Joint Resources and Phase-Shift Optimization of MEC-Enabled UAV in IRS-Assisted 6G THz Networks

Yu Min Park; Sheikh Salman Hassan; Yan Kyaw Tun; Zhu Han; Choong Seon Hong

doi:10.1109/NOMS54207.2022.9789841

Joint Resources and Phase-Shift Optimization of MEC-Enabled UAV in IRS-Assisted 6G THz Networks

Yu Min Park, Sheikh Salman Hassan, Yan Kyaw Tun, Zhu Han, Choong Seon Hong

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

27 Citations (Scopus)

Abstract

Terahertz (THz) communication has the promise of enabling ultra-high data speeds in the sixth-generation (6G) wireless networks. Meanwhile, an intelligent reflecting surface (IRS) may influence incident electromagnetic wave propagation by changing the phase shifts with passive reflecting components. It can enhance spectrum efficiency and coverage capability, and minimize blockage vulnerability caused by severe THz wave propagation attenuation and poor diffraction. Recently, unmanned aerial vehicles (UAVs) have provided the services of aerial-based multi-access edge computing (MEC) ubiquitously. Motivated by above facts, this paper considers the IRS-assisted MEC-enabled UAV system for 6G THz communications networks. To that aim, the joint optimization of UAV computation power, IRS phase shift, and THz sub-band allocation are being explored to reduce total network latency. However, the designed problem is mixed-integer non-linear programming (MINLP), which is challenging to solve in polynomial time. Therefore, an iterative algorithm based on the Hungarian algorithm and the Whale-Optimization algorithm (WOA) is proposed to address this problem. The Hungarian algorithm optimizes the sub-band allocation while WOA optimizes the IRS phase shift. Finally, simulation results show that the proposed algorithm can reduce network latency by up to 50% compared to baseline algorithms.

Original language	English
Title of host publication	Proceedings of the IEEE/IFIP Network Operations and Management Symposium 2022
Subtitle of host publication	Network and Service Management in the Era of Cloudification, Softwarization and Artificial Intelligence, NOMS 2022
Editors	Pal Varga, Lisandro Zambenedetti Granville, Alex Galis, Istvan Godor, Noura Limam, Prosper Chemouil, Jerome Francois, Marc-Oliver Pahl
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781665406017
DOIs	https://doi.org/10.1109/NOMS54207.2022.9789841
Publication status	Published - 2022
Event	2022 IEEE/IFIP Network Operations and Management Symposium, NOMS 2022 - Budapest, Hungary Duration: 25 Apr 2022 → 29 Apr 2022

Publication series

Name	Proceedings of the IEEE/IFIP Network Operations and Management Symposium 2022: Network and Service Management in the Era of Cloudification, Softwarization and Artificial Intelligence, NOMS 2022

Conference

Conference	2022 IEEE/IFIP Network Operations and Management Symposium, NOMS 2022
Country/Territory	Hungary
City	Budapest
Period	25/04/22 → 29/04/22

Bibliographical note

Publisher Copyright:
© 2022 IEEE.

Keywords

Intelligent reflecting surface (IRS)
phase-shift
sixth-generation (6G)
terahertz (THz) communication
unmanned aerial vehicles (UAVs)

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10.1109/NOMS54207.2022.9789841

Cite this

Park, Y. M., Hassan, S. S., Tun, Y. K., Han, Z., & Hong, C. S. (2022). Joint Resources and Phase-Shift Optimization of MEC-Enabled UAV in IRS-Assisted 6G THz Networks. In P. Varga, L. Z. Granville, A. Galis, I. Godor, N. Limam, P. Chemouil, J. Francois, & M.-O. Pahl (Eds.), Proceedings of the IEEE/IFIP Network Operations and Management Symposium 2022: Network and Service Management in the Era of Cloudification, Softwarization and Artificial Intelligence, NOMS 2022 (Proceedings of the IEEE/IFIP Network Operations and Management Symposium 2022: Network and Service Management in the Era of Cloudification, Softwarization and Artificial Intelligence, NOMS 2022). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/NOMS54207.2022.9789841

