Resource allocation scheme for 5G C-RAN: a Swarm Intelligence based approach

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dc.contributor.authorAri, Ado Adamou Abba
dc.contributor.authorGueroui, Abdelhak
dc.contributor.authorTitouna, Chafiq
dc.contributor.authorThiare, Ousmane
dc.contributor.authorAliouat, Zibouda
dc.date.accessioned2022-05-10T12:56:51Z
dc.date.available2022-05-10T12:56:51Z
dc.date.issued2019-09-22
dc.descriptionIn recent years, wireless communications are subjected to a tremendous growth in traen_US
dc.description.abstractThe recent fifth generation (5G) system enabled a highly promising evolution of Cloud Radio Access Network (C-RAN). Unlike the conventional Radio Access Network (RAN), the C-RAN decouples the baseband processing unit (BBU) from the remote radio head (RRH) by allowing BBUs from multiple Base Stations (BSs) to operate into a centralized BBU pool on a remote cloud-based infrastructure and a scalable deployment of light-weight RRHs. In this paper, we propose an efficient resource allocation scheme for 5G C-RAN called Bee-Ant-CRAN. The challenge addressed is to design a logical joint mapping between User Equipment (UE) and RRHs as well as between RRHs and BBUs. This is done adaptively to network load conditions, in a way to reducethe overall network costs while maintaining the user QoS and QoE. The network load has been formulated as a mixed integer nonlinear problem with a number of constraints. Then, the formulated optimization problem is decomposed into two stage resource allocation problem: UE-RRH association and RRH-BBU mapping. Therefore, a modified Artificial Bee Colony is developed as a swarm intelligence based approach to build the UE-RRH mapping (resource allocation). Moreover, an ameliorated Ant Colony Optimization algorithm is proposed to solve the RRH-BBU mapping (clustering) problem. Computational results demonstrate that our proposed Bee-Ant-CRAN scheme reduces the resource wastage and significantly improves the spectral efficiency as well as the throughput.en_US
dc.description.sponsorshipWorld Banken_US
dc.identifier.citationAri, A.A.A., Gueroui, A.,Titouna, C., Thiare, O., Aliouat, Z. (2019) Resource allocation scheme for 5G C-RAN: a Swarm Intelligence based approach. Computer Networks, pp. 1-34. https://www.elsevier.com/open-access/userlicense/1.0/en_US
dc.identifier.urihttp://hdl.handle.net/123456789/1433
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.relation.ispartofserieshttps://www.elsevier.com/open-access/userlicense/1.0/;34
dc.subjectC-RANen_US
dc.subjectClusteringen_US
dc.subjectSwarm Intelligenceen_US
dc.subjectRRHen_US
dc.subjectBBUen_US
dc.subjectResource Allocationen_US
dc.subject5Gen_US
dc.titleResource allocation scheme for 5G C-RAN: a Swarm Intelligence based approachen_US
dc.typeArticleen_US
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