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WO2025156418A1 - Collecte et rapport de données pour aider à des fonctions d'intelligence artificielle dans une connectivité double sans fil - Google Patents

Collecte et rapport de données pour aider à des fonctions d'intelligence artificielle dans une connectivité double sans fil

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Publication number
WO2025156418A1
WO2025156418A1 PCT/CN2024/085751 CN2024085751W WO2025156418A1 WO 2025156418 A1 WO2025156418 A1 WO 2025156418A1 CN 2024085751 W CN2024085751 W CN 2024085751W WO 2025156418 A1 WO2025156418 A1 WO 2025156418A1
Authority
WO
WIPO (PCT)
Prior art keywords
wireless terminal
base station
predicted
request
network
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
PCT/CN2024/085751
Other languages
English (en)
Inventor
Jiajun Chen
Yin Gao
Dapeng Li
Man ZHANG
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
ZTE Corp
Original Assignee
ZTE Corp
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by ZTE Corp filed Critical ZTE Corp
Priority to PCT/CN2024/085751 priority Critical patent/WO2025156418A1/fr
Publication of WO2025156418A1 publication Critical patent/WO2025156418A1/fr
Pending legal-status Critical Current
Anticipated expiration legal-status Critical

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Classifications

    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W24/00—Supervisory, monitoring or testing arrangements
    • H04W24/02—Arrangements for optimising operational condition
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W24/00—Supervisory, monitoring or testing arrangements
    • H04W24/10—Scheduling measurement reports ; Arrangements for measurement reports
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W36/00—Hand-off or reselection arrangements
    • H04W36/0005—Control or signalling for completing the hand-off
    • H04W36/0055—Transmission or use of information for re-establishing the radio link
    • H04W36/0069—Transmission or use of information for re-establishing the radio link in case of dual connectivity, e.g. decoupled uplink/downlink

Definitions

  • This disclosure is generally directed to intelligent wireless dual connectivity (DC) and specifically directed to methods and network devices for network data collection and report for assisting in artificial intelligence (AI) functions for DC in cellular wireless communication systems.
  • DC intelligent wireless dual connectivity
  • AI artificial intelligence
  • a wireless terminal may be simultaneously connected to multiple base stations.
  • the wireless terminal may be connected to two base stations of distinct radio access technologies.
  • Such mode of communication may be referred to as dual connectivity (DC) .
  • the two base stations may operate in a collaborative and intelligent manner in performing network configuration and in providing data connectivity to the wireless terminal device.
  • Such DC operation may be assisted by artificial intelligence (AI) prediction models. It is important to improve the performance of these AI prediction models for achieving efficient DC operations.
  • AI artificial intelligence
  • This disclosure is generally directed to intelligent wireless dual connectivity (DC) and specifically directed to methods and network devices for network data collection and report for assisting in artificial intelligence (AI) functions for DC in cellular wireless communication systems.
  • DC intelligent wireless dual connectivity
  • AI artificial intelligence
  • a network measurement and reporting procedures between a source master node (MN) , one or more secondary nodes (SNs) , a target MN, and one or more target SNs may be implemented for measuring and collecting network data for purposes of evaluating performance of the AI models and for triggering updating and retaining of the AI models.
  • Such network data measurements and reporting may be configured such that the various network nodes can be ready for such network data measurements before a mobility procedure and can provide timely and adapted reporting.
  • Such network data measurements may particularly pertain to measured trajectories and network performance of terminal devices, in comparison to AI-predicted trajectories and performance for the terminal devices.
  • the set of network measurements are identified by the wireless access network using at least one measurement ID.
  • the set of network measurements comprise at least one of: a trajectory of the wireless terminal comprising one or more of a PSCell list including PSCells served by one or more secondary nodes, a PCell list including PCells served by one or more master nodes, a Secondary Cell Group (SCG) history information for the wireless terminal, a location list of the wireless terminal, and a correlation relationship between PCells and PSCells for the wireless terminal; or traffic measurement of the wireless terminal including one or more of an uplink usage count and a downlink usage count of the wireless terminal.
