RAN nodes, user equipment, and methods

Abstract

Provided is a Radio Access Network (RAN) node (2) wherein a control unit (102) is configured to cause a communication unit (101) to transmit a first message to a RAN node (3). The first message includes information related to a prediction value with respect to a parameter pertaining to the load of a first cell in the RAN node (2).

Description

Technical Field

[0001] The present disclosure relates to a RAN node and a method.

Background Art

[0002] In 3GPP (Registered Trademark) (3rd Generation Partnership Project), communication between adjacent RAN (Radio Access Network) nodes that manage cells, such as HO (Handover), is defined. For example, Non-Patent Document 1 defines the signaling procedures of the radio network layer of the control plane between NG-RAN nodes in NG-RAN (Next Generation-Radio Access Network).

Prior Art Documents

Non-Patent Documents

[0003]

Non-Patent Document 1

Non-Patent Document 2

Non-Patent Document 3

[0004] One of the purposes of this disclosure is to provide a RAN node and method that contribute to collecting information useful for the RAN node to provide cells. It should be noted that this purpose is only one of several purposes that the various embodiments disclosed herein seek to achieve. Other purposes or problems and novel features will be revealed in the description herein or in the accompanying drawings. [Means for solving the problem]

[0005] A radio access network (RAN) node according to the first embodiment is: Memory and A processor coupled to the aforementioned memory, Equipped with a transceiver, The processor is configured to cause the transceiver to send a first message to another RAN node. The first message includes information relating to predicted values ​​for parameters concerning the load of the RAN node cells.

[0006] A radio access network (RAN) node according to the second embodiment is: Memory and A processor coupled to the aforementioned memory, Equipped with a transceiver, The processor is configured to cause the transceiver to receive a first message transmitted from another RAN node. The first message includes information regarding predicted values ​​for parameters relating to the load of the cells of the other RAN node.

[0007] The method according to the third aspect is a method performed by a radio access network (RAN) node, This includes sending the first message to other RAN nodes, The first message includes information related to a predicted value of a parameter regarding the load of a cell of the RAN node.

[0008] A method according to a fourth aspect is a method executed by a radio access network (RAN) node, comprising: receiving a first message transmitted from another RAN node, where the first message includes information related to a predicted value of a parameter regarding the load of a cell of the other RAN node.

Advantages of the Invention

[0009] According to the present disclosure, it is possible to provide a RAN node and a method that contribute to collecting information useful for the RAN node to provide a cell.

Brief Description of the Drawings

[0010] [Figure 1] It is a diagram showing a configuration example of a communication system according to a first embodiment. [Figure 2] It is a diagram showing a configuration example of a RAN node. [Figure 3] It is a diagram showing an operation example of a communication system according to a first embodiment. [Figure 4] It is a diagram showing an operation example of a communication system according to a second embodiment. [Figure 5] It is a diagram showing a configuration example of a communication system according to a third embodiment. [Figure 6] It is a diagram showing an operation example of a communication system according to a third embodiment. [Figure 7A] It is a diagram for explaining an example of time-series data of information related to a predicted value of a load parameter. [Figure 7B] It is a diagram for explaining another example of time-series data of information related to a predicted value of a load parameter. [Figure 8] It is a diagram showing a Resource Status Reporting Initiation procedure. [Figure 9] FIG. showing another example of time-series data of information related to predicted values of load parameters. [Figure 10] FIG. showing the procedure of Resource Status Reporting. [Figure 11] FIG. showing the PREDICTIONS Reporting Initiation procedure. [Figure 12] FIG. showing the procedure of PREDICTIONS Reporting. [Figure 13] FIG. showing an example of the hardware configuration of a RAN node. [Figure 14A] FIG. showing an example of the configuration of a RESOURCE STATUS REQUEST message. [Figure 14B] FIG. showing an example of the configuration of a RESOURCE STATUS REQUEST message (continuation of FIG. 14A). [Figure 14C] FIG. showing an example of the configuration of a RESOURCE STATUS REQUEST message (continuation of FIG. 14B). [Figure 15] FIG. showing an example of the configuration of a RESOURCE STATUS UPDATE message. [Figure 16A] FIG. showing an example of the configuration of a Radio Resource Status IE. [Figure 16B] FIG. showing an example of the configuration of a Radio Resource Status IE (continuation of FIG. 16A). [Figure 16C] FIG. showing an example of the configuration of a Radio Resource Status IE (continuation of FIG. 16B). [Figure 16D] FIG. showing an example of the configuration of a Radio Resource Status IE (continuation of FIG. 16C). [Figure 16E] FIG. showing an example of the configuration of a Radio Resource Status IE (continuation of FIG. 16D). [Figure 17]This figure shows an example configuration for a Composite Available Capacity Group IE. [Figure 18] This figure shows an example configuration for Composite Available Capacity IE. [Figure 19] This figure shows an example of the configuration of CellCapacity Class Value IE. [Figure 20] This figure shows an example configuration for Capacity Value IE. [Figure 21] This figure shows an example configuration for Slice Available Capacity IE. [Figure 22A] This figure shows an example of the structure of a PREDICTIONS REQUEST message. [Figure 22B] This is a diagram (a continuation of Figure 22A) showing an example of the structure of a PREDICTIONS REQUEST message. [Figure 23] This diagram shows an example of the structure of a PREDICTIONS RESPONSE message. [Figure 24] This diagram shows an example of the structure of a PREDICTIONS UPDATE message. [Figure 25A] This diagram shows an example configuration for Radio Resource Load Predictions IE. [Figure 25B] This is a diagram (a continuation of Figure 25A) showing an example configuration of Radio Resource Load Predictions IE. [Figure 26] This figure shows an example configuration for the Load Prediction type. [Figure 27] This figure shows an example of the configuration of a prediction time series. [Modes for carrying out the invention]

[0011] Embodiments of the present disclosure will be described below with reference to the drawings. Note that the following description and drawings have been omitted and simplified as appropriate for clarity of explanation. Furthermore, in the following drawings, the same elements are denoted by the same reference numerals, and redundant explanations have been omitted where necessary. Also, unless otherwise specified, in this disclosure, "at least one of A or B (A / B)" may mean any one of A or B, or both A and B. Similarly, when "at least one" is used for three or more elements, it may mean any one of these elements, or any multiple elements (including all elements).

[0012] <First Embodiment> <Example of a communication system configuration> Figure 1 shows an example configuration of a communication system according to the first embodiment. Communication system 1 is, for example, a fifth-generation mobile communication system (5G system). The 5G System is NR (New Radio Access), which is fifth-generation radio access technology. Note that communication system 1 is not limited to a fifth-generation mobile communication system, but may be a different mobile communication system such as an LTE (Long Term Evolution) system, an LTE-Advanced system, or a sixth-generation mobile communication system. Communication system 1 may also be another wireless communication system that includes at least a radio access network (RAN) node and user equipment (UE). Communication system 1 may also be a communication system in which an ng-eNB (LTE evolved NodeB), which is a base station in LTE (Long Term Evolution), connects to a 5G core network (5GC) via an NG interface.

[0013] Communication system 1 includes RAN node 2 and RAN node 3. Although only two RAN nodes are shown in Figure 1, communication system 1 may have three or more RAN nodes.

[0014] RAN Node 2 and RAN Node 3 may also be gNBs. A gNB is a node that terminates the NR user plane and control plane protocols for the UE and connects to 5GC via the NG interface. RAN Node 2 and RAN Node 3 may also be ng-eNBs. An ng-eNB is a node that terminates the E-UTRA (Evolved Universal Terrestrial Radio Access) user plane and control plane protocols for the UE and connects to 5GC via the NG interface. RAN Node 2 and RAN Node 3 may also be CUs (Central Units) in a C-RAN (Cloud RAN) configuration, or gNB-CUs. A gNB-CU is a logical node that hosts the gNB's RRC (Radio Resource Control) protocol, SDAP (Service Data Adaptation Protocol) protocol, and PDCP (Packet Data Convergence Protocol) protocol. Alternatively, a gNB-CU is a logical node that hosts the en-gNB's RRC protocol and PDCP protocol, which control the operation of one or more gNB-DUs (gNB-Distributed Units). gNB-CU terminates the F1 interface that connects to gNB-DU. RAN nodes 2 and 3 may be CP (Control Plane) Units or gNB-CU-CP (gNB-CU-Control Plane). gNB-CU-CP is a logical node that hosts the control plane portion of the RRC protocol and the gNB-CU PDCP protocol for en-gNB or gNB. gNB-CU-CP terminates the E1 interface that connects to gNB-CU-UP (gNB-CU-User Plane) and the F1-C interface that connects to gNB-DU. gNB-CU-UP is a logical node that hosts the user plane portion of the gNB-CU PDCP protocol for en-gNB. gNB-CU-UP terminates the E1 interface that connects to gNB-CU-CP and the F1-U interface that connects to gNB-DU.

