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Author details

Dapeng Wu

Also published under: Dapeng Oliver Wu, D. Wu, Dapeng wu, Dapeng O. Wu, Da-peng Wu

Publications

358

Citations

6,199

Publications by Year

20012025

Co-Authors:

Qingsong AiBo AiRichard Al-BayatyMohamed AlzenadGaoyun An

Show All Co-Authors (587)

Dapeng Wu

Also published under: Dapeng Oliver Wu, D. Wu, Dapeng wu, Dapeng O. Wu, Da-peng Wu

Affiliation

School of Communications and Information Engineering

Chongqing University of Posts and Telecommunications

Chongqing, China

Advanced Network and Intelligent Connection Technology Key Laboratory of Chongqing Education Commission of China

Chongqing Key Laboratory of Ubiquitous Sensing and Networking

Chongqing, China

Publication Topics

Internet Of Things,
Deep Reinforcement Learning,
Edge Server,
Base Station,
Unmanned Aerial Vehicles,
Time Slot,
Federated Learning,
Neural Network,
Convolutional Neural Network,
Energy Consumption,
Global Model,
Internet Of Vehicles

Biography

Dapeng Oliver Wu (Fellow, IEEE) received the B.E. degree in electrical engineering from the Huazhong University of Science and Technology, Wuhan, China, in 1990, the M.E. degree in electrical engineering from the Beijing University of Posts and Telecommunications, Beijing, China, in 1997, and the Ph.D. degree in electrical and computer engineering from Carnegie Mellon University, Pittsburgh, PA, USA, in 2003. He is currently a Professor with the Department of Computer Science, City University of Hong Kong, Hong Kong. His research interests include the areas of networking, communications, signa processing, computer vision, machine learning, smart grid, and information and network security. He was an Elected Member of Multimedia Signal Proces...

Publications

358

Citations

6,199

Publications by Year

20012025

Co-Authors:

Qingsong Ai
Bo Ai
Richard Al-Bayaty
Mohamed Alzenad
Gaoyun An

Show All Co-Authors (587)

Author's Published Works

Search History

Showing 1-25 of 358 results

Journals (204)

Conferences (131)

Magazines (18)

Early Access Articles (5)

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Dapeng Wu(303)
Ruyan Wang(123)
Yaping Cui(47)
Peng He(45)
Honggang Wang(41)
Department of Electrical and Computer Engineering, University of Florida, Gainesville, FL, USA(83)
School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing, China(66)
Chongqing Key Laboratory of Ubiquitous Sensing and Networking, Chongqing, China(36)
Advanced Network and Intelligent Connection Technology Key Laboratory of Chongqing Education Commission of China, Chongqing, China(29)
Department of Computer Science, City University of Hong Kong, Kowloon, Hong Kong(13)
IEEE Internet of Things Journal(39)
IEEE Transactions on Vehicular Technology(32)
IEEE Transactions on Multimedia(13)
IEEE Access(11)
IEEE Transactions on Circuits and Systems for Video Technology(10)
IEEE(358)
Media(11)
Code(4)
Chengdu, China(6)
Beijing, China(5)
Dalian, China(5)
London, United Kingdom(5)
Hangzhou, China(4)
Time Slot(59)
Internet Of Things(51)
Service Quality(45)
Wireless Networks(41)
Energy Consumption(39)

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Multi-User Semantic Communication With Federated Learning for Intelligent Search Service

Meiyu Sun;Dapeng Wu;Puning Zhang;Ruyan Wang

IEEE Internet of Things Journal

Year: 2025 | Early Access Article |

Intelligent search enables users to access information from the Internet quickly, but existing schemes fail to achieve accurate semantic awareness and reliable information transmission, especially in constrained communication conditions, which degrade search accuracy and personalized user experience. To address these challenges, we propose a multi-user semantic communication system to perform pers...Show More

Multi-User Semantic Communication With Federated Learning for Intelligent Search Service

