Fair resource optimization for cooperative non-terrestrial vehicular networks

Fair resource optimization; High altitude platform stations; Interference management; Non-terrestrial networks; Asynchrony; Communications networks; High altitude platform station; Non-terrestrial network; Optimization problems; Performance; Resources optimization; Terrestrial networks; Computer Networks and Communications

Résumé :

[en] Non-terrestrial networks aim to extend wireless communications capabilities beyond traditional terrestrial infrastructure by utilizing various platforms such as satellites, high-altitude platform stations (HAPS), and unmanned aerial vehicles to provide global or localized coverage. However, improving data rates in non-terrestrial cooperative communications (NTCC) networks presents unique challenges, necessitating innovative solutions. This paper presents a novel approach to enhance the request–response ratio (RRR) of NTCC in time asynchrony. By leveraging the advantages of HAPS, such as wide coverage, high altitude, and flexible deployment, we aim to optimize the performance of NTCC networks. We formulate an optimization problem considering the simultaneous connection between the HAPS and ground users, power distribution, and decoding order. The joint optimization problem is formulated as non-convex-non-linear and is also NP-hard, making it very challenging to obtain a globally optimal solution. To reduce the complexity of the problem and make it more tractable, we decouple it into subproblems and achieve an efficient solution in two steps. In the first step, we use the Gale–Shapley algorithm to solve the many-to-many two-sided matching problem of HAPS user terminal association, given the fixed decoding and power allocation. Then, we solve the decoding order and power allocation problem using the Dinkeback-like algorithm, given the optimal association in the second step. Our proposed method iteratively updates the preference lists, mitigating interference among HAPS and enhancing overall system performance. Through extensive simulations, we demonstrate that implementing our proposed schemes achieves high RRR compared to benchmark schemes. Additionally, when temporal asynchrony is employed alongside our approach, there is an increase in the overall performance obtained from the process.

Disciplines :

Sciences informatiques

Auteur, co-auteur :

Dutta, Ashit Kumar; Department of Computer Science and Information Systems, College of Applied Sciences, AlMaarefa University, Riyadh, Saudi Arabia

Alruwais, Nuha; Department of Computer Science and Engineering, College of Applied Studies and Community Services, King Saud University, Riyadh, Saudi Arabia

Alabdulkreem, Eatedal; Department of Information Systems, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia

Negm, Noha; Department of Computer Science, College of Science & Art at Mahayil, King Khalid University, Saudi Arabia

Darem, Abdulbasit A. ; Department of Computer Science at College of Science, Northern Border University, Arar, Saudi Arabia

Al Duhayyim, Mesfer; Department of Computer Science, College of Computer Engineering and Sciences, Prince Sattam bin Abdulaziz University, Al-Kharj, Saudi Arabia

KHAN, Wali Ullah ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SigCom

Nauman, Ali; School of Computer Science and Engineering Yeungnam University, Gyeongsan, South Korea

Co-auteurs externes :

yes

Langue du document :

Anglais

Titre :

Fair resource optimization for cooperative non-terrestrial vehicular networks

Titre original :

[en] Fair resource optimization for cooperative non-terrestrial vehicular networks

Date de publication/diffusion :

septembre 2024

Titre du périodique :

Computer Networks

ISSN :

1389-1286

eISSN :

1872-7069

Maison d'édition :

Elsevier B.V.

Volume/Tome :

251

Pagination :

110639

Peer reviewed :

Peer reviewed vérifié par ORBi

Focus Area :

Security, Reliability and Trust

URL complémentaire :

https://api.elsevier.com/content/article/PII:S1389128624004717?httpAccept=text/xml

Subventionnement (détails) :

This work was supported by the Researchers Supporting Project Number (MHIRSP2024005) Almaarefa University, Riyadh, Saudi Arabia. The authors extend their appreciation to the Deanship of Research and Graduate Studies at King Khalid University for funding this work through Large Research Project under grant number RGP2/86/45. Princess Nourah bint Abdulrahman University Researchers Supporting Project number (PNURSP2024R161), Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia. Research Supporting Project number (RSPD2024R608), King Saud University, Riyadh, Saudi Arabia. The authors extend their appreciation to the Deanship of Scientific Research at Northern Border University, Arar, KSA for funding this research work through the project number \u201CNBU-FFR-2024-2903-04\u201D. This study is supported via funding from Prince Sattam bin Abdulaziz University project number (PSAU/2024/R/1445).

Jeu de données :

https://www.sciencedirect.com/science/article/pii/S1389128624004717

Disponible sur ORBilu :

depuis le 11 décembre 2024

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