activity
20192026
most citedInterference Management for Over-the-Air Federated Learning in Multi-Cell Wireless Networks

105 citations · 332 across the 31 of their papers we have counts for

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Showing 2021Show all

11 papers · 1 filter

eess.SP2021

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…

eess.SP2021

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…

eess.SP2021

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…

cs.IT2021

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…

eess.SP2021

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…

cs.IT2021

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…