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Optimizing the investments in mobile networks and subscriber migrations for a telecommunication operator
Author(s) -
Cambier Adrien,
Chardy Matthieu,
Figueiredo Rosa,
Ouorou Adam,
Poss Michael
Publication year - 2021
Publication title -
networks
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.977
H-Index - 64
eISSN - 1097-0037
pISSN - 0028-3045
DOI - 10.1002/net.21970
Subject(s) - leverage (statistics) , computer science , dimensioning , time horizon , operator (biology) , mathematical optimization , integer programming , context (archaeology) , operations research , engineering , mathematics , paleontology , biochemistry , repressor , machine learning , biology , transcription factor , gene , aerospace engineering , chemistry
We consider the context of a telecommunication company that is at the same time an infrastructure operator and a service provider. When planning its network expansion, the company can leverage over its knowledge of the subscriber dynamic to better optimize the network dimensioning, therefore avoiding unnecessary costs. In this work, the network expansion represents the deployment and/or reinforcement of several technologies (e.g., 2G, 3G, 4G), assuming that subscribers to a given technology can be served by this technology or older ones. The operator can influence subscriber dynamic by subsidies. The planning is made over a discretized time horizon while some strategic guideline requirements are required at the end of the time horizon. Following classical models, we consider that the willingness of customers for shifting to a new technology follows an S ‐shape piecewise constant function. We propose a mixed‐integer linear programming formulation, improved through several valid inequalities and a heuristic algorithm. We assess the formulation numerically on real instances.