Satellite constellation design and radio resource management using genetic algorithm

The paper describes optimization Non-GEO satellite constellation design with satellite diversity using genetic algorithm. This algorithm is called as genetic satellite constellation algorithm. A rank fitness assignment method of multiobjective optimization is proposed to capture a number of solutions simultaneously. The non-dominated in GA’s is sorted to find the multiple Pareto optimal points. The genetic satellite constellation algorithm is investigated to produce the optimum satellite constellation design with the minimum number of satellites while minimizing the maximum orbit’s altitude, to minimize the angle shift between satellites, to maximize the angle between planes and the inclination angle with satellite diversity. Illustrative results of satellite constellation components and dual satellite diversity statistics for LEO and MEO constellation are presented. The simulation results are compared to ICO for MEO constellation and to Globalstar for LEO constellation. Using genetic algorithm, satellite constellation design can be achieved the visibility of dual satellite diversity statistics whilst reducing the total number of satellites. Genetic algorithm is a robust method ideally suited for satellite constellation design.

As a fundamental and significant stage of satellite networks which play an important role in global communications, a design of satellite constellations with inter-satellite links(ISLs) becomes necessary. An optimization method is proposed to determine both satellite elements and constellation elements using the multi-objective genetic algorithm(GA) in this paper. The objectives to be optimized, which are determined by the elements to be designed, are divided into performance objectives and cost objectives. The former consist of the coverage rate, the ISL range and the minimum elevation while the latter contain the total satellite count, the orbital altitude and the orbital inclination. With the aim of maximizing the performance minimizing the cost, the proposed method tries to achieve a balance among multi objectives and design specific satellite constellations considered in different conditions. Then the constellations designed in different schemes are compared with each other to demonstrate the correctness and effectiveness of the method.

There are two types of strategies to assign the channels to a cell: fixed channel assignment (FCA) and dynamic channel assignment (DCA). The basic characteristics of DCA are presented in comparison with FCA. The authors introduce various DCA strategies and discuss some of most important DCA research topics currently being pursued. In particular, the authors focus on microcellular systems, including a proposed MD (moving direction) strategy. It uses the information a mobile station's (MS's) moving direction with the DCA strategy. A channel is selected among those occupied by MSs moving in the same direction with the concerned MS. In this manner, the MS can still use the same channel at the handover with high probability. DCA requires more radio equipment at each base station than FCA, and it requires elaborate channel assignment control. However, it exploits the limited frequency spectrum efficiently and has a lower forced call-termination rate than FCA when the blocking rates are equal.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

We propose a framework for network-assisted radio resource management in wireless data networks. This type of radio resource management techniques offer implementation and capacity benefits compared to conventional, interference-measurement based, dynamic channel assignment (DCA) algorithms. The basic idea is to use interbase signaling to shift most of the burden of the resource allocation from the air interface to the backbone infrastructure. By exchanging channel assignment as well as other relevant information in real time through the backbone network, each base can calculate the impact of a resource assignment on the system. As a result, rapid interference measurements, which are typically needed to implement DCA schemes, are replaced by a limited amount of path loss measurements and the computation of interference conditions by the base stations. This significantly reduces the measurement and over-the-air signaling requirements, and can also provide an opportunity for a better optimization of the system performance. We focus on two specific algorithms: network-assisted least-interference-based dynamic packet assignment (NA-LI-DPA) and network-assisted dynamic packet assignment with throughput optimization (NA-DPA). NA-LI-DPA closely resembles a least-interference-based dynamic channel assignment algorithm, and NA-DPA attempts to further improve the overall system throughput. The algorithms, as defined, are appropriate for a best-effort data service, where the primary goal is to provide a higher throughput. However, it will be clear from the discussion that it is also feasible to alter the algorithms to optimize performance metrics other than throughput, e.g., to ensure a certain quality of service. We show through simulation that, for a system like enhanced general packet radio service (EGPRS) system, NA-DPA can provide a throughput that is 50% higher than random packet assignment, and 25% higher than that obtained by conventional DCA algorithms.

