Support on energy related parameters monitoring, calculation and exposure

Abstract

A method of a first network entity (e.g. a base station or a core network entity) in a communication network, comprising acquiring (calculating or receiving from another network entity) a granular ene

Description

BACKGROUND Field Certain examples of the present disclosure provide various techniques relating to Energy Related Parameters Monitoring, Calculation and Exposure for example within 3rd Generation Partnership Project (3GPP) 5th Generation (5G) New Radio (NR) and later generation networks. Description of the Related Art Currently, there are more than 110 countries committed to a net zero emissions target by 2050. What the Paris Agreement attempts to uphold is making sure global temperatures stay within 2°C by 2100, but preferably closer to 1.5°C. The motivation of reducing the energy emissions and increase the energy efficiency of the telecoms sector is more urgent than before. Also considering the price of energy is going up and the increasing traffic load of the telecoms system, mobile network operators are keen to optimize the costs of ongoing operations (opex). Energy-saving measures in network operations are necessary for NR radio equipment and other components of telecommunications systems. Compared to the previous generations, the 5G New Radio (NR) offers a significant energyefficiency improvement in its first release (3GPP Rel-15), i.e. cell activation / deactivation over Xn / X2 / F1 interface via coordination between peer eNB / gNBs, sparser RS and SS signals, URLLC, CU / DU architecture and MR-DC, etc. However, based on the GSMA report ‘5G energy efficiencies: Green is the new black’ (https: / / data.gsmaintelligence.com / api-web / v2 / research-file-download?id=54165956&file=241120-5G-energy.pdf) published in 2020, network opex may account for around 25% of an operator’s cost base, or 10% of revenue. In addition, over 90% of network costs are spent on energy, consisting mostly of fuel and electricity consumption. To further reduce energy consumption and improve the efficiency of the 3GPP system, in the releases later than Rel-15, some of the working groups (WGs) in RAN, SA and CT have completed or are developing mechanisms to increase energy saving or energy efficiency. To reduce the energy consumption of RAN part, in Rel-18, RAN WG started to study and specify the techniques on network energy savings (RAN WID in RP-223540 / RP-230566 September 2023), and RAN will further work on network energy saving improvement in Rel-19 (RP- 234065) on supporting on-demand SSB SCell operation for UEs in connected mode, on-demand SIB1 for UEs in idle / inactive mode, and adaptation of common signal / channel transmissions. SA5 started their work on Energy efficiency of the 5G system in Rel-16. In Rel-17 (TR 28.813 - Study on new aspects of Energy Efficiency (EE) for 5G) and Rel-18 (TR 28.913), SA5 extended its scope from RAN only to the whole 5G system. The specified techniques are documented in TS 28.310 ‘Management and orchestration; Energy efficiency of 5G’ and the corresponding KPIs and measurements related to Energy efficiency (EE) are documented TS 28.552 ‘Management and orchestration; 5G performance measurements’ and TS 28.554 ‘Management and orchestration; 5G end to end Key Performance Indicators (KPI)’. In Rel-19, SA5 will keep working on energy efficiency and energy saving aspects of 5G networks and services according to the SID approved in SP-231723 in Dec 2023. SA1 is currently working on the potential requirements and solutions on Rel-19 Energy Efficiency as a service criteria (acronym: EnergyServ). This topic will be 100% completed by TSG 102 (Dec, 2023). The outcome of the study phase is documented in TR 22.882 - Study on Energy Efficiency as service criteria). And some of the specified SA1 stage 1 requirements, e.g. the max. energy credit, might be down streamed to SA2 for further stage 2 work. Existing and ongoing work in 3GPP SA1 working groups In the previous releases of NR (earlier than Rel-19), the studies concentrated more on how to satisfy user experience and try to achieve energy efficiency at the same time. The use cases and solutions basically concern enhancements within the 3GPP network. For example, requirements for energy efficiency have been introduced by SA1 to clause 6.15 of TS 22.261 as a fundamental 5G system requirement. However, those requirements more focused on the optimization of UEs battery life based on network configuration and control, including the UEs using small rechargeable and single coin cell batteries. But the verticals (diverse industry sectors' service providers) and customers have no approach to enhance or improve the energy efficiency for the whole system. SA1 is completed a study on energy efficiency as a service in Rel-19 (TR 22.882), which enables the users to select energy efficiency criteria based on request and some of the network performance parameters is needed. Therefore, in some scenarios, e.g. satellite and terrestrial convenience scenario, the users or operators could choose / request the best way in satisfying both user experience and energy efficiency. At the same time, the network could also deploy the more efficient strategies, i.e. energy-efficient network resource allocation and scheduling. The SA1 work on Energy Efficiency as a service criteria mainly focuses on: • Define and support energy efficiency criteria as part of communication service to user and application services. • Provide information exposure on systematic energy consumption or level of energy efficiency to vertical customers. The conclusions of this study have been captured in the 5G system requirements specification, TS 22.261. These requirements might be addressed by SA2, the system architecture group. SA2 is studying potential solutions to accomplish or satisfy the corresponding SA1 requirements. The consolidated conclusions include but are not limited to the following (in clause 6 of TR 22.882 and clause 6.15a of TS 22.261): • Subject to operator’s policy, the 5G system shall support subscription policies and means to enforce the policy that define a maximum energy consumption rate for services without QoS criteria; • The 5G network shall support a means to define maximum energy consumption rate with specific granularities (which include subscriber granularity, network slice granularity). • Subject to operator’s policy, the 5G system shall support subscription policies that define a maximum energy credit limit for services. The maximum energy credit limit could be used to control the services. • Charging related requirements, i.e. subject to operator’s policy, the 5G system shall support a means to associate energy consumption with charging information based on subscription policies. • The 5G system shall support different energy states of network elements and network functions and dynamic switch between different energy states. • For monitoring and measurement related to energy efficiency purposes, the 5G network shall support energy consumption monitoring at per network slice and per subscriber granularity, 5G system shall be able to acquire energy consumption information of the network functions serving this 3rd party, 5G system shall be able to acquire the ratio of renewable energy used to provide dedicated communication service to this 3rd party on periodic basis, , the 5G system shall be able to acquire the energy efficiency information (e.g., including the estimated carbon emissions) related to a subscriber based on the subscriber’s data volume over a specific period of time, the operator’s network energy consumption, and the carbon intensity of operator’s network. In Rel-20, SA1 approved Study on Energy Efficiency as Service Criteria Ph2 in S1-240310 during SA1 Meeting # 105 (26 Feb -1 March 2024). The objectives include: This study is aiming at identifying use cases, providing gap analysis and defining potential requirements in the following aspects regarding enhancement on energy as service criteria. The objectives are: - Information exposure of energy-related characteristics of the network for the communication service (i.e. energy consumption, energy supply mix, carbon footprint, energy capacity and availability conditions) to authorized users or authorized 3rd parties. - Potential dynamic adjustments of the delivered communication service from 5G system perspective (including service performance adjustments) resulting from the changes of energy-related characteristics of this service. Note: Dynamic adjustments can be based on criteria such as network decision, user preference or agreement between authorized 3rd parties and network. - Other aspects including security, charging and privacy for the scenarios above. Note: It is expected that use cases result in net energy saving. SA1 may also continue working on energy related topics towards 6G. Existing and ongoing work in 3GPP RAN working groups To improve the energy saving / efficiency and reduce the operation expense of NR system, in R15 and later release, RAN3 introduced energy saving for intra- and inter-system, as described in clause 15.4 of TS 38.300. This function allows the deployment of capacity boosters which provides extra capability on top of the basic coverage. Different from the cell that provides basic coverage, the capacity booster cells could be turned on and off by the NR-RAN node or the O&M autonomously, i.e. based on the load of the cell. The activation status or request of the capacity booster cell will be interacted over Xn interface between the corresponding NG-RAN nodes. The O&M-involved energy saving was specified by SA5 and documented in clause 5.1.3.3 of TS 28.310. In Rel-18, considering the significant operational cost in the radio part, RAN approved the topic - ‘Network energy savings for NR’ in order to optimize the energy consumption and energy efficiency of the radio part. The objectives of RAN WGs include but not limited to the following: • Specify SSB-less SCell operation for inter-band CA for FR1 and co-located cells. • Specify