  • a trajectory of the wireless terminal comprising one or more of a PSCell list including PSCells served by one or more secondary nodes, a PCell list including PCells served by one or more master nodes, a Secondary Cell Group (SCG) history information for the wireless terminal, a location list of the wireless terminal, and a correlation relationship between PCells and PSCells for the wireless terminal; or traffic measurement of the wireless terminal including one or more of an uplink usage count and a downlink
  • the request for the network data collection/report comprises at least one of: a first measurement ID associated with the first base station and a second measurement ID associated with the second base station; a registration request for the network data collection/report indicating types of network data in the set of network measurements; a reporting configuration for the set of network measurements; a measured trajectory collection/report configuration for collecting and/or reporting measured trajectory for the wireless terminal; a measured performance feedback configuration for collecting and/or reporting measured performance feedback of the wireless terminal; or a measured traffic collection/report configuration for collecting and/or reporting measured traffic of the wireless terminal.
  • the request for the network data collection/report further indicates a number of visited PSCells for indicating a maximum number of PSCells visited by the wireless terminal, at which time collected data should be reported.
  • the registration request for the network data collection/report comprises a bit map, at least one bit in the bit map indicating whether UE traffic and/or secondary cell group (SCG) information is to be measured.
  • SCG secondary cell group
  • the request for the network data collection/report comprises the measured traffic collection/report configuration, the measured traffic collection/report configuration comprising a collection/report time configuration for collecting and/or reporting the measured traffic of the wireless terminal.
  • the collection/report time configuration for collecting and/or reporting the measured traffic of the wireless terminal indicates at least one of a start time, an end time, or time duration for collecting and/or reporting the measured traffic of the wireless terminal.
  • the mobility management procedure comprises: transmitting a mobility request for the wireless terminal; and receiving an acknowledgement from the second base station after the second base station completes the mobility management procedure by the second base station.
  • the mobility request comprises: predicted information generated by the AI function for assisting with the mobility management procedure; and the first measurement ID and the second measurement ID.
  • the predicted information comprises at least one of: a predicted trajectory information generated by the AI function for the wireless terminal; or a predicted network traffic information generated by the AI function for the wireless terminal.
  • the predicted trajectory information comprises at least one of: a predicted primary secondary cell (PSCell) list for the dual connectivity including IDs for predicted PSCells to which the wireless terminal is predicted to connect; a predicted primary cell (PCell) list for the dual connectivity including IDs for predicted PCells to which the wireless terminal is predicted to connect; a predicted cell List including cell IDs to which wireless terminal is predicted to connect without due connectivity; paring correlation between the predicted PCells and predicted PSCells for the dual connectivity; or predicted number of PSCells for indicating a predicted maximum number of PSCells that a target secondary cell (SN) for the dual connectivity can prepare.
  • PSCell predicted primary secondary cell
  • the predicted network traffic information comprises at least one: a predicted uplink usage count for the wireless terminal; or a predicted downlink usage count for the wireless terminal.
  • the set of measurements received by the first base station are reported from the second base station and are identified by the second base station by adding to the reporting the first measurement ID and the second measurement ID as received by the second base station from the mobility request.
  • the first base station comprises a master node (MN) associated with the wireless terminal and the second base station comprises a secondary node (SN) associated with the wireless terminal for the dual connectivity.
  • MN master node
  • SN secondary node
  • the mobility management procedure comprises sending an SN addition request by the MN to the SN.
  • mobility management procedure comprises sending an SN modification request.
  • the first base station comprises a source MN associated with the wireless terminal and the second base station comprises a target MN associated with the wireless terminal.
  • the mobility management procedure comprises sending a handover request by the source MN to the target MN.
  • the request for the network data collection/report triggers the target MN to send a corresponding network data collection/report request to at least one target SN associated with the target MN for the dual connectivity of the wireless terminal.
