Satellite Communication Systems

Últimos artículos

• Space Generative AI with Solar Energy Harvesting

  Jierui Zhang, Jianhao Huang, Zhanwei Wang, Kaibin Huang · 2 de septiembre de 2026

  Satellites are emerging as promising platforms to extend generative \emph{artificial intelligence} (AI) services to remote areas lacking terrestrial infrastructure. However, deploying space generative AI is fundamentally constrained by the limited, time-varying onboard energy supplied by solar \emph…

• FractalNet-Based Heterogeneous Federated Learning for Orbital Edge Intelligence in Satellite Mega-Constellations: A Wildfire Case Study

  Sai Puppala, Koushik Sinha · 2 de septiembre de 2026

  Satellite mega-constellations are emerging as large-scale sensing, communication, and computation fabrics, yet their learning architectures remain largely inherited from terrestrial federated learning and ground-centric mission operations--- ill-suited to satellites that differ by orders of magnitud…

• SatDL: Jointly Optimizing Data Redistribution and Training for Satellite-Based Distributed Learning

  Hao Wu, Kin Whye Chew, Yizhan Han, Han Li, Jingxian Wang · 26 de agosto de 2026

  Satellite-based distributed learning promises to train machine-learning models directly in orbit using massive, globally dispersed sensor data, thereby avoiding large-scale data downloads to ground servers. However, training convergence is significantly slowed by severe non-IID data, specifically la…

• ORBITALIF: An Efficient Spiking Federated Learning Framework for Onboard Cloud Removal

  Bohan Zhang, Chenyu Xu, Yijie Mao, Yuanming Shi · 26 de agosto de 2026

  Low-earth-orbit (LEO) satellites enable high-resolution, large-scale Earth observation for applications such as disaster monitoring and environmental surveillance. However, cloud coverage often obscures the Earth's surface, and conventional cloud-removal pipelines that download cloudy images to grou…

• Implicit Q-learning-bootstrapped ant colony optimization for maritime moving-target observation scheduling with agile satellites

  He Wang, Junyu Wu, Yeye Liu, Yifan Zhou, Jie Zhang, Hui Li, Yanjie Song, Liang Li · 26 de agosto de 2026

  Maritime moving-target observation scheduling with agile Earth observation satellites is a dynamic, sequence-dependent combinatorial optimization problem. Sea-surface targets move continuously, causing feasible observation windows to vary with target motion and satellite orbital geometry. The schedu…

• Reinforcement Learning-Guided Evolutionary Policy Optimization for Preference-Adjustable Heterogeneous Agile Earth Observation Satellite Scheduling

  He Wang, Junyu Wu, Hui Li, Yanjie Song, Witold Pedrycz, Liang Li · 26 de agosto de 2026

  Heterogeneous agile Earth observation satellite (AEOS) scheduling requires task selection, satellite assignment, and observation sequencing under satellite-dependent visibility windows, attitude maneuvering requirements, energy consumption, and onboard storage constraints. Since satellites differ in…

• Orbital AI Computing: Carbon Tradeoffs Across Satellite Scale

  Nisha Sarwar, Lei Jiang, Fan Chen · 18 de agosto de 2026

  Low Earth Orbit (LEO) computing is emerging for low-latency, globally distributed AI services, enabled by advances in satellite constellations and reusable launch systems. However, its sustainability remains unclear. Prior work introduces ESpaS, a framework for estimating lifecycle carbon intensity,…

• Task-Driven Three-Layer Distributed Scheduling for Emergency Earth Observation in Large Low-Earth-Orbit Constellations

  Qian Yin, Xinwei Wang, Guohua Wu · 18 de agosto de 2026

  Large low-Earth-orbit (LEO) Earth-observation (EO) constellations offer frequent access to geographically dispersed ground targets, but emergency requests may arrive after committed routine-plan execution has begun. The resulting dynamic emergency observation scheduling problem (DEOSP) requires urge…