enhancement on cell DTX / DRX mechanism including the alignment of cell DTX / DRX and UE DRX in RRC_CONNECTED mode, and inter-node information exchange on cell DTX / DRX. • Improve energy efficiency or reduce energy consumption via spatial and power domains optimization, i.e. enhancements on CSI and beam management related procedures. • Specify mechanism(s) to prevent legacy UEs camping on cells adopting the Rel-18 NES techniques, if necessary • Specify CHO procedure enhancement(s) in case source / target cell is in NES mode • Specify inter-node beam activation and enhancements on restricting paging in a limited area • Specify the corresponding RRM / RF core requirements, if necessary, for the above features For the above RAN works, 5GC are not involved into either the decision making on energy saving and energy efficiency enhancement or the capacity booster cell activation and deactivation or configuration in the currently standards. Existing and ongoing work in 3GPP SA5 working groups 3GPP SA5 started the work on ‘Energy efficiency of 5G’ since Rel-16. In Rel-16, SA5 focused on the Energy Efficiency (EE) and Energy saving (ES) of mobile networks. In Rel-17, the SA5 extended the scope from RAN part only to the whole 5G system. EE Key Performance Indicators (KPI) have been defined for the 5G core network, network slices etc. SA5 work focuses on OA&M, i.e. define mechanisms to collect measurements from the 5G Network Functions via OA&M standardized APIs. Performance of network slices has been defined per type of network slice, namely for enhanced Mobile Broadband (eMBB), Ultra-Reliable and Low Latency Communication (URLLC) and massive Internet of Things (MIoT), whereas user plane traffic volumes have been considered to define the performance of the 5GC. How to measure the energy consumption (EC) of Physical Network Functions (PNF) has been defined by ETSI EE, howeverto measure the EC of Virtualized Network Functions (VNF) was blank. In Rel-17, SA5 has defined a method to estimate it, based on the estimated energy consumption of the underlying virtual compute resource instance(s), i.e. Virtual Machine(s) (VM). Currently, SA5 is still working on Rel-18 energy efficiency of 5G. On top of Rel-17, in Rel-18, SA5 is working on more accurate virtual CPU usage measurements from ETSI NFV MANO which could be used to estimate the Energy Consumption of virtual machines, new use cases for Energy Saving in the whole 3GPP system, considerations on digital sobriety etc. In the future releases, some of the parameters and measurement technique / metrics may be further enhanced by SA2 WG to support the system level energy saving and the efficient operation. SA5 also introduced the MDA (Management Data Analytics) assisted Energy Saving in clause 7.2.4 and clause 8.4.4 of TS 28.104. The MDA assisted energy saving is achieved by activating the energy saving mode of the NR capacity booster cell or 5GC NFs (e.g. UPF etc.). With considering the energy saving policies setup by the operators, the Management Data Analytics Service (MDAS) producer is able to provide energy saving recommendations to the service consumer to assist with the energy saving decision-making. For example, the MDAS procedure may provide the output to indicate where the energy efficiency issues (e.g. high-energy consumption, low energy efficiency) exist in the system and the cause of the energy efficiency issues based on the request of the consumer. Currently, SA5 can support the measurements and exposure of multiple energy related information at different granularities. For example, in TS 28.554, Energy Efficiency (EE) KPI was introduced including: • Energy Efficiency (EE) of 5GC, NG-RAN data and Network slice • Energy Consumption (EC) of NF, 5GC, network slice, NG-RAN and single gNB node. The above EE KPIs in TS 28.554 can be calculated based on the Power, Energy and Environmental (PEE) measurements in clause 5.1.1.19 of TS 28.552 and other necessary measurements, e.g. data volume at different granularities. In Rel-18, SA5 introduced TS 28.558 for Management and orchestration; UE level measurements for 5G system. Even though currently, the per UE energy related parameters are not available in the TS. But the TS open to the door to collect per UE level information from RAN and UE for energy related parameters at potential finer granularities. Existing and ongoing work in 3GPP in SA2 Considering the energy cost is one of the most significant sources of operations costs for Mobile Network Operators (MNOs), there has been increasing work in 3GPP on improving energy efficiency (EE), energy saving (ES) and reducing the energy consumption (EC) of 5GS. In the above clauses, the existing work related to EE, ES and EC in other 3GPP WGs is reviewed. From the network perspective, the previous solutions studied how to optimize energy consumption by adapting the network itself, e.g. activating and deactivating parts of the network including cells, network functions (NFs), etc. Such change to the topology and components of the network could be either transparent to the network architecture or have implications with the architecture, e.g. reselection of proper network functions. The previous work is more from the perspective of network management, including the GAM and Ran node / cell management; or from the UE perspective. Previous work does not study how to improve and enhance the energy saving and energy efficiency from the system level, i.e. considering the end-to-end energy saving and energy efficiency of a service or UE etc. before R19, standardization work on Enhancement for Energy Efficiency and Energy Saving as Service Criteria for NR system has not been introduced to SA2 before Rel-19. As mentioned in Clause 3.2.2, stage 1 requirements for energy as a service criteria have been identified by SA1 in the FS_EnergyServ study. Some of the SA1 requirements need to be addressed by SA2, i.e. by introducing new functionalities and mechanisms by SA2. The goal of the SA1 energy efficiency is to provide the same services in a more efficient manner, i.e. the services could be provided in an energy-aware manner with considering the energy use control as service criteria, functional requirements include the ability to control energy use based on operator policies such as 'energy credit limits' and 'maximum energy usage rate' applying to services provided to a UE or group of UEs. Also, SA plenary has issued a 3GPP-wide recommendation on considering Energy efficiency as an important design criterion for the technical solutions 3GPP defines in their specifications (see SP-211621). Therefore, SA2 decided to investigate options for improved system behaviour aimed at energy saving and energy efficiency in Rel-19. The SID of SA2 work has been approved in the plenary meeting in SP-231192 (September 2023), including: • WT #1. Study potential framework for network energy consumption exposure. This will include whether and what information is exposed, how it is exposed (e.g., charging) and at what granularity, e.g., at RAN level, Core Network level, network slice level, UE level, PDU session level, and / or QoS flow level. Additionally, whether and how renewable energy or carbon emission information for such granularities can be exposed by an MNO will be studied. 5 • WT #2. Study enhancement for subscription and policy control to enable network energy savings as service criteria. • WT #3. Study 5GS enhancements (e.g., energy usage adjustment for NF from CN aspect, energy saving related decision making, NF selection leveraging NF energy states) for network energy saving including 5GC(NFs) and NG-RAN interactions, 10 analytics, etc. Impacts on the UE are not ruled out e. g., for scenarios specified in TR 22.882 by SA1 EnergyServ. In order to support the above objectives, SA2 study is being carried out between November 2023 to May 2024. For WT#2, the Key Issue (KI) descriptions have been approved in S2-2313823 in SA2 160 15 meeting in Nov. 2023 and documented in clause 5.2 of TR 23.700-66: 5.2 Key Issue #2: Subscription and policy control to support energy efficiency and energy saving as service criteria 5.2.1 Description Energy related information as service criteria allows delivering services based on e.g., energy related subscriptions and policies to achieve the goal of energy saving. The following aspects will be studied for this key issue: Whether and how to enhance the existing subscription and policy control framework to support energy related information as service criteria, including: Whether and what new energy related UE subscription information are to be defined, and whether and how to use the energy related UE subscription information. Whether and what new energy related policies are to be defined, and how to perform energy related policy control, e.g. to determine, provision and enforce energy related policies. At what granularity (e.g., network slice, UE, NF, PDU Session, QoS flow, application ID, etc.) the energy related policy control can be performed. What network energy related information is required for subscription and policy control and how it is obtained. Whether and how the above enhancements on subscription and policy control will impact charging. NOTE 1: Charging enhancement aspects, if any, are to be addressed in coordination with SA WG5. The WID of SA2 R19 Energy_sys was approved in SP-241388 during SA# 105 meeting, 10 -13 September 2024. The objectives include: - WT #1. The objective of this WT is to specify the basic elements for supporting the collection 5 and calculation of energy saving and efficiency and the exposure of network energy related information. The following enhancements will be specified: 1) A new network functionality is defined to collect and calculate the energy related information and exposes to the authorized consumer subject to operator’s policy: If the authorized consumer is AF, the granularities include: per UE, per UE per 10 application, per PDU session; If the authorized consumer is 5GC NFs, the granularities include: per application, per UE, per-UE-per-QoS flow, per PDU session; The energy related information for the granularities above include: Energy consumption information; Renewable energy information. 