Meiyu Sun;Dapeng Wu;Puning Zhang;Ruyan Wang

IEEE Internet of Things Journal

Year: 2025 | Early Access Article |

Survey on Near-Space Information Networks: Channel Modeling, Transmission, and Networking Perspectives

Xianbin Cao;Xiaoning Su;Peng Yang;Yue Gao;Dapeng Oliver Wu;Tony Q. S. Quek

IEEE Communications Surveys & Tutorials

Year: 2025 | Early Access Article |

Near-space information networks (NSINs) composed of high-altitude platforms (HAPs) and high-and low-altitude unmanned aerial vehicles (UAVs) are a new regime for providing quick, robust, and cost-efficient sensing and communication services. Precipitated by innovations and breakthroughs in manufacturing, materials, communications, electronics, and control techniques, NSINs have been envisioned as ...Show More

Survey on Near-Space Information Networks: Channel Modeling, Transmission, and Networking Perspectives

Xianbin Cao;Xiaoning Su;Peng Yang;Yue Gao;Dapeng Oliver Wu;Tony Q. S. Quek

IEEE Communications Surveys & Tutorials

Year: 2025 | Early Access Article |

Multi-dimensional Modeling and Connectivity Analysis for THz Space-Air-Ground Integrated Network

Yingchen Gu;Ruyan Wang;Dapeng Wu;Yaping Cui;Peng He;Boran Yang

IEEE Transactions on Wireless Communications

Year: 2025 | Early Access Article |

Non-terrestrial networks (NTNs) are integrated with terrestrial networks to form space-air-ground integrated networks (SAGINs), providing seamless global coverage and supporting the development of the digital economy. However, when it comes to the actual design and deployment of SAGINs, the heterogeneity, self-organization, and flexibility of SAGIN pose challenges for precise modeling and quantita...Show More

Multi-dimensional Modeling and Connectivity Analysis for THz Space-Air-Ground Integrated Network

Yingchen Gu;Ruyan Wang;Dapeng Wu;Yaping Cui;Peng He;Boran Yang

IEEE Transactions on Wireless Communications

Year: 2025 | Early Access Article |

From Dense to Sparse: Event Response for Enhanced Residential Load Forecasting

Xin Cao;Qinghua Tao;Yingjie Zhou;Lu Zhang;Le Zhang;Dongjin Song;Dapeng Oliver Wu;Ce Zhu

IEEE Transactions on Instrumentation and Measurement

Year: 2025 | Volume: 74 | Journal Article |

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Residential load forecasting (RLF) is crucial for resource scheduling in power systems. Most existing methods use all given load records (dense data) to indiscriminately extract the dependencies between historical and future time series. However, there exist important regular patterns residing in the event-related associations among different appliances (sparse knowledge), which have yet been igno...Show More

From Dense to Sparse: Event Response for Enhanced Residential Load Forecasting

Xin Cao;Qinghua Tao;Yingjie Zhou;Lu Zhang;Le Zhang;Dongjin Song;Dapeng Oliver Wu;Ce Zhu

IEEE Transactions on Instrumentation and Measurement

Year: 2025 | Volume: 74 | Journal Article |

ADStereo: Efficient Stereo Matching With Adaptive Downsampling and Disparity Alignment

Yun Wang;Kunhong Li;Longguang Wang;Junjie Hu;Dapeng Oliver Wu;Yulan Guo

IEEE Transactions on Image Processing

Year: 2025 | Volume: 34 | Journal Article |

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The balance between accuracy and computational efficiency is crucial for the applications of deep learning-based stereo matching algorithms in real-world scenarios. Since matching cost aggregation is usually the most computationally expensive component, a common practice is to construct cost volumes at a low resolution for aggregation and then directly regress a high-resolution disparity map. Howe...Show More

ADStereo: Efficient Stereo Matching With Adaptive Downsampling and Disparity Alignment

