Resource allocation for UAV-assisted backscatter communication

被引:0
作者
Zhengqiang Wang
Duan Hong
Zifu Fan
Xiaoyu Wan
Yongjun Xu
Bin Duo
机构
[1] Chongqing University of Posts and Telecommunications,School of Communication and Information Engineering
[2] Chongqing University of Posts and Telecommunications,Institute of Next Generation Network Application Technology
[3] Chengdu University of Technology,College of Computer and Network Security
来源
EURASIP Journal on Wireless Communications and Networking | / 2022卷
关键词
Backscatter communication; Unmanned aerial vehicle (UAV); Trajectory design; Resource allocation; Time division multiple access (TDMA);
D O I
暂无
中图分类号
学科分类号
摘要
As a promising new technology for green communication, backscatter communication has attracted wide attention in academics and industry. This paper studies the resource allocation problem for an unmanned aerial vehicle (UAV)-assisted backscatter communication network. The UAV acts as an airborne mobile base station and broadcasts signals to the ground backscatter devices (BDs), which transmit the data signals to the backscatter receiver (BR) in a backscattered manner. Specifically, the ground-based BDs communicate with the BR using a dynamic protocol based on time division multiple access. Considering the fairness among BDs, we aim to investigate maximizing the minimum (max–min) rate of the proposed network by jointly optimizing backscatter device scheduling, reflection coefficient, UAV’s power control, and UAV’s trajectory. The optimization problem is a non-convex problem, which is challenging to obtain the optimal solution. Therefore, we propose an efficient iterative algorithm to decompose the optimization problem into four subproblems by the block coordinate descent method. The variables are alternatively optimized by the interior point method and successive convex approximation techniques in each iteration. Finally, simulation results show that the max–min rate of the system obtained by the proposed scheme outperforms other benchmark schemes.
引用
收藏
相关论文
共 50 条
[41]   MAHTD-DDPG-Based Multiobjective Resource Allocation for UAV-Assisted Wireless Network [J].
Sun, Wentao ;
Li, Zan ;
Shi, Jia ;
Bai, Zixuan ;
Wang, Feng ;
Quek, Tony Q. S. .
IEEE JOURNAL ON MINIATURIZATION FOR AIR AND SPACE SYSTEMS, 2025, 6 (02) :70-81
[42]   Resource Allocation and Trajectory Design in UAV-Assisted Jamming Wideband Cognitive Radio Networks [J].
Wang, Yuhao ;
Chen, Long ;
Zhou, Yifan ;
Liu, Xiaodong ;
Zhou, Fuhui ;
Al-Dhahir, Naofal .
IEEE TRANSACTIONS ON COGNITIVE COMMUNICATIONS AND NETWORKING, 2021, 7 (02) :635-647
[43]   URLLC-Oriented Joint Power Control and Resource Allocation in UAV-Assisted Networks [J].
Chen, Kanghua ;
Wang, Ying ;
Zhao, Junwei ;
Wang, Xue ;
Fei, Zixuan .
IEEE INTERNET OF THINGS JOURNAL, 2021, 8 (12) :10103-10116
[44]   Joint Task and Resource Allocation in SDN-based UAV-assisted Cellular Networks [J].
Zhu, Yujiao ;
Wang, Sihua ;
Liu, Xuanlin ;
Tong, Haonan ;
Yin, Changchuan .
2020 IEEE/CIC INTERNATIONAL CONFERENCE ON COMMUNICATIONS IN CHINA (ICCC), 2020, :430-435
[45]   Online Trajectory Optimization and Resource Allocation in UAV-Assisted NOMA-MEC Systems [J].
Lu, Yadong ;
Zhou, Huan ;
Wang, Hengtao ;
Jiang, Tingyao ;
Leung, Victor C. M. .
2024 IEEE/ACM 32ND INTERNATIONAL SYMPOSIUM ON QUALITY OF SERVICE, IWQOS, 2024,
[46]   Deep Reinforcement Learning for Jointly Resource Allocation and Trajectory Planning in UAV-Assisted Networks [J].
Jwaifel, Arwa Mahmoud ;
Van Do, Tien .
COMPUTATIONAL COLLECTIVE INTELLIGENCE, ICCCI 2023, 2023, 14162 :71-83
[47]   Energy-Efficient Resource Allocation for UAV-Assisted Vehicular Networks With Spectrum Sharing [J].
Qi, Weijing ;
Song, Qingyang ;
Guo, Lei ;
Jamalipour, Abbas .
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2022, 71 (07) :7691-7702
[48]   UAV-assisted wireless powered Internet of Things: Joint trajectory optimization and resource allocation [J].
Na, Zhenyu ;
Zhang, Mengshu ;
Wang, Jun ;
Gao, Zihe .
AD HOC NETWORKS, 2020, 98
[49]   A Mobile Edge Computing Framework for Task Offloading and Resource Allocation in UAV-assisted VANETs [J].
He, Yixin ;
Zhai, Daosen ;
Zhang, Ruonan ;
Du, Jianbo ;
Aujla, Gagangeet Singh ;
Cao, Haotong .
IEEE CONFERENCE ON COMPUTER COMMUNICATIONS WORKSHOPS (IEEE INFOCOM WKSHPS 2021), 2021,
[50]   Energy efficient UAV-assisted communication with joint resource allocation and trajectory optimization in NOMA-based internet of remote things [J].
Zhou, Cong ;
Shi, Shuo ;
Wu, Chenyu ;
Wei, Shouming .
WIRELESS NETWORKS, 2024, 30 (06) :5361-5374