LEO Satellite Research Articles

Deep Learning Forecasting and Statistical Modeling for Q/V-Band LEO Satellite Channels

As the number of satellite networks increases, the radio spectrum is becoming more congested, prompting the need to explore higher frequencies. However, it is more difficult to operate at higher frequencies due to severe impairments caused by varying atmospheric conditions. Hence, radio channel forecasting is crucial for operators to adjust and maintain the link’s quality. This paper presents a practical approach for Q/V-band modeling for low Earth orbit satellite channels based on tools from machine learning and statistical modeling. The developed Q/V-band LEO satellite channel model is composed of; (i) forecasting method using model-based deep learning, intended for real-time operation of satellite terminals, and (ii) statistical channel simulator that generates a time-series path-loss random process, intended for system design and research. Both approaches capitalize on real-measurements obtained from Al-phaSat’s Q/V-band transmitter at different geographic latitudes. The results show that model-based deep learning can outperform simple statistical and deep learning methods by at least 50%. Moreover, the model is capable of incorporating varying rain and elevation angle profiles.

K-/Ka-Band Shared-Aperture Phased Array With Wide Bandwidth and Wide Beam Coverage for LEO Satellite Communication

A K-/Ka-band shared-aperture endfire phased array antenna is presented in this article. The antenna has the properties of dual wide bandwidths, orthogonal circular polarizations (CPs), wide beam coverage, and high isolation between the K-band and Ka-band channels. In this work, a new array topology is proposed to enhance the design freedom and the periodicity of the antenna array. Then, the filtering structures used to reflect the crossband coupled power also enhance the isolation between the K-band and Ka-band channels. The crossband mutual coupling is reflected and reradiated to generate the wideband CP beams. The high-order parallel plate waveguide (PPW) mode is suppressed to realize the wide CP beam coverage. The working bands at the boresight are 17.7–21.2 and 27.5–31.0 GHz, respectively. The polarizations are right-hand CP (RHCP) in K-band and left-hand CP (LHCP) in Ka-band. The maximal scan angles are ±60°. The axial ratios (ARs) are below 3 dB at boresight and below 5 dB when the beam scans to ±60°. The isolation between the K-band and Ka-band channels is higher than 40 dB.

Distance-Based Back-Pressure Routing for Load-Balancing LEO Satellite Networks

Featuring wide coverage and high data rate, LEO satellite networks will be an important supplement to the traditional terrestrial networks, enabling the space-air-ground integrated network service. However, effective load balancing routing strategies for LEO satellite networks need to be designed, due to the bursty characteristic of the network traffic and imbalanced regional communication load. To achieve that, we propose a Distance-based Back-Pressure Routing (DBPR) strategy for LEO satellite networks. DBPR calculates the link weights based on a novel distance-based metric, which can select uncongested short-distance paths to the destinations and distribute network traffic dynamically with low delay. To control the number of forwardings in the network, we restrict the transmission range to a rectangle region between each source-destination pair. We design DBPR in the distributed fashion without collecting the global network load information, which is suitable for LEO satellite networks with limited resources, long propagation delay, dynamic topology, etc. We analyze the network stability and prove the throughput optimality of DBPR. Simulation results demonstrate that DBPR can achieve higher throughput and lower delay, compared with the state-of-the-art strategies, especially in the environments with limited cache resource.

Sensor Fusion Based on Mathematical Model of LEO Satellite

In this study, the mathematical model of attitude motion is obtained for low orbit sattelite (LEO) with its kinematic and dynamic equations. The mathematical model of orbit motion for LEO satellite is obtained using Kepler parameters. Sensor data are generated adding zero mean Gaussian noise to data comes from model response. These measurement data are fused using INS/GPS integration structure. Extended Kalman filter algorithm is used to sensor fusion. Compare the estimated data comes from extended Kalman filter and the actual data generated from mathematical model. It has been observed from the results that the estimated data is closest to the actual attitude data. All study is performed at the MATLAB/Simulink environment.

Multi-Static Multi-Band Synthetic Aperture Radar (SAR) Constellation Based on Integrated Photonic Circuits

Multi-static SARs from LEO orbits allow the single-pass high-resolution imaging and detection of moving targets. A coherent MIMO approach requires the generation of multi-band, thus orthogonal, signals, the fusion of which increases the system resolution. Up to now the synchronization capability of SAR signals of different satellites is critical. Here, we propose the use of photonics to generate, receive and distribute the radar signals in a coherent multi-static SAR constellation. Photonics overcomes issues in the implementation of MIMO SAR, allowing for the flexible generation of multi-band signals and centralized generation in a primary satellite with coherent distribution to all the secondary satellites of the SAR signals over FSO links. The numerical analysis shows the proposed system has a NESZ < −29.6 dB, satisfying the SAR system requirements. An experimental proof of concept based on COTS, for both signal up- and down-conversion, is implemented to demonstrate the system functionality, showing performance similar to the simulations. The implementation of the proposed systems with integrated technologies could reduce the system SWaP and increase robustness to vibrations. A design based on the consolidated SOI platform with the transfer printing-based hybrid integration of InP semiconductor optical amplifiers is proposed. The amplifiers compensate for the losses of the passive SOI waveguides, decreasing the overall conversion loss. The polarization multiplexing of the modulated and unmodulated combs to be sent from (to) the primary to (from) the secondary satellite over the FSO links avoids complex space-consuming optical filters requiring several control signals.