[0015] Note that RAN Node 2 and RAN Node 3 may be eNBs or eNB-CUs. Also, RAN Node 2 and RAN Node 3 may be EUTRAN (Evolved Universal Mobile Telecommunications System (UMTS) Terrestrial Radio Access Network) nodes or NG-RAN (Next Generation Radio Access Network) nodes. EUTRAN nodes may be eNBs or en-gNBs. NG-RAN nodes may be gNBs or ng-eNBs. en-gNBs provide protocol termination for the NR user plane and control plane to the UE and operate as secondary nodes in EN-DC (NR Dual Connectivity).

[0016] RAN node 2 and RAN node 3 establish an inter-node interface and communicate with each other via this interface. The inter-node interface may be an Xn interface (network interface between NG-RAN nodes), an X2 interface, or any other inter-node interface.

[0017] In Figure 1, RAN node 2 serves at least one cell 4-1 (the first cell). RAN node 2 operates cell 4-1, connects to and communicates with the UE located in cell 4-1. RAN node 3 serves at least one cell 4-2 (the second cell). RAN node 3 operates cell 4-2, connects to and communicates with the UE located in cell 4-2. Here, cells 4-1 and 4-2 are adjacent. Being adjacent to cell 4-2 may mean that cells 4-1 and 4-2 are touching each other, or that a portion of cell 4-1 overlaps with cell 4-2.

[0018] Figure 2 shows an example of a RAN node configuration. In Figure 2, RAN node 2 and RAN node 3 are collectively referred to as RAN node 100. RAN node 100 comprises a communication unit 101 and a control unit 102. The communication unit 101 and control unit 102 may be software or modules whose processing is executed by a processor executing a program stored in memory. Alternatively, the communication unit 101 and control unit 102 may be hardware such as circuits or chips.

[0019] The communication unit 101 connects to and communicates with other RAN nodes and core network nodes included in the access network. The communication unit 101 also connects to and communicates with the UE. More specifically, the communication unit 101 receives various information from other RAN nodes, core network nodes, and UEs. Furthermore, the communication unit 101 transmits various information to other RAN nodes, core network nodes, and UEs.

[0020] The control unit 102 executes various processes of the RAN node 100 by reading and executing various information and programs stored in memory. The control unit 102 processes according to any or all of the setting information, such as various information elements (IE), various fields, and various conditions, contained in the message received by the communication unit 101. The control unit 102 is configured to execute processing of multiple layers. These multiple layers may include the Physical layer, MAC (Media Access Control) layer, RLC (Radio Link Control) layer, PDCP layer, RRC layer, and NAS (Non Access Stratum) layer.

[0021] The example communication system configuration shown above is common to both the first and second embodiments. Furthermore, RAN node 2 is a collective term for RAN nodes 2A and 2B in both the first and second embodiments, and RAN node 3 is a collective term for RAN nodes 3A and 3B in both the first and second embodiments. The first and second embodiments describe different operations performed by different RAN nodes, respectively.

[0022] <Example of communication system operation> Figure 3 shows an example of the operation of the communication system according to the first embodiment. The operation example of the communication system 1 will be described below using Figure 3.

[0023] In step S1, RAN node 2A sends a first message to RAN node 3A. The first message contains information related to predicted values ​​for load parameters of cell 4-1. "Load parameters" are parameters that can serve as indicators of the load of cell 4-1. "Predicted values ​​for load parameters" means values ​​for load parameters that are not measured values. "Information related to predicted values" may include predicted values ​​for each of multiple timings. For example, "predicted values ​​for load parameters" may include predicted values ​​for load parameters at the time the prediction is executed, predicted values ​​for load parameters at timings after that time, or both. In the following, "load parameters" may be referred to as "load parameters".

[0024] Furthermore, for example, “information related to the predicted value” may include the predicted value and the prediction accuracy of the predicted value. Also, for example, “information related to the predicted value” may include predicted values ​​assuming that the number of active user equipment (UEs) in the domain related to the cell load parameter (e.g., cell, beam, slice, or any combination thereof) does not change during the prediction period, predicted values ​​that take into account that the number of active UEs in the domain related to the cell load parameter changes during the prediction period, or both.

[0025] Then, RAN node 3A receives the first message sent from RAN node 2A. As will be explained in detail later, the first message is not particularly limited, but may be, for example, a Resource Status Update message from the Resource Status Reporting procedure, or a message from a new procedure (for example, a Predictions Update message from the Predictions reporting procedure).

[0026] As described above, according to the first embodiment, RAN node 2A sends a first message to RAN node 3A. The first message includes information related to predicted values ​​for the load parameters of cell 4-1. This allows RAN node 3A to obtain information about the load parameters at a timing closer to the timing used for processing than the timing of the measured values. As a result, the accuracy of processing by RAN node 3A can be improved. In other words, RAN node 2A contributes to collecting information that is useful for RAN node 3A to provide the cell.

[0027] <Second Embodiment> Figure 4 shows an example of the operation of the communication system according to the second embodiment. The operation example of the communication system 1 in the second embodiment will be described below using Figure 4.

[0028] In step S2, RAN node 3B sends a second message to RAN node 2B. The second message contains information, for example, regarding a request for information related to the predicted values ​​(a request for a report of information related to the predicted values). Hereafter, the "request for information related to the predicted values" may simply be referred to as the "request for the predicted values." For example, the "request for the predicted values" may be made for each combination of load parameters and prediction types. For example, the second message may have a bit field prepared for each combination of load parameters and prediction types, and depending on the bit value included in that bit field, it may indicate whether the predicted value for the combination corresponding to that bit field is requested or not. For example, if the bit value of that bit field = "1", the predicted value for the combination corresponding to that bit field is requested. On the other hand, if the bit value of that bit field = "0", the predicted value for the combination corresponding to that bit field is not requested.

[0029] Furthermore, for example, the second message may include information regarding the reporting cycle of the predicted value. "Reporting cycle of the predicted value" means, for example, the time interval between the transmission timings of two first messages containing the predicted value, when the predicted value is repeatedly transmitted as included in the first message.

[0030] Furthermore, for example, the second message may include information about the prediction granularity related to the timing interval of the predicted values. "Prediction granularity" means the time interval between the timings corresponding to each pair of predicted values ​​when the first message contains multiple predicted values.

[0031] Then, RAN node 2B receives the second message sent from RAN node 3B. In response to the second message's request for the transmission of predicted values, RAN node 2B sends a first message to RAN node 3B containing information related to the predicted values ​​for the load parameters of cell 4-1. As will be explained in detail later, the second message is not particularly limited, but may be, for example, the RESOURCE STATUS REQUEST message defined in section 9.1.3.18 of Non-Patent Literature 1, or a message for a new procedure (for example, the Predictions Request message for the Predictions reporting initiation procedure).

[0032] As described above, according to the second embodiment, RAN node 3B sends a second message to RAN node 3A. The second message includes information regarding a request to send predicted values. Therefore, RAN node 3B can cause RAN node 3A to send information related to load parameters at a timing closer to the timing used for processing than the timing of measured values. As a result, RAN node 3B can obtain information related to load parameters at a timing closer to the timing used for processing than the timing of measured values. This improves the accuracy of processing by RAN node 3B. In other words, RAN nodes 2B and RAN node 3B contribute to collecting information useful for RAN node 3B to provide cells.

[0033] <Third Embodiment> In the third embodiment, specific examples of the communication systems shown in the first and second embodiments will be described.

