Securing satellite communication systems for sixth-generation (6G) networks is a significant challenge owing to the broadcast nature of satellite channels. Existing physical-layer security (PLS) methods, such as traditional beamforming and cryptographic techniques, do not provide efficient real-time solutions for dynamic resource-constrained satellite links. To address this gap, we propose a novel approach that combines direction-of-arrival (DoA) estimation using multiple signal classification (MUSIC) and Min-Norm algorithms with adaptive beamforming techniques, specifically least mean squares (LMS) and recursive least squares (RLS) algorithms. Our method dynamically adjusts the beam patterns to enhance the secrecy capacity while minimizing interference to eavesdroppers (Eve) in multibeam satellite systems. Simulation results show that the LMS algorithm achieves superior secrecy capacity and null depth, whereas the RLS algorithm converges faster under time-varying conditions. This paper demonstrates that adaptive beamforming techniques can significantly improve the PLS of satellite links, providing an efficient and scalable solution for 6G non-terrestrial networks (NTNs).
Securing satellite communication systems for sixth-generation (6G) networks is a significant challenge owing to the broadcast nature of satellite channels. Existing physical-layer security (PLS) methods, such as traditional beamforming and cryptographic techniques, do not provide efficient real-time solutions for dynamic resource-constrained satellite links. To address this gap, we propose a novel approach that combines direction-of-arrival (DoA) estimation using multiple signal classification (MUSIC) and Min-Norm algorithms with adaptive beamforming techniques, specifically least mean squares (LMS) and recursive least squares (RLS) algorithms. Our method dynamically adjusts the beam patterns to enhance the secrecy capacity while minimizing interference to eavesdroppers (Eve) in multibeam satellite systems. Simulation results show that the LMS algorithm achieves superior secrecy capacity and null depth, whereas the RLS algorithm converges faster under time-varying conditions. This paper demonstrates that adaptive beamforming techniques can significantly improve the PLS of satellite links, providing an efficient and scalable solution for 6G non-terrestrial networks (NTNs).
Due to the broadcasting nature, satellite signals are vulnerable to potential eavesdropping attacks, which pose a significant security risk for users. Physical layer security (PLS) and cryptography technologies have been independently developed to address this security risk. However, the independent use of each technology in the power-limited satellite systems results in a trade-off problem between onboard power consumption and security performance due to additional encryption costs and dependence of PLS on the performance of eavesdroppers (Eves). In this paper, we integrate the PLS and cryptography considering the complementary properties of the adaptability to wireless channel characteristics and inherent message confidentiality for secure multibeam satellite networks. To this end, we estimate the eavesdropping risk as a function of the given number of Eves for independent and collaborative attacks. Moreover, we design an onboard power model utilized for transmission and computation, and Gaussian beamforming based on the eavesdropping risk. Then, we derive solutions for onboard power allocation, beam scheduling, and security algorithm selection in the non-orthogonal multiple access (NOMA) systems. Finally, we demonstrate that the secure transmission performance improves even under the increment of the eavesdropping risk, and the trade-off performance between cryptography and PLS is provided through analytical and simulation results.
This letter proposes a robust beamforming (BF) scheme to enhance physical layer security (PLS) of the downlink of a multibeam satellite system in the presence of either uncoordinated or coordinated eavesdroppers (Eves). Specifically, with knowing only the approximate locations of the Eves, we aim at maximizing the worst-case achievable secrecy rate (ASR) of the legitimate user (LU), subject to the constraints of per-antenna transmit power and quality of service (QoS) requirement of the LU. Since the optimization problem is non-convex, we first adopt the discretization method to deal with the unknown regions of the Eves and then exploit the log-sum-exp function to approximate the objective function. Afterwards, a BF method joint alternating direction method of multipliers (ADMM) with Dinkelbach iteration is presented to solve this non-convex problem. Finally, simulation results verify that our robust BF algorithm can effectively improve the security of multibeam satellite systems.
