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

Abstract The rising energy demand in urban 6G 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 6G 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 micro base stations (µBSs) and integrate renewable energy through energy harvesting techniques. The aim is to reduce the grid power consumption and promote sustainable 6G network operations. We formulate the problem as an integer linear program (ILP) to find the optimal solution. Moreover, we propose three heuristic solutions: Greedy Green User Allocation Strategy (GUAS), Random User Allocation Strategy (RUAS), and Sequential User Allocation Strategy (SUAS). We considered two dynamic µBS 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 CO2 emissions and carbon tax costs at the European level, highlighting their potential to drive the future of “Green Networks”.