PCE-BASED APPROACH TO WORST-CASE SCENARIO ANALYSIS IN WIRELESS TELECOMMUNICATION SYSTEMS

In the paper, we present a novel PCE-based approach for the effective analysis of worstcase scenario in a wireless telecommunication system. Usually, in such analysis derivation of polynomial chaos expansion (PCE meta-model) of a considered EM field function for one precise set of probability densities of random variables does not provide enough information. Consequently, a number of PCE meta-models of the EM field function should be derived, each for the different joint probability density of a vector of random variables, e.g., associated with different mean (nominal) values of random variables. The general polynomial chaos (gPC) approach requires numerical calculations for each PCE meta-model derivation. In order to significantly decrease the time required to derive all of the PCE meta-models, the novel approach has been introduced. It utilizes the novel so-called primary approximation and the novel analytical formulas. They significantly decrease the number of numerical calculations required to derive all of the PCE meta-models compared with the gPC approach. In the paper, we analyze the stochastic EM fields distributions in a telecommunication system in a spatial domain. For this purpose, analysis of uncertainties associated with a propagation channel as well as with transmitting and receiving antennas was introduced. We take advantage of a ray theory in our analysis. This allows us to provide the novel method for rapid calculation of a PCE meta-model of a telecommunication system transfer function by using the separate PCE meta-models associated with antennas and a propagation channel.