75 citations · 105 across the 9 of their papers we have counts for
9 papers
AI/ML for Mobile Networks: Release 19 Status and Future Challenges
Yuan Gao, Xinyi Wu, Jun Jiang +8
Artificial intelligence (AI) and machine learning (ML) have become essential drivers of sixth-generation (6G) mobile networks. Unlike earlier surveys that mainly review high-level…
Task-Oriented Real-time Visual Inference for IoVT Systems: A Co-design Framework of Neural Networks and Edge Deployment
Jiaqi Wu, Simin Chen, Zehua Wang +4
As the volume of image data grows, data-oriented cloud computing in Internet of Video Things (IoVT) systems encounters latency issues. Task-oriented edge computing addresses this b…
Internet of Intelligence: A Survey on the Enabling Technologies, Applications, and Challenges
Qinqin Tang, F. Richard Yu, Renchao Xie +3
The Internet of intelligence is conceived as an emerging networking paradigm, which will make intelligence as easy to obtain as information. This paper provides an overview of the…
Robust Federated Learning with Noisy Communication
Fan Ang, Li Chen, Nan Zhao +3
Federated learning is a communication-efficient training process that alternates between local training at the edge devices and averaging the updated local model at the central ser…
From the Internet of Information to the Internet of Intelligence
F. Richard Yu
In the era of the Internet of information, we have gone through layering, cross-layer, and cross-system design paradigms. Recently, the ``curse of modeling" and ``curse of dimensio…
Computing and Communicating Functions in Disorganized Wireless Networks
Fangzhou Wu, Li Chen, Nan Zhao +3
For future wireless networks, enormous numbers of interconnections are required, creating a disorganized topology and leading to a great challenge in data aggregation. Instead of c…
Multi-Antenna Covert Communications with Random Access Protocol
Weile Zhang, Nan Zhao, Shun Zhang +1
In this paper, we consider the issue of covert communications with random access protocol. We consider that the legitimate user Bob has no priori knowledge about packet arrival tim…
Computation Over NOMA: Improved Achievable Rate Through Sub-Function Superposition
Fangzhou Wu, Li Chen, Nan Zhao +3
Massive numbers of nodes will be connected in future wireless networks. This brings great difficulty to collect a large amount of data. Instead of collecting the data individually,…
Computation over Wide-Band MAC: Improved Achievable Rate through Sub-Function Allocation
Fangzhou Wu, Li Chen, Nan Zhao +3
Future networks are expected to connect an enormous number of nodes wirelessly using wide-band transmission. This brings great challenges. To avoid collecting a large amount of dat…