In Situ Wireless Channel Visualization Using Augmented Reality and Ray Tracing
Date
2020-01
Authors
Koutitas, George
Siddaraju, Varun Kumar
Metsis, Vangelis
Journal Title
Journal ISSN
Volume Title
Publisher
Multidisciplinary Digital Publishing Institute
Abstract
This article presents a novel methodology for predicting wireless signal propagation using ray-tracing algorithms, and visualizing signal variations in situ by leveraging Augmented Reality (AR) tools. The proposed system performs a special type of spatial mapping, capable of converting a scanned indoor environment to a vector facet model. A ray-tracing algorithm uses the facet model for wireless signal predictions. Finally, an AR application overlays the signal strength predictions on the physical space in the form of holograms. Although some indoor reconstruction models have already been developed, this paper proposes an image to a facet algorithm for indoor reconstruction and compares its performance with existing AR algorithms, such as spatial understanding that are modified to create the required facet models. In addition, the paper orchestrates AR and ray-tracing techniques to provide an in situ network visualization interface. It is shown that the accuracy of the derived facet models is acceptable, and the overall signal predictions are not significantly affected by any potential inaccuracies of the indoor reconstruction. With the expected increase of densely deployed indoor 5G networks, it is believed that these types of AR applications for network visualization will play a key role in the successful planning of 5G networks.
Description
Keywords
augmented reality, network signal visualization, ray tracing, spatial mapping, 5G networks, Computer Science
Citation
Koutitas, G., Siddaraju, V. K., & Metsis, V. (2020). In situ wireless channel visualization using augmented reality and ray tracing. Sensors, 20(3) 690.
Rights
Rights Holder
© 2020 The Authors.
Rights License
This work is licensed under a Creative Commons Attribution 4.0 International License.
This work is licensed under a Creative Commons Attribution 4.0 International License.
This work is licensed under a Creative Commons Attribution 4.0 International License.