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Comparative Techno-Economic Evaluation of 5G Infrastructure Sharing Business Models in European Rural Areas

Author

Listed:
  • Ioannou, Nikos
  • Kokkinis, Dimitris
  • Katsianis, Dimitris
  • Varoutas, Dimitris

Abstract

The deployment of 5G standalone (5G SA) broadband networks in European rural areas lags behind urban and suburban regions due to high infrastructure costs and the unique characteristics of these areas. However, the advancements in 5G and Beyond-5G (B5G) telecommunication networks have presented new opportunities for cost-effective network deployment through infrastructure sharing. This paper conducts a comprehensive techno-economic study to determine the most cost-effective infrastructure sharing business model for providing affordable broadband in European rural areas, taking into account the specific attributes of each country. By examining real data from EU statistics and considering diverse infrastructure sharing scenarios, the study aims to bridge the research gap regarding the evaluation of 5G infrastructure sharing models on a per-country basis. The study applies a bottom-up model based on Discounted Cash Flow (DCF) analysis, encompassing both Mobile Broadband and Fixed Wireless Access (FWA) use cases. Leveraging the Eurostat database for geographical and demand data, the research utilizes logistic models to forecast demand based on the diffusion characteristics of broadband telecom services. The techno-economic analysis is adjusted for different infrastructure sharing models, including Single Host Network (SHN), Multiple Host Network (MHN) via Passive Sharing and Active Sharing, and Neutral Host Network (NHN). The paper presents total cost results, CAPEX/OPEX outcomes, Net Present Value (NPV), Return on Investment (ROI), and payback periods for each infrastructure sharing model in each country group consisting of European countries with similar density characteristics. Sensitivity and risk analyses are conducted to identify the most influential factors affecting the investment viability for each model and case. Moreover, the study examines the profitability of each scenario, considering the Average Revenue Per User (ARPU) and demand conditions necessary for investment sustainability. The discussion encompasses the reuse of existing infrastructure, network slicing implications, and regulatory policy considerations.

Suggested Citation

  • Ioannou, Nikos & Kokkinis, Dimitris & Katsianis, Dimitris & Varoutas, Dimitris, 2023. "Comparative Techno-Economic Evaluation of 5G Infrastructure Sharing Business Models in European Rural Areas," 32nd European Regional ITS Conference, Madrid 2023: Realising the digital decade in the European Union – Easier said than done? 277973, International Telecommunications Society (ITS).
    • Handle: RePEc:zbw:itse23:277973
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    References listed on IDEAS

    as
    1. Edward J. Oughton & William Lehr, 2022. "Surveying 5G Techno-Economic Research to Inform the Evaluation of 6G Wireless Technologies," Papers 2201.02272, arXiv.org, revised Jan 2022.
    2. Edward Oughton, 2018. "Towards 5G: scenario-based assessment of the future supply and demand for mobile telecommunications infrastructure," Working Papers 2017/04 (revised), Cambridge Judge Business School, University of Cambridge.
    3. Ioannou, Nikos & Katsianis, Dimitris & Varoutas, Dimitris, 2020. "Comparative techno-economic evaluation of LTE fixed wireless access, FTTdp G.fast and FTTC VDSL network deployment for providing 30 Mbps broadband services in rural areas," Telecommunications Policy, Elsevier, vol. 44(3).
    4. Oughton, Edward & Frias, Zoraida & Russell, Tom & Sicker, Douglas & Cleevely, David D., 2018. "Towards 5G: Scenario-based assessment of the future supply and demand for mobile telecommunications infrastructure," Technological Forecasting and Social Change, Elsevier, vol. 133(C), pages 141-155.
    Full references (including those not matched with items on IDEAS)

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    Keywords

    techno-economic feasibility; 5G Standalone; rural; infrastructure sharing; network slicing; neutral host; business models;
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