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Title: | Exploiting heterogeneity for cost efficient 5G base station deployment using metaheuristics |
Authors: | Aondoakaa, D Cosmas, J Swift, S |
Keywords: | optimisation;next generation networks;search problems;5G mobile communication;radio access networks;cellular radio;MIMO communication;meta-heuristics;radio access network;considerably higher infrastructure;power consumption cost;conventional mobile network standards;optimal planning;additional complexity;cost-efficient radio access planning;novel optimisation framework;cost-efficient deployment;5G base stations;key 5G technologies;heterogeneous base station architecture;cell range extension;multiple-input-multiple-output;network designmeta-heuristic algorithms;cost efficiency;infrastructural cost;cost efficient 5G base station deployment |
Issue Date: | 1-Sep-2020 |
Publisher: | The Institution of Engineering and Technology |
Citation: | Aondoakaa. D., Cosmas, J. and Swift, S. (2020) 'Exploiting heterogeneity for cost efficient 5G base station deployment using metaheuristics', IET Networks, 2020, 9 (5), pp. 270 - 275. doi: 10.1049/iet-net.2019.0111. |
Abstract: | A key concern in the design of 5G is the radio access network, which is expected to be significantly denser and more advanced, with considerably higher infrastructure and power consumption cost than that of conventional mobile network standards. Novel algorithms/approaches for optimal planning of the radio access network are required for tackling the additional complexity of the problem of cost-efficient radio access planning in 5G, which cannot be properly handled by conventional approaches. This study proposes a novel optimisation framework for the cost-efficient deployment and configuration of 5G base stations. The main idea of the proposed optimisation framework is to exploit heterogeneity in three key 5G technologies, heterogeneous base station architecture, cell range extension and multiple-input–multiple-output spatial multiplexing, by jointly optimising their configurations during network design. In addition, the proposed optimisation framework includes generic steps for applying meta-heuristic algorithms to the problem, which are necessary to overcome the problem's complexity, especially for large problem instances. The authors’ results show that their novel optimisation framework improves the cost efficiency of the network planning both in terms of power and infrastructural cost to operators. |
URI: | https://bura.brunel.ac.uk/handle/2438/30384 |
DOI: | https://doi.org/10.1049/iet-net.2019.0111 |
ISSN: | 2047-4954 |
Other Identifiers: | ORCiD: David Aondoakaa https://orcid.org/0000-0002-7811-5129 ORCiD: John Cosmas https://orcid.org/0000-0003-4378-5576 ORCiD: Stephen Swift https://orcid.org/0000-0001-8918-3365 |
Appears in Collections: | Dept of Computer Science Research Papers Dept of Electronic and Electrical Engineering Research Papers |
Files in This Item:
File | Description | Size | Format | |
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FullText.pdf | Copyright © 2020 The Institution of Engineering and Technology. Open Access. This paper is a postprint of a paper submitted to and accepted for publication in Selected Papers from the Ubiquitous Clouds and Cognitive Communication Networks (UCCCN 2019), Shenyang, China, 21-23 October 2019, and is subject to Institution of Engineering and Technology Copyright (see: https://digital-library.theiet.org/files/Author_self-archiving_policy.pdf). The copy of record is available at the IET Hub on https://ietresearch.onlinelibrary.wiley.com/doi/full/10.1049/iet-net.2019.0111. | 1.15 MB | Adobe PDF | View/Open |
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