Frequency Characteristics of Geometry-Based Clusters in Indoor Hall Environment at SHF Bands

Abstract

This paper presents an analysis of geometry-based cluster frequency dependency at super-high-frequency bands, including 3, 10, and 28 GHz. First, multipath components were extracted from the measured data by using the space-alternating generalized expectation-maximization algorithm. Then, geometry-based clusters were estimated by using the enhanced scattering point-based KPowerMeans (SPKPM) algorithm. Finally, the frequency dependencies of their scattering intensities were discussed with the assistance of physical optics. The analysis results showed that the SPKPM could also be applied to obtain reasonable scattering locations at multiple frequencies in most cases. In addition, reflection on smooth surfaces was the dominant mechanism of clustering where there was no frequency dependence, whereas diffraction, scattering, and shadowing were significant causes of frequency dependence. Assuming that the line-of-sight is obstructed, diffraction, scattering, and shadowing accounted for 30-40% of the entire channel in terms of power, which was not negligible and thus the channel was largely frequency-dependent. The analysis results are expected to provide crucial insights for multiple-frequency channel modeling for fifth-generation wireless systems.