Location-Based Timing Advance Estimation for 5G Integrated LEO Satellite Communications

TL;DR

This paper proposes a novel location-based timing advance estimation method for 5G LEO satellite systems, addressing the limitations of terrestrial schemes by utilizing TDOA and FDOA measurements for accurate uplink synchronization.

Contribution

It introduces a new TA estimation approach using satellite-based measurements and quadratic optimization, tailored for the unique characteristics of LEO satellite networks.

Findings

Proposed methods approach the constrained CRLB of TA estimation.

The algorithms enable effective uplink frame alignment in 5G LEO satellite systems.

Numerical results validate the accuracy and efficiency of the proposed techniques.

Abstract

Integrated satellite-terrestrial communications networks aim to exploit both the satellite and the ground mobile communications, thus providing genuine ubiquitous coverage. For 5G integrated low earth orbit (LEO) satellite communication systems, the timing advance (TA) is required to be estimated in the initial random access procedure in order to facilitate the uplink frame alignment among different users. However, due to the inherent characteristics of LEO satellite communication systems, e.g., wide beam coverage and long propagation delays, the existing 5G terrestrial uplink TA scheme is not applicable in the satellite networks. In this paper, we investigate location-based TA estimation for 5G integrated LEO satellite communication systems. We obtain the time difference of arrival (TDOA) and frequency difference of arrival (FDOA) measurements in the downlink timing and frequency synchronization phase, which are made from the satellite at different time instants. We propose to take these measurements for either UE geolocation or ephemeris estimation, thus calculating the TA value. The estimation is then formulated as a quadratic optimization problem whose globally optimal solution can be obtained by a quadratic penalty algorithm. To reduce the computational complexity, we further propose an alternative approximation method based on iteratively performing a linearization procedure on the quadratic equality constraints. Numerical results show that the proposed methods can approach the constrained Cramer-Rao lower bound (CRLB) of the TA estimation and thus assure uplink frame alignment for different users.