International Journal of Satellite Communications and Networking最新文献

This study introduces a novel method for repositioning multi-steerable antennas on inclined geostationary earth orbit (GEO) satellites to enhance signal quality by mitigating signal degradation caused by coverage shifts due to satellite inclination. The innovation of this research lies in the real-time tracking of target ground stations (boresights) by spaceborne satellite antennas to maintain stable coverage footprints, marking a first in inclined geostationary satellite operations. Orbit simulations and analyses were conducted on the operational satellite Sat-A to evaluate the proposed onboard satellite antenna repositioning (OSAR) method. Various inclination angles (1°, 2°, 4°, and 6°) were considered, focusing on two coverage areas, BR1 and BR2. The method was validated through simulations by comparing Sat-A's zero-inclination baseline values with the repositioning results when pointing towards ground stations. The repositioned spaceborne antennas (S1 and S2) achieved remarkable pointing accuracy, with maximum errors of only 0.0165° in latitude and 0.0023° in longitude. Corresponding link performance metrics further confirmed the method's reliability, showing an equivalent isotropically radiated power (EIRP) deviation of 10⁻¹³ dB and an energy per bit to noise density ratio (E_b/N₀) variation of just 0.0795 dB. This performance is particularly critical for regions affected by beam shifts due to inclination. The simulation results demonstrate that the OSAR method is both accurate and cost-effective, making it suitable for various satellite services. By ensuring signal quality during inclined operations, the OSAR method offers a robust solution for satellite operators, enabling the delivery of reliable and high-quality services to customers.

Satellite communication has gained significant attention in the context of sixth-generation (6G) internet technology. Due to their high altitudes, dynamic link switching, and limited resources, satellite nodes are prone to higher bit error rates and communication delays. Additionally, the threat of Distributed Denial-of-Service (DDoS) attacks poses a serious challenge to satellite communication. These attacks are constantly evolving. Hence, it is crucial to develop a strategy to counter both known and unknown DDoS attacks. This article has proposed a scheme to mitigate the impact of DDoS attacks on satellite internet for reliable communication. The proposed scheme, Adaptive Link Backing Detection and Mitigation (ALBDM), leverages traffic and link features for DDoS attack detection. By implementing an adaptive model, ALBDM offers flexibility for reliable communication during DDoS assaults. To effectively mitigate DDoS attacks, a Blockchain has been integrated into the proposed scheme. Simulation and performance analysis results demonstrate that the proposed ALBDM scheme significantly reduces the impact of DDoS attacks. The proposed scheme achieves a true positive rate of 99.84%, an accuracy rate of 99.3%, and a false positive rate of only 0.14%.

Low Earth orbit (LEO) satellite networks, characterized by wide coverage, low latency, and high bandwidth, will be a key component of the future 6G mobile communication networks. However, the periodic handover of satellites in LEO networks will lead to dynamic path changes and fluctuations in propagation delay, affecting the end-to-end performance. Establishing a minimum round-trip time (minRTT) prediction model for LEO satellite networks is crucial for optimizing the design of related mechanisms such as routing, congestion control, and loss recovery. To this end, this paper first conducts a Starlink measurement to collect real-life data and then proposes a novel model combining hybrid attention (HA) mechanisms with multiscale convolutional neural networks (MCNN) and long short-term memory networks (LSTM) to explore minRTT prediction. The method utilizes HA to highlight important positional features in the minRTT sequence, while the MCNN and LSTM are exploited to capture the variation patterns of minRTTs, thereby enhancing the prediction accuracy. Experimental results show that the proposed HA-MCNN-LSTM model outperforms existing methods.

