Dezhi Chen - IEEE Xplore Author Profile

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Author details

Dezhi Chen

Publications

8

Citations

72

Publications by Year

20212025

Co-Authors:

Xiaoyuan FuQianlong FuSong GuoZhu HanRongxin Han

Show All Co-Authors (18)

Dezhi Chen

Affiliation

Pengcheng Laboratory, Shenzhen, China

Publication Topics

Deep Reinforcement Learning,
Markov Decision Process,
Network Slicing,
Time Slot,
Age Of Information,
Control Problem,
Coordination Of Resources,
Deep Learning,
Deep Neural Network,
Deep Neural Network Model,
Deep Q-network,
Deep Reinforcement Learning Algorithm

Biography

Dezhi Chen is currently working toward the PhD degree with the Beijing University of Posts and Telecommunications, Beijing, China. His research interests include UAV control, game theory, and next-generation mobile communication networks using reinforcement learning, and artificial intelligence technologies.(Based on document published on 22 June 2023).

Publications

8

Citations

72

Publications by Year

20212025

Co-Authors:

Xiaoyuan Fu
Qianlong Fu
Song Guo
Zhu Han
Rongxin Han

Show All Co-Authors (18)

Author's Published Works

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Showing 1-8 of 8 results

Journals (5)

Conferences (2)

Early Access Articles (1)

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Dezhi Chen(8)
Jianxin Liao(8)
Jingyu Wang(8)
Qi Qi(8)
Zirui Zhuang(4)
State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, China(6)
Department of Electrical and Computer Engineering, University of Houston, Houston, TX, USA(3)
Department of Computer Science and Engineering, Kyung Hee University, Seoul, South Korea(3)
Department of Computing, The Hong Kong Polytechnic University, Hong Kong, China(2)
EBUPT.COM, Beijing, China(2)
IEEE Transactions on Intelligent Transportation Systems(2)
2022 IEEE Smartworld, Ubiquitous Intelligence & Computing, Scalable Computing & Communications, Digital Twin, Privacy Computing, Metaverse, Autonomous & Trusted Vehicles (SmartWorld/UIC/ScalCom/DigitalTwin/PriComp/Meta)(1)
2024 International Joint Conference on Neural Networks (IJCNN)(1)
IEEE Internet of Things Journal(1)
IEEE Transactions on Mobile Computing(1)
IEEE(8)
Haikou, China(1)
Yokohama, Japan(1)
Deep Reinforcement Learning(8)
Time Slot(5)
Markov Decision Process(4)
State Space(4)
Unmanned Aerial Vehicles(4)

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Flight Trajectory Control With Network-Oriented Hierarchical Reinforcement Learning for UAVs-Assisted Data Time-Sensitive IoT

Jingyu Wang;Songyang Li;Dezhi Chen;Qianlong Fu;Qi Qi;Haifeng Sun;Bo He;Jianxin Liao

IEEE Transactions on Intelligent Transportation Systems

Year: 2025 | Early Access Article |

Within the Internet of Things (IoT) for traffic monitoring, the employment of autonomous aerial vehicles (AAVs) as relays for collecting and transmitting real-time data from traffic sensors to base stations has proven a promising approach. In UAV-assisted Data Time-Sensitive IoT (DTIoT), the Age of Information is a crucial metric assessing data freshness, measuring the elapsed time from traffic se...Show More

Flight Trajectory Control With Network-Oriented Hierarchical Reinforcement Learning for UAVs-Assisted Data Time-Sensitive IoT

Jingyu Wang;Songyang Li;Dezhi Chen;Qianlong Fu;Qi Qi;Haifeng Sun;Bo He;Jianxin Liao

IEEE Transactions on Intelligent Transportation Systems

Year: 2025 | Early Access Article |

Work Together to Keep Fresh: Hierarchical Learning for UAVs-assisted Data Time-Sensitive IoT