Yun Wang;Kunhong Li;Longguang Wang;Junjie Hu;Dapeng Oliver Wu;Yulan Guo

IEEE Transactions on Image Processing

Year: 2025 | Volume: 34 | Journal Article |

Nonterrestrial Network Technologies: Applications and Future Prospects

Peng He;Hailong Lei;Dapeng Wu;Ruyan Wang;Yaping Cui;Yan Zhu;Zhaopeng Ying

IEEE Internet of Things Journal

Year: 2025 | Volume: 12, Issue: 6 | Journal Article |

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This review delves into the applications and prospects of nonterrestrial networks (NTNs) in the field of information and communication. NTNs utilize aerial or space platforms as critical components of the communication network, including high-altitude unmanned systems, low-altitude unmanned systems, and satellites. Compared to traditional terrestrial cellular networks, NTNs offer advantages, such ...Show More

Nonterrestrial Network Technologies: Applications and Future Prospects

Peng He;Hailong Lei;Dapeng Wu;Ruyan Wang;Yaping Cui;Yan Zhu;Zhaopeng Ying

IEEE Internet of Things Journal

Year: 2025 | Volume: 12, Issue: 6 | Journal Article |

Predicting the Compressive Strength of Recycled Concrete Using Ensemble Learning Model

Binghao Pan;Wensheng Liu;Pan Zhou;Dapeng Oliver Wu

Year: 2025 | Volume: 13 | Journal Article |

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This research proposes a stacking machine learning method to accurately predict the compressive strength of recycled concrete. The model integrates eXtreme Gradient Boosting (XGBoost), Extra Trees (ET), Decision Tree (DT), and Linear Regression (LR) models, aiming to maximize the prediction accuracy of concrete compressive strength. The model was evaluated using a combination of 63 self-made recyc...Show More

Predicting the Compressive Strength of Recycled Concrete Using Ensemble Learning Model

Binghao Pan;Wensheng Liu;Pan Zhou;Dapeng Oliver Wu

Year: 2025 | Volume: 13 | Journal Article |

Towards Optimal Customized Architecture for Heterogeneous Federated Learning With Contrastive Cloud-Edge Model Decoupling

Xingyan Chen;Tian Du;Mu Wang;Tiancheng Gu;Yu Zhao;Gang Kou;Changqiao Xu;Dapeng Oliver Wu

IEEE Transactions on Computers

Year: 2025 | Volume: 74, Issue: 4 | Journal Article |

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Federated learning, as a promising distributed learning paradigm, enables collaborative training of a global model across multiple network edge clients without the need for central data collecting. However, the heterogeneity of edge data distribution drags the model towards the local minima, which can be distant from the global optimum. Such heterogeneity often leads to slow convergence and substa...Show More

Towards Optimal Customized Architecture for Heterogeneous Federated Learning With Contrastive Cloud-Edge Model Decoupling

Xingyan Chen;Tian Du;Mu Wang;Tiancheng Gu;Yu Zhao;Gang Kou;Changqiao Xu;Dapeng Oliver Wu

IEEE Transactions on Computers

Year: 2025 | Volume: 74, Issue: 4 | Journal Article |

Triplet Bridge for Zero-Shot Sketch-Based Image Retrieval

Jiahao Zheng;Yu Tang;Dapeng Wu

IEEE Transactions on Emerging Topics in Computational Intelligence

Year: 2025 | Volume: 9, Issue: 2 | Journal Article |

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Zero-Shot Sketch-Based Image Retrieval (ZS-SBIR) has always been a hard nut to crack due to the scarcity of sketch data and the abstract visual information contained in sketches. Previous works focus on designing various network architectures and using the gold standard triplet loss to solve ZS-SBIR, but they have always encountered obstacles in enhancing model generalization and extracting abstra...Show More

Triplet Bridge for Zero-Shot Sketch-Based Image Retrieval

Jiahao Zheng;Yu Tang;Dapeng Wu

IEEE Transactions on Emerging Topics in Computational Intelligence

Year: 2025 | Volume: 9, Issue: 2 | Journal Article |

DAiMo: Motif Density Enhances Topology Robustness for Highly Dynamic Scale-Free IoT

