Budgeted Thompson Sampling for Trajectory Planning in UAV-Enhanced NOMA Emergency Networks

Ramez Hosny; Sherief Hashima; Ehab Mahmoud Mohamed; Kohei Hatano; Rokaia M. Zaki; Basem M. Elhalawany

doi:10.1109/IoTaIS60147.2023.10346048

Budgeted Thompson Sampling for Trajectory Planning in UAV-Enhanced NOMA Emergency Networks

Ramez Hosny, Sherief Hashima, Ehab Mahmoud Mohamed, Kohei Hatano, Rokaia M. Zaki, Basem M. Elhalawany

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Citation (Scopus)

Abstract

Modern Non-Orthogonal Multiple Access (NOMA) and Unmanned Aerial Vehicles (UAVs) wireless technologies are valuable assets in emergency scenarios to enable quick and flexible infrastructure of wireless communication networks. Still, efficient trajectory planning of UAV-NOMA emergency networks is a big challenge where the UAV should assist the maximum number of survivors and optimize its limited battery energy. Hence, in this paper, we formulate this problem as Budgeted Thompson Sampling for UAV Trajectory Planning (BTS-UTP), which is a theoretically guaranteed Budgeted Multi-Armed Bandits (BMAB) derived from the original TS via considering the random cost for drawing an arm and the total cost is constrained by budget (UAV energy). Here the bandit player, arms, cost, and payoff are the UAV, disaster area grids, UAV battery expenditure, and the number of assisted survivors. Numerical results ensure the superior performance of the proposed BTS-UTP technique.

Original language	English
Title of host publication	Proceedings of 2023 IEEE International Conference on Internet of Things and Intelligence Systems, IoTaIS 2023
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	14-20
Number of pages	7
ISBN (Electronic)	9798350319040
DOIs	https://doi.org/10.1109/IoTaIS60147.2023.10346048
Publication status	Published - 2023
Event	2023 IEEE International Conference on Internet of Things and Intelligence Systems, IoTaIS 2023 - Hybrid, Bali, Indonesia Duration: Nov 28 2023 → Nov 30 2023

Publication series

Name	Proceedings of 2023 IEEE International Conference on Internet of Things and Intelligence Systems, IoTaIS 2023

Conference

Conference	2023 IEEE International Conference on Internet of Things and Intelligence Systems, IoTaIS 2023
Country/Territory	Indonesia
City	Hybrid, Bali
Period	11/28/23 → 11/30/23

All Science Journal Classification (ASJC) codes

Artificial Intelligence
Computer Networks and Communications
Information Systems
Computer Science Applications

Access to Document

10.1109/IoTaIS60147.2023.10346048

Cite this

Hosny, R., Hashima, S., Mohamed, E. M., Hatano, K., Zaki, R. M., & Elhalawany, B. M. (2023). Budgeted Thompson Sampling for Trajectory Planning in UAV-Enhanced NOMA Emergency Networks. In Proceedings of 2023 IEEE International Conference on Internet of Things and Intelligence Systems, IoTaIS 2023 (pp. 14-20). (Proceedings of 2023 IEEE International Conference on Internet of Things and Intelligence Systems, IoTaIS 2023). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IoTaIS60147.2023.10346048

Budgeted Thompson Sampling for Trajectory Planning in UAV-Enhanced NOMA Emergency Networks. / Hosny, Ramez; Hashima, Sherief; Mohamed, Ehab Mahmoud et al.
Proceedings of 2023 IEEE International Conference on Internet of Things and Intelligence Systems, IoTaIS 2023. Institute of Electrical and Electronics Engineers Inc., 2023. p. 14-20 (Proceedings of 2023 IEEE International Conference on Internet of Things and Intelligence Systems, IoTaIS 2023).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Hosny, R, Hashima, S, Mohamed, EM, Hatano, K, Zaki, RM & Elhalawany, BM 2023, Budgeted Thompson Sampling for Trajectory Planning in UAV-Enhanced NOMA Emergency Networks. in Proceedings of 2023 IEEE International Conference on Internet of Things and Intelligence Systems, IoTaIS 2023. Proceedings of 2023 IEEE International Conference on Internet of Things and Intelligence Systems, IoTaIS 2023, Institute of Electrical and Electronics Engineers Inc., pp. 14-20, 2023 IEEE International Conference on Internet of Things and Intelligence Systems, IoTaIS 2023, Hybrid, Bali, Indonesia, 11/28/23. https://doi.org/10.1109/IoTaIS60147.2023.10346048

Hosny R, Hashima S, Mohamed EM, Hatano K, Zaki RM, Elhalawany BM. Budgeted Thompson Sampling for Trajectory Planning in UAV-Enhanced NOMA Emergency Networks. In Proceedings of 2023 IEEE International Conference on Internet of Things and Intelligence Systems, IoTaIS 2023. Institute of Electrical and Electronics Engineers Inc. 2023. p. 14-20. (Proceedings of 2023 IEEE International Conference on Internet of Things and Intelligence Systems, IoTaIS 2023). doi: 10.1109/IoTaIS60147.2023.10346048

Hosny, Ramez ; Hashima, Sherief ; Mohamed, Ehab Mahmoud et al. / Budgeted Thompson Sampling for Trajectory Planning in UAV-Enhanced NOMA Emergency Networks. Proceedings of 2023 IEEE International Conference on Internet of Things and Intelligence Systems, IoTaIS 2023. Institute of Electrical and Electronics Engineers Inc., 2023. pp. 14-20 (Proceedings of 2023 IEEE International Conference on Internet of Things and Intelligence Systems, IoTaIS 2023).

