On-Demand Optimization Method for Cross-Layer Topology in Multi-Task VLEO and Mega-LEO Heterogeneous Satellite Networks

The improvement of BDS Observation Geometry with LEO constellations in Orbit Determination

This work develops an analytical framework for downlink low Earth orbit (LEO) or medium Earth orbit (MEO) satellite communications, leveraging tools from stochastic geometry. We propose a tractable approach to the analysis of such satellite communication systems, accounting for the fact that satellites are located on circular orbits. We accurately incorporate this geometric property of LEO or MEO satellite constellations by developing a Cox point process model that jointly produces orbits and satellites on these orbits. Our work contrasts with previous modeling studies that presumed satellite locations to be entirely random, thereby overlooking the fundamental fact that satellites are jointly positioned on orbits. Employing this Cox model, we analyze the network performance experienced by users located on Earth. Specifically, we evaluate the no-satellite probability of the proposed network and the Laplace transform of the interference created by such a network. Using it, we compute its SIR (signalto-interference) distribution, namely its coverage probability. By presenting fundamental network performance as functions of key parameters, this model allows one to assess the statistical properties of downlink LEO or MEO satellite communications and can thus be used as a system-level design tool to operate and optimize forthcoming complex LEO or MEO satellite networks.

This paper presents three 4-level optical modulation formats; two of which are intensity modulation formats - the 4-pulse amplitude modulation (4-PAM) and the absolute added correlative coding (AACC); and one coherent modulation format - the quadrature phase shift keying (QPSK); in a laser inter-satellite link (LISL), respectively. Each modulated link is modelled to operate in a low Earth orbit (LEO) satellite broadband constellation network and simulated for various performance parameters. These parameters include the power-efficiency, link-extendibility, receiver-sensitivity and spectral-efficiency of the modelled links. As all three modulated LISLs share a spectral-efficiency, the 4-PAM is observed to need a minimum transmitter laser power of 32 dBm to support a bit rate of 20 Gbps at the maximum LEO LISL distance of 6000 km. The AACC and QPSK required 28 dBm. Keeping to a bit-error rate (BER) of 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">−9</sup> and a constant transmitter power of 30 dBm, the AACC and QPSK sustains the maximum LEO LISL distance whereas the 4-PAM supports a link distance of 4000 km. The AACC modulated LISL also observed an improvement of ~ 7 dBm in receiver-sensitivity over the 4-PAM. All three modulated LISLs are then simulated for a bit rate of 40 Gbps. The 4-PAM and QPSK were found to support a link distance of 3000 km and 5000 km, respectively, whilst the AACC sustains up to a distance of 6000 km.

International organizations such as the 3rd Generation Partnership Project (3GPP) and the International Telecommunication Union (ITU) regard non-terrestrial networks (NTNs) as an essential component of the sixth-generation (6G) mobile communication technology and have advanced relevant standardization efforts. Low Earth orbit (LEO) satellite communication (SatCom) constitutes a key part of NTNs, and efficient uplink random access (RA) is crucial for establishing initial connections in LEO SatCom systems. However, the long propagation delay and wide coverage of LEO satellites substantially increase access latency and collision probability due to the limited number of beams and their constrained coverage areas. In addition, the highly non-uniform spatial distribution of user equipment (UE) further aggravates access inefficiency. To this end, this paper investigates joint beam position grouping and RA channel (RACH) occasions (ROs) allocation (JBPGRA) for LEO SatCom systems. Specifically, we develop a system model for RA under beam hopping and identify the key factors that influence RA performance. Furthermore, we derive expressions for both the instantaneous signal-to-interference-plus-noise ratio (SINR) and the average SINR under a given non-uniform UE spatial distribution. Building on this analysis, the JBPGRA problem is formulated as an integer linear programming problem that seeks to maximize RA success while conserving RO resources under non-uniform UE distribution. To achieve a practical solution, we propose an efficient JBPGRA algorithm composed of beam position classification, sparse beam position grouping, and RO allocation modules. Simulation results demonstrate that, under the same UE density, the proposed JBPGRA scheme achieves over 29% higher access success rate in dense beam positions compared with the uniform baseline adopted in existing SatCom systems, while reducing RO consumption by more than 49% and decreasing the number of beam position groups by over 57%.

Satellites in low Earth orbit (LEO) are accessible to an unprecedented number of users around the globe with numerous applications, especially with the recent rapid development in LEO satellite constellations for communications. Until a few years ago, advanced designs for satellite communications systems had focused on conventional geostationary Earth orbit (GEO) communications technologies which are not necessarily tailored to the LEO environment. Such sub-optimal designs were accommodated by the typical application of LEO satellites-remote sensing satellites-normally being large satellites with ever-increasing power and bandwidth and equipped with large ground stations. These days, the current trend of the satellite industry is towards smaller satellites and smaller terminals, made possible through continuous technological improvement. Advances in sensor and payload technology have permitted rapidly increasing amounts of data to be transferred. This, coupled with user demands for reliable, efficient data delivery from small satellites to even smaller terminals, calls for an urgent need to optimise the LEO communications link, particularly for payload data retrieval.

