Statistical methods for joint antenna-radio channel modelling

Abstract :

The description of the electromagnetic behavior of antennas needs a large amount of data to be complete, since it requires complex numbers for the radiated far field in all possible directions and polarizations, for all frequencies of interest and all antenna elements in case of arrays or multiport antennas, plus the full impedance matrix. In addition, since most of the time the radio channel linking the transmitting and receiving antennas in a wireless communication is not in free space, many propagation effects are involved and result in the particularities of the received signals. Finally, while it is often designed and measured in nearly ideal conditions (e.g. anechoic chamber) an antenna is rarely used in emptiness and its close environment does impact its performance, sometimes dramatically. While strong close disturbers can be taken into account at the design phase (such as a casing or a human head), variations in the effective impact of such disturbers can take place, which to some extent can unpredictably affect the antenna characteristics. Deterministic methods can hardly take into account all the variabilities that occur in real life and would be much too expensive to implement and to use. The natural approach, widely practiced in other domains, is to resort to statistical descriptions, based on metamodels able to represent these variabilities with a limited number of parameters while achieving an adequate trade-off between accuracy and simplicity. The presentation will address these issues for joint antenna-channel modelling, giving some examples about the development and use of such methods.

Type de document :
Communication dans un congrès
RINEM 2018, Sep 2018, Cagliari, Italy. RINEM 2018, 2018
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Soumis le : vendredi 17 août 2018 - 13:05:57
Dernière modification le : dimanche 19 août 2018 - 01:08:45


  • HAL Id : hal-01857792, version 1


Alain Sibille. Statistical methods for joint antenna-radio channel modelling. RINEM 2018, Sep 2018, Cagliari, Italy. RINEM 2018, 2018. 〈hal-01857792〉



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