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 …
Five facets of 6G: Research challenges and opportunities
While the fifth-generation systems are being rolled out across the globe, researchers have
turned their attention to the exploration of radical next-generation solutions. At this early …
turned their attention to the exploration of radical next-generation solutions. At this early …
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 …
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) …
Enhancing 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 (GenAI), demonstrating their versatility and efficacy across …
Generative Artificial Intelligence (GenAI), demonstrating their versatility and efficacy across …
Hybrid-Generative Diffusion Models for Attack-Oriented Twin Migration in Vehicular Metaverses
The vehicular metaverse is envisioned as a blended immersive domain that promises to
bring revolutionary changes to the automotive industry. As a core component of vehicular …
bring revolutionary changes to the automotive industry. As a core component of vehicular …
Sum rate maximization in muti-cell muti-user networks: An inverse reinforcement learning-based approach
Currently, reinforcement learning (RL) is widely used in wireless network optimization,
where the key factor is to design the efficient reward functions manually. However, the …
where the key factor is to design the efficient reward functions manually. However, the …
面向6G 的生成对抗网络研究进展综述
孟婵媛， 熊轲， 高博， 张煜， 樊平毅 - 物联网学报, 2024 - infocomm-journal.com
人工智能(AI, artificial intelligence) 与通信技术的深度融合是6G 网络的典型特征. 一方面, AI
为6G 网络发展注入了新动力, 能够有效利用网络运行产生的历史数据, 使网络具备自维护 …
为6G 网络发展注入了新动力, 能够有效利用网络运行产生的历史数据, 使网络具备自维护 …
Scheduling of Digital Twin Synchronization in Industrial Internet of Things: A Hybrid Inverse Reinforcement Learning Approach
Q Zhang, Y Wang, Z Li - IEEE Internet of Things Journal, 2024 - ieeexplore.ieee.org
The digital transformation of industrial systems has been significantly influenced by the
emergence of the Industrial Internet of Things. Digital twin (DT) technology plays a pivotal …
emergence of the Industrial Internet of Things. Digital twin (DT) technology plays a pivotal …
Communication Load Balancing via Efficient Inverse Reinforcement Learning
Communication load balancing aims to balance the load between different available
resources, and thus improve the quality of service for network systems. After formulating the …
resources, and thus improve the quality of service for network systems. After formulating the …