Park, Yu Min ; Hassan, Sheikh Salman ; Tun, Yan Kyaw et al. / Joint Resources and Phase-Shift Optimization of MEC-Enabled UAV in IRS-Assisted 6G THz Networks. Proceedings of the IEEE/IFIP Network Operations and Management Symposium 2022: Network and Service Management in the Era of Cloudification, Softwarization and Artificial Intelligence, NOMS 2022. editor / Pal Varga ; Lisandro Zambenedetti Granville ; Alex Galis ; Istvan Godor ; Noura Limam ; Prosper Chemouil ; Jerome Francois ; Marc-Oliver Pahl. Institute of Electrical and Electronics Engineers Inc., 2022. (Proceedings of the IEEE/IFIP Network Operations and Management Symposium 2022: Network and Service Management in the Era of Cloudification, Softwarization and Artificial Intelligence, NOMS 2022).

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title = "Joint Resources and Phase-Shift Optimization of MEC-Enabled UAV in IRS-Assisted 6G THz Networks",

abstract = "Terahertz (THz) communication has the promise of enabling ultra-high data speeds in the sixth-generation (6G) wireless networks. Meanwhile, an intelligent reflecting surface (IRS) may influence incident electromagnetic wave propagation by changing the phase shifts with passive reflecting components. It can enhance spectrum efficiency and coverage capability, and minimize blockage vulnerability caused by severe THz wave propagation attenuation and poor diffraction. Recently, unmanned aerial vehicles (UAVs) have provided the services of aerial-based multi-access edge computing (MEC) ubiquitously. Motivated by above facts, this paper considers the IRS-assisted MEC-enabled UAV system for 6G THz communications networks. To that aim, the joint optimization of UAV computation power, IRS phase shift, and THz sub-band allocation are being explored to reduce total network latency. However, the designed problem is mixed-integer non-linear programming (MINLP), which is challenging to solve in polynomial time. Therefore, an iterative algorithm based on the Hungarian algorithm and the Whale-Optimization algorithm (WOA) is proposed to address this problem. The Hungarian algorithm optimizes the sub-band allocation while WOA optimizes the IRS phase shift. Finally, simulation results show that the proposed algorithm can reduce network latency by up to 50% compared to baseline algorithms.",

keywords = "Intelligent reflecting surface (IRS), phase-shift, sixth-generation (6G), terahertz (THz) communication, unmanned aerial vehicles (UAVs)",

author = "Park, {Yu Min} and Hassan, {Sheikh Salman} and Tun, {Yan Kyaw} and Zhu Han and Hong, {Choong Seon}",

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year = "2022",

doi = "10.1109/NOMS54207.2022.9789841",

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

editor = "Pal Varga and Granville, {Lisandro Zambenedetti} and Alex Galis and Istvan Godor and Noura Limam and Prosper Chemouil and Jerome Francois and Marc-Oliver Pahl",

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Park, YM, Hassan, SS, Tun, YK, Han, Z & Hong, CS 2022, Joint Resources and Phase-Shift Optimization of MEC-Enabled UAV in IRS-Assisted 6G THz Networks. in P Varga, LZ Granville, A Galis, I Godor, N Limam, P Chemouil, J Francois & M-O Pahl (eds), Proceedings of the IEEE/IFIP Network Operations and Management Symposium 2022: Network and Service Management in the Era of Cloudification, Softwarization and Artificial Intelligence, NOMS 2022. Proceedings of the IEEE/IFIP Network Operations and Management Symposium 2022: Network and Service Management in the Era of Cloudification, Softwarization and Artificial Intelligence, NOMS 2022, Institute of Electrical and Electronics Engineers Inc., 2022 IEEE/IFIP Network Operations and Management Symposium, NOMS 2022, Budapest, Hungary, 25/04/22. https://doi.org/10.1109/NOMS54207.2022.9789841

Joint Resources and Phase-Shift Optimization of MEC-Enabled UAV in IRS-Assisted 6G THz Networks. / Park, Yu Min; Hassan, Sheikh Salman; Tun, Yan Kyaw et al.
Proceedings of the IEEE/IFIP Network Operations and Management Symposium 2022: Network and Service Management in the Era of Cloudification, Softwarization and Artificial Intelligence, NOMS 2022. ed. / Pal Varga; Lisandro Zambenedetti Granville; Alex Galis; Istvan Godor; Noura Limam; Prosper Chemouil; Jerome Francois; Marc-Oliver Pahl. Institute of Electrical and Electronics Engineers Inc., 2022. (Proceedings of the IEEE/IFIP Network Operations and Management Symposium 2022: Network and Service Management in the Era of Cloudification, Softwarization and Artificial Intelligence, NOMS 2022).

