Abstract
High communicational standards have been set for the 5G mobile networks. Therefore, it is of great importance that technological solutions that include all the significant features, such as the high coverage and capacity and low round-trip delays, are adopted for the next generation of mobile networks. Except for their technical efficiency, these technologies should be profitable for providers as well. As a result, the need for limiting the costs spent for the development of these technologies emerges. In this papers, four models two for each one of the two solutions for 5G networks are developed, namely the Multiple Input Multiple Output (MIMO) and the Distributed Antenna System. The architectural models assumed for the techno-economic analyses are presented. The mathematical models for both technologies are developed. Experiments are conducted using prices of the Greek market and also Sensitivity Analysis (SA) is used to pinpoint, which cost parameters are the most expensive ones and therefore it is likely that they discourage providers to invest in them. To our knowledge there are not many studies comparing and contrasting these technologies and there is no SA for MIMO. Therefore, it is considered that research for these models is of vital importance for the next generation of mobile communication networks, as they are foundation stonesfor the formation of 5G.
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Bouras, C., Ntarzanos, P., & Papazois, A. (2016). Cost modeling for SDN/NFV based mobile 5G networks. In 2016 8th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT) (pp. 56–61).
Bouras, C., Kokkinos, V., Kollia, A., & Papazois, A. (2015). Techno-economic analysis of ultra-dense and DAS deployments in mobile 5G. In 2015 International Symposium on Wireless Communication Systems (ISWCS) (pp. 241–245).
Bouras, C., Kollia, A., & Papazois, A. (2016). Sensitivity analysis of small cells and DAS techno-economic models in mobile 5G. In 2016 IEEE Wireless Communications and Networking Conference (pp. 1–6).
Bouras, C., Kollia, A., & Papazois, A. (2017). Dense deployments and das in 5G: A techno-economic comparison. Wireless Personal Communications, 94(3), 1777–1797.
Passas, V., Miliotis, V., Makris, N., Korakis, T., & Tassiulas, L. (2016). Paris metro pricing for 5G hetnets. In Global Communications Conference (GLOBECOM), 2016 IEEE (pp. 1–6). IEEE.
Nikolikj, V., & Janevski, T. (2015). Incremental deployment aspects of beyond 4G and 5G mobile hetnets. International Journal of Future Generation Communication and Networking, 8(6), 177–196.
Deng, N., Zhou, W., & Haenggi, M. (2015). Heterogeneous cellular network models with dependence. IEEE Journal on Selected Areas in Communications, 33(10), 2167–2181.
Elmannai, W., & Elleithy, K. M. (2014). Cost analysis of 5th generation technology. International Society for Computers and Their Applications, Inc.
Ahokangas, P., Matinmikko, M., Yrjl, S., Mustonen, M., Posti, H., Luttinen, E., et al. (2014). Business models for mobile network operators in licensed shared access (LSA). In 2014 IEEE International Symposium on Dynamic Spectrum Access Networks (DYSPAN) (pp. 263–270).
Khodashenas, P. S., Ruiz, C., Riera, J. F., Fajardo, J. O., Taboada, I., Blanco, B., et al. (2016). Service provisioning and pricing methods in a multi-tenant cloud enabled ran. In 2016 IEEE Conference on Standards for Communications and Networking (CSCN) (pp. 1–6).
Gohad, A., Narendra, N. C., & Ramachandran, P. (2013). Cloud pricing models: A survey and position paper. In 2013 IEEE International Conference on Cloud Computing in Emerging Markets (CCEM) (pp. 1–8).
Andrews, J. G., Buzzi, S., Choi, W., Hanly, S. V., Lozano, A., Soong, A. C. K., et al. (2014). What will 5G be? IEEE Journal on Selected Areas in Communications, 32, 1065–1082.
Bouras, C., Kollia, A., & Papazois, A. (2017). SDN NFV in 5G: Advancements and challenges. In 2017 20th Conference on Innovations in Clouds, Internet and Networks (ICIN) (pp. 107–111).
Yunas, S. F., Valkama, M., & Niemelä, J. (2015). Techno-economical comparison of dynamic DAS and legacy macrocellular densification. International Journal of Wireless Information Networks, 22(4), 312–326.
Liu, Z., Kolding, T., Mogensen, P., Vejgaard, B., & Sorensen, T. (2012). Economical comparison of enterprise in-building wireless solutions using DAS and Femto. In Vehicular Technology Conference (VTC Fall), 2012 IEEE (pp. 1–5).
Senel, K., Björnson, E., & Larsson, E. G. (2017). Optimal base station design with limited fronthaul: Massive bandwidth or massive MIMO? Preprint arXiv:1709.05172. Accessed 17 Sep 2017.
Verde, F., Hong, Y.-W. P., Samardzija, D., Schober, R., & Tao, Z. (2012). Cooperative MIMO multicell networks. EURASIP Journal on Advances in Signal Processing, 2012(1), 41.
Lim, Y.-G., Chae, C.-B., & Caire, G. (2015). Performance analysis of massive MIMO for cell-boundary users. IEEE Transactions on Wireless Communications, 14(12), 6827–6842.
Muharar, R., & Evans, J. (2017). Performance analysis of massive MIMO networks with random unitary pilot matrices. Preprint arXiv:1709.03325. Accessed 11 Sep 2017.
Katsigiannis, M., Basaure, A., & Matinmikko, M. (2014). Cost comparison of licensed shared access (LSA) and MIMO scenarios for capacity growth in finland. In 2014 1st International Conference on 5G for Ubiquitous Connectivity (5GU) (pp. 291–296). IEEE.
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Bouras, C., Kokkalis, S., Kollia, A. et al. Techno-economic comparison of MIMO and DAS cost models in 5G networks. Wireless Netw 26, 1–15 (2020). https://doi.org/10.1007/s11276-018-1780-6
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DOI: https://doi.org/10.1007/s11276-018-1780-6