[0034] <Example of a communication system configuration> Figure 5 shows an example of the configuration of a communication system according to the third embodiment. The communication system 10 is, for example, a 5G system and includes RAN nodes 20 and 30 which are gNBs or gNB-CUs.

[0035] In Figure 5, RAN node 20 provides cells 41-43. Specifically, RAN node 20 operates cells 41-43, connects to and communicates with the UEs located in cells 41-43. In this example, RAN node 20 is connected to UE 51 in cell 43. Also in Figure 5, RAN node 30 provides cells 44-46. Specifically, RAN node 30 operates cells 44-46, connects to and communicates with the UEs located in cells 44-46. RAN nodes 20 and 30 establish an inter-node Xn interface and communicate with each other via this interface. For the sake of simplicity, it is explained here that RAN nodes 20 and 30 each operate three cells, but the number of cells operated by each RAN node is not limited to this.

[0036] In Figure 5, cell 43 provided by RAN node 20 is adjacent to cell 44 provided by RAN node 30. Hereafter, cells 43 and 44 may be referred to as "neighbor cells." Here, "neighbor cells" refers to two or more cells that have at least partially overlapping coverage areas. Similarly, two or more RAN nodes that have neighbor cells are called "neighbor RAN nodes." For example, RAN nodes 20 and 30 are neighbor RAN nodes. On the other hand, cells 41 and 42 of RAN node 20 are not adjacent to any cells of RAN node 30. Also, cells 45 and 46 of RAN node 30 are not adjacent to any cells of RAN node 20. For this reason, below, cells 41 and 42 may be referred to as "internal cells" of RAN node 20, and cells 45 and 46 may be referred to as "internal cells" of RAN node 30.

[0037] Furthermore, RAN node 20 is an AI-enabled RAN node (RAN AI / ML node). RAN node 20 may also be referred to as a RAN node equipped with AI functionality, or a RAN node with AI functionality. In the third embodiment, RAN node 20 is referred to as an AI-enhanced RAN node. RAN node 20 is equipped with AI functionality that performs communication control based on information received from RAN node 30 and other devices (other network elements), including UEs such as UE51. In the third embodiment, machine learning (ML) is provided as an example of AI functionality. In this example, the AI / ML functionality performs the process of "predicting values ​​related to load parameters," but the processes performed are not limited to this.

[0038] In this disclosure, "AI-enabled RAN node," "RAN node equipped with AI functionality," and "RAN node with AI functionality" refer to a RAN node that uses an AI / ML model to perform communication control based on information received from other devices (other network elements). For example, RAN node 20 may operate as an AI-equipped RAN node by communicating with a RAN intelligence device (not shown) and using an AI / ML model held by the RAN intelligence device. Alternatively, RAN node 20 may operate as an AI-equipped RAN node by having the functionality of a RAN intelligence device and using an AI / ML model held by the RAN intelligence device. Alternatively, RAN node 20 may operate as an AI-equipped RAN node by acquiring an AI / ML model from a RAN intelligence device and using the said AI / ML model.

[0039] A RAN intelligence device is, for example, a control device responsible for making the RAN intelligent and a control device that controls RAN communication. A RAN intelligence device may also be, for example, a RIC (RAN Intelligent Controller) as defined in O-RAN (Open-RAN). A RAN intelligence device performs tasks such as policy management, analysis of various RAN information, AI-based function management, load balancing per UE, wireless resource management, QoS (Quality of Service) management, and mobility management such as handover control.

[0040] An example configuration of RAN nodes 20 and 30 is shown in Figure 2. Here, if RAN node 100 operates as RAN node 20 and the RAN intelligence device is located outside of RAN node 20, the communication unit 101 connects to the RAN intelligence device and communicates with it. In this case, the communication unit 101 communicates with the RAN intelligence device, and the control unit 102 may make the AI / ML model held by the RAN intelligence device available for use. Alternatively, the communication unit 101 may communicate with the RAN intelligence device and acquire the AI / ML model held by the RAN intelligence device.

[0041] If RAN node 100 is RAN node 20, the control unit 102 may use an AI / ML model to control the RAN communication based on the information received by the communication unit 101. Specifically, the control unit 102 may input the information received by the communication unit 101 into the AI / ML model and output various information related to RAN communication control and / or various information related to UE communication control. The control unit 102 may control the RAN and UE by transmitting such various information to the RAN node and UE. The control unit 102 may also train the AI / ML model using machine learning based on the information received by the communication unit 101. In this disclosure, "learning," "training," and "training" mean automatically adjusting the parameters of the AI / ML model and building the model.

[0042] In the third embodiment, a deployment scenario is provided in which the AI ​​functionality on the RAN node serves only one gNB or gNB-CU, thereby providing a fully distributed autonomous solution. However, the AI ​​functionality on the RAN node may serve multiple gNBs or gNB-CUs.

[0043] Furthermore, the CN (Core Network) node 60 in Figure 5 is the NWDAF (Network Data Analytic Function) in this example. The CN node 60 has the function of collecting and analyzing various data acquired on the network in 5GC. In addition, the OAM (Operations, Administration and Management) device 70 has the operation and management function of the communication system 10.

[0044] <Example of communication system operation> Figure 6 is a diagram showing an example of the operation of the communication system according to the third embodiment. The outline of the processes performed by the communication system 10 will be described below with reference to Figure 6. In this embodiment, it is assumed that the RAN node 20 knows the adjacent RAN node 30, and that RAN node 20, RAN node 30, CN node 60, and OAM device 70 have established inter-node interfaces with each other. The order of the steps shown below is not limited unless otherwise specified. Furthermore, the presence or absence of each step, or the presence or absence of detailed processing in each step, can be changed as appropriate.

[0045] (Step S1001) RAN node 20 obtains various information from UEs (e.g., UE51) located in the cells provided by RAN node 20.

[0046] The information obtained from the UE (e.g., UE51) includes some or all of the following information: • Information regarding the location of the UE (Union Engine). • Information regarding the required quality of service for the UE (UE QoS requirements) • UE traffic information: For example, average traffic rate, or more detailed information about the traffic (such as information about the next packet arrival). • Information regarding UE radio measurements: For example, quality information measured for the serving cell where the UE is located, adjacent cells, or both. The quality information may include at least one of RSRP, RSRQ, and SINR. • Information about inactive UEs

[0047] (Step S1002) RAN node 20 acquires various information from the neighboring RAN node 30.

[0048] "Information obtained from the adjacent RAN node 30" includes, for example, some or all of the following information:

[0049] • Load information (also called Load metrics) for the adjacent RAN node 30: Load information may indicate traffic, or it may be information related to traffic. Load information may indicate bitrate, or it may be information related to bitrate. For example, load information may indicate GBR (Guaranteed Bit Rate) or non-GBR for at least one of DL (Downlink) / UL (Uplink). Load information may also indicate resource block usage, or it may be information related to such usage. For example, load information may indicate total PRB (Physical Resource Block) usage. Specifically, load information may indicate at least one of the following: At least one of the following usages of GBR (Guaranteed Bit Rate), non-GBR, or total PRB (Physical Resource Block) for at least one of DL (Downlink) / UL (Uplink) in each cell or beam provided by RAN node 30. At least one of the DL / UL amounts per slice in each cell, either GBR, non-GBR, or total PRB usage. Furthermore, the load information may also include individual load information for at least one of NUL (Normal UL) or SUL (Supplementary UL).

[0050] • Information related to handover performance with RAN node 30: This is information regarding the handover performance between cells in RAN node 20 and cells in the adjacent RAN node 30.

[0051] • Information about UEs moving toward this RAN node: This is information about UEs located in a cell of the adjacent RAN node 30 that are moving toward RAN node 20.

[0052] Furthermore, if RAN node 30 is also an AI-enabled RAN node, the information obtained from the adjacent RAN node 30 may include "information related to the predicted values ​​of the load parameters of the adjacent RAN node 30's cells."

[0053] In this disclosure, "slice" refers to a network slice provided in the core network (e.g., 5GC), as defined, for example, in section 16.3.1 of Non-Patent Document 6. More specifically, network slicing can be implemented in the NG-RAN of NRs connected to 5GC and E-UTRAs connected to 5GC. A slice consists of a RAN portion and a CN portion, and slice support is based on the principle that traffic for different slices is handled by different PDU sessions. The network can implement different slices by providing scheduling and different L1 / L2 configurations.