Current low earth orbit (LEO) satellite network display poor power efficiency, running network devices at full capacity all the time regardless of the traffic matrix and the distribution of the population over the Globe. Most of the research on energy efficiency of LEO satellites has focused on component level or link level. Therefore, this kind of research is not holistic to try to look at the satellite system as a single node. To enhance the energy efficiency. The solution should exploits multipath routing and load balancing. LEO network is overprovisioned, and hence selectively shutting down some satellite nodes and links during off-peaks hours seems like a good way to reduce energy consumption. In this paper, we exploit the fact that due to geographical and climatic conditions, some satellite links are expected to be loaded with data while others remain unused. Our approach is to power down satellite nodes and links during period of low traffic, while guaranteeing the connectivity and QoS. Finding the optimal solution is NP-problem and therefore, we explore in this work two heuristic algorithms. We evaluate our heuristics on a realistic LEO topology and real traffic matrices. Simulation results show that the power saving can be significant.

Low earth orbit (LEO) satellite system becomes an emerging non-terrestrial network solution for future radio communications. To maximize the system capacity, an LEO satellite could utilize circularly polarized planar antenna array with the frequency reuse technique to form multiple earthmoving beams. With the increasing number of LEO satellites, inline interference from the geosynchronous equatorial orbit (GEO) satellite is an important issue to be resolved when the spectrum resource is shared. With the frequency hopping phenomena in earth-moving LEO networks, the inline interference could be minimized if the GEO users also perform the similar frequency hopping via coordination between LEO and GEO satellite networks. This paper proposes eight spectrum sharing schemes for GEO satellite networks to produce the frequency hopping sequence in earth-moving LEO network. We evaluate the system capacity, fairness between LEO and GEO users, and time costs of all schemes. Simulation results validate the advantage obtained from coordination, and show that the simple greedy scheme performs as good as the optimal scheme due to fixed frequency hopping patterns.

With the advancement of low earth orbit (LEO) satellite communications, direct-to-satellite technology has attracted widespread attention. Due to the constrained onboard resources of LEO satellite, an efficient resource allocation strategy is essential to meet diverse user traffic demands. Furthermore, the spectrum sharing among multi-layer LEO satellites requires effective interference avoidance mechanism to enhance the overall service quality of the satellite system. To achieve efficient resource management in a dual-layer LEO satellite system, we propose a resource allocation strategy based on multi-agent proximal policy optimization (MAPPO). This strategy consists of three steps. Firstly, beam hopping time plan (BHTP) is designed based on a low complexity strategy. Next, the users served in each time slot are selected according to the buffer status. Finally, the MAPPO framework is employed to enable the flexible allocation of bandwidth and power resources. Simulation results demonstrate that the proposed strategy not only satisfies the diverse traffic demands of terminal users but also effectively reduces satellite power consumption.

Low earth orbit (LEO) satellite has the advantages of global coverage, low propagation delay and low path losses, etc.Combined with orthogonal frequency division multiplexing (OFDM) transmission, LEO satellite system can support very high capacity suitable for wideband multimedia traffic.This paper analyzes the channel model and throughput for LEO OFDM satellite communication system.First, several channel models for LEO satellite system are expounded with simulations because channel model is the basis of throughput analysis.Second, the beam model and the signaling model for LEO satellite are introduced.Considering high speed movement of LEO satellite, channel fading and the channel quality information (CQI), link throughput is simulated.Finally, compared with MF-TDMA system, simulation results demonstrate that OFDM system outperforms the former because its feasibility and superiority in throughput.

Gravity field recovery of inter-satellite links between Beidou navigation satellite system (BDS) and LEO based on geodesy and time reference in space (GETRIS)

