In Low Earth Orbit (LEO) mega constellations, there are relevant use cases, such as inference based on satellite imaging, in which a large number of satellites collaboratively train a machine learning model without sharing their local datasets. To address this problem, we propose a new set of algorithms based on Federated learning (FL), including a novel asynchronous FL procedure based on FedAvg that exhibits better robustness against heterogeneous scenarios than the state-of-the-art. Extensive numerical evaluations based on MNIST and CIFAR-10 datasets highlight the fast convergence speed and excellent asymptotic test accuracy of the proposed method.
Missouri University of Science and Technology（密苏里科技大学）
Low Earth Orbit (LEO) satellite constellations have seen a surge in deployment over the past few years by virtue of their ability to provide broadband Internet access as well as to collect vast amounts of Earth observational data that can be utilized to develop AI on a global scale. As traditional machine learning (ML) approaches that train a model by downloading satellite data to a ground station (GS) are not practical, Federated Learning (FL) offers a potential solution. However, existing FL approaches cannot be readily applied because of their excessively prolonged training time caused by t…
Missouri University of Science and Technology（密苏里科技大学）
Low Earth Orbit (LEO) constellations, each comprising a large number of satellites, have become a new source of big data "from the sky". Downloading such data to a ground station (GS) for big data analytics demands very high bandwidth and involves large propagation delays. Federated Learning (FL) offers a promising solution because it allows data to stay in-situ (never leaving satellites) and it only needs to transmit machine learning model parameters (trained on the satellites' data). However, the conventional, synchronous FL process can take several days to train a single FL model in the con…
Missouri University of Science and Technology（密苏里科技大学）
The advances in satellite technology developments have recently seen a large number of small satellites being launched into space on Low Earth orbit (LEO) to collect massive data such as Earth observational imagery. The traditional way which downloads such data to a ground station (GS) to train a machine learning (ML) model is not desirable due to the bandwidth limitation and intermittent connectivity between LEO satellites and the GS. Satellite edge computing (SEC), on the other hand, allows each satellite to train an ML model onboard and uploads only the model to the GS which appears to be a…
Royal Institute of Technology (KTH)（皇家理工学院（KTH））；ABB Corporate Research Sweden（瑞典ABB企业研究中心）
Driven by the ever-increasing penetration and proliferation of data-driven applications, a new generation of wireless communication, the sixth-generation (6G) mobile system enhanced by artificial intelligence (AI), has attracted substantial research interests. Among various candidate technologies of 6G, low earth orbit (LEO) satellites have appealing characteristics of ubiquitous wireless access. However, the costs of satellite communication (SatCom) are still high, relative to counterparts of ground mobile networks. To support massively interconnected devices with intelligent adaptive learnin…
SFL-LEO: Asynchronous Split-Federated Learning Design for LEO Satellite-Ground Network Framework
Institute of Space Internet, Fudan University（复旦大学空间互联网研究所）；School of Computer Science, Fudan University（复旦大学计算机学院）；School of Information Science and Technology, Fudan University（复旦大学信息科学与技术学院）
Accelerating Privacy-Preserving Federated Learning in Large-Scale LEO Satellite Systems
School of Telecommunication Engineering, Xidian University（电信工程学院，西安电子科技大学）；Tianjin Artificial Intelligence Innovation Center (TAIIC)（天津人工智能创新中心）；Pillar of ISTD, Singapore University of Technology and Design（ISTD支柱，新加坡科技与设计大学）；School of Electrical and Electronic Engineering, Nanyang Technological University（电子与电气工程学院，南洋理工大学）；Department of Electrical and Computer Engineering, University of Houston（电气与计算机工程系，休斯顿大学）
National Yang Ming Chiao Tung University（国立阳明交通大学）；University of Southampton（南安普顿大学）；Hon Hai Research Institute（鸿海研究院）
Low Earth orbit (LEO) satellite constellation is capable of providing global coverage area with high-rate services in the next sixth-generation (6G) non-terrestrial network (NTN). Due to limited onboard resources of operating power, beams, and channels, resilient and efficient resource management has become compellingly imperative under complex interference cases. However, different from conventional terrestrial base stations, LEO is deployed at considerable height and under high mobility, inducing substantially long delay and interference during transmission. As a result, acquiring the accura…
Distributed training of machine learning models directly on satellites in low Earth orbit (LEO) is considered. Based on a federated learning (FL) algorithm specifically targeted at the unique challenges of the satellite scenario, we design a scheduler that exploits the predictability of visiting times between ground stations (GS) and satellites to reduce model staleness. Numerical experiments show that this can improve the convergence speed by a factor three.
