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Hao Zhang - IEEE Xplore Author Profile

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Author details

Hao Zhang

Publications

14

Citations

115

Publications by Year

20212025

Co-Authors:

Naofal Al-DhahirNiklas BoersWei ChaiHong-Wei CuiRui Ding

Show All Co-Authors (30)

Hao Zhang

Affiliation

College of Electronic and Information Engineering, China

Publication Topics

Convolutional Neural Network,
Classification Accuracy,
Convolutional Layers,
Deep Learning,
Recurrent Neural Network,
Automatic Classification,
Automatic Modulation Classification,
Long Short-term Memory,
Training Data,
Additive Noise,
Classification Framework,
Feature Maps

Biography

Hao Zhang (Graduate Student Member, IEEE) received the master’s degree from the School of Information Engineering, Nanchang University, China, in 2020. He is currently pursuing the Ph.D. degree with the College of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, China. His research interests focus on machine learning, deep learning, wireless communication, and signal processing.(Based on document published on 23 June 2021).

Publications

14

Citations

115

Publications by Year

20212025

Co-Authors:

Naofal Al-Dhahir
Niklas Boers
Wei Chai
Hong-Wei Cui
Rui Ding

Show All Co-Authors (30)

Author's Published Works

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Showing 1-14 of 14 results

Conferences (7)

Journals (4)

Early Access Articles (3)

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Single Year
Hao Zhang(14)
Fuhui Zhou(12)
Qihui Wu(11)
Lu Yuan(4)
Chau Yuen(3)
College of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, China(4)
Nanjing University of Aeronautics and Astronautics, China(3)
College of Electronic and Information Engineering, China(2)
College of Electronic and Information Engineering and the Key Laboratory of Dynamic Cognitive System of Electromagnetic Spectrum Space, Nanjing University of Aeronautics and Astronautics, Nanjing, China(2)
Ministry of Industry and Information Technology, Nanjing, China(2)
2023 International Conference on Ubiquitous Communication (Ucom)(2)
IEEE Internet of Things Journal(2)
2021 IEEE 6th International Conference on Signal and Image Processing (ICSIP)(1)
2022 7th International Conference on Communication, Image and Signal Processing (CCISP)(1)
2022 9th International Conference on Internet of Things: Systems, Management and Security (IOTSMS)(1)
IEEE(14)
Xi'an, China(2)
Chengdu, China(1)
Hefei, China(1)
Milan, Italy(1)
Nanjing, China(1)
Convolutional Neural Network(10)
Convolutional Layers(9)
Classification Accuracy(8)
Automatic Classification(6)
Deep Learning(6)

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Results

Revolution of Wireless Signal Recognition for 6G: Recent Advances, Challenges and Future Directions

Hao Zhang;Fuhui Zhou;Hongyang Du;Qihui Wu;Chau Yuen

IEEE Communications Surveys & Tutorials

Year: 2025 | Early Access Article |

Wireless signal recognition (WSR) is a crucial technique for intelligent communications and spectrum sharing in the next six-generation (6G) wireless communication networks. It can be utilized to enhance network performance and efficiency, improve quality of service (QoS), and improve network security and reliability. Additionally, WSR can be applied for military applications such as signal interc...Show More

Revolution of Wireless Signal Recognition for 6G: Recent Advances, Challenges and Future Directions

Hao Zhang;Fuhui Zhou;Hongyang Du;Qihui Wu;Chau Yuen

IEEE Communications Surveys & Tutorials

Year: 2025 | Early Access Article |

FSOS-AMC: Few-Shot Open-Set Learning for Automatic Modulation Classification Over Multipath Fading Channels

Hao Zhang;Fuhui Zhou;Qihui Wu;Chau Yuen

IEEE Internet of Things Journal

Year: 2025 | Early Access Article |

Automatic modulation classification (AMC) plays a vital role in advancing future wireless communication networks. Although deep learning (DL)-based AMC frameworks have demonstrated remarkable classification capabilities, they typically require large-scale training datasets and assume consistent class distributions between training and testing data-prerequisites that prove challenging in few-shot a...Show More

