Fine-scale modelling of rain fields for radio network simulation

Electromagnetic waves at microwave frequencies are strongly scattered by rain. Rain fade is the mechanism that limits the performance of terrestrial microwave telecommunication systems. To predict the Quality of Service (QoS) at a node in heterogeneous networks of line-of-sight, terrestrial, microwave links; requires knowledge of the spatial and temporal statistics of rain over scales of a few meters to tens or hundreds of kilometres, and over temporal periods as short as one-second. Current internationally recognised models are not able to predict QoS, even for an individual link. This project aims to produce a radio network simulator that will predict the correct first and second order joint, rain fade statistics on heterogeneousnetworks of arbitrary geometry.Meteorological radar databases provide rain rate maps over areas with a spatial resolution as fine as a few hundred meters and a sampling period of 2 to 15 minutes. Such two-dimensional, rain rate map time-series could be used to predict the QoS provided by arbitrary millimetre-wave radio networks, if the sampling period were considerably shorter i.e. of the order of 10 s or less. This work analyses the spatial and temporal rain rate variation by using data gathered as part of the Chilbolton Radar Interference Experiment (CRIE). Numerical algorithms have been developed to interpolate one, two and three dimensional (1D, 2D and 3D) rain rate fields to a finer sampling interval. A series of radar derived rain maps, with a 10 minute sample period, are interpolated to 10 seconds. Stochastic algorithms have been developed to preserve important statistics present in the CRIE data while introducing rain rates at new data points which preserve a priori statistics determined from other datasets. The resulting fine-scale spatial-temporal rain rate fields form the basis of a link simulation tool. The performance of several links is simulated and the simulation statistics are compared with international models and measured data.EThOS - Electronic Theses Online ServiceGBUnited Kingdo