b'Guangxu Zhu'

research

∙ 08/12/2023

Integrated Sensing-Communication-Computation for Over-the-Air Edge AI Inference

Edge-device co-inference refers to deploying well-trained artificial int...

0 Zeming Zhuang, et al. ∙

research

∙ 06/28/2023

Communication Resources Constrained Hierarchical Federated Learning for End-to-End Autonomous Driving

While federated learning (FL) improves the generalization of end-to-end ...

0 Wei-Bin Kou, et al. ∙

research

∙ 06/11/2023

Task-Oriented Integrated Sensing, Computation and Communication for Wireless Edge AI

With the advent of emerging IoT applications such as autonomous driving,...

0 Hong Xing, et al. ∙

research

∙ 06/05/2023

Integrated Sensing, Computation, and Communication for UAV-assisted Federated Edge Learning

Federated edge learning (FEEL) enables privacy-preserving model training...

0 Yao Tang, et al. ∙

research

∙ 05/07/2023

Bayesian Over-the-Air FedAvg via Channel Driven Stochastic Gradient Langevin Dynamics

The recent development of scalable Bayesian inference methods has renewe...

0 Boning Zhang, et al. ∙

research

∙ 04/05/2023

Semantic Communications for Image Recovery and Classification via Deep Joint Source and Channel Coding

With the recent advancements in edge artificial intelligence (AI), futur...

0 Zhonghao Lyu, et al. ∙

research

∙ 03/20/2023

Over-the-Air Federated Edge Learning with Error-Feedback One-Bit Quantization and Power Control

Over-the-air federated edge learning (Air-FEEL) is a communication-effic...

0 Yuding Liu, et al. ∙

research

∙ 11/04/2022

Pushing AI to Wireless Network Edge: An Overview on Integrated Sensing, Communication, and Computation towards 6G

Pushing artificial intelligence (AI) from central cloud to network edge ...

0 Guangxu Zhu, et al. ∙

research

∙ 11/02/2022

Task-Oriented Over-the-Air Computation for Multi-Device Edge AI

Departing from the classic paradigm of data-centric designs, the 6G netw...

0 Dingzhu Wen, et al. ∙

research

∙ 08/11/2022

An Overview on Over-the-Air Federated Edge Learning

Over-the-air federated edge learning (Air-FEEL) has emerged as a promisi...

0 Xiaowen Cao, et al. ∙

research

∙ 08/07/2022

Low-Latency Cooperative Spectrum Sensing via Truncated Vertical Federated Learning

In recent years, the exponential increase in the demand of wireless data...

0 Zezhong Zhang, et al. ∙

research

∙ 07/03/2022

Task-Oriented Sensing, Computation, and Communication Integration for Multi-Device Edge AI

This paper studies a new multi-device edge artificial-intelligent (AI) s...

0 Dingzhu Wen, et al. ∙

research

∙ 06/13/2022

Toward Ambient Intelligence: Federated Edge Learning with Task-Oriented Sensing, Computation, and Communication Integration

In this paper, we address the problem of joint sensing, computation, and...

0 Peixi Liu, et al. ∙

research

∙ 02/28/2022

Over-the-Air Computation with Imperfect Channel State Information

This paper investigates the effect of imperfect channel state informatio...

0 Yilong Chen, et al. ∙

research

∙ 02/23/2022

Towards Tailored Models on Private AIoT Devices: Federated Direct Neural Architecture Search

Neural networks often encounter various stringent resource constraints w...

0 Chunhui Zhang, et al. ∙

research

∙ 01/29/2022

Integrated Sensing, Communication, and Computation Over-the-Air: MIMO Beamforming Design

To support the unprecedented growth of the Internet of Things (IoT) appl...

0 Xiaoyang Li, et al. ∙

research

∙ 01/21/2022

Vertical Federated Edge Learning with Distributed Integrated Sensing and Communication

This letter studies a vertical federated edge learning (FEEL) system for...

0 Peixi Liu, et al. ∙

research

∙ 12/29/2021

Training Time Minimization for Federated Edge Learning with Optimized Gradient Quantization and Bandwidth Allocation

Training a machine learning model with federated edge learning (FEEL) is...

0 Peixi Liu, et al. ∙

research

∙ 11/10/2021

Transmission Power Control for Over-the-Air Federated Averaging at Network Edge

Over-the-air computation (AirComp) has emerged as a new analog power-dom...

0 Xiaowen Cao, et al. ∙

research

∙ 10/06/2021

Joint Maneuver and Beamforming Design for UAV-Enabled Integrated Sensing and Communication

This paper studies the UAV-enabled integrated sensing and communication ...

0 Zhonghao Lyu, et al. ∙

research

∙ 07/24/2021

Accelerating Federated Edge Learning via Optimized Probabilistic Device Scheduling

The popular federated edge learning (FEEL) framework allows privacy-pres...