• ML-Based Hierarchical Prediction for Practical Energy Scheduling in Dynamic NTN-WPT Systems

  Zhanyu Ju, Wenchi Cheng · 11 de agosto de 2026

  With advancements in long-distance wireless power transfer (WPT) and space-based energy technologies, integrating WPT into non-terrestrial networks (NTNs), referred to as NTN-WPT, is emerging as a promising approach for next-generation wireless networks. This paper proposes an energy-scheduling appr…

• FedOrbit: Adaptive Personalized Federated Learning for Non-IID LEO Satellite Constellations

  Satwat Bashir, Tasos Dagiuklas, Muddesar Iqbal · 11 de agosto de 2026

  Federated learning (FL) in Low Earth Orbit (LEO) satellite constellations is affected by non-IID data and irregular ground-station visibility, both driven by orbital geometry. Global aggregation performs poorly when orbit-level class distributions are disjoint, while strong personalisation can be ex…

• FedRings: A Scalable and Topology-Aware Federated Learning Framework for LEO Satellite Constellations

  Ziwu Liu, In\^es Pinto Gouveia, Rehana Yasmin, Paulo Esteves-Verissimo, Ali Shoker · 5 de agosto de 2026

  Federated learning over low Earth orbit (LEO) satellite networks is limited by frequent link changes, short contact times, and a highly dynamic topology, making centralized or synchronized training inefficient and hard to scale. To address this, we propose FedRings, a decentralized framework that or…

• Clear-Weighted Bit Allocation for Satellite Downlinks

  Alireza Furutanpey, Qiyang Zhang, Yujie Huang, Philipp Raith, Schahram Dustdar · 4 de agosto de 2026

  Earth-observation satellites capture more imagery than intermittent ground contacts can transmit. Onboard systems threshold a cloud detector, discard frames or tiles, and compress the survivors with a fixed codec. On expert-labeled imagery, these rules remove more than one-fifth of clear pixels, pri…

• Distributed Constraint Optimization via Online Learning and Iterative Pricing with Application to Large-Scale Satellite Scheduling

  Itai Zilberstein, Pranav Rajbhandari, Steve Chien, Tuomas Sandholm · 29 de julio de 2026

  Distributed constraint optimization problems (DCOPs) provide a popular framework for distributed decision making under limited communication, but many real-world instances are too large to solve monolithically. We address this challenge from two complementary directions. We revisit the connection be…

• A GAN-Based Framework for Robust Data Synthesis in Satellite Internet Observations

  Xiang Shi, Peng Hu · 29 de julio de 2026

  Low-Earth orbit (LEO) satellite Internet has become an important infrastructure for enabling ubiquitous connectivity to align with the International Telecommunications Union vision for 6G telecommunications networks. However, current LEO satellite Internet observations often suffer from missing data…

• A VAE-Driven Multi-Task Satellite-Aided Semantic Communication Framework for 6G-Enabled Connected Autonomous Vehicles

  S. M. Abtahiul Alam, Niloy Das, Apurba Adhikary, Yu Qiao, Zhu Han, Choong Seon Hong · 16 de julio de 2026

  The development of smart transportation systems and the introduction of 6G wireless communication technologies have significantly changed vehicle network topologies. Future connected autonomous vehicle (CAV) networks require bandwidth-efficient, reliable, and low-latency communication for safety-cri…

• Robust Design of Integrated Sensing and Communication in LEO Satellite Systems

  Hezhen Yang, Xiaoming Chen, Qi Wang · 15 de julio de 2026

  With the growing demand for satellite sensing and communication, the limited wireless resources are difficult to support multiple satellite systems. Therefore, it is desired to investigate integrated sensing and communication (ISAC) in low Earth orbit (LEO) satellite systems to enable multi-function…

• Compound Interference Recognition for LR-FHSS Satellite IoT Uplinks via Multi-Domain Instance Fusion

