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Technoeconomic assessment of an FTTH network investment in the Greek telecommunications market

Author

Listed:
  • Aggelos Skoufis

    (Harokopio University of Athens, Department of Informatics and Telematics)

  • Georgios Chatzithanasis

    (Harokopio University of Athens, Department of Informatics and Telematics)

  • Georgia Dede

    (Harokopio University of Athens, Department of Informatics and Telematics)

  • Evangelia Filiopoulou

    (Harokopio University of Athens, Department of Informatics and Telematics)

  • Thomas Kamalakis

    (Harokopio University of Athens, Department of Informatics and Telematics)

  • Christos Michalakelis

    (Harokopio University of Athens, Department of Informatics and Telematics)

Abstract

Recent years have seen an increasing need for higher broadband connections, fueled by novel applications including fifth generation wireless networks (5G). The European Commission is working on achieving specific milestones regarding the development of next generation networks. Many EU countries have opted to adopt a gradual migration path towards the Fiber-to-the-Home (FTTH) technology in view of the high costs of implementation. The Fiber-to-the-Cabinet (FTTC) architecture, combined with very-high-bit-rate digital subscriber line 2 (VDSL2) and vectoring noise cancellation techniques may therefore provide a viable short-term basis solution. Techno-economic modeling and assessment is vital at the initial stages of the development of a telecommunication network investment project involving high capital expenditures for the infrastructure. The present work provides a techno-economic model in order to assess the prospects of such a network upgrade project from a financial perspective, following a three-way migration path. The three stages are: the implementation of the FTTC architecture with VDSL2 vectoring technology, the upgrade to FTTC with G.Fast and finally the migration to FTTH. The analysis is implemented over a suburb of the city of Athens, Greece. Different scenarios are evaluated, predicting profits even from the first years following the investment. The analysis includes the estimation of the degree of market penetration, analytical cost calculations for the implementation and operation of the network and the evaluation of crucial financial indicators, regarding the prospects of the investment in vectoring services. The study can serve as a complete road-map and can be applied in similar upgrade scenarios. The most important outcome of the analysis is that the profits resulted from each upgrade will finance the next step.

Suggested Citation

  • Aggelos Skoufis & Georgios Chatzithanasis & Georgia Dede & Evangelia Filiopoulou & Thomas Kamalakis & Christos Michalakelis, 2023. "Technoeconomic assessment of an FTTH network investment in the Greek telecommunications market," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 82(2), pages 211-227, February.
    • Handle: RePEc:spr:telsys:v:82:y:2023:i:2:d:10.1007_s11235-022-00971-6
    DOI: 10.1007/s11235-022-00971-6
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    References listed on IDEAS

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    1. Michalakelis, C. & Sphicopoulos, T., 2012. "A population dependent diffusion model with a stochastic extension," International Journal of Forecasting, Elsevier, vol. 28(3), pages 587-606.
    2. Karl-Heinz Neumann, 2014. "Benefits and regulatory challenges of VDSL Vectoring (and VULA)," EUI-RSCAS Working Papers p0390, European University Institute (EUI), Robert Schuman Centre of Advanced Studies (RSCAS).
    3. Thomas Plückebaum & Stephan Jay & Karl-Heinz Neumann, 2014. "Benefits and regulatory challenges of VDSL Vectoring (and VULA)," RSCAS Working Papers 2014/69, European University Institute.
    4. Aggelos Skoufis & Georgios Chatzithanasis & Georgia Dede & Thomas Kamalakis & Christos Michalakelis, 2020. "Technoeconomic analysis of a VDSL2/G.fast vectoring network: a case study from Greece," Netnomics, Springer, vol. 21(1), pages 83-101, December.
    5. Meade, Nigel & Islam, Towhidul, 2015. "Forecasting in telecommunications and ICT—A review," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1105-1126.
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