Machine Learning and Analytical Power Consumption
oduce a new power consumption model for 5G active antenna units (AAUs), the highest power consuming component of a BS1 and in turn of a mobile network. particular, we present an
Aiming at minimizing the base station (BS) energy consumption under low and medium load scenarios, the 3GPP recently completed a Release 18 study on energy saving techniques for 5G NR BSs . A broad range of techniques was evaluated in terms of the obtained network energy saving (NES) gain and their impact to the user-perceived throughput (UPT).
A substantial quantity of power is used by 5G BS. Radio transmitters and processors are a couple of base station components whose power consumption can be optimized with the use of PSO. PSO can assist in lowering the consumption of energy while preserving network performance by modifying parameters like transmission power and duty cycles.
[email protected]—The energy consumption of the fifth generation (5G) of mobile networks is one of the major co cerns of the telecom industry. However, there is not currently an accurate and tractable approach to evaluate 5G base stations (BSs) power consumption. In this article, we pr
This technical report explores how network energy saving technologies that have emerged since the 4G era, such as carrier shutdown, channel shutdown, symbol shutdown etc., can be leveraged to mitigate 5G energy consumption.
PDF version includes complete article with source references. Suitable for printing and offline reading.
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