Propagation Channel Modeling Utilizing Discrimination Analysis for Outdoor Environments

In a wireless communication network, the performance and QoS of the network mainly depend on the propagation model of the channel. However, most empirical propagation models for outdoor environments don’t estimate the propagation of radio signals properly. This study proposes a novel technique based on machine learning to predict channel propagation in outdoor environments. The Linear Discriminate Analysis (LDA) method is proposed to estimate the path loss measurements in an urban and suburban environment, the proposed model considers; the geo-location of the receiver antenna, line-of-sight, and non-LOS propagation scenarios. In terms of accuracy, the results show that when using the LDA-based model to predict the pathloss measurements, results are better than traditional theoretical and analytical models.