@inproceedings{acaa193037ba44d6b122b3dbd3236d90,

title = "Budgeted Thompson Sampling for Trajectory Planning in UAV-Enhanced NOMA Emergency Networks",

abstract = "Modern Non-Orthogonal Multiple Access (NOMA) and Unmanned Aerial Vehicles (UAVs) wireless technologies are valuable assets in emergency scenarios to enable quick and flexible infrastructure of wireless communication networks. Still, efficient trajectory planning of UAV-NOMA emergency networks is a big challenge where the UAV should assist the maximum number of survivors and optimize its limited battery energy. Hence, in this paper, we formulate this problem as Budgeted Thompson Sampling for UAV Trajectory Planning (BTS-UTP), which is a theoretically guaranteed Budgeted Multi-Armed Bandits (BMAB) derived from the original TS via considering the random cost for drawing an arm and the total cost is constrained by budget (UAV energy). Here the bandit player, arms, cost, and payoff are the UAV, disaster area grids, UAV battery expenditure, and the number of assisted survivors. Numerical results ensure the superior performance of the proposed BTS-UTP technique.",

author = "Ramez Hosny and Sherief Hashima and Mohamed, {Ehab Mahmoud} and Kohei Hatano and Zaki, {Rokaia M.} and Elhalawany, {Basem M.}",

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 2023 IEEE International Conference on Internet of Things and Intelligence Systems, IoTaIS 2023 ; Conference date: 28-11-2023 Through 30-11-2023",

year = "2023",

doi = "10.1109/IoTaIS60147.2023.10346048",

language = "English",

series = "Proceedings of 2023 IEEE International Conference on Internet of Things and Intelligence Systems, IoTaIS 2023",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "14--20",

booktitle = "Proceedings of 2023 IEEE International Conference on Internet of Things and Intelligence Systems, IoTaIS 2023",

address = "United States",

}

TY - GEN

T1 - Budgeted Thompson Sampling for Trajectory Planning in UAV-Enhanced NOMA Emergency Networks

AU - Hosny, Ramez

AU - Hashima, Sherief

AU - Mohamed, Ehab Mahmoud

AU - Hatano, Kohei

AU - Zaki, Rokaia M.

AU - Elhalawany, Basem M.

PY - 2023

Y1 - 2023

N2 - Modern Non-Orthogonal Multiple Access (NOMA) and Unmanned Aerial Vehicles (UAVs) wireless technologies are valuable assets in emergency scenarios to enable quick and flexible infrastructure of wireless communication networks. Still, efficient trajectory planning of UAV-NOMA emergency networks is a big challenge where the UAV should assist the maximum number of survivors and optimize its limited battery energy. Hence, in this paper, we formulate this problem as Budgeted Thompson Sampling for UAV Trajectory Planning (BTS-UTP), which is a theoretically guaranteed Budgeted Multi-Armed Bandits (BMAB) derived from the original TS via considering the random cost for drawing an arm and the total cost is constrained by budget (UAV energy). Here the bandit player, arms, cost, and payoff are the UAV, disaster area grids, UAV battery expenditure, and the number of assisted survivors. Numerical results ensure the superior performance of the proposed BTS-UTP technique.

AB - Modern Non-Orthogonal Multiple Access (NOMA) and Unmanned Aerial Vehicles (UAVs) wireless technologies are valuable assets in emergency scenarios to enable quick and flexible infrastructure of wireless communication networks. Still, efficient trajectory planning of UAV-NOMA emergency networks is a big challenge where the UAV should assist the maximum number of survivors and optimize its limited battery energy. Hence, in this paper, we formulate this problem as Budgeted Thompson Sampling for UAV Trajectory Planning (BTS-UTP), which is a theoretically guaranteed Budgeted Multi-Armed Bandits (BMAB) derived from the original TS via considering the random cost for drawing an arm and the total cost is constrained by budget (UAV energy). Here the bandit player, arms, cost, and payoff are the UAV, disaster area grids, UAV battery expenditure, and the number of assisted survivors. Numerical results ensure the superior performance of the proposed BTS-UTP technique.

UR - http://www.scopus.com/inward/record.url?scp=85182402361&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85182402361&partnerID=8YFLogxK

U2 - 10.1109/IoTaIS60147.2023.10346048

DO - 10.1109/IoTaIS60147.2023.10346048

M3 - Conference contribution

AN - SCOPUS:85182402361

T3 - Proceedings of 2023 IEEE International Conference on Internet of Things and Intelligence Systems, IoTaIS 2023

SP - 14

EP - 20

BT - Proceedings of 2023 IEEE International Conference on Internet of Things and Intelligence Systems, IoTaIS 2023

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2023 IEEE International Conference on Internet of Things and Intelligence Systems, IoTaIS 2023

Y2 - 28 November 2023 through 30 November 2023

ER -

Budgeted Thompson Sampling for Trajectory Planning in UAV-Enhanced NOMA Emergency Networks

Abstract

Publication series

Conference

All Science Journal Classification (ASJC) codes

Access to Document

Other files and links

Fingerprint

Cite this