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Cited by 89Advanced MIMO Systems OptimizationMillimeter-Wave Propagation and ModelingTelecommunications and Broadcasting Technologies

An Open-Source Techno-Economic Assessment Framework for 5G Deployment

Open access
Oughton, Edward J., Katsaros, Konstantinos, Entezami, Fariborz, Kaleshi, Dritan, Crowcroft, Jon·2019·IEEE Access
DOI 10.1109/access.2019.2949460
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Abstract

Optimal network planning is crucial to ensure viable investments. However, engineering analysis and cost assessment frequently occur independently of each other. Whereas considerable research has been undertaken on 5G networks, there is a lack of openly accessible tools that integrate the engineering and cost aspects, in a techno-economic assessment framework capable of providing geospatially-explicit network analytics. Consequently, this paper details an open-source python simulator for integrated modelling of 5G (pysim5G), that enables both engineering and cost metrics to be assessed in a single unified framework. The tool includes statistical analysis of radio interference to assess the system-level performance of 4G and 5G frequency band coexistence (including millimeter wave), while simultaneously quantifying the costs of ultra-dense 5G networks. An example application of this framework explores the techno-economics of 5G infrastructure sharing strategies, finding that total deployment costs can be reduced by 30% using either passive site sharing, or passive backhaul sharing, or by up to 50% via a multi-operator radio access network. The key contribution is a fully-tested, open-source software codebase, allowing users to undertake integrated techno-economic assessment of 5G deployments in a single geospatial framework.

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  • The posterior p(f|X*,y) can be approximated by a Gaussian distribution q(f|X*,y), forming the Laplace approximation with a theoretical guarantee.

    “The posterior p ( f | X ∗ , y ) in (8) can be approximated by a Gaussian distribution q ( f | X ∗ , y ) , thus forming the Laplace approximation with a theoretical guarantee according to [37].”

    From Orchestrating Joint Offloading and Scheduling for Low-Latency Edge SLAM (2025) · cites this paper as [37]

    Section III, “Capacity Assessment Model” (page not available), describes Monte Carlo simulations and lognormal distributions for 5G propagation, not a Gaussian approximation to a posterior. Searches for “Laplace approximation with a theoretical guarantee” and “Gaussian posterior q(f|X*,y) approximation” found no passage addressing the claimed approximation or its guarantee. (LLM, conf=0.78)

    Experimental — accuracy not yet measured

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Research works printed but not linked: 24

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Cited by

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Authors
Oughton, E. J., Katsaros, K., Entezami, F., Kaleshi, D., & Crowcroft, J.
Affiliations
  • University of Cambridge (GB)
  • Digital Catapult (GB)
ORCID
Venue
IEEE Access
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Published
2019
Volume
7
Pages
155930-155940
ISSN
2169-3536 (ISSN-L)
DOI
10.1109/access.2019.2949460
OpenAlex
W2981969281
Cited by
89
References
1
Citations by year
2026: 4 · 2025: 10 · 2024: 12 · 2023: 20 · 2022: 12 · 2021: 17 · 2020: 13 · 2019: 1
FWCI
3.86
Type
journal article
Language
en
Open access
Licence
Locations
  • IEEE Access (publishedVersion, cc-by)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
  • UKRI EPSRC Researcher in Residence Program, Digital Catapult, U.K
  • Engineering and Physical Sciences Research Council
Topics
  • Physical Sciences › Engineering › Electrical and Electronic Engineering › Advanced MIMO Systems Optimization
  • Physical Sciences › Engineering › Electrical and Electronic Engineering › Millimeter-Wave Propagation and Modeling
  • Physical Sciences › Engineering › Media Technology › Telecommunications and Broadcasting Technologies
Keywords
5G deployment, techno-economic analysis, millimeter wave, ultra-dense networks, infrastructure sharing, 4G/5G coexistence, network planning, deployment cost minimization

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