Mixed Wave-Front Signal Model for 5G Indoor Passive Sounding and Channel Parameter Estimation

Abstract

Due to the universal coverage of the 5thGeneration (5G) mobile communication networks, indoor positioning based on 5G radio signal has attracted significant research and industrial interests. Accurate signal propagation models are beneficial to 5G communications and high precision 5G positioning. However, in the sub-6GHz frequency band of 5G networks, the traditional plane wave-front and spherical wave-front signal models are no longer fully applicable for indoor environments. In this paper, we propose a mixed wave-front signal model by combining the plane wave-front signal model with the spherical wave-front signal model. Simulation results show that when applied with the classic Space-Alternating Generalized Expectation-maximization (SAGE) algorithm, the proposed mixed model can yield better results in channel parameter estimation.