A Joint UAV Trajectory, User Association, and Beamforming Design Strategy for Multi-UAV-Assisted ISAC Systems

被引:5
|
作者
Zhang, Ruizhi [1 ]
Zhang, Ying [1 ]
Tang, Rui [2 ,3 ]
Zhao, Huapeng [4 ]
Xiao, Qing [1 ]
Wang, Chenye [1 ]
机构
[1] Univ Elect Sci & Technol China, Sch Informat & Commun Engn, Chengdu 611731, Peoples R China
[2] China West Normal Univ, Sch Elect Informat Engn, Key Lab Optimizat Theory & Applicat, Nanchong 637002, Peoples R China
[3] China West Normal Univ, Internet Things Percept & Big Data Anal Key Lab N, Nanchong 637002, Peoples R China
[4] Univ Elect Sci & Technol China, Sch Elect Sci & Engn, Chengdu 611731, Peoples R China
来源
IEEE INTERNET OF THINGS JOURNAL | 2024年 / 11卷 / 18期
基金
中国国家自然科学基金;
关键词
Alternating optimization; fractional programming (FP); integrated sensing and communication (ISAC); matching theory; resource allocation; sequential quadratic programming (SQP); unmanned aerial vehicle (UAV); DATA-COLLECTION; POWER-CONTROL; COMMUNICATION; RADAR; OPTIMIZATION;
D O I
10.1109/JIOT.2024.3430390
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In this article, we investigate a resource allocation problem for a multiunmanned aerial vehicle (UAV) assisted integrated sensing and communication (ISAC) system, where a group of dual-functional UAVs perform simultaneous radar sensing of a target and data communication with multiple ground users (GUs). In particular, the trajectory of UAVs, user association, and beamforming design are jointly considered to maximize the sum weighted bit rate of all GUs while ensuring the sensing beampattern gain of the target. To cope with the above mixed-integer nonconvex optimization problem, we propose an efficient strategy by decomposing the original problem into two subproblems under the alternating optimization framework. For the user association and beamforming design, we propose a novel algorithm to circumvent the coupling relationship among GUs and UAVs by leveraging matching theory and fractional programming theory. For the nonconvex UAV trajectory subproblem, we apply the sequential quadratic programming to obtain a suboptimal solution by solving a sequence of quadratic programming problems. The above two subproblems are iteratively solved and a stable solution is obtained upon convergence. Simulation results show that the proposed strategy outperforms various benchmark schemes that are based on the deferred acceptance algorithm, K-means algorithm, and a heuristic algorithm. It is demonstrated that the proposed strategy efficiently improve the sensing beampattern gain and communication rate.
引用
收藏
页码:29360 / 29374
页数:15
相关论文
共 50 条
  • [41] Joint Trajectory, Sensing, and Transmission Design for IRS-Assisted Cognitive UAV Systems
    Deng, Qian
    Yu, Guangcheng
    Liang, Xiaopeng
    Shu, Feng
    Wang, Jiangzhou
    IEEE WIRELESS COMMUNICATIONS LETTERS, 2024, 13 (01) : 233 - 237
  • [42] Trajectory Design and Power Control for Multi-UAV Assisted Wireless Networks: A Machine Learning Approach
    Liu, Xiao
    Liu, Yuanwei
    Chen, Yue
    Hanzo, Lajos
    IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2019, 68 (08) : 7957 - 7969
  • [43] Joint Deployment and Resource Allocation for Service Provision in Multi-UAV-Assisted Wireless Networks
    Geng, Shengqi
    Wei, Zhe
    Zhao, Jian
    Shen, Furao
    Joung, Jingon
    Sun, Sumei
    IEEE INTERNET OF THINGS JOURNAL, 2024, 11 (22): : 37269 - 37286
  • [44] URLLC Facilitated by Mobile UAV Relay and RIS: A Joint Design of Passive Beamforming, Blocklength, and UAV Positioning
    Ranjha, Ali
    Kaddoum, Georges
    IEEE INTERNET OF THINGS JOURNAL, 2021, 8 (06): : 4618 - 4627
  • [45] Multi-Agent Deep Reinforcement Learning for Joint Decoupled User Association and Trajectory Design in Full-Duplex Multi-UAV Networks
    Dai, Chen
    Zhu, Kun
    Hossain, Ekram
    IEEE TRANSACTIONS ON MOBILE COMPUTING, 2023, 22 (10) : 6056 - 6070
  • [46] AoI-Minimal Task Assignment and Trajectory Optimization in Multi-UAV-Assisted Wireless Powered IoT Networks
    Gu, Yu
    Qiu, Hongbing
    Chen, Baoqing
    DRONES, 2025, 9 (02)
  • [47] Joint optimization of UAV position and user grouping for UAV-assisted hybrid NOMA systems
    Sun, Yuan
    Dong, Zhicheng
    Yang, Liuqing
    Cai, Donghong
    Zhou, Weixi
    Zhou, Yanxia
    COMPUTATIONAL INTELLIGENCE, 2024, 40 (01)
  • [48] Joint Distributed Beamforming and Backscattering for UAV-Assisted WPSNs
    Mao, Zhi
    Hu, Fengye
    Wu, Wen
    Wu, Huaqing
    Shen, Xuemin
    IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, 2023, 22 (03) : 1510 - 1522
  • [49] ISAC-Enabled Multi-UAV Cooperative Perception and Trajectory Optimization
    Wang, Qinyuan
    Chai, Rong
    Sun, Ruijin
    Pu, Renyan
    Chen, Qianbin
    IEEE INTERNET OF THINGS JOURNAL, 2024, 11 (24): : 40982 - 40995
  • [50] Joint Optimization of UAV Trajectory Statistical Precoding and User Scheduling
    Zuo, Xingxuan
    Han, Gangtao
    Mu, Xiaomin
    IEEE ACCESS, 2020, 8 : 73232 - 73240