Transfer table service for 5G core network

Abstract

A mobility management node or other network node generates and maintains a probability distribution function indicating a probability that a user equipment (UE) transfers from one or more source service areas to a specified destination service area. When congestion of a destination service area is predicted, a request may be sent to a mobility management node to obtain transition probability data for the destination service area to identify possible source service areas as well as distributed data indicating high traffic users in those possible source service areas. Policy control nodes or other network nodes may use transition probability data and scatter data to implement congestion mitigation measures.

Description

Technical Field

[0001] This disclosure generally relates to analysis-based congestion management in wireless communication networks, and more particularly to congestion mitigation based on transition probability functions. Background Technology

[0002] The Network Automation specification in the Fifth Generation (5G) standard released by the Third Generation Partnership Project (3GPP) introduces the Network Data Analytics Function (NWDAF) as a primary network function for calculating analytical reports. NWDAF supports various types of analysis, including user data congestion analysis and distributed data analysis.

[0003] User data congestion analysis involves providing statistics or predictions about congestion encountered during the transmission of user data over the control plane or user plane within a specific region or for an individual user. This information helps identify areas or network slices experiencing congestion and enables measures to be implemented to mitigate congestion and improve user experience.

[0004] Distributed data analytics focuses on identifying regions or network slices in which specific users or groups generate a significant portion of their data volume and session transactions. It determines the percentage of activity occurring at a specific location or network slice within a given time period. This analytics allows operators to target and resolve congestion issues in specific locations or slices.

[0005] In 5G networks, NWDAF (Network Data Digestion Analysis) can provide insights into congestion in areas such as Tracking Areas (TA), gNB areas, or cells. This information can trigger measures to alleviate congestion for users in affected areas. Furthermore, distributed data analysis can be used to identify relevant subsets of users within congested areas, such as... High-traffic users ( TopHeavyUsers The typical user analyzed by the NWDAF is the Policy Control Function (PCF), which targets a subset of identified users (e.g., High-traffic users Mitigation measures can be applied to effectively reduce congestion and enhance network performance, as described in Clause 6.1.1.3 of 3GPP Technical Standard (TS) 23.503.

[0006] In addition to its current congestion detection capabilities, NWDAF is expected to support congestion prediction in specific regions using, for example, standard time series forecasting algorithms. This feature aims to predict congestion before it occurs, providing a degree of confidence in anticipating congestion in a given region.

[0007] Predicting which specific UEs will appear in a particular region (especially one where congestion is expected) is a challenging task. Identifying future UEs in a region can be achieved by leveraging distributed data analytics rather than relying on statistics. High flow users It also involves predicting user mobility. However, in 5G networks, there is currently no mature method to effectively balance prediction accuracy, model complexity, and training management. Specifically, developing machine learning (ML) models that accurately predict user mobility requires a large amount of data for development, training, and frequent retraining. Therefore, solving this problem becomes more complex and requires additional research and development efforts. Furthermore, when congestion is predicted in a specific area, implementing mitigation actions for UEs in that area that are not expected to experience congestion becomes impractical. Summary of the Invention

[0008] This disclosure provides a simple method for determining the probability of a User Equipment (UE) moving from one or more source serving areas to a destination serving area. A Mobility Management Node (MLM) or other network node generates and maintains a probability distribution function that indicates the probability of a UE moving from one or more source serving areas to a specified destination serving area. When congestion is predicted in the destination serving area, a request can be sent to the MLM to obtain transfer probability data for the destination serving area, identifying possible source serving areas and dispersion data indicating high-traffic users in those possible source serving areas. A Policy Control Node (PCN) or other network node can use the transfer probability data and dispersion data to implement congestion mitigation measures. While not as accurate as ML prediction models, the techniques described herein are easy to implement and sufficient for many congestion-prone scenarios.

[0009] A first aspect of this disclosure includes a method, implemented by a producer network node in the core network of a wireless communication network, for providing handover probability data for congestion mitigation to a consumer network node. The method includes receiving from the consumer network node a first request for handover probability data, the handover probability data indicating the probability that a user equipment (UE) transferring to a destination service area will originate from each of one or more source service areas. The method also includes, in response to the first request, providing the consumer network node with a first response including the handover probability data or other information for accessing the handover probability data.

[0010] A second aspect of this disclosure includes a producer network node in the core network of a wireless communication network, configured to provide a consumer network node with handover probability data for congestion mitigation. The network node is configured to receive from the consumer network node a first request for handover probability data, which indicates the probability that a user equipment (UE) transferring to a destination service area will originate from each of one or more source service areas. The network node is also configured to, in response to the first request, provide the consumer network node with a first response including the handover probability data or other information for accessing the handover probability data.

[0011] A third aspect of this disclosure includes a producer network node in the core network of a wireless communication network, configured to provide a consumer network node with handover probability data for congestion mitigation. The network node includes communication circuitry configured to communicate with one or more other network nodes, and processing circuitry operatively connected to the communication circuitry. The processing circuitry is configured to receive from the consumer network node a first request for handover probability data, the handover probability data indicating the probability that a user equipment (UE) transferring to a destination service area will originate from each of the one or more source service areas. The processing circuitry is also configured to, in response to the first request, provide the consumer network node with a first response including the handover probability data or other information for accessing the handover probability data.

[0012] A fourth aspect of this disclosure includes a computer program for a producer network node. The computer program includes executable instructions that, when executed by processing circuitry in the producer network node within a communication network, cause the producer network node to perform the method according to the first aspect.

