5G Positioning Method Based on Finite Rate of Innovation Sampling

Although the 5G positioning accuracy has been greatly improved due to the support of technologies such as large bandwidth and massive MIMO, it also brings a problem that the receiver needs to process massive amounts of data to obtain the position information of user equipment (UE). The finite rate of innovation (FRI) sampling theory can recover unknown information of signals through a small number of samples. In order to reduce the amount of data that needs to be processed during the 5G positioning process and effectively estimate the position of UE, this paper proposes a 5G positioning method based on FRI sampling. A FRI sampling structure for sounding reference signal (SRS) is proposed in this paper, and a signal arrival time reconstruction algorithm for this sampling structure is proposed. Finally, based on the estimated signal arrival time parameters, the position estimation of UE can be obtained by solving the positioning equation. The simulation results show that under certain conditions, this method can significantly reduce the sampling rate while maintaining positioning accuracy at the sub meter level. This article also analyzes the impact of factors such as the number of samples and sampling interval on the performance of this method.