A high dynamic weak spread spectrum signal acquisition strategy based on the transfer model

To solve the problem of low Earth orbit (Leo) satellite constellation link spread spectrum signal acquisition in the high dynamic weak environment, this paper proposes a acquisition strategy based on transfer model. In this paper, we analyze the dynamic characteristics of link signal. An improved method of parallel code phase search acquisition based on transfer model acquisition strategy is introduced, the improvement of the proposed acquisition strategy to the traditional acquisition algorithm is illustrated through theoretical analysis. Simulation results verify the superiority of the acquisition strategy based on the transfer model for high dynamic weak signal acquisition.

Data-Driven In-Orbit Current and Voltage Prediction Using Bi-LSTM for LEO Satellite Lithium-Ion Battery SOC Estimation

Accurate estimation of the battery system state of charge (SOC) is essential to the satellite mission design and fault management. However, it is difficult for low Earth orbit satellites to continuously monitor the battery SOC on the ground due to the noncontact duration. To estimate the battery SOC for the entire orbit, it is necessary to predict or monitor the battery data for all times. Therefore, existing studies use SOC estimation that relies on real-time onboard battery information or utilizes probability-based technique and power budget-based technique. The real-time onboard-based technique is unsuitable for mission design because the status information is not available to the ground during the noncontact duration. Probability-based and power budget-based techniques are not reliable during the noncontact duration. In this study, we propose the ground-based battery SOC estimation technique that predicts the current and voltage by using the bidirectional long short-term memory network for the noncontact duration and estimates the SOC by the unscented Kalman filter for all operating conditions. The proposed technique is tested with in-orbit data of the KOMPSAT-3A satellite, and we demonstrate its superior performance than other conventional ground-based SOC estimation techniques.

LDM-satellite: A new scheme for packet loss classification over LEO satellite network

The packet loss classification has always been a hot and difficult issue in TCP congestion control research. Compared with the terrestrial network, the probability of packet loss in LEO satellite network increases dramatically. What's more, the problem of concept drifting is also more serious, which greatly affects the accuracy of the loss classification model. In this paper, we propose a new loss classification scheme based on concept drift detection and hybrid integration learning for LEO satellite networks, named LDM-Satellite, which consists of three modules: concept drift detection, lost packet cache and hybrid integration classification. As far, this is the first paper to consider the influence of concept drift on the loss classification model in satellite networks. We also innovatively use multiple base classifiers and a naive Bayes classifier as the final hybrid classifier. And a new weight algorithm for these classifiers is given. In ns-2 simulation, LDM-Satellite has a better AUC (0.9885) than the single-model machine learning classification algorithms. The accuracy of loss classification even exceeds 98%, higher than traditional TCP protocols. Moreover, compared with the existing protocols used for satellite networks, LDM-Satellite not only improves the throughput rate but also has good fairness.

DNN Beamforming for LEO Satellite Communication at Sub-THz Bands

The 6G communication system will be designed at sub-THz frequencies due to increasing demand in data rates, emerging new applications and advanced communication technologies. These high-performing systems will heavily rely on artificial intelligence (AI) for efficient and robust design of transceivers. In this work, we propose a deep neural network (DNN) beamformer that will replace the use of phase shifters for a massive array of antenna elements employed at the ground station for wideband LEO satellite communication at sub-THz bands. We show that the signal processing algorithm employed using DNN is capable to match the performance of a true-time delay beamformer as the angle of arrival of the received wideband signal at the ground station is changing due to rapid movement of the LEO satellite. The implementation of DNN beamformer will be able to reduce the cost of receiver and provide a way for the efficient and compact design of the massive array beamforming for wideband LEO satellite applications.

