Interactive Generative AI Agents for Satellite Networks through a Mixture of Experts Transmission
In response to the needs of 6G global communications, satellite communication networks
have emerged as a key solution. However, the large-scale development of satellite …
have emerged as a key solution. However, the large-scale development of satellite …
Towards a Fully-Observable Markov Decision Process With Generative Models for Integrated 6G-Non-Terrestrial Networks
A Machumilane, P Cassara… - IEEE Open Journal of the …, 2023 - ieeexplore.ieee.org
The upcoming sixth generation (6G) mobile networks require integration between terrestrial
mobile networks and non-terrestrial networks (NTN) such as satellites and high altitude …
mobile networks and non-terrestrial networks (NTN) such as satellites and high altitude …
Cached model-as-a-resource: Provisioning large language model agents for edge intelligence in space-air-ground integrated networks
Space-air-ground integrated networks (SAGINs) enable worldwide network coverage
beyond geographical limitations for users to access ubiquitous intelligence services.{\color …
beyond geographical limitations for users to access ubiquitous intelligence services.{\color …
FedLEO: An offloading-assisted decentralized federated learning framework for low earth orbit satellite networks
Low Earth orbit (LEO) satellites enable complex Earth observation tasks (eg, remote sensing
and cooperative monitoring) by leveraging large-scale satellite-generated Earth imageries …
and cooperative monitoring) by leveraging large-scale satellite-generated Earth imageries …
Mixture of Experts for Network Optimization: A Large Language Model-enabled Approach
Optimizing various wireless user tasks poses a significant challenge for networking systems
because of the expanding range of user requirements. Despite advancements in Deep …
because of the expanding range of user requirements. Despite advancements in Deep …
Towards Autonomous Satellite Communications: An AI-based Framework to Address System-level Challenges
The next generation of satellite constellations is designed to better address the future needs
of our connected society: highly-variable data demand, mobile connectivity, and reaching …
of our connected society: highly-variable data demand, mobile connectivity, and reaching …
Collaborative Ground-Space Communications via Evolutionary Multi-objective Deep Reinforcement Learning
In this paper, we propose a distributed collaborative beamforming (DCB)-based uplink
communication paradigm for enabling ground-space direct communications. Specifically …
communication paradigm for enabling ground-space direct communications. Specifically …
Large Language Model Enhanced Multi-Agent Systems for 6G Communications
The rapid development of the Large Language Model (LLM) presents huge opportunities for
6G communications, eg, network optimization and management by allowing users to input …
6G communications, eg, network optimization and management by allowing users to input …
FedSN: A General Federated Learning Framework over LEO Satellite Networks
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 …
deployed successfully in space by commercial companies, such as SpaceX. Due to …
Satellite-based ITS data offloading & computation in 6G networks: A cooperative multi-agent proximal policy optimization DRL with attention approach
The proliferation of intelligent transportation systems (ITS) has led to increasing demand for
diverse network applications. However, conventional terrestrial access networks (TANs) are …
diverse network applications. However, conventional terrestrial access networks (TANs) are …