2) The consumer NFs including 5GC NFs and / or AF, may request the energy consumption information exposure with reporting request e.g. Periodic reporting or Threshold based reporting. 3) The new functionality supporting the calculation of the Energy Consumption information includes the following aspects: a) CAM provides the NF / Node-level energy consumption information at the gNB(s) and UPF(s) serving the UE to the new functionality. b) OAM: provides the overall data volume of the gNB to the new functionality; c) The NF / Node-level information of a) and b) received from OAM, could be used by the new functionality for all the UEs serving by the NF / Node. d) UPF: provides the overall data volume of the UPF; e) UPF: provides the data volume for the QoS flow or the SDF. f) When the gNB and / or the (l-)UPF(s) which serving the UE are changed, the serving gNB ID and UPF ID will be sent to the new functionality through AMF / SMF. 4) The new functionality determines the E2E energy consumption based on energy consumption per the granularities above at serving NF (i.e. NG-RAN and UPF). 5) In the current release of the specification, only the energy-related information of user plane communication (not control plane signalling) is supported. - WT #2. The objective of this WT is to specify the enhancements for subscription and policy control to enable network energy savings as service criteria based in WT#1. The following enhancements will be specified: - The definition of energy saving subscription information per UE that is stored as part of the subscription data in the UDM / UDR, to assist the network to perform energy saving strategies for the UE - The detailed procedures for the PCF to receive UE subscription data and notification related to the energy related information to trigger making policy decisions (reusing the existing parameters) - WT #3. The objective of this WT is to specify the 5GS enhancements to support network energy saving and efficiency based on WT#1. The following enhancements will be specified: - Enhancements of NF discovery and (re-)selection based on energy related information - New energy related information and / or existing NF profile parameters in the NF Profile to allow an operator to influence NF discovery and selection based on their energy strategy Enhancement on NF discovery and (re-)selection to consider the energy related information from the NF profiles and / or discovery request from the NF consumer Enhancements on existing operations and procedures for energy saving and energy efficiency: The optional UP path adjustment for a PDU session(s) will be specified. Based on the SA2 conclusions for Rel-19 Energy_sys documented in TR 23.700-66: 1) A new network functionality is defined to collect and calculate the energy related information and exposes to the authorized consumer subject to operator's policy: If the authorized consumer is AF, the granularities include: per UE, per UE per application, per PDU session. If the authorized consumer is 5GC NFs, the granularities include: per application, per UE, per-UE-per-QoS flow, per PDU session. The energy related information for the granularities above include: Energy consumption information; Renewable energy information. 2) The consumer NFs including 5GC NFs and / or AF, may request the energy consumption information exposure with reporting request e.g. Periodic reporting or Threshold based reporting. 3) The new functionality supporting the calculation of the Energy Consumption information includes the following aspects: a) OAM provides the NF / Node-level energy consumption information at the gNB(s) and UPF(s) serving the UE to the new functionality. b) OAM provides the overall data volume of the gNB to the new functionality. c) The NF / Node-level information of a) and b) received from OAM, could be used by the new functionality for all the UEs serving by the NF / Node. d) UPF: provides the overall data volume of the UPF. e) UPF: provides the data volume for the QoS flow or the SDF. f) When the gNB and / or the (l-)UPF(s) which serving the UE are changed, the serving gNB ID and UPF ID will be sent to the new functionality through AMF / SMF. 4) The new functionality determines the E2E energy consumption based on energy consumption per the granularities above at serving NF (i.e. NG-RAN and UPF). 5) In the current release of the specification, only the energy-related information of user plane communication (not control plane signalling) is supported. Problem statement Based on the design of 5GS, the network (e.g. the RAN node or the core network) is not able to split the energy consumption at per UE level or even finer granularity accurately. One reason is that for DL transmission mechanism, the NG-RAN node may ‘multiplexed’ the data transmission to different UEs into the same slot. To maintain the service quality, the NW chooses the transmission power based on the UE in the worst radio link condition. And the same transmission power will be applied to the other UEs. However, in reality, the other UEs with better connection quality do not require this high transmission power, lower transmission power might be enough to perform the DL transmission at the same service quality. Deploying highertransmission power results in higher network energy consumption. If the network simply calculate the per UE energy consumption based on per transmission (e.g. number of RBs, data volume, etc.), the UEs with better radio connection will be ‘sacrified’ for the UEs in worse radio condition. Furthermore, SA2 Rel-19 Energy_sys, the energy consumption only targets the EC of user plane. The energy related information of control plane is not considered yet. Considering the significant amount of control signaling between UE, RAN and the core network, the EC of the CP should be also considered into the energy consumption information. Therefore, the current specified methods in SA2 and potentially SA5 on per UE energy calculation is not accurate enough to support many purposes, e.g. charging, network optimization, traffic scheduling for UEs, etc. A method that can calculate the energy consumption and other energy related parameters at per UE and even finer granularities accurately is needed in the future network design. The above information is presented as background information only to assist with an understanding of the present disclosure. No determination has been made, and no assertion is made, as to whether any of the above might be applicable as prior art with regard to the present invention. SUMMARY It is an aim of certain examples of the present disclosure to address, solve and / or mitigate, at least partly, at least one of the problems and / or disadvantages associated with the related art, for example at least one of the problems and / or disadvantages described herein. It is an aim of certain examples of the present disclosure to provide at least one advantage over the related art, for example at least one of the advantages described herein. The present invention is defined in the independent claims. Advantageous features are defined in the dependent claims. Embodiments or examples disclosed in the description and / or figures falling outside the scope of the claims are to be understood as examples useful for understanding the present invention. Other aspects, advantages, and salient features of the invention will become apparent to those skilled in the art from the following detailed description taken in conjunction with the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS Figure 1 illustrates an example method of a network entity that may be used in examples of the present disclosure. Figure 2 illustrates an example method of a first network entity that may be used in examples of the present disclosure. Figure 3 is a block diagram of an example network entity that may be used in examples of the present disclosure. DETAILED DESCRIPTION The following description of examples of the present disclosure, with reference to the accompanying drawings, is provided to assist in a comprehensive understanding of the present invention, as defined by the claims. The description includes various specific details to assist in that understanding but these are to be regarded as merely exemplary. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the examples described herein can be made. The same or similar components may be designated by the same or similar reference numerals, although they may be illustrated in different drawings. Detailed descriptions of techniques, structures, constructions, functions or processes known in the art may be omitted for clarity and conciseness, and to avoid obscuring the subject matter of the present disclosure. The terms and words used herein are not limited to the bibliographical or standard meanings, but, are merely used to enable a clear and consistent understanding of the examples disclosed herein. Throughout the description and claims, the words “comprise”, “contain” and “include”, and variations thereof, for example “comprising”, “containing” and “including”, means “including but not limited to”, and is not intended to (and does not) exclude other features, elements, components, integers, steps, processes, functions, characteristics, and the like. Throughout the description and claims, the singular form, for example “a”, “an” and “the”, encompasses the plural unless the context otherwise requires. For example, reference to “an object” includes reference to one or more of such objects. Throughout the description and claims, language in the general form of “X for Y” (where Y is some action, process, function, activity or step and X is some means for carrying out that action, process, function, activity or step) encompasses means X adapted, configured or arranged specifically, but not necessarily exclusively, to do Y. Features, elements, components, integers, steps, processes, functions, characteristics, and the like, described