0000-0001-8773-4629

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Kaibin Huang (Fellow, IEEE) received the B.Eng. and M.Eng. degrees from the National University of Singapore and the Ph.D. degree from The University of Texas at Austin, all in electrical engineering. He is currently an Associate Professor with the Department of Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong. He received the IEEE Communication Society’s 2021 Best Survey Paper, 2019 Best Tutorial Paper, 2019 Asia–Pacific Outstanding Paper, 2015 Asia–Pacific Best Paper Award, and the best paper awards at IEEE GLOBECOM 2006 and IEEE/CIC ICCC 2018. He received the Outstanding Teaching Award from Yonsei University, South Korea, in 2011. He has been named as a Highly Cited Researcher by the Clarivate Analytics in 2019-2021 and awarded a Research Fellowship by Hong Kong Research Grants Council. He served as the Lead Chair for the Wireless Communications Symposium of IEEE Globecom 2017 and the Communication Theory Symposium of IEEE GLOBECOM 2014, and the TPC Co-chair for IEEE PIMRC 2017 and IEEE CTW 2013. He is also an Executive Editor of IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, an Associate Editor of IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, and an Area Editor for IEEE TRANSACTIONS ON GREEN COMMUNICATIONS AND NETWORKING. Previously, he served on the Editorial Board for IEEE WIRELESS COMMUNICATIONS LETTERS. He has guest edited special issues of IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING, and IEEE Communications Magazine. He is also a Distinguished Lecturer of the IEEE Communications Society and the IEEE Vehicular Technology Society.

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Beamforming Design for Semantic-Bit Coexisting Communication System

IEEE Journal on Selected Areas in Communications

2025 | Journal article

DOI: 10.1109/JSAC.2025.3531537

Contributors: Maojun Zhang; Guangxu Zhu; Richeng Jin; Xiaoming Chen; Qingjiang Shi; Caijun Zhong; Kaibin Huang

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Works (50 of 106)

Beamforming Design for Semantic-Bit Coexisting Communication System

Compression Ratio Allocation for Probabilistic Semantic Communication with RSMA

Digital Over-the-Air Computation: Achieving High Reliability via Bit-Slicing

Integrating Data Collection, Communication, and Computation for Importance-Aware Online Edge Learning Tasks

Mobile Edge Intelligence for Large Language Models: A Contemporary Survey

Over-the-Air Fusion of Sparse Spatial Features for Integrated Sensing and Edge AI over Broadband Channels

Resource Management for Low-latency Cooperative Fine-tuning of Foundation Models at the Network Edge

Towards Atomic MIMO Receivers

D²-JSCC: Digital Deep Joint Source-Channel Coding for Semantic Communications

Towards ubiquitous radio access using nanodiamond based quantum receivers

A Survey on Integrated Sensing, Communication, and Computation

Beamforming Design for Massive MIMO-Aided Over-the-Air Computation: A Mutual Information Perspective

Decentralized Federated Learning With Asynchronous Parameter Sharing for Large-Scale IoT Networks

Efficient Multiuser AI Downloading via Reusable Knowledge Broadcasting

Goal-Oriented Wireless Communication Resource Allocation for Cyber-Physical Systems

Green Edge AI: A Contemporary Survey

Integrating Sensing, Communication, and Power Transfer: Multiuser Beamforming Design

Knowledge-Based Ultra-Low-Latency Semantic Communications for Robotic Edge Intelligence

Multi-Channel Attentive Feature Fusion for Radio Frequency Fingerprinting

On the View-and-Channel Aggregation Gain in Integrated Sensing and Edge AI

Semantic Communication Meets Edge Intelligence: Semantic-Relay-Aided Text Transmissions

Semantic-Topology Preserving Quantization of Word Embeddings for Human-to-Machine Communications

Spectrum Breathing: Protecting Over-the-Air Federated Learning Against Interference

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

Wireless Communication and Control Co-Design for System Identification

Efficient Parallel Split Learning Over Resource-Constrained Wireless Edge Networks

Joint Batching and Scheduling for High-Throughput Multiuser Edge AI With Asynchronous Task Arrivals

The Interplay Between Generative AI and 5G-Advanced Toward 6G

Over-the-Air Multi-View Pooling for Distributed Sensing

Precoding Design for Ensuring Data Freshness in Multi-User MISO Networks

Realizing In-Memory Baseband Processing for Ultrafast and Energy-Efficient 6G

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

On-the-Fly Communication-and-Computing for Distributed Tensor Decomposition Over MIMO Channels

Vertical Layering of Quantized Neural Networks for Heterogeneous Inference

Progressive Feature Transmission for Split Classification at the Wireless Edge

Resource Allocation for Multiuser Edge Inference With Batching and Early Exiting

Energy Efficient Wireless Crowd Labeling: Joint Annotator Clustering and Power Control

Timely and Massive Communication in 6G: Pragmatics, Learning, and Inference

Joint Sensing and Communication-Rate Control for Energy Efficient Mobile Crowd Sensing

Accelerating Federated Edge Learning via Topology Optimization

Distributed Over-the-Air Computing for Fast Distributed Optimization: Beamforming Design and Convergence Analysis

Analog MIMO Communication for One-Shot Distributed Principal Component Analysis

A Two-Timescale Approach to Mobility Management for Multicell Mobile Edge Computing

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

Turning Channel Noise Into an Accelerator for Over-the-Air Principal Component Analysis

A Perspective on Time Toward Wireless 6G

An Energy-Efficient Aerial Backhaul System With Reconfigurable Intelligent Surface

Federated Dropout—A Simple Approach for Enabling Federated Learning on Resource Constrained Devices

Deploying Federated Learning in Large-Scale Cellular Networks: Spatial Convergence Analysis

Guest Editorial Special Issue on Distributed Learning Over Wireless Edge Networks—Part II

Peer review (1 review for 1 publication/grant)