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Modularity-based user-centric clustering and resource allocation for ultra dense networks

Modularity-based user-centric clustering and resource allocation for ultra dense networks
Modularity-based user-centric clustering and resource allocation for ultra dense networks

A novel modularity-based user-centric (MUC) clustering is conceived for resource allocation in ultra dense networks (UDNs), in order to maximise the sum-rate per orthogonal resource block (RB). The idea of MUC clustering is to decompose the UDN into several sub-networks by exploiting the inherent group structure of user equipment (UE). In particular, we propose a modified Louvain method for MUC clustering relying on efficient resource allocation heuristics. Our numerical results show the superiority of our MUC design.

resource allocation, Ultra dense networks, unsupervised learning, user-centric clustering
0018-9545
Lin, Yan
47e4ee77-1450-4dc1-98b2-d629072f011d
Zhang, Rong
e54ae375-3495-4e40-aff1-4b8635ee2ede
Yang, Luxi
66464b8a-7efa-4535-84a6-2410a364e855
Hanzo, Lajos
66e7266f-3066-4fc0-8391-e000acce71a1
Lin, Yan
47e4ee77-1450-4dc1-98b2-d629072f011d
Zhang, Rong
e54ae375-3495-4e40-aff1-4b8635ee2ede
Yang, Luxi
66464b8a-7efa-4535-84a6-2410a364e855
Hanzo, Lajos
66e7266f-3066-4fc0-8391-e000acce71a1

Lin, Yan, Zhang, Rong, Yang, Luxi and Hanzo, Lajos (2018) Modularity-based user-centric clustering and resource allocation for ultra dense networks. IEEE Transactions on Vehicular Technology. (doi:10.1109/TVT.2018.2875547).

Record type: Article

Abstract

A novel modularity-based user-centric (MUC) clustering is conceived for resource allocation in ultra dense networks (UDNs), in order to maximise the sum-rate per orthogonal resource block (RB). The idea of MUC clustering is to decompose the UDN into several sub-networks by exploiting the inherent group structure of user equipment (UE). In particular, we propose a modified Louvain method for MUC clustering relying on efficient resource allocation heuristics. Our numerical results show the superiority of our MUC design.

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More information

Accepted/In Press date: 2018
e-pub ahead of print date: 18 October 2018
Keywords: resource allocation, Ultra dense networks, unsupervised learning, user-centric clustering

Identifiers

Local EPrints ID: 425701
URI: http://eprints.soton.ac.uk/id/eprint/425701
ISSN: 0018-9545
PURE UUID: 023428d4-b31d-4043-b4b1-aa1e7c738a3e
ORCID for Lajos Hanzo: ORCID iD orcid.org/0000-0002-2636-5214

Catalogue record

Date deposited: 01 Nov 2018 17:30
Last modified: 18 Mar 2024 02:36

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Contributors

Author: Yan Lin
Author: Rong Zhang
Author: Luxi Yang
Author: Lajos Hanzo ORCID iD

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