Pulsar Constellation Evolution and PPP Convergence using LEO GNSS
Xona Space Systems（Xona太空系统公司）；University of Calgary（卡尔加里大学）；BITS Pilani（比蒂斯皮拉尼理工学院）；VTU, India（印度维斯瓦塔德大学）；Cranfield University（克兰菲尔德大学）；The University of Nottingham（诺丁汉大学）；Ford Motor Company（福特汽车公司）；Google（谷歌）；Stanford University（斯坦福大学）；Queen's University, Canada（加拿大女王大学）；Qatar University（卡塔尔大学）
Mega-constellations of small-size Low Earth Orbit (LEO) satellites are currently planned and deployed by various private and public entities. While global connectivity is the main rationale, these constellations also offer the potential to gather immense amounts of data, e.g., for Earth observation. Power and bandwidth constraints together with motives like privacy, limiting delay, or resiliency make it desirable to process this data directly within the constellation. We consider the implementation of on-board federated learning (FL) orchestrated by an out-of-constellation parameter server (PS…
The next frontier towards truly ubiquitous connectivity is the use of Low Earth Orbit (LEO) small-satellite constellations to support 5G and Beyond-5G (B5G) networks. Besides enhanced mobile broadband (eMBB) and massive machine-type communications (mMTC), LEO constellations can support ultra-reliable communications (URC) with relaxed latency requirements of a few tens of milliseconds. Small-satellite impairments and the use of low orbits pose major challenges to the design and performance of these networks, but also open new innovation opportunities. This paper provides a comprehensive overvie…
LEO Constellations as a Decentralized GNSS Network: Optimizing PNT Corrections in Space
Universitat Autònoma de Barcelona (UAB)（巴塞罗那自治大学）；Institute for Space Studies of Catalonia (IEEC)（加泰罗尼亚太空研究所）；King Abdullah University of Science and Technology (KAUST)（阿卜杜拉国王科技大学）
The rapid development of communication technologies in the past decades has provided immense vertical opportunities for individuals and enterprises. However, conventional terrestrial cellular networks have unfortunately neglected the huge geographical digital divide, since high bandwidth wireless coverage is concentrated to urban areas. To meet the goal of ``connecting the unconnected'', integrating low Earth orbit (LEO) satellites with the terrestrial cellular networks has been widely considered as a promising solution. In this article, we first introduce the development roadmap of LEO satell…
DRL-Based Beam Positioning for LEO Satellite Constellations with Weighted Least Squares
Research Center for Information Technology Innovation (CITI), Academia Sinica (AS)（信息科技创新研究中心（CITI），中国科学院（AS））；Department of Electrical Engineering, National Taiwan Normal University (NTNU)（电气工程系，国立台湾师范大学（NTNU））；Bradley Department of Electrical and Computer Engineering (ECE), Virginia Tech (VT)（电气与计算机工程系（ECE），弗吉尼亚理工学院（VT））
Physical layer authentication (PLA) is the process of claiming identity of a node based on its physical layer characteristics such as channel fading or hardware imperfections. In this work, we propose a novel PLA method for the inter-satellite communication links (ISLs) of the LEO satellites. In the proposed PLA method, multiple receiving satellites validate the identity of the transmitter by comparing the Doppler frequency measurements with the reference mobility information of the legitimate transmitter and then fuse their decision considering the selected decision rule. Analytical expressio…
5G NB-IoT is seen as a key technology for providing truly ubiquitous, global 5G coverage (1.000.000 devices/km2) for machine type communications in the internet of things. A non-terrestrial network (NTN) variant of NB-IoT is being standardized in the 3GPP, which along with inexpensive and non-complex chip-sets enables the production of competitively priced IoT devices with truly global coverage. NB-IoT allows for narrowband single carrier transmissions in the uplink, which improves the uplink link-budget by as much as 16.8 dB over the 180 [kHz] downlink. This allows for a long range sufficient…
