Uplink Sensing Using CSI Ratio in Perceptive Mobile Networks

TL;DR

This paper introduces an advanced parameter estimation scheme in uplink sensing for perceptive mobile networks, capable of localizing multiple moving targets without LOS, by leveraging CSI ratio and Taylor series-based algorithms.

Contribution

It develops a novel multi-parameter estimation method using CSI ratio and Taylor series to enable multi-target localization in non-LOS conditions.

Findings

Effective in estimating Doppler, AoA, and delay for multiple targets

Works well in both experimental and simulation environments

Does not require line-of-sight for accurate sensing

Abstract

Uplink sensing in perceptive mobile networks (PMNs), which uses uplink communication signals for sensing the environment around a base station, faces challenging issues of clock asynchronism and the requirement of a line-of-sight (LOS) path between transmitters and receivers. The channel state information (CSI) ratio has been applied to resolve these issues, however, current research on the CSI ratio is limited to Doppler estimation in a single dynamic path. This paper proposes an advanced parameter estimation scheme that can extract multiple dynamic parameters, including Doppler frequency, angle-of-arrival (AoA), and delay, in a communication uplink channel and completes the localization of multiple moving targets. Our scheme is based on the multi-element Taylor series of the CSI ratio that converts a nonlinear function of sensing parameters to linear forms and enables the applications of traditional sensing algorithms. Using the truncated Taylor series, we develop novel multiple-signal-classification grid searching algorithms for estimating Doppler frequencies and AoAs and use the least-square method to obtain delays. Both experimental and simulation results are provided, demonstrating that our proposed scheme can achieve good performances for sensing both single and multiple dynamic paths, without requiring the presence of a LOS path.