in conjunction with a particular aspect, embodiment, example or claim are to be understood to be applicable to any other aspect, embodiment, example or claim disclosed herein unless incompatible therewith. The following examples are applicable to, and use terminology associated with, 3GPP 5G. However, the skilled person will appreciate that the techniques disclosed herein are not limited to these examples orto 3GPP 5G, and may be applied in any suitable system or standard, for example one or more existing and / or future generation wireless communication systems or standards. The skilled person will appreciate that the techniques disclosed herein may be applied in any existing or future releases of 3GPP 5G NR or any other relevant standard. For example, the functionality of the various network entities and other features disclosed herein may be applied to corresponding or equivalent entities or features in other communication systems or standards. Corresponding or equivalent entities or features may be regarded as entities or features that perform the same or similar role, function, operation or purpose within the network. The skilled person will appreciate that certain examples of the present disclosure may not be directly related to standardization but rather proprietary implementation of some of the NR Rel-17 and beyond networks. The skilled person will appreciate that the present invention is not limited to the specific examples disclosed herein. For example: • The techniques disclosed herein are not limited to 3GPP 5G. • One or more entities in the examples disclosed herein may be replaced with one or more alternative entities performing equivalent or corresponding functions, processes or operations. • One or more of the messages in the examples disclosed herein may be replaced with one or more alternative messages, signals or other type of information carriers that communicate equivalent or corresponding information. • One or more further elements, entities and / or messages may be added to the examples disclosed herein. • One or more non-essential elements, entities and / or messages may be omitted in certain examples. • The functions, processes or operations of a particular entity in one example may be divided between two or more separate entities in an alternative example. • The functions, processes or operations of two or more separate entities in one example may be performed by a single entity in an alternative example. • Information carried by a particular message in one example may be carried by two or more separate messages in an alternative example. • Information carried by two or more separate messages in one example may be carried by a single message in an alternative example. • The order in which operations are performed may be modified, if possible, in alternative examples. • The transmission of information between network entities is not limited to the specific form, type and / or order of messages described in relation to the examples disclosed herein. The different granularities / levels referred to in the present disclosure may include one or more of the following granularities / levels: • PLMN level (e.g. multiple core networks / 5GCs / 6GCs) • single Core Network (e.g. one 5GC or6GC) level • Core network function (e.g. NF) level • network slice level • RAN level (e.g. include one or more base stations) • RAN node level (e.g. per gNB) . UE level • PDU session level • QoS flow level • Resource block level (e.g. one or more Resource blocks) • byte / bit level The different entities / resources referred to in the present disclosure may include one or more of the following: . PLMN • Core network, e.g. 5GC, 6GC • Core network function (e.g. NF) • network slice • Base station (e.g. gNB, RAN node) . UE • PDU session • Qos flow • Radio resources, e.g. Resource block • Byte / bit Energy related information referred to in the present disclosure may include one or more of the following: • Energy Efficiency (EE): Indicating the energy efficiency at different granularities (e.g. Low, Medium, High, or 1,2, 3, 4, 5). • Energy Consumption (EC): Indicating the average amount of energy consumed over the duration e.g. configured by the operator. The EC can be the energy consumed by one or more Network function of the core network, one or more UEs, one or more slices, etc. • Maximum Allowed Energy Consumption: Indicating the maximum allowed amount of energy consumption of the NF. • Energy credit: the Maximum Allowed Energy Consumption • Renewable Energy Factor: Indicating the ratio of the renewable energy to the total energy (see ISO / IEC 30134-3:2016). • Carbon Emission Factor: Indicating the amount of carbon emissions relative to an amount of resource consumption. E.g. kilograms of equivalent carbon dioxide emitted per kWh (kg of CO2eq / kWh) (see ETSI GS OEU 020). Figure 1 illustrates an example method of a network entity that may be used in examples of the present disclosure. In step 101, the network entity may acquire a granular energy consumption. Acquiring the granular energy consumption may comprise at least one of: calculating, by the network entity, the granular energy consumption; or receiving, from another network entity, the granular energy consumption. Details of how the granular energy may be calculated in examples of the present disclosure are provided below. Optionally, in step 102, the network entity may use the acquired granular energy consumption. Details of how the granular energy may be used in examples of the present disclosure are provided below. Technical effect and use of measurement In some examples of the present disclosure, a network entity may acquire a granular energy consumption. For example, the measured per UE energy consumption or per RRC connection UE energy consumption may be calculated by a gNB. This may be reported to different parts of a core network. For instance the gNB may reported it to a core network element such as an AMF or an MME. It may be reported to OAM. The measured per UE energy consumption or per RRC connection UE energy consumption may also be calculated by a core network element such as an OAM, AMF or MME, or for instance a new network function for this purpose. In some examples of the present disclosure, the network entity may use the acquired granular energy consumption. For example, the use of per UE energy consumption may for instance be for a wide range of network purposes or action: - Attempt to improve the energy consumption for specific UEs o Certain UEs may be configured to not be allowed to access certain cells, certain tracking areas or other network elements. o Certain radio functions may be turned off for UEs with high energy consumption - Attempt to improve parts of network with high energy consumption o Certain cells may be turned off or reconfigured, for instance by the OAM. Detect malfunctioning or fraudulent UEs o UEs may be barred or deregistered by the network For charging purposes, i.e. charge certain users more for network energy consumption, or charge certain users less for using energy consumption o This means that energy consumption may be sent to a charging function, which may be used to calculate the rate of a UE. The above actions may be performed by the base station, or any core network element such as an AMF, MME or OAM. General method of energy consumption calculation The network energy is mainly consumed for DL transmission, including the transmission for UE traffic / service data and control signalling. The general method to split the network energy consumption into per UE head is based on the traffic volume of specific UEs. The network is able to monitor or calculate the traffic / data volume (DV) of a network function (e.g. UPF), the RAN (e.g. a RAN node), and specific UEs. Based on existing techniques, the network is able to monitor or calculate the energy consumption of a network function (e.g. UPF), the RAN (e.g. a RAN node), etc., as detailed in the description of the related art. Therefore, the energy consumption (EC) of a specific UE can be generalised to: Equation 1: ECue = (ECnw I DVnw) * DVue The data volume can be any resource that can represent or can be used to calculate the data. For example, the data volume can be the size of the service data indicated by the AF (e.g. for picture downloading, the size of the picture), the data volume of the UE monitored by UPF / SMF / gNB / OAM; orany resources used in radio link interface, e.g. the size of one or more grants for the UE, the resource blocks allocated or transmitted to the UE, etc. Above focuses on energy consumption at the NG-RAN due to servicing of a specific UE. Knowledge of energy consumption at UE could also be beneficial in overall optimization of energy consumption. Therefore in an embodiment the consumption of a network includes energy consumption at UEs connecting to its cells. Energy consumption of RRC connected UEs For RRC connected UEs, from the perspective of radio link, the UE traffic / service data and UE specific control signaling are transmitted together, e.g. one DL grant may include both UE traffic / service data and signaling. Therefore, forthe RRC connected UEs, the data transmitted to the UE from the gNB includes all UE specific data. It is assumed that the gNB is able to count the resources allocated or transmitted to specific UE during a period of time. It is assumed that the gNB output power is highly correlated with the gNB energy consumption, e.g. higher transmission power results in higher EC. The gNB output power might be proportional to energy consumption, or the gNB has the prior knowledge on the relationship between output power and energy consumption. The energy consumption of a UE may in one aspect be composed of multiple components that are added together. Which component may be configurable, or request when another node requests the UE energy consumption, or may be reported along with any reported Energy Consumption value. In one aspect of the invention, the gNB determines the full or part of the energy consumption per radio resource (e.g. EC per RB). The