of the two satellites is investigated. A significant correlation is found in the mean power of the direct signal components in some environments, when both satellites are shadowed or blocked by obstacles

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“…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%

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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Extended two-state narrowband LMS propagation model for S-Band

Cited by 18 publications

References 7 publications

State modelling of the land mobile propagation channel for dual-satellite systems

State modelling of the land mobile propagation channel for dual-satellite systems

Estimation of fading parameter correlation for modeling the land mobile satellite channel

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

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