210 citations · 607 across the 38 of their papers we have counts for
19 papers · 1 filter
Nonparametric Variational Bayesian Learning for Channel Estimation with OTFS Modulation
Chong Cao, Zhuyu Liu, Zheng Dong +2
Orthogonal time frequency space (OTFS) modulation has demonstrated significant advantages in high-mobility scenarios in future 6G networks. However, existing channel estimation met…
Machine Learning for Large-Scale Optimization in 6G Wireless Networks
Yandong Shi, Lixiang Lian, Yuanming Shi +6
The sixth generation (6G) wireless systems are envisioned to enable the paradigm shift from "connected things" to "connected intelligence", featured by ultra high density, large-sc…
Over-the-Air Computation for 6G: Foundations, Technologies, and Applications
Zhibin Wang, Yapeng Zhao, Yong Zhou +3
The rapid advancement of artificial intelligence technologies has given rise to diversified intelligent services, which place unprecedented demands on massive connectivity and giga…
Interference Management for Over-the-Air Federated Learning in Multi-Cell Wireless Networks
Zhibin Wang, Yong Zhou, Yuanming Shi +1
Federated learning (FL) over resource-constrained wireless networks has recently attracted much attention. However, most existing studies consider one FL task in single-cell wirele…
Differentially Private Federated Learning via Reconfigurable Intelligent Surface
Yuhan Yang, Yong Zhou, Youlong Wu +1
Federated learning (FL), as a disruptive machine learning paradigm, enables the collaborative training of a global model over decentralized local datasets without sharing them. It…
Learning Proximal Operator Methods for Massive Connectivity in IoT Networks
Yinan Zou, Yong Zhou, Yuanming Shi +1
Grant-free random access has the potential to support massive connectivity in Internet of Things (IoT) networks, where joint activity detection and channel estimation (JADCE) is a…
Sparse Signal Processing for Massive Connectivity via Mixed-Integer Programming
Shuang Liang, Yuanming Shi, Yong Zhou
Massive connectivity is a critical challenge of Internet of Things (IoT) networks. In this paper, we consider the grant-free uplink transmission of an IoT network with a multi-ante…
Over-the-Air Computation via Cloud Radio Access Networks
Lukuan Xing, Yong Zhou, Yuanming Shi
Over-the-air computation (AirComp) has recently been recognized as a promising scheme for a fusion center to achieve fast distributed data aggregation in wireless networks via expl…
UAV Aided Over-the-Air Computation
Min Fu, Yong Zhou, Yuanming Shi +2
Over-the-air computation (AirComp) seamlessly integrates communication and computation by exploiting the waveform superposition property of multiple-access channels. Different from…
Over-the-Air Computation via Reconfigurable Intelligent Surface
Wenzhi Fang, Yuning Jiang, Yuanming Shi +3
Over-the-air computation (AirComp) is a disruptive technique for fast wireless data aggregation in Internet of Things (IoT) networks via exploiting the waveform superposition prope…
Optimal Receive Beamforming for Over-the-Air Computation
Wenzhi Fang, Yinan Zou, Hongbin Zhu +2
In this paper, we consider fast wireless data aggregation via over-the-air computation (AirComp) in Internet of Things (IoT) networks, where an access point (AP) with multiple ante…
UAV-Assisted Over-the-Air Computation
Min Fu, Yong Zhou, Yuanming Shi +2
Over-the-air computation (AirComp) provides a promising way to support ultrafast aggregation of distributed data. However, its performance cannot be guaranteed in long-distance tra…
Reconfigurable Intelligent Surface Enhanced Cognitive Radio Networks
Jinglian He, Kaiqiang Yu, Yong Zhou +1
The cognitive radio (CR) network is a promising network architecture that meets the requirement of enhancing scarce radio spectrum utilization. Meanwhile, reconfigurable intelligen…
Reconfigurable Intelligent Surface for Interference Alignment in MIMO Device-to-Device Networks
Min Fu, Yong Zhou, Yuanming Shi
In multiple-input multiple-output (MIMO) device-to-device (D2D) networks, interference and rank-deficient channels are the critical bottlenecks for achieving high degrees of freedo…
Communication-Efficient Edge AI Inference Over Wireless Networks
Kai Yang, Yong Zhou, Zhanpeng Yang +1
Given the fast growth of intelligent devices, it is expected that a large number of high-stake artificial intelligence (AI) applications, e.g., drones, autonomous cars, tactile rob…
Federated Machine Learning for Intelligent IoT via Reconfigurable Intelligent Surface
Kai Yang, Yuanming Shi, Yong Zhou +3
Intelligent Internet-of-Things (IoT) will be transformative with the advancement of artificial intelligence and high-dimensional data analysis, shifting from "connected things" to…
Reconfigurable Intelligent Surface for Green Edge Inference
Sheng Hua, Yong Zhou, Kai Yang +1
Reconfigurable intelligent surface (RIS) as an emerging cost-effective technology can enhance the spectrum- and energy-efficiency of wireless networks. In this paper, we consider a…
Reconfigurable Intelligent Surface Empowered Downlink Non-Orthogonal Multiple Access
Min Fu, Yong Zhou, Yuanming Shi +1
Power-domain non-orthogonal multiple access (NOMA) has become a promising technology to exploit the new dimension of the power domain to enhance the spectral efficiency of wireless…
Intelligent Reflecting Surface for Downlink Non-Orthogonal Multiple Access Networks
Min Fu, Yong Zhou, Yuanming Shi
Intelligent reflecting surface (IRS) has recently been recognized as a promising technology to enhance the energy and spectrum efficiency of wireless networks by controlling the wi…