Today most operational Earth observing satellites reside in low Earth orbits (LEO) at less than 1,000 km altitude, and in geostationary Earth orbits (GEO) at ~35,800 km altitude. These orbits have been the venues of choice for observations, albeit for very different reasons. LEO provides high spatial resolution with low temporal resolution while GEO provides for low spatial resolution, but high temporal resolution. NOAA utilizes both venues for their environmental satellites. The NOAA Polar-orbiting Operational Environmental Satellites (POES) reside in LEO Sun synchronous orbits at approximately 830 km in altitude, as do the Defense Meteorological Satellite Program (DMSP) satellites of the Department of Defense. In the near future the POES and DMSP satellites will be merged into a new satellite system referred to as the National Polar-orbiting Operational Environmental Satellite System (NPOESS). The NOAA Geostationary Operational Environmental Satellite (GOES) system, as the name specifies, resides at the other preferred observational venue of GEO. The Jet Propulsion Laboratory (JPL), under contract to NOAA, has been studying the characteristics of medium Earth orbits (MEO), at altitudes between 1000 and 35,800 km, as an observation venue to answer the question as to whether MEO might capture the attributes of the two traditional venues. This on-going study initially focused on determining the optimal altitude for MEO observations, through numerous trade studies involving altitude, instrument complexity, coverage, radiation environment, data temporality, revisit time, data rates, downlink requirements and other parameters including cost and launch complexity. Once the optimal altitude of 10,400 km had been determined the study proceeded to explore single through multiple MEO satellite constellation performance capabilities using two instrument types, a visible through infrared (IR) imager and IR sounder as the satellites’ payload. The MEO performance capabilities were compared to comparable LEO and GEO satellite constellation capabilities. This portion of the study concluded that indeed for global coverage a constellation of satellites operating in the MEO venue could capture the attributes of those operating in the LEO and GEO venues. Three 8-satellite constellations configurations - Walker, ICO, and Equatorial-Polar (EP) - then were studied to develop more constellation coverage statistics including robustness to individual satellite failure. That study phase concluded that the EP constellation was superior to both the ICO and Walker configurations. The study is presently examining if, and to what extent, the equatorial portion of the EP constellation might provide substantive supplemental data to that collected by the NPOESS and GOES satellite constellations.

In little more than two decades, communications satellite technology has gone from being revolutionary to commonplace, from an idea to world wide service. In both industrialized and developing countries, economic and social progress depends on improved telecommunications. Like other means of transport, telephones, computers, satellites and fiber optic cables and their proper interfaces are essential for moving commercial goods and services. Benefits of satellite communications should in the 1990's be extended to users in all parts of the world through the use of smaller, inexpensive and less sophisticated Earth stations for two way (voice and data), and one way (video, data) use. While earlier satellite systems have been designed and implemented using C and S band communications with satellites in geostationary orbits (GEO), K band communications using VSATs (Very Small Aperture Terminals) have enabled the communications across areas of the US and the world where extensive telecommunications networks did not exist and/or were not affordable. In addition, several systems have been proposed (being built) to provide for the global communication of the mobile users using clusters of smaller, less complex satellites in low Earth orbit (LEG) and medium Earth orbit (MEO). Mobile satellite systems are the future of the satellite communications technology applications. In this presentation, we will briefly summarize the status for satellite communications and then present a comparison of the enabling mobile satellite communications technologies and mobile satellite systems currently being developed. We will also review applications of these systems in public and commercial areas in this presentation. >

Due to the relative orbiting of Low Earth Orbit (LEO) satellite and Medium Earth Orbit (MEO) satellite, the inter-layer links (IIL) of LEO/MEO Double-Layered Satellite Networks (DLSN) have to switch dynamically, resulting in dynamic changes of satellite network topology, which has an impact on the data transmission performance of DLSN. In this paper, the IIL topology of LEO/MEO DLSN is analyzed and simulated. Firstly, the visibility calculation method and establishment strategy of IIL between LEO and MEO satellite as well as the calculation and optimization of system snapshots is analyzed. Then, simulation analysis regarding the number and duration of system snapshots, IIL switching time for LEO, the number of switching IIL in each system snapshot, the number of IILs that each MEO needs to establish are presented. Finally, the future research trends of DLSN IIL topology are discussed, such as how to reduce the maximum IIL number for MEO and so on.