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

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AU - Hassan, Sheikh Salman

AU - Tun, Yan Kyaw

AU - Han, Zhu

AU - Hong, Choong Seon

PY - 2022

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N2 - Terahertz (THz) communication has the promise of enabling ultra-high data speeds in the sixth-generation (6G) wireless networks. Meanwhile, an intelligent reflecting surface (IRS) may influence incident electromagnetic wave propagation by changing the phase shifts with passive reflecting components. It can enhance spectrum efficiency and coverage capability, and minimize blockage vulnerability caused by severe THz wave propagation attenuation and poor diffraction. Recently, unmanned aerial vehicles (UAVs) have provided the services of aerial-based multi-access edge computing (MEC) ubiquitously. Motivated by above facts, this paper considers the IRS-assisted MEC-enabled UAV system for 6G THz communications networks. To that aim, the joint optimization of UAV computation power, IRS phase shift, and THz sub-band allocation are being explored to reduce total network latency. However, the designed problem is mixed-integer non-linear programming (MINLP), which is challenging to solve in polynomial time. Therefore, an iterative algorithm based on the Hungarian algorithm and the Whale-Optimization algorithm (WOA) is proposed to address this problem. The Hungarian algorithm optimizes the sub-band allocation while WOA optimizes the IRS phase shift. Finally, simulation results show that the proposed algorithm can reduce network latency by up to 50% compared to baseline algorithms.

AB - Terahertz (THz) communication has the promise of enabling ultra-high data speeds in the sixth-generation (6G) wireless networks. Meanwhile, an intelligent reflecting surface (IRS) may influence incident electromagnetic wave propagation by changing the phase shifts with passive reflecting components. It can enhance spectrum efficiency and coverage capability, and minimize blockage vulnerability caused by severe THz wave propagation attenuation and poor diffraction. Recently, unmanned aerial vehicles (UAVs) have provided the services of aerial-based multi-access edge computing (MEC) ubiquitously. Motivated by above facts, this paper considers the IRS-assisted MEC-enabled UAV system for 6G THz communications networks. To that aim, the joint optimization of UAV computation power, IRS phase shift, and THz sub-band allocation are being explored to reduce total network latency. However, the designed problem is mixed-integer non-linear programming (MINLP), which is challenging to solve in polynomial time. Therefore, an iterative algorithm based on the Hungarian algorithm and the Whale-Optimization algorithm (WOA) is proposed to address this problem. The Hungarian algorithm optimizes the sub-band allocation while WOA optimizes the IRS phase shift. Finally, simulation results show that the proposed algorithm can reduce network latency by up to 50% compared to baseline algorithms.

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M3 - Conference contribution

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T3 - Proceedings of the IEEE/IFIP Network Operations and Management Symposium 2022: Network and Service Management in the Era of Cloudification, Softwarization and Artificial Intelligence, NOMS 2022

BT - Proceedings of the IEEE/IFIP Network Operations and Management Symposium 2022

A2 - Varga, Pal

A2 - Granville, Lisandro Zambenedetti

A2 - Galis, Alex

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PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2022 IEEE/IFIP Network Operations and Management Symposium, NOMS 2022

Y2 - 25 April 2022 through 29 April 2022

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Park YM, Hassan SS, Tun YK, Han Z, Hong CS. Joint Resources and Phase-Shift Optimization of MEC-Enabled UAV in IRS-Assisted 6G THz Networks. In Varga P, Granville LZ, Galis A, Godor I, Limam N, Chemouil P, Francois J, Pahl MO, editors, Proceedings of the IEEE/IFIP Network Operations and Management Symposium 2022: Network and Service Management in the Era of Cloudification, Softwarization and Artificial Intelligence, NOMS 2022. Institute of Electrical and Electronics Engineers Inc. 2022. (Proceedings of the IEEE/IFIP Network Operations and Management Symposium 2022: Network and Service Management in the Era of Cloudification, Softwarization and Artificial Intelligence, NOMS 2022). doi: 10.1109/NOMS54207.2022.9789841

Joint Resources and Phase-Shift Optimization of MEC-Enabled UAV in IRS-Assisted 6G THz Networks

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