EC of a specific UE could be calculated by the radio resources (RR) used: Equation 2: ECue = EC per radio resource * RRue Based on gNB knowledge and implementation, the gNB might be able to determine the (average) energy consumption per radio resource (e.g. EC per RR). The (average) energy consumption per radio source might be statistical value, based on the previous measurements and monitoring data and / or prediction of the future condition. For instance, the network may use the EC of the same time of day of previous days. Average energy consumption could be vendor specific and something that is declared by the vendor. Average energy consumption could be deployment specific (e.g. Small Cell / HetNets, macrocells, FR1 vs FR2 vs FR3) and average values could be determined for typical deployments and UE densities and UE traffic. The average EC per radio resource can be updated by the network. The energy consumption per radio resource could be different for every specific UE, e.g. based on the UE radio link quality, the UE always requires high power for DL transmission; therefore, the EC per radio source of this UE will be higher than the UEs with better connection quality. The energy consumption per radio source might be a per cell or per gNB specific value, e.g. for all the UEs in one cell or served by one gNB, the energy consumption per radio source is considered to be the same value. The gNB may introduce some adjustors for calculating the energy more accurately, by considering UE radio link quality (e.g. for the UEs with in different air link quality, different values are deploy to adjust the EC), UE MIMO capability and configuration (e.g. if MIMO is configured for a UE, this UE may consume more energy than other UEs, even the radio link quality is in similar level), etc. Multi-antenna usage may introduce an increase in power consumption. The power consumed may be dependent on the number of transmit or receive antennas that are in use. This can be used for both MIMO and / or beamforming (for increasing antenna gain). The power consumption can be said to be increased based on the number of MIMO streams used. The energy consumption may also be dependent on whetherthe UE is configured with Carrier Aggregation or Dual Connectivity. In the case of Carrier Aggregation, the energy consumption may be determined by the number of carriers that have been configured to the UE, or the number of carriers that are activated. In the case of Dual Connectivity, both gNBs, i.e. Main and Secondary Nodes may be estimated the power consumption independently. The radio resource may for instance be the number of Resource Blocks (RBs) or the amount of bandwidth used. In another aspect of the invention, one method of calculating the energy consumption of a UE may be determined or estimated based on the time a UE is in connected mode. This can for instance be determined by a network by measuring or determining when the UE enters and leaves connected mode. The power consumption may thus be determined based on the time (T) that a UE is in connected mode and the power consumption per time unit in connected mode of the UE, for instance in the following manner: Equation 3: ECue = EC per time unit * Trrc_connected The power consumption per time unit in connected may be determined or estimated in a number of ways. It may for instance be estimated per UE or an average value for all UEs per time unit. It may also be dependent on the coverage or any signal strength of signal quality sent by a UE. This may for instance be useful in the case where the QoS configured to a UE is the same for all UEs and the network will attempt to deliver the data as fast as possible. Then the longer the UE is in connected mode will largely correspond to the energy consumption. It may also help to account for energy consumption due to other reasons than downlink transmissions. It may indicate the energy consumption of locking up resources for a UE, energy consumption of the gNB being unable to shut down etc. The energy consumption may also partly be determined or estimated based on the energy consumption for a UE to enter the connected mode. Thus may comprise the energy consumption of performing random access, the energy consumption for perform initial access, the energy consumption for the RACH reception or similar. This may be a fixed amount of energy consumption, in other words each UE is considered to use the same amount of energy to enter connected mode, or it may be differentiated per UE. The network may attempt to estimate the number of access attempts if it is believed that multiple access attempts were made. In one aspect of the invention, if energy consumption is partly determined or estimated based on the energy consumption for random access, the network may also include other events in the energy consumption, such as for radio link failures, beam failures. This can be the same amount for each event for all UEs, or be differentiated. This for instance allows a network to compute the energy due to repeated failures, which may occur for specific UEs in bad locations. In one aspect of the invention, handovers may be included in the power consumption of a UE. This is because a handover may indicate a mobile UE, which is more likely to consume more power compared to a stationary UE. Any energy consumption may be dependent on measurements sent by a UE. For instance if the UE sends measurements indicating per signal strength or poor signal quality, the UE may be considered to have higher energy consumption. When combining different parts for the energy consumption in RRC connected, some examples may for instance be the addition of energy consumption of the radio resources, energy consumption of time in RRC_CONNECTED and energy consumption of entering RRC_CONNECTED: Equation 4: ECue = ECrr + ECt rrc_connected + ECenter RRC_CONNECTED Each energy component may be weighted. The energy consumption may be calculated per RRC connection. In other words, the energy consumption of a UE may only be determined for each time that the UE is in RRC connected. The UE may calculate the energy consumption per UE identifier, such as per TMSI or 5G S TMSI. This may mean that a gNB or a cell stores the energy consumption for an identifier, such as for each TMSI or 5G S TMSI. Identification of Energy Consumption by Control Plane operations Tracing Energy consumption monitoring for all PDN or PDU Sessions, all the time, would be wasteful of resources, and violate a specific principle known as 'energy sobriety.' The approach to saving energy or controlling energy use should not significantly worsen energy use. For this reason specific PDN or PDU Sessions will support a means to perform 'energy utilization trace' - which can activated by the MNO. This activation could be controlled by the PCF (as part of a policy for enforcing energy utilization, the energy trace could be engaged.) Also, it could be activated by the SMF, or by direct intervention of deployment of static policy by the GAM. For those PDN or PDU Sessions that are to be 'energy consumption traced' each NF in the network that performs operations on behalf of the session will gather information concerning that actions performed. This could be in terms of specific SBA service invocations, or counted at a higher level, e.g. operations as defined by procedures. This counter is incremented on the basis of each action performed and linked with the PDN or PDU session. The counter could be indiscriminate (in which all actions are counted the same), or discriminate (in which different actions are counted separately.) This is in principle the same as the different counters for operations that are supported in SNMP MIBs, exposed to OAM according to IETF standards. However, examples of the present disclosure provide innovative uses of these counters. For a given network function, there is a total amount of energy used Etotai and a total number of operations performed Ototai. For a given PDU session there is a total number of operations Opdu. It is possible to identify in reasonable detail the share of the energy Etotai incurred by the PDU session by means of the following equation: Equation 5: Opdu * Etotai / Ototai = Epdu The counter saved would include at least the following information {PDU session ID, OPDU counter value, EPDU, timex}. These counter values could be saved incrementally, in which time is the latest time saved (accurate up until timex), or discretely, at different timex, so that the 'energy use overtime' can be modeled. This could be relevant, e.g. if there are different charging or other consequences for energy use at different times (of day, maximum rate of use [as per the Rel-19 requirements], etc.) This can be done at the indiscriminate level, or be done for each of the discriminated categories, then summed together, as Equation 6. £ (Opou-i * Etotai-i / Ototai-i) However for this, there needs to be a statistical assignment of the energy utilization contribution to different discriminated categories (i). For example, an operation that performs a caching of state or starts a timer to trigger a later operation can cost more than one which merely results in a stateless transfer of information. In this case the energy information stored by each NF would be {PDU session ID, category i (scalar), Opdu counter value for category i, Epdu for category i, timex} It is also possible that the granularity of the measurement is of finer granularity - at the level of a specific QoS flow. Only a subset of the control plane nodes are aware of this (PCF, SMF, UPF, AF,...) In this case, to correlate actions on behalf of a specific QoS flow (which is at the granularity of a specific service) additional identifiers are carried with control plane signalling. These function as keys and could be established in the PCF or SMF. In this case, the energy information stored by each NF would be {PDU session ID, Opdu counter value, QoS Flow ID, EPDu-fiow, timex} This could also be used with discrimination of different actions, as above. Using the QoS Flow ID and energy use value