Related papers: Orbit-Aware Split Learning: Optimizing LEO Satelli…
Federated learning (FL) has emerged as a promising distributed training paradigm for Low Earth Orbit (LEO) networks by significantly reducing communication overhead. However, its deployment faces critical challenges, e.g., topology-induced…
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…
The rapid deployment of low earth orbit (LEO) satellite constellations has drawn attention to the potential of nonterrestrial networks (NTN) in providing global communication services. Telecom operators are attempting to collaborate with…
The deployment of low earth orbit (LEO) satellites with terrestrial networks can potentially increase the efficiency and reduce the cost of relaying content from a data center to a set of edge caches hosted by 6G and beyond enabled macro…
With the proliferation of distributed edge computing resources, the 6G mobile network will evolve into a network for connected intelligence. Along this line, the proposal to incorporate federated learning into the mobile edge has gained…
The increasing number of satellite deployments, both in the low and geostationary Earth orbit exacerbates the already ongoing scarcity of wireless resources when targeting ubiquitous connectivity. For the aim of supporting a massive number…
Detecting spoofing attacks to Low-Earth-Orbit (LEO) satellite systems is a cornerstone to assessing the authenticity of the received information and guaranteeing robust service delivery in several application domains. The solutions…
Marine Internet of Things (IoT) systems have grown substantially with the development of non-terrestrial networks (NTN) via aerial and space vehicles in the upcoming sixth-generation (6G), thereby assisting environment protection, military…
Ensuring network resilience in 6G and beyond is essential to maintain service continuity during base station (BS) outages due to failures, disasters, attacks, or energy-saving operations. This paper proposes a novel resilience optimization…
In recent years, there has been increasing investment in the deployment of massive commercial Low Earth Orbit (LEO) constellations to provide global Internet connectivity. These constellations, now equipped with inter-satellite links, can…
We design deep neural networks (DNNs) and corresponding networks' splittings to distribute DNNs' workload to camera sensors and a centralized aggregator on head mounted devices to meet system performance targets in inference accuracy and…
Machine learning techniques using proper elements to reconnect families of satellite fragmentation debris have recently advanced, becoming key to space sustainability and domain awareness. However, an evolving circumterrestrial environment…
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…
The integration of Non-Terrestrial Networks (NTNs) with Low Earth Orbit (LEO) satellite constellations into 5G and Beyond is essential to achieve truly global connectivity. A distinctive characteristic of LEO mega constellations is that…
Terrestrial network limitations drive the integration of non-terrestrial networks (NTNs), notably mega-constellations comprising thousands of low Earth orbit (LEO) satellites. While these satellites act as interconnected network switches…
In this letter, we propose an energy-efficient split learning (SL) framework for fine-tuning large language models (LLMs) using geo-distributed personal data at the network edge, where LLMs are split and alternately across massive mobile…
In this paper, we propose scalable distributed beamforming schemes over low Earth orbit (LEO) satellite networks that rely solely on statistical channel state information for downlink orthogonal frequency division multiplexing systems. We…
Recently, a large number of Low Earth Orbit (LEO) satellites have been launched and deployed successfully in space by commercial companies, such as SpaceX. Due to multimodal sensors equipped by the LEO satellites, they serve not only for…
The continuous scaling of deep neural networks has fundamentally transformed machine learning, with larger models demonstrating improved performance across diverse tasks. This growth in model size has dramatically increased the…
Low Earth Orbit (LEO) Earth Observation (EO) satellites have changed the way we monitor Earth. Acting like moving cameras, EO satellites are formed in constellations with different missions and priorities, and capture vast data that needs…