  • the handover request triggers the target MN to send an SN addition request to at least one target SN associated with the target MN.
  • the first base station comprises a wireless access network node to which the wireless terminal is currently connected to without dual connectivity; and the second base station comprises a target MN for dual connectivity for the wireless terminal.
  • the mobility management procedure comprises sending a handover request from the wireless access network node to the target MN.
  • request for network data collection/report triggers the target MN to a send corresponding network data collection/report request to at least one target SN associated with the target MN for the dual connectivity of the wireless terminal.
  • the handover request triggers the target MN to send an SN addition request to at least one target SN associated with the target MN.
  • the first base station comprises an SN associated with the wireless terminal and the second base station comprises an MN associated with the wireless terminal for the dual connectivity.
  • the mobility management procedure comprises sending an SN modification required message by the SN to the MN.
  • methods by the second base station above are disclosed, corresponding to the interaction steps performed by the second base station in communication with the first base station and the wireless terminal when performing anyone of the methods above.
  • a wireless device comprising a processor and a memory
  • the processor may be configured to read computer code from the memory to implement any one of the methods above.
  • a computer program product comprising a non-transitory computer-readable program medium with computer code stored thereupon is disclosed.
  • the computer code when executed by a processor, may cause the processor to implement any one of the methods above.
  • FIG. 1 illustrates an example wireless communication network including a wireless access network, a core network, and data networks.
  • FIG. 2 illustrates an example wireless access network including a plurality of mobile stations/terminals or UEs and a wireless access network node in communication with one another via an over-the-air radio communication interface.
  • FIG. 3 shows an exemplary radio access work configured with multiple cells for supporting dual connectivity.
  • FIG. 4 shows an example procedure between two network nodes for configuring network data collection and reporting for facilitating mobility management using AI functions.
  • FIG. 5 shows an example procedure between a master node (MN) and a secondary node (SN) for configuring network data collection and reporting for assisting with an MN initiated SN addition procedure using AI functions.
  • MN master node
  • SN secondary node
  • FIG. 6 shows an example procedure between a master node (MN) and a secondary node (SN) for configuring network data collection and reporting for assisting with an MN initiated SN modification procedure using AI functions.
  • MN master node
  • SN secondary node
  • FIG. 7 shows an example handover procedure between a source MN and a target MN including network data collection and reporting for facilitating AI functions in mobility management with dual connectivity.
  • FIG. 8 shows another example handover procedure including network data collection and reporting for facilitating AI functions in mobility management with dual connectivity.
  • FIG. 9 shows another example procedure between an SN and an MN for configuring network data collection and reporting for assisting with mobility management using AI functions.
  • This disclosure is generally directed to intelligent wireless dual connectivity (DC) and specifically directed to methods and network devices for network data collection and report for assisting in artificial intelligence (AI) functions for DC in cellular wireless communication systems.
  • DC intelligent wireless dual connectivity
  • AI artificial intelligence
  • a network measurement and reporting procedures between a source master node (MN) , one or more secondary nodes (SNs) , a target MN, and one or more target SNs may be implemented for measuring and collecting network data for purposes of evaluating performance of the AI models and for triggering updating and retaining of the AI models.
  • Such network data measurements and reporting may be configured such that the various network nodes can be ready for such network data measurements before a mobility procedure and can provide timely and adapted reporting.
  • Such network data measurements may particularly pertain to measured trajectories and network performance of terminal devices, in comparison to AI-predicted trajectories and performance for the terminal devices.
  • An example cellular wireless communication network may include wireless terminal devices or user equipment (UE) 110, 111, and 112, a carrier network 102, various service applications 140, and other data networks 150.
  • the wireless terminal devices or UEs may be alternatively referred to as wireless terminals.
  • the carrier network 102 may include access network nodes 120 and 121, and a core network 130.
  • the carrier network 110 may be configured to transmit voice, data, and other information (collectively referred to as data traffic) among UEs 110, 111, and 112, between the UEs and the service applications 140, or between the UEs and the other data networks 150.