described above, it is now possible to count how much energy is used by the specific QoS flow. Accounting The information captured at each NF which has the energy trace function active, for a given PDU session, or a given set of QoS flows for specific PDN sessions, will be gathered to one location so that it can be summed (total energy use over all NFs for the control plane use.) This gathering can be accomplished in different ways: - The control plane signalling to the SMF from the given NF will carry the counter(s) as an additional information element, so the SMF can gather the information. - The counter information can be captured in Charging Records with specific energy charging information elements. - The counter information can be signalled to a new Energy Control Function by means of an accounting interface, to centrally gather the information in one place. Use of energy consumption info for network optimization and handover Energy consumption of a network node or a group of nodes ING-RAN depends on the number of UEs being served, the split of those UEs into IDLE / INACTIVE / CONNECTED at any given time, the type of data etc. It also depends on energy efficiency of individual nodes or NG-RANs - some could be more efficient than others. Handover decision may therefore take into account not just radio conditions (as is common in legacy systems) or ON / OFF approach (switching entire sites and handing over UEs to another site for purposes of energy consumption reduction), but also the current per UE energy consumption (e.g. based on UE RRC state, traffic being served etc.) and the efficiency of the current node, and how overall energy consumption could differ following a HO to more energy efficient nodes and / or nodes where channel conditions for UEs would improve. To avoid penalising gNBs serving UEs which are far from the gNB, where there is a need for either UEs or gNB or both to use higher power due to e.g. interference, the considerations on energy consumption and related network optimization may differentiate between UEs which have higher output power and / or require gNB to transmit at higher power because users are consuming more data, and those who have higher output power because of channel conditions. Additionally, gNBs currently exchange info on transmit power per bands, in order to facilitate interference management - additional signalling exchange between nodes linked to energy consumption may be introduced, so that overall NG-RAN energy could be minimised e.g. gNB informs neighbours of its own average EC parameters like those detailed in this invention. Figure 2 illustrates an example method of a first network entity that may be used in examples of the present disclosure. In step 201, the first network entity may acquire a granular energy consumption. The granular energy consumption may be an energy consumption of at least one of: PLMN level, single Core Network level, Core network function level, network slice level, RAN level, RAN node level, RRC connection, UE level, PDU session level, QoS flow level, resource block level, or byte / bit level. Certain examples of the present disclosure may be provided in the form of an apparatus / device / network entity configured to perform one or more defined network functions and / or a method therefor. Such an apparatus / device / network entity may comprise one or more elements, for example one or more of receivers, transmitters, transceivers, processors, controllers, modules, units, and the like, each element configured to perform one or more corresponding processes, operations and / or method steps for implementing the techniques described herein. For example, an operation / function of X may be performed by a module configured to perform X (or an X-module). Certain examples of the present disclosure may be provided in the form of a system (e.g. a network) comprising one or more such apparatuses / devices / network entities, and / or a method therefor. It will be appreciated that examples of the present disclosure may be realized in the form of hardware, software or a combination of hardware and software. Certain examples of the present disclosure may provide a computer program comprising instructions or code which, when executed, implement a method, system and / or apparatus in accordance with any aspect, claim, example and / or embodiment disclosed herein. Certain embodiments of the present disclosure provide a machine-readable storage storing such a program. Figure 3 is a block diagram of an exemplary network entity (e.g. gNB or core network entity) that may be used in examples of the present disclosure. The skilled person will appreciate that the network entity illustrated in Figure 3 may be implemented, for example, as a network element on a dedicated hardware, as a software instance running on a dedicated hardware, or as a virtualised function instantiated on an appropriate platform, e.g. on a cloud infrastructure. The entity 300 comprises a processor (or controller) 301, a transmitter 303 and a receiver 305. The receiver 305 is configured for receiving one or more messages from one or more other network entities. The transmitter 303 is configured for transmitting one or more messages to one or more other network entities. The processor 301 is configured for performing operations as described above. While the invention has been shown and described with reference to certain examples, it will be understood by those skilled in the art that various changes in form and detail may be made therein without departing from the scope of the invention, as defined by the appended claims. Certain examples of the present disclosure provide one or more techniques as disclosed in the following examples. The skilled person will appreciate that any of these techniques may be applied in combination with any of the techniques described above and illustrated in the Figures. In a first example, there is provided a method of a network entity in a communication network, the method comprising: acquiring a granular energy consumption. In a second example, there is provided the method of the first example, wherein the granular energy consumption is an energy consumption of at least one of: PLMN level, single Core Network level, Core network function level, network slice level, radio access network (RAN) level, RAN node level, user equipment (UE) level, protocol data unit (PDU) session level, quality of service (QoS) flow level, resource block level, or byte / bit level. In a third example, there is provided the method of the first or second example, wherein acquiring the granular energy consumption comprises at least one of: calculating, by the network entity, the granular energy consumption; or receiving, from another network entity, the granular energy consumption. In a fourth example, there is provided the method of any of the first to third examples, further comprising using the acquired granular energy consumption. In a fifth example, there is provided the method of the fourth example, wherein using the acquired granular energy consumption comprises at least one of: reporting the acquired granular energy consumption to another network entity, controlling to change energy consumption of a UE based on the acquired granular energy consumption, controlling to change energy consumption of part of the network based on the acquired granular energy consumption, detecting a malfunctioning or fraudulent UE based on the acquired granular energy consumption, determining a charge based on the acquired granular energy consumption, or performing a handover based on the acquired granular energy consumption. In a sixth example, there is provided the method of any of the first to fifth examples, wherein the network entity is one of a base station or a core network entity (e.g. AMF, MME or OAM). In a seventh example, there is provided a first network entity (e.g. a gNB or core network entity) configured to operate according to a method of any of the first to sixth examples. In an eighth example, there is provided a second network entity (e.g. a gNB or core network entity) configured to cooperate with a first network entity of the seventh example according to a method of any of the first to sixth examples. In a ninth example, there is provided a network orwireless communication system comprising a first network entity according to the seventh example and a second network entity according to the eighth example. In a tenth example, there is provided a computer program comprising instructions which, when the program is executed by a computer or processor, cause the computer or processor to carry out a method according to any of the first to sixth examples. In an eleventh example, there is provided a computer or processor-readable data carrier having stored thereon a computer program according to the tenth example. In a twelfth example, there is provided a method of a first network entity in a communication network, the method comprising: acquiring a granular energy consumption, and wherein the granular energy consumption is an energy consumption of at least one of: PLMN level, single Core Network level, Core network function level, network slice level, radio access network (RAN) level, RAN node level, RRC connection, user equipment (UE) level, protocol data unit (PDU) session level, quality of service (QoS) flow level, resource block level, or byte / bit level. In a thirteenth example, there is provided the method of the twelfth example, wherein acquiring the granular energy consumption comprises at least one of: calculating, by the first network entity, the granular energy consumption; or receiving, from a second network entity, the granular energy consumption. In a fourteenth example, there is provided the method of the thirteenth example, wherein calculating the granular energy consumption comprises calculating the granular energy consumption based on at least one of: radio resources (e.g. number of resource blocks, amount of bandwidth) used by a UE, and an energy consumption per radio resource used by a UE. In a fifteenth