To maximize overall benefits for the investors and operators of base station energy storage, we proposed a bi-level optimization model for the operation of the energy storage, and the
5G base stations (BSs) are potential flexible resources for power systems due to their dynamic adjustable power consumption.
Abstract—We consider in this paper multiple 5G base stations (BSs) implementing Advanced Sleep Modes (ASM) wherein each base station is able to deactivate some of its components when it does
To enhance system efficiency and establish green wireless communication systems, this paper investigates base station sleeping and power allocation strategy based on deep reinforcement
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 sleep modes),
A multi-BS cooperation self-optimising sleep strategy for 5G BSs that consists of an initial user association stage based on multi-BS cooperation (MBSC) and a self-optimising variable
In this regard, this study models a 5G BS as an (M^ { [X]}/G/1) feedback retrial queue with a sleeping strategy to reduce average power consumption and conserve power in 5G mobile
To solve this crucial issue, a day-ahead collaborative regulation method for 5G BSs and power grids considering a sleep strategy and energy storage regulation capacity is proposed.
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 reduce mobile
An energy consumption optimization strategy of 5G base stations (BSs) considering variable threshold sleep mechanism (ECOS-BS) is proposed, which includes the initial matching
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