  Although various linear log-distance path loss models have been developed,
advanced models are requiring to more accurately and flexibly represent the
path loss for complex environments such as the urban area. This letter proposes
an artificial neural network (ANN) based multi-dimensional regression framework
for path loss modeling in urban environments at 3 to 6 GHz frequency band. ANN
is used to learn the path loss structure from the measured path loss data which
is a function of distance and frequency. The effect of the network architecture
parameter (activation function, the number of hidden layers and nodes) on the
prediction accuracy are analyzed. We observe that the proposed model is more
accurate and flexible compared to the conventional linear model.
