Enabling OTFS for Hypersonic Aircraft Over LEO Satellite: A 3-D System Model and Differential Delay–Doppler Pilot

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Authors: Wenliang Lin, Wenjia Wang, K R Wang, Zhongliang Deng, Da Wan, Yaohua Deng, Zibo Feng, Zhengdao Fan, Senchao Deng
Cited by: 1
References: 27

Abstract

The integration of Low-Earth Orbit (LEO) satellites with hypersonic aircraft presents a critical frontier for next-generation non-terrestrial networks (NTN). However, the ultra-high dynamics inherent in these scenarios introduce severe Doppler frequency shifts and time-varying delays, significantly degrading link reliability. To address these challenges, this article proposes a robust Orthogonal Time Frequency Space (OTFS) communication framework tailored for hypersonic-LEO links. First, we establish a three-dimensional (3D) kinematic model based on the Earth-Centered Inertial (ECI) coordinate system. This model accurately characterizes the dynamic delay-Doppler (DD) channel features across the aircraft’s ascent, cruise, and descent phases. Guided by these channel insights, we develop a phase-adaptive dynamic pilot design scheme that jointly optimizes pilot position, pilot power, pilot quantity, and guard intervals to maximize spectral efficiency and estimation accuracy. Furthermore, leveraging the temporal correlation of the OTFS channel in the DD domain, we propose a Multi-Frame Joint Cross-Correlation Matching (MF-JCM) channel estimation algorithm. This algorithm aggregates multi-frame channel responses to suppress noise and enhance detection probability. Simulation results demonstrate that the proposed scheme achieves a Bit Error Rate (BER) of 10−4at an signal-to-noise ratio (SNR) of 7.5 dB in the ascent phase and 11 dB in the descent phase. Hardware experiments based on Software-Defined Radio (SDR) further validate the feasibility and superiority of the proposed approach in practical ultra-high dynamic scenarios.

Fields of Study & Subjects

GNSS positioning and interference UAV Applications and Optimization PAPR reduction in OFDM

Publication details

Journal / source
IEEE Internet of Things Journal
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Volume
13
Issue
7
Pages
14810–14828
Publication date
5 January 2026