University of Oulu

P. Luoto, M. Bennis, P. Pirinen, S. Samarakoon and M. Latva-Aho, "Enhanced Co-Primary Spectrum Sharing Method for Multi-Operator Networks," in IEEE Transactions on Mobile Computing, vol. 16, no. 12, pp. 3347-3360, 1 Dec. 2017. doi: 10.1109/TMC.2017.2694831

Enhanced co-primary spectrum sharing method for multi-operator networks

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Author: Luoto, Petri1; Bennis, Mehdi1; Pirinen, Pekka1;
Organizations: 1Centre for Wireless Communications, University of Oulu, Oulu 90014, Finland
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 1.4 MB)
Persistent link: http://urn.fi/urn:nbn:fi-fe2018080233253
Language: English
Published: Institute of Electrical and Electronics Engineers, 2017
Publish Date: 2018-08-02
Description:

Abstract

We consider a multi-operator small cell network where mobile network operators are sharing a common pool of radio resources. The goal is to ensure long term fairness of spectrum sharing without coordination among small cell base stations. It is assumed that spectral allocation of the small cells is orthogonal to the macro network layer, and thus, only the small cell traffic is modeled. We develop a decentralized control mechanism for base stations using the Gibbs sampling based learning technique, which allocates a suitable amount of spectrum for each base station. Five algorithms are compared addressing co-primary multi-operator resource sharing under heterogeneous traffic requirements and the performance is assessed through extensive system-level simulations. The main performance metrics are user throughput and fairness between operators. The numerical results demonstrate that the proposed Gibbs sampling based learning algorithm provides about tenfold cell edge throughput gains compared to state-of-the-art algorithms, while ensuring fairness between operators.

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Series: IEEE transactions on mobile computing
ISSN: 1536-1233
ISSN-E: 1558-0660
ISSN-L: 1536-1233
Volume: 16
Issue: 12
Pages: 3347 - 3360
DOI: 10.1109/TMC.2017.2694831
OADOI: https://oadoi.org/10.1109/TMC.2017.2694831
Type of Publication: A1 Journal article – refereed
Field of Science: 213 Electronic, automation and communications engineering, electronics
Subjects:
Funding: This research was supported by the Finnish Funding Agency for Technology and Innovation (TEKES), Nokia, Anite, Huawei Technologies, and Infotech Oulu Graduate School.
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