Frédéric Lacoste

Development and validation of time-series synthesizers of rain attenuation for Ka-band and Q/V-band satellite communication systems

The aim of this paper is to present recent developments in terms of propagation time-series synthesizers, carried out in the framework of the ESA study 16865/03/NL/EC Development of propagation models for telecommunication satellite systems (ONERA Final Report RF 4/07757/DEMR, 2004). The paper is composed of three parts: a review of the initial requirements related to propagation time series for system performance simulation, a description of a collection of rain attenuation time-series synthesizers and of their related input parameters, and a comparative analysis of the output characteristics of these time-series synthesizers as compared with experimental data collected during the OLYMPUS and ITALSAT propagation experiments.

A Large-Scale Space-Time Stochastic Simulation Toolof Rain Attenuation for the Design and Optimization of Adaptive Satellite Communication Systems Operating between 10 and 50 GHz

The design and optimization of propagation impairment techniques for space telecommunication systems operating at frequencies above 20 GHz require a precise knowledge of the propagation channel both in space and time. For that purpose, space-time channel models have to be developed. In this paper the description of a model for the simulation of long-term rain attenuation time series correlated both in space and time is described. It relies on the definition of a stochastic rain field simulator constrained by the rain amount outputs of the ERA-40 reanalysis meteorological database. With this methodology, realistic propagation conditions can be generated at the scale of satellite coverage (i.e., over Europe or USA) for many years. To increase the temporal resolution, a stochastic interpolation algorithm is used to generate spatially correlated time series sampled at 1 Hz, providing that way valuable inputs for the study of the performances of propagation impairment techniques required for adaptive SatCom systems operating at Ka band and above.

A new ‘event‐on‐demand’ synthesizer of rain attenuation time series at Ku‐, Ka‐ and Q/V‐bands

To develop and test real-time fade mitigation techniques control algorithms, propagation time series are needed. An alternative to using real data collected from propagation experiments is to generate typical fading time-series making use of climatological characteristics as well as geometrical and radio-electrical parameters of the link. The objective of this paper is to present a rain attenuation time-series synthesizer and able to generate events on demand. The model is based on an enhanced version of the Maseng–Bakken stochastic model. In the first part of this paper, the basic principles of the enhanced Maseng–Bakken model are recalled and the parameterization of this channel model is discussed for temperate European climates. Then, the theoretical bases of the Lacoste–Carrie ‘event-on-demand’ model and its validation constitute the second part of this paper. The enhanced Maseng–Bakken model is fully stochastic, whereas the Lacoste-Carrie ‘event-on-demand’ one offers the possibility to command the maximum attenuation level and the duration of the synthesized event. Copyright

Classical and On -Demand Rain Attenuation Time Series Synthesis: Principle and Applications

To develop and test real -time Fade Mitigation Techniques control algorithms, propagation time series are needed. An alternative to using real data collected from propagation experiments is to gen erate typical fading time -series making use of climatological characteristics as well as geometrical and radio -electrical parameters of the link. These dynamic channel models must be as global as possible to be used for all the possible link characteristic s. The design of transmission links for interactive SatCom systems can be done in three steps. The first one is based on a worst case link budget requiring an exceeded value for a given percentage of time. For this purpose, ITU -R models can be used. The se cond step consists in the survey of the FMT control loop behavior in some typical cases of impairments. The synthesis of such attenuation events implies a strong need for dynamic channel models in which users can command some events characteristics. It mus t concern in priority the duration of the synthesized rain attenuation event and/or its maximum value. Such channel models are said to produce “on -demand” events. And the last step is the global assessment of the capacity and of the availability of the who le communications system. For such exhaustive studies, time series synthesizers able to reproduce the channel dynamic behavior on a long -term basis (including periods of no rain) are needed. For those reasons, two types of time series synthesizers have bee n developed relying on the same theoretical bases. The first one is directly an improved version of the Maseng -Bakken model which does not produce “on -demand” rain attenuation events. The second channel model enables to command the maximum level and the du ration of rain attenuation events to synthesize. This model can also be used to complete channel models that are not able to produce one sample every second.

Validation of rain attenuation time series synthesizers for temperate area - on the enhanced Maseng-Bakken model

To develop and test real time fade mitigation techniques control algorithms, propagation time series are needed. An alternative to using real data collected from propagation experiments is to generate typical fading time series making use of climatological characteristics as well as geometrical and radio-electrical parameters of the link. The aim of the study presented in this paper is to validate time-series synthesisers relying on an enhanced Maseng-Bakken model for temperate areas. In the first part of this paper, the basic principles of the Maseng-Baken model are recalled and the parameterisation of this channel model is discussed for temperate climates. Then, Ka band beacon data collected in European and in North-American areas are used: on the one hand to retrieve the input parameters of the channel models and on the other hand to test them with respect to long-term statistics. The results of this testing analysis constitute the second part of this paper.

