Poster: Optimizing ABS Deployment via LSTM-based Mobility and Data Traffic Demand Prediction
Pages 893 - 894
Abstract
This paper proposes a proactive aerial base station (ABS) deployment framework for hotspots that optimizes the placement of ABSs based on mobility and data traffic demand prediction using a LSTM model. We design a greedy-based ABS deployment algorithm to solve the data rate maximization problem, which is known to be NP-hard. Simulation results demonstrate that the proposed algorithm achieves a higher data rate with fewer ABSs compared to benchmark methods.
References
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Qianqian Zhang, Walid Saad, Mehdi Bennis, Xing Lu, Mérouane Debbah, and Wangda Zuo. Predictive Deployment of UAV Base Stations in Wireless Networks: Machine Learning Meets Contract Theory. IEEE Trans. Wirel. Commun., 20(1):637--652, 2021.
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Javad Sabzehali, Vijay K. Shah, Qiang Fan, Biplav Choudhury, Lingjia Liu, and Jeffrey H. Reed. Optimizing Number, Placement, and Backhaul Connectivity of Multi-UAV Networks. IEEE Internet Things J., 9(21):21548--21560, 2022.
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Feiyang Guo, Linyan Lu, Zelin Zang, and Mohammad Shikh-Bahaei. Machine Learning for Predictive Deployment of UAVs With Multiple Access. IEEE Open J. Commun. Soc., 4:908--921, 2023.
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Yanan Liu, Xianbin Wang, Gary Boudreau, Akram Bin Sediq, and Hatem Abou-zeid. Deep Learning Based Hotspot Prediction and Beam Management for Adaptive Virtual Small Cell in 5G Networks. IEEE Trans. Emerg. Top. Comput. Intell., 4(1):83--94, 2020.
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Hailong Huang and Andrey V. Savkin. A Method of Optimized Deployment of Charging Stations for Drone Delivery. IEEE Trans. Transp. Electrif., 6(2):510--518, 2020.
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Nithin Babu, Petar Popovski, and Constantinos B. Papadias. Cost-Efficient Deployment of a Reliable Multi-UAV Unmanned Aerial System. In IEEE Veh. Technol. Conf.(VTC2022-Fall), pages 1--5, 2022.
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Index Terms
- Poster: Optimizing ABS Deployment via LSTM-based Mobility and Data Traffic Demand Prediction
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Information
Published In
November 2024
950 pages
ISBN:9798400706974
DOI:10.1145/3666025
- Chair:
- Jie Liu,
- Co-chairs:
- Yuanchao Shu,
- Jiming Chen,
- Program Chair:
- Yuan He,
- Program Co-chair:
- Rui Tan
Copyright © 2024 Copyright held by the owner/author(s).
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the owner/author(s).
Sponsors
- SIGARCH: ACM Special Interest Group on Computer Architecture
- SIGBED: ACM Special Interest Group on Embedded Systems
- SIGMETRICS: ACM Special Interest Group on Measurement and Evaluation
- SIGMOBILE: ACM Special Interest Group on Mobility of Systems, Users, Data and Computing
- SIGOPS: ACM Special Interest Group on Operating Systems
Publisher
Association for Computing Machinery
New York, NY, United States
Publication History
Published: 04 November 2024
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- Poster
Funding Sources
- National Research Foundation of Korea(NRF)
Conference
SenSys '24
SenSys '24: 22nd ACM Conference on Embedded Networked Sensor Systems
November 4 - 7, 2024
Hangzhou, China
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Overall Acceptance Rate 174 of 867 submissions, 20%
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