[0054] Each slice is uniquely identified by Single Network Slice Selection Assistance Information (S-NSSAI), as defined in Non-Patent Document 7. NSSAI (Network Slice Selection Assistance Information) includes one or more S-NSSAIs, which are combinations of the following: • Identify the slice type and enter the required SST (Slice / Service Type) field, which consists of 8 bits (range 0-255). • Distinguish between slices with the same SST field using an optional 24-bit SD (Slice Differentiator) field. This list includes up to eight S-NSSAIs. The UE will provide the NSSAI for slice selection in RRCSetupComplete if it is provided by the NAS. While the network can support a large number (hundreds of them) of slices, the UE does not need to support more than eight slices simultaneously. A BL (Bandwidth Reduced Low Complexity) UE or an NB-IoT (Narrow Band Internet of Things) UE will support up to eight slices simultaneously.

[0055] Slices are notified, for example, from the core network (e.g., 5GC) to the UE's NAS layer, and from the UE's NAS layer to the AS layer (e.g., RRC). Network slices selected and intended by the UE may be called selected NSSAI and intended NSSAI, respectively. A selected network slice (selected NSSAI) may also be called an allowed NSSAI, meaning a network slice permitted for use by the core network. SSTs may be included in S-NSSAI (i.e., S-NSSAI may contain information about SSTs).

[0056] Each network slice selected or intended by the UE may be identified by the identifier S-NSSAI. The selected or intended network slice may be an S-NSSAI(s) included in the Configured NSSAI or an S-NSSAI(s) included in the Allowed NSSAI. Note that S-NSSAIs in the Requested NSSAI included in the NAS registration request message must be part of the Configured NSSAI and / or Allowed NSSAI. Therefore, the intended network slice may be an S-NSSAI(s) included in the Requested NSSAI.

[0057] Such network slicing uses Network Function Virtualization (NFV) and software-defined networking (SDN) technologies to enable the creation of multiple virtualized logical networks on top of the physical network. Each virtualized logical network is called a network slice or network slice instance and contains logical nodes and functions used for specific traffic and signaling. The NG RAN or NG Core, or both, has a Slice Selection Function (SSF). The SSF selects one or more network slices suitable for the NG UE based on information provided by at least one of the NG UE and NG Core.

[0058] Multiple slices are distinguished, for example, by the services or use cases provided to the UE on each network slice. Use cases include, for example, enhanced Mobile Broadband (eMBB), Ultra-Reliable and Low Latency Communication (URLLC), and massive Machine Type Communication (mmTC). These are called slice types (e.g., Slice / Service Type (SST)). A RAN node providing communication to a UE may assign to that UE RAN slices and radio slices associated with the network slices of the core network selected for the UE, in order to provide end-to-end network slicing to the UE.

[0059] (Step S1003) RAN node 20 obtains network information from CN node 60 (NWDAF).

[0060] Network information can be obtained, for example, through an existing NWDAF subscription service. Network information transmitted from CN node 60 may include, for example, network function load, slice load, and service experience. Network information may also include network performance. Network information may also include UE mobility. Here, network performance may include statistics or predictions of RAN node status such as gNB, resource usage, communication and mobility performance, the number of UEs in an area of ​​interest, and the average rate of successful handovers. UE mobility may also be a time series of statistics or predictions of the location of a particular UE or group of UEs. However, RAN node 20 may obtain such network information from devices on 5GC other than CN node 60.

[0061] (Step S1004) RAN node 20 is an AI-enhanced RAN node, and therefore acquires network information from OAM device 70.

[0062] The network information transmitted from the OAM device 70 may include area information such as the cell where the UE is located, traffic information, and statistical information. The statistical information may include statistics related to handover, as well as statistics related to call processing such as call connection and call disconnection. Step S1004 may be performed before step S1003, after step S1003, or simultaneously with step S1003.

[0063] Thus, the RAN node 20 can receive network information from the CN node 60 and the OAM device 70. Therefore, the system including the RAN node 20, the CN node 60, and the OAM device 70 contributes to the AI-enabled RAN node 20 sending and receiving information between the CN node 60 and the OAM device 70. In addition, the RAN node 20 can further optimize RAN communication control using the AI ​​functions it possesses, based on the network information.

[0064] (Step S1005) RAN node 20 retrieves its own internal information.

[0065] "Internal information" may include a time series of information about loads measured (generated) in the past. "Internal information" may also include information about the distribution of UEs between slices, cells, beams, or any combination thereof of RAN node 20. Furthermore, "internal information" may include information about the operation of load balancing algorithms applied to the slices, cells, beams, or any combination thereof of RAN node 20.

[0066] (Step S1006) Based on the various information (e.g., measured values) acquired in steps S1001 to S1005, the RAN node 20 performs initial or periodic training of the AI / ML model held by the RAN intelligence device, or the AI / ML model acquired from the RAN intelligence device. The AI / ML model is a machine learning (ML) model that takes the information acquired in steps S1001 to S1005 as input and controls the RAN communication. In this embodiment, the AI / ML model is an ML model that takes the information acquired in steps S1001 to S1005 as input and outputs at least "information related to predicted values ​​for load parameters". When the RAN node 20 acquires information for the first time in steps S1001 to S1005, it performs initial training of the AI / ML model. In addition, the RAN node 20 periodically trains and updates the AI / ML model each time information is acquired in steps S1001 to S1005. This ensures that the AI / ML is sufficiently trained. Furthermore, the RAN node 20 may pass the information acquired in steps S1001 to S1005 to, for example, a training device for updating the AI / ML model. The AI / ML model used in this disclosure may be a novel one or a known ML model (for example, as described in Non-Patent Documents 3-5).

[0067] (Steps S1007-S1011) In steps S1007-S1011, RAN node 20 acquires various information, similar to steps S1001-S1005.

[0068] (Step S1012) When the AI / ML is sufficiently trained, RAN node 20 uses the information acquired in S1007-S1011 to generate "information related to predicted values ​​for the load parameters of the cells of RAN node 20".

[0069] The "cell load parameters" may include, for example, at least one of the following: Regarding the requested cells, beams, and slices: - At least one of the following usages of DL (Downlink) / UL (Uplink) per beam of each cell provided by RAN node 20: GBR (Guaranteed Bit Rate), non-GBR, or total PRB (Physical Resource Block) usage. - At least one of the following usages of DL (Downlink) / UL (Uplink) per slice of each cell provided by RAN node 20: GBR (Guaranteed Bit Rate), non-GBR, or total PRB (Physical Resource Block) usage. Regarding the requested cells and beams: DL, UL, Supplementary UL (SUL) capacity, which includes at least one of the capacity per cell or the capacity per beam of each cell provided by RAN node 20. Regarding the requested cells and slices: The capacity of at least one of the DL (Downlink) or UL (Uplink) per beam of each cell provided by RAN node 20.

[0070] Furthermore, the following “prediction types” may be included in the predictions for each parameter related to the cell load: • "Predictions for a fixed number of UEs" - Average load prediction - Minimum and maximum load prediction • "Predictions for changing number of UEs" - Average load prediction - Minimum and maximum load prediction

[0071] In other words, any combination of a prediction for a fixed number of UEs, a prediction for a changing number of UEs, the items included in the prediction for a fixed number of UEs (average load prediction, minimum load prediction, and maximum load prediction), and the items included in the prediction for a changing number of UEs (average load prediction, minimum load prediction, and maximum load prediction) can each constitute a "prediction type".

