Document Type

Article

Publication Title

IEEE Wireless Communications Letters

Abstract

Non-terrestrial networks (NTNs) are expected to play a pivotal role in the future wireless ecosystem. Due to its high-dynamic characteristics, the accurate estimation and compensation of carrier frequency offset (CFO) are crucial for supporting 5G new radio (NR) enabled satellite direct access. With emphasis on ensuring reliable uplink synchronization, we propose a clustering-neural network based CFO estimation scheme by virtue of NR random access preambles. By leveraging the sparsity and regularity of input samples, the proposed scheme can achieve fast and precise prediction of CFOs, while establishing robustness against time uncertainty and channel variation within a satellite beam. Simulation results validate the feasibility of our scheme in various NTN scenarios, and demonstrate its superiority in terms of stable estimation performance over the existing schemes.

First Page

587

Last Page

591

DOI

10.1109/LWC.2023.3333810

Publication Date

11-16-2023

Keywords

Estimation, OFDM, Indexes, Channel models, Delays, Satellite broadcasting, Uncertainty

Comments

Author version downloaded from the University of Surrey repository

Uploaded on June 4, 2024

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