Phase Noise Model Construction and Denoising Method for Dynamic Infrastructure Measurement in 5G Base Station

Abstract. The 5G base station pass-sensing integration technology, characterized by its all-weather capability, wide coverage, high dynamics, and high precision, has proven effective in deformation monitoring for various types of infrastructure. It plays a critical role in mitigating potential risks and ensuring the safe operation of cities. However, due to the unstable signal output from 5G base station hardware, phase noise arises, leading to frequency or phase shifts in the monitoring signal spectrum. This interferes with the processing of atmospheric effects, base station vibrations, and clutter, significantly reducing monitoring accuracy. Therefore, this study focuses on investigating the influence mechanism of phase noise in 5G base stations and developing a corresponding compensation method. First, the generation and influence mechanisms of phase noise are analyzed through simulation experiments, revealing that oscillator instability induces the coupling of multiple colored noises, thereby reducing the accuracy of base station clock synchronization. Subsequently, phase stability tests conducted in both internal and external fields of the base station verify the ability of first-path signals to characterize phase noise. Based on these findings, a method for suppressing phase noise by rejecting first-path signals is proposed. Finally, the effectiveness of the proposed method is validated through dynamic deflection monitoring experiments on bridges using 5G base stations. The results demonstrate that the application of this method reduces the RMSE by 29.2%, significantly enhancing the reliability and accuracy of deformation monitoring.