Compared with terrestrial communication, satellite communication has played a crucial role in 6G communication as a result of wide-area coverage characteristics. Among them, beamforming scheduling and information security are critical research issues to improve system transmission performance. However, in geostationary earth orbit (GEO)-based satellite communication systems, owing to the wide-area coverage, ground users are susceptible to inter-beam interference caused by multibeam antennas at the satellite, and the information received by terrestrial users may be eavesdropped by air or terrestrial eavesdroppers. To this end, in this article, we propose a new robust security transmission strategy by combining beamforming and artificial noise (AN) techniques. Specifically, based on the actual satellite communication network scenario, the uncertain channel models are formulated as bounded uncertainty sets by considering the impact of imperfect channel state information of both legitimate and wiretap channels. Then, we build a bounded-constrained beamforming optimization to maximize the sum rate of legitimate users, while guaranteeing the constraints of total transmit power on the satellite and the minimum security rate of each legitimate user. Since the original problem is non-convex and mathematically intractable, we jointly exploit the successive convex approximation, Taylor series expansion, S-Procedure, and the semi-definite relaxation approach, with which the original problem can be transformed into a tractable one with a series of linear matrix inequality constraints. Furthermore, we propose an iterative algorithm to obtain the optimal beamforming and AN vectors. Finally, simulation results show that, compared with the existing algorithms, the proposed algorithm has better security and robustness.
Security threats introduced due to the vulnerability of the transmission medium may hinder the proliferation of Ka band multibeam satellite systems for civil and military data applications. This paper sets the analytical framework and then studies physical layer security techniques for fixed legitimate receivers dispersed throughout multiple beams, each possibly surrounded by multiple (passive) eavesdroppers. The design objective is to minimize via transmit beamforming the costly total transmit power on board the satellite, while satisfying individual intended users' secrecy rate constraints. Assuming state-of-the-art satellite channel models, when perfect channel state information (CSI) about the eavesdroppers is available at the satellite, a partial zero-forcing approach is proposed for obtaining a low-complexity sub-optimal solution. For the optimal solution, an iterative algorithm combining semi-definite programming relaxation and the gradient-based method is devised by studying the convexity of the problem. Furthermore, the use of artificial noise as an additional degree-of-freedom for protection against eavesdroppers is explored. When only partial CSI about the eavesdroppers is available, we study the problem of minimizing the eavesdroppers' received signal to interference-plus-noise ratios. Simulation results demonstrate substantial performance improvements over existing approaches.
In this paper, we study multibeam satellite secure communication through physical (PHY) layer secu-rity techniques, i.e., joint power control and beamforming. By first assuming that the Channel State Infor-mation (CSI) is available and the beamforming weights are fixed, a novel secure satellite system design is investigated to minimize the transmit power with individual secrecy rate constraints. An iterative algorithm is proposed to obtain an optimized power allocation strategy. Moreover, sub-optimal beamforming weights are obtained by completely eliminating the co-channel interference and nulling the eavesdroppers ’ signal simultaneously. In order to obtain jointly optimized power allocation and beamforming strategy in some practical cases, e.g., with certain estimation errors of the CSI, we further evaluate the impact of the eavesdropper’s CSI on the secure multibeam satellite system design. The convergence of the iterative algorithm is proven under justifiable assumptions. The performance is evaluated by taking into account the impact of the number of antenna elements, number of beams, individual secrecy rate requirement, and CSI. The proposed novel secure multibeam satellite system design can achieve optimized power allocation to ensure the minimum individual secrecy rate requirement. The results show that the joint beamforming scheme is more favorable than fixed beamforming scheme, especially in the cases of a
This paper investigates the physical layer security (PLS) of a multibeam satellite communication system where the satellite transmits the private signal to a legitimate user (LU) which is intercepted by multiple eavesdroppers (Eves). By considering the imperfect channel state information (CSI) of Eve channels, we formulate the constrained problem to maximize the LU achievable secrecy rate (ASR) subject to secrecy rate outage probability constraint, the total satellite transmit power constraint and the LU rate constraint. Firstly, we adopt golden section method to transform the difficult original problem into a series easier sub-problem. Then, considering the nonconvex of sub-problem, we employ Bernstein inequality and semidefinite programming (SDP) to transform the sub-problem into solvable one. Then, we use standard software package to get the optimal beamforming (BF) weight vector through an iterative penalty-based algorithm. Finally, simulation results confirm the superiority and robustness of the designed BF scheme.