[0013] The fifth aspect of this disclosure includes a carrier containing a computer program according to the fourth aspect. The carrier is one of an electronic signal, an optical signal, a radio signal, or a non-transitory computer-readable storage medium.

[0014] A sixth aspect of this disclosure includes a congestion mitigation method implemented by a consumer network node in a wireless communication network. The method includes sending a first request to a producer network node for transfer probability data, the transfer probability data indicating the probability that a user equipment (UE) transferring to a destination service area will originate from each of one or more source service areas. The method also includes receiving, in response to the first request, a response from the producer network node including the transfer probability data or other information for accessing the transfer probability data.

[0015] A seventh aspect of this disclosure includes a consumer network node in a wireless communication network configured to perform congestion mitigation. The network node is configured to send a first request to a producer network node for transfer probability data, the transfer probability data indicating the probability that a user equipment (UE) transferring to a destination service area will originate from each of one or more source service areas. The network node is also configured to receive, in response to the first request, a response from the producer network node including the transfer probability data or other information for accessing the transfer probability data.

[0016] An eighth aspect of this disclosure includes a consumer network node in a wireless communication network configured to perform congestion mitigation. The network node includes communication circuitry configured to communicate with one or more other network nodes, and processing circuitry operatively connected to the communication circuitry. The processing circuitry is configured to send a first request to a producer network node for transfer probability data, the transfer probability data indicating the probability that a user equipment (UE) transferring to a destination service area will originate from each of the one or more source service areas. The processing circuitry is also configured to receive, in response to the first request, a response from the producer network node including the transfer probability data or other information for accessing the transfer probability data.

[0017] The ninth aspect of this disclosure includes a computer program for a consumer network node. The computer program includes executable instructions that, when executed by processing circuitry in the consumer network node within a communication network, cause the consumer network node to perform the method according to the sixth aspect.

[0018] The tenth aspect of this disclosure includes a carrier containing a computer program according to the ninth aspect. The carrier is one of an electronic signal, an optical signal, a radio signal, or a non-transitory computer-readable storage medium.

[0019] Brief description of the attached figures

[0020] Figure 1 The logical network functions in the core network of the communication network are shown.

[0021] Figure 2 This is a schematic diagram showing the transition probability function in tabular form.

[0022] Figure 3 This is a schematic diagram showing the transition probability function in graphical form.

[0023] Figure 4 This illustrates the standard procedures for congestion mitigation in the core network of a wireless communication network.

[0024] Figure 5A first exemplary process for congestion mitigation based on a transition probability function is shown.

[0025] Figure 6 A second exemplary process for congestion mitigation based on a transition probability function is shown.

[0026] Figure 7 The congestion mitigation method implemented by the producer network nodes is shown.

[0027] Figure 8 A congestion mitigation method implemented by consumer network nodes is shown.

[0028] Figure 9 An exemplary network node configured for congestion mitigation is shown. Detailed Implementation

[0029] Exemplary embodiments of this disclosure will now be described in the context of a 5G wireless communication network, with reference to the accompanying drawings. Those skilled in the art will understand that the methods and apparatus described herein are not limited to use in 5G networks, but can also be used in communication networks operating according to other standards using a service-based architecture.

[0030] Figure 1A wireless communication network 10 according to an exemplary embodiment is illustrated. The wireless communication network 10 includes a 5G Radio Access Network (RAN) 20 and a 5G core network (5GC) 30 employing a service-based architecture. RAN 20 includes one or more base stations 25 providing radio access to a UE 15 operating within the communication network 10. Base station 25 is also referred to as a gNodeB (gNB) in applicable standards. UE 15 may include a cellular phone, smartphone, tablet, laptop computer, or other electronic device with communication capabilities. 5GC 30 provides connectivity between RAN 20 and other packet data networks, such as Internet Protocol (IP) Multimedia Subsystem (IMS) or the Internet. Those skilled in the art will understand that other types of RANs besides 5G RAN 25 can also be connected to 5GC 30. For example, Evolved UMTS Terrestrial Radio Access (EUTRA) base stations in the Evolved Universal Mobile Telecommunications System (UMTS) Terrestrial Radio Access Network (EUTRAN) can also be connected to 5GC 30.

[0031] 5GC 30 includes multiple Network Functions (NFs). These NFs include a User Plane Function (UPF) 35, an Access and Mobility Management Function (AMF) 40, a Session Management Function (SMF) 45, a Policy Control Function (PCF) 50, a Unified Data Repository (UDR) 55, a Network Exposure Function (NEF) 60, a Network Repository Function (NRF) 65, a Network Data Analytics Function (NWDAF) 70, and a Charging Function (CHF) 75. Some embodiments may also include an Analytics Data Repository Function (ADRF) 80 to store historical data analysis for NWDAF 70. One or more Application Functions (AFs) 90 that provide application services may reside within or outside the core network 30.

[0032] In conventional communication networks, various NFs in the 5GC 30 (e.g., UPF 35, SMF 45, AMF 40, PCF 50, etc.) communicate with each other through predefined interfaces. Figure 1 In the service-based architecture shown, 5GC 30 uses a service model where NFs query the Network Repository Function (NRF) (65) or other NF discovery nodes to discover other NFs and communicate with each other via a web-based Application Programming Interface (API). In some deployments, UPF 35 communicates with SMF 45 using a predefined interface called the N4 interface. NFs can subscribe to receive notification services and data from other NFs. In this context, NFs that provide services or data are called service producers or producer NFs, while NFs that receive data and reports are called service consumers or consumer NFs. These NFs can be implemented as part of network nodes. Network nodes that implement producer NFs are called producer network nodes, and network nodes that implement consumer NFs are called consumer network nodes.