Ning Chen;Tie Qiu;Weisheng Si;Dapeng Oliver Wu

IEEE Transactions on Mobile Computing

Year: 2025 | Volume: 24, Issue: 3 | Journal Article |

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Robust Topology is a key prerequisite to providing consistent connectivity for highly dynamic Internet-of-Things (IoT) applications that are suffering node failures. In this paper, we present a two-step approach to organizing the most robust IoT topology. First, we propose a novel robustness metric denoted as $I$I, which is based on network motifs and is specifically designed to sensitively analyz...Show More

DAiMo: Motif Density Enhances Topology Robustness for Highly Dynamic Scale-Free IoT

Ning Chen;Tie Qiu;Weisheng Si;Dapeng Oliver Wu

IEEE Transactions on Mobile Computing

Year: 2025 | Volume: 24, Issue: 3 | Journal Article |

FedLaw: Value-Aware Federated Learning With Individual Fairness and Coalition Stability

Jianfeng Lu;Hangjian Zhang;Pan Zhou;Xiong Wang;Chen Wang;Dapeng Oliver Wu

IEEE Transactions on Emerging Topics in Computational Intelligence

Year: 2025 | Volume: 9, Issue: 1 | Journal Article |

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A long-standing problem remains with the heterogeneous clients in Federated Learning (FL), who often have diverse gains and requirements for the trained model, while their contributions are hard to evaluate due to the privacy-preserving training. Existing works mainly rely on single-dimension metric to calculate clients' contributions as aggregation weights, which however may damage the social fai...Show More

FedLaw: Value-Aware Federated Learning With Individual Fairness and Coalition Stability

Jianfeng Lu;Hangjian Zhang;Pan Zhou;Xiong Wang;Chen Wang;Dapeng Oliver Wu

IEEE Transactions on Emerging Topics in Computational Intelligence

Year: 2025 | Volume: 9, Issue: 1 | Journal Article |

RIS-Assisted Unsupervised Beamforming in Internet of Vehicles

Yaping Cui;Gongxun Wang;Dapeng Wu;Peng He;Ruyan Wang;Yanping Liu

IEEE Transactions on Vehicular Technology

Year: 2025 | Volume: 74, Issue: 1 | Journal Article |

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Internet of vehicles (IoVs) will require massive high data rate connections with the base station (BS) to provide promising vehicular entertainment services, such as autonomous driving and traffic management. However, vehicles often encounter obstruction from buildings while traveling in urban areas, resulting in blocked direct links between the BS and the vehicle, thereby impacting the channel qu...Show More

RIS-Assisted Unsupervised Beamforming in Internet of Vehicles

Yaping Cui;Gongxun Wang;Dapeng Wu;Peng He;Ruyan Wang;Yanping Liu

IEEE Transactions on Vehicular Technology

Year: 2025 | Volume: 74, Issue: 1 | Journal Article |

SR-ABR: Super Resolution Integrated ABR Algorithm for Cloud-Based Video Streaming

Haiqiao Wu;Dapeng Oliver Wu;Peng Gong

IEEE Transactions on Emerging Topics in Computational Intelligence

Year: 2025 | Volume: 9, Issue: 1 | Journal Article |

Cited by: Papers (1)

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Super-resolution is a promising solution to improve the quality of experience (QoE) for cloud-based video streaming when the network resources between clients and the cloud vendors become scarce. Specifically, the received video can be enhanced with a trained super-resolution model running on the client-side. However, all the existing solutions ignore the content-induced performance variability of...Show More

SR-ABR: Super Resolution Integrated ABR Algorithm for Cloud-Based Video Streaming

Haiqiao Wu;Dapeng Oliver Wu;Peng Gong

IEEE Transactions on Emerging Topics in Computational Intelligence

Year: 2025 | Volume: 9, Issue: 1 | Journal Article |

Optimizing Proximity Strategy for Federated Learning Node Selection in the Space-Air–Ground Information Network for Smart Cities

Weidong Wang;Ping Li;Siqi Li;Jihao Zhang;Zijiao Zhou;Dapeng Oliver Wu;Duk Kyung Kim;Guangwei Zhang;Peng Gong

