Channel Modeling for Multiple Satellite Broadcasting Systems

Milojević, Marko; Haardt, Martin; Eberlein, Ernst; Heuberger, Albert

doi:10.1109/tbc.2009.2030464

Cited by 23 publications

(31 citation statements)

References 17 publications

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“…• First-order Markov model [3] • Dynamic Markov model [9] • Semi-Markov model [10] In the following the main characteristics of these models are described.…”

Section: Channel State Models For Single-satellite Systemsmentioning

confidence: 99%

“…Results in [9,10] have shown that an exponential SDPDF is no accurate approximation for the LMS channel. Therefore, to improve the state duration modelling dynamic Markov chains were introduced [9].…”

Section: Dynamic Markov Modelmentioning

confidence: 99%

“…However, first-order Markov chains have limitations in state duration modelling, as their state durations follow an exponential distribution. Studies in [8][9][10] found that this condition does not hold for the LMS channel. Nevertheless, a correct state duration modelling is of high interest for the optimal configuration of physical layer and link layer parameters for modern broadcasting standards with long time interleaving (e.g.…”

Section: Introductionmentioning

confidence: 99%

“…for physical layer interleaver size, link layer protection time). Therefore, different concepts improving the state duration modelling were introduced: semi-Markov chains [10] and dynamic Markov chains [9]. For these approaches some exemplary parameters for the single-satellite reception are published.…”

Section: Introductionmentioning

confidence: 99%

“…The parameters are derived from the measurements for different modelling approaches assuming two states per satellite ('good' , 'bad'). Chosen models are: first-order Markov approach [7], semi-Markov approach [10], and dynamic Markov approach [9]. To assess the performance of these models, correlation coefficients, state probabilities and state duration statistics are gained from re-simulated state sequences and compared with the measurement data.…”

Section: Introductionmentioning

confidence: 99%

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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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“…• First-order Markov model [3] • Dynamic Markov model [9] • Semi-Markov model [10] In the following the main characteristics of these models are described.…”

Section: Channel State Models For Single-satellite Systemsmentioning

confidence: 99%

Section: Dynamic Markov Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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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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Additive statistical modelling of land mobile satellite channels in three-dimensional scattering environment

Hazra

Mitra

2012

IET Commun.

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A new channel model with additive complex envelope process for land mobile satellite channel is proposed. The two fading processes, small-scale fading and shadow fading, are represented with Nakagami-q and lognormal distribution, respectively. Exact analytical expressions of first-and second-order statistics are derived for the proposed model. For the purpose of normalisation of second-order statistics with respect to maximum Doppler frequency, a three-dimensional scattering model is taken. A special case of the authors' proposed channel model gives rise to a new distribution, 'extended Nakagami-q distribution', and the same is reported with its statistics. The dependence of second-order statistics on different parameters is analysed with the computed results obtained from derived expressions. The results computed from the analytical expressions are also in good resemblance with the corresponding measurement results in a suburban propagation environment.

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Channel Modeling for Satellite Communication Channels at Q-Band in High Latitude

et al. 2019

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This paper proposes a three-dimensional (3D) channel model for satellite communications at Q-band in a high latitude, including the path loss, shadowing, and small-scale fading. The shadowing effect is modelled by a Markov chain. The three states in the Markov chain are separated by the threshold of the received power level for the link budget and system optimization. The probability density function (PDF) of shadowing amplitude is modelled by a mixture of two Gaussian distributions with parameters obtained by the expectation-maximum (EM) algorithm. The small-scale fading is represented by a 3D geometrybased stochastic model (GBSM) where scatterers are located on the spherical surface of a hemisphere. The movement of the receiver and the Rician factor influenced by environment scattering are considered. Statistical properties including the local temporal autocorrelation function (ACF) and Wigner-Ville spectrum are derived. The satellite communication channel measurement at Q-band is conducted on the campus of Heriot-Watt University (HWU) in Edinburgh, UK. The parameters of our proposed channel model are estimated by the measurement data. Numerical and simulation results demonstrate that our proposed channel model has the ability to reproduce main statistical properties which are also consistent well with the corresponding theoretical and measurement results.

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Channel Modeling for Multiple Satellite Broadcasting Systems

Cited by 23 publications

References 17 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

Additive statistical modelling of land mobile satellite channels in three-dimensional scattering environment

Channel Modeling for Satellite Communication Channels at Q-Band in High Latitude

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