Entities and methods for enabling efficient data collection in a mobile core network
By introducing network entities with adaptive reporting cycles and effective time windows into mobile communication networks, the frequency of data collection and reporting is dynamically adjusted, solving the problems of frequent signaling load and low energy efficiency, and achieving efficient utilization of network resources and energy saving.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- HUAWEI TECH CO LTD
- Filing Date
- 2023-11-13
- Publication Date
- 2026-06-05
Smart Images
Figure CN122162400A_ABST
Abstract
Description
Technical Field
[0001] This application relates to wireless communications. More specifically, this application relates to entities and methods for achieving efficient data collection in mobile communication networks (including the core network of the mobile communication network). Background Technology
[0002] In mobile communication networks (or simply mobile networks), such as 5G or 5G-A networks, network operations typically require subscription to and notification of service operations. These network operations can be, but are not limited to, quality of service (QoS) monitoring, analysis, and network operations such as network access. Typically, subscription to and notification of service operations requires extensive data collection, monitoring, and reporting capabilities. These extensive features require communication and computing resources, where communication resources typically include signaling related to data collection and reporting, while computing resources include resources for measurement, event detection, monitoring, and data processing.
[0003] Subscription and notification services are essential and fundamental operations in 5G or 5G-A networks. The associated signaling load and data traffic vary in frequency from infrequent to extremely frequent, depending on the notification mechanism employed. Typically, networks use periodic or event-based notifications. Generally, periodic notifications generate higher signaling loads than event-based notifications. If frequent or extremely frequent notifications are required, reducing the signaling load per service operation will positively impact the overall signaling load. On the other hand, reducing the signaling load should not affect the requirements that must be met to serve the subscription request. Therefore, the key is to improve the overall signaling load without affecting the subscription request requirements (e.g., the request type or required accuracy level).
[0004] The efficiency of signaling load is directly related to network energy consumption. Fundamentally, improving signaling load efficiency helps improve energy efficiency and / or achieve energy savings. For 6G mobile communication networks, energy saving and energy efficiency are core indicators that must be considered in architecture, process, and operational design. Summary of the Invention
[0005] The purpose of this application is to provide improved entities and methods for achieving efficient data collection in mobile communication networks, including the core network of the mobile communication network.
[0006] The foregoing and other objectives are achieved through the subject matter claimed in the independent claims. Other implementations are apparent from the dependent claims, the specification, and the drawings.
[0007] According to a first aspect, a network entity for providing subscription services in a mobile network is provided. In one implementation, the network entity may be a network function of the mobile network.
[0008] The network entity according to the first aspect is used to receive subscription requests from network functions (also referred to herein as consumer network functions) for notification reports of the subscription service provided by the producer network function. Furthermore, the network entity according to the first aspect is used to provide the network function with notification reports having a time-varying, i.e., adaptive reporting period (which may also be expressed as reporting frequency) and / or a time-varying, i.e., adaptive reporting validity window. The network entity according to the first aspect allows for improved signaling load efficiency of the network operation and processes by adjusting the adaptive reporting period and / or the adaptive reporting validity window over time, thereby preventing the sending of unnecessary data collection or notification reports in response to the subscription request. Therefore, the network entity according to the first aspect can improve energy efficiency and power saving performance in mobile communication networks, particularly 5G-A or 6G mobile communication networks.
[0009] In another possible implementation, the subscription request is a request for a notification report with a time-varying reporting period and / or a valid time window for time-varying reporting. Therefore, a new type of subscription request is provided in mobile networks.
[0010] In another possible implementation, the subscription request includes an indication of a notification report having a time-varying reporting period and / or a time-varying reporting validity window. In one implementation, the indication may be an indication of an "adaptive notification mode." Therefore, the subscription request may specifically indicate a request for an adaptive notification mode.
[0011] In another possible implementation, the subscription request includes one or more of the following: an initial reporting period, the expected accuracy associated with the subscription request, the expected energy efficiency information, the expected energy consumption information, and / or the expected data sensitivity level.
[0012] In another possible implementation, the network entity is used to determine the time-varying reporting period and / or the effective time window for time-varying reporting. Therefore, the network entity itself can determine the time-varying reporting period and / or the effective time window for time-varying reporting.
[0013] In another possible implementation, the network entity is used to determine the time-varying reporting period and / or the effective time window for time-varying reporting based on one or more of the following: - Statistical information of the data collected or processed by the network entity to generate the notification report; - Data or statistical information received from another network function for generating the notification report; - Statistical information from the notification reports submitted to the consumer network function; - Predictive information from the data collected or processed by the network entity to generate upcoming notification reports; - Data or predictive information for generating upcoming notification reports received from the other network function; - The predicted information of the upcoming report reported to the consumer network function; - The expected accuracy related to the notification report or subscription request; - Expected energy efficiency or energy consumption information, and / or - Expected data sensitivity level.
[0014] In another possible implementation, the network entity is also configured to receive the notification report from another network function related to the subscription request from the network function. The notification report from the other network function includes data required to process the notification report or a final notification report reported to the network function. Therefore, the network entity can efficiently handle further processing operations on the notification report from the other network function.
[0015] In another possible implementation, the network entity is also used to provide a time-varying adaptive data collection cycle to the other network function. For example, in the generation of analysis output, data collection is a fundamental mechanism, and further optimization of the adaptive data collection cycle controls signaling load and associated energy consumption. Therefore, the network entity can efficiently control the periodicity of data collection (especially the data required for the notification report) by the other network function.