IEEE Internet of Things Journal

Year: 2025 | Volume: 12, Issue: 6 | Journal Article |

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As the Internet of Things (IoT) technology and artificial intelligence (AI) technology continue to evolve, many envisaged concepts regarding smart cities are gradually becoming a reality. However, the proliferation of numerous IoT devices in smart cities has led to several challenges. The existing 5G networks are incapable of meeting the requirements of these devices in terms of channel capacity a...Show More

Optimizing Proximity Strategy for Federated Learning Node Selection in the Space-Air–Ground Information Network for Smart Cities

Weidong Wang;Ping Li;Siqi Li;Jihao Zhang;Zijiao Zhou;Dapeng Oliver Wu;Duk Kyung Kim;Guangwei Zhang;Peng Gong

IEEE Internet of Things Journal

Year: 2025 | Volume: 12, Issue: 6 | Journal Article |

Pedestrian Trajectory Prediction by Short-Term Target Estimation in Autonomous Driving Scenarios

Jing Yang;Peng Wang;Yaping Cui;Peng He;Dapeng Wu;Ruyan Wang

GLOBECOM 2024 - 2024 IEEE Global Communications Conference

Year: 2024 | Conference Paper |

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As the most vulnerable part of the traffic scenario, it is vital to ensure the safety of pedestrians. Accurately predicting the future trajectory of pedestrians not only ensures the safety of pedestrians but also improves the efficiency of traffic operations. In light of this, this paper presents a novel target-driven method for pedestrian trajectory prediction. The method uses bidirectional long ...Show More

Pedestrian Trajectory Prediction by Short-Term Target Estimation in Autonomous Driving Scenarios

Jing Yang;Peng Wang;Yaping Cui;Peng He;Dapeng Wu;Ruyan Wang

GLOBECOM 2024 - 2024 IEEE Global Communications Conference

Year: 2024 | Conference Paper |

GroupGCN: Group-Aware Dense Crowd Trajectory Prediction for Autonomous Driving

Ruyan Wang;Yudie Zhou;Dapeng Wu;Ang Duan;Yaping Cui;Peng He

GLOBECOM 2024 - 2024 IEEE Global Communications Conference

Year: 2024 | Conference Paper |

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Pedestrian trajectory prediction in autonomous driving is a critical and complex issue with important implications for road traffic safety. The primary challenges of this task stem from: 1) difficulty in simultaneous learning of individual and group motion behaviors within dense crowd scenarios and 2) limited interpretability of the model. In this work, we implement the social force model to the C...Show More

GroupGCN: Group-Aware Dense Crowd Trajectory Prediction for Autonomous Driving

Ruyan Wang;Yudie Zhou;Dapeng Wu;Ang Duan;Yaping Cui;Peng He

GLOBECOM 2024 - 2024 IEEE Global Communications Conference

Year: 2024 | Conference Paper |

Connection Performance Modeling and Analysis of a Radiosonde Network in a Typhoon

Hanyi Liu;Xianbin Cao;Peng Yang;Zehui Xiong;Tony Q. S. Quek;Dapeng Oliver Wu

IEEE Transactions on Communications

Year: 2024 | Early Access Article |

This paper is concerned with the theoretical modeling and analysis of uplink connection performance of a radiosonde network deployed in a typhoon. Similar to existing works, the stochastic geometry theory is leveraged to derive the expression of the uplink connection probability (CP) of a radiosonde. Nevertheless, existing works assume that network nodes are spherically or uniformly distributed. D...Show More

Connection Performance Modeling and Analysis of a Radiosonde Network in a Typhoon

Hanyi Liu;Xianbin Cao;Peng Yang;Zehui Xiong;Tony Q. S. Quek;Dapeng Oliver Wu

IEEE Transactions on Communications

Year: 2024 | Early Access Article |

A Robust Multisource Remote Sensing Image Matching Method Utilizing Attention and Feature Enhancement Against Noise Interference

