University of Oulu

P. Susarla et al., "Learning-Based Trajectory Optimization for 5G mmWave Uplink UAVs," 2020 IEEE International Conference on Communications Workshops (ICC Workshops), Dublin, Ireland, 2020, pp. 1-7, doi: 10.1109/ICCWorkshops49005.2020.9145194

Learning-based trajectory optimization for 5G mmWave uplink UAVs

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Author: Susarla, Praneeth1; Deng, Yansha2; Destino, Giuseppe1,2;
Organizations: 1University of Oulu, Finland
2King’s College London, United Kingdom
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 0.7 MB)
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Language: English
Published: Institute of Electrical and Electronics Engineers, 2020
Publish Date: 2020-11-02


A Connectivity-constrained based path planning for unmanned aerial vehicles (UAVs) is proposed within the coverage area of a 5G NR Base Station (BS) that uses mmWave technology. We consider an uplink communication between UAV and BS under multipath channel conditions for this problem. The objective is to guide a UAV, starting from a random location and reaching its destination within the BS coverage area, by learning a trajectory alongside achieving better connectivity. We propose simultaneous learning-based path planning of UAV and beam tracking at the BS side under urban macro-cellular(UMa) pathloss conditions, to reduce its sweeping time with apriori computational overhead using the deep reinforcement learning method such as Deep Q-Network (DQN). Our results show that our proposed learning-based joint path planning and beam tracking method is on par with the learning-based shortest path planning, besides beam tracking comparable to heuristic exhaustive beam searching method.

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Series: IEEE/CIC International Conference on Communications in China - Workshops
ISSN: 2474-9133
ISSN-E: 2474-9141
ISSN-L: 2474-9133
ISBN: 978-1-7281-7440-2
ISBN Print: 978-1-7281-7441-9
Pages: 1 - 7
Article number: 9145194
DOI: 10.1109/ICCWorkshops49005.2020.9145194
Host publication: 2020 IEEE International Conference on Communications Workshops (ICC Workshops)
Conference: IEEE International Conference on Communications Workshops
Type of Publication: A4 Article in conference proceedings
Field of Science: 213 Electronic, automation and communications engineering, electronics
Funding: The research leading to these results has received funding from European-Union project Primo-5G, Academy of Finland projects 6Genesis Flagship (Grant No. 318927), IIoT CONnectivity for mechanICAL systems (ICONICAL) and Positioning-aided Reliably-connected Industrial Systems with Mobile mmWave Access (PRISMA).
Academy of Finland Grant Number: 318927
Detailed Information: 318927 (Academy of Finland Funding decision)
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