[0033] Figure 1 The NF shown includes a logical entity that can be implemented by one or more processors, hardware, firmware, or a combination thereof. In cloud-based networks, NFs are typically implemented as virtual machines (VMs) or containers (e.g., Kubernetes). Network 10 may include multiple instances of each NF type. NFs can also be implemented on standalone servers or dedicated servers.

[0034] UPF 35 supports the processing of user plane traffic, including packet inspection, packet routing and forwarding, traffic usage reporting, and QoS processing. UPF 35 connects to external IP networks and serves as the IP anchor for UE 15 served by UPF 35, ensuring UE 15's reachability even when moving within network 10. UPF 35 processes the data being forwarded. This processing may include packet inspection, classification, and QoS labeling of forwarded packets. UPF 35 generates traffic usage reports (which SMF 45 includes in its billing reports) and participates in policy enforcement.

[0035] AMF 40 is a network function that manages access to the 5G network and handles mobility-related functions for UE 15. Its role is similar to the Mobility Management Entity (MME) in a fourth-generation (4G) network. gNB handover is visible to AMF 40 when the UE is not in idle mode. Furthermore, AMF 40 can use other signaling elements to determine which gNB the UE 15 is attached to. AMF 40 can also expose these events through a standardized interface.

[0036] SMF 45 manages Packet Data Unit (PDU) sessions for UE 15, including the establishment, modification, and release of PDU sessions. SMF 45 selects UPF 35 to handle PDU sessions and controls UPF 35. SMF 45 receives Policy and Charging Control (PCC) rules from PCF 50 and configures UPF 35 for various data flow tasks, such as shaping, policing to provide bandwidth, and charging functions.

[0037] PCF 50 supports a unified policy framework for managing network behavior. Specifically, PCF 50 provides policy and charging control (PCC) rules to the Policy and Charging Enforcement Function (PCEF) (i.e., the SMF 50 / UPF 35 that enforces policy and charging decisions based on configured PCC rules).

[0038] UDR 55 is a data repository for storing various types of data. The stored data can include subscription data, policy data, structured data for public access, and application data. UDR 55 provides data storage and access as a service to other NFs in 5GC 30.

[0039] NWDAF 70 collects various types of network and subscriber data, performs data analysis, and provides analysis reports to other NFs. NWDAF 70 can store historical analysis reports and data in ADRF 80. Consumer NFs within 5GC 30 send subscription requests for analysis reports to NWDAF 70 using the Nnwdaf interface. The request can specify the target for the requested data (e.g., UE 15 group or NF group). NWDAF 70 collects event data from these NFs (e.g., AMF 40, SMF 45, and PCF 50) using the Event Open Service provided by other NFs. NWDAF 70 can also retrieve data from the O&M system and retrieve data related to various NFs from NRF 65. Subscriber-related data is retrieved from UDR 55 via a Unified Data Management (UDM) node (not shown). After data collection, NWDAF 70 generates analysis reports for the targets identified in the requests and sends the analysis reports to the subscribed NFs. Analysis reports can be sent periodically or in response to triggered events. In some embodiments, NWDAF 70 may be distributed, and the services provided by NWDAF 70 may be co-located with other NFs (e.g., AMF 40).

[0040] One aspect of this disclosure includes a transfer table service implemented by the AMF 40 or other mobility management node, which indicates the probability that a UE 15 will transfer from one or more source service areas to a destination service area. Examples of service areas are areas served by the gNB or tracking areas (TAs). Given a predicted congested destination service area and UEs 15 currently in adjacent areas, it is possible to estimate with a given probability which of these UEs 15 are likely to reach the predicted congested destination service area. Using this knowledge, it becomes possible to preemptively process UEs entering areas predicted to be congested.

[0041] In an exemplary embodiment, AMF 40 or other network nodes create and open a transfer table that records transfers between gNBs or other service areas and provides a transfer probability function. When congestion in the destination service area is predicted, a request can be sent to AMF 40 to obtain transfer probability data for that destination service area to identify possible source service areas and indicate the distribution of users in those possible source service areas. Using the transfer probability function, mitigation measures (or simply warnings) can be proactively applied to UEs 15 that are not currently in a gNB area that is about to become congested, without implementing a complete UE mobility prediction (ML) model. This functionality is easier to implement than an ML prediction model.

[0042] Figure 2 This diagram illustrates one representation of a transition probability function implemented as a table. Those skilled in the art will understand that a "transition probability table" is one of several different methods for implementing a transition probability function. A transition probability table can be implemented using an online hidden Markov model. Other techniques can also be used to implement the transition probability function.

[0043] exist Figure 2 In this context, the service area granularity is at the gNB service area level. As mentioned earlier, the service area granularity can be at the TA level or other granularity levels. Figure 2 The column on the left shows the destination gNBs. Each destination gNB is linked to a list of source gNBs. For each source gNB, the transfer table provides a handover count from the source gNB to the destination gNB, and the percentage of handovers from the source gNB to the total number of handovers from all source gNBs to the destination gNB. This count may include the cumulative number of handovers over a predetermined time period (e.g., 30 minutes). In other embodiments, the count may include a run count with a decay function applied. For example, the cumulative count may be a run count that decreases by a fixed percentage (e.g., 50%) after a predetermined time interval (e.g., every 10 minutes).

