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
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).
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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08496818
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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
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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
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