FSOS-AMC: Few-Shot Open-Set Learning for Automatic Modulation Classification Over Multipath Fading Channels

Hao Zhang;Fuhui Zhou;Qihui Wu;Chau Yuen

IEEE Internet of Things Journal

Year: 2025 | Early Access Article |

FSOS-AMC: Few-Shot Open-Set Learning for Automatic Modulation Classification

Hao Zhang;Fuhui Zhou;Qihui Wu;Chau Yuen

2024 16th International Conference on Wireless Communications and Signal Processing (WCSP)

Year: 2024 | Conference Paper |

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Automatic modulation classification (AMC) is essential for the advancement and efficiency of future wireless commu-nication networks. Deep learning (DL)-based AMC frameworks have garnered extensive attention for their impressive classification performance. However, existing DL-based AMC frameworks rely on two assumptions, large-scale training data and the same class pool between the training and t...Show More

FSOS-AMC: Few-Shot Open-Set Learning for Automatic Modulation Classification

Hao Zhang;Fuhui Zhou;Qihui Wu;Chau Yuen

2024 16th International Conference on Wireless Communications and Signal Processing (WCSP)

Year: 2024 | Conference Paper |

When Geoscience Meets Foundation Models: Toward a general geoscience artificial intelligence system

Hao Zhang;Jin-Jian Xu;Hong-Wei Cui;Lin Li;Yaowen Yang;Chao-Sheng Tang;Niklas Boers

IEEE Geoscience and Remote Sensing Magazine

Year: 2024 | Early Access Article |

Cited by: Papers (2)

Artificial intelligence (AI) has significantly advanced Earth sciences, yet its full potential in to comprehensively modeling Earth’s complex dynamics remains unrealized. Geoscience foundation models (GFMs) emerge as a paradigm-shifting solution, integrating extensive cross-disciplinary data to enhance the simulation and understanding of Earth system dynamics. These data-centric AI models extract ...Show More

When Geoscience Meets Foundation Models: Toward a general geoscience artificial intelligence system

Hao Zhang;Jin-Jian Xu;Hong-Wei Cui;Lin Li;Yaowen Yang;Chao-Sheng Tang;Niklas Boers

IEEE Geoscience and Remote Sensing Magazine

Year: 2024 | Early Access Article |

SSwsrNet: A Semi-Supervised Few-Shot Learning Framework for Wireless Signal Recognition

Hao Zhang;Fuhui Zhou;Qihui Wu;Naofal Al-Dhahir

IEEE Transactions on Communications

Year: 2024 | Volume: 72, Issue: 9 | Journal Article |

Cited by: Papers (6)

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Wireless signal recognition (WSR) is crucial in modern and future wireless communication networks since it aims to identify properties of the received signal. Although many deep learning-based WSR models have been developed, they still rely on a large amount of labeled training data. Thus, they cannot tackle the few-sample problem in the practically and dynamically changing wireless communication ...Show More

SSwsrNet: A Semi-Supervised Few-Shot Learning Framework for Wireless Signal Recognition

Hao Zhang;Fuhui Zhou;Qihui Wu;Naofal Al-Dhahir

IEEE Transactions on Communications

Year: 2024 | Volume: 72, Issue: 9 | Journal Article |

Small Objects Recognition by Exploiting an Improved YOLOv5 Algorithm on the UAV Platform

Dongjun Han;Hao Zhang;Shujie Wang;Wei Chai;Haonan Zhou;Fuhui Zhou

2023 International Conference on Ubiquitous Communication (Ucom)

Year: 2023 | Conference Paper |

Cited by: Papers (2)

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The aerial imagery captured by unmanned aerial vehicles (UAVs) exhibits several challenging characteristics such as large variations in object size and complex backgrounds, which make it difficult for existing detectors to detect small objects in such imagery. To address the problem of false or missed detections of small objects in UAV imagery, the BHF-YOLOv5 detection model is proposed. Firstly, ...Show More

