21 citations · 38 across the 20 of their papers we have counts for
20 papers
Enhancing Deep Reinforcement Learning: A Tutorial on Generative Diffusion Models in Network Optimization
Hongyang Du, Ruichen Zhang, Yinqiu Liu +10
Generative Diffusion Models (GDMs) have emerged as a transformative force in the realm of Generative Artificial Intelligence (GenAI), demonstrating their versatility and efficacy a…
Deep Plug-and-Play Prior for Multitask Channel Reconstruction in Massive MIMO Systems
Weixiao Wan, Wei Chen, Shiyue Wang +2
Scalability is a major concern in implementing deep learning (DL) based methods in wireless communication systems. Given various channel reconstruction tasks, applying one DL model…
Deep Learning for Asynchronous Massive Access with Data Frame Length Diversity
Yanna Bai, Wei Chen, Bo Ai +1
Grant-free non-orthogonal multiple access has been regarded as a viable approach to accommodate access for a massive number of machine-type devices with small data packets. The spo…
Deep-Learning-Aided Alternating Least Squares for Tensor CP Decomposition and Its Application to Massive MIMO Channel Estimation
Xiao Gong, Wei Chen, Bo Ai +1
CANDECOMP/PARAFAC (CP) decomposition is the mostly used model to formulate the received tensor signal in a massive MIMO system, as the receiver generally sums the components from d…
Digital-SC: Digital Semantic Communication with Adaptive Network Split and Learned Non-Linear Quantization
Lei Guo, Wei Chen, Yuxuan Sun +1
Semantic communication, an intelligent communication paradigm that aims to transmit useful information in the semantic domain, is facilitated by deep learning techniques. Robust se…
Semantic Communications for Image Recovery and Classification via Deep Joint Source and Channel Coding
Zhonghao Lyu, Guangxu Zhu, Jie Xu +2
With the recent advancements in edge artificial intelligence (AI), future sixth-generation (6G) networks need to support new AI tasks such as classification and clustering apart fr…
Uplink Power Control for Extremely Large-Scale MIMO with Multi-Agent Reinforcement Learning and Fuzzy Logic
Ziheng Liu, Zhilong Liu, Jiayi Zhang +3
In this paper, we investigate the uplink transmit power optimization problem in cell-free (CF) extremely large-scale multiple-input multiple-output (XL-MIMO) systems. Instead of ap…
Asynchronous Cell-Free Massive MIMO With Rate-Splitting
Jiakang Zheng, Jiayi Zhang, Julian Cheng +3
In practical cell-free (CF) massive multiple-input multiple-output (MIMO) networks with distributed and low-cost access points, the asynchronous arrival of signals at the user equi…
Improving Fairness for Cell-Free Massive MIMO Through Interference-Aware Massive Access
Shuaifei Chen, Jiayi Zhang, Emil Björnson +1
Cell-free massive multiple-input multiple-output (CF mMIMO) provides good interference management by coordinating many more access points (APs) than user equipments (UEs). It becom…
Federated Learning-Based Cell-Free Massive MIMO System for Privacy-Preserving
Jiayi Zhang, Jing Zhang, Derrick Wing Kwan Ng +1
Cell-free massive MIMO (CF mMIMO) is a promising next generation wireless architecture to realize federated learning (FL). However, sensitive information of user equipments (UEs) m…
CSI-PPPNet: A One-Sided One-for-All Deep Learning Framework for Massive MIMO CSI Feedback
Wei Chen, Weixiao Wan, Shiyue Wang +3
To reduce multiuser interference and maximize the spectrum efficiency in orthogonal frequency division duplexing massive multiple-input multiple-output (MIMO) systems, the downlink…
Deep Joint Source-Channel Coding for Semantic Communications
Jialong Xu, Tze-Yang Tung, Bo Ai +3
Semantic communications is considered as a promising technology to increase the efficiency of next-generation communication systems, particularly targeting human-machine and machin…
Asynchronous Activity Detection for Cell-Free Massive MIMO: From Centralized to Distributed Algorithms
Yang Li, Qingfeng Lin, Ya-Feng Liu +2
Device activity detection in the emerging cell-free massive multiple-input multiple-output (MIMO) systems has been recognized as a crucial task in machine-type communications, in w…
Decentralized Coordinated Precoding Design in Cell-Free Massive MIMO Systems for URLLC
Enyu Shi, Jing Zhang, Jiayi Zhang +2
Cell-free massive multiple-input multiple-output (MIMO) is a promising network to offer huge improvement of the achievable rate compared with conventional cellular massive MIMO sys…
Data-Driven Compressed Sensing for Massive Wireless Access
Yanna Bai, Wei Chen, Feifei Sun +2
The central challenge in massive machine-type communications (mMTC) is to connect a large number of uncoordinated devices through a limited spectrum. The typical mMTC communication…
Deep Reinforcement Learning Coordinated Receiver Beamforming for Millimeter-Wave Train-ground Communications
Xutao Zhou, Xiangfei Zhang, Chen Chen +6
As more and more people choose high-speed rail (HSR) as a means of transportation for short trips, there is ever growing demand of high quality of multimedia services. With its ric…
Deep Joint Source-Channel Coding for CSI Feedback: An End-to-End Approach
Jialong Xu, Bo Ai, Ning Wang +1
The increased throughput brought by MIMO technology relies on the knowledge of channel state information (CSI) acquired in the base station (BS). To make the CSI feedback overhead…
Heterogeneous Transformer: A Scale Adaptable Neural Network Architecture for Device Activity Detection
Yang Li, Zhilin Chen, Yunqi Wang +2
To support the modern machine-type communications, a crucial task during the random access phase is device activity detection, which is to detect the active devices from a large nu…
Multiple Residual Dense Networks for Reconfigurable Intelligent Surfaces Cascaded Channel Estimation
Yu Jin, Jiayi Zhang, Chongwen Huang +4
Reconfigurable intelligent surface (RIS) constitutes an essential and promising paradigm that relies programmable wireless environment and provides capability for space-intensive c…
Deep Joint Source-Channel Coding for Image Transmission with Visual Protection
Jialong Xu, Bo Ai, Wei Chen +2
Joint source-channel coding (JSCC) has achieved great success due to the introduction of deep learning (DL). Compared to traditional separate source-channel coding (SSCC) schemes,…