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Real-Time Large-Scale 6G Satellite-UAV Networks
Queen's University Belfast, United Kingdom.
Ho Chi Minh City University of Technology, Vietnam.
Dong Nai University,Vietnam.
Queen's University Belfast, United Kingdom.
Show others and affiliations
2023 (English)In: IEEE Workshop on Statistical Signal Processing Proceedings, IEEE Computer Society, 2023, p. 100-104Conference paper, Published paper (Refereed)
Abstract [en]

In this paper, we consider an Internet-of-Things network supported by several satellites and multiple cache-assisted unmanned aerial vehicles (UAVs). We propose an optimisation problem with the aim of minimising the total network latency. To reduce the complexity of the original problem, it is divided into three sub-problems, namely, clustering ground users associated with UAVs, cache placement in UAVs (to support the network in avoiding backhaul congestion), and power allocation for satellites and UAVs. A non-cooperative game is designed to obtain the solution to the clustering problem; a genetic algorithm, which is powerful in the scenario of many variables, is employed to obtain the optimal solution to the high-complexity caching problem; and a quick estimation technique is used for power allocation. The total network latency is then minimised by using alternating optimisation technique. Numerical results prove the efficiency of our methods compared to other traditional ones. © 2023 IEEE.

Place, publisher, year, edition, pages
IEEE Computer Society, 2023. p. 100-104
Series
IEEE Statistical Signal Processing Workshop (SSP), ISSN 2373-0803, E-ISSN 2693-3551
Keywords [en]
Antennas, Complex networks, Game theory, Numerical methods, Satellites, Unmanned aerial vehicles (UAV), Aerial vehicle, Cache placement, Clusterings, Large-scales, Network latencies, Optimization problems, Power allocations, Real- time, Sub-problems, Vehicle network, Genetic algorithms
National Category
Signal Processing
Identifiers
URN: urn:nbn:se:bth-25358DOI: 10.1109/SSP53291.2023.10208078ISI: 001051091700021Scopus ID: 2-s2.0-85168913203ISBN: 9781665452458 (print)OAI: oai:DiVA.org:bth-25358DiVA, id: diva2:1795387
Conference
22nd IEEE Statistical Signal Processing Workshop, SSP 2023, Hanoi, 2 July through 5 July 2023
Funder
EU, Horizon Europe, UKRI 10061165Available from: 2023-09-08 Created: 2023-09-08 Last updated: 2023-10-26Bibliographically approved

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Zepernick, Hans-Juergen

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