Currently, Global Navigation Satellite Systems (GNSS) do not contribute to the realization of origin and scale of combined global terrestrial reference frame (TRF) solutions due to present system design limitations. The future Galileo-like medium Earth orbit (MEO) constellation, called “Kepler”, proposed by the German Aerospace Center DLR, is characterized by a low Earth orbit (LEO) segment and the innovative key features of optical inter-satellite links (ISL) delivering highly precise range measurements and of optical frequency references enabling a perfect time synchronization within the complete constellation. In this study, the potential improvements of the Kepler constellation on the TRF origin and scale are assessed by simulations. The fully developed Kepler system allows significant improvements of the geocenter estimates (realized TRF origin in long-term). In particular, we find improvements by factors of 43 for the Z and of 8 for the X and Y component w. r. t. a contemporary MEO-only constellation. Furthermore, the Kepler constellation increases the reliability due to a complete de-correlation of the geocenter coordinates and the orbit parameters related to the solar radiation pressure modeling (SRP). However, biases in SRP modeling cause biased geocenter estimates and the ISL of Kepler can only partly compensate this effect. The realized scale enabling all Kepler features improves by 34% w. r. t. MEO-only. The dependency of the estimated satellite antenna phase center offsets (PCOs) upon the underlying TRF impedes a scale realization by GNSS. In order to realize the network scale with 1 mm accuracy, the PCOs have to be known within 2 cm for the MEO and 4 mm for the LEO satellites. Independently, the scale can be realized by estimating the MEO PCOs and by simultaneously fixing the LEO PCOs. This requires very accurate LEO PCOs; the simulations suggest them to be smaller than 1 mm in order to keep scale changes below 1 mm.

We propose a new Cochannel information based Dynamic Channel Assignment (CDCA) strategy for small and microcell systems and a new Group Dynamic Channel Assignment (GDCA) strategy which handles multichannel traffic in wireless networks. Copyright © 1999 John Wiley & Sons, Ltd.

This paper presents a theoretical analysis of the potential risk posed by artificial debris clouds in low Earth orbit (LEO) from mega-constellations, modeled after current communication constellations such as Starlink and OneWeb with 750 satellites each. The analysis examines three different constellation designs: a low-altitude LEO, a high-altitude LEO, and a medium Earth orbit (MEO) constellation, which will be positioned using the Walker-Delta design. The study is based on physics-based digital mission engineering and a Monte Carlo simulation framework. The simulation involves debris generated from a single breakup of one randomly selected satellite per run, but does not consider cascading debris events. This debris cloud is propagated for 1 week and how it interacts with the mega-constellation is recorded. The results show an average of 705.65 potential conjunctions within the LEO constellation, with 14.40% of those being considered catastrophic, and an average of 165.5 conjunctions in the MEO constellation, with 0.72% considered catastrophic.

Precise orbit and Earth parameter determination supported by LEO satellites, inter-satellite links and synchronized clocks of a future GNSS

The Earth is surrounded by a swarm of satellites and associated debris known as Resident Space Objects (RSOs). All RSOs will orbit the Earth until they reentry into Earth’s atmosphere. There are three main RSO categories: Low Earth Orbit (LEO), when the satellite orbits at an altitude below 1 500 km; a Medium Earth Orbit (MEO) for Global Navigation Satellite Systems (GNSS) at an altitude of around 20 000 km, and a Geostationary Earth Orbit (GEO) (also sometimes called the Clarke orbit), for geostationary satellites, at an altitude of 36 000 km. The Geostationary Earth Orbits and the orbits of higher altitude are also known as High Earth Orbits (HEO). Crucial for keeping an eye on RSOs, the Surveillance of Space (SofS) comprises detection, tracking, propagation of orbital parameters, cataloguing and analysis of these objects. This paper presents a large baseline stereovision based approach for detection and ranging of RSO orbiting at medium to high altitudes. Two identical observation systems, consisting of camera, telescope, control computer and GPS receiver are located 37 km apart, and set to observe the same region of the sky. The telescopes are placed on equatorial mounts able to compensate for the Earth’s rotation, so that the stars appear stationary in the acquired images, and the satellites will appear as linear streaks. The two cameras are triggered simultaneously. The satellite streaks are detected in each image of the stereo pair using its streak-like appearance against point-like stars, the motion of the streaks between successive frames, and the stereo disparity. The detected satellite pixels are then put into correspondence using the epipolar geometry, and the 3D position of the satellite in the Earth Center, Earth Fixed (ECEF) reference frame is computed using stereo triangulation. Preliminary tests have been performed, for both MEO and HEO orbits. The preliminary results indicate a very high detection rate for MEO orbits, and good detection rate for HEO orbits, dependent on the satellite’s rotation.