Small Objects Recognition by Exploiting an Improved YOLOv5 Algorithm on the UAV Platform

Dongjun Han;Hao Zhang;Shujie Wang;Wei Chai;Haonan Zhou;Fuhui Zhou

2023 International Conference on Ubiquitous Communication (Ucom)

Year: 2023 | Conference Paper |

A Novel Lightweight Automatic Modulation Classification Scheme Based on Inverted Residuals

Ruitao Wang;Hao Zhang;Ming Xu;Fuhui Zhou;Qihui Wu

2023 International Conference on Ubiquitous Communication (Ucom)

Year: 2023 | Conference Paper |

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Automatic modulation classification is an indispensable part of present and future wireless communication systems. The deep learning helps automatic modulation classification realize superior performance. However, most of the DL-based schemes have a large model scale and their computational complexity is high, which leads to the difficulty in the applications. In order to overcome this challenge, ...Show More

A Novel Lightweight Automatic Modulation Classification Scheme Based on Inverted Residuals

Ruitao Wang;Hao Zhang;Ming Xu;Fuhui Zhou;Qihui Wu

2023 International Conference on Ubiquitous Communication (Ucom)

Year: 2023 | Conference Paper |

Robust Semantic Communication Driven by Knowledge Graph

Linsheng Hu;Yihao Li;Hao Zhang;Lu Yuan;Fuhui Zhou;Qihui Wu

2022 9th International Conference on Internet of Things: Systems, Management and Security (IOTSMS)

Year: 2022 | Conference Paper |

Cited by: Papers (8)

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Semantic communications could improve the transmission efficiency significantly by extracting the semantic information. In contrast to traditional communication systems, semantic communication systems are additionally impacted by semantic noise because of the semantic, in addition to the physical noise present in the wireless communication environment. Semantic noise is a type of noise that leads ...Show More

Robust Semantic Communication Driven by Knowledge Graph

Linsheng Hu;Yihao Li;Hao Zhang;Lu Yuan;Fuhui Zhou;Qihui Wu

2022 9th International Conference on Internet of Things: Systems, Management and Security (IOTSMS)

Year: 2022 | Conference Paper |

GAN-Enabled Robust Backdoor Attack for UAV Recognition

Ming Xu;Yuhang Wu;Hao Zhang;Lu Yuan;Yiyao Wan;Fuhui Zhou;Qihui Wu

2022 7th International Conference on Communication, Image and Signal Processing (CCISP)

Year: 2022 | Conference Paper |

Cited by: Papers (1)

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Unmanned aerial vehicle (UAV) recognition is of crucial importance due to the blowout amount of UAVs and their threats on the public safety. Although many UAV recognition methods based on deep learning (DL) have been proposed by utilizing the radio frequency fingerprints and have achieved appreciable results, their vulnerability to adversarial attacks, especially backdoor attacks, has not been stu...Show More

GAN-Enabled Robust Backdoor Attack for UAV Recognition

Ming Xu;Yuhang Wu;Hao Zhang;Lu Yuan;Yiyao Wan;Fuhui Zhou;Qihui Wu

2022 7th International Conference on Communication, Image and Signal Processing (CCISP)

Year: 2022 | Conference Paper |

Data-and-Knowledge Dual-Driven Automatic Modulation Recognition for Wireless Communication Networks

Rui Ding;Hao Zhang;Fuhui Zhou;Qihui Wu;Zhu Han

ICC 2022 - IEEE International Conference on Communications

Year: 2022 | Conference Paper |

Cited by: Papers (16)

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Automatic modulation classification is of crucial importance in wireless communication networks. Deep learning based automatic modulation classification schemes have attracted extensive attention due to the superior accuracy. However, the data-driven method relies on a large amount of training samples and the classification accuracy is poor in the low signal-to-noise radio (SNR). In order to tackl...Show More