Maximizing the operational lifespan of Geostationary Earth Orbit (GEO) satellites is a critical objective for satellite operators. Throughout their service life, satellites are maintained within a designated control box through North–South (NS) and East–West (EW) station-keeping maneuvers. NS maneuvers, which adjust the satellite's inclination relative to the equatorial plane, require significantly more propellant than EW maneuvers. As a result, operators often choose to discontinue NS maneuvers, allowing the satellite to transition into an “inclined orbit” while relying on EW maneuvers to manage orbit drift and maintain longitude positioning. This approach is typically adopted when the satellite nears the end of its operational life or when fuel conservation becomes a priority. A critical challenge in this process is determining the optimal timing for initiating inclined orbit, which involves carefully balancing factors such as fuel availability, satellite health, mission requirements, and operational constraints. This study provides a comprehensive analysis of these factors, with a detailed exploration of timing optimization, and concludes with a practical case study to illustrate the findings.

This paper proposes a pragmatic approach to integrate communication (COM) and positioning navigation timing (PNT) services in (beyond) 5G ((B)5G) low Earth orbiting (LEO) satellite nonterrestrial networks (NTN). The goal is to optimize performance and minimize complementary PNT service costs. The current third generation partnership program (3GPP) fifth generation (5G) standard incorporates positioning reference signal (PRS) for enhancing user equipment (UE) positioning accuracy. However, this approach relies on network connectivity and is not suitable for UE standalone PNT service provision. Additionally, PRS exploitation in a NTN satellite constellation shows major issues on top of its know limitations in terrestrial networks (TNs). To address these limitations, we propose a solution inspired by the Chinese multimedia digital broadcasting standard (CMMB) standard, adapted for satellite NTN. This approach involves broadcasting a dedicated direct-sequence spread-spectrum (DS-SS) PNT signal on-top of the primary COM signal. This allows for efficient PNT service provision without compromising the performance of the core COM services. By decoupling PNT and COM services, we can optimize the satellite payload design providing wide area coverage for the PNT signal with reduced interference on the COM narrow beams, thus optimizing overall system performance. The proposed solution offers a promising and cost effective approach to enable accurate and reliable PNT services in satellite NTN, even in challenging environments with limited network connectivity.

As the satellite launch and manufacturing costs have become affordable, the industrial and academic interest in low-Earth orbit (LEO) satellites has increased in recent years. With this interest, the concept of LEO-based positioning, navigation, and timing (LEO-PNT) has also gained popularity as a complementary and/or standalone system in addition to the already existing Global Navigation Satellite Systems (GNSS). This article proposes a LEO constellation optimization methodology from the perspective of a LEO-PNT design, identifies and discusses the state-of-art of the LEO satellite constellation optimization approaches, introduces relevant performance- and feasibility-related metrics and parameters, and addresses key concepts and trade-offs that must be considered for any LEO-PNT constellation design. In addition, a case study for a LEO-PNT constellation optimization is presented, where we showcase the discussed trade-offs. We present optimization results obtained with the adaptive weighting algorithm “ADaW” applied to the Pareto-optimization algorithm nondominated sorting genetic algorithm III (“NSGA-III”). A detailed performance analysis is done for six relevant scenarios with varying receiver location properties, namely, by considering indoor/outdoor, rural/urban and line of sight/non–line of sight (NLOS) cases.

This paper investigates a robust secure transmission design for enhancing the physical layer security (PLS) in an intelligent reflecting surface (IRS)-aided satellite system. Especially since it is challenging to obtain the perfect channel state information (CSI) related to the IRS links, we consider here two different scenarios. Specifically, (1) perfect legitimate users' CSI (LCSI) and imperfect eavesdroppers' CSI (ECSI) are adopted. (2) the case of imperfect LCSI and imperfect ECSI. Under both scenarios, we formulate an optimization problem aiming to maximize the minimal achievable secrecy rate (ASR) among legitimate users subject to quality-of-service requirements and satellite transmit power budget. In order to tackle this nonconvex optimization problem, we propose a robust beamforming (BF) algorithm combining second-order Taylor series expansion and Bernstein-type inequality to jointly optimize transmit power of satellite and phase shifts of IRS. Finally, numerical results confirm the robustness and superiority of the proposed scheme under different CSI uncertainty scenarios.