[0072] For example, the following prediction types may exist. Five examples are given here, but this is not an exhaustive list. "Prediction type 1" = "Prediction for a fixed number of UEs: Average load prediction" "Prediction Type 2" = "Prediction for a fixed number of UEs: Average load prediction, minimum load prediction, maximum load prediction" "Prediction Type 3" = "Prediction for a fixed number of UEs: Minimum load prediction, Maximum load prediction" "Prediction Type 4" = "Prediction for a fixed number of UEs: Average Load Prediction" + "Prediction for a changing number of UEs: Average Load Prediction" "Prediction Type 5" = "Prediction for a fixed number of UEs: average load prediction, minimum load prediction, maximum load prediction" + "Prediction for a changing number of UEs: average load prediction, minimum load prediction, maximum load prediction"

[0073] Here, "Predictions for a fixed number of UEs" refers to predictions that assume the number of active user devices (UEs) in a domain related to the load parameter (e.g., cell, beam, slice, or any combination thereof) remains unchanged during the prediction period. Furthermore, "Predictions for changing number of UEs" are predictions that take into account changes in the number of active UEs in domains related to load parameters (e.g., cells, beams, slices, or any combination thereof) during the prediction period. Furthermore, "average load prediction" is a prediction of the average load based on the current measured load values ​​for the cell of interest. Furthermore, "minimum load prediction" is a prediction of the minimum load based on the measured load values ​​of the cell of interest and its adjacent internal cells (for example, internal cell 42 adjacent to cell 43), assuming traffic offloading from the cell of interest to the adjacent internal cells (for example, internal cell 42 adjacent to cell 43). Furthermore, "maximum load prediction" is a prediction of the maximum load based on the measured load values ​​of the cell of interest and its internal cells, assuming that traffic is offloaded from the internal cell adjacent to the cell of interest (for example, internal cell 42 adjacent to cell 43) to the cell of interest.

[0074] Furthermore, "information related to predicted values ​​for load parameters" may be represented as a time series. Figure 7A illustrates an example of time series data for information related to predicted values ​​for load parameters. In the example shown in Figure 7A, the time series data for "information related to predicted values" includes multiple datasets. In Figure 7A, one dataset is represented as a part enclosed in parentheses. Each dataset contains timing information (time (N)) and predicted values ​​(load_value (N)).

[0075] Figure 7B illustrates another example of time-series data related to predicted values ​​for load parameters. In the example shown in Figure 7B, the time-series data for “information related to predicted values” includes multiple datasets. In Figure 7B, each dataset is represented as a part enclosed in parentheses. Each dataset contains timing information (time (N)), predicted values ​​(load_value (N)), and prediction accuracy (load_accuracy (N)).

[0076] Furthermore, the time-series data of "information related to predicted values" may include multiple datasets based on a predetermined "prediction granularity." "Prediction granularity" corresponds to the timing interval of the predicted values. In other words, in the examples of Figures 7A and 7B, "prediction granularity" corresponds to "time (N) - time (N-1)."

[0077] (Step S1013) RAN node 20 sends a first message containing the generated "information related to the predicted values ​​for the cell load parameters" to RAN node 30.

[0078] The first message may be, for example, a Resource Status Update message from a Resource Status Reporting procedure, or a message from a new procedure (for example, a Predictions Update message from a Predictions reporting procedure).

[0079] (A) Using the Resource Status Reporting Procedure Figure 8 shows the Resource Status Reporting Initiation procedure used to request load measurements from other NG-RAN nodes. This procedure can be used to send the second message described in the second embodiment. In step S11 of Figure 8, NG-RAN node R1 sends a RESOURCE STATUS REQUEST message to NG-RAN node R2. NG-RAN node R1 corresponds to the RAN node 30, and NG-RAN node R2 corresponds to the RAN node 20.

[0080] The RESOURCE STATUS REQUEST message can be used to send "information related to predicted values ​​for cell load parameters" from NG-RAN node R2 to NG-RAN node R1. The RESOURCE STATUS REQUEST message is defined in section 9.1.3.18 of Non-Patent Document 1. Examples of such RESOURCE STATUS REQUEST messages are shown in Figures 14A-14C.

[0081] This RESOURCE STATUS REQUEST message is sent from NG-RAN node R1 to NG-RAN node R2, initiating the transmission of predictions and prediction results for the requested load parameters according to the parameters given in the message. In Figures 14A-14C, the underlined IE (Report Characteristics IE) values ​​(bits from the 6th bit onward) indicate a "request to transmit prediction values." In Figures 14A-14C, the bits from the 6th bit onward each correspond to a different combination of load parameter and prediction type. As a preliminary step to step S1013, this RESOURCE STATUS REQUEST message is sent, and in step S1013, "information related to the prediction values ​​for the load parameters" is included in and transmitted in the RESOURCE STATUS UPDATE message. That is, the Report Characteristics IE in Figures 14A-14C is used to indicate which prediction values ​​of which load parameters and prediction types, among the prediction values ​​of the load parameters formed in step S1012, should be reported using the RESOURCE STATUS UPDATE message.

[0082] The "load parameters" may include, for example, at least one of the following: Regarding the requested cells, beams, and slices: - At least one of the following usages of DL (Downlink) / UL (Uplink) per beam of each cell provided by RAN node 20: GBR (Guaranteed Bit Rate), non-GBR, or total PRB (Physical Resource Block) usage. - At least one of the following usages of DL (Downlink) / UL (Uplink) per slice of each cell provided by RAN node 20: GBR (Guaranteed Bit Rate), non-GBR, or total PRB (Physical Resource Block) usage. Regarding the requested cells and beams: DL, UL, SUL capacity, which includes at least one of the capacity per cell or the capacity per beam of each cell provided by RAN node 20. Regarding the requested cells and slices: The capacity of at least one of DL (Downlink) or UL (Uplink) for each cell slice provided by RAN node 20.

[0083] The "prediction type" may include, for example, at least one of the following: • "Predictions for a fixed number of UEs" - Average load prediction - Minimum and maximum load prediction • "Predictions for changing number of UEs" - Average load prediction - Minimum and maximum load prediction

[0084] In other words, as described above, any combination of the following can constitute a "prediction type": a prediction for a fixed number of UEs, a prediction for a changing number of UEs, the items included in the prediction for a fixed number of UEs (average load prediction, minimum load prediction, and maximum load prediction), and the items included in the prediction for a changing number of UEs (average load prediction, minimum load prediction, and maximum load prediction).

[0085] For example, in Figures 14A-14C, load metric #1 and prediction type #1, corresponding to the 6th bit of Report Characteristics IE, may correspond to a combination of a "load parameter," which is the amount of DL (Downlink) / UL (Uplink) usage for each beam of each cell, whether GBR (Guaranteed Bit Rate), non-GBR, or total PRB (Physical Resource Block), and a "prediction type," which is the average load prediction for a fixed number of UEs.

[0086] Furthermore, the RESOURCE STATUS REQUEST message can be used to set the "prediction value reporting cycle," "prediction granularity," or both. Figure 9 shows another example of time-series data related to predicted values ​​for load parameters. In the time-series data shown in Figure 9, the timing information for adjacent datasets is in 100-millisecond increments. That is, by setting the "prediction granularity" value in the RESOURCE STATUS REQUEST message to a value corresponding to 100 milliseconds, the time-series data shown in Figure 9 will be reported. Also, in Figure 9, the time-series data is transmitted (reported) at the timing of "timing information = 0 milliseconds" and "timing information = 2000 milliseconds." That is, by setting the "prediction value reporting cycle" value in the RESOURCE STATUS REQUEST message to a value corresponding to 2000 milliseconds, the time-series data shown in Figure 9 will be reported. Here, "information related to predicted values ​​for load parameters" is included and transmitted in the RESOURCE STATUS UPDATE message. Therefore, the "reporting cycle for predicted values" may be equal to the transmission cycle of the RESOURCE STATUS UPDATE message, which contains "information related to predicted values ​​for load parameters." In the example shown in Figure 9, the timing of the actual measurement of load parameters is 1000 milliseconds before the timing of transmitting (reporting) the time series data (0 milliseconds). For example, the time series data reported at timing (0 milliseconds) may include predicted values ​​for timings between the actual measurement timing (-1000 milliseconds) and the reporting timing of the next time series data (+2000 milliseconds).

