activity
20132023
most citedDeep Learning for Wireless Physical Layer: Opportunities and Challenges

45 citations · 177 across the 30 of their papers we have counts for

collaborators

51 papers

cs.IT2023

Auto-CsiNet: Scenario-customized Automatic Neural Network Architecture Generation for Massive MIMO CSI Feedback

Xiangyi Li, Jiajia Guo, Chao-Kai Wen +1

Deep learning has revolutionized the design of the channel state information (CSI) feedback module in wireless communications. However, designing the optimal neural network (NN) ar…

cs.IT20221 cited

Multi-domain Cooperative SLAM: The Enabler for Integrated Sensing and Communications

Jie Yang, Chao-Kai Wen, Xi Yang +3

Simultaneous localization and mapping (SLAM) provides user tracking and environmental mapping capabilities, enabling communication systems to gain situational awareness. Advanced c…

eess.SP20221 cited

Wireless Semantic Transmission via Revising Modules in Conventional Communications

Peiwen Jiang, Chao-Kai Wen, Shi Jin +1

Semantic communication has become a popular research area due its high spectrum efficiency and error-correction performance. Some studies use deep learning to extract semantic feat…

cs.IT2022

Hybrid Active and Passive Sensing for SLAM in Wireless Communication Systems

Jie Yang, Chao-Kai Wen, Shi Jin

Integrating sensing functions into future mobile equipment has become an important trend. Realizing different types of sensing and achieving mutual enhancement under the existing c…

cs.IT2021

A Linear Bayesian Learning Receiver Scheme for Massive MIMO Systems

Alva Kosasih, Wibowo Hardjawana, Branka Vucetic +1

Much stringent reliability and processing latency requirements in ultra-reliable-low-latency-communication (URLLC) traffic make the design of linear massive multiple-input-multiple…

cs.IT202119 cited

A Bayesian Receiver with Improved Complexity-Reliability Trade-off in Massive MIMO Systems

Alva Kosasih, Vera Miloslavskaya, Wibowo Hardjawana +3

The stringent requirements on reliability and processing delay in the fifth-generation (G) cellular networks introduce considerable challenges in the design of massive multiple-…