Identification of Transient Radio Frequency Occlusion Events in Urban Environments

• Published in: IEEE access Vol. 11; pp. 68051 - 68065
• Main Authors: Rooney, Margaret M., Hinders, Mark K.
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2023; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: 5G networks; Algorithms; Buildings; electromagnetic modeling; electromagnetic scattering; FDTD simulations; Fingerprints; Finite difference methods; Finite difference time domain method; Machine learning; Military applications; Occlusion; OFDM; Radio frequency; Radio signals; Scattering; SHF; Solid modeling; Superhigh frequencies; Time-domain analysis; Urban areas; Urban environments; Wireless communications
• ISSN: 2169-3536; 2169-3536
• DOI: 10.1109/ACCESS.2023.3292343

We model the propagation of SHF OFDM signals around vehicles and buildings since these are the most common elements present in urban environments that could lead to complex radio frequency signal scattering. Scenarios involving temporary hidden node situations, which we term transient occlusion events, are simulated and compared to scenarios where a line of sight transmission event occurs. Sets of fingerprints generated from signals recorded in full-wave 3D finite difference time domain simulations of these two different types of situations are compared, and features in the fingerprints corresponding to the occlusion of a transmitted signal by a vehicle or a building are identified. The features we identify in the sets of fingerprints have promise to be used with machine learning algorithms to automate the detection of hidden nodes and to provide an understanding of node behavior in an environment. When combined with knowledge of the existence of scatterers such as vehicles and buildings in the immediate neighborhood of a device, this information can be exploited to determine the likelihood of obstructed vs. concluded transmissions for both civilian and military applications.