[0087] Figure 10 shows the Resource Status Reporting procedure used to report load information. Upon receiving the RESOURCE STATUS REQUEST message shown in Figure 8, NG-RAN node R2 initiates the requested measurements and predictions according to the parameters given in the message, and in step S21 sends a RESOURCE STATUS UPDATE message to NG-RAN node R1. This RESOURCE STATUS UPDATE message may contain the following information elements. Note that ">" indicates the data hierarchy. > Radio Resource Status IE >Composite Available Capacity Group IE >Slice Available Capacity IE

[0088] Radio Resource Status IE is used to report the following load parameters for the requested cell, beam, and slice. >Total PRB usage per beam (DL GBR / nonGBR / DL) per cell > Per cell, per beam: UL GBR / non-GBR / total PRB usage > Per cell per slice DL GBR / nonGBR / total PRB usage > Per cell per slice UL GBR / nonGBR / total PRB usage

[0089] The Composite Available Capacity Group IE is used to report the following load parameters for the requested cells and beams. DL, UL, and Supplementary UL (SUL) capacities including the following: >>Capacity per cell >>Capacity of each beam per cell

[0090] The Slice Available Capacity IE is used to report the following load parameters for the requested cells and slices. >> DL / UL capacity of each slice per cell After receiving such information from RAN node R2, RAN node R1 can, if necessary, initiate LB HO from a cell in RAN node R1 to a cell in RAN node R2.

[0091] Specific examples of the RESOURCE STATUS UPDATE message configuration are shown in Figures 15-21. First, as shown in Figure 15, the RESOURCE STATUS UPDATE message includes: > Radio Resource Status IE >Composite Available Capacity Group IE >Slice Available Capacity IE It includes.

[0092] The Radio Resource Status IE is defined in section 9.2.2.50 of Non-Patent Document 1. The Radio Resource Status IE shows the PRB usage for each cell, each SSB (Synchronization Signal Block) area, and each slice for all downlink and uplink traffic, as well as the usage of the PDCCH CCE (Control Channel Element) for downlink and uplink scheduling.

[0093] In this disclosure, the Radio Resource Status IE may be used to report, for the requested cell, beam, and slice, at least one of the following: DL (Downlink) / UL (Uplink) usage per beam for each cell in each RAN node, GBR (Guaranteed Bit Rate), non-GBR, or total PRB (Physical Resource Block) usage. In this disclosure, the Radio Resource Status IE may also be used to report, for the requested cell, beam, and slice, at least one of the following: DL (Downlink) / UL (Uplink) usage per slice for each cell in each RAN node, GBR (Guaranteed Bit Rate), non-GBR, or total PRB (Physical Resource Block) usage. An example of implementing the "Information related to predicted load parameters" in this disclosure in the Radio Resource Status IE is shown in Figures 16A-16E. Each IE underlined in Figures 16A-16E corresponds to the "Information related to predicted load parameters" in this disclosure. Note that the Presence of each IE underlined in Figures 16A-16E may be either "O" (Optional) or "M" (Mandatory). Also, not all of the IEs underlined in Figures 16A-16E need to be included in the Radio Resource Status IE; one or more arbitrary IEs may be included. An example of a prediction type definition is shown in Figure 26. An example of a time series data definition for "information related to the predicted value" included in each IE underlined in Figures 16A-16E is shown in Figure 27.

[0094] Furthermore, the Composite Available Capacity Group IE is defined in section 9.2.2.51 of Non-Patent Document 1. In this disclosure, the Composite Available Capacity Group IE may be used to report DL, UL, Supplementary UL (SUL) capacity for the requested cells and beams, including at least one of the capacity per cell of each RAN node or the capacity per beam of each cell. Figures 17-20 show an example of implementing the "information related to predicted values ​​for load parameters" of this disclosure in the Composite Available Capacity Group IE. Each IE underlined in Figures 17-20 corresponds to the "information related to predicted values ​​for load parameters" of this disclosure. Note that the Presence of each IE underlined in Figures 17-20 may be "O" (Optional) or "M" (Mandatory). Furthermore, not all of the IEs underlined in Figures 17-20 need to be included in the Composite Available Capacity Group IE; one or more arbitrary IEs may be included. An example of a prediction type definition is shown in Figure 26. An example of a time series data definition for "information related to the predicted value" to be included in each IE underlined in Figures 17-20 is shown in Figure 27.

[0095] The Slice Available Capacity IE is defined in section 9.2.2.55 of Non-Patent Document 1. In this disclosure, the Slice Available Capacity IE may be used to report the capacity of at least one of the DL (Downlink) / UL (Uplink) per slice of each PLMN for each cell and slice requested. An example of implementing the "information related to predicted values ​​for load parameters" of this disclosure in the Slice Available Capacity IE is shown in Figure 21. Each IE underlined in Figure 21 corresponds to the "information related to predicted values ​​for load parameters" of this disclosure. Note that the Presence of each IE underlined in Figure 21 may be "O" (Optional) or "M" (Mandatory). Also, not all of the IEs underlined in Figure 21 need to be included in the Composite Available Capacity Group IE; one or more arbitrary IEs may be included. An example of the definition of a prediction type is shown in Figure 26. Furthermore, an example of the definition of time-series data for "information related to predicted values" included in each IE (Information Indicator) underlined in Figure 21 is shown in Figure 27.

[0096] (B) Use of new procedures This document proposes a procedure specifically for setting up and reporting predicted values. This procedure can be used not only for setting up and reporting "information related to predicted values ​​for load parameters," but also for setting up and reporting other predicted values.

[0097] Figure 11 shows the PREDICTIONS Reporting Initiation procedure used to request other NG-RAN nodes to report information related to predicted values ​​for load parameters. This procedure can be used to send the second message described in the second embodiment. In step S31 of Figure 11, NG-RAN node R1 sends a PREDICTIONS REQUEST message to NG-RAN node R2. NG-RAN node R1 corresponds to the RAN node 30, and NG-RAN node R2 corresponds to the RAN node 20.

[0098] The PREDICTIONS REQUEST message can be used to configure the "information related to predicted values ​​for cell load parameters" sent from NG-RAN node R2. The PREDICTIONS REQUEST message is shown in Figures 22A and 22B.

[0099] This PREDICTIONS REQUEST message is sent from NG-RAN node R1 to NG-RAN node R2, initiating the transmission of predictions and prediction results for the requested load parameters according to the parameters given in the message. The values ​​of Report Characteristics IE (the value of each bit) in Figures 22A and 22B indicate a "request to transmit prediction values." In Figures 22A and 22B, each bit corresponds to a different combination of load parameter and prediction type. As a preliminary step to step S1013, this PREDICTIONS REQUEST message is sent, and in step S1013, "information related to the prediction values ​​for the load parameters" is included in the PREDICTIONS UPDATE message and transmitted. In other words, the Report Characteristics IE in Figures 22A and 22B is used to indicate which prediction values ​​of which load parameters and prediction types, among the prediction values ​​of the load parameters formed in step S1012, should be reported using the PREDICTIONS UPDATE message.

[0100] The explanations for "Load Parameters," "Prediction Type," "Prediction Value Reporting Cycle," and "Prediction Granularity" were provided in the Resource Status Reporting procedure, so they are omitted here.

[0101] In step S32 of Figure 11, NG-RAN node R2 sends a PREDICTIONS RESPONSE message to NG-RAN node R1. The PREDICTIONS RESPONSE message is shown in Figure 23.

[0102] Figure 12 shows the PREDICTIONS Reporting procedure used to report information related to predicted values ​​for load parameters. Upon receiving the PREDICTIONS REQUEST message shown in Figure 11, NG-RAN node R2 initiates the requested measurements and predictions according to the parameters given in the message, and in step 41 sends a PREDICTIONS UPDATE message to NG-RAN node R1. The PREDICTIONS UPDATE message is shown in Figure 24. This PREDICTIONS UPDATE message may include "Radio Resource Load Predictions IE". This "Radio Resource Load Predictions IE" may include "information related to predicted values ​​for load parameters" shown in Figures 15-21. An example of the configuration of Radio Resource Load Predictions IE is shown in Figures 25A and 25B. Figures 25A and 25B do not include all of the "information related to predicted values ​​for load parameters" shown in Figures 15-21; some of it is omitted. Furthermore, the PREDICTIONS UPDATE message may include other Predictions IEs, which may include information related to other predicted values ​​(for example, information related to predicted values ​​for UE trajectories).

