Method and a system for power management of the one or more base stations in a wireless communication network

1 . A method performed by a base station for a power management in a communication network, the method comprising:

transmitting, to a central management entity (CME), a key performance indicator (KPI) parameter of the base station;

receiving, from a federal server controller via the CME, a KPI relationship determined based on one or more KPI parameters of one or more base stations including the base station, wherein the KPI relationship is used for predicting a future load of the one or more base stations; and

adjusting a central processing unit (CPU) frequency of the base station based on the KPI relationship.

2 . The method of claim 1 , wherein adjusting the CPU frequency comprises applying the KPI relationship through a CPU governor of the base station.

3 . The method of claim 1 , wherein

transmitting the KPI parameter comprises:

collecting the KPI parameter from a E2 node or an O-cloud associated with the base station in a periodic manner;

determining whether a value associated with the KPI parameter is greater than a threshold value associated with the KPI parameter; and

in response to determining that the value is greater than the threshold value, transmitting, to the CME, the KPI parameter.

4 . The method of claim 1 , wherein the KPI parameter is one of an average load, a CPU Frequency, a downlink throughput, an uplink throughput, a plurality of user equipment (UE) connected to the one or more base stations, a maximum throughput associated with the one or more base stations, an average plurality of UE connected to the one or more base stations, a maximum plurality of UE connected to the one or more base stations, an average CPU usage, an average memory usage, a maximum memory usage, a minimum memory usage, an average solid state drive (SSD) usage, a maximum SSD usage, or a minimum SSD usage.

5 . A method performed by a central management entity (CME) for a power management of one or more base stations in a communication network, the method comprising:

receiving, from the one or more base stations, a plurality of key performance indicator (KPI) parameters of the one or more base stations;

generating a machine learning (ML) based model based on the plurality of KPI parameters;

transmitting, to a federal server controller, the ML based model;

receiving, from the federal server controller, a KPI relationship determined based on the ML based model, wherein the KPI relationship is used for predicting a future load of the one or more base stations; and

transmitting, to the one or more base stations, the KPI relationship in response to receiving the KPI relationship from the federal server controller.

6 . The method of claim 5 , wherein the KPI parameter is one of an average load, a CPU Frequency, a downlink throughput, an uplink throughput, a plurality of user equipment (UE) connected to the one or more base stations, a maximum throughput associated with the one or more base stations, an average plurality of UE connected to the one or more base stations, a maximum plurality of UE connected to the one or more base stations, an average CPU usage, an average memory usage, a maximum memory usage, a minimum memory usage, an average solid state drive (SSD) usage, a maximum SSD usage, or a minimum SSD usage.

7 . The method of claim 5 , wherein transmitting the KPI relationship comprises:

analyzing the KPI relationship based on an accuracy, a computational complexity, a past prediction record, and the plurality of KPI parameters; and

encoding the KPI relationship upon analyzing the KPI relationship.

8 . A base station for a power management, comprising:

communication circuitry;

memory, including one or more storage media, storing instructions; and

at least one processor including processing circuitry, wherein the instructions, when executed by the at least one processor, cause the base station to:

transmit, to a central management entity (CME), a key performance indicator (KPI) parameter of the base station;

receive, from a federal server controller via the CME, a KPI relationship determined based on one or more KPI parameters of one or more base stations including the base station, wherein the KPI relationship is used for predicting a future load of the one or more base stations; and

adjust a central processing unit (CPU) frequency of the base station based on the KPI relationship.

9 . The base station of claim 8 , wherein instructions, when executed by the at least one processor, cause the base station to:

apply the KPI relationship through a CPU governor of the base station.

10 . The base station of claim 8 , wherein the instructions, when executed by the at least one processor, cause the base station to:

collect the KPI parameter from a E2 node or an O-cloud associated with the base station in a periodic manner;

determine whether a value associated with the KPI parameter is greater than a threshold value associated with the KPI parameter; and

in response to determining that the value is greater than the threshold value, transmit the KPI parameter.

11 . The base station of claim 8 , wherein the KPI parameter is one of an average load, a CPU Frequency, a downlink throughput, an uplink throughput, a plurality of user equipment (UE) connected to the one or more base stations ( 202 ), a maximum throughput associated with the one or more base stations ( 202 ), average plurality of UE connected to the one or more base stations ( 202 ), a maximum plurality of UE connected to the one or more base stations ( 202 ), an average CPU usage, an average memory usage, a maximum memory usage, a minimum memory usage, an average solid state drive (SSD) usage, a maximum SSD usage, or a minimum SSD usage.

12 . A central management entity (CME) for a power management of one or more base stations in a communication network, comprising:

communication circuitry;

memory, including one or more storage media, storing instructions; and

at least one processor including processing circuitry, wherein the instructions, when executed by the at least one processor, cause the CME to:

receive, from the one or more base stations, a plurality of key performance indicator (KPI) parameters of the one or more base stations;

generate a machine learning (ML) based model based on the plurality of KPI parameters;

transmit, to a federal server controller, the ML based model;

receive, from the federal server controller, a KPI relationship determined based on the ML based model, wherein the KPI relationship is used for predicting a future load of the one or more base stations; and

transmit, to the one or more base stations, the KPI relationship in response to receiving the KPI relationship from the federal server controller.

13 . The CME of claim 12 , wherein the KPI parameter is one of an average load, a CPU Frequency, a downlink throughput, an uplink throughput, a plurality of user equipment (UE) connected to the one or more base stations, a maximum throughput associated with the one or more base stations, an average plurality of UE connected to the one or more base stations, a maximum plurality of UE connected to the one or more base stations, an average CPU usage, an average memory usage, a maximum memory usage, a minimum memory usage, an average solid state drive (SSD) usage, a maximum SSD usage, or a minimum SSD usage.

14 . The CME of claim 12 , wherein instructions, when executed by the at least one processor, cause the CME to:

analyze the KPI relationship based on an accuracy, a computational complexity, a past prediction record, and the plurality of KPI parameters; and

encode the KPI relationship upon analyzing the KPI relationship.