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International Conference on Electronics, Information, and Communication (ICEIC)

Artificial Noise Assisted Secure Transmission for Low Earth Orbit Satellite Communications

Inkyu Bang, Seong Ho Chae, Taehoon Kim

Published Jan 28, 2024• 2 citations
Publisher

Abstract

Satellite communications have become essential in several domains such as broadcasting, navigation, and military applications. However, wireless communications including satellite communications are vulnerable to eavesdropping by malicious users. In this paper, we propose artificial noise assisted low earth orbit (LEO) satellite scheduling to enhance the secrecy of satellite communications. Further, we evaluate our proposed scheme through extensive simulations in terms of the secrecy rate and finally provide intuition to design future satellite communication systems from the aspect of security.

DOI
10.1109/iceic61013.2024.10457264

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IEEE Open Journal of the Communications Society•Jan 1, 2026•0 citations
Satellite communications have become essential in several domains such as broadcasting, navigation, and military applications. However, wireless communications including satellite communications are vulnerable to eavesdropping by malicious users. In this paper, we propose artificial noise assisted low earth orbit (LEO) satellite scheduling to enhance the secrecy of satellite communications. Further, we evaluate our proposed scheme through extensive simulations in terms of the secrecy rate and finally provide intuition to design future satellite communication systems from the aspect of security.
Low Earth Orbit (LEO) satellite communications are vulnerable to eavesdropping due to open wireless links. To address this issue, a simplified artificial noise (AN)-aided physical layer security scheme is proposed. A practical system model including a multi-antenna LEO satellite, a single-antenna ground user, and multiple eavesdroppers is established, considering shadowed Rician fading and imperfect channel state information (CSI). The AN is projected into the null space of the legitimate user’s channel to avoid interference, while suppressing eavesdroppers. A fixed power allocation strategy is adopted for easy implementation. Simulation results show that the proposed scheme outperforms traditional methods in secrecy rate and secrecy outage probability (SOP) with low computational complexity, making it suitable for resource-constrained LEO satellite systems.
Satellite communication has become essential for achieving seamless global connectivity in the 5 G and the future 6G networks. However, preventing eavesdropping attacks on data transmission remains a challenge due to the broadcasting nature of radio signals. Physical layer security (PLS) is a promising approach that can offer a lightweight solution suitable for satellites with hardware constraints such as limited computing and processing power. Recent studies considering PLS techniques have investigated secrecy performance in various satellite communication environments such as non-orthogonal multiple access but multi-satellite scheduling problems have been less highlighted. Particularly, in this paper, we investigate secrecy outage probability in low Earth orbit satellite networks by jointly considering multi-satellite scheduling for data and artificial noise transmissions against eavesdropping attacks. We propose a novel multi-satellite scheduling scheme and derive a closed-form of secrecy outage probability over Nakagami-mmmfading channels. We verify our analysis and evaluate our proposed scheme compared to several baseline schemes through extensive simulations.
As key enablers of 6G, low Earth orbit (LEO) satellite constellations are expected to offer global and low-latency connectivity. However, the broadcast nature and open-space propagation of satellite communications make it inherently vulnerable to eavesdropping. In dense LEO constellations where multiple satellites simultaneously cover overlapping regions, satellite scheduling can significantly contribute to secrecy performance. In this letter, we investigate a novel deep learning-based secure scheduling problem for physical layer security (PLS) in LEO satellite networks. During the scheduling process, we jointly consider multi-satellite transmission and cooperative artificial noise (AN) generation to defend against eavesdropping. The proposed deep learning-based scheduler, designed using attention-based permutation-invariant neural networks, learns security-oriented scheduling policies based solely on statistical channel information of eavesdroppers. Simulation results demonstrate that the proposed scheduling algorithm significantly enhances secrecy performance in terms of both secrecy rate and secrecy outage probability, outperforming conventional baseline schemes.
Low Earth Orbit (LEO) satellite communications are vulnerable to eavesdropping over open wireless links. This paper proposes a simplified artificial noise (AN)-aided physical layer security scheme. A system model with a multi-antenna LEO satellite, a single-antenna ground user, and multiple eavesdroppers is built under shadowed-Rician fading and imperfect channel state information. AN is projected into the null space of the legitimate channel to avoid interference, and fixed power allocation is adopted for low complexity. Simulations show the scheme achieves better secrecy rate and secrecy outage probability than traditional methods, suitable for resource-constrained LEO satellite systems.
In recent years, satellite communications have become the focus of research on space-air-ground-sea integrated wireless communication networks because of their wide coverage. Due to the broadcasting nature of satellite communications, the security of satellite systems has become a critical issue. In this paper, we study the secure transmission of satellite communications, focusing on the geostationary earth orbit (GEO) and low earth orbit (LEO) satellite scenarios, respectively. Because of the satellite's high mobility and long propagation delays, the transmitter side cannot obtain accurate channel state information (CSI). To this end, we establish the channel phase uncertainty model of GEO satellite users, the channel angle uncertainty model of LEO satellite users, and the norm-bounded model of eavesdroppers, respectively. Then, a corresponding robust secure transmission design is proposed. Since the resulting optimization problems are non-convex and challenging to handle, we propose an algorithm that transforms the original problem into a series of convex optimization subproblems and obtains the beamforming weight vectors through iterative calculation. Simulation results indicate that the security and robustness performance of the proposed algorithms are significantly improved compared with the conventional baselines.
Low-earth orbit (LEO) satellite systems provide global coverage and low latency, yet their rapid motion induces severe channel variations, rendering full-service-period physical layer security design prohibitively costly and inefficient. To address this issue, we investigate a high-altitude platform (HAP)-assisted secure transmission scheme, where the HAP transmits artificial noise (AN) to enhance satellite communication security and improve user fairness. Specifically, we formulate a minimum secrecy rate maximization problem with joint power allocation and the HAP beamforming vector as optimization variables. Due to the non-convexity nature of the problem, solving it for a single time slot is computationally intensive, and directly extending the optimization across all time slots incurs prohibitive overhead. Therefore, we propose a learning-based framework that first optimizes key time slots and then trains a kernel ridge regression (KRR) model. In particular, the number of training samples is adaptively adjusted based on the minimum distance between eavesdroppers and legitimate users, while a warm-start strategy is used to accelerate optimization over the sampled slots. The trained KRR model learns the mapping from satellite angular positions to secure transmission parameters and predicts suitable solutions for the remaining time slots. Simulation results show that the proposed method achieves secrecy and user fairness performance comparable to per-slot optimization with much lower computational complexity, offering a scalable and efficient solution for secure LEO satellite communications.