Saved in:
Bibliographic Details
Main Authors: Yin, Zhisheng, Liu, Yonghong, Li, Dongbo, Cheng, Nan, Liang, Linlin, Li, Changle, Liu, Jie
Format: Preprint
Published: 2025
Subjects:
Online Access:https://arxiv.org/abs/2504.21446
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866910922846502912
author Yin, Zhisheng
Liu, Yonghong
Li, Dongbo
Cheng, Nan
Liang, Linlin
Li, Changle
Liu, Jie
author_facet Yin, Zhisheng
Liu, Yonghong
Li, Dongbo
Cheng, Nan
Liang, Linlin
Li, Changle
Liu, Jie
contents Low Earth Orbit (LEO) satellite networks are integral to next-generation communication systems, providing global coverage, low latency, and minimal signal loss. However, their unique characteristics, such as constrained onboard resources, Line-of-Sight (LoS) propagation, and vulnerability to eavesdropping over wide coverage areas, present significant challenges to physical layer security. To address these challenges, this paper focuses on the design of anti-intercept waveforms for satellite-ground links within Orthogonal Frequency Division Multiplexing (OFDM) systems, aiming to enhance security against eavesdropping threats. We formulate a secrecy rate maximization problem that aims to balance secrecy performance and communication reliability under eavesdropping constraints and sub-carrier power limitations. To solve this non-convex optimization problem, we propose a bisection search-activated neural network (BSA-Net) that integrates unsupervised learning for secure coding optimization and bisection search for dynamic power allocation. The proposed method is structured in two stages: the first optimizes secure coding under power constraints, while the second allocates power across sub-carriers under eavesdropping constraints. Extensive simulation results demonstrate the efficacy of our approach, showcasing significant improvements in secrecy rate performance.
format Preprint
id arxiv_https___arxiv_org_abs_2504_21446
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Anti-Intercept OFDM Waveform Design with Secure Coding for Satellite Networks
Yin, Zhisheng
Liu, Yonghong
Li, Dongbo
Cheng, Nan
Liang, Linlin
Li, Changle
Liu, Jie
Signal Processing
Low Earth Orbit (LEO) satellite networks are integral to next-generation communication systems, providing global coverage, low latency, and minimal signal loss. However, their unique characteristics, such as constrained onboard resources, Line-of-Sight (LoS) propagation, and vulnerability to eavesdropping over wide coverage areas, present significant challenges to physical layer security. To address these challenges, this paper focuses on the design of anti-intercept waveforms for satellite-ground links within Orthogonal Frequency Division Multiplexing (OFDM) systems, aiming to enhance security against eavesdropping threats. We formulate a secrecy rate maximization problem that aims to balance secrecy performance and communication reliability under eavesdropping constraints and sub-carrier power limitations. To solve this non-convex optimization problem, we propose a bisection search-activated neural network (BSA-Net) that integrates unsupervised learning for secure coding optimization and bisection search for dynamic power allocation. The proposed method is structured in two stages: the first optimizes secure coding under power constraints, while the second allocates power across sub-carriers under eavesdropping constraints. Extensive simulation results demonstrate the efficacy of our approach, showcasing significant improvements in secrecy rate performance.
title Anti-Intercept OFDM Waveform Design with Secure Coding for Satellite Networks
topic Signal Processing
url https://arxiv.org/abs/2504.21446