[0016] In another possible implementation, the network entity is used to initially provide the network function with the notification report having an initial reporting period. Therefore, the network entity can begin sending the notification report with a beneficial initial reporting period.
[0017] In another possible implementation, the network entity adjusts the initial reporting period and provides the network function with a notification report having the time-varying reporting period and / or the effective time window for the time-varying reporting. Therefore, the network entity may adjust the initial reporting period due to, for example, environmental changes.
[0018] In another possible implementation, the effective time window for time-varying reporting is defined by when the network function receives the next notification report from the network entity.
[0019] In another possible implementation, the network entity is also used to negotiate the time-varying reporting period with the network function. Therefore, the network entity can ensure a time-varying reporting period that is also acceptable using the network function.
[0020] In another possible implementation, the subscription service provided by the network entity in the mobile network is related to QoS monitoring, analysis, data openness, and / or event openness service operations.
[0021] In another possible implementation, the notification report includes energy efficiency and / or energy consumption related information.
[0022] In another possible implementation, the network entity is also used to determine the energy efficiency or energy consumption related information associated with the time-varying reporting period or the effective time window for time-varying reporting.
[0023] According to a second aspect, a method for providing a subscription service in a mobile network is provided, the method comprising: Receive subscription requests from notification reports of the subscription service received from the network function; Provide the network function with time-varying (i.e., adaptive reporting period) and / or time-varying (i.e., adaptive reporting effective time window) notification reports.
[0024] The method described according to the second aspect of this application can be performed by a network entity (e.g., a network function) described according to the first aspect of this application. Therefore, other features of the method described according to the second aspect of this application arise directly from the network entity described according to the first aspect of this application and the functionality of its various implementations described above and below.
[0025] According to a third aspect, a computer program product is provided, including a computer-readable storage medium for storing program code, which, when executed by a computer or processor, causes the computer or processor to perform the method according to the second aspect.
[0026] The accompanying drawings and the following description illustrate details of one or more embodiments. Other features, objects, and advantages will be apparent from the specification, drawings, and claims. Attached Figure Description
[0027] The embodiments of this application will be described in detail below with reference to the accompanying drawings. In the drawings: Figure 1 A schematic diagram of a mobile communication network is shown, specifically, the core network of the mobile communication network, including a network entity according to one embodiment, which is used to provide notification reports from producer network functions with adaptive notification periods to consumer network functions; Figure 2 A schematic diagram of the traditional reporting mechanism in a mobile communication network is shown. Figure 3A schematic diagram illustrating the interaction between a network entity and a network function according to one embodiment to negotiate an adaptive notification cycle is shown. Figure 4 A schematic diagram illustrating the interaction between a network entity and a network function according to one embodiment to provide a notification report with an adaptive notification cycle is shown. Figure 5 A schematic diagram illustrating the interaction between a network entity and a network function according to another embodiment to provide a notification report with an adaptive notification cycle is shown. Figure 6 The diagram illustrates the interaction between a network entity in the form of DCCF according to one embodiment and another network entity in the form of NWDAF according to one embodiment, to provide a signaling diagram with an adaptive notification cycle for a notification report to a consumer network function. Figure 7 The diagram illustrates the interaction between a network entity in the form of an SMF and a consumer network function in the form of a UPF, according to one embodiment, to provide the UPF with an N4 session-level reporting notification report with an adaptive notification period. Figure 8 The diagram illustrates the interaction between a network entity in the form of NSACF according to one embodiment and another network entity in the form of NEF according to one embodiment, providing a signaling diagram in the form of AF to a consumer network function with a notification report including network slice related service level agreement (SLA) parameters with an adaptive notification period. Figure 9 A schematic diagram illustrating the inputs and outputs of a network entity for determining an adaptive notification period according to one embodiment is shown; Figure 10 (a) through (c) show the network slice load level measurement. Figure 10 (a) of the traditional periodic reporting scheme Figure 10 (b) in the example and the adaptive reporting scheme implemented by a network entity using an adaptive notification period according to one embodiment; Figure 11 A schematic diagram of a backward algorithm for determining an adaptive notification period implemented by a network entity, according to one embodiment, is shown. Figure 12 A schematic diagram illustrating the inputs and outputs of a network entity for determining an adaptive notification validity time window, according to one embodiment, is shown. Figure 13 (a) through (c) show the network slice load level measurement. Figure 13 (a) of the traditional periodic reporting scheme Figure 13(b) in the above and an adaptive reporting scheme implemented by a network entity using an adaptive notification effective time window according to one embodiment; Figure 14 A schematic diagram of a long short-term memory (LSTM) recurrent neural network (RNN) implemented according to one embodiment for determining an adaptive notification effective time window is shown. Figure 15 This is a flowchart of a method for operating a network entity according to one embodiment.
[0028] In the following text, the same reference numerals refer to the same or at least functionally equivalent features. Detailed Implementation
[0029] In the following description, reference is made to the accompanying drawings, which form part of this application, illustrating by way of description specific aspects of embodiments of the present application or aspects in which embodiments of the present application may be used. It should be understood that embodiments of the present application may be used in other aspects and may include structural or logical variations not depicted in the drawings. Therefore, the following detailed description should not be construed in a limiting sense, and the scope of the present application is defined by the appended claims.
