IREE Oriented Green 6G Networks: A Radial Basis Function Based Approach

TL;DR

This paper introduces a novel RBF-based optimization framework for energy-efficient 6G networks, maximizing the IREE metric and outperforming existing designs through numerical experiments.

Contribution

It proposes a new RBF-based approach with convergence analysis for optimizing IREE in 6G networks, including a novel JS divergence constrained region.

Findings

IREE outperforms existing SE and EE designs.

Identified a new JS divergence constrained region.

Highlighted the importance of traffic-capacity balancing for IREE.

Abstract

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.