36 citations · 72 across the 27 of their papers we have counts for
27 papers
Rank-Aware Element Grouping for Power-Efficient Multiuser ISAC With an Extremely Large-Scale IRS
Shengsheng Zhang, Ritao Cheng, Zitong Wang +3
We investigate power-efficient multiuser integrated sensing and communication (ISAC) assisted by an element-grouping extremely large-scale intelligent reflecting surface (EG-XL-IRS…
Coordinated Multipoint Anti-jamming Beam Pattern Synthesis: From AI Accelerated Algorithm to Hardware Implementation
Zilong Wang, Cheng Zhang, Zhilei Zhang +3
This paper presents a deep unfolding-supported coordinated multipoint beam pattern synthesis (DUCoMP-BPS) scheme to overcome the high complexity, poor adaptability, and limited sca…
Generative Learning Enhanced Intelligent Resource Management for Cell-Free Delay Deterministic Communications
Shuangbo Xiong, Cheng Zhang, Wen Wang +2
Cell-free multiple-input multiple-output (CF-MIMO) architecture significantly enhances wireless network performance, offering a promising solution for delay-sensitive applications.…
Near-Field Wideband Channel Estimation for XL-MIMO Systems via Denoising Diffusion Model
Qingxia Feng, Yin Fang, Meng Hua +4
Extremely large-scale multiple-input multiple-output (XL-MIMO) is a key enabling technology for sixth-generation (6G) communication systems. Nevertheless, the increase in array ape…
Joint Optimization of Latency and Accuracy for Split Federated Learning in User-Centric Cell-Free MIMO Networks
Zitong Wang, Cheng Zhang, Wen Wang +3
This paper proposes a user-centric split federated learning (UCSFL) framework for user-centric cell-free multiple-input multiple-output (CF-MIMO) networks to support split federate…
RMTransformer: Accurate Radio Map Construction and Coverage Prediction
Yuxuan Li, Cheng Zhang, Wen Wang +1
Radio map, or pathloss map prediction, is a crucial method for wireless network modeling and management. By leveraging deep learning to construct pathloss patterns from geographica…
Joint Detection and Angle Estimation for Multiple Jammers in Beamspace Massive MIMO
Pengguang Du, Cheng Zhang, Changwei Zhang +2
In this paper, we study the joint detection and angle estimation problem for beamspace multiple-input multiple-output (MIMO) systems with multiple random jamming targets. An iterat…
Lyapunov-guided Multi-Agent Reinforcement Learning for Delay-Sensitive Wireless Scheduling
Cheng Zhang, Lan Wei, Ji Fan +2
In this paper, a two-stage intelligent scheduler is proposed to minimize the packet-level delay jitter while guaranteeing delay bound. Firstly, Lyapunov technology is employed to t…
Over-the-Air Federated Learning in Cell-Free MIMO with Long-term Power Constraint
Yifan Wang, Cheng Zhang, Yuanndon Zhuang +3
Wireless networks supporting artificial intelligence have gained significant attention, with Over-the-Air Federated Learning emerging as a key application due to its unique transmi…
Jamming Detection and Channel Estimation for Spatially Correlated Beamspace Massive MIMO
Pengguang Du, Cheng Zhang, Yindi Jing +3
In this paper, we investigate the problem of jamming detection and channel estimation during multi-user uplink beam training under random pilot jamming attacks in beamspace massive…
Anti-jamming Transmission of Downlink Cell Free Millimeter-Wave MIMO System
Zilong Wang, Cheng Zhang, Changwei Zhang +1
In this letter, the maximization of resistible jamming power is studied for multi-user downlink millimeter-wave cell-free multiple-input-multiple-output (CF-MIMO) systems. We propo…
Joint Optimization of Data- and Model-Driven Probing Beams and Beam Predictor
Tianheng Lu, Fan Meng, Zhilei Zhang +3
Hierarchical search in millimeter-wave (mmWave) communications incurs significant beam training overhead and delay, especially in a dynamic environment. Deep learning-enabled beam…
Generative Learning Powered Probing Beam Optimization for Cell-Free Hybrid Beamforming
Cheng Zhang, Shuangbo Xiong, Mengqing He +3
Probing beam measurement (PBM)-based hybrid beamforming provides a feasible solution for cell-free MIMO. In this letter, we propose a novel probing beam optimization framework wher…
Intelligent Hybrid Resource Allocation in MEC-assisted RAN Slicing Network
Chong Zheng, Yongming Huang, Cheng Zhang +1
In this paper, we aim to maximize the SSR for heterogeneous service demands in the cooperative MEC-assisted RAN slicing system by jointly considering the multi-node computing resou…
Entropy-based Probing Beam Selection and Beam Prediction via Deep Learning
Fan Meng, Cheng Zhang, Yongming Huang +3
Hierarchical beam search in mmWave communications incurs substantial training overhead, necessitating deep learning-enabled beam predictions to effectively leverage channel priors…
Digital Twin-Enhanced Deep Reinforcement Learning for Resource Management in Networks Slicing
Zhengming Zhang, Yongming Huang, Cheng Zhang +3
Network slicing-based communication systems can dynamically and efficiently allocate resources for diversified services. However, due to the limitation of the network interface on…
Traffic-Aware Hierarchical Beam Selection for Cell-Free Massive MIMO
Chenyang Wang, Cheng Zhang, Fan Meng +2
Beam selection for joint transmission in cell-free massive multi-input multi-output systems faces the problem of extremely high training overhead and computational complexity. The…
Incremental Collaborative Beam Alignment for Millimeter Wave Cell-Free MIMO Systems
Cheng Zhang, Leming Chen, Lujia Zhang +2
Millimeter wave (mmWave) cell-free MIMO achieves an extremely high rate while its beam alignment (BA) suffers from excessive overhead due to a large number of transceivers. Recentl…
Interleaved Training for Massive MIMO Downlink via Exploring Spatial Correlation
Cheng Zhang, Chang Liu, Yindi Jing +2
Interleaved training has been studied for single-user and multi-user massive MIMO downlink with either fully-digital or hybrid beamforming. However, the impact of channel correlati…
Joint Port Selection Based Channel Acquisition for FDD Cell-Free Massive MIMO
Cheng Zhang, Pengguang Du, Minjie Ding +2
In frequency division duplexing (FDD) cell-free massive MIMO, the acquisition of the channel state information (CSI) is very challenging because of the large overhead required for…
Toward 6G TK Extreme Connectivity: Architecture, Key Technologies and Experiments
Xiaohu You, Yongming Huang, Shengheng Liu +20
Sixth-generation (6G) networks are evolving towards new features and order-of-magnitude enhancement of systematic performance metrics compared to the current 5G. In particular, the…
True-data Testbed for 5G/B5G Intelligent Network
Yongming Huang, Shengheng Liu, Cheng Zhang +2
Future beyond fifth-generation (B5G) and sixth-generation (6G) mobile communications will shift from facilitating interpersonal communications to supporting Internet of Everything…
Signal Processing for MIMO-NOMA: Present and Future Challenges
Yongming Huang, Cheng Zhang, Jiaheng Wang +3
Non-orthogonal multiple access (NOMA), as the newest member of the multiple access family, is envisioned to be an essential component of 5G mobile networks. The combination of NOMA…
Performance Analysis for Massive MIMO Downlink with Low Complexity Approximate Zero-Forcing Precoding
Cheng Zhang, Yindi Jing, Yongming Huang +1
Zero-forcing (ZF) precoding plays an important role for massive MIMO downlink due to its near optimal performance. However, the high computation cost of the involved matrix inversi…