444 citations · 1.7k across the 86 of their papers we have counts for
64 papers · 1 filter
Over-the-Air Federated Learning in MIMO Cloud-RAN Systems
Haoming Ma, Xiaojun Yuan, Zhi Ding
To address the limitations of traditional over-the-air federated learning (OA-FL) such as limited server coverage and low resource utilization, we propose an OA-FL in MIMO cloud ra…
Matrix Factorization Based Blind Bayesian Receiver for Grant-Free Random Access in mmWave MIMO mMTC
Zhengdao Yuan, Fei Liu, Qinghua Guo +3
Grant-free random access is promising for massive connectivity with sporadic transmissions in massive machine type communications (mMTC), where the hand-shaking between the access…
Simultaneous Active and Passive Information Transfer for RIS-Aided MIMO Systems: Iterative Decoding and Evolution Analysis
Wenjun Jiang, Xiaojun Yuan
This paper investigates the potential of reconfigurable intelligent surface (RIS) for passive information transfer in a RIS-aided multiple-input multiple-output (MIMO) system. We p…
Message Passing-Based Joint User Activity Detection and Channel Estimation for Temporally-Correlated Massive Access
Weifeng Zhu, Meixia Tao, Xiaojun Yuan +1
This paper studies the user activity detection and channel estimation problem in a temporally-correlated massive access system where a very large number of users communicate with a…
RIS-Aided Multiuser MIMO-OFDM with Linear Precoding and Iterative Detection: Analysis and Optimization
Mingyang Yue, Lei Liu, Xiaojun Yuan
In this paper, we consider a reconfigurable intelligence surface (RIS) aided uplink multiuser multi-input multi-output (MIMO) orthogonal frequency division multiplexing (OFDM) syst…
Joint Active and Passive Beamforming Design for Reconfigurable Intelligent Surface Enabled Integrated Sensing and Communication
Zhe Xing, Rui Wang, Xiaojun Yuan
To exploit the potential of the RIS in supporting ISAC, this paper proposes a novel joint active and passive beamforming design for RIS-enabled ISAC system in consideration of the…
Over-the-Air Federated Multi-Task Learning via Model Sparsification and Turbo Compressed Sensing
Haoming Ma, Xiaojun Yuan, Zhi Ding +2
To achieve communication-efficient federated multitask learning (FMTL), we propose an over-the-air FMTL (OAFMTL) framework, where multiple learning tasks deployed on edge devices s…
RIS Partitioning Based Scalable Beamforming Design for Large-Scale MIMO: Asymptotic Analysis and Optimization
Chang Cai, Xiaojun Yuan, Ying-Jun Angela Zhang
In next-generation wireless networks, reconfigurable intelligent surface (RIS)-assisted multiple-input multiple-output (MIMO) systems are foreseeable to support a large number of a…
Energy-Efficient UAV Communications: A Generalised Propulsion Energy Consumption Model
Xinhong Dai, Bin Duo, Xiaojun Yuan +1
This paper proposes a generalised propulsion energy consumption model (PECM) for rotary-wing ummanned aerial vehicles (UAVs) under the consideration of the practical thrust-to-weig…
Intelligent Reflecting Surface Aided MIMO with Cascaded LoS Links: Channel Modelling and Full Multiplexing Region
Mingchen Zhang, Xiaojun Yuan
This work studies the modelling and the optimization of intelligent reflecting surface (IRS) assisted multiple-input multiple-output (MIMO) systems through cascaded line-of-sight (…
Joint Beamforming and Reconfigurable Intelligent Surface Design for Two-Way Relay Networks
Jun Wang, Ying-Chang Liang, Jingon Joung +2
In this paper, we consider a reconfigurable intelligent surface (RIS)-assisted two-way relay network, in which two users exchange information through the base station (BS) with the…
MIMO-OFDM-Based Massive Connectivity With Frequency Selectivity Compensation
Wenjun Jiang, Mingyang Yue, Xiaojun Yuan +1
