1 citations · 2 across the 13 of their papers we have counts for
13 papers
Rate-Splitting and Sum-DoF for the K-User MISO Broadcast Channel with Mixed CSIT and Order-(K-1) Messages
Shuo Zheng, Tong Zhang, Jingfu Li +4
In this paper, we propose a rate-splitting design and characterize the sum-degrees-of-freedom (DoF) for the K-user multiple-input-single-output (MISO) broadcast channel with mixed…
DoF Upper Bound on Three-User MISO Broadcast Channel with Two Antennas and Mixed CSIT
Shuo Zheng, Tong Zhang, Shuai Wang +4
With delayed and imperfect current channel state information at the transmitter (CSIT), namely mixed CSIT, the sum degrees-of-freedom (sum-DoF) in the two-user multiple-input multi…
Rate-Splitting with Hybrid Messages: DoF Analysis of the Two-User MIMO Broadcast Channel with Imperfect CSIT
Tong Zhang, Yufan Zhuang, Gaojie Chen +4
Most of the existing research on degrees-of-freedom (DoF) with imperfect channel state information at the transmitter (CSIT) assume the messages are private, which may not reflect…
Large-Scale Bandwidth and Power Optimization for Multi-Modal Edge Intelligence Autonomous Driving
Xinrao Li, Tong Zhang, Shuai Wang +3
Edge intelligence autonomous driving (EIAD) offers computing resources in autonomous vehicles for training deep neural networks. However, wireless channels between the edge server…
Accelerating Federated Edge Learning via Topology Optimization
Shanfeng Huang, Zezhong Zhang, Shuai Wang +2
Federated edge learning (FEEL) is envisioned as a promising paradigm to achieve privacy-preserving distributed learning. However, it consumes excessive learning time due to the exi…
Integrated Sensing, Communication, and Computation Over-the-Air: MIMO Beamforming Design
Xiaoyang Li, Fan Liu, Ziqin Zhou +4
To support the unprecedented growth of the Internet of Things (IoT) applications, tremendous data need to be collected by the IoT devices and delivered to the server for further co…
Accelerating Federated Edge Learning via Optimized Probabilistic Device Scheduling
Maojun Zhang, Guangxu Zhu, Shuai Wang +3
The popular federated edge learning (FEEL) framework allows privacy-preserving collaborative model training via frequent learning-updates exchange between edge devices and server.…
Data Partition and Rate Control for Learning and Energy Efficient Edge Intelligence
Xiaoyang Li, Shuai Wang, Guangxu Zhu +3
The rapid development of artificial intelligence together with the powerful computation capabilities of the advanced edge servers make it possible to deploy learning tasks at the w…
Accelerating Edge Intelligence via Integrated Sensing and Communication
Tong Zhang, Shuai Wang, Guoliang Li +3
Realizing edge intelligence consists of sensing, communication, training, and inference stages. Conventionally, the sensing and communication stages are executed sequentially, whic…
Wireless Sensing With Deep Spectrogram Network and Primitive Based Autoregressive Hybrid Channel Model
Guoliang Li, Shuai Wang, Jie Li +3
Human motion recognition (HMR) based on wireless sensing is a low-cost technique for scene understanding. Current HMR systems adopt support vector machines (SVMs) and convolutional…
The DoF Region of Order-(K-1) Messages for the K-user MIMO Broadcast Channel with Delayed CSIT
Tong Zhang, Shuai Wang, Taotao Wang +1
This paper theoretically characterizes the degrees-of-freedom (DoF) region of order- messages for the -user multiple-input multiple-output (MIMO) broadcast channel with d…
On Secure Degrees of Freedom of the MIMO Interference Channel with Local Output Feedback
Tong Zhang, Yinfei Xu, Shuai Wang +2
This paper studies the problem of sum-secure degrees of freedom (SDoF) of the (M,M,N,N) multiple-input multiple-output (MIMO) interference channel with local output feedback, so as…
Reconfigurable Intelligent Surface Assisted Edge Machine Learning
Shanfeng Huang, Shuai Wang, Rui Wang +2
The ever-growing popularity and rapid improving of artificial intelligence (AI) have raised rethinking on the evolution of wireless networks. Mobile edge computing (MEC) provides a…