[0103] Figure 26 shows the types of predictions that may be included in each IE associated with the predicted values ​​for load parameters. Each IE associated with the predicted values ​​for load parameters can have the following configuration as shown in Figure 26. Note that ">" indicates the data hierarchy. > "Predictions for a fixed number of UEs" >>Average load prediction >> Minimum load prediction >>Maximum load prediction > "Predictions for changing number of UEs" >>Average load prediction >> Minimum load prediction >>Maximum load prediction

[0104] Figure 27 shows an example of the structure of time-series data related to predicted values. The time-series data can take the following structure as shown in Figure 27. Note that ">" indicates the data hierarchy. >Time series of predictions >> Timing information (Prediction Time) >> Predicted Value >> Prediction Accuracy

[0105] The prediction value can present multiple candidate values. These candidate values ​​are defined, for example, by a bit string. For example, the prediction value may be encoded as an integer (0...100). For instance, 0 corresponds to a 0% load, and 100 corresponds to a 100% load.

[0106] Prediction accuracy can be expressed as multiple candidate values. These candidate values ​​can be defined, for example, as a bit string.

[0107] For example, prediction accuracy may be encoded as an integer (0...100). For instance, 0 corresponds to an accuracy of 0 (completely inaccurate), and 100 corresponds to an accuracy of 1 (completely accurate).

[0108] For example, prediction accuracy may be encoded as follows: • Very accurate = a value greater than 0.95 and less than or equal to 1 • High precision = values ​​greater than 0.9 and less than or equal to 0.95 • Quite accurate = a value greater than 0.75 and less than or equal to 0.9 • Inaccurate = Value less than or equal to 0.75

[0109] (Step S1014) RAN node 30 receives a "first message" containing "information related to predicted values ​​for the cell's load parameters." RAN node 30 may also receive load-related information from other neighboring RAN nodes that do not have AI / ML. RAN node 30 may use this load-related information obtained from nearby RAN nodes to determine load balancing (e.g., load balancing handover decisions).

[0110] <Other Embodiments> The hardware configuration examples of the RAN node 100 described in the above-described embodiments are now explained. Figure 13 is a block diagram showing the configuration examples of the RAN node according to each embodiment. Referring to Figure 13, the RAN node 100 includes an RF (Radio Frequency) transceiver 1001, a network interface 1003, a processor 1004, and memory 1005. The RF transceiver 1001 performs analog RF signal processing to communicate with the UE. The RF transceiver 1001 may include multiple transceivers. The RF transceiver 1001 is coupled with an antenna 1002 and a processor 1004. The RF transceiver 1001 receives modulation symbol data (or OFDM (Orthogonal Frequency Division Multiplexing) symbol data) from the processor 1004, generates a transmit RF signal, and supplies the transmit RF signal to the antenna 1002. The RF transceiver 1001 also generates a baseband receive signal based on the received RF signal received by the antenna 1002 and supplies this to the processor 1004.

[0111] The network interface 1003 is used to communicate with network nodes (e.g., other core network nodes). The network interface 1003 may include, for example, a network interface card (NIC) compliant with the IEEE (Institute of Electrical and Electronics Engineers) 802.3 series.

[0112] The processor 1004 performs data plane processing and control plane processing, including digital baseband signal processing for wireless communication. For example, in the case of LTE and 5G, the digital baseband signal processing by the processor 1004 may include signal processing for the MAC layer and the Physical layer.

[0113] The processor 1004 may include multiple processors. For example, the processor 1004 may include a modem processor (e.g., a DSP (Digital Signal Processor)) that performs digital baseband signal processing, and a protocol stack processor (e.g., a CPU (Central Processing Unit) or an MPU (Micro Processor Unit)) that performs control plane processing.

[0114] Memory 1005 is composed of a combination of volatile and non-volatile memory. Memory 1005 may include multiple physically independent memory devices. Volatile memory is, for example, Static Random Access Memory (SRAM) or Dynamic RAM (DRAM), or a combination thereof. Non-volatile memory is Mask Read Only Memory (MROM), Electrically Erasable Programmable ROM (EEPROM), flash memory, or hard disk drive, or any combination thereof. Memory 1005 may include storage located away from the processor 1004. In this case, the processor 1004 may access memory 1005 via the network interface 1003 or an I / O interface not shown.

[0115] Memory 1005 may store a software module (computer program) containing instruction sets and data for processing by the RAN node 100 as described in the above embodiments. In some implementations, the processor 1004 may be configured to read the software module from memory 1005 and execute it to perform the processing of the RAN node 100 as described in the above embodiments.

[0116] As described above, the one or more processors in each of the above embodiments execute one or more programs that include a set of instructions for causing a computer to perform the algorithm described with reference to the drawings. This process enables the signal processing method described in each embodiment.

[0117] The program, when loaded into a computer, includes a set of instructions (or software code) for causing the computer to perform one or more of the functions described in the embodiments. The program may be stored on a non-temporary computer-readable medium or a physical storage medium. Examples, but not limited to, of a non-temporary computer-readable medium or a physical storage medium include random-access memory (RAM), read-only memory (ROM), flash memory, solid-state drive (SSD) or other memory technologies, CD-ROM, digital versatile disk (DVD), Blu-ray® disc or other optical disc storage, magnetic cassette, magnetic tape, magnetic disk storage or other magnetic storage devices. The program may be transmitted over a temporary computer-readable medium or a communication medium. Examples, but not limited to, of a temporary computer-readable medium or a communication medium include electrically, optically, acoustically, or otherwise propagating signals.

[0118] In this specification, User Equipment (UE) (or including mobile station, mobile terminal, mobile device, or wireless device, etc.) is an entity connected to a network via a wireless interface.

