In order to provide design guidelines for energy efficient 6G networks, we propose a novel radial basis function (RBF) based optimization framework to maximize the integrated relative energy efficiency (IREE) metric. Different from the conventional energy efficient optimization schemes, we maximize the transformed utility for any given IREE using spectrum efficiency oriented RBF network and gradually update the IREE metric using proposed Dinkelbach's algorithm. The existence and uniqueness properties of RBF networks are provided, and the convergence conditions of the entire framework are discussed as well. Through some numerical experiments, we show that the proposed IREE outperforms many existing SE or EE oriented designs and find a new Jensen-Shannon (JS) divergence constrained region, which behaves differently from the conventional EE-SE region. Meanwhile, by studying IREE-SE trade-offs under different traffic requirements, we suggest that network operators shall spend more efforts to balance the distributions of traffic demands and network capacities in order to improve the IREE performance, especially when the spatial variations of the traffic distribution are significant.

翻译：为提供高能效6G网络的设计指南，我们提出了一种新型基于径向基函数（RBF）的优化框架，以最大化综合相对能效（IREE）指标。与传统的能效优化方案不同，我们使用面向频谱效率的RBF网络，针对任意给定的IREE最大化转换后的效用函数，并通过提出的Dinkelbach算法逐步更新IREE指标。本文给出了RBF网络的存在性与唯一性证明，并讨论了整个框架的收敛条件。通过数值实验表明，所提出的IREE方法优于许多现有的面向频谱效率（SE）或能效（EE）的设计方案，并发现了一个新的Jensen-Shannon（JS）散度约束区域，其行为与传统EE-SE区域显著不同。同时，通过研究不同业务需求下IREE-SE的权衡关系，我们建议网络运营商应投入更多精力平衡业务需求与网络容量的分布，以提升IREE性能，尤其是在业务分布空间变化显著的情况下。