Field strength prediction by ray-tracing for adaptive base station positioning in mobile communication networks

The Adaptive Base Station Positioning Algorithm (ABPA) is presented, which is based on a neural net approximation of the tra c density in the coverage area of a cellular mobile communication system. ABPA employs simulated annealing, thereby achieving quasi-optimal base station locations depending on the topography of the investigated area. Furthermore, ABPA considers the radio wave propagation within this area for the base station positions. Therefore, a three dimensional digital surface model is used to approximate the topography and two eld strength prediction methods, a line-of-sight (LOS) approach and a ray-tracing technique, are investigated within the context of adaptive positioning. In particular, the results obtained by the ray-tracing technique are encouraging, showing supplying areas, which seem to be similar to those, stemming from real measurements. However, as simulations show, the more realistic eld strength prediction by ray-tracing has a strong in uence on the performance of ABPA, resulting in di erent base station locations. As an outlook, the combination of eld strength prediction using ray-tracing with adaptive tra c prediction on a road graph by neural nets is proposed for further investigation.