LEO Satellite Constellation Design Method for Continuous Coverage

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

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.

Aiming at the problems of high dynamic topology and limited on-board resources in Low Earth Orbit (LEO) satellite networks leading to poor performance of traditional routing algorithms, this paper combines the centralized control idea of Software-Defined Networking (SDN) with the collective learning ability of the Particle Swarm Optimization (PSO) algorithm to propose an adaptive potential field routing algorithm based on PSO. This algorithm models the network as a dynamic potential field, defines potential energy based on the cumulative congestion degree to guide data packet transmission; adaptively learns and optimizes link cost weights through the PSO mechanism, achieving dynamic evolution of the path evaluation criterion; and adopts a probability-based multi-path forwarding mechanism to achieve load balancing. Simulation results show that compared to traditional algorithms such as Dijkstra and ACO (Ant Colony Optimization), this algorithm significantly improves performance in terms of average end-to-end delay, network throughput, and load balancing, especially suitable for dynamic traffic scenarios.

Recent research indicates that self-similarity is a common phenomenon in wired network. However, there are no sufficient studies that focus on the characteristics in wireless network, especially in low earth orbit (LEO) satellite network. This paper presents a practicable model based on analysis of aggregate self-similar traffic and impact on performances of LEO satellite network, and then validate that the traffic in LEO satellite network is self-similar. Then, the quality of service (QoS) measures under self-similar traffic such as queue length and buffer size are discussed.

The precise orbit determination (POD) accuracy of the Chinese BeiDou Navigation Satellite System (BDS) is still not comparable to that of the Global Positioning System because of the unfavorable geometry of the BDS and the uneven distribution of BDS ground monitoring stations. Fortunately, low Earth orbit (LEO) satellites, serving as fast moving stations, can efficiently improve BDS geometry. Nearly all studies on Global Navigation Satellite System POD enhancement using large LEO constellations are based on simulations and their results are usually overly optimistic. The receivers mounted on a spacecraft or an LEO satellite are usually different from geodetic receivers and the observation conditions in space are more challenging than those on the ground. The noise level of spaceborne observations needs to be carefully calibrated. Moreover, spaceborne observational errors caused by space weather events, i.e., solar geomagnetic storms, are usually ignored. Accordingly, in this study, the actual spaceborne observation noises are first analyzed and then used in subsequent observation simulations. Then, the observation residuals from the actual-processed LEO POD during a solar storm on 8 September 2017 are extracted and added to the simulated spaceborne observations. The effect of the observational errors on the BDS POD augmented with different LEO constellation configurations is analyzed. The results indicate that the noise levels from the Swarm-A, GRACE-A, and Sentinel-3A satellites are different and that the carrier-phase measurement noise ranges from 2 mm to 6 mm. Such different noise levels for LEO spaceborne observations cause considerable differences in the BDS POD solutions. Experiments calculating the augmented BDS POD for different LEO constellations considering spaceborne observational errors extracted from the solar storm indicate that these errors have a significant influence on the accuracy of the BDS POD. The 3D root mean squares of the BDS GEO, IGSO, and MEO satellite orbits are 1.30 m, 1.16 m, and 1.02 m, respectively, with a Walker 2/1/0 LEO constellation, and increase to 1.57 m, 1.72 m, and 1.32 m, respectively, with a Walker 12/3/1 constellation. When the number of LEO satellites increases to 60, the precision of the BDS POD improves significantly to 0.89 m, 0.77 m, and 0.69 m for the GEO, IGSO, and MEO satellites, respectively. While 12 satellites are sufficient to enhance the BDS POD to the sub-decimeter level, up to 60 satellites can effectively reduce the influence of large spaceborne observational errors, i.e., from solar storms.

The rapid expansion of low Earth orbit (LEO) satellite networks to improve global internet access has raised concerns about their environmental impact compared to terrestrial infrastructure. This study conducts a panel lifecycle assessment (LCA) and econometric analysis to compare the carbon intensity of LEO satellite and terrestrial fibre-optic networks across 100 countries from 2005 to 2023. Using ISO 14040-compliant LCA, we find LEO systems emit 0.1–0.5 kg CO₂e/GB, significantly higher than terrestrial systems (0.05–0.20 kg CO₂e/GB), with these emissions generated primarily during the launch (40%) and operational (35%) phases. Fixed-effects regression reveals that internet usage increases CO₂ emissions per capita (β = 0.1435, p < 0.01), while the share of renewable energy reduces emissions (β = –95.1288, p < 0.05), with LEO penetration having only a minimal impact (β = 0.0012, p = 0.332). Advanced two-stage least squares, Arellano-Bond generalized method of moments, Moran’s I (I = 0.12, p = 0.08), and random forest analyses confirm these findings, highlighting renewables and internet usage as key drivers of emissions. The findings suggest that emissions reporting frameworks and renewable energy integration may play an important role in aligning digital connectivity expansion with climate goals. These results highlight the need for sustainable digital infrastructure to balance global connectivity with planetary boundaries.

According to previous studies, the UDLs (user data links) or ISLs (intersatellite links) switch and failure can result in the packet reordering in Low Earth Orbit (LEO) satellite networks. The packet reordering can severely deteriorate the performance of transmission in LEO satellite networks, especially at very high levels of packet reordering. In order to improve the TCP (Transmission Control Protocol) performance in LEO satellite networks, this paper proposes a modified TCP variant named TCP-D-SACK, which is based on the TCP-SACK. Our results indicate that the new TCP variant can improve the throughput.

