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.
Highlights
Nowadays, the need for a good and stable wireless connectivity at any indoor location and any time has grown to a necessity in our current daily lives due to the growing demands of Internet of Things (IoT) applications
This paper presents a novel ray-launching propagation loss model that is categorized as a deterministic model
A realistic ray launching propagation loss model is discussed based on the implementation that contains four different parts
Summary
The need for a good and stable wireless connectivity at any indoor location and any time has grown to a necessity in our current daily lives due to the growing demands of Internet of Things (IoT) applications. This makes it possible to compute all locations where signal strength measurements were taken and will result in an automated validation solution that empowers the usability of radio propagation algorithms [7] Such an automated solution can be used in different application domains such as indoor/outdoor localization systems, telecommunications systems, and wireless network systems to optimize the results based on realistic signal strengths simulations [3,13,14]. To validate and quantify our ray-launching propagation loss model so that an optimal simulation configuration can be found, two different indoor office environments are used Both environments were equipped with several transmitters that were operating at 433.0 MHz and were able to broadcast a packet according to the sub-GHz mid-range DASH7-standard [15].
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