  H. Xu, B. He, S. Wang, Y. Jiang · 14 de julio de 2026

  Long range-frequency hopping spread spectrum (LR-FHSS) is a promising uplink physical layer for massive low Earth orbit satellite Internet of Things, where low power terminals report short packets from wide area regions with limited terrestrial infrastructure. However, satellite IoT links are expose…

• Deciphering Region-Level Signatures from Latency Measurements in LEO Satellite Internet

  Xiang Shi, Yifei Zhang, Peng Hu · 30 de junio de 2026

  Low-Earth orbit (LEO) satellite Internet has become an indispensable infrastructure that provide growing coverage for global users. Despite extensive measurement efforts, the principles underlying region-level performance characteristics remain insufficiently understood, limiting the ability to iden…

• SpaceRipple: Lightweight Semantic Delivery for Mission-Oriented LEO Earth Observation Satellite Networks

  Ziyi Yang, Hao Yuan, Yunxiang Yi, Wenbo Wang, Xing Zhang · 26 de junio de 2026

  Earth observation satellite networks generate massive volumes of high-resolution imagery, whereas inter-satellite and downlink resources remain limited. In many time-sensitive missions, ground users require mission-relevant semantic information rather than a full raw-image downlink. This paper propo…

• Free-Placement Optimization of Ground Station Locations for Low-Earth Orbit Satellites

  Grace Ra Kim, Duncan Eddy, Vedant Srinivas, Mykel J. Kochenderfer · 12 de junio de 2026

  Rapidly expanding low Earth orbit satellite constellations are placing increasing demands on terrestrial ground networks, motivating the development of more efficient ground station network designs. Current approaches select sites from predefined locations, limiting optimization to existing infrastr…

• Dynamic Distributed Constraint Optimization and Metareasoning for Continual, Large-Scale Satellite Operations

  Itai Zilberstein, Steve Chien · 9 de junio de 2026

  As Earth-observing satellite constellations grow in size and capability, distributed onboard control offers a pathway to novel responses and time-sensitive measurements. However, deploying autonomy to satellites requires efficient computation and communication. This work addresses the challenge of s…

• DIFFRACT: Neuralized Utility Maximization for Wireless Networks by Differentiable Programming

  Chee Wei Tan, Siya Chen · 8 de junio de 2026

  Next-generation wireless networks, including satellite-to-Open RAN systems, demand agile and intelligent resource management capable of handling dynamic multi-user interference under stochastic quality of service constraints. This paper introduces DIFFRACT, a neuralized utility maximization framewor…

• DRIFT: Joint Channel Estimation and Prediction Towards Pilotless 6G Non-Terrestrial Networks

  Bruno De Filippo, Carla Amatetti, Alessandro Vanelli-Coralli · 1 de junio de 2026

  Non-terrestrial networks (NTNs) are expected to play a pivotal role in sixth-generation (6G) systems by enabling ubiquitous connectivity and massive communication. In this context, channel prediction emerges as a key technique to improve the spectrum utilization efficiency by limiting the pilot over…

• HADT: A Heterogeneous Multi-Agent Differential Transformer for Autonomous Earth Observation Satellite Cluster

  Mohamad A. Hady, Muhammad Anwar Masum, Siyi Hu, Mahardhika Pratama, Jimmy Cao, Ryszard Kowalczyk · 1 de junio de 2026

  This work addresses the problem of autonomous resource management in heterogeneous satellite cluster conducting Earth Observation (EO) missions including optical and Synthetic Aperture Radar (SAR) satellites. In autonomous operation mode, satellites are equipped with intelligent capabilities enablin…

• Adversarial Water-Filling: Theory, Algorithms and Foundation Model

  Xindi Tong, Chee Wei Tan, H. Vincent Poor · 27 de mayo de 2026

  Competitive resource allocation problems over frequency and space can be formulated as minimax interaction between transmit power and worst-case interference. This formulation naturally arises in multi-operator low Earth orbit (LEO) satellite spectrum sharing, where transmissions from competing cons…