Adaptive Sector Shutdown for Base Stations Energy Saving: Implementation and Field Evaluation in Dense Urban Networks

Date

2025-01-01

Author

Aktas, Semih
Kranda, Yakup Tarik
Kefeli, Can
Cavdar, Cicek
Alemdar, Hande

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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In this paper, we present a study on energy-saving techniques for mobile networks by focusing on sector shut down. We propose a novel algorithm called the Neighbour-Based Expert System Solution, which is an alternative to the traditional carrier shutdown method. The proposed algorithm takes into account the coverage and capacity needs of the network, as well as the potential impact on the customer experience. We also compare the proposed algorithm with the vendor sleeping feature and show that it can improve energy savings by up to 10% without compromising network coverage or quality of service. The algorithm leverages real-world geolocated user measurement data to identify compensable sectors, enabling precise and risk-aware shutdown decisions. It is specifically designed to operate under live network conditions in dense urban areas where service continuity is critical. We present results from a live network trial, demonstrating the proposed algorithm's effectiveness in a real-world setting. Overall, our results show that the proposed algorithm can significantly reduce energy consumption in mobile networks while maintaining network performance.

Subject Keywords

Energy saving, expert system, genetic algorithm, live network, sector shutdown

URI

https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=105022627697&origin=inward
https://hdl.handle.net/11511/117528

Collections

Department of Computer Engineering, Article