210 citations · 1.1k across the 95 of their papers we have counts for
50 papers · 1 filter
Integrated Sensing-Communication-Computation for Over-the-Air Edge AI Inference
Zeming Zhuang, Dingzhu Wen, Yuanming Shi +3
Edge-device co-inference refers to deploying well-trained artificial intelligent (AI) models at the network edge under the cooperation of devices and edge servers for providing amb…
Integrated Sensing-Communication-Computation for Edge Artificial Intelligence
Dingzhu Wen, Xiaoyang Li, Yong Zhou +3
Edge artificial intelligence (AI) has been a promising solution towards 6G to empower a series of advanced techniques such as digital twins, holographic projection, semantic commun…
Vertical Federated Learning over Cloud-RAN: Convergence Analysis and System Optimization
Yuanming Shi, Shuhao Xia, Yong Zhou +3
Vertical federated learning (FL) is a collaborative machine learning framework that enables devices to learn a global model from the feature-partition datasets without sharing loca…
Task-Oriented Communications for 6G: Vision, Principles, and Technologies
Yuanming Shi, Yong Zhou, Dingzhu Wen +3
Driven by the interplay among artificial intelligence, digital twin, and wireless networks, 6G is envisaged to go beyond data-centric services to provide intelligent and immersive…
STAR-RIS Assisted Over-the-Air Vertical Federated Learning in Multi-Cell Wireless Networks
Xiangyu Zeng, Yijie Mao, Yuanming Shi
Vertical federated learning (FL) is a critical enabler for distributed artificial intelligence services in the emerging 6G era, as it allows for secure and efficient collaboration…
Task-Oriented Over-the-Air Computation for Multi-Device Edge AI
Dingzhu Wen, Xiang Jiao, Peixi Liu +3
Departing from the classic paradigm of data-centric designs, the 6G networks for supporting edge AI features task-oriented techniques that focus on effective and efficient executio…
UAV-Assisted Multi-Cluster Over-the-Air Computation
Min Fu, Yong Zhou, Yuanming Shi +2
In this paper, we study unmanned aerial vehicles (UAVs) assisted wireless data aggregation (WDA) in multicluster networks, where multiple UAVs simultaneously perform different WDA…
Robust Information Bottleneck for Task-Oriented Communication with Digital Modulation
Songjie Xie, Shuai Ma, Ming Ding +3
Task-oriented communications, mostly using learning-based joint source-channel coding (JSCC), aim to design a communication-efficient edge inference system by transmitting task-rel…
Task-Oriented Sensing, Computation, and Communication Integration for Multi-Device Edge AI
Dingzhu Wen, Peixi Liu, Guangxu Zhu +4
This paper studies a new multi-device edge artificial-intelligent (AI) system, which jointly exploits the AI model split inference and integrated sensing and communication (ISAC) t…
Reconfigurable Intelligent Surfaces Empowered Green Wireless Networks with User Admission Control
Jinglian He, Yijie Mao, Yong Zhou +2
Reconfigurable intelligent surface (RIS) has emerged as a cost-effective and energy-efficient technique for 6G. By adjusting the phase shifts of passive reflecting elements, RIS is…
Over-the-Air Federated Learning via Second-Order Optimization
Peng Yang, Yuning Jiang, Ting Wang +3
Federated learning (FL) is a promising learning paradigm that can tackle the increasingly prominent isolated data islands problem while keeping users' data locally with privacy and…
Edge Artificial Intelligence for 6G: Vision, Enabling Technologies, and Applications
Khaled B. Letaief, Yuanming Shi, Jianmin Lu +1
The thriving of artificial intelligence (AI) applications is driving the further evolution of wireless networks. It has been envisioned that 6G will be transformative and will revo…
Over-the-Air Decentralized Federated Learning
Yandong Shi, Yong Zhou, Yuanming Shi
In this paper, we consider decentralized federated learning (FL) over wireless networks, where over-the-air computation (AirComp) is adopted to facilitate the local model consensus…
Byzantine-Resilient Federated Machine Learning via Over-the-Air Computation
Shaoming Huang, Yong Zhou, Ting Wang +1
Federated learning (FL) is recognized as a key enabling technology to provide intelligent services for future wireless networks and industrial systems with delay and privacy guaran…
Reconfigurable Intelligent Surface for Massive Connectivity
Shuhao Xia, Yuanming Shi, Yong Zhou +1
With the rapid development of Internet of Things (IoT), massive machine-type communication has become a promising application scenario, where a large number of devices transmit spo…
Federated Learning via Intelligent Reflecting Surface
Zhibin Wang, Jiahang Qiu, Yong Zhou +4
Over-the-air computation (AirComp) based federated learning (FL) is capable of achieving fast model aggregation by exploiting the waveform superposition property of multiple access…
Fast Convergence Algorithm for Analog Federated Learning
Shuhao Xia, Jingyang Zhu, Yuhan Yang +3
In this paper, we consider federated learning (FL) over a noisy fading multiple access channel (MAC), where an edge server aggregates the local models transmitted by multiple end d…
Reconfigurable Intelligent Surface Assisted Massive MIMO with Antenna Selection
Jinglian He, Kaiqiang Yu, Yuanming Shi +3
Antenna selection is capable of reducing the hardware complexity of massive multiple-input multiple-output (MIMO) networks at the cost of certain performance degradation. Reconfigu…
Graph Neural Networks for Scalable Radio Resource Management: Architecture Design and Theoretical Analysis
Yifei Shen, Yuanming Shi, Jun Zhang +1
Deep learning has recently emerged as a disruptive technology to solve challenging radio resource management problems in wireless networks. However, the neural network architecture…
Outage Minimization for Intelligent Reflecting Surface Aided MISO Communication Systems via Stochastic Beamforming
Wenzhi Fang, Min Fu, Yuanming Shi +1
Intelligent reflecting surface (IRS) has the potential to significantly enhance the network performance by reconfiguring the wireless propagation environments. It is however diffic…
Towards Reconfigurable Intelligent Surfaces Powered Green Wireless Networks
Siyuan Sun, Min Fu, Yuanming Shi +1
The adoption of reconfigurable intelligent surface (RIS) in wireless networks can enhance the spectrum- and energy-efficiency by controlling the propagation environment. Although t…
Stochastic Beamforming for Reconfigurable Intelligent Surface Aided Over-the-Air Computation
Wenzhi Fang, Min Fu, Kunlun Wang +2
Over-the-air computation (AirComp) is a promising technology that is capable of achieving fast data aggregation in Internet of Things (IoT) networks. The mean-squared error (MSE) p…
Sparse Optimization for Green Edge AI Inference
Xiangyu Yang, Sheng Hua, Yuanming Shi +3
With the rapid upsurge of deep learning tasks at the network edge, effective edge artificial intelligence (AI) inference becomes critical to provide low-latency intelligent service…
Communication-Efficient Edge AI: Algorithms and Systems
Yuanming Shi, Kai Yang, Tao Jiang +2
Artificial intelligence (AI) has achieved remarkable breakthroughs in a wide range of fields, ranging from speech processing, image classification to drug discovery. This is driven…