252 citations · 414 across the 21 of their papers we have counts for
23 papers
UL-Assisted Parametric CSI Feedback and Prediction for FDD Systems
Hao Chang, Mingcheng Nie, Shuangyang Li +4
In frequency-division duplex (FDD) systems, the uplink (UL) and downlink (DL) channels are not fully reciprocal. Therefore, DL channel state information (CSI) estimated by each use…
Learning-Aided Short Code Design for ISAC based on MIMO-OFDM
Mingcheng Nie, Shuangyang Li, Geng Wang +5
This paper proposes a deep learning (DL)-based coded waveform design for integrated sensing and communications (ISAC), enabling flexible trade-offs between communication reliabilit…
Hybrid Network- and User-Centric Scalable Cell-Free Massive MIMO for Fronthaul Signaling Minimization
Phu Lai, Wei Xiang, William Damario Lukito +4
Cell-free massive multiple-input multiple-output (CFmMIMO) coordinates a great number of distributed access points (APs) with central processing units (CPUs), effectively reducing…
Networked Integrated Sensing and Communications for 6G Wireless Systems
Jiapeng Li, Xiaodan Shao, Feng Chen +4
Integrated sensing and communication (ISAC) is envisioned as a key pillar for enabling the upcoming sixth generation (6G) communication systems, requiring not only reliable communi…
Integrated Sensing, Navigation, and Communication for Secure UAV Networks with a Mobile Eavesdropper
Zhiqiang Wei, Fan Liu, Chang Liu +3
This paper proposes an integrated sensing, navigation, and communication (ISNC) framework for safeguarding unmanned aerial vehicle (UAV)-enabled wireless networks against a mobile…
Integrated Sensing and Communication in Coordinated Cellular Networks
Dongfang Xu, Chang Liu, Shenghui Song +1
Integrated sensing and communication (ISAC) is a promising technique to provide sensing services in future wireless networks. Numerous existing works have adopted a monostatic rada…
Predictive Precoder Design for OTFS-Enabled URLLC: A Deep Learning Approach
Chang Liu, Shuangyang Li, Weijie Yuan +2
This paper investigates the orthogonal time frequency space (OTFS) transmission for enabling ultra-reliable low-latency communications (URLLC). To guarantee excellent reliability p…
Scalable Predictive Beamforming for IRS-Assisted Multi-User Communications: A Deep Learning Approach
Chang Liu, Xuemeng Liu, Zhiqiang Wei +2
Beamforming design for intelligent reflecting surface (IRS)-assisted multi-user communication (IRS-MUC) systems critically depends on the acquisition of accurate channel state info…
Deep CLSTM for Predictive Beamforming in Integrated Sensing and Communication-enabled Vehicular Networks
Chang Liu, Xuemeng Liu, Shuangyang Li +2
Predictive beamforming design is an essential task in realizing high-mobility integrated sensing and communication (ISAC), which highly depends on the accuracy of the channel predi…
Resource Allocation and 3D Trajectory Design for Power-Efficient IRS-Assisted UAV-NOMA Communications
Yuanxin Cai, Zhiqiang Wei, Shaokang Hu +3
In this paper, an intelligent reflecting surface (IRS) is introduced to assist an unmanned aerial vehicle (UAV) communication system based on non-orthogonal multiple access (NOMA)…
Predictive Beamforming for Integrated Sensing and Communication in Vehicular Networks: A Deep Learning Approach
Chang Liu, Weijie Yuan, Shuangyang Li +3
The implementation of integrated sensing and communication (ISAC) highly depends on the effective beamforming design exploiting accurate instantaneous channel state information (IC…
Beamforming Design for Intelligent Reflecting Surface-Enhanced Symbiotic Radio Systems
Shaokang Hu, Chang Liu, Zhiqiang Wei +3
This paper investigates multiuser multi-input single-output downlink symbiotic radio communication systems assisted by an intelligent reflecting surface (IRS). Different from exist…
A Novel ISAC Transmission Framework based on Spatially-Spread Orthogonal Time Frequency Space Modulation
Shuangyang Li, Weijie Yuan, Chang Liu +4
In this paper, we propose a novel integrated sensing and communication (ISAC) transmission framework based on the spatially-spread orthogonal time frequency space (SS-OTFS) modulat…
Learning-based Predictive Beamforming for Integrated Sensing and Communication in Vehicular Networks
Chang Liu, Weijie Yuan, Shuangyang Li +4
This paper investigates the integrated sensing and communication (ISAC) in vehicle-to-infrastructure (V2I) networks. To realize ISAC, an effective beamforming design is essential w…
Deep Learning-Empowered Predictive Beamforming for IRS-Assisted Multi-User Communications
Chang Liu, Xuemeng Liu, Zhiqiang Wei +3
The realization of practical intelligent reflecting surface (IRS)-assisted multi-user communication (IRS-MUC) systems critically depends on the proper beamforming design exploiting…
Robust and Secure Sum-Rate Maximization for Multiuser MISO Downlink Systems with Self-sustainable IRS
Shaokang Hu, Zhiqiang Wei, Yuanxin Cai +3
This paper investigates robust and secure multiuser multiple-input single-output (MISO) downlink communications assisted by a self-sustainable intelligent reflection surface (IRS),…
Deep Residual Network Empowered Channel Estimation for IRS-Assisted Multi-User Communication Systems
Chang Liu, Xuemeng Liu, Derrick Wing Kwan Ng +1
Channel estimation is of great importance in realizing practical intelligent reflecting surface-assisted multi-user communication (IRS-MC) systems. However, different from traditio…
Deep Transfer Learning-Assisted Signal Detection for Ambient Backscatter Communications
Chang Liu, Xuemeng Liu, Zhiqiang Wei +3
Existing tag signal detection algorithms inevitably suffer from a high bit error rate (BER) due to the difficulties in estimating the channel state information (CSI). To eliminate…
Location-aware Predictive Beamforming for UAV Communications: A Deep Learning Approach
Chang Liu, Weijie Yuan, Zhiqiang Wei +2
Unmanned aerial vehicle (UAV)-assisted communication becomes a promising technique to realize the beyond fifth generation (5G) wireless networks, due to the high mobility and maneu…
Deep Residual Learning-Assisted Channel Estimation in Ambient Backscatter Communications
Xuemeng Liu, Chang Liu, Yonghui Li +2
Channel estimation is a challenging problem for realizing efficient ambient backscatter communication (AmBC) systems. In this letter, channel estimation in AmBC is modeled as a den…
Deep Transfer Learning for Signal Detection in Ambient Backscatter Communications
Chang Liu, Zhiqiang Wei, Derrick Wing Kwan Ng +2
Tag signal detection is one of the key tasks in ambient backscatter communication (AmBC) systems. However, obtaining perfect channel state information (CSI) is challenging and cost…
Deep Residual Learning for Channel Estimation in Intelligent Reflecting Surface-Assisted Multi-User Communications
Chang Liu, Xuemeng Liu, Derrick Wing Kwan Ng +1
Channel estimation is one of the main tasks in realizing practical intelligent reflecting surface-assisted multi-user communication (IRS-MC) systems. However, different from tradit…
Performance Analysis for Practical Unmanned Aerial Vehicle Networks with LoS/NLoS Transmissions
Chang Liu, Ming Ding, Chuan Ma +3
In this paper, we provide a performance analysis for practical unmanned aerial vehicle (UAV)-enabled networks. By considering both line-of-sight (LoS) and non-line-of-sight (NLoS)…