相关论文: Quantum-Assisted Joint Caching and Power Allocatio…
Mixed-integer linear programming problems are extensively used in industry for a wide range of optimization tasks. However, as they get larger, they present computational challenges for classical solvers within practical time limits.…
Computing tasks are ubiquitous in space missions. Conventionally, these tasks are offloaded to ground servers for computation, where the transmission of raw data on satellite-to-ground links severely constrains the performance. To overcome…
Low earth orbit (LEO) satellite networks have the potential to provide low-latency communication with global coverage. To unleash this potential, it is crucial to achieve efficient packet delivery. In this paper, we propose a…
In real-time and high-resolution Earth observation imagery, Low Earth Orbit (LEO) satellites capture images that are subsequently transmitted to ground to create an updated map of an area of interest. Such maps provide valuable information…
Hierarchical edge-cloud computing-aided Internet of Things (IoT) networks offer low-latency and cost-efficient services to a growing number of data-intensive IoT devices. However, optimizing service placement, which involves determining the…
The use of Low Earth Orbit (LEO) satellites in the next generation (Next-G) communication systems has been gaining traction over the last few years due to their potential for providing global connectivity with low latency. Since they are…
Low earth orbit (LEO) satellite plays an indispensable role in the earth network because of its low latency, large capacity, and seamless global coverage. For such an unprecedented extensive irregular system, stochastic geometry (SG) is a…
Quantum computing is emerging as a new computing resource that could be superior to conventional computing for certain classes of optimization problems. However, in principle, most existing approaches to quantum optimization are intended to…
Recently advanced low-Earth-orbit (LEO) satellite networks represented by large constellations and advanced payloads provide great promises for enabling high-quality Internet connectivity to any place on Earth. However, the traditional…
Current theoretical studies on IoT-over-LEO satellite systems often rely on unrealistic assumptions, such as infinite terrestrial areas and omnidirectional satellite coverage, leaving significant gaps in theoretical analysis for more…
Low Earth Orbit (LEO) Non-Terrestrial Networks (NTNs) require efficient beam management under dynamic propagation conditions. This work investigates Federated Learning (FL)-based beam selection in LEO satellite constellations, where orbital…
The high mobility of satellites in Low Earth Orbit (LEO) mega-constellations induces a highly dynamic network topology, leading to many problems like frequent service disruptions. To mitigate this, Packet-based Load Balancing (PBLB) is…
Recent advancements in space technology have equipped low Earth Orbit (LEO) satellites with the capability to perform complex functions and run AI applications. Federated Learning (FL) on LEO satellites enables collaborative training of a…
With numerous ongoing deployments owned by private companies and startups, dense satellite constellations deployed in low Earth orbit (LEO) will play a major role in the near future of wireless communications. In addition, the 3rd…
Satellite-terrestrial integrated networks (STINs) are promising architecture for providing global coverage. In STINs, full frequency reuse between a satellite and a terrestrial base station (BS) is encouraged for aggressive spectrum reuse,…
Low Earth orbit (LEO) satellite networks have shown strategic superiority in maritime communications, assisting in establishing signal transmissions from shore to ship through space-based links. Traditional performance modeling based on…
Low-Earth orbit (LEO) satellites have been prosperously deployed for various Earth observation missions due to its capability of collecting a large amount of image or sensor data. However, traditionally, the data training process is…
This paper proposes a joint decomposition method that combines La- grangian decomposition and generalized Benders decomposition, to efficiently solve multiscenario nonconvex mixed-integer nonlinear programming (MINLP) problems to global…
Low Earth Orbit Satellite Networks (LSNs) are integral to supporting a broad range of modern applications, which are typically modeled as Service Function Chains (SFCs). Each SFC is composed of Virtual Network Functions (VNFs), where each…
Deploying data- and computation-intensive applications such as large-scale AI into heterogeneous dispersed computing networks can significantly enhance application performance by mitigating bottlenecks caused by limited network resources,…