[0044] The method of storing the gNB transfer table is not important. For example, the data can be stored in the internal memory or external memory of the AMF 40.

[0045] Figure 3 Another representation of the same gNB transfer table is shown. In Figure 3 In this diagram, the transfer table is represented as a graph. The nodes of this graph are gNBs, and the edges represent transfers between gNBs. The edges are directed, pointing from the source gNB to the destination gNB. Each edge has a property describing the cumulative transfer count and the proportion of transfers from the source to the destination gNB to the total number of transfers to the destination gNB.

[0046] A typical implementation of the transfer table service can be achieved through a Representational State Transfer (REST) ​​application programming interface (API). Requests for transfer probability data can use any method that includes the gNB identifier (ID) of the destination gNB and a Uniform Resource Locator (URL). As an example, a request can take the form of a GET command as shown below: GET https: / / amf.example.com / services / {serviceId} / gnodebs / {gNodeBId} In this example, {serviceId} represents the identifier of the service, and {gNodeBId} represents the identifier of the gNB within that service.

[0047] The result of this operation, using JavaScript Object Notation (JSON) mode, can be as follows: { Type: "object" "characteristic":{ "destination":{ "Type": "String" Description: Identifier of the destination gNB }, "source":{ "Type": "array" "project":{ Type: "object" "characteristic":{ “id”: { "Type": "String" Description: Identifier of the source gNB }, "count":{ "Type": "Integer" "Description": "Number of UEs transferred from the source gNB to the destination gNB" }, "Proportion":{ "Type": "Number" "Description": "The percentage of UEs that transferred from the source gNB to the destination gNB out of the total number of transfers to the destination gNB". } }, "Required": ["id", "count", "proportion"] } } }, "Required": ["Destination", "Source"] This JSON schema describes a document with two main elements: "Destination" and "Source". "Destination" is a string value that passes the destination gNB ID. "Source" is an array containing all gNBs in the transfer table for the destination gNB. Each object in the array has three elements: "id": Pass a string value representing the id of the source gNB.

[0048] "Count": An integer value that transmits the number of UE 15s transferred from the source gNB identified by id to the destination gNB.

[0049] "Proportion": A floating-point value representing the proportion of the number of UEs transferred from the source gNB identified by id to the destination gNB to the total number of transfers to the destination gNB.

[0050] This pattern specifies that both the "Destination" and "Source" elements are required. Furthermore, each object within the "Source" array must have "id," "count," and "ratio" elements. Of course, this pattern is merely one example implementation of the transfer table service. For instance, the JSON pattern above could be modified to include a field describing the time range to which the count applies.

[0051] Transfer table services can be used as part of a congestion mitigation process. For comparison, Figure 4 A typical process for congestion mitigation, not based on a transfer table service, is illustrated. In this example, PCF 50 subscribes to gNB-level congestion predictions from NWDAF 70's User Data Congestion Service (S1). Those skilled in the art will understand that the granularity of the service area can alternatively be TA level or other levels. NWDAF 70 predicts congestion in gNB A and notifies clients by sending event notifications to all subscribers (S2). In this example, PCF 50 is configured to... High-traffic users Applying congestion mitigation measures, PCF 50 sends data to the distributed data service of NWDAF 70 for services provided by gNB A. High-traffic users The request (S3). NWDAF 70 uses gNBA High-traffic users The list is used to respond to the request (S4). Then, PCF 50 sends the response to the identified... High-traffic users Mitigation measures for UE 15 applications.

[0052] Figure 5The process of using the transfer table service for congestion mitigation is illustrated. PCF 50 subscribes to the NWDAF User Data Congestion Service for gNB-level congestion prediction (S1). Those skilled in the art will understand that the granularity of the service area can alternatively be TA level or other levels. NWDAF 70 predicts congestion in gNB A and notifies PCF 50 by sending an event notification to all subscribers (S2). When congestion is predicted in gNB A, PCF 50 sends a request to AMF 40 to obtain a list of source gNBs for gNB A using the transfer table service (S3). AMF 40 responds with a source list that includes a list of neighboring gNBs from which the UE may transfer to gNBA (S4). This request may include a threshold (e.g., "only include gNBs with a proportion greater than 10% for UE 15" (gNBs B, C, and D in this example). Alternatively, PCF 50 may discard or ignore gNBs with a proportion below the threshold. Similar to the previous example, PCF 50 is configured to... High-traffic users Applying congestion mitigation measures, PCF 50 sends data to the distributed data service of NWDAF 70 for services provided by gNB A. High-traffic users The request (S5). NWDAF 70 uses services provided by gNB A, B, C and D. High-traffic users The list is used to respond to the request (S6). For gNB A, this is done by sending a list to those not yet in the service area of ​​gNB A. High-traffic users Applying mitigation measures is impractical. Therefore, in obtaining... High-traffic users Following the list, PCF 50 subscribes to AMF 40 to receive information related to... High-traffic users Notification of the switching event (S7). When targeting High-traffic users one of the High-traffic users When a handover is triggered, AMF 40 sends an event notification (S8) to PCF 50. Then, when identified as High-traffic users When a UE is transferred to the service area of ​​gNB A, PCF 50 applies mitigation measures (S9).