Global and regional satellite navigation systems are constellations orbiting the Earth and transmitting radio signals for determining position and velocity of users around the globe. The state-of-the-art navigation satellite systems are located in medium Earth orbits and geosynchronous Earth orbits and are characterized by high launching, building and maintenance costs. For applications that require only regional coverage, the continuous and global coverage that existing systems provide may be unnecessary. Thus, a nano-satellites-based regional navigation satellite system in Low Earth Orbit (LEO), with significantly reduced launching, building and maintenance costs, can be considered. Thus, this paper is aimed at developing a LEO constellation optimization and design method, using genetic algorithms and gradient-based optimization. The preliminary results of this study include 268 LEO constellations, aimed at regional navigation in an approximately 1000 km $$\times $$ 1000 km area centered at the geographic coordinates [30, 30] degrees. The constellations performance is examined using simulations, and the figures of merit include total coverage time, revisit time, and geometric dilution of precision (GDOP) percentiles. The GDOP is a quantity that determines the positioning solution accuracy and solely depends on the spatial geometry of the satellites. Whereas the optimization method takes into account only the Earth’s second zonal harmonic coefficient, the simulations include the Earth’s gravitational field with zonal and tesseral harmonics up to degree 10 and order 10, Solar radiation pressure, drag, and the lunisolar gravitational perturbation.

In cellular mobile communications, how to achieve optimum system capacity with limited frequency spectrum is one of the main research issues. Many dynamic channel assignment (DCA) schemes have been proposed and studied to increase the capacity of cellular systems. Reuse partitioning (RP) is another technique to achieve higher capacity by reducing the overall reuse distance. In this paper, a new network-based DCA scheme with the use of RP technique is proposed, namely dynamic reuse partitioning with interference information (DRP-WI). The scheme aims to minimize the effect of assigned channels on the availability of channels for use in the interfering cells and to reduce their overall reuse distances. Simulation results have confirmed the effectiveness of DRP-WI scheme. Under both uniform and nonuniform traffic distributions, DRP-WI exhibits outstanding performance in improving the system capacity. It can provide about 100% capacity improvement as compared to conventional fixed channel assignment scheme.

The increasing demand for ultra-low-latency and high-throughput communication necessitates network architectures capable of ensuring reliable real-time connectivity. To address this requirement, integrated architectures combining terrestrial networks (TN) and non-terrestrial networks (NTN)—particularly hierarchical multi-layer satellite systems composed of geostationary Earth orbit (GEO), medium Earth orbit (MEO), and low Earth orbit (LEO) satellites—have attracted considerable attention. Such hierarchical systems offer global coverage, low latency, and high capacity. However, their highly dynamic topology, fast-moving satellites, and fluctuating link quality pose significant challenges to establishing efficient end-to-end routing paths. Traditional routing methods based on static paths or centralized control lack the adaptability required for such environments. To address these challenges, this paper introduces a neural hierarchical reinforcement learning (HRL)-based routing algorithm for satellite networks. The framework exploits the layered structure of GEO, MEO, and LEO satellites, enabling gateway-assisted routing and adaptive path selection. Control responsibilities are distributed across orbital layers: the GEO layer allocates hop-count budgets, the MEO layer selects feasible LEO paths, and the LEO layer forwards data packets. When inter-satellite links are unavailable, terrestrial gateways provide alternative routes. Routing decisions further account for satellite-to-satellite and satellite-to-ground link quality, with an end-to-end delay-based reward function capturing transmission, processing, and propagation effects. Simulation results show that the proposed neural hierarchical framework, supported by integrated terrestrial and non-terrestrial networking, achieves faster convergence, greater route stability, and better adaptability than conventional routing algorithms and HRL approaches.