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<p>The rising energy demand in urban 6&#xa0;G ultra-dense mmWave mobile networks will present economic and environmental concerns. Addressing these issues calls for efficient energy management frameworks that enhance the reliance of 6&#xa0;G networks on renewable energy sources while minimizing dependence on grid-based power. This is particularly important as base stations (BSs) are the most energy-intensive components in these networks. This paper focuses on the problem of <i>User Association with Green Power Maximization</i>. We propose intelligent load-based on–off switching mechanisms for grid-powered microbase stations (<InlineEquation ID="IEq1"> <EquationSource Format="TEX">\(\upmu\)</EquationSource> <EquationSource Format="MATHML"><math> <mi mathvariant="normal">μ</mi> </math></EquationSource> </InlineEquation>BSs) and integrate renewable energy through energy harvesting techniques. The aim is to reduce the grid-power consumption and promote sustainable 6&#xa0;G network operations. We formulate the problem as an integer linear pGUASrogram to find the optimal solution. Moreover, we propose three heuristic solutions: greedy green user allocation strategy, random user allocation strategy, and sequential user allocation strategy. We considered two dynamic <InlineEquation ID="IEq2"> <EquationSource Format="TEX">\(\upmu\)</EquationSource> <EquationSource Format="MATHML"><math> <mi mathvariant="normal">μ</mi> </math></EquationSource> </InlineEquation>BS power models: a stepwise and a load-based linear model. We evaluated our proposed solutions via simulations with both power models. Finally, we provide insights into how these solutions can significantly reduce <InlineEquation ID="IEq3"> <EquationSource Format="TEX">\(\text {CO}_2\)</EquationSource> <EquationSource Format="MATHML"><math> <msub> <mtext>CO</mtext> <mn>2</mn> </msub> </math></EquationSource> </InlineEquation> emissions and carbon tax costs at the European level, highlighting their potential to drive the future of “Green Networks”.</p>

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Green 6 G: energy-efficient user association and power allocation with locally harvested renewable energy

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年3月5日

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  • Abdulhalim Fayad,
  • Tibor Cinkler,
  • Jeroen Famaey,
  • István Gódor

摘要

The rising energy demand in urban 6 G ultra-dense mmWave mobile networks will present economic and environmental concerns. Addressing these issues calls for efficient energy management frameworks that enhance the reliance of 6 G networks on renewable energy sources while minimizing dependence on grid-based power. This is particularly important as base stations (BSs) are the most energy-intensive components in these networks. This paper focuses on the problem of User Association with Green Power Maximization. We propose intelligent load-based on–off switching mechanisms for grid-powered microbase stations ( \(\upmu\) μ BSs) and integrate renewable energy through energy harvesting techniques. The aim is to reduce the grid-power consumption and promote sustainable 6 G network operations. We formulate the problem as an integer linear pGUASrogram to find the optimal solution. Moreover, we propose three heuristic solutions: greedy green user allocation strategy, random user allocation strategy, and sequential user allocation strategy. We considered two dynamic \(\upmu\) μ BS power models: a stepwise and a load-based linear model. We evaluated our proposed solutions via simulations with both power models. Finally, we provide insights into how these solutions can significantly reduce \(\text {CO}_2\) CO 2 emissions and carbon tax costs at the European level, highlighting their potential to drive the future of “Green Networks”.