0 Maojun Zhang, et al. ∙

research

∙ 07/19/2021

Data Partition and Rate Control for Learning and Energy Efficient Edge Intelligence

The rapid development of artificial intelligence together with the power...

0 Xiaoyang Li, et al. ∙

research

∙ 06/29/2021

Symbiotic Sensing and Communications Towards 6G: Vision, Applications, and Technology Trends

Driven by the vision of intelligent connection of everything and digital...

0 Zhiqin Wang, et al. ∙

research

∙ 06/17/2021

Optimized Power Control Design for Over-the-Air Federated Edge Learning

This paper investigates the transmission power control in over-the-air f...

0 Xiaowen Cao, et al. ∙

research

∙ 11/11/2020

Optimized Power Control for Over-the-Air Federated Edge Learning

Over-the-air federated edge learning (Air-FEEL) is a communication-effic...

0 Xiaowen Cao, et al. ∙

research

∙ 09/04/2020

Over-the-Air Computing for 6G – Turning Air into a Computer

Wireless data aggregation (WDA), referring to aggregating data distribut...

0 Guangxu Zhu, et al. ∙

research

∙ 07/23/2020

Cooperative Interference Management for Over-the-Air Computation Networks

This paper considers a multi-cell AirComp network and investigates the o...

0 Xiaowen Cao, et al. ∙

research

∙ 01/16/2020

One-Bit Over-the-Air Aggregation for Communication-Efficient Federated Edge Learning: Design and Convergence Analysis

Federated edge learning (FEEL) is a popular framework for model training...

0 Guangxu Zhu, et al. ∙

research

∙ 12/25/2019

Joint Annotator-and-Spectrum Allocation in Wireless Networks for Crowd Labelling

The massive sensing data generated by Internet-of-Things will provide fu...

0 Xiaoyang Li, et al. ∙

research

∙ 10/05/2019

Data-Importance Aware User Scheduling for Communication-Efficient Edge Machine Learning

With the prevalence of intelligent mobile applications, edge learning is...

0 Dongzhu Liu, et al. ∙

research

∙ 06/17/2019

Optimal Power Control for Over-the-Air Computation in Fading Channels

In this paper, we study the power control problem for Over-the-air compu...

0 Xiaowen Cao, et al. ∙

research

∙ 12/30/2018

Broadband Analog Aggregation for Low-Latency Federated Edge Learning (Extended Version)

The popularity of mobile devices results in the availability of enormous...

0 Guangxu Zhu, et al. ∙

research

∙ 12/30/2018

Broadband Analog Aggregation for Low-Latency Federated Edge Learning

The popularity of mobile devices results in the availability of enormous...

0 Guangxu Zhu, et al. ∙

research

∙ 12/30/2018

Low-Latency Broadband Analog Aggregation for Federated Edge Learning

The popularity of mobile devices results in the availability of enormous...

0 Guangxu Zhu, et al. ∙

research

∙ 12/06/2018

Reduced-Dimension Design of MIMO Over-the-Air Computing for Data Aggregation in Clustered IoT Networks

One basic operation of Internet-of-Things (IoT) networks is aggregating ...

0 Dingzhu Wen, et al. ∙

research

∙ 12/05/2018

Wireless Data Acquisition for Edge Learning: Importance Aware Retransmission

By deploying machine learning algorithms at the network edge, edge learn...

0 Dongzhu Liu, et al. ∙

research

∙ 09/02/2018

Towards an Intelligent Edge: Wireless Communication Meets Machine Learning

The recent revival of artificial intelligence (AI) is revolutionizing al...

0 Guangxu Zhu, et al. ∙

research

∙ 08/14/2018

Wirelessly Powered Data Aggregation for IoT via Over-the-Air Functional Computation: Beamforming and Power Control

As a revolution in networking, Internet of Things (IoT) aims at automati...

0 Xiaoyang Li, et al. ∙

research

∙ 08/07/2018

Grassmannian Learning: Embedding Geometry Awareness in Shallow and Deep Learning

Modern machine learning algorithms have been adopted in a range of signa...

4 Jiayao Zhang, et al. ∙

research

∙ 04/10/2018

Automatic Recognition of Space-Time Constellations by Learning on the Grassmann Manifold (Extended Version)

Recent breakthroughs in machine learning especially artificial intellige...

0 Yuqing Du, et al. ∙

research

∙ 04/10/2018

Automatic Recognition of Space-Time Constellations by Learning on the Grassmann Manifold

Recent breakthroughs in machine learning especially artificial intellige...

0 Yuqing Du, et al. ∙

research

∙ 03/29/2018

Over-the-Air Computation in MIMO Multi-Access Channels: Beamforming and Channel Feedback

To support future IoT networks with dense sensor connectivity, a techniq...

0 Guangxu Zhu, et al. ∙

Guangxu Zhu

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