Abstract
This research article proposes a novel ray-launching propagation loss model that is able to use an environment model that contains the real geometry. This environment model is made by applying a Simultaneous Localization and Mapping (SLAM) algorithm. As a solution to the rising demands of Internet of Things applications for indoor environments, this deterministic radio propagation loss model is able to simulate an accurate coverage map that can be used for localization applications or network optimizations. Since this propagation loss model uses a 2D environment model that was captured by a moving robot, an automated validation model is developed so that a wireless sensor network can be used for validating the propagation loss model. We validated the propagation loss model by evaluated two environment models towards the lowest Root Mean Square Error (RMSE), the Mean Absolute Error (MAE), and the Mean Error (ME). Furthermore, the correlation between the number of rays and the RMSE is analyzed and the correlation between the number of reflections versus the RMSE is also analyzed. Finally, the performance of the radio propagation loss model is analyzed.