Optimal Policies of Advanced Sleep Modes for Energy-Efficient 5G networks

TL;DR

This paper develops an optimal control framework using Markov Decision Processes to determine energy-efficient sleep policies for 5G networks, balancing power savings with user delay.

Contribution

It introduces a novel MDP-based model for optimizing Advanced Sleep Modes in 5G, incorporating switching costs to improve energy-delay trade-offs.

Findings

Optimal sleep policies significantly reduce power consumption.

Switching costs influence the energy-delay balance.

Model provides a systematic way to design sleep strategies.

Abstract

We study in this paper optimal control strategy for Advanced Sleep Modes (ASM) in 5G networks. ASM correspond to different levels of sleep modes ranging from deactivation of some components of the base station for several micro-seconds to switching off of almost all of them for one second or more. ASMs are made possible in 5G networks thanks to the definition of so-called lean carrier radio access which allows for configurable signaling periodicities. We model such a system using Markov Decision Processes (MDP) and find optimal sleep policy in terms of a trade-off between saved power consumption versus additional incurred delay for user traffic which has to wait for the network components to be woken-up and serve it. Eventually, for the system not to oscillate between sleep levels, we add a switching component in the cost function and show its impact on the energy reduction versus delay trade-off.