[0053] In an alternative embodiment, NWDAF 70 can implement a transfer table service. In this alternative embodiment, NWDAF 70 subscribes to handover events from AMF 40 and maintains a transfer table. PCF 50 does not contact AMF 40, but instead sends requests for transfer probability data to the transfer table service provided by NWDAF 70.

[0054] Figure 6The process of congestion mitigation using the transfer table service implemented by NWDAF 70 is illustrated. To create the transfer table, NWDAF 70 subscribes to all UE handover events (S1) from the AMF. When a handover is triggered, the AMF 40 provides an event notification to NWDAF 70, identifying the UE, source gNB, and destination gNB. Based on these event notifications, NWDAF 70 can build and maintain the transfer table.

[0055] PCF 50 subscribes to gNB-level congestion predictions from NWDAF 70's User Data Congestion Service (S3). Those skilled in the art will understand that the granularity of the service area can alternatively be TA level or other levels. NWDAF 70 predicts congestion in gNB A and notifies PCF 50 by sending an event notification to all subscribers (S4). When congestion is predicted in gNB A, PCF 50 sends a request to AMF 40 to obtain a list of source gNBs for gNB A using the transfer table service (S5). AMF 40 responds with a source list that includes a list of neighboring gNBs from which UE 15 may transfer (S6). This request may include a threshold (e.g., "only gNBs with a proportion greater than 10% of the UE's data" (gNBs B, C, and D in this example). Alternatively, PCF 50 may discard or ignore gNBs with a proportion below the threshold. Similar to the previous example, PCF 50 is configured to... High traffic user Applying congestion mitigation measures, PCF 50 sends data to the distributed data service of NWDAF 70 for services provided by gNB A. High-traffic users The request (S7). NWDAF 70 uses services provided by gNB A, B, C and D. High-traffic users The list is used to respond to the request (S8). For gNB A, this is done by sending a list to those not yet in the service area of ​​gNB A. High-traffic users Applying mitigation measures is impractical. Therefore, in obtaining... High-traffic users Following the list, PCF 50 subscribes to AMF 40 to receive information related to... High-traffic users Notification of the switching event (S9). When targeting High-traffic users one of the High-traffic users When a handover is triggered, AMF 40 sends an event notification to PCF50 (S10). Then, when it is identified as High-traffic users When a UE is transferred to the service area of ​​gNB A, PCF50 applies mitigation measures to it (S11).

[0056] It should be noted that, Figure 5 and Figure 6 In the illustrated embodiment, some NWDAF services may co-address with AMF 40.

[0057] Figure 7 A method implemented by AMF 40, NWDAF 70, or other producer network nodes providing transfer table services is illustrated. The producer network node receives a first request from a consumer network node (e.g., PCF 50) for transfer probability data indicating the probability that a user equipment (UE) transferred to a destination service area (i.e., any UE served in a source service area) will originate from that source service area for each of one or more source service areas (block 130). In response to the first request, the producer network node provides a first response to the consumer network node, including the transfer probability data or other information for accessing the transfer probability data (block 140).

[0058] In some embodiments of method 100 (e.g., where the service is implemented by NWDAF 70), the producer network node may optionally receive a subscription request from the consumer network node for a congestion prediction of the destination service area (block 110). In response to the subscription request, the producer network node provides the consumer network node with an event notification including the congestion prediction for the destination service area (block 120).

[0059] In some embodiments of method 100 (e.g., where the service is implemented by NWDAF 70), the producer network node may optionally receive a second request for distributed data that identifies users or user groups that account for a relatively large portion of the total traffic (block 150). In response to the second request, the producer network node provides a second response including the distributed data (block 160).

[0060] In some embodiments of method 100 (e.g., where the service is implemented by NWDAF 70), the producer network node receives from a first network node a subscription request for a handover event notification involving a handover of one or more users indicated by distributed data (block 170). In response to the subscription request, the producer network node provides an event notification when a handover involving one of the one or more users indicated by distributed data is triggered (block 180).

[0061] In some embodiments of method 100, the transfer probability data includes a count of UE transfers from a corresponding source service area to a destination service area for each of one or more corresponding source service areas.

[0062] In some embodiments of method 100, the transfer probability data includes, for each of one or more corresponding source service areas, the proportion of transfers from the corresponding source service area to the total number of transfers from all corresponding source service areas to the destination service area.

[0063] In some embodiments of method 100, the first request includes an indication of at least one destination service area.

[0064] In some embodiments of method 100, the first response includes a list of corresponding source serving areas for each destination serving area. In some embodiments of method 100, the first response also includes a count of UE transfers from the corresponding source serving area to the destination serving area for each corresponding source serving area.

[0065] In some embodiments of method 100, the first response further includes, for each corresponding source service region, the proportion of the number of transfers from the corresponding source service region to the total number of transfers from all corresponding source service regions to the destination service region.

[0066] In some embodiments of method 100, the first response includes a link to a resource that can access the transition probability data.

[0067] In some embodiments of method 100, the first request is sent after it has been provided. In some embodiments of method 100, the destination service area and the corresponding source service area include the service areas of the respective base stations in the radio access network.

[0068] In some embodiments of method 100, the destination service area and the corresponding source service area include a tracking area in a wireless communication network.