  • the access network nodes 120 and 121 may be configured as various wireless access network nodes (WANNs, alternatively referred to as wireless base stations) to interact with the UEs on one side of a communication session and the core network 130 on the other.
  • WANNs wireless access network nodes
  • the term “access network” may be used more broadly to refer a combination of the wireless terminal devices 110, 111, and 112 and the access network nodes 120 and 121.
  • a wireless access network may be alternatively referred to as Radio Access Network (RAN) .
  • the core network 130 may include various network nodes configured to control communication sessions and perform network access management and traffic routing.
  • the service applications 140 may be hosted by various application servers deployed outside of but connected to the core network 130.
  • the other data networks 150 may also be connected to the core network 130.
  • the core network 130 of FIG. 1 may include various network nodes geographically distributed and interconnected to provide network coverage of a service region of the carrier network 102. These network nodes may be implemented as dedicated hardware network nodes. Alternatively, these network nodes may be virtualized and implemented as virtual machines or as software entities. These network nodes may each be configured with one or more types of network functions which collectively provide the provisioning and routing functionalities of the core network 130.
  • the UEs may communicate with one another via the wireless access network.
  • UE 110 and 112 may be connected to and communicate via the same access network node 120.
  • the UEs may communicate with one another via both the access networks and the core network.
  • UE 110 may be connected to the access network node 120 whereas UE 111 may be connected to the access network node 121, and as such, the UE 110 and UE 111 may communicate to one another via the access network nodes 120 and 121, and the core network 130.
  • the UEs may further communicate with the service applications 140 and the data networks 150 via the core network 130. Further, the UEs may communicate to one another directly via side link communications, as shown by 113.
  • FIG. 2 further shows an example system diagram of the wireless access network 120 including a WANN 202 serving UEs 110 and 112 via the over-the-air interface 204.
  • the wireless transmission resources for the over-the-air interface 204 include a combination of frequency, time, and/or spatial resource.
  • Each of the UEs 110 and 112 may be a mobile or fixed terminal device installed with mobile access units such as SIM/USIM modules for accessing the wireless communication network 100.
  • the UEs 110 and 112 may each be implemented as a terminal device including but not limited to a mobile phone, a smartphone, a tablet, a laptop computer, a vehicle on-board communication equipment, a roadside communication equipment, a sensor device, a smart appliance (such as a television, a refrigerator, and an oven) , or other devices that are capable of communicating wirelessly over a network.
  • each of the UEs such as UE 112 may include transceiver circuitry 206 coupled to one or more antennas 208 to effectuate wireless communication with the WANN 120 or with another UE such as UE 110.
  • the transceiver circuitry 206 may also be coupled to a processor 210, which may also be coupled to a memory 212 or other storage devices.
  • the memory 212 may be transitory or non-transitory and may store therein computer instructions or code which, when read and executed by the processor 210, cause the processor 210 to implement various ones of the methods described herein.
  • the WANN 120 may include a wireless base station or other wireless network access point or node capable of communicating wirelessly via the over-the-air interface 204 with one or more UEs and communicating with the core network 130.
  • the WANN 120 may be implemented, without being limited, in the form of a 2G base station, a 3G nodeB, an LTE eNB, a 4G LTE base station, a 5G NR base station of a 5G gNB, a 5G central-unit base station, or a 5G distributed-unit base station.
  • Each type of these WANNs may be configured to perform a corresponding set of wireless network functions.
  • the WANN 202 may include transceiver circuitry 214 coupled to one or more antennas 216, which may include an antenna tower 218 in various forms, to effectuate wireless communications with the UEs 110 and 112.
  • the transceiver circuitry 214 may be coupled to one or more processors 220, which may further be coupled to a memory 222 or other storage devices.
  • the memory 222 may be transitory or non-transitory and may store therein instructions or code that, when read and executed by the one or more processors 220, cause the one or more processors 220 to implement various functions of the WANN 120 described herein.
