Dynamic Multi-Sleeping Control with Diverse Quality-of-Service
These technologies involve strategies for dynamically adjusting the operational status of base stations, such as activating sleep modes during periods of low demand, to
Deep Learning-Based Traffic-Aware Base Station Sleep
ks. Among these, base stations (BSs) in radio access networks (RANs) account for over half of the total energy usage. To address this, we propose a multi-cell sleep strategy combined with ad.
Stochastic Modeling of a Base Station in 5G Wireless Networks
Advanced sleep mechanism (ASM) is one of the efficient techniques for saving energy in the base station. This paper introduces three stochastic models for ASM based on
Stochastic modelling of sleeping strategy in 5G base station for
To reduce average power consumption and save power in 5G, we have modelled the 5G BSs sleeping mechanism as an M/G/1 queue with two types of vacations (two different
A User-Driven Sleep and Wake-Up Technology for Energy
This paper designs a user-driven base station sleep and wake-up mechanism that considers user-generated wake-up signals to activate sleeping BSs and indicates that this method can
Exploring power system flexibility regulation potential based on
By adopting a user association and sleep strategy in this paper, BS power consumption can be reduced and the power system can allocate more power resources to
Energy-saving control strategy for ultra-dense network base stations
To reduce the extra power consumption due to frequent sleep mode switching of base stations, a sleep mode switching decision algorithm is proposed. The algorithm reduces
Optimal Base Station Sleep Control via Multi-agent
In this paper, we propose a practical learning approach to obtain policies for BS sleep control via MARL with data-driven radio environment map (REM) calibration. In this approach, we first
Base station power control strategy in ultra-dense networks via
To enhance system efficiency and establish green wireless communication systems, this paper investigates base station sleeping and power allocation strategy based on
A User-Driven Sleep and Wake-Up Technology for Energy
As the primary source of energy consumption in communication networks, the power usage of 5G base station (BS) is a significant concern. The sleep mode (SM) of BS can be utilized to
Energy-saving control strategy for ultra-dense network base
To reduce the extra power consumption due to frequent sleep mode switching of base stations, a sleep mode switching decision algorithm is proposed. The algorithm reduces