Abstract
The exponential increase of mobile traffic will continue to be a reality in the next years. To support it, some actions should be taken: the current frequency bands can be refarmed, the number of base stations can be increased, the technologies can evolve etc. Even with all of these, the spectrum in use will not be enough. Therefore, it will be necessary to allocate more spectrum, so the new expected traffic can properly flow. However, the spectrum is a scarce resource. Hence, from a spectrum management point of view, it is not suitable to allocate a huge amount of spectrum without planning. One question arises: how much spectrum is necessary to support all this new traffic that will emerge? This paper answers this question.
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Notes
Some of these bands are allocated for fixed and mobile services, being designated for different telecommunication services. Among them is the personal mobile service, which is the name of the mobile service provided through cellular systems in Brazil.
In 2015, Brazil had 897 MHz (for downlink, uplink and guard band) designated for personal mobile services. However, there was in use only 210 MHz for downlink (equivalent to 420 MHz for downlink and uplink) in São Paulo. Some frequency bands do not have any licensed mobile operators associated with (e.g. 3.4–3.6 GHz). And the others, although there are mobile operators allowed to use them, they were not in use yet (e.g. 718–748 MHz and 773–803 MHz).
The simple way to estimate the quantity of base stations in the next years is using a polynomial regression, which will find a polynomial that best fits (in a least-squares sense) the data. Considering a second-order polynomial, the number of base stations between the years 2000 and 2015 can be described by the equation \(BS = 14.564426 \times y^2 -58138.5312 \times y + 58019863\), where BS is the number of base stations at the end of the year y. The coefficient of determination of this polynomial is \(R^2 = 0.979\), which indicates that the polynomial fits the data with good accuracy. The number of base stations at the end of 2016–2020 were predicted using this equation.
References
Cisco. (2016). Cisco Visual Networking Index: Global mobile data traffic forecast update, 2015–2020. White paper, Cisco.
ITU. (2013). Recommendation ITU-R M.1768-1: Methodology for calculation of spectrum requirements for the terrestrial component of international mobile telecommunications. Technical report, ITU-R.
LS telcom. (2014). Mobile spectrum requirements estimate: Getting the inputs right. Technical report, LS telcom.
Bakaus, T. A., & Martinhão, M. S. (2010). Policies for spectrum estimation in Brazil. In The 13th international symposium on wireless personal multimedia communications.
Ameil, C. (2014). Analysis of the ITU-R model for forecasting IMT spectrum demand. Presentation at 19th LS Summit.
Russian Federation. (2012). Document 5D/118-E: Future IMT spectrum requirements assessment for the Russian Federation. Technical report, ITU-R.
Eberspächer, J., Vögel, H.-J., Bettstetter, C., & Hartmann, C. (2009). GSM architecture, protocols and services (3 edn.). New York: Wiley.
Rysavy, P. (2014). Challenges and considerations in defining spectrum efficiency. Proceedings of the IEEE, 102(3), 386–392.
Teleco. 4G—Frequencies and biddings [in portuguese: 4G—Frequências e licitações]. http://www.teleco.com.br/4g_brasil_lic.asp.
Anatel. Telecommunications Service System [in Portuguese: STEL—Sistema de Serviços de telecomunicações]. http://sistemas.anatel.gov.br/stel/.
Anatel. (2016). Monitoring the telecommunications sector [in Portuguese: Relatório de acompanhamento do setor de telecomunicações - Serviço Móvel Pessoal (SMP)]. Technical report, Anatel.
Rysavy, P. (2011). Efficient use of spectrum. Technical report, Rysavy Research.
Rysavy, P. (2013). Mobile broadband explosion the 3GPP wireless evolution. Technical report, Rysavy Research.
ABI research. Small cells surge at 43% compound annual growth rate as mobile networks operators densify networks. http://www.abiresearch.com/press/small-cells-surge-43-compound-annual-growth-rate-m/. Accessed May 23 2016.
ITU. (2008). Report ITU-R M.2134-0: Requirements related to technical performance for IMT-Advanced radio interface(s). Technical report, ITU-R.
ITU. (2015). Recomendation ITU-R M.2083-0: IMT Vision—Framework and overall objectives of the future development of IMT for 2020 and beyond. Technical report, ITU-R.
ITU. (2008). Report ITU-R M.2370-0: IMT traffic estimates for the years 2020 to 2030. Technical report, ITU-R.
Kottkamp, M., Roessler, A., & Schlienz, J. (2012). LTE-Advanced—Technology introduction. White paper, Rohde & Schwarz.
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Fernandes, L.C., Linhares, A. & Ferreira, L.R.N. Spectrum forecasting for IMT-Advanced. Telecommun Syst 66, 121–130 (2017). https://doi.org/10.1007/s11235-017-0276-5
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DOI: https://doi.org/10.1007/s11235-017-0276-5