[0069] Figure 8 A method implemented by PCF 50 or other consumer network nodes using a transfer table service provided by another network node (e.g., AMF 40 or NWDAF 70) is illustrated. The consumer network node sends a first request to the producer network node (e.g., AMF40 or NWDAF 70) for transfer probability data indicating the probability that a user equipment (UE) transferring to a destination service area will originate from each of one or more source service areas (block 230). In response to the first request, the consumer network node (e.g., PCF 50) receives a response from the producer network node including the transfer probability data or other information for accessing the transfer probability data (block 240).

[0070] In some embodiments of method 200, the consumer network node sends a subscription request for congestion prediction from the producer network node or a second producer network node (e.g., NWDAF 40) (block 210). In response to the subscription request, the consumer network node receives congestion predictions for the destination service area from the producer network node or the second producer network node (e.g., NWDAF 40) (block 220).

[0071] In some embodiments of method 200, the consumer network node sends a second request to the producer network node or a second producer network node for distributed data that identifies users or user groups that account for a relatively large portion of the total traffic (block 250). In response to the second request, the consumer network node receives a second response including the distributed data from the producer network node or the second producer network node (block 260).

[0072] In some embodiments of method 200, the consumer network node sends a subscription request to the producer network node for a handover event notification involving a handover of one or more users indicated by distributed data (block 270). In response to the subscription request, the consumer network node receives an event notification from the producer network node when a handover involving one of the one or more users indicated by distributed data is triggered (block 280).

[0073] In some embodiments, consumer network nodes perform congestion mitigation, for example, by applying one or more... High traffic user Apply congestion mitigation (block 290).

[0074] In some embodiments of method 200, the transfer probability data includes a count of UE transfers from a corresponding source service area to a destination service area for each of one or more corresponding source service areas.

[0075] In some embodiments of method 200, the transfer probability data includes, for each of one or more corresponding source service areas, the proportion of transfers from the corresponding source service area to the total number of transfers from all corresponding source service areas to the destination service area.

[0076] In some embodiments of method 200, the counting includes a cumulative count over a predetermined time period.

[0077] Some embodiments of method 200 also include applying a decay function to the count at predetermined time intervals.

[0078] In some embodiments of method 200, the first request includes an indication of at least one destination service area.

[0079] In some embodiments of method 200, the first response includes a list of corresponding source service areas for each destination service area.

[0080] In some embodiments of method 200, the first response further includes, for each corresponding source service area, a count of UE transfers from the corresponding source service area to the destination service area.

[0081] In some embodiments of method 200, the first response further includes, for each corresponding source service region, the proportion of the number of transfers from the corresponding source service region to the total number of transfers from all corresponding source service regions to the destination service region.

[0082] In some embodiments of method 200, the first response includes a link to a resource that can access the transition probability data.

[0083] In some embodiments of method 200, a first request is sent in response to a congestion prediction in the destination service area.

[0084] Some embodiments of method 200 also include performing network operations to alleviate congestion in the destination service area.

[0085] In some embodiments of method 200, the destination service area and the corresponding source service area include the service area of ​​the corresponding base station in the radio access network.

[0086] In some embodiments of method 200, the destination service area and the corresponding source service area include a tracking area in a wireless communication network.

[0087] The apparatus can perform any of the methods described herein by implementing any functional components, modules, units, or circuits. In one embodiment, for example, the apparatus includes a corresponding circuitry or circuit system configured to perform the steps shown in the method diagram. In this regard, the circuitry or circuit system may include circuitry dedicated to performing certain functional processing and / or one or more microprocessors combined with memory. For example, the circuit system may include one or more microprocessors or microcontrollers, as well as other digital hardware, which may include a digital signal processor (DSP), special-purpose digital logic, etc. The processing circuitry may be configured to execute program code stored in memory, which may include one or more types of memory, such as read-only memory (ROM), random access memory (RAM), cache memory, flash memory devices, optical storage devices, etc. In several embodiments, the program code stored in the memory may include program instructions for executing one or more telecommunications and / or data communication protocols, and instructions for executing one or more techniques described herein. In embodiments employing memory, the memory stores program code that, when executed by one or more processors, performs the techniques described herein.

[0088] Figure 9 The main functional components of another exemplary network node 300 are shown, which can be configured to perform Figure 7 and Figure 8Any one of methods 100 and 200 shown. Network node 300 includes communication circuitry 310, processing circuitry 320, and memory 330.

[0089] The communication circuit 310 includes a network interface circuit for communicating with other core network nodes via a communication network (such as an Internet Protocol (IP) network).

[0090] The processing circuit 320 controls the overall operation of the network node 300 and is configured to execute individual operations. Figure 7 and Figure 8 One or more of methods 100 and 200 are shown. Processing circuitry 320 may include one or more microprocessors, hardware, firmware, or a combination thereof. The processing circuitry can be configured by software to execute these methods respectively. Figure 7 and Figure 8 Methods 100 and 200 are shown.

[0091] Memory 330 includes volatile and non-volatile memory for storing computer program code and data required for the operation of processing circuitry 320. Memory 330 may include any tangible, non-transitory computer-readable storage medium for storing data, including electronic, magnetic, optical, electromagnetic, or semiconductor data storage. Memory 330 stores computer program 340, which includes executable instructions that configure processing circuitry 320 to implement… Figure 7 and Figure 8 One or more of methods 100 and 200 shown. In this respect, the computer program may include one or more code modules corresponding to the aforementioned components or units. Typically, computer program instructions and configuration information are stored in non-volatile memory, such as ROM, erasable programmable read-only memory (EPROM), or flash memory. Temporary data generated during operation may be stored in volatile memory, such as random access memory (RAM). In some embodiments, the computer program 340 for configuring the processing circuitry 320 as described herein may be stored in removable memory, such as a portable optical disc, portable digital video disc, or other removable medium. The computer program 340 may also be embodied in a carrier, such as an electronic signal, optical signal, radio signal, or computer-readable storage medium.