example, there is provided the method of the fourteenth example, wherein the energy consumption per radio resource used by a UE is based on at least one of: previous measurements, monitoring data, predicted future conditions, vendor, deployment, the UE, a cell that the UE is in, a RAN node serving the UE, radio link quality, and UE capability or configuration (e.g. MIMO, carrier aggregation, dual connectivity). In a sixteenth example, there is provided the method of any of the thirteenth to fifteenth examples, wherein calculating the granular energy consumption comprises calculating the granular energy consumption based on at least one of: a time that the UE is in connected mode, and an energy consumption per unit of time that a UE is in connected mode. In a seventeenth example, there is provided the method of the sixteenth example, wherein the energy consumption per unit of time that a UE is in connected mode is based on at least one of: the UE, signal strength of the UE, and signal quality of the UE. In an eighteenth example, there is provided the method of any of the thirteenth to seventeenth examples, wherein calculating the granular energy consumption comprises calculating the granular energy consumption based on energy consumption of events at the UE (e.g. entering connected mode, random access, initial access, RACH reception, radio link failure, beam failure, handover). In a nineteenth example, there is provided the method of the thirteenth example, wherein calculating the granular energy consumption of a session (e.g. PDN, PDU) or flow (e.g. QoS) comprises: identifying, for each network function that performs operations on behalf of the session or flow, information related to the operations performed; and calculating the granular energy consumption of the session or flow based on the identified information related to the operations performed. In a twentieth example, there is provided the method of the nineteenth example, wherein the information related to the operations performed includes at least one of: information identifying a session, information identifying the number of operations performed, information identifying an energy consumption of the operations performed, information identifying a time, information identifying at least one category of operations performed, information identifying the number of operations performed for each of the at least one categories, information identifying an energy consumption of the operations performed for each of the at least one categories information identifying a flow, and information identifying an energy consumption of the operations performed on behalf of a flow. In a twenty-first example, there is provided the method of the nineteenth or twentieth examples, wherein identifying, for each network function that performs operations on behalf of the session orflow, information related to the operations performed comprises: determining, at each network function, whether energy consumption monitoring is activated for the session or flow; and only identifying information related to the operations performed on behalf of the session or flow if it is determined that energy consumption monitoring is activated for the session orflow. In a twenty-second example, there is provided the method of any of the nineteenth to twenty-first examples, wherein identifying, for each network function that performs operations on behalf of the session or flow, information related to the operations performed comprises receiving, at the first network entity from each of the network functions, the information related to the operations performed. In a twenty-third example, there is provided the method of any of the twelfth to twenty-second examples, further comprising using the acquired granular energy consumption. In a twenty-fourth example, there is provided the method of the twenty-third example, wherein using the acquired granular energy consumption comprises at least one of: reporting the acquired granular energy consumption to a second network entity, controlling to change energy consumption of a UE based on the acquired granular energy consumption, controlling to change energy consumption of part of the network based on the acquired granular energy consumption, detecting a malfunctioning or fraudulent UE based on the acquired granular energy consumption, determining a charge based on the acquired granular energy consumption, or performing a handover based on the acquired granular energy consumption. In a twenty-fifth example, there is provided the method of the twenty-fourth example, wherein controlling to change energy consumption of a UE based on the acquired granular energy consumption comprises at least one of: configuring the UE to prevent access to one or more cells, configuring the UE to prevent access to one or more tracking areas, configuring the UE to prevent access to one or more network elements, and configuring the UE to disable one or more radio functions. In a twenty-sixth example, there is provided the method of twenty-fourth example, wherein controlling to change energy consumption of part of the network based on the acquired granular energy consumption comprises at least one of: disabling one or more cells based on the acquired granular energy consumption, and reconfiguring one or more cells based on the acquired granular energy consumption. In a twenty-seventh example, there is provided the method of the twenty-fourth example, wherein performing a handover based on the acquired granular energy consumption comprises at least one of: determining whether to perform handover based on the acquired granular energy consumption, determining a node to handover to based on the acquired granular energy consumption, performing a handover based on determined overall network energy consumption. In a twenty-eighth example, there is provided the method of the twenty-seventh example wherein the determining is further based on at least one of: node efficiency, and energy consumption cause (e.g. data use, channel conditions). In a twenty-ninth example, there is provided the method of any of the twelfth to twenty-eighth examples, further comprising transmitting to a second network entity, energy consumption information of the first network entity. In a thirtieth example, there is provided the method of any of the twelfth to twenty-ninth examples, wherein the first network entity is one of a base station or a core network entity (e.g. AMF, MME or OAM). In a thirty-first example, there is provided a first network entity (e.g. a gNB or core network entity) configured to operate according to a method of any of the twelfth to thirtieth examples. In a thirty-second example, there is provided a second network entity (e.g. a gNB or core network entity) configured to cooperate with a first network entity of the thirty-first example according to a method of any of the twelfth to thirtieth examples. In a thirty-third example, there is provided a network or wireless communication system comprising a first network entity according to the thirty-first example and a second network entity according to the thirty-second example. In a thirty-fourth example, there is provided a computer program comprising instructions which, when the program is executed by a computer or processor, cause the computer or processor to carry out a method according to any of the twelfth to thirtieth examples. In a thirty-fifth example, there is provided a computer or processor-readable data carrier having stored thereon a computer program according to the thirty-fourth example. Abbreviations / Definitions In the present disclosure, the following abbreviations and definitions may be used. 3GPP 5G 3rd Generation Partnership Project 5th Generation 5 5GC 5G Core 5G S TMSI 5G S-Temporary Mobile Station Identifier AF Application Function AMF Access and Mobility Management Function API Application Programming Interface 10 CA Carrier Aggregation CE Control Element CHO Conditional Handover CP Control Plane CSI Channel State Information 15 CT Core networks and Terminals CU Central Unit DL DownLink DRX Discontinuous Reception DTX Discontinuous Transmission 20 DU Distributed Unit DV Data Volume EC Energy Consumption EE Energy Efficiency eMBB enhanced Mobile Broadband 25 eNB 4G base station ES Energy Saving E2E End-to-end F1 interface between DU and CU FFS For Further Study 30 FR1 Frequency Range 1 FR2 Frequency Range 2 FR3 Frequency Range 3 gNB 5G base station ID Identity / ldentification 35 IP Internet Protocol IE Information Element IETF Internet Engineering Task Force KI Key Issue KPI Key Performance Indicator 40 MDA Management Data Analytics MDAS Management Data Analytics Service MIB Master Information Block MIoT Massive Internet of Things MNO Mobile Network Operator 45 MR-DC Multi-RAT Dual Connectivity NF Network Function NG Interface between 5G RAN and Core NR New Radio OAM / OA&M Operations, Administration, and Maintenance 50 O&M Operation and Maintenance PCF Policy Control Function PDN Packet Data Network PDU Protocol Data Unit PEE Power, Energy and Environmental 55 PNF Physical Network Function QoS Quality of Service RACH Random RAN Radio Access Network RAN2 Radio layer 2 and Radio layer 3 Working Group RAN3 UTRAN / E-UTRAN / NG-RAN Working Group Rei Release 5 RF Radio Frequency RRC Radio Resource Control RRM Radio Resource Management RS Reference Signal SA1 Services Working Group 10 SA2 System Architecture and Services Working Group SA5 Management, Orchestration, and Charging Working Group SBA Service Based Architecture SIB System Information Block SMF Session Management Function 15 SNMP Simple Network Management Protocol SS Synchronization Signal SSB Synchronization Signal Block TMSI Temporary Mobile Station Identifier TR Technical Report 20 TS Technical Specification UDM Unified Data Management UDR User Data Repository UE User Equipment UL UpLink 25 UPF User Plane Function URLLC Ultra-Reliable and Low Latency Communication VNF Virtulaized Network Function WG Working Group Xn network interface between NG-RAN nodes 30 X2 interface between 2 base stations

