Spatio-Temporal Trajectory Design for UAVs: Enhancing URLLC and LoS Transmission in Communications

被引:0
|
作者
Yu, Jingxiang [1 ]
Wu, Juntao [2 ]
Jiang, Hong [1 ]
机构
[1] Southwest Univ Sci & Technol, Sch Informat Engn, Mianyang 621010, Peoples R China
[2] Univ Elect Sci & Technol China, Glasgow Coll, Chengdu 611731, Peoples R China
基金
中国国家自然科学基金;
关键词
Autonomous aerial vehicles; Trajectory; Ultra reliable low latency communication; Optimization; Device-to-device communication; Polynomials; Vectors; UAV; trajectory planner; URLLC; short packet; LoS; D2D comunication; CONNECTIVITY; NETWORK;
D O I
10.1109/LWC.2024.3416742
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This letter explores the potential of unmanned aerial vehicles (UAVs) to support Ultra-Reliable Low-Latency Communication (URLLC). The primary objective is to enhance link quality by leveraging the high-probability Line-of-Sight (LoS) links inherent in UAV communication systems. This letter presents a novel trajectory planning framework that addresses energy consumption in the high-dynamic flight states of UAVs while maintaining communication quality by managing communication constraints. To achieve this, the framework introduces a LoS persistence-based motion prediction method and a path exploration technique that considers Device-to-Device (D2D) communication quality. These methods establish optimal topology structures and evaluate the costs associated with signal quality loss. Additionally, the study proposes an efficient trajectory optimization method for generating spatio-temporally optimal trajectories within predefined flight corridors, aimed at achieving optimal LoS link quality. To ensure flight safety and LoS persistence, specific optimization expressions are designed to concurrently address all these requirements. Simulation results indicate that this approach not only maintains high communication signal link quality but also minimizes flight time.
引用
收藏
页码:2417 / 2421
页数:5
相关论文
共 50 条
  • [31] SPATIO-TEMPORAL PATTERNS IN A CHOLERA TRANSMISSION MODEL
    Misra, A. K.
    Tiwari, Milan
    Sharma, Anupama
    JOURNAL OF BIOLOGICAL SYSTEMS, 2015, 23 (03) : 471 - 484
  • [32] SiamSTA: Spatio-Temporal Attention based Siamese Tracker for Tracking UAVs
    Huang, Bo
    Chen, Junjie
    Xu, Tingfa
    Wang, Ying
    Jiang, Shenwang
    Wang, Yuncheng
    Wang, Lei
    Li, Jianan
    2021 IEEE/CVF INTERNATIONAL CONFERENCE ON COMPUTER VISION WORKSHOPS (ICCVW 2021), 2021, : 1204 - 1212
  • [33] Enhancing Spatio-Temporal Identity: States of Existence and Presence
    Hallot, Pierre
    Billen, Roland
    ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION, 2016, 5 (05):
  • [34] PPQ-Trajectory: Spatio-temporal Quantization for Querying in Large Trajectory Repositories
    Wang, Shuang
    Ferhatosmanoglu, Hakan
    PROCEEDINGS OF THE VLDB ENDOWMENT, 2020, 14 (02): : 215 - 227
  • [35] Directional Higher Order Information for Spatio-Temporal Trajectory Dataset
    Wang, Ye
    Lee, Kyungmi
    Lee, Ickjai
    2014 IEEE INTERNATIONAL CONFERENCE ON DATA MINING WORKSHOP (ICDMW), 2014, : 35 - 42
  • [36] A trajectory data compression algorithm based on spatio-temporal characteristics
    Zhong Y.
    Kong J.
    Zhang J.
    Jiang Y.
    Fan X.
    Wang Z.
    PeerJ Computer Science, 2022, 8
  • [37] Spatio-temporal Similarity Measure for Network Constrained Trajectory Data
    Xia, Ying
    Wang, Guo-Yin
    Zhang, Xu
    Kim, Gyoung-Bae
    Bae, Hae-Young
    INTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE SYSTEMS, 2011, 4 (05) : 1070 - 1079
  • [38] Spatio-temporal Similarity Measure for Network Constrained Trajectory Data
    Xia Y.
    Wang G.-Y.
    Zhang X.
    Kim G.-B.
    Bae H.-Y.
    International Journal of Computational Intelligence Systems, 2011, 4 (5) : 1070 - 1079
  • [39] Group Vehicle Trajectory Prediction With Global Spatio-Temporal Graph
    Xu, Dongwei
    Shang, Xuetian
    Liu, Yewanze
    Peng, Hang
    Li, Haijian
    IEEE TRANSACTIONS ON INTELLIGENT VEHICLES, 2023, 8 (02): : 1219 - 1229
  • [40] GraphTCN: Spatio-Temporal Interaction Modeling for Human Trajectory Prediction
    Wang, Chengxin
    Cai, Shaofeng
    An, Gary
    2021 IEEE WINTER CONFERENCE ON APPLICATIONS OF COMPUTER VISION WACV 2021, 2021, : 3449 - 3458