;Chuanfeng Wei;Dapeng Wu;Yaping Cui;Peng He;;Ruyan Wang

IEEE Transactions on Geoscience and Remote Sensing

Year: 2024 | Volume: 62 | Journal Article |

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Image matching is a fundamental and critical task of multisource remote sensing image (RSI) applications. However, RSIs are susceptible to various noises. Accordingly, how to effectively achieve accurate matching in noise images is a challenging problem. To solve this issue, we propose a robust multisource RSI matching method utilizing attention and feature enhancement against noise interference. ...Show More

A Robust Multisource Remote Sensing Image Matching Method Utilizing Attention and Feature Enhancement Against Noise Interference

;Chuanfeng Wei;Dapeng Wu;Yaping Cui;Peng He;;Ruyan Wang

IEEE Transactions on Geoscience and Remote Sensing

Year: 2024 | Volume: 62 | Journal Article |

Cost Volume Aggregation in Stereo Matching Revisited: A Disparity Classification Perspective

Yun Wang;Longguang Wang;Kunhong Li;Yongjian Zhang;Dapeng Oliver Wu;Yulan Guo

IEEE Transactions on Image Processing

Year: 2024 | Volume: 33 | Journal Article |

Cited by: Papers (1)

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Cost aggregation plays a critical role in existing stereo matching methods. In this paper, we revisit cost aggregation in stereo matching from disparity classification and propose a generic yet efficient Disparity Context Aggregation (DCA) module to improve the performance of CNN-based methods. Our approach is based on an insight that a coarse disparity class prior is beneficial to disparity regre...Show More

Cost Volume Aggregation in Stereo Matching Revisited: A Disparity Classification Perspective

Yun Wang;Longguang Wang;Kunhong Li;Yongjian Zhang;Dapeng Oliver Wu;Yulan Guo

IEEE Transactions on Image Processing

Year: 2024 | Volume: 33 | Journal Article |

Age of Information in Internet of Vehicles: A Discrete-Time Multisource Queueing Model

Tianci Zhang;Zhengchuan Chen;Zhong Tian;Min Wang;Li Zhen;Dapeng Oliver Wu;Yonghui Li;Tony Q. S. Quek

IEEE Transactions on Communications

Year: 2024 | Early Access Article |

This work studies information freshness of a V2I status updating link in IoV. The status updating link is modeled as a multi-source Ber/Geo/1/1 non-preemptive or preemptive queue. We focus on statistical characteristics of the age of information (AoI) and peak AoI (PAoI). To fully track the AoI evolutions under non-preemptive and preemptive policies, Markov three-dimensional age process (3DAP) and...Show More

Age of Information in Internet of Vehicles: A Discrete-Time Multisource Queueing Model

Tianci Zhang;Zhengchuan Chen;Zhong Tian;Min Wang;Li Zhen;Dapeng Oliver Wu;Yonghui Li;Tony Q. S. Quek

IEEE Transactions on Communications

Year: 2024 | Early Access Article |

Channel Estimation Refinement for Tethered Aerial Platform Enabled Multi-User Communication Systems

Puguang An;Peng Yang;Xianbin Cao;Chaoqun You;Q. S. Tony Quek;Dapeng Oliver Wu

2024 IEEE/CIC International Conference on Communications in China (ICCC)

Year: 2024 | Conference Paper |

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This paper investigates the three-dimensional (3D) downlink sparse channel estimation for tethered aerial platformenabled multi-user communication systems operating in a frequency division duplexing mode with large-scale antenna arrays. To this end, we design a non-identical Bernoulli-Gaussian distribution-based channel model that reflects the potential common sparsity caused by distant scatterers...Show More

Channel Estimation Refinement for Tethered Aerial Platform Enabled Multi-User Communication Systems

Puguang An;Peng Yang;Xianbin Cao;Chaoqun You;Q. S. Tony Quek;Dapeng Oliver Wu

2024 IEEE/CIC International Conference on Communications in China (ICCC)

Year: 2024 | Conference Paper |

Energy-Efficient Ground-Air-Space Vehicular Crowdsensing by Hierarchical Multi-Agent Deep Reinforcement Learning With Diffusion Models

