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Smart Power Management with Small Cells: A Path to Sustainable Data Connectivity

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  • Amna Shabbir

    (Department of Electronic Engineering NED UET Karachi, Pakistan)

Abstract

The rising demand for energy-efficient networks capable of supporting high-speed data traffic poses a critical challenge for network operators. This study addresses this issue by proposing a power control strategy that dynamically adjusts small cell transmit power based on traffic patterns. Power usage is reduced to 40% of the total capacity during normal traffic, while 60% is utilized during high traffic intensity. This traffic-driven power allocation approach achieves a 13-15% improvement in energy efficiency compared to conventional small cell-controlled sleep modes. By optimizing energy consumption without compromising network performance, this research provides a practical solution for balancing efficiency and user satisfaction in modern mobile networks.

Suggested Citation

  • Amna Shabbir, 2025. "Smart Power Management with Small Cells: A Path to Sustainable Data Connectivity," International Journal of Innovations in Science & Technology, 50sea, vol. 7(1), pages 58-68, Janurary.
    • Handle: RePEc:abq:ijist1:v:7:y:2025:i:1:p:58-68
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    File URL: https://journal.50sea.com/index.php/IJIST/article/view/1160/1697
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    File URL: https://journal.50sea.com/index.php/IJIST/article/view/1160
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    References listed on IDEAS

    as
    1. Muhammad Shafiq & Amjad Ali & Farman Ali & Jin-Ghoo Choi, 2024. "Machine Learning, Data Mining, and IoT Applications in Smart and Sustainable Networks," Sustainability, MDPI, vol. 16(18), pages 1-5, September.
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