A Framework for Distributed LEO SAR Air Moving Target 3D Imaging via Spectral Estimation

This paper aims to perform imaging and detect moving targets in a 3D scene for space-borne air moving target indication (AMTI). Specifically, we propose a feasible framework for distributed LEO space-borne SAR air moving target 3D imaging via spectral estimation. This framework contains four subsystems: the distributed LEO satellite and radar modeling, moving target information processing, baseline design framework, and spectrum estimation 3D imaging. Firstly in our method, we develop a relative motion model between the satellite platform and the 3D moving target for satellite and radar modeling. In a very short time, the relative motion between the platform and the target is approximated as a uniform motion. We then establish the space-borne distributed SAR moving target 3D imaging model based on the motion model. After that, we analyze the influencing factors, including the Doppler parameters, the three-dimensional velocity, acceleration, and baseline intervals, and further investigate the performance of the 3D imaging of the moving target. The moving target spectrum estimation 3D imaging finally obtains the 3D imaging results of the target, which preliminarily solves the imaging and resolution problems of slow air moving targets. Simulations are conducted to verify the effectiveness of the proposed distributed LEO space-borne SAR moving target 3D imaging framework.

Energy-Efficient Controller Placement in Software-Defined Satellite-Terrestrial Integrated Network

The satellite-terrestrial integrated network (STIN), as an integration of the satellite network and terrestrial, has become a promising architecture to support global coverage and ubiquitous connection. The architecture of software-defined networking (SDN) is utilized to intelligently coordinate the global STIN, in which the placement schemes of SDN controllers, including the locations, number, and roles, would produce various performances. However, the uneven distribution of global users leads to the unbalanced energy consumption of satellite resources, which brings a heavy burden for satellites to maintain the control flows for network management. To provide green communication for international economic trade in the countries along the Belt and Road, in this paper, we focus on the energy-efficient controller placement (EECP) problem in the software-defined STIN. The satellite gateways are located in the countries along the Belt and Road, which accounts for a large number of traffic demands and a dense population. The controllers are deployed on the LEO satellites, where each LEO satellite is a candidate controller. The energy consumption for the control paths and the user data links is modeled and then formulated as the flow processing-oriented optimization problem. A modified simulated annealing placement (MSAP) algorithm is developed to solve the EECP problem, in which we use the greedy way to obtain the initial set of controllers, and then the final optimal controller placement result is obtained by the simulated annealing algorithm. Extensive simulations are conducted on the simulated Iridium satellite network topology and statistics data. Compared with other algorithms, the results show that MSAP reduces network energy consumption by 20% and average latency by 25%.

Matching-Based Resource Allocation for Satellite-Ground Network.

With the vigorous development of information and communication technology, mobile internet has undergone tremendous changes. How to achieve global coverage of the network has become the primary problem to be solved. GEO satellites and LEO satellites, as important components of the satellite-ground network, can offer service for hotspots or distant regions where ground-based base stations' coverage is limited. Therefore, we build a satellite-ground network model, which transforms the satellite-ground network resource allocation problem into a matching issue between GEO satellites, LEO satellites, and users. A GEO satellite provides data backhaul for users, and a LEO satellite provides data transmission services according to users' requests. It is important to consider the relationships between all entities and establish a distributed scheme, so we propose a three-sided cyclic matching algorithm. It is confirmed by a large number of simulation experiments that the method suggested in this research is better than the conventional algorithm in terms of average delay, satellite revenue, and number of users served.

High-order ionospheric delay correction of GNSS data for precise reduced-dynamic determination of LEO satellite orbits: cases of GOCE, GRACE, and SWARM

High-order ionospheric delay correction of GNSS data for precise reduced-dynamic determination of LEO satellite orbits: cases of GOCE, GRACE, and SWARM

Precise real-time navigation of the small TJU-1 satellite using GPS, GLONASS and BDS

Precise real-time navigation of the small Tianjin University-1 (TJU-1) satellite based on GPS, GLONASS, BDS-2 and BDS-3 is studied in this contribution for the first time. Experimental results showed that (1) the real-time position accuracies could reach the level of 0.6 ∼ 0.8 m, 0.9 ∼ 1.1 m, 2.0 ∼ 3.5 m and 0.18 ∼ 0.22 m, respectively, for the solutions based on single GPS, GLONASS, BDS-2 and BDS-3; (2) The multi-GNSS fusion could significantly improve the accuracy, reliability and availability of real-time navigation compared with the single-GNSS solution especially when the observation conditions of a single-GNSS are poor or over some anomalous orbit arcs where only few or even no observations are available; (3) a remarkable real-time orbit accuracy of 0.187 m for 3D position is achieved based on BDS-2 + BDS-3 fusion. These accuracy performances have fully demonstrated that, precise real-time navigation based on multi-GNSS measurements would be a very attractive technique for broad small LEO satellite applications requiring the high-precision real-time orbits.