The integration of Low Earth Orbit (LEO) satellite constellations into 5G and Beyond is essential to achieve efficient global connectivity. As LEO satellites are a global infrastructure with predictable dynamics, a pre-planned fair and load-balanced allocation of the radio resources to provide efficient downlink connectivity over large areas is an achievable goal. In this paper, we propose a distributed and a global optimal algorithm for satellite-to-cell resource allocation with multiple beams. These algorithms aim to achieve a fair allocation of time-frequency resources and beams to the cell…
The flourishing low-Earth orbit (LEO) constellation communication network provides a promising solution for seamless coverage services to Internet-of-Things (IoT) terminals. However, confronted with massive connectivity and rapid variation of terrestrial-satellite link (TSL), the traditional grant-free random-access schemes always fail to match this scenario. In this paper, a new non-orthogonal multiple-access (NOMA) transmission protocol that incorporates orthogonal time frequency space (OTFS) modulation is proposed to solve these problems. Furthermore, we propose a two-stages joint active us…
Traditional Global Navigation Satellite System (GNSS) immunity to interference may be approaching a practical performance ceiling. Greater gains are possible outside traditional GNSS orbits and spectrum. GNSS from low Earth orbit (LEO) has long been viewed as promising but expensive, requiring large constellations for rapid navigation solutions. The recent emergence of commercial broadband LEO mega-constellations invites study on dual-purposing these for both communications -- their primary mission -- and a secondary positioning, navigation, and timing (PNT) service. Operating at shorter wavel…
Dense constellations of Low Earth Orbit (LEO) small satellites are envisioned to make extensive use of the inter-satellite link (ISL). Within the same orbital plane, the inter-satellite distances are preserved and the links are rather stable. In contrast, the relative motion between planes makes the inter-plane ISL challenging. In a dense set-up, each spacecraft has several satellites in its coverage volume, but the time duration of each of these links is small and the maximum number of active connections is limited by the hardware. We analyze the matching problem of connecting satellites usin…
Korea University（高丽大学）；Deakin University（迪肯大学）；University of Oulu（奥卢大学）
A mega-constellation of low-earth orbit (LEO) satellites has the potential to enable long-range communication with low latency. Integrating this with burgeoning unmanned aerial vehicle (UAV) assisted non-terrestrial networks will be a disruptive solution for beyond 5G systems provisioning large scale three-dimensional connectivity. In this article, we study the problem of forwarding packets between two faraway ground terminals, through an LEO satellite selected from an orbiting constellation and a mobile high-altitude platform (HAP) such as a fixed-wing UAV. To maximize the end-to-end data rat…
As low Earth orbit (LEO) satellite communication systems are gaining increasing popularity, new theoretical methodologies are required to investigate such networks' performance at large. This is because deterministic and location-based models that have previously been applied to analyze satellite systems are typically restricted to support simulations only. In this paper, we derive analytical expressions for the downlink coverage probability and average data rate of generic LEO networks, regardless of the actual satellites' locality and their service area geometry. Our solution stems from stoc…
Downlink Performance of Cell-Free Massive MIMO for LEO Satellite Mega-Constellation
Eastern Institute of Technology（东方理工学院）；Zhejiang Key Laboratory of Industrial Intelligence and Digital Twin（浙江省工业智能与数字孪生重点实验室）；Xidian University（西安电子科技大学）；State Key Laboratory of Integrated Services Networks（综合业务网国家级重点实验室）