[0092] Those skilled in the art will also understand that the embodiments herein also include corresponding computer programs. The computer program includes instructions that, when executed on at least one processor of the device, cause the device to perform any of the corresponding processes described above. In this respect, the computer program may include one or more code modules corresponding to the aforementioned components or units.

[0093] The embodiments also include a carrier containing such a computer program. The carrier may include one of electronic signals, optical signals, radio signals, or a computer-readable storage medium.

[0094] In this regard, embodiments herein also include a computer program product stored on a non-transitory computer-readable (storage or recording) medium, the computer program product including instructions that, when executed by a processor of the device, cause the device to perform as described above.

[0095] The embodiments also include a computer program product comprising program code portions for performing the steps of any of the embodiments herein when the computer program product is executed by a computing device. The computer program product may be stored on a computer-readable recording medium.

Claims

1. A method (100) implemented by producer network nodes (40, 70, 300) in the core network (30) of a wireless communication network (10), comprising: Receive (130) a first request for transfer probability data from consumer network nodes (50, 300), the transfer probability data indicating the probability that a user equipment (UE) transferring to a destination service area will come from each of the source service areas for one or more source service areas; and In response to the first request, the consumer network node (50, 300) is provided with (140) a first response including the transition probability data or other information for accessing the transition probability data.

2. The method (100) according to claim 1, wherein, The transfer probability data includes a count of UE transfers from the corresponding source service area to the destination service area for each of one or more corresponding source service areas.

3. The method (100) according to claim 1 or 2, wherein, The transfer probability data includes, for each of one or more corresponding source service regions, the proportion of transfers from the corresponding source service region to the total number of transfers from all corresponding source service regions to the destination service region.

4. The method (100) according to any one of claims 1 to 3, wherein, The count includes the cumulative count over a predetermined time period.

5. The method (100) according to any one of claims 1 to 3 further includes applying a decay function to the count at predetermined time intervals.

6. The method (100) according to any one of claims 1 to 5, wherein, The first request includes an indication of at least one destination service area.

7. The method (100) according to claim 6, wherein, The first response includes a list of corresponding source service regions for each destination service region.

8. The method (100) according to claim 7, wherein, The first response also includes, for each corresponding source service area, a count of UE transfers from the corresponding source service area to the destination service area.

9. The method (100) according to claim 7 or 8, wherein, The first response also includes, for each corresponding source service region, the proportion of transfers from the corresponding source service region to the total number of transfers from all corresponding source service regions to the destination service region.

10. The method (100) according to claim 6, wherein, The first response includes a link to a resource that provides access to the transition probability data.

11. The method (100) according to any one of claims 1 to 10, further comprising: Receive (150) a second request for distributed data from the consumer network nodes (50, 300), the distributed data identifying users or user groups that account for a relatively large portion of the total traffic; and In response to the second request, a second response including the distributed data is provided (160) to the consumer network nodes (50, 300).

12. The method (100) according to any one of claims 1 to 11, further comprising: Receive (170) a subscription request from the consumer network node (50, 300), the subscription request being for a handover event notification involving a handover of one or more users indicated by the distributed data; and In response to the subscription request, when a switch involving one of one or more users indicated by the distributed data is triggered, an event notification (180) is provided to the consumer network nodes (50, 300).

13. The method (100) according to any one of claims 1 to 12, further comprising: Receive (110) subscription requests for congestion prediction from the consumer network nodes (50, 300); and In response to the subscription request, the consumer network nodes (50, 300) are provided with (120) a prediction of congestion in the destination service area.

14. The method (100) according to claim 13, wherein, The first request is sent after providing a prediction of congestion in the destination service area.

15. The method (100) according to any one of claims 1 to 14, wherein, The destination service area and the corresponding source service area include the service areas of the corresponding base stations in the radio access network.

16. The method (100) according to any one of claims 1 to 14, wherein, The destination service area and the corresponding source service area include the tracking area in the wireless communication network (10).

17. A method (200) implemented by consumer network nodes (50, 300) in the core network (30) of a wireless communication network (910), comprising: Send (230) a first request for transfer probability data to the producer network nodes (40, 70, 300), the transfer probability data indicating the probability that a user equipment (UE) transferring to a destination service area will come from the source service area for each of one or more source service areas; and In response to the first request, a response including the transition probability data or other information for accessing the transition probability data is received (240) from the producer network nodes (40, 70, 300).

18. The method (200) according to claim 17, wherein, The transfer probability data includes a count of UE transfers from the corresponding source service area to the destination service area for each of the one or more corresponding source service areas.

19. The method (200) according to claim 17 or 18, wherein, The transfer probability data includes, for each of one or more corresponding source service regions, the proportion of transfers from the corresponding source service region to the total number of transfers from all corresponding source service regions to the destination service region.

20. The method (200) according to any one of claims 17 to 19, wherein, The count includes the cumulative count over a predetermined time period.

21. The method (200) according to any one of claims 17 to 20, further comprising applying a decay function to the count at predetermined time intervals.

22. The method (200) according to any one of claims 17 to 21, wherein, The first request includes an indication of at least one destination service area.