Machine learning (ML) frameworks are investigated for use in simultaneous tracking and navigation (STAN) with low Earth orbit (LEO) satellites. STAN is a navigation paradigm that utilizes specialized LEO receivers to extract navigation observables (e.g., pseudorange and Doppler) from LEO satellite signals. Two neural network architectures are compared: Feed Forward Neural Network (FFNN) and Recurrent Neural Network (RNN). Additionally, two ML-based orbit determination frameworks are compared: ephemeris propagation and residual error propagation. The objective of the comparison is to select an approach with the lowest open-loop propagation error as well as computational cost. Based on simulation results, a nonlinear autoregressive neural network with exogenous inputs (NARX) embedded within the residual error modeling framework is selected as the best ML approach among the compared candidates. Experimental results are presented demonstrating a ground vehicle navigating for a total of 258 seconds, while receiving signals from two Orbcomm LEO satellites. Global navigation satellite system (GNSS) signals were artificially cut off for the last 30 seconds, during which the vehicle traversed a trajectory of 871 m. Two navigation frameworks are compared to estimate the vehicle’s trajectory: (i) LEO signal-aided inertial navigation system (INS) STAN framework using Simplified General Perturbation (SGP4) as its propagator and (ii) the proposed LEO signal-aided INS STAN framework using ML as its propagator. The STAN with SGP4 achieved a three-dimensional (3-D) position root-mean squared error (RMSE) of 30 m. In contrast, the proposed STAN with SGP4+NARX framework achieved a 3-D position RMSE of 3.6 m.

Low Earth Orbit (LEO) satellite communication systems have evolved into a critical component of global broadband networks, enabling wide‐area connectivity, IoT services, and intelligent multilayer satellite–terrestrial integration. Despite rapid advancements in constellation deployment, routing mechanisms, resource management, and LEO–5G/6G convergence, the long‐term evolution of research themes and network architectures remains insufficiently mapped. This study analyzes 2420 Web of Science articles published between 1995 and 2025 and applies bibliometric techniques, main path analysis, and edge‐betweenness clustering to identify the core technological trajectories shaping the LEO communication domain. The results reveal five major phases of development: foundational constellation design, multilayer architecture integration, performance and QoS optimization, 6G‐driven intelligent connectivity, and secure collaborative networking. Four dominant research clusters emerge: communication and IoT applications, routing and topology management, satellite edge computing and task offloading, and LEO‐enhanced GNSS positioning, highlighting the field's structural diversification. Main path and key‐route analyses further show a gradual shift from traditional connectivity‐oriented engineering toward distributed, AI‐enabled, and security‐aware satellite communication frameworks. This study provides the first longitudinal mapping of LEO communication research, offering an integrated understanding of how architectural evolution, protocol innovation, and emerging intelligent services intersect. The findings support future advances in satellite networking, resource optimization, and the design of resilient and interoperable LEO systems.

Validation of enhanced orbit determination for GPS satellites with LEO GPS data considering multi ground station networks

The demand for high-quality Direct-to-Home (D2H) television broadcasting services delivered via Low Earth Orbit (LEO) satellite constellations has surged in recent years. To address the growing needs of viewers, satellite communication must optimize the scheduling and routing of signals while balancing conflicting objectives. This research presents a novel approach named as Multi-Objective Deep Routing and Scheduling (MODRS) algorithm that is designed to tackle the challenges of signal latency minimization, bandwidth utilization maximization, and viewer demand satisfaction. The Multi-Objective Deep Neural Network (MODNN) is implemented in this paper to make intelligent routing and scheduling decisions for balancing multiple objectives. To enhance the learning process and provide training stability, the experience replay is used and the epsilon-greedy strategy is included to balance exploitation and exploration strategies. The Pareto-front concept is used for efficient D2H television broadcasting in the LEO satellite constellation. The experimental validation is conducted based on low-latency broadcasting, high-bandwidth utilization, viewer demand flexibility, adaptive signal strength and resource allocation efficiency. Using a series of simulated scenarios, this paper explores the versatility and robustness of MODRS, showcasing its exceptional performance in real-time, resource-efficient, disaster recovery, and rural broadcasting contexts. The findings indicate that MODRS is well-suited for a wide range of real-world applications, from low-latency broadcasting and disaster recovery to cost-effective rural expansion, enhancing the quality and accessibility of D2H television services. The MODRS algorithm emerges as a transformative solution for satellite communication optimization, ensuring viewer satisfaction and operational efficiency.

With the emergence of cellular radio technology, there has been a renewal of interest in low-Earth orbit (LEO) satellite communication networks. Interest in these type of systems is fuelled by reduced propagation delays compared to those experienced by geostationary satellites as well as the benefits associated with mobile and tetherless communications. LEO systems are presently being proposed to provide global communications for both voice and data applications. These systems are being designed to provide communications to areas of the world where either public telephone systems do not exist or cannot be provided due to terrain constraints. This paper examines the effects of packet-switched low-Earth orbit satellite systems as a medium for wireless communications. An overview of LEO systems is provided, as well as critical issues associated with the implementation of such a system. The benefits as well as the detriments to the implementation of LEO systems over other types of communication networks are addressed. To illustrate the nature of LEO communications, six representative constellations, varying in size from 36 to 77 satellites and residing at orbital altitudes ranging from 765 to 1549 kilometers, are examined.