Abstract
The development of future wireless access networks often results in very high energy consumption. To reduce this consumption, decision-makers (DM) minimize the number of base stations (\(\hbox {BS}_s\)) installed while using a dynamic BS on/off strategy. However, reducing the number of base stations leads to insufficient network coverage. Indeed, for better coverage, the decision-maker (DM) should install enough base stations. We can therefore see that we have two contradictory objectives. On the other hand, we can easily notice that the information of the network traffic evolves over time. Therefore and in order to make a realistic study, we will consider the traffic information as an imprecise and uncertain value instead of a constant value. For the reasons aforementioned, we introduce in this paper, a fuzzy multi-objective mathematical model in which each traffic is a fuzzy variable, and then, we present a decision-making model based on possibility theory. To solve this problem, we used two meta-heuristic algorithms. The obtained results proved the efficiency of our model compared to previous studies. Indeed, the proposed methodology results not only in a reduction of \(\hbox {CO}_2\) emissions (between 18.15 and 24.18%) but also guarantees good network coverage.









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Dahmani, S., Gabli, M. & Serghini, A. A green fuzzy multi-objective approach to the RNP problem for LTE networks . Prog Artif Intell 11, 29–41 (2022). https://doi.org/10.1007/s13748-021-00259-x
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DOI: https://doi.org/10.1007/s13748-021-00259-x