Recently, more research attention has been focused on LEO (Low Earth Orbit) satellite networks connected to ISL (Inter Satellite Link). If terrestrial and LEO satellite networks are seamlessly interconnected by TCP/IP protocols, a global network that covers the whole earth can be integrated into the Internet. However, handover and rerouting issues in LEO satellite networks cause delay variance, and the delay variance can degrade performance of TCP, originally designed for wired networks, because of unnecessary retransmission. In this paper, we propose a method for avoiding the unnecessary retransmission by using the TTL (Time To Live) field in IP headers. Our simulation results show how our mechanism is effectively avoiding unnecessary retransmissions. © 2004 Wiley Periodicals, Inc. Electron Comm Jpn Pt 1, 88(1): 64–71, 2005; Published online in Wiley InterScience (www.interscience.wiley. com). DOI 10.1002/ecja.10205

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.

The low earth orbit (LEO) satellite network has the potential to provide low-latency transmission for global Internet services. Due to the mobility of LEO satellites, the frequent handover between a ground station (GS) and satellites will significantly affect the quality of content delivery. To overcome this challenge, we propose a multicast source routing mechanism for large-scale LEO satellite networks. This mechanism enables the source satellite to flexibly select the routes towards multiple satellites covering the same GS, thus ensures seamless satellite handover. Different from IP-based multicast, our approach assigns link identifiers for each unidirectional inter-satellite link, which can enable us to achieve reliable and efficient packet forwarding. Specifically, we design the equivalent virtual links based on the link identifiers, which can mitigate the impact of occasional link failures by forwarding the packets via the alternative route. Moreover, we use two bloom filters to encode the route (i.e., physical and virtual link identifiers) into the packet header. This way, the intermediate satellites could efficiently forward the packet according to its link identifier table. We evaluate the performance of the proposed mechanism via packet-level simulation on OMNeT++. Results show that our proposed method outperforms IP-based routing in terms of end-to-end delay and delivery ratio.

Low Earth Orbit (LEO) satellite networks are playing an important role in current global mobile communications. An optimized handover scheme can greatly improve performance in respect of end-to-end communication delay and link bandwidth utilization of LEO satellite networks. Various handover schemes in LEO satellite networks are researched in this paper. Ground-satellite link handover and recomputing routes problem is analyzed in detail. Then, a link handover algorithm for LEO satellite mobile communication network is proposed. Simulation results show that the satellite link handover algorithm proposed has less end-to-end delay, and is more stable and customizable.KeywordsSatellite NetworkHandover SchemeDynamic Channel AllocationHandover ManagementHandover AlgorithmThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

As an integral component of the space-air-ground integrated network (SAGIN), the low Earth orbit (LEO) satellite network has displayed immense potential in providing ubiquitous connectivity and broadband mobile communication. However, the intrinsic dynamics of LEO satellites pose unprecedented challenges in network management and service delivery. In this paper, we investigate the service function chain (SFC) orchestration in dynamic LEO satellite networks to achieve flexible and efficient service provision. Considering the service requirements and the limitations of network resources, we formulate the SFC orchestration problem as the integer nonlinear programming (INLP) problem for maximizing the service acceptance and the load fairness of satellites. Then, an efficient heuristic algorithm is proposed to solve this problem. Addressing the situation with frequent service requests, a graph attention network (GAT)-based approach with low complexity is also presented. Simulation results demonstrate that our proposed approaches outperform the benchmarks by a substantial margin in terms of load fairness and service acceptance. Besides, the proposed GAT-based approach shows its advantage in computation complexity, and exhibits robustness in unstable network scenarios with intermittent link interruptions.

A low earth orbit (LEO) observation satellite offers a shorter distance to the target area, low cost, and low communication latency. The low orbit translates to high orbital speed and results in short observation and communication contact periods. Swarms of multiple satellites offer extended coverage and spatial resolution for applications such as earth observation and monitoring. LEO communication satellite constellations create a network that includes hundreds to tens of thousands of satellites with onboard processing capabilities (as routing nodes) connected by Inter-Satellite Links (ISL) that provide continuous coverage of the earth. The LEO constellations aim to provide end-to-end routing between multiple gateways and terminals. This paper assumes the LEO constellation satellite payload includes sensors and processing capabilities. We explore the problem of managing an autonomous LEO virtual satellite swarm that will provide continuous and adjustable coverage. We preset a novel virtual swarm: a subset of the constellation satellites is dynamically assigned to the swarm when they cover the target area. The virtual swarm algorithm provides distributed data synchronization among the swarm virtual satellites and a distributed dynamic assignment of physical satellites to the virtual swarm satellites.

We propose a routing methodology for multi-hop low Earth orbit (LEO) satellite networks aiming at minimising the number of link handovers per connection, while at the same time satisfying QoS requirements. For the representation of the network topology, an approach with a graph method is used, where a new metric for inter-satellite links, called lifetime, is introduced. This metric is then considered for minimisation of connection re-routing attempts due to the connectivity changes. In addition to this, we propose a QoS-based routing strategy for multi-service LEO satellite networks, for which the so-called per service performance is studied by numerical examples.

Reinforcement learning based dynamic distributed routing scheme for mega LEO satellite networks