Analytic solution for perturbed Keplerian motion under small acceleration using averaging theory

A novel approach is developed for analytic orbit propagation based on asymptotic expansion with respect to a small perturbative acceleration. The method improves upon existing first order asymptotic expansions by leveraging on linear systems and averaging theories. The solution starts with the linearization of Gauss planetary equations with respect to both the small perturbation and the six orbital elements. Then, an approximate solution is obtained in terms of secular and short period components. The method is tested on a low-thrust maneuver scenario consisting of a Keplerian orbit perturbed by a constant tangential acceleration, for which a solution can be obtained in terms of elliptic integrals. Results show that the positional propagation error is about one order of magnitude smaller with respect to state-of-the-art methods. The position accuracy for a LEO orbit, apart from pathological cases, is typically in the range of tens of meters for a tangential acceleration of 10−7 km/s2 after 5 orbital periods propagation.

Random Access With Massive MIMO-OTFS in LEO Satellite Communications

This paper considers the joint channel estimation and device activity detection in the grant-free random access systems, where a large number of Internet-of-Things devices intend to communicate with a low-earth orbit satellite in a sporadic way. In addition, the massive multiple-input multiple-output (MIMO) with orthogonal time-frequency space (OTFS) modulation is adopted to combat the dynamics of the terrestrial-satellite link. We first analyze the input-output relationship of the single-input single-output OTFS when the large delay and Doppler shift both exist, and then extend it to the grant-free random access with massive MIMO-OTFS. Next, by exploring the sparsity of channel in the delay-Doppler-angle domain, a two-dimensional pattern coupled hierarchical prior with the sparse Bayesian learning and covariance-free method (TDSBL-FM) is developed for the channel estimation. Then, the active devices are detected by computing the energy of the estimated channel. Finally, the generalized approximate message passing algorithm combined with the sparse Bayesian learning and two-dimensional convolution (ConvSBL-GAMP) is proposed to decrease the computations of the TDSBL-FM algorithm. Simulation results demonstrate that the proposed algorithms outperform conventional methods.

A Parallel Robotic Antenna Design for Downlinking Leo Satellite Signal Subject to Wind Disturbance

Passive LEO (Low Earth Orbit) satellites are a telecom premier option. However, LEO satellites impose not only stringent specifications on the resolution, precision and repeatability but also requiring advanced antenna technology for signal downlinking. To efficiently downlink LEO signals at each passage onto a given Earth region, we explored large size passive Earth antenna and an array of smaller size active Earth antennas to minimize the trajectory loss. To guarantee design specifications, the dynamics cannot be neglected given the size and inertia of base and antenna. In this paper, it is proposed the design, path planning and control of a six DoF robotic antenna maneuvering the antenna subject to aerodynamic wind disturbance. The system maneuvers to point at the LEO satellite over the whole envelope with the required precision to guarantee robust point-to-point tracking. Representative simulation results for three geolocations shows practical tracking with off-the-shelf-component actuators, without requiring any knowledge of the dynamics while withstanding state-dependent persistent disturbances.

A Weighted Graph-Based Handover Strategy for Aeronautical Traffic in LEO SatCom Networks

With the development of space-air-ground integrated network (SAGIN), the Low Earth Orbit Satellite Communication (LEO SatCom) network has great potential to provide high rate communication services for aeronautical traffic. To overcome the frequency handovers between aircraft and LEO satellites, we generated a global aeronautical traffic demand map and utilized the graph-based handover (GBH) framework and the multi-attribute decision making (MADM) algorithm jointly to optimize the overall throughput. Moreover, we further propose a new parameter, called channel reservation order (CRO), for MADM algorithm. Simulation results indicate our strategy improves the performance in terms of overall throughput and access failure probability.

Looking at NB-IoT Over LEO Satellite Systems: Design and Evaluation of a Service-Oriented Solution

The adoption of the Narrowband-Internet of Things technology in satellite communications intends to boost Internet of Things services beyond the boundaries imposed by the current terrestrial infrastructures. Apart from link-level studies in the scientific literature and preliminary 3GPP technical reports, the overall debate is still open. To provide a further step forward in this direction, the work presented herein pursues a novel service-oriented methodology to design an effective solution, meticulously stitched around application requirements and technological constraints. To this end, it conducts link-level and system-level investigations to tune physical transmissions, satellite constellation, and protocol architecture, while ensuring the expected system behavior. To offer a real smart agriculture service operating in Europe, the resulting solution exploits 24 low-Earth orbit satellites, grouped into eight different orbits, moving at an altitude of 500 km. The configured protocol stack supports the transmission of tens of bytes generated at the application layer, by also counteracting the issues introduced by the satellite link. Since each satellite has the whole protocol stack onboard, terminals can transmit data without the need for the feeder link. This ensures communication latencies ranging from 16 to 75 min, depending on the served number of terminals and the physical transmission settings. Moreover, the usage of the early data transmission scheme reduces communication latencies up to 40%. These results pave the way toward the deployment of an effective proof of concept, which drastically reduces the time to market imposed by the current state of the art.

A regional interest-aware caching placement scheme for reducing latency in the LEO satellite networks

A regional interest-aware caching placement scheme for reducing latency in the LEO satellite networks