A measurement-based study on the use of spatial interpolation for propagation estimation

In this paper, we provide a first comprehensive comparison on the performance of two spatial estimation approaches used for propagation estimation. The first estimates the shadowing distribution with considerably low number of measurements and the second estimates the received power with no information of the transmitter location. We discuss in details the relative advantages of these techniques and study particularly their performance when using different number of measurement points. Our study is based on data from a very carefully conducted large-scale measurement campaign with a high spatial density. The robustness of our results is verified in different propagation environments and different frequencies. In particular, we show that for very small number of samples, prediction based on shadowing results in better performance. However, with small increase in the number of available measurements, this more complex approach becomes unnecessary and direct prediction of the received power yields very good results.