Land mobile satellite dual polarized MIMO channel along roadside trees: Modeling and performance evaluation

We present a novel physical-statistical, generative model for the land mobile satellite (LMS), dual polarized, multiple-input-multiple-output (MIMO) channel along tree-sided roads. Said model is parameterized by means of a physical model based on the multiple scattering theory (MST) which accounts for the signal attenuation and scattering by trees. Moreover, finite-difference time-domain (FDTD) electromagnetic computations were performed to characterize the scattering pattern of an isolated tree, and to calculate the MIMO shadowing correlation matrix required by the model, and not provided by MST. This modeling framework also encompasses the single-input-multiple-output (SIMO)/space diversity case. To illustrate the capabilities of the developed model, time series were generated and used in system performance calculations. The obtained results give an insight into the advantages of dual polarized MIMO and SIMO/space diversity techniques in these very frequent scenarios and may help service providers in evaluating the technical feasibility of such systems.

Inter-annual variability, risk and confidence intervals associated with propagation statistics. Part I: theory of estimation

SUMMARY This set of two companion papers aims at providing a statistical framework to quantify the inter-annual variability observed on the statistics of rain attenuation or rainfall rate derived from Earth-space propagation measurements. This part I is more specifically devoted to the theoretical study of the variance of estimation of empirical complementary cumulative distribution functions (ECCDFs) derived from Earth-space rain attenuation or rainfall rate time series. To focus the analysis on the statistical variability but without loss of generality, synthetic rain attenuation time series are considered. A large variability on the ECCDFs, which depends on the duration of the synthetic data, is first put into evidence. The variance of estimation is then derived from the properties of the statistical estimator. The formulation is validated numerically, by comparison with the ECCDF variances derived from the synthetic data. The variance of the fluctuations around the CCDF is then shown to be dependent on the average of the correlation function of the time series, on the probability level and on the measurement duration. This variance of estimation is needed as a prerequisite in conjunction with the knowledge of the climatic variability to characterize the yearly fluctuations of propagation statistics computed from experimental time series. The extensions from simulations to experiments as well as the application to system planning are detailed in part II. Copyright

A Rain Attenuation Time-Series Synthesizer Based on a Dirac and Lognormal Distribution

In Recommendation ITU-R P.1853-1, a stochastic approach is proposed to generate long-term rain attenuation time series , including rain and no rain periods anywhere in the world. Nevertheless, its dynamic properties have been validated so far from experimental rain attenuation time series collected at mid-latitudes only. In the present paper, an effort is conducted to derive analytically the first- and second-order statistical properties of the ITU rain attenuation time-series synthesizer. It is then shown that the ITU synthesizer does not reproduce the first-order statistics (particularly the rain attenuation cumulative distribution function CDF), however, given as input parameters. It also prevents any rain attenuation correlation function other than exponential to be reproduced, which could be penalizing if a worldwide synthesizer that accounts for the local climatology has to be defined. Therefore, a new rain attenuation time-series synthesizer is proposed. It assumes a mixed Dirac-lognormal modeling of the absolute rain attenuation CDF and relies on a stochastic generation in the Fourier plane. It is then shown analytically that the new synthesizer reproduces much better the first-order statistics given as input parameters and enables any rain attenuation correlation function to be reproduced. The ability of each synthesizer to reproduce absolute rain attenuation CDFs given by Recommendation ITU-R P.618 is finally compared on a worldwide basis. It is then concluded that the new rain attenuation time-series synthesizer reproduces the rain attenuation CDF much better, preserves the rain attenuation dynamics of the current ITU synthesizer for simulations at mid-latitudes, and, if it proves to be necessary for worldwide applications, is able to reproduce any rain attenuation correlation function.

A large scale, high resolution channel model for propagation impairment techniques design and optimization

As the impairments due to rain on the propagation channel for frequency bands such as Ka or Q/V have to be compensated by adaptive fade mitigation techniques, optimized radio resource management needs to be implemented, which requires a coarse knowledge of spatio-temporal dynamic of the attenuation due to rain. In this paper a model able to emulate the space-time dynamic of the attenuation due to rain on a satellite coverage is presented. It consists of a stochastic model that is constrained by the outputs of a reanalysis model. The spatial resolution of the modeling is of 1 km and the temporal one of 0.1 h. A stochastic interpolation model is then used to get a temporal resolution of 1s more suitable to study fade dynamic.

Inter‐annual variability, risk and confidence intervals associated with propagation statistics. Part II: parameterization and applications

SUMMARY This set of two companion papers aims at providing a model for the inter-annual variability of earth-space propagation statistics and for the inherent risk and CIs. In part I, it was proposed to model the yearly variance σ² of empirical complementary CDFs so that where is the variance of estimation, the inter-annual climatic variance and p the long-term probability. Particularly, an analytical formulation of was derived and parameterized from synthetic rain attenuation data. Considering the statistical framework developed in part I, this part II is specifically devoted to the parameterization of the variance of estimation from experimental data of rain attenuation and rainfall rate. Then, a methodology to model and parameterize worldwide the inter-annual climatic variance is presented. The model of yearly variance of the empirical complementary CDFs is finally compared against yearly experimental variances derived from data collected worldwide. The knowledge of this variability is very useful for system design as it allows the risk on a required availability and associated with a given propagation margin to be quantified. Copyright