Carbon efficiency modeling and optimization of solar-powered cellular networks.

As wireless communication traffic experiences rapid growth, the carbon emissions caused by the communication industry are also on the rise. To achieve “carbon neutrality”, researchers are considering the use of renewable energy sources to power cellular networks, thereby reducing carbon emissions. However, a challenge arises when using renewable energy, specifically owing to the unpredictable nature of both the energy consumption of the cellular network and the power generation from renewable sources. This inconsistency results in low renewable energy utilization and reduced carbon efficiency. Herein, we construct a carbon efficiency model of solar-powered cellular networks using practical data from solar radiation. We propose a mechanism that alternately optimizes the performance of the renewable energy network and the cellular network. This approach is based on convex optimization theory and the Dinkelback algorithm, and it leads to the design of a carbon efficiency optimization algorithm. This algorithm aims to improve the carbon efficiency of cellular networks and reduce their carbon emissions. Simulation results demonstrate that our optimization scheme yields a maximum improvement of 2.56 × 10⁸ bps/g in the carbon efficiency of the cellular network as compared to conventional power allocation schemes such as the traditional water filling method and heuristic energy sharing and charge/discharge algorithms. [ABSTRACT FROM AUTHOR]