AOA-Assisted Fingerprint Localization for Cell-Free Massive MIMO System Based on 3D Multipath Channel Model

Abstract

In this paper, an angle of arrival (AOA) assisted fingerprint localization technology based on three-dimensional (3D) multipath channel model is proposed for cell-free massive multiple-input multiple-output (MIMO) system. Firstly, according to the channel characteristics of cell-free massive MIMO system, a 3D narrowband multipath channel model is constructed. In the offline phase, the AOA information from different access points (APs) to users is utilized to construct the angular domain power matrix, which is used as fingerprint information. Angular similarity coefficient is proposed to measure the similarity between different reference points. In the online phase, we use the angular similarity coefficient weight (ASCW) algorithm to obtain the estimated localization of the user. The simulation results show that properly increasing the number of antennas and reducing the sampling interval can improve the localization accuracy. Finally, the effect of 3D multipath channel on fingerprint localization performance is analyzed compared with two-dimensional (2D) channel, as well as other received signal strength (RSS) localization algorithms.