Songyang Li;Dezhi Chen;Qianlong Fu;Qi Qi;Jingyu Wang;Jianxin Liao

2024 International Joint Conference on Neural Networks (IJCNN)

Year: 2024 | Conference Paper |

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In the context of disaster warning and monitoring within the Internet of Things (IoT), the utilization of unmanned aerial vehicles (UAVs) as relays to gather time-sensitive data from disaster monitoring sensors and transmit it to the base station (BS) has emerged as a highly promising application. In UAV-assisted Data Time-Sensitive IoT (DTIoT), the Age of Information (AoI) serves as a critical pe...Show More

Work Together to Keep Fresh: Hierarchical Learning for UAVs-assisted Data Time-Sensitive IoT

Songyang Li;Dezhi Chen;Qianlong Fu;Qi Qi;Jingyu Wang;Jianxin Liao

2024 International Joint Conference on Neural Networks (IJCNN)

Year: 2024 | Conference Paper |

Dynamic Network Slice for Bursty Edge Traffic

Rongxin Han;Jingyu Wang;Qi Qi;Dezhi Chen;Zirui Zhuang;Haifeng Sun;Xiaoyuan Fu;Jianxin Liao;Song Guo

IEEE/ACM Transactions on Networking

Year: 2024 | Volume: 32, Issue: 4 | Journal Article |

Cited by: Papers (1)

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Edge network slicing promises better utilization of network resources by dynamically allocating resources on demand. However, addressing the imbalance between slice resources and user demands becomes challenging when complex user behaviors lead to bursty traffic within the edge network. Hence, we propose a comprehensive dynamic slice strategy with two coupled sub-strategies (i) bursty-sensitive sl...Show More

Dynamic Network Slice for Bursty Edge Traffic

Rongxin Han;Jingyu Wang;Qi Qi;Dezhi Chen;Zirui Zhuang;Haifeng Sun;Xiaoyuan Fu;Jianxin Liao;Song Guo

IEEE/ACM Transactions on Networking

Year: 2024 | Volume: 32, Issue: 4 | Journal Article |

Transformer-Based Reinforcement Learning for Scalable Multi-UAV Area Coverage

Dezhi Chen;Qi Qi;Qianlong Fu;Jingyu Wang;Jianxin Liao;Zhu Han

IEEE Transactions on Intelligent Transportation Systems

Year: 2024 | Volume: 25, Issue: 8 | Journal Article |

Cited by: Papers (4)

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Compared with terrestrial networks, unmanned aerial vehicles (UAVs) have the characteristics of flexible deployment and strong adaptability, which are an important supplement to intelligent transportation systems (ITS). In this paper, we focus on the multi-UAV network area coverage problem (ACP) which require intelligent UAVs long-term trajectory decisions in the complex and scalable network envir...Show More

Transformer-Based Reinforcement Learning for Scalable Multi-UAV Area Coverage

Dezhi Chen;Qi Qi;Qianlong Fu;Jingyu Wang;Jianxin Liao;Zhu Han

IEEE Transactions on Intelligent Transportation Systems

Year: 2024 | Volume: 25, Issue: 8 | Journal Article |

Slice Sandwich: Jagged Slicing Multi-Tier Dynamic Resources for Diversified V2X Services

Yu Liu;Zirui Zhuang;Qi Qi;Jingyu Wang;Dezhi Chen;Lu Lu;Hongwei Yang;Jianxin Liao;Zhu Han

IEEE Transactions on Mobile Computing

Year: 2024 | Volume: 23, Issue: 5 | Journal Article |

Cited by: Papers (1)

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With the advancement of intelligent transportation systems, a series of diversified V2X applications come into being, which have different key performance indicators (KPIs) and transmission features. Moreover, multi-tier computing as a new system-level architecture distributes computing and communication capabilities anywhere between the cloud and the end-user. Unfortunately, the existing network ...Show More

Slice Sandwich: Jagged Slicing Multi-Tier Dynamic Resources for Diversified V2X Services