[0030] For example, it should be understood that the disclosure relating to the described method is also applicable to the corresponding device or system used for the method, and vice versa. For instance, if one or more specific method steps are described, the corresponding device may include one or more units (e.g., functional units) to perform the described one or more method steps (e.g., one unit performs one or more steps, or multiple units perform one or more of a plurality of steps respectively), even if such one or more units are not explicitly described or shown in the drawings. Furthermore, if a particular apparatus is described based on one or more units (e.g., functional units), the corresponding method may include a step to perform the function of one or more units (e.g., one step performs the function of one or more units, or multiple steps perform the function of one or more of a plurality of units respectively), even if such one or more steps are not explicitly described or shown in the drawings. Moreover, it should be understood that, unless otherwise expressly stated, features of the various exemplary embodiments and / or aspects described herein can be combined with each other.
[0031] Figure 1A schematic diagram is shown of a mobile communication network 100, specifically, the core network of the mobile communication network 100, including a network entity 120 according to one embodiment, for providing a notification report from a producer network function 110 to a consumer network function 130, having a time-varying, i.e., adaptive reporting period (which may also be represented as a reporting frequency) and / or a time-varying, i.e., adaptive reporting effective time window. Figure 1 In one embodiment, network entity 120 is referred to as adaptive data scheduler (ADS) 120. In one embodiment, network entity 120 may be a standalone network function implemented in the core network of mobile communication network 100. According to other embodiments detailed below, network entity 120 may be implemented alongside or as part of producer network function 110.
[0032] As detailed below, network entity 120 (e.g., ADS 120) supports adaptive mechanisms for subscription and notification service operations. More specifically, these adaptive mechanisms can be used to collect data from producer NF 110 and to report data or notification events to consumer NF 130. Adaptive mechanisms may include adapting or adjusting the data collection frequency or rate, data reporting frequency or rate, and / or notification cycle or event. Adaptive notification cycles or events may also include a valid time window for the reported event or data. The valid time window represents the (expected) reporting time of the next data or event. The next data reporting may be triggered by network entity 120 before the provided valid time window expires, for example, due to the detection of a significant change in the value to be notified or a significant change in the required level of accuracy.
[0033] As detailed below, network entity 120 (e.g., ADS 120) can determine the adaptive reporting frequency or adaptive effective time window based on statistics or forecasts of previously collected or reported data. Furthermore, network entity 120 may also consider subscription requirements in the determination process. Subscription requirements may include one or more of the following: accuracy level, energy efficiency requirements, energy saving level, and data sensitivity level.
[0034] As detailed below, network entities (such as ADS 120) can improve the signaling load efficiency of network operations and processes by adjusting the adaptive reporting period and / or the adaptive reporting validity window over time, thereby, for example, preventing the sending of unnecessary notification reports in response to subscription requests. Thus, network entity 120 can improve the energy efficiency and power saving performance of mobile communication networks, especially 5G-A or 6G mobile communication networks.
[0035] Before describing in more detail embodiments of network entity 120 and producer network function 110 for providing notification reports with adaptive reporting frequencies to consumer network function 130, some technical background and terminology will be introduced below using one or more of the following abbreviations: 5G fifth-generation mobile network technology standard 5G-A fifth-generation mobile network evolution technology standard 6G sixth-generation mobile network technology standard CN core network AF application function DCCF data collection and coordination function SMF session management function NWDAF network data analytics function UPF user plane function NF network function NSACF network slice admission control function The energy used in this article is understood according to the ITU-T L.1330 standard, where energy is defined as "the ability to do work; which exists in many forms and can be converted into one another (such as thermal, mechanical, electrical or chemical energy), and is measured in joules (J), watt-hours (Wh) or kilowatt-hours (kWh)".
[0036] Based on the TS 28.554 and TS28.310 standards, energy consumption in this paper refers to the total amount of energy consumed to achieve a specific system purpose, expressed in joules (J) or watt-hours (Wh).
[0037] Based on ETSI ES 203 228 and ITU-T L.1330 standards, the energy saving in this paper refers to the feature that can effectively reduce energy consumption compared to when a specific feature is not achieved.
[0038] The energy efficiency definition used in this article is based on ITU-T L.1330 and TS 28.554. Energy efficiency refers to the ratio between useful output and energy consumption. Specifically, SA5 defines the formula for the general key performance indicator (KPI) for energy efficiency in clause 6.7.4.1:
[0039] Among them, "5GC Useful Output" 5GC ")" indicates the useful output of 5GC (the specific definition varies depending on the 5GC network function considered), and "5GC power consumption (EC)" indicates the energy consumption of 5GC. 5GC ")" indicates the energy consumption of 5GC. Essentially, energy efficiency is a KPI, which is evaluated as the ratio between a specific performance metric and the energy required to achieve that performance.
[0040] The signaling used in this document refers to signals used to control the operation of communication services. This may include the exchange of information required for the establishment and control of service operations related to processes.
[0041] The signaling load used in this article refers to the total amount of signaling required to complete a single service operation or step.
[0042] As used in this document, accuracy refers to the tolerance (defined by a unit value, such as milliseconds, seconds, bits per second, etc.) of a reported, collected, or processed value relative to a baseline value. Tolerance is the total error allowed to exist from the baseline value. An example of a baseline value is the notification report mentioned above. The terms "accuracy" or "accuracy grade" are generally used interchangeably.
[0043] The sensitivity level or data sensitivity level used in this article is a quantitative indication of the level of data sensitivity in subscriptions and notifications. There is more than one sensitivity level. Examples of (data) sensitivity levels can be low, medium, or high. A sensitivity level or data sensitivity level can be defined as a range of desired time-varying reporting periods or effective time windows. The consumer NF can define the desired range, i.e., the minimum and maximum allowed reporting periods or effective time windows. The producer NF determines specific (time-varying) reporting period or effective time window values based on this desired range. If the determined (time-varying) reporting period or effective time window value exceeds this range, the producer NF can negotiate with the consumer NF. The sensitivity level required for a subscription may be a factor in determining notifications.
