Unleashing the power of edge-cloud generative ai in mobile networks: A survey of aigc services
Artificial Intelligence-Generated Content (AIGC) is an automated method for generating,
manipulating, and modifying valuable and diverse data using AI algorithms creatively. This …
manipulating, and modifying valuable and diverse data using AI algorithms creatively. This …
A tutorial on extremely large-scale MIMO for 6G: Fundamentals, signal processing, and applications
Extremely large-scale multiple-input-multiple-output (XL-MIMO), which offers vast spatial
degrees of freedom, has emerged as a potentially pivotal enabling technology for the sixth …
degrees of freedom, has emerged as a potentially pivotal enabling technology for the sixth …
Beyond deep reinforcement learning: A tutorial on generative diffusion models in network optimization
Generative Diffusion Models (GDMs) have emerged as a transformative force in the realm of
Generative Artificial Intelligence (GAI), demonstrating their versatility and efficacy across a …
Generative Artificial Intelligence (GAI), demonstrating their versatility and efficacy across a …
Distributed deep reinforcement learning based gradient quantization for federated learning enabled vehicle edge computing
Federated Learning (FL) can protect the privacy of the vehicles in vehicle edge computing
(VEC) to a certain extent through sharing the gradients of vehicles' local models instead of …
(VEC) to a certain extent through sharing the gradients of vehicles' local models instead of …
Generative AI agents with large language model for satellite networks via 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 …
Semantic communications for wireless sensing: RIS-aided encoding and self-supervised decoding
Semantic communications can reduce the resource consumption by transmitting task-related
semantic information extracted from source messages. However, when the source …
semantic information extracted from source messages. However, when the source …
Graph neural networks and deep reinforcement learning based resource allocation for v2x communications
In the rapidly evolving landscape of Internet of Vehicles (IoV) technology, Cellular Vehicle-to-
Everything (C-V2X) communication has attracted much attention due to its superior …
Everything (C-V2X) communication has attracted much attention due to its superior …
Generative AI-enabled vehicular networks: Fundamentals, framework, and case study
Recognizing the tremendous improvements that the integration of generative AI can bring to
intelligent transportation systems, this article explores the integration of generative AI …
intelligent transportation systems, this article explores the integration of generative AI …
Advanced deep learning models for 6G: overview, opportunities and challenges
The advent of the sixth generation of mobile communications (6G) ushers in an era of
heightened demand for advanced network intelligence to tackle the challenges of an …
heightened demand for advanced network intelligence to tackle the challenges of an …
Sum-rate maximization in star-ris assisted rsma networks: A ppo-based algorithm
This article investigates simultaneous transmitting and reflecting reconfigurable intelligent
surface (STAR-RIS)-assisted downlink multiuser multiple-input–single-output (MU-MISO) …
surface (STAR-RIS)-assisted downlink multiuser multiple-input–single-output (MU-MISO) …