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Heterogeneous user-centric cluster migration design for vehicular networks: The connectivity versus handover rate trade-off

Heterogeneous user-centric cluster migration design for vehicular networks: The connectivity versus handover rate trade-off
Heterogeneous user-centric cluster migration design for vehicular networks: The connectivity versus handover rate trade-off
User-centric (UC) clustering has recently emerged as a promising paradigm for enhancing the connectivity of mobile users by grouping an appropriate number of access points (APs), thus paving the way for seamlessly connected vehicular networks. However, for a high-velocity vehicular user, UC clustering may lead to overly frequent handovers (HOs), which increases the risk of throughput-reduction, call dropping and energy wastage. To mitigate this problem, we aim for reducing the HO overhead imposed on the heterogeneous UC (HUC) cluster migration process of vehicular networks. Specifically, we first conceive a novel hybrid HUC cluster migration strategy that adaptively switches between horizontal and vertical HOs for supporting both vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication. Then, a dynamic decision-making problem is formulated for balancing the benefits of HUC cluster migration and the total HO overhead, subject to realistic HUC clustering constraints. In the face of unknown vehicular mobility, we propose a sequential HUC cluster migration solution based on max-bipartite matching theory imposing a low complexity. As a design alternative, we also propose a holistic solution relying on model-free deep reinforcement learning (DRL). Finally, our numerical results reveal the superiority of the proposed cluster migration design in terms of striking a compelling trade-off between the per-user average data rate (PAR) and the number of HOs in different scenarios.
0018-9545
16027-16043
Lin, Yan
882ebefb-469c-4a10-a4f3-967e730ed105
Zhang, Zhengming
5ed2fab6-d6ca-45e1-ad78-8bbc871b978b
Huang, Yongming
aed0c759-1dce-4fd2-adfe-356e04dbb627
Li, Jun
173328aa-1759-4a78-9514-319c5a6ff4b0
Shu, Feng
862e7a4a-480e-440f-a2f9-6d31f6397930
Hanzo, Lajos
66e7266f-3066-4fc0-8391-e000acce71a1
Lin, Yan
882ebefb-469c-4a10-a4f3-967e730ed105
Zhang, Zhengming
5ed2fab6-d6ca-45e1-ad78-8bbc871b978b
Huang, Yongming
aed0c759-1dce-4fd2-adfe-356e04dbb627
Li, Jun
173328aa-1759-4a78-9514-319c5a6ff4b0
Shu, Feng
862e7a4a-480e-440f-a2f9-6d31f6397930
Hanzo, Lajos
66e7266f-3066-4fc0-8391-e000acce71a1

Lin, Yan, Zhang, Zhengming, Huang, Yongming, Li, Jun, Shu, Feng and Hanzo, Lajos (2020) Heterogeneous user-centric cluster migration design for vehicular networks: The connectivity versus handover rate trade-off. IEEE Transactions on Vehicular Technology, 69 (12), 16027-16043. (doi:10.1109/TVT.2020.3041521).

Record type: Article

Abstract

User-centric (UC) clustering has recently emerged as a promising paradigm for enhancing the connectivity of mobile users by grouping an appropriate number of access points (APs), thus paving the way for seamlessly connected vehicular networks. However, for a high-velocity vehicular user, UC clustering may lead to overly frequent handovers (HOs), which increases the risk of throughput-reduction, call dropping and energy wastage. To mitigate this problem, we aim for reducing the HO overhead imposed on the heterogeneous UC (HUC) cluster migration process of vehicular networks. Specifically, we first conceive a novel hybrid HUC cluster migration strategy that adaptively switches between horizontal and vertical HOs for supporting both vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication. Then, a dynamic decision-making problem is formulated for balancing the benefits of HUC cluster migration and the total HO overhead, subject to realistic HUC clustering constraints. In the face of unknown vehicular mobility, we propose a sequential HUC cluster migration solution based on max-bipartite matching theory imposing a low complexity. As a design alternative, we also propose a holistic solution relying on model-free deep reinforcement learning (DRL). Finally, our numerical results reveal the superiority of the proposed cluster migration design in terms of striking a compelling trade-off between the per-user average data rate (PAR) and the number of HOs in different scenarios.

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Heterogeneous User-Centric Cluster Migration Design for Vehicular Networks The Connectivity versus Handover Rate Trade-Off - Accepted Manuscript
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Accepted/In Press date: 25 November 2020
e-pub ahead of print date: 1 December 2020
Published date: December 2020

Identifiers

Local EPrints ID: 446590
URI: http://eprints.soton.ac.uk/id/eprint/446590
ISSN: 0018-9545
PURE UUID: 010c6b60-0f53-4d73-881a-5d5d2d3fcde8
ORCID for Lajos Hanzo: ORCID iD orcid.org/0000-0002-2636-5214

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Date deposited: 15 Feb 2021 17:33
Last modified: 18 Feb 2021 16:36

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Contributors

Author: Yan Lin
Author: Zhengming Zhang
Author: Yongming Huang
Author: Jun Li
Author: Feng Shu
Author: Lajos Hanzo ORCID iD

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