PROJECT TITLE :

Inverse Gaussian-based composite channel model and time series generator for land mobile satellite systems under tree shadowing

ABSTRACT:

In this study, a brand new composite channel model for land mobile satellite (LMS) systems underneath tree shadowing is proposed utilising the inverse Gaussian (IG) distribution to model the shadowing component. Using the experimental knowledge of received power under tree shadowing at L-band, which were administrated at Stromovka Park in Prague, the Czech Republic, the assumption of the IG distribution for the description of the primary-order statistics of large-scale effects is investigated and validated. A new LMS channel model is developed as a total of a symbol experiencing IG shadowing and a signal underneath Rayleigh multipath effects. Moreover, a strategy to get accurate time series of the received signal envelope using the IG distribution is presented. Such methodology and usually time series generators will be used for the evaluation of system's performance and for finish-to-finish simulations. Finally, it is shown that the proposed time series generator reproduces the first-order and second-order statistics of the LMS channel model with a very sensible accuracy.