In this paper, we study how to efficiently and reliably detect active devices and estimate their channels in a multiple-input multiple-output (MIMO) orthogonal frequency-division m…
Temporal-Structure-Assisted Gradient Aggregation for Over-the-Air Federated Edge Learning
Dian Fan, Xiaojun Yuan, Ying-Jun Angela Zhang
In this paper, we investigate over-the-air model aggregation in a federated edge learning (FEEL) system. We introduce a Markovian probability model to characterize the intrinsic te…
Sparse Kronecker-Product Coding for Unsourced Multiple Access
Zeyu Han, Xiaojun Yuan, Chongbin Xu +2
In this paper, a sparse Kronecker-product (SKP) coding scheme is proposed for unsourced multiple access. Specifically, the data of each active user is encoded as the Kronecker prod…
Semi-Blind Cascaded Channel Estimation for Reconfigurable Intelligent Surface Aided Massive MIMO
Zhen-Qing He, Hang Liu, Xiaojun Yuan +2
Reconfigurable intelligent surface (RIS) is envisioned to be a promising green technology to reduce the energy consumption and improve the coverage and spectral efficiency of massi…
CSIT-Free Model Aggregation for Federated Edge Learning via Reconfigurable Intelligent Surface
Hang Liu, Xiaojun Yuan, Ying-Jun Angela Zhang
We study over-the-air model aggregation in federated edge learning (FEEL) systems, where channel state information at the transmitters (CSIT) is assumed to be unavailable. We lever…
Reconfigurable Intelligent Surface for Massive Connectivity
Shuhao Xia, Yuanming Shi, Yong Zhou +1
With the rapid development of Internet of Things (IoT), massive machine-type communication has become a promising application scenario, where a large number of devices transmit spo…
Deep-Learned Approximate Message Passing for Asynchronous Massive Connectivity
Weifeng Zhu, Meixia Tao, Xiaojun Yuan +1
This paper considers the massive connectivity problem in an asynchronous grant-free random access system, where a huge number of devices sporadically transmit data to a base statio…
Hierarchical Passive Beamforming for Reconfigurable Intelligent Surface Aided Communications
Chang Cai, Xiaojun Yuan, Wenjing Yan +3
In reconfigurable intelligent surfaces (RISs) aided communications, the existing passive beamforming (PB) design involves polynomial complexity in the number of reflecting elements…
Reconfigurable Intelligent Surface Enabled Federated Learning: A Unified Communication-Learning Design Approach
Hang Liu, Xiaojun Yuan, Ying-Jun Angela Zhang
To exploit massive amounts of data generated at mobile edge networks, federated learning (FL) has been proposed as an attractive substitute for centralized machine learning (ML). B…
An Overview on Multiway Relay Communications: Fundamental Issues, Recent Advances, and New Challenges
Rui Wang, Xiaojun Yuan
To address the coverage and capacity challenges in fifth-generation (5G) wireless networks, the relay technique has been considered as a promising solution and recently attracted g…
Reconfigurable Intelligent Surfaces for Energy Efficiency in D2D Communication Network
Shuaiqi Jia, Xiaojun Yuan, Ying-Chang Liang
In this letter, the joint power control of D2D users and the passive beamforming of reconfigurable intelligent surfaces (RIS) for a RIS-aided device-to-device (D2D) communication n…
Two-Timescale Optimization for Intelligent Reflecting Surface Aided D2D Underlay Communication
Chang Cai, Huiyuan Yang, Xiaojun Yuan +1
The performance of a device-to-device (D2D) underlay communication system is limited by the co-channel interference between cellular users (CUs) and D2D devices. To address this ch…
Statistical Beamforming for FDD Downlink Massive MIMO via Spatial Information Extraction and Beam Selection
Hang Liu, Xiaojun Yuan, Ying Jun +1
In this paper, we study the beamforming design problem in frequency-division duplexing (FDD) downlink massive MIMO systems, where instantaneous channel state information (CSI) is a…