[0044] The adaptive effective time window used in this article refers to the (expected) next reporting time. This is a time-varying value and can also be considered as the effective time period of the current report, the data value of the report, or the notification. The effective time window is usually associated with a notification report or the data value of the report.
[0045] The adaptive reporting cycle (or equivalent "frequency") used in this article refers to a reporting cycle that varies over time and can be determined based on statistical or predictive information about the collected or reported data.
[0046] The adaptive data collection period used in this paper refers to a data collection period that varies over time and can be determined based on statistical information or predictions of the collected data.
[0047] Figure 2 A schematic diagram of the traditional reporting mechanism in a mobile communication network is shown. More specifically, Figure 2 This illustrates basic subscription and notification service operations implemented as part of the CN process in traditional mobile communication networks. For example, Figure 2 The CN process illustrated involves analysis and generation, QoS monitoring, and (external) accessibility, requiring fundamental features such as data collection, data reporting, and event notification. Subscription and notification service operations supporting these fundamental features include traditional periodic or event-based mechanisms.
[0048] In a traditional "periodic" mechanism, the consumer NF subscribes to the producer NF to periodically notify it of specific service operations, for example, every "x" units. Here, "x" can be any integer value, and the unit can be milliseconds, seconds, minutes, or hours. In a traditional "event-based" mechanism, the consumer NF subscribes to the producer NF based on one or more specific conditions to notify it of specific service operations. The producer NF only notifies the consumer NF of the subscribed event when one or more of these conditions are met. In this case, one or more conditions define the constraints of the event-based subscription, which are typically defined by the consumer NF.
[0049] It should be understood that static notification reporting provided by the traditional "periodic" mechanism constitutes a simple scheme; however, in some scenarios, this scheme may lack efficiency and / or flexibility. For example, although repeated notifications of the same or very similar values are unnecessary, i.e., redundant, the producer NF sends the same notification to the consumer NF every "x" units, such as the same or similar values of subscribed service operations. Event-based mechanisms are more efficient than "periodic" mechanisms, for example, in terms of signaling load efficiency. However, event reporting conditions are fixed and configured by specific conditions, thus allowing only limited flexibility. In "periodic" or "event-based" mechanisms, the configuration of periodic or event reporting conditions is usually set by the consumer NF. In most cases, the consumer NF does not fully understand the behavior of the reports generated by the producer NF. Therefore, periodic or event reporting conditions are not properly defined or are ambiguous.
[0050] Figure 3A schematic diagram illustrating the interaction between a network entity 120 (e.g., ADS 120) and a consumer network function 130, according to another embodiment, to negotiate an adaptive notification cycle is shown. (As in...) Figure 3 As will be understood in the illustrated embodiments, network entity 120 (e.g., ADS 120) is juxtaposed or implemented as a component of producer network function 110.
[0051] exist Figure 3 In this embodiment, network entity 120 (e.g., ADS 120) implements "..." for subscription and notification service operations. Adaptive "Reporting mode. If the event reporting mode requested by the consumer NF 130 is..." Adaptive In the reporting mode, the time-varying notification frequency and / or effective time window are determined by the ADS 120. The following describes the process of adaptive subscription and notification service operation negotiated between the ADS 120 and the consumer NF 130.
[0052] exist Figure 3 In Phase 1, the consumer NF 130 uses the event reporting mode = "adaptive" and initial The data reporting frequency (e.g., 5 seconds) is subscribed to to implement the producer NF 110 of ADS 120.
[0053] exist Figure 3 In Phase 2, the producer NF 110 implementing ADS 120 responds to the subscription request by sending the subscription association ID to the consumer NF 130.
[0054] exist Figure 3 In phase 3, the producer NF 110 implementing ADS 120 notifies the consumer NF 130 of the subscription event at an initial reporting frequency (e.g., every 5 seconds).
[0055] At the same time, Figure 3 In Phase 4, the producer NF 110 implementing ADS 120 processes and determines an adaptive reporting frequency (if the subscription includes these requirements) based on statistical data of the stored data and optional requirements (accuracy, energy consumption, data sensitivity level). Based on this input data, the producer NF 110 implementing ADS 120 can determine a new reporting frequency for notification reports sent to the consumer NF 130, which will be detailed below.
[0056] exist Figure 3 In phase 5, the producer NF 110 implementing ADS 120 uses the UpdateNotify service operation to trigger an update notification to the consumer NF 130 at a new data collection frequency (e.g., every 10 seconds).
[0057] exist Figure 3In phase 6, the consumer NF 130 responds to the UpdateNotify request by sending an accept or reject instruction to the producer NF 110 that implements ADS 120.
[0058] If in Figure 3 In phase 7, if the producer NF 110 implementing ADS 120 receives a new reporting frequency, then the producer NF 110 implementing ADS 120 will send the next notification report to the consumer NF 130 according to the new reporting frequency.
[0059] It should be understood that if the producer NF 110 implementing ADS 120 determines to trigger a new reporting frequency and / or a new valid time window, then Figure 3 Phases 5 through 7 can occur at any time.
[0060] Figure 4 This shows the situation without negotiating the adaptive reporting frequency. Figure 3 Variations of the illustrated embodiment.