Yinuo Zhao;Chi Harold Liu;Tianjiao Yi;Guozheng Li;Dapeng Wu

IEEE Journal on Selected Areas in Communications

Year: 2024 | Volume: 42, Issue: 12 | Journal Article |

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The integrated ground-air-space (GAS) communications system can enhance post-disaster rescue and management efforts when traditional networks fail, by navigating unmanned ground vehicles (UGVs) and unmanned arieal vehicles (UAVs) to collaboratively collect sufficient data from point-of-interests (PoIs) in a timely manner. In this paper, we consider the GAS vehicular crowdsensing (VCS) campaign, wh...Show More

Energy-Efficient Ground-Air-Space Vehicular Crowdsensing by Hierarchical Multi-Agent Deep Reinforcement Learning With Diffusion Models

Yinuo Zhao;Chi Harold Liu;Tianjiao Yi;Guozheng Li;Dapeng Wu

IEEE Journal on Selected Areas in Communications

Year: 2024 | Volume: 42, Issue: 12 | Journal Article |

Quantum-Inspired Robust Networking Model With Multiverse Co-Evolution for Scale-Free IoT

Songwei Zhang;Xiaobo Zhou;Tie Qiu;Dapeng Oliver Wu

IEEE Transactions on Mobile Computing

Year: 2024 | Volume: 23, Issue: 12 | Journal Article |

Cited by: Papers (1)

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The robustness of scale-free Internet of Things (IoT) topology is seriously affected by malicious attacks. Improving the tolerance to node failures is critical to the stability of IoT systems. Heuristic algorithms, especially genetic algorithms, enhance the stability of network topology through the evolution of population chromosomes. However, the loss of genetic diversity makes the optimization e...Show More

Quantum-Inspired Robust Networking Model With Multiverse Co-Evolution for Scale-Free IoT

Songwei Zhang;Xiaobo Zhou;Tie Qiu;Dapeng Oliver Wu

IEEE Transactions on Mobile Computing

Year: 2024 | Volume: 23, Issue: 12 | Journal Article |

Improving the Transmission Rate by A Two-Phase Hybrid Duplex Scheme for Gaussian Relay Channel

Jianxin Duan;Zhengchuan Chen;Zhong Tian;Min Wang;Li Zhen;Dapeng O. Wu;Tony Q. S. Quek

ICC 2024 - IEEE International Conference on Communications

Year: 2024 | Conference Paper |

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Combining half-duplex (HD) and full-duplex (FD) is promising in improving the information transmission rate of relay channels. This work proposes a novel two-phase hybrid duplex scheme for Gaussian relay channel where the relay operates in FD mode for a fraction of time and only transmits information for the rest of time. The achievable rate of the proposed hybrid duplex scheme is characterized in...Show More

Improving the Transmission Rate by A Two-Phase Hybrid Duplex Scheme for Gaussian Relay Channel

Jianxin Duan;Zhengchuan Chen;Zhong Tian;Min Wang;Li Zhen;Dapeng O. Wu;Tony Q. S. Quek

ICC 2024 - IEEE International Conference on Communications

Year: 2024 | Conference Paper |

A Novel Lightweight Attention Network for Fall Detection in Internet of Medical Things

Dapeng Wu;Shiguang Li;Peng He;Yaping Cui;Ruyan Wang

ICC 2024 - IEEE International Conference on Communications

Year: 2024 | Conference Paper |

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Internet of Medical Things (IoMT) is increasingly gaining attentions in fall detection because of its ability to sense, monitor and analyze, which can provide proper assistance to the elderly with fragile health conditions. As fall events are infrequent, its important to timely detect its occurrence in order to alleviate the harmless. This paper presents a Lightweight Attention Network Fall Detect...Show More

A Novel Lightweight Attention Network for Fall Detection in Internet of Medical Things

Dapeng Wu;Shiguang Li;Peng He;Yaping Cui;Ruyan Wang

ICC 2024 - IEEE International Conference on Communications

Year: 2024 | Conference Paper |

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