[0119] Some or all of the above embodiments may also be described as follows, but are not limited to the following: (Note 1) A Wireless Access Network (RAN) node, Memory and A processor coupled to the aforementioned memory, Equipped with a transceiver, The processor is configured to cause the transceiver to send a first message to another RAN node. The first message includes information relating to predicted values ​​for parameters concerning the load of the RAN node cells, RAN node. (Note 2) The information related to the aforementioned predicted value includes the aforementioned predicted value at each of the multiple timings, The RAN node described in Appendix 1. (Note 3) The information related to the predicted value includes the predicted value at a timing after the sending timing of the first message. The RAN node described in Appendix 1 or 2. (Note 4) The information related to the aforementioned predicted value includes the predicted value and the prediction accuracy of the aforementioned predicted value. A RAN node as described in any one of the items 1 to 3 in the appendix. (Note 5) The information related to the aforementioned predicted value includes multiple sets, Each of the above sets includes timing information, the predicted value, and the prediction accuracy of the predicted value. A RAN node as described in any one of the items 1 to 4 in the appendix. (Note 6) The information related to the aforementioned predicted values ​​is, Predicted value assuming that the number of active user devices (UEs) in the domain related to the load parameters of the cell does not change during the prediction period, A predicted value that takes into account the change in the number of active UEs in the domain related to the load parameters of the cell during the forecast period, or Including both of these, A RAN node as described in any one of the items 1 through 5 of the appendix. (Note 7) The information related to the aforementioned predicted values ​​includes the aforementioned predicted values ​​for each uplink and each downlink in the cell. A RAN node as described in any one of the items 1 through 6 of the appendix. (Note 8) The information related to the aforementioned predicted value includes the aforementioned predicted value in the slice of the cell, A RAN node as described in any one of the items 1 through 7 of the appendix. (Note 9) The processor is configured to cause the transceiver to receive a second message containing information about a request to transmit information related to the predicted value, which was sent from the other RAN node. A RAN node as described in any one of the items 1 through 8 of the appendix. (Note 10) The second message further includes information regarding the reporting cycle of the predicted value, The RAN node described in Appendix 9. (Note 11) The second message further includes information regarding the prediction granularity related to the timing interval of the predicted value, RAN nodes as described in Appendix 9 or 10. (Note 12) The first message mentioned above is a RESOURCE STATUS REQUEST message. A RAN node as described in any one of the items 1 through 11 of the appendices. (Note 13) The second message mentioned above is a RESOURCE STATUS UPDATE message. A RAN node as described in any one of the items 9 to 11 in the appendix. (Note 14) A Wireless Access Network (RAN) node, Memory and A processor coupled to the aforementioned memory, Equipped with a transceiver, The processor is configured to cause the transceiver to receive a first message transmitted from another RAN node. The first message includes information regarding predicted values ​​for parameters relating to the load of the cells of the other RAN node, RAN node. (Note 15) The information related to the aforementioned predicted value includes the aforementioned predicted value at each of the multiple timings, The RAN node described in Appendix 14. (Note 16) The information related to the predicted value includes the predicted value at a timing after the sending timing of the first message. RAN nodes as described in Appendix 14 or 15. (Note 17) The information related to the aforementioned predicted value includes the predicted value and the prediction accuracy of the aforementioned predicted value. A RAN node as described in any one of the items 14 to 16 of the appendix. (Note 18) The information related to the aforementioned predicted value includes multiple sets, Each of the above sets includes timing information, the predicted value, and the prediction accuracy of the predicted value. A RAN node as described in any one of the items 14 to 17 of the appendix. (Note 19) The information related to the aforementioned predicted values ​​is, Predicted value assuming that the number of active user devices (UEs) in the domain related to the load parameters of the cell does not change during the prediction period, A predicted value that takes into account the change in the number of active UEs in the domain related to the load parameters of the cell during the forecast period, or Including both of these, A RAN node as described in any one of the items in Appendix 14 to 18. (Note 20) The information related to the aforementioned predicted values ​​includes the aforementioned predicted values ​​for each uplink and each downlink in the cell. A RAN node as described in any one of the items 14 to 19 of the appendix. (Note 21) The information related to the aforementioned predicted value includes the aforementioned predicted value in the slice of the cell, A RAN node as described in any one of the items 14 to 20 of the appendix. (Note 22) The processor is configured to cause the transceiver to send a second message to the other RAN node, which includes information regarding a request to transmit information related to the predicted value. A RAN node as described in any one of the items in Appendix 14 to 21. (Note 23) The second message further includes information regarding the reporting cycle of the predicted value, The RAN node described in Appendix 22. (Note 24) The second message further includes information regarding the prediction granularity related to the timing interval of the predicted value, RAN nodes as described in Appendix 22 or 23. (Note 25) The first message mentioned above is a RESOURCE STATUS UPDATE message. A RAN node as described in any one of the items 14 to 24 of the appendix. (Note 26) The second message mentioned above is a RESOURCE STATUS REQUEST message. A RAN node as described in any one of the items 22 to 24 of the appendix. (Note 27) A method performed by a Wireless Access Network (RAN) node, This includes sending the first message to other RAN nodes, The first message includes information relating to predicted values ​​for parameters concerning the load of the RAN node cells, method. (Note 28) The aforementioned information includes the predicted values ​​at each of the multiple timings, The method described in Appendix 27. (Note 29) A method performed by a Wireless Access Network (RAN) node, This includes receiving a first message sent from another RAN node, The first message includes information relating to predicted values ​​for parameters concerning the load of cells in the other RAN node, method. (Note 30) The aforementioned information includes the predicted values ​​at each of the multiple timings, The method described in Appendix 29. (Note 31) To a Wireless Access Network (RAN) node, The first message is sent to another RAN node, and the process is executed, The first message includes information relating to predicted values ​​for parameters concerning the load of the RAN node cells, program. (Note 32) The aforementioned information includes the predicted values ​​at each of the multiple timings, The program described in Appendix 31. (Note 33) To a Wireless Access Network (RAN) node, Perform a process that includes receiving a first message sent from another RAN node, The first message includes information relating to predicted values ​​for parameters concerning the load of cells in the other RAN node, program. (Note 34) The aforementioned information includes the predicted values ​​at each of the multiple timings, The program described in Appendix 33.

[0120] While the present disclosure has been described above with reference to embodiments, the present disclosure is not limited thereto. Various modifications to the structure and details of the present disclosure may be made that can be understood by those skilled in the art within the scope of the disclosure.

[0121] This application claims priority based on Japanese Patent Application No. 2022-035279, filed on 8 March 2022, and incorporates all of its disclosures herein. [Explanation of symbols]

[0122] 1.10 Communication Systems 2,3,20,30,100,R1,R2 RAN nodes Cells 4-1, 4-2, 41, 42, 43, 44, 45, 46 51 UE 101 Communications Department 102 Control Unit

Claims

1. A first radio access network (RAN) node, The system is equipped with means for receiving a first message from a second RAN node, The first message includes a first information element, The first information element indicates the prediction type for which the first RAN node performs the prediction. The first RAN node is, Means for performing the prediction in order to generate predictive information, Means for transmitting a second message containing the aforementioned prediction information to the second RAN node, It is equipped with, The aforementioned forecast information includes the usage of physical resource blocks (PRBs) per synchronous signal block (SSB) area for downlink and uplink traffic. 1st RAN node.

2. The first message includes a second information element, The second information element indicates the time interval between the timings of the predictions. The first RAN node according to claim 1.

3. The aforementioned prediction information relates to the predicted number of active user devices (UEs). The first RAN node according to claim 1 or 2.

4. The aforementioned forecast information includes the PRB usage for the downlink (DL) compensated bitrate (GBR) in the SSB area, the PRB usage for the uplink (UL) GBR in the SSB area, the PRB usage for the non-GBR DL in the SSB area, the PRB usage for the non-GBR UL in the SSB area, the total PRB usage for DL ​​in the SSB area, and the total PRB usage for UL in the SSB area. The first RAN node according to claim 1 or 2.

5. The first information element is a ReportCharacteristicsIE (Information Element). The first RAN node according to claim 1 or 2.

6. The aforementioned forecast information is Radio Resource StatusIE (Information Element). The first RAN node according to claim 1 or 2.

7. The second information element is a Prediction Reporting Granularity IE (Information Element). The first RAN node according to claim 2.

8. The first RAN node is a Next Generation RAN (NG-RAN) node, The second RAN node is an NG-RAN node, The first message is an Xn message, The second message is an Xn message. The first RAN node according to claim 1 or 2.

9. A method performed by a first radio access network (RAN) node, This includes receiving a first message from the second RAN node, The first message includes a first information element, The first information element indicates the prediction type for which the first RAN node performs the prediction. The aforementioned method, Performing the aforementioned prediction in order to generate predictive information, A second message containing the aforementioned prediction information is transmitted to the second RAN node. Includes, The aforementioned forecast information includes the usage of physical resource blocks (PRBs) per synchronous signal block (SSB) area for downlink and uplink traffic. method.

10. The first message includes a second information element, The second information element indicates the time interval between the timings of the predictions. The method according to claim 9.

11. The aforementioned prediction information relates to the predicted number of active user devices (UEs). The method according to claim 9 or 10.

12. The aforementioned forecast information includes the PRB usage for the downlink (DL) compensated bitrate (GBR) in the SSB area, the PRB usage for the uplink (UL) GBR in the SSB area, the PRB usage for the non-GBR DL in the SSB area, the PRB usage for the non-GBR UL in the SSB area, the total PRB usage for DL ​​in the SSB area, and the total PRB usage for UL in the SSB area. The method according to claim 9 or 10.

13. The first information element is a ReportCharacteristicsIE (Information Element). The method according to claim 9 or 10.

14. The aforementioned forecast information is Radio Resource StatusIE (Information Element). The method according to claim 9 or 10.

15. The second information element is a Prediction Reporting Granularity IE (Information Element). The method according to claim 10.

16. The first RAN node is a Next Generation RAN (NG-RAN) node, The second RAN node is an NG-RAN node, The first message is an Xn message, The second message is an Xn message. The method according to claim 9 or 10.

17. User equipment (UE), It is equipped with means for communicating with a first wireless access network (RAN) node, The first RAN node is configured to receive the first message from the second RAN node. The first message includes a first information element, The first information element indicates the prediction type for which the first RAN node performs the prediction. The first RAN node is configured to perform the prediction in order to generate prediction information and to send a second message containing the prediction information to the second RAN node. The aforementioned forecast information includes the usage of physical resource blocks (PRBs) per synchronous signal block (SSB) area for downlink and uplink traffic. UE.

18. A method performed by a user device (UE), This includes communicating with a first radio access network (RAN) node, The first RAN node is configured to receive the first message from the second RAN node. The first message includes a first information element, The first information element indicates the prediction type for which the first RAN node performs the prediction. The first RAN node is configured to perform the prediction in order to generate prediction information and to send a second message containing the prediction information to the second RAN node. The aforementioned forecast information includes the usage of physical resource blocks (PRBs) per synchronous signal block (SSB) area for downlink and uplink traffic. method.

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