[0061] exist Figure 4 In Phase 1, the consumer NF 130 implements the producer NF 110 of ADS 120 with an event reporting mode = "adaptive" subscription. Furthermore, subscription requests may include required accuracy, required or desired energy efficiency ratings, required or desired energy-saving information, and / or sensitivity ratings indicating the importance of subscription events and related data. It should be understood that sensitivity ratings may differ from accuracy. Accuracy relates to the tolerance of reporting based on measurements in specific units (such as milliseconds, seconds, bits per second, etc.). Sensitivity ratings relate to the importance of the subscription request and the conditions under which the notification is determined. For example, a subscription request related to ultra-reliable low-latency communications (URLLC) services may generally be more sensitive than one for enhanced mobile broadband (eMBB) services.
[0062] exist Figure 4 In Phase 2, the producer NF 110 implementing ADS 120 responds to the subscription request by returning the subscription association ID to the consumer NF 130.
[0063] Based on forecasts and / or statistics and inputs from subscription requests and other relevant subscription requests, in Figure 4In Phase 3, the producer NF 110 implementing ADS 120 processes notifications and determines an adaptive reporting frequency (e.g., 10 seconds) and / or an effective time window as the (expected) next notification time to the consumer NF 130. The producer NF 110 implementing ADS 120 can also determine (expected) data accuracy and energy efficiency or energy-saving information, such as energy consumption information.
[0064] Building upon the previous stage, the producer NF 110 of ADS 120 is now implemented in... Figure 4 In phase 4, an adaptive notification is triggered and sent to the consumer NF. Furthermore, the notification message sent to the consumer NF 130 may include (expected) data accuracy and energy efficiency or energy-saving information, such as energy consumption information.
[0065] As described above, the effective time window represents the (expected) time for the next data report. In one embodiment, the next data report may be triggered before the provided effective time window expires, for example, due to a significant change in the required variance / accuracy level.
[0066] Figure 3 and Figure 4 Another variation of the embodiment is as follows: Figure 5 As shown.
[0067] exist Figure 5 In Phase 1, the producer NF 110 implementing ADS 120 receives subscription requests (e.g., data collection, data openness, analytics subscriptions, QoS monitoring related subscriptions) from the consumer NF 130, where the event reporting mode is "periodic" and the reporting period is (e.g., 5 seconds).
[0068] exist Figure 5 In Phase 2, the producer NF 110 implementing ADS 120 responds to the subscription request by returning the subscription association ID to the consumer NF 130.
[0069] exist Figure 5 In Phase 3, the producer NF 110 implementing ADS 120 periodically, for example, every 5 seconds, notifies the consumer NF130 of the subscribed data.
[0070] exist Figure 5 In Phase 4, the producer NF 110 of ADS 120 determines the need for an adaptive reporting cycle based on statistics of data collected related to subscriptions. Based on this information, the producer NF 110 of ADS 120 determines a new (adaptive) reporting cycle.
[0071] exist Figure 5In Phase 5, the producer NF 110 of ADS 120 initiates negotiation of a new reporting period with the consumer NF 130. This trigger may be part of one of the notification reports sent to the consumer NF 130. For the new trigger, a dedicated service operation, such as an updateNotify service operation, may be sent to the consumer NF 130 at a new reporting period (e.g., 10 seconds). Alternatively, the notification report may include the new reporting period.
[0072] If the consumer NF 130 accepts the recommended new reporting cycle, then in Figure 5 In phase 6, the modified subscription request is sent to the producer NF 110 implementing ADS 120, including the subscription association ID and the received reporting frequency or acceptance indication. The consumer NF 130 may, for example, reject the suggested reporting cycle based on operator policies or if other service requirements are not met.
[0073] exist Figure 5 In phase 7, the producer NF 110 implementing ADS 120 sends a notification report to the consumer NF 130 based on the new reporting cycle.
[0074] It should be understood that whenever the producer NF 110 implementing ADS 120... Figure 5 When determining the new reporting cycle in Phase 4, Figure 5 Phases 5 through 7 can occur at any point in time.
[0075] As described above, providing adaptive notification reports involves the ADS 120 determining the adaptive reporting frequency or effective time window. Below, two algorithms that can be implemented by the ADS 120 for determining the adaptive reporting frequency or effective time window are described.
[0076]
[0077]
[0078] Figure 6 A signaling diagram illustrating another embodiment is shown, in which components of ADS 120 and DCCF 110 are co-located or implemented as components of DCCF 110, and another component of ADS 120 is co-located or implemented as a component of NWDAF 110 for providing notification reports with adaptive notification cycles to consumer network function 130.
[0079] exist Figure 6In phase 1, the DCCF 110 of the ADS 120 with an "adaptive" data reporting mode is analyzed for consumer function 130 subscriptions (e.g., DataManagement_Subscribe). The subscription request may include the required accuracy, initial cycle time interval T, energy efficiency level, and energy-saving information related to the data subscription.
[0080] In Figure 6 phases 2 and 3, the DCCF 110 determines the NWDAF 110 instance and whether the requested analysis has been collected.
[0081] In Figure 6 phase 4, the DCCF 110 of the ADS 120 for subscription (e.g., AnalyticsSubscription_Subscribe) implements the NWDAF 110 of the ADS 120 with an "adaptive" data reporting mode. The subscription includes the required accuracy, initial cycle time interval T1 (i.e., T1 < T), energy efficiency level, data sensitivity level related to the subscription, and Figure 6 the message in the subscription request included in phase 1.
[0082] In Figure 6 phases 5a and 5b, the NWDAF 110 of the ADS 120 is implemented to notify the DCCF110 of the AnalyticsSubscription subscription message at the initial cycle time interval T1.
