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

Abstract 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 ( $$\upmu$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>μ</mml:mi> </mml:math> 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 $$\upmu$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>μ</mml:mi> </mml:math> 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 $$\text {CO}_2$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msub> <mml:mtext>CO</mml:mtext> <mml:mn>2</mml:mn> </mml:msub> </mml:math> emissions and carbon tax costs at the European level, highlighting their potential to drive the future of “Green Networks”.