Zobrazeno 1 - 10
of 323
pro vyhledávání: '"Shi, Yuanming"'
The forthcoming generation of wireless technology, 6G, promises a revolutionary leap beyond traditional data-centric services. It aims to usher in an era of ubiquitous intelligent services, where everything is interconnected and intelligent. This vis
Externí odkaz:
http://arxiv.org/abs/2408.08074
Pre-trained foundation models (FMs), with extensive number of neurons, are key to advancing next-generation intelligence services, where personalizing these models requires massive amount of task-specific data and computational resources. The prevale
Externí odkaz:
http://arxiv.org/abs/2407.02924
Edge-device co-inference, which concerns the cooperation between edge devices and an edge server for completing inference tasks over wireless networks, has been a promising technique for enabling various kinds of intelligent services at the network e
Externí odkaz:
http://arxiv.org/abs/2407.00955
In this paper, a cloud radio access network (Cloud-RAN) based collaborative edge AI inference architecture is proposed. Specifically, geographically distributed devices capture real-time noise-corrupted sensory data samples and extract the noisy loca
Externí odkaz:
http://arxiv.org/abs/2404.06007
The proliferation of low-earth-orbit (LEO) satellite networks leads to the generation of vast volumes of remote sensing data which is traditionally transferred to the ground server for centralized processing, raising privacy and bandwidth concerns. F
Externí odkaz:
http://arxiv.org/abs/2404.01875
The integration of various power sources, including renewables and electric vehicles, into smart grids is expanding, introducing uncertainties that can result in issues like voltage imbalances, load fluctuations, and power losses. These challenges ne
Externí odkaz:
http://arxiv.org/abs/2403.16402
In this work, we unveil the advantages of synergizing cooperative rate splitting (CRS) with user relaying and simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR RIS). Specifically, we propose a novel STAR RIS-assisted
Externí odkaz:
http://arxiv.org/abs/2403.10921
Autor:
Li, Xiaoyang, Han, Zidong, Zhu, Guangxu, Shi, Yuanming, Xu, Jie, Gong, Yi, Zhang, Qinyu, Huang, Kaibin, Letaief, Khaled B.
To support the development of internet-of-things applications, an enormous population of low-power devices are expected to be incorporated in wireless networks performing sensing and communication tasks. As a key technology for improving the data col
Externí odkaz:
http://arxiv.org/abs/2311.09031
Distributed learning has become a promising computational parallelism paradigm that enables a wide scope of intelligent applications from the Internet of Things (IoT) to autonomous driving and the healthcare industry. This paper studies distributed l
Externí odkaz:
http://arxiv.org/abs/2310.11998
Federated learning (FL), as an emerging distributed machine learning paradigm, allows a mass of edge devices to collaboratively train a global model while preserving privacy. In this tutorial, we focus on FL via over-the-air computation (AirComp), wh
Externí odkaz:
http://arxiv.org/abs/2310.10089