[0083] In Figure 6 phase 6a, the DCCF 110 of the ADS 120 is implemented to notify the analysis consumer function 130 of the DataManagment subscription message at the initial cycle time interval T.
[0084] In Figure 6 phase X, the DCCF 110 of the ADS 120 is implemented to process the adaptive notification and determine a new valid time window for the next notification report based on the prediction and / or statistical information and input data from the subscription request. If a new valid time window is determined, the valid time window and the current notification message can be sent together to the analysis consumer NF 130.
[0085] In Figure 6 phase X+1, the DCCF 110 implementing the ADS 120 function notifies the analysis consumer NF 130 of the new valid time window. Optionally, the notification may include the associated accuracy and energy consumption level.
[0086] In Figure 6In phase Y, another ADS 120, the NWDAF 110, independently processes adaptive notifications and determines a new valid time window for the next report based on forecasts and / or statistics from subscription requests and input data. If a new valid time window is determined, it can be sent to the DCCF 110 along with the current notification message.
[0087] exist Figure 6 In phase Y+1, the NWDAF 110 of another ADS 120 notifies the DCCF 110 of the new valid time window. Optionally, the notification message may include associated accuracy and energy consumption information.
[0088] exist Figure 6 In phases 7 and 8, the analysis consumer NF 130 uses Ndccf_DataManagement_Fetch requests and Ndccf_DataManagement_Fetch responses to request and receive information about data retrieval from DCCF 110.
[0089] exist Figure 6 In phase 9, the unsubscribe service operation Ndccf_DataManagement_Unsubscribe can occur between analytics consumers NF 130 and DCCF 110.
[0090] exist Figure 6 In phase 10, the unsubscribe service operation Nnwdaf_AnalyticsSubscription_Unsubscribe can occur between DCCF 110 and NWDAF 110.
[0091] Figure 7 A signaling diagram illustrating another embodiment is shown, in which ADS 120 is co-located with SMF 110 or implemented as a component of SMF 110, and Consumer Network Function 130 is implemented as UPF 130 for providing N4 Session Level Reporting notification reports with adaptive notification periods to UPF 130.
[0092] exist Figure 7 In Phase 1, the SMF 110 of the ADS 120 is implemented to process adaptive data reporting frequency and determine new reporting frequency based on the prediction and / or statistical information of the received reports.
[0093] exist Figure 7 In Phase 2, the SMF 110 implementing ADS 120 sends an N4 session modification request with a new reporting frequency to the UPF 130.
[0094] exist Figure 7In phase 3, UPF 130, in response to the previous phase 2, sends an N4 session modification request with a new reporting frequency to SMF 110. The response to the N4 session modification request may include an indication to accept or reject the new reporting frequency.
[0095] exist Figure 7 In Phase 4, the SMF 110 interacts with other network functions. Figure 7 In phases 5 and 6, UPF 130 triggers a reporting event and initiates an N4 session report to SMF 110. Figure 7 In phase 7, SMF 110 confirms the reported event with UPF 130.
[0096] Figure 8 A signaling diagram illustrating another embodiment is shown, in which components of ADS 120 and NSACF 110 are co-located or implemented as components of NSACF 110, and another component of ADS 120 is co-located or implemented as a component of NEF 110, for providing a notification report including network slice-related SLA parameters to consumer network function 130 in the form of AF 130 with an adaptive notification cycle.
[0097] exist Figure 8 In Phase 1, the AF 130 subscription has adaptive subscription and notification features for the NEF 110.
[0098] exist Figure 8 In Phase 2, NEF 110 confirms the subscription request to AF 130.
[0099] exist Figure 8 In Phase 3, NEF 110 subscriptions feature adaptive subscriptions and notifications for NSACF 110.
[0100] exist Figure 8 In Phase 4, NSACF 110 confirms the subscription request to NEF 110.
[0101] exist Figure 8 In phase 5, the NSACF 110 of ADS 120 determines the effective time window.
[0102] exist Figure 8 In phase 6, NSACF 110 triggers an adaptive notification with a valid time window to NEF 110.
[0103] In a multi-NSACF scenario, the NEF 110 implementing ADS 120 can... Figure 8 In Phase 7, aggregation is performed on the open data from each NSACF110 network slice, and an effective time window is determined.
[0104] exist Figure 8 In phase 8, NEF 110 triggers an adaptive notification with a valid time window to AF 130.
[0105] As mentioned above, the producer NF 110 (which can implement ADS 120) or consumer NF 130 can be any 5GC NF defined in TS23.501. Subscription and notification service operations between any two 5GC NFs are applicable.
[0106] In the following sections, further detailed embodiments of adaptive notification implemented by network entity 120 (e.g., ADS 120) will be described with reference to examples of reporting NSLL analysis. However, it should be understood that the concepts described below are the same for other types of data to be reported.
[0107] Figure 9 A schematic diagram illustrating the inputs and outputs of a network entity 120 (e.g., ADS 120) for determining adaptive notification periods in real time, according to one embodiment, is shown. Figure 9 In the illustrated embodiment, the ADS 120 implements a real-time algorithm for providing adaptive notifications based on the following inputs: statistical data (e.g., sampled data up to time instance (t_i) for the notification, the required accuracy, and the (initial) periodic time interval). Figure 9 As shown, ADS 120 receives statistics on the sampled data (e.g., for generating NSLL analysis), the required accuracy (percentage), and the initial periodic time interval T. Based on the required accuracy, the NSLL statistics, and the currently generated NSLL, ADS 120 determines adaptive notifications in real time. If the currently generated NSLL meets the required accuracy—for example, if the difference between the previous NSLL value and the currently generated NSLL value is less than the accuracy value—ADS 120 can determine not to send a notification to consumer NF 130. If the difference is greater than the accuracy value, ADS 120 can trigger a notification report to consumer NF 130.