Claims

1. A method of a first network entity in a communication network, the method comprising: acquiring a granular energy consumption, andwherein the granular energy consumption is an energy consumption of at least one of: PLMN level, single Core Network level, Core network function level, network slice level, radio access network (RAN) level, RAN node level, RRC connection, user equipment (UE) level, protocol data unit (PDU) session level, quality of service (QoS) flow level, resource block level, or byte / bit level.

2. The method of claim 1, wherein acquiring the granular energy consumption comprises at least one of:calculating, by the first network entity, the granular energy consumption; or receiving, from a second network entity, the granular energy consumption.

3. The method of claim 2, wherein calculating the granular energy consumption comprises calculating the granular energy consumption based on at least one of:radio resources (e.g. number of resource blocks, amount of bandwidth) used by a UE, andan energy consumption per radio resource used by a UE.

4. The method of claim 3, wherein the energy consumption per radio resource used by a UE is based on at least one of:previous measurements,monitoring data,predicted future conditions,vendor,deployment,the UE,a cell that the UE is in,a RAN node serving the UE, radio link quality, andUE capability or configuration (e.g. MIMO, carrier aggregation, dual connectivity).

5. The method of any of claims 2 to 4, wherein calculating the granular energy consumption comprises calculating the granular energy consumption based on at least one of:a time that the UE is in connected mode, andan energy consumption per unit of time that a UE is in connected mode.

6. The method of claim 5, wherein the energy consumption per unit of time that a UE is in connected mode is based on at least one of:the UE,signal strength of the UE, andsignal quality of the UE.

7. The method of any of claims 2 to 6, wherein calculating the granular energy consumption comprises calculating the granular energy consumption based on energy consumption of events at the UE (e.g. entering connected mode, random access, initial access, RACH reception, radio link failure, beam failure, handover).

8. The method of claim 2, wherein calculating the granular energy consumption of a session (e.g. PDN, PDU) or flow (e.g. QoS) comprises:identifying, for each network function that performs operations on behalf of the session or flow, information related to the operations performed; andcalculating the granular energy consumption of the session or flow based on the identified information related to the operations performed.

9. The method of claim 8, wherein the information related to the operations performed includes at least one of:information identifying a session,information identifying the number of operations performed,information identifying an energy consumption of the operations performed,information identifying a time,information identifying at least one category of operations performed,information identifying the number of operations performed for each of the at least one categories,information identifying an energy consumption of the operations performed for each of the at least one categoriesinformation identifying a flow, andinformation identifying an energy consumption of the operations performed on behalf of a flow.

10. The method of claim 8 or 9, wherein identifying, for each network function that performs operations on behalf of the session or flow, information related to the operations performed comprises:determining, at each network function, whether energy consumption monitoring is activated for the session or flow; andonly identifying information related to the operations performed on behalf of the session or flow if it is determined that energy consumption monitoring is activated for the session or flow.

11. The method of any of claims 8 to 10, wherein identifying, for each network function that performs operations on behalf of the session or flow, information related to the operations performed comprises receiving, at the first network entity from each of the network functions, the information related to the operations performed.

12. The method of any preceding claim, further comprising using the acquired granular energy consumption.

13. The method of claim 12, wherein using the acquired granular energy consumption comprises at least one of:reporting the acquired granular energy consumption to a second network entity, controlling to change energy consumption of a UE based on the acquired granular energy consumption,controlling to change energy consumption of part of the network based on the acquired granular energy consumption,detecting a malfunctioning or fraudulent UE based on the acquired granular energy consumption,determining a charge based on the acquired granular energy consumption, or performing a handover based on the acquired granular energy consumption.

14. The method of claim 13, wherein controlling to change energy consumption of a UE based on the acquired granular energy consumption comprises at least one of:configuring the UE to prevent access to one or more cells,configuring the UE to prevent access to one or more tracking areas, configuring the UE to prevent access to one or more network elements, and configuring the UE to disable one or more radio functions.

15. The method of claim 13, wherein controlling to change energy consumption of part of the network based on the acquired granular energy consumption comprises at least one of: disabling one or more cells based on the acquired granular energy consumption, and reconfiguring one or more cells based on the acquired granular energy consumption.

16. The method of claim 13, wherein performing a handover based on the acquired granular energy consumption comprises at least one of:determining whether to perform handover based on the acquired granular energy consumption,determining a node to handover to based on the acquired granular energy consumption,performing a handover based on determined overall network energy consumption.

17. The method of claim 16 wherein the determining is further based on at least one of: node efficiency, andenergy consumption cause (e.g. data use, channel conditions).

18. The method of any preceding claim, further comprising transmitting to a second network entity, energy consumption information of the first network entity.

19. The method of any preceding claim, wherein the first network entity is one of a base station or a core network entity (e.g. AMF, MME or OAM).

20. A first network entity (e.g. a gNB or core network entity) configured to operate according to a method of any preceding claim.

21. A second network entity (e.g. a gNB or core network entity) configured to cooperate with a first network entity of claim 20 according to a method of any of claims 1 to 19.

22. A network or wireless communication system comprising a first network entity according to claim 20 and a second network entity according to claim 21.

23. A computer program comprising instructions which, when the program is executed by a computer or processor, cause the computer or processor to carry out a method according to any of claims 1 to 19.

24. A computer or processor-readable data carrier having stored thereon a computer program according to claim 23.T +44(0)30 0300 2000A

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