Abstract

Lee's (1974) macroscopic propagation model is one of the most widely used propagation models due to its ability to achieve good prediction accuracy while still remaining relatively simple and intuitive. Another very important feature of the Lee model is that its prediction ability can be significantly improved by the incorporation of measurement data. Commonly, the measured data is used to optimize two parameters of the model, namely one-mile intercept and slope. This paper addresses the incorporation of the measured data from the standpoint of received signal level sampling. In particular, we discuss statistical criteria imposed on the received signal level sampling that have to be satisfied in order to achieve a valid propagation model optimization.

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