[0108] Figure 10 (a) through (c) show the network slice load level measurement. Figure 10 (a) of the traditional periodic reporting scheme Figure 10 (b) and network entity 120 (e.g., ADS 120) according to one embodiment use an adaptive reporting scheme implemented in real time with an adaptive notification period. For a given average NSLL measurement (i.e., input sampled data, Figure 10 In (a) of the traditional periodic mechanism, at each interval T ( Figure 10(b) in the above notifies the consumer NF (i.e., C). In a real-time mechanism implemented by ADS 120 according to one embodiment ( Figure 10 In (c) of the above, the ADS 120 monitors the current NSLL data and the previously notified NSLL at each time interval T and determines whether the value is within the provided accuracy range compared to the previous value. If the difference between the current NSLL value and the previous NSLL value is greater than the accuracy range, an adaptive notification is triggered. For example, as shown in (c) Figure 10 As shown in (c), the ADS 120 observed that at time T_A, the NSLL value did not meet the accuracy range compared to the previous value (e.g., Figure 10 As shown in (a) above, an adaptive notification is then sent to the consumer NF 130 (see [reference]). Figure 10 (c) step 2). Afterwards, if the accuracy exceeds the range, the next adaptive notification is sent at T_A'. It should be understood that the timing of sending the adaptive notification, i.e., T_A and T_A' being unequal, represents the adaptive nature, i.e., the non-periodic reporting implemented by the ADS 120.
[0109] Figure 11 A schematic diagram is shown of a backward algorithm implemented by a network entity 120 (e.g., ADS 120) for determining an adaptive notification period according to one embodiment. The backward algorithm implemented by ADS 120 calculates the adaptive reporting frequency based on statistical data (e.g., sampled data up to time instance (t_i), the required accuracy, and the time interval T). An exemplary implementation of the backward ADS 120 can use Discrete Fourier Transform (DFT) box 121. By converting a finite sequence of sampled input data (i.e., NSLL(t)) in the time domain into a sequence of the same length in the frequency domain, ADS 120 can determine the maximum frequency (i.e., fM) required to avoid losing information. During the determination process, the resulting frequency domain signal is then passed through filter 122 to remove unwanted frequencies, providing a signal with a cutoff frequency fM as the output. Figure 11 (See box 123 shown in the image). Here, fM is the adaptive reporting frequency, which determines the reporting time of adaptive notifications. In this scenario, ADS 120 determines the new reporting frequency for the consumer NF 130 to improve the efficiency of subscription and notification service operations. Essentially, the ADS 120 with its backward mechanism determines the new reporting frequency based on statistical data and can be used long-term. This means that changes in the new reporting frequency are not very frequent.
[0110] Figure 12A schematic diagram is shown of the inputs and outputs of a network entity 120 (e.g., ADS 120) for determining an adaptive notification validity time window based on a forward algorithm, according to another embodiment. Figure 12 As shown, the forward algorithm uses historical timestamps of NSLL data, accuracy requirements expressed as a percentage, and sampling period T to determine the effective time window.
[0111] Figure 13 Tables (a) to (c) show the network slice load level measurement. Figure 13 (a) of the traditional periodic reporting scheme Figure 13 (b) and the adaptive reporting scheme implemented by network entity 120 (e.g., ADS 120) according to one embodiment, for use in Figure 12 The example illustrates the implementation of the forward algorithm. It should be understood that traditional periodic reporting (such as...) Figure 13 As shown in (b), adaptive notifications are sent periodically according to the sampling period T. However, by using the forward algorithm implemented according to an embodiment of ADS 120, the value of NSLL can be predicted for the prediction horizon (PH), where PH can be the number of timestamps for which the prediction is performed. Figure 13 As shown in (a) of the diagram. Then, according to one embodiment, ADS 120 analyzes these predicted NSLL values based on the required accuracy requirements. When an NSLL value violates the accuracy requirements, the period up to that timestamp is considered at the effective time window (i.e., T_V). This process continues until the next violation occurs. For example, as... Figure 13 As shown in (c), the next violation occurs at T_V', and according to one embodiment, this violation will be reported by ADS 120 as a valid time window. It should be understood that T_V and T_V' may or may not be equal.
[0112] Figure 14 A schematic diagram of an LSTM RNN implemented according to one embodiment for determining an adaptive notification effective time window (e.g., ADS 120) is shown. More specifically, in Figure 14 In the illustrated embodiment, ADS 120 is used to implement LSTM model 1402 for predicting NSLL values. LSTM model 1402 is trained using historical statistical NSLL data and deployed after training (see [link to documentation]). Figure 14 Phase 1401). To perform predictions, multiple historical NSLL(T) values are fed into the LSTM model 1402, a process called the backtracking period. An exemplary backtracking period is... Figure 14The LSTM model 1402 performs multi-step predictions on PH values over 60 minutes (i.e., one value per minute). Once these values are predicted, they are analyzed to determine the effective window and notifications are sent accordingly (see [link to LSTM model 1402]). Figure 14 (Stage 1403). For a given accuracy range σ, if the difference between two values is greater than σ, then the timestamp is considered to be used for sending an adaptive notification. Therefore, the period between sending these two adaptive notifications is considered the effective window, such as... Figure 14 As shown in T_V, T_V', and T_V''.