Yu Liu;Zirui Zhuang;Qi Qi;Jingyu Wang;Dezhi Chen;Lu Lu;Hongwei Yang;Jianxin Liao;Zhu Han

IEEE Transactions on Mobile Computing

Year: 2024 | Volume: 23, Issue: 5 | Journal Article |

Multi-SP Network Slicing Parallel Relieving Edge Network Conflict

Rongxin Han;Dezhi Chen;Song Guo;Jingyu Wang;Qi Qi;Lu Lu;Jianxin Liao

IEEE Transactions on Parallel and Distributed Systems

Year: 2023 | Volume: 34, Issue: 11 | Journal Article |

Cited by: Papers (3)

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Network slicing is rapidly prevailing in the edge network, which provides computing, network, and storage resources for various services. When the multiple service providers (SPs) respond to their tenants in parallel, individual decisions on the dynamic and shared edge network may lead to resource conflicts, which affects the delivery of network slicing services. Existing works ignore resource int...Show More

Multi-SP Network Slicing Parallel Relieving Edge Network Conflict

Rongxin Han;Dezhi Chen;Song Guo;Jingyu Wang;Qi Qi;Lu Lu;Jianxin Liao

IEEE Transactions on Parallel and Distributed Systems

Year: 2023 | Volume: 34, Issue: 11 | Journal Article |

Digital Twins-based Multi-agent Deep Reinforcement Learning for UAV-assisted Vehicle Edge Computing

Chen Hu;Qi Qi;Lei Zhang;Cong Liu;Dezhi Chen;Jianxin Liao;Zirui Zhuang;Jingyu Wang

2022 IEEE Smartworld, Ubiquitous Intelligence & Computing, Scalable Computing & Communications, Digital Twin, Privacy Computing, Metaverse, Autonomous & Trusted Vehicles (SmartWorld/UIC/ScalCom/DigitalTwin/PriComp/Meta)

Year: 2022 | Conference Paper |

Cited by: Papers (5)

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UAV-assisted vehicle-edge-computing (VEC) has become a viable solution for a new generation of intelligent transportation systems (ITS) and has attracted widespread attention from academia and industry. Compared with fixed ground devices, UAV can provide line-of-sight (LoS) link and has good mobility, which better matches the needs of individual wireless connectivity and high mobility of vehicle. ...Show More

Digital Twins-based Multi-agent Deep Reinforcement Learning for UAV-assisted Vehicle Edge Computing

Chen Hu;Qi Qi;Lei Zhang;Cong Liu;Dezhi Chen;Jianxin Liao;Zirui Zhuang;Jingyu Wang

2022 IEEE Smartworld, Ubiquitous Intelligence & Computing, Scalable Computing & Communications, Digital Twin, Privacy Computing, Metaverse, Autonomous & Trusted Vehicles (SmartWorld/UIC/ScalCom/DigitalTwin/PriComp/Meta)

Year: 2022 | Conference Paper |

Mean Field Deep Reinforcement Learning for Fair and Efficient UAV Control

Dezhi Chen;Qi Qi;Zirui Zhuang;Jingyu Wang;Jianxin Liao;Zhu Han

IEEE Internet of Things Journal

Year: 2021 | Volume: 8, Issue: 2 | Journal Article |

Cited by: Papers (58)

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Unmanned aerial vehicles (UAVs) can provide flexible network coverage services. UAVs can be applied in a large number of scenarios, such as emergency communication and network access in areas without terrestrial network coverage. However, UAVs are limited to relatively short communication range and restricted energy resources. In extreme conditions such as disasters, there may also be a problem th...Show More

Mean Field Deep Reinforcement Learning for Fair and Efficient UAV Control

Dezhi Chen;Qi Qi;Zirui Zhuang;Jingyu Wang;Jianxin Liao;Zhu Han

IEEE Internet of Things Journal

Year: 2021 | Volume: 8, Issue: 2 | Journal Article |

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