Channel modelling based on N-state Markov chains for satcom systems simulation

Castanet, Laurent; Deloues, Thierry; Lemorton, J.

doi:10.1049/cp:20030030

Cited by 23 publications

(21 citation statements)

References 2 publications

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“…To be able to generate attenuation time series with an N-state Markov model, the states have to represent attenuation levels, so there are many states according to the number of attenuation levels [2], [11]. In the considered time discrete model each state represents an attenuation level with 0.05 dB resolution, so the model is discrete in states as well.…”

Section: The Considered N-state Markov Chain Modelmentioning

confidence: 99%

General N-State Markov Model for Rain Attenuation Time Series Generation

Héder

Bito

2007

Wireless Pers Commun

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Nowadays and mainly in the near future the wireless point-to-point or pointto-multipoint connections are operating in high frequency. These systems are applied in feeder network for future cellular mobile communication systems or BFWA (Broadband Fixed Wireless Access) networks. Besides the obvious benefits of the applied high carrier frequency there is a significant disadvantage, the considerable attenuation caused by precipitation, especially by rain. For accurate planning of the proposed microwave links the statistics of the expectable rain attenuation is highly important. Applying our previous research results the this work provides a general N-state Markov Chain model to generate rain attenuation time series on a proposed microwave link according to the link parameters. The first and second order rain attenuation statistics of the generated time series can be derived directly from the Markov model parameters, so the N-state Markov model can be applied for prediction of rain attenuation on the proposed link even in the early planning phase. With our proposed model very accurate realisation of the physical fade process can be achieved.

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Section: The Considered N-state Markov Chain Modelmentioning

confidence: 99%

General N-State Markov Model for Rain Attenuation Time Series Generation

Héder

Bito

2007

Wireless Pers Commun

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“…This allows the channel to be used more efficiently, since the power and the rate can be allocated to take advantage of favorable conditions. Those methods that counteract the atmospheric propagation losses and permit link adaptation are referred to as FMT (Fade Mitigation Techniques) [1]. The basic idea behind adaptive transmission is to maintain the bit error rate, and therefore the quality of service, during a fade event by adapting transmission parameters to the propagation conditions; parameters which can be adapted are either the transmitted power, the transmission symbol rate, the constellation size, the coding rate/scheme, the space diversity, or any combination of them.…”

Section: Introductionmentioning

confidence: 99%

Dynamic uplink frame optimization with ACM in DVB-RCS2 satellite networks

Pietrabissa

Fiaschetti

2012

2012 IEEE First AESS European Conference on Satellite Telecommunications (ESTEL)

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In current generation of satellite networks, modulation and coding schemes can be dynamically changed in real-time to face different link conditions. Therefore, the link budget is no more required to be computed under the worst-case, with relevant advantages in terms of efficiency. The new DVB-RCS2 standard extends the dynamic modulation and coding to the return link: by using different modulation and coding schemes within the uplink frame, the terminals experiencing good link conditions transmit at very high bitrates, while the terminals experiencing fade events transmit at lower bitrates. This paper addresses the problem of optimizing the uplink frame modulation and coding schemes based on the current link conditions experienced by the terminals and on their transmission capacity requirements. The problem is formulated as an Integer Program and an efficient Linear Program approximation is proposed. Simulation results validate the proposed approach

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“…Since the uplink is more affected by attenuation than the downlink (because it generally operates at a higher frequency), the downlink attenuation is predicted and then scaled to the uplink frequency in order to estimate the future propagation conditions of the uplink. Various prediction models have been proposed, such as a linear regression (Dossi, 1990), a first order stochastic equation (Manning, 1990(Manning, , 1991, Markov chains (Castanet et al, 2003;Fiebig, 2002), an adaptive linear filter (Grémont et al, 1999), a neural networks (Chambers and Otung, 2005) or a model based on the fade slope ( Van de Kamp, 2002). A comparison was performed with Olympus 20 GHz data (Sect.…”

Section: Introductionmentioning

confidence: 99%

Short-term prediction of rain attenuation level and volatility in Earth-to-Satellite links at EHF band

Montera¹,

Mallet²,

Barthès³

et al. 2008

Nonlin. Processes Geophys.

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Abstract. This paper shows how nonlinear models originally developed in the finance field can be used to predict rain attenuation level and volatility in Earth-to-Satellite links operating at the Extremely High Frequencies band (EHF,. A common approach to solving this problem is to consider that the prediction error corresponds only to scintillations, whose variance is assumed to be constant. Nevertheless, this assumption does not seem to be realistic because of the heteroscedasticity of error time series: the variance of the prediction error is found to be time-varying and has to be modeled. Since rain attenuation time series behave similarly to certain stocks or foreign exchange rates, a switching ARIMA/GARCH model was implemented. The originality of this model is that not only the attenuation level, but also the error conditional distribution are predicted. It allows an accurate upper-bound of the future attenuation to be estimated in real time that minimizes the cost of Fade Mitigation Techniques (FMT) and therefore enables the communication system to reach a high percentage of availability. The performance of the switching ARIMA/GARCH model was estimated using a measurement database of the Olympus satellite 20/30 GHz beacons and this model is shown to outperform significantly other existing models.The model also includes frequency scaling from the downlink frequency to the uplink frequency. The attenuation effects (gases, clouds and rain) are first separated with a neural network and then scaled using specific scaling factors. As to the resulting uplink prediction error, the error contribution of the frequency scaling step is shown to be larger than that of the downlink prediction, indicating that further study should focus on improving the accuracy of the scaling factor.

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Channel modelling based on N-state Markov chains for satcom systems simulation

Cited by 23 publications

References 2 publications

General N-State Markov Model for Rain Attenuation Time Series Generation

General N-State Markov Model for Rain Attenuation Time Series Generation

Dynamic uplink frame optimization with ACM in DVB-RCS2 satellite networks

Short-term prediction of rain attenuation level and volatility in Earth-to-Satellite links at EHF band

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