[0113] Figure 15 The diagram illustrates methods for operating network entities (e.g., network entity 120, in particular). Figure 1 The flowchart illustrates a method 1500 for providing a subscription service in a mobile communication network 100 using an ADS 120. Method 1500 includes step 1501, receiving a subscription request as a notification report of the subscription service from a consumer network function 130. Furthermore, method 1500 includes step 1503, providing the consumer network function 130 with a notification report having an adaptive time-varying reporting period and / or an adaptive time-varying reporting validity window.
[0114] Method 1500 can be performed by network entity 120 according to one embodiment. Therefore, other features of method 1500 are directly derived from network entity 120 and the functionality of its various embodiments described above and below.
[0115] Those skilled in the art will understand that “blocks” (“units”) in the various drawings (methods and apparatuses) represent or describe the functionality of embodiments of this application (and are not necessarily independent “units” in hardware or software), thereby equally describing the functionality or features (unit = step) of apparatus embodiments and method embodiments.
[0116] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the described apparatus embodiments are merely exemplary. For example, the unit division is merely a logical functional division, and other division methods may exist in actual implementation. For example, multiple units or components may be merged or integrated into another system, or some features may be ignored or not performed. Furthermore, the mutual coupling or direct coupling or communication connection shown or discussed can be implemented through some interface. Indirect coupling or communication connection between devices or units can be implemented electronically, mechanically, or otherwise.
[0117] The units described as individual components may or may not be physically separate; the components shown as units may or may not be physical units, and may be located in the same position or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of the embodiment scheme according to actual needs.
[0118] In addition, the functional units in the embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.
Claims
1. A network entity (110; 120) providing subscription services in a mobile network (100), characterized in that, The network entities (110; 120) are used for: Receive the subscription request from the network function (130) in the notification report of the subscription service; Provide the network function with a notification report having a time-varying reporting period and / or a time-varying reporting validity window.
2. The network entity (110; 120) according to claim 1, characterized in that, The subscription request is a request for a notification report with a time-varying reporting period and / or a time-varying reporting effective time window.
3. The network entity (110; 120) according to claim 1 or 2, characterized in that, The subscription request includes an indication of a notification report with a time-varying reporting period and / or a time-varying reporting validity window.
4. The network entity (110; 120) according to any one of the preceding claims, characterized in that, The subscription request includes one or more of the following: initial reporting cycle, expected accuracy related to the reporting or subscription request, expected energy efficiency information, expected energy consumption information, and / or expected data sensitivity level.
5. The network entity (110; 120) according to any one of the preceding claims, characterized in that, The network entities (110; 120) are used to determine the time-varying reporting period and / or the effective time window for time-varying reporting.
6. The network entity (110; 120) according to claim 5, characterized in that, The network entity (110; 120) is used to determine the time-varying reporting period and / or the effective time window for time-varying reporting based on one or more of the following: -Statistical information collected or processed by the network entities (110; 120) for generating the notification report; - Data or statistical information received from another network function (120) for generating the notification report; -Statistical information of the notification report reported to the network function (130); - Predictive information that will be collected or processed by the network entities (110; 120) to generate upcoming notification reports; - Data or predictive information for generating upcoming notification reports received from the other network function (120); - The predicted information of the upcoming report reported to the network function (130); - The expected accuracy related to the notification report or subscription request; - Expected energy efficiency or energy consumption information, and / or - Expected data sensitivity level.
7. The network entity (110; 120) according to any one of the preceding claims, characterized in that, The network entity (120) is also configured to receive the notification report from another network function (110) associated with the subscription request from the network function (130).
8. The network entity (120) according to claim 7, characterized in that, The network entity (120) is also used to provide a time-varying adaptive data collection cycle to the other network function (110).
9. The network entity (110; 120) according to any one of the preceding claims, characterized in that, The network entities (110; 120) are used to initially provide the notification report with an initial reporting period to the network function (130).
10. The network entity (110; 120) according to claim 9, characterized in that, The network entity (110; 120) is used to adjust the initial reporting period and provide the network function (130) with the time-varying reporting period and / or the time-varying reporting effective time window.
11. The network entity (110; 120) according to any one of the preceding claims, characterized in that, The effective time window for time-varying reporting is defined by when the network function (130) receives the next notification report from the network entity (110; 120).
12. The network entity (110; 120) according to any one of the preceding claims, characterized in that, The network entity (110; 120) is also used to negotiate the time-varying reporting period with the network function (130).
13. The network entity (110; 120) according to any one of the preceding claims, characterized in that, The subscription service provided by the network entity (110; 120) in the mobile network (110) is related to the operation of QoS monitoring, analysis, data access and / or event access services.
14. The network entity (110; 120) according to any one of the preceding claims, characterized in that, The notification report includes energy efficiency and / or energy consumption related information.
15. The network entity (110; 120) according to any one of the preceding claims, characterized in that, The network entities (110; 120) are also used to determine the energy efficiency or energy consumption related information associated with the time-varying reporting period or the effective time window of the time-varying reporting.
16. A method (1500) for providing a subscription service in a mobile network (100), characterized in that, The method (1500) includes: Receive a subscription request from the network function (130) for a notification report of the subscription service (1501); Provide the network function (130) (1503) with a notification report having a time-varying reporting period and / or a time-varying reporting effective time window.
17. A computer program product comprising a computer-readable storage medium, characterized in that, The computer-readable storage medium is used to store program code that, when executed by a computer or processor, causes the computer or processor to perform the method (1500) according to claim 16.