23. The method (200) according to claim 22, wherein, The first response includes a list of corresponding source service regions for each destination service region.

24. The method (200) according to claim 23, wherein, The first response also includes, for each corresponding source service area, a count of UE transfers from the corresponding source service area to the destination service area.

25. The method (200) according to claim 23 or 24, wherein, The first response also includes, for each corresponding source service region, the proportion of transfers from the corresponding source service region to the total number of transfers from all corresponding source service regions to the destination service region.

26. The method (200) according to claim 22, wherein, The first response includes a link to a resource that provides access to the transition probability data.

27. The method (200) according to any one of claims 17 to 26, further comprising: Send (250) a second request for distributed data to the producer network node (40, 70, 300) or the second producer network node, the distributed data identifying users or user groups that account for a relatively large portion of the total traffic; and In response to the second request, a second response including the distributed data is received (260) from the producer network node (40, 70, 300) or the second producer network node.

28. The method (200) according to any one of claims 17 to 27, further comprising: Send a (270) subscription request to the producer network node (40, 70, 300) or the second producer network node (40, 70, 300), the subscription request being for a switching event notification involving a switching of one or more users indicated by the distributed data; and In response to the subscription request, when a switch involving one of the users indicated by the distributed data is triggered, an event notification (280) is received from the producer network node (40, 70, 300) or a second producer network node.

29. The method (200) according to any one of claims 17 to 28, further comprising: Send (210) a subscription request for congestion prediction from the producer network nodes (40, 70, 300); and In response to the subscription request, receive (220) a congestion prediction in the destination service area.

30. The method (200) according to claim 29, wherein, The first request is sent in response to a congestion prediction in the destination service area.

31. The method (200) according to any one of claims 17 to 30 further includes performing network operations to alleviate congestion in the destination service area.

32. The method (200) according to any one of claims 17 to 31, wherein, The destination service area and the corresponding source service area include the service areas of the corresponding base stations in the radio access network.

33. The method (200) according to any one of claims 17 to 31, wherein, The destination service area and the corresponding source service area include the tracking area in the wireless communication network.

34. A producer network node (40, 70, 300) in a wireless communication network, said producer network node being configured to: Receive a first request from a consumer network node for transfer probability data, the transfer probability data indicating the probability that a user equipment (UE) transferring to a destination service area will originate from each of one or more source service areas; In response to the first request, a first response is provided to the consumer network node, including the transition probability data or other information for accessing the transition probability data.

35. The producer network nodes (40, 70, 300) according to claim 34, wherein, The network node is also configured to perform the method of any one of claims 2 to 16.

36. A producer network node (300) in a wireless communication network, the producer network node comprising: A communication circuit (310) is configured to communicate with one or more other network nodes; Processing circuitry (320), operably connected to the communication circuitry and configured to: Receive a first request from a consumer network node for transfer probability data, the transfer probability data indicating the probability that a user equipment (UE) transferring to a destination service area will originate from each of one or more source service areas; In response to the first request, a first response is provided to the consumer network node, including the transition probability data or other information for accessing the transition probability data.

37. The producer network node (300) according to claim 36, wherein, The processing circuit is also configured to perform the method of any one of claims 2 to 16.

38. A computer program (340) comprising executable instructions, which, when executed by processing circuitry in a producer network node (40, 70, 300) in a wireless communication network, cause the producer network node to perform the method of any one of claims 1 to 16.

39. A carrier comprising the computer program (340) of claim 38, wherein, The carrier is one of electronic signals, optical signals, radio signals, or computer-readable storage media.

40. A non-transitory computer-readable storage medium (330) comprising a computer program (340) including executable instructions that, when executed by processing circuitry in a producer network node (40, 70, 300) in a wireless communication network, cause the producer network node to perform the method of any one of claims 1 to 16.

41. A consumer network node (50, 300) in a wireless communication network, wherein the producer network node is configured to: Send a first request to the producer network node for transfer probability data, the transfer probability data indicating the probability that a user equipment (UE) transferring to a destination service area will originate from each of one or more source service areas; and In response to the first request, a response is received from the producer network node including the transition probability data or other information for accessing the transition probability data.

42. The consumer network node (50, 300) according to claim 41, wherein, The network node is also configured to perform the method of any one of claims 18 to 33.

43. A consumer network node (300) operable to manage energy consumption in a wireless communication network, the network node comprising: A communication circuit (310) is configured to communicate with one or more other network nodes; Processing circuitry (320), operably connected to the communication circuitry and configured to: Send a first request to the producer network node for transfer probability data, the transfer probability data indicating the probability that a user equipment (UE) transferring to a destination service area will originate from each of the one or more source service areas; and In response to the first request, a response is received from the producer network node including the transition probability data or other information for accessing the transition probability data.

44. The consumer network node (300) according to claim 43, wherein, The network node is also configured to perform the method of any one of claims 18 to 33.

45. A computer program (340) comprising executable instructions, which, when executed by processing circuitry in a consumer network node (50, 300) in a wireless communication network, cause the consumer network node to perform the method of any one of claims 17 to 33.

46. ​​A carrier comprising the computer program (340) of claim 45, wherein, The carrier is one of electronic signals, optical signals, radio signals, or computer-readable storage media.

47. A non-transitory computer-readable storage medium (330) comprising a computer program (340) including executable instructions that, when executed by processing circuitry in a consumer network node (50, 300) in a wireless communication network, cause the consumer network node to perform the method of any one of claims 17 to 33.

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