In-building measurement-based radio propagation modeling using a geostatistical interpolation technique

Abstract

Channel modeling can enhance communication efficiency through an accurate design to deliver higher quality to mobile users inside buildings. Clear processes and methodologies that can provide a high level of confidence in the design of indoor radio propagation systems are thus required. With the deployment of wireless communication and the need to accommodate for the shorter signal range, millimeter-wave (mmWave) enabled networks will have a high density of base stations. In such a dense network, interference is an important factor affecting network performance. In this way, accurate channel modeling combined with more spectrum availability is essential to achieve the ongoing demands faced by wireless carriers. Therefore, it is important to explore suitable in‐building mathematical propagation modeling approaches that can accurately make predictions and support the ever‐growing consumer data rate demands of modern communication systems. The research here report is aimed at providing solid theoretical and empirical foundations of how radio waves behave in practical wireless channels; validating the improvement in predictions when Kriging is included for path loss modeling not only in indoor scenarios, such as offices, classrooms, long corridors, libraries, and rooms but also in complex scenarios as is a stadium. In order to quantify the accuracy of the proposed methodology, it is compared with several traditional models described in the literature. Extensive path loss measurements were collected at different frequencies and heights providing the empirical basis for the three-dimensional (3D) Kriging-aided model. Through numerous studies during this doctoral research, It was found that this method significantly improves the accuracy as it considers all the singularities and site-associated features that are implicit in measured samples. The findings of this doctoral research lay a good foundation for a greater understanding of mmWave channel propagation, but mainly provide one of the most accurate methods for indoor 3D modeling, using few measurements and low computational complexity, yielding a practical and fast solution.