Data-and-Knowledge Dual-Driven Automatic Modulation Recognition for Wireless Communication Networks

Rui Ding;Hao Zhang;Fuhui Zhou;Qihui Wu;Zhu Han

ICC 2022 - IEEE International Conference on Communications

Year: 2022 | Conference Paper |

A Multiscale CNN Framework for Wireless Technique Classification in Internet of Things

Lu Yuan;Hao Zhang;Ming Xu;Fuhui Zhou;Qihui Wu

IEEE Internet of Things Journal

Year: 2022 | Volume: 9, Issue: 12 | Journal Article |

Cited by: Papers (11)

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Wireless technique classification (WTC) is of crucial importance in Internet of Things for realizing efficient spectrum sharing and interference management. However, the existing deep-learning-based methods have low classification accuracy, especially at low signal-to-noise ratio levels. In this article, a multiscale convolutional neural network framework is proposed for WTC. A multiscale module i...Show More

A Multiscale CNN Framework for Wireless Technique Classification in Internet of Things

Lu Yuan;Hao Zhang;Ming Xu;Fuhui Zhou;Qihui Wu

IEEE Internet of Things Journal

Year: 2022 | Volume: 9, Issue: 12 | Journal Article |

A Novel Automatic Modulation Classification Scheme Based on Multi-Scale Networks

Hao Zhang;Fuhui Zhou;Qihui Wu;Wei Wu;Rose Qingyang Hu

IEEE Transactions on Cognitive Communications and Networking

Year: 2022 | Volume: 8, Issue: 1 | Journal Article |

Cited by: Papers (42)

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Automatic modulation classification enables intelligent communications and it is of crucial importance in today’s and future wireless communication networks. Although many automatic modulation classification schemes have been proposed, they cannot tackle the intra-class diversity problem caused by the dynamic changes of the wireless communication environment. In order to overcome this problem, ins...Show More

A Novel Automatic Modulation Classification Scheme Based on Multi-Scale Networks

Hao Zhang;Fuhui Zhou;Qihui Wu;Wei Wu;Rose Qingyang Hu

IEEE Transactions on Cognitive Communications and Networking

Year: 2022 | Volume: 8, Issue: 1 | Journal Article |

Small Object Detection Based on Modified FSSD and Model Compression

Qingcai Wang;Hao Zhang;Xianggong Hong;Qinqin Zhou

2021 IEEE 6th International Conference on Signal and Image Processing (ICSIP)

Year: 2021 | Conference Paper |

Cited by: Papers (13)

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Small objects have relatively low resolution, the unobvious visual features which are difficult to be extracted, so the existing object detection methods cannot effectively detect small objects, and the detection speed and stability are poor. Thus, this paper proposes a small object detection algorithm based on FSSD, meanwhile, in order to reduce the computational cost and storage space, pruning i...Show More

Small Object Detection Based on Modified FSSD and Model Compression

Qingcai Wang;Hao Zhang;Xianggong Hong;Qinqin Zhou

2021 IEEE 6th International Conference on Signal and Image Processing (ICSIP)

Year: 2021 | Conference Paper |

Automatic Modulation Classification Using Involution Enabled Residual Networks

Hao Zhang;Lu Yuan;Guangyu Wu;Fuhui Zhou;Qihui Wu

IEEE Wireless Communications Letters

Year: 2021 | Volume: 10, Issue: 11 | Journal Article |

Cited by: Papers (14)

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Automatic modulation classification (AMC) is of crucial importance for realizing wireless intelligence communications. Many deep learning based models especially convolution neural networks (CNNs) have been proposed for AMC. However, the computation cost is very high, which makes them inappropriate for beyond the fifth generation wireless communication networks that have stringent requirements on ...Show More

Automatic Modulation Classification Using Involution Enabled Residual Networks

Hao Zhang;Lu Yuan;Guangyu Wu;Fuhui Zhou;Qihui Wu

IEEE Wireless Communications Letters

Year: 2021 | Volume: 10, Issue: 11 | Journal Article |

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