Fluid Antenna-Aided Robust Secure Uplink Transmission in LEO Satellite Constellations
Abstract
Secure uplink transmission in low-earth orbit (LEO) satellite constellations faces significant challenges due to the time-varying spatial distributions of serving and potential eavesdropping satellites, particularly when their angular separations are small and eavesdropper channel state information (CSI) is imperfect. To address these challenges, this paper investigates fluid antenna (FA)-aided robust secure uplink transmission in LEO satellite constellations. To avoid frequent antenna reconfiguration, the FA positions are optimized over an observation interval and remain fixed throughout the interval, while transmit beamforming dynamically adapts to the time-varying satellite channels. We formulate an average worst-case secrecy rate maximization problem by jointly optimizing FA positions and time-varying beamforming under norm-bounded eavesdropper CSI uncertainties and per-slot secrecy rate constraints. Two new alternating optimization (AO) algorithms are developed to solve the resulting non-convex problem. For robust beamforming optimization, the S-procedure, semidefinite relaxation (SDR), and first-order approximation are employed to construct a tractable convex problem, followed by Gaussian randomization for rank-one recovery. For FA position optimization, we derive concave surrogate functions for successive convex approximation (SCA) and develop a differential evolution (DE)-based search strategy to reduce computational complexity. Numerical results demonstrate that both FA-aided schemes consistently outperform conventional fixed-position antenna arrays across different constellation configurations and CSI uncertainty levels. Moreover, the two algorithms exhibit different performance-complexity tradeoffs as the number of FA elements increases, with DE offering a computational advantage for larger arrays while SCA can achieve higher secrecy rates.
Related
- Fluid Antenna Secure Channel-driven Constellation (FASCC): a Physical Layer Security approach
- Beyond LLM-GA: Secure Fluid Antenna Systems with ReEvo-Designed Memetic Algorithm
- Sensing-Aided Secure Multicast in Rotatable Antenna-Enabled ISAC Systems
- On the Investigation of Antenna Beam Pattern Models for Fast Beam Placement in LEO Satellite Networks
- An adaptive voxel-wise iterative satellite interference localization method based on a double-layer UCA antenna
BibTeX
@misc{luo2026fluid,
title = {{Fluid Antenna-Aided Robust Secure Uplink Transmission in LEO Satellite Constellations}},
author = {Suhong Luo and Pan Tang and Jianhua Zhang and Ji Wang and Yixuan Li and Xingwang Li},
howpublished = {arXiv},
year = {2026},
month = nov,
doi = {10.48550/arxiv.2605.18099},
eprint = {2605.18099},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2605.18099},
}
RIS
TY - UNPB
TI - Fluid Antenna-Aided Robust Secure Uplink Transmission in LEO Satellite Constellations
AU - Suhong Luo
AU - Pan Tang
AU - Jianhua Zhang
AU - Ji Wang
AU - Yixuan Li
AU - Xingwang Li
PY - 2026
DA - 2026/11/05
PB - arXiv
DO - 10.48550/arxiv.2605.18099
UR - https://arxiv.org/abs/2605.18099
AB - Secure uplink transmission in low-earth orbit (LEO) satellite constellations faces significant challenges due to the time-varying spatial distributions of serving and potential eavesdropping satellites, particularly when their angular separations are small and eavesdropper channel state information (CSI) is imperfect. To address these challenges, this paper investigates fluid antenna (FA)-aided robust secure uplink transmission in LEO satellite constellations. To avoid frequent antenna reconfiguration, the FA positions are optimized over an observation interval and remain fixed throughout the interval, while transmit beamforming dynamically adapts to the time-varying satellite channels. We formulate an average worst-case secrecy rate maximization problem by jointly optimizing FA positions and time-varying beamforming under norm-bounded eavesdropper CSI uncertainties and per-slot secrecy rate constraints. Two new alternating optimization (AO) algorithms are developed to solve the resulting non-convex problem. For robust beamforming optimization, the S-procedure, semidefinite relaxation (SDR), and first-order approximation are employed to construct a tractable convex problem, followed by Gaussian randomization for rank-one recovery. For FA position optimization, we derive concave surrogate functions for successive convex approximation (SCA) and develop a differential evolution (DE)-based search strategy to reduce computational complexity. Numerical results demonstrate that both FA-aided schemes consistently outperform conventional fixed-position antenna arrays across different constellation configurations and CSI uncertainty levels. Moreover, the two algorithms exhibit different performance-complexity tradeoffs as the number of FA elements increases, with DE offering a computational advantage for larger arrays while SCA can achieve higher secrecy rates.
ER -