  • Data packets in a wireless access network may be transmitted as protocol data units (PDUs) .
  • the data included therein may be packaged as PDUs at various network layers wrapped with nested and/or hierarchical protocol headers.
  • the PDUs may be communicated between a transmitting device or transmitting end (these two terms are used interchangeably) and a receiving device or receiving end (these two terms are also used interchangeably) once a connection (e.g., a radio link control (RRC) connection) is established between the transmitting and receiving ends.
  • RRC radio link control
  • Any of the transmitting device or receiving device may be either a wireless terminal device such as device 110 and 120 of FIG. 2 or a wireless access network node such as node 202 of FIG. 2. Each device may both be a transmitting device and receiving device for bi-directional communications.
  • the example wireless access network or radio access network above may be configured as a cellular network, in which radio communication resources are managed in cells.
  • the communication cells are configured to minimize radio interference.
  • each base station 302, 304, and 306 may be associated with a particular Radio Access Technology (RAT) .
  • RAT Radio Access Technology
  • the various RATs may include but not limited to 2G, 3G, 4G/LTE, 5G, 6G, and other generations of radio access technologies.
  • the term base station is used to refer to a network node or a portion of a network node that communicates with wireless terminals using one or more OTA interfaces.
  • the term base station may be used refer to a DU.
  • the base stations 302, 304, and 306 may use separate or shared radio resources (e.g., carrier frequencies and/or time) .
  • Each of the base stations may be associated with a coverage area, which may include one or more cells. For example, as shown in FIG.
  • the base station 302 may be a 4G/LTE base station associated with an approximate coverage area 303 and configured to provision cells 310, 312 and 314; the base station 304 may be a 5G/New Radio (NR) DU associated with approximate coverage area 305 and configured to provision cells 320 and 322; whereas the base station 306 may be another 4G/LTE base station associated with an approximate coverage area 307 and configured to provision cells 330 and 332.
  • NR New Radio
  • the wireless terminals 340, 342. and 344 in FIG. 3, for example, may be mobile wireless terminals and thus may move from cell to cell and/or from RAT to RAT.
  • a particular wireless terminal may be potentially connected to multiple cells or multiple RAT.
  • Dual connectivity (DC) or multi-connectivity refers to network implementations where a wireless terminal is simultaneously connected to two (or multiple) cells of two (or multiple) distinct RATs.
  • the wireless terminal 342 of FIG. 3 may be configured to be in DC operation m mode with cell 414 (provisioned by the 4G/LET base station 302) and cell 320 (provisioned by the 5G/NR base station 304) .
  • the multiple cells shown in FIG. 3 for each base station may be configured into cell groups (CGs) . Both the cells and CGs are provisioned (e.g., added, configured, modified removed, etc. ) by the corresponding base station.
  • a cell group may be either a Master CG (MCG) or Secondary CG (SCG) .
  • MCG Master CG
  • SCG Secondary CG
  • a primary cell in a MSG for example, may be referred to as a PCell, whereas a primary cell in a SCG may be referred to as PScell.
  • Secondary cells in either an MCG or an SCG may be all referred to as SCells.
  • the primary cells including PCell and PScell may be collectively referred to as spCells (special Cells) . All these cells may be referred to as serving cells or cells.
  • the term “cell” and “serving cell” may be used interchangeably in a general manner unless specifically differentiated.
  • the term “serving cell” may refer to a cell that is serving, will serve, or may serve the UE. In other words, a “serving cell” may not be currently serving the UE. While the various embodiment described below may at times be referred to one of the types of serving cells above, the underlying principles apply to all types of serving cells in both types of serving cell groups.
  • a wireless terminal such as 342 in FIG. 3, may be in active connection with two base stations having distinct RATs (e.g., 4G/LTE and 5G/NR technologies in the example of FIG. 3) .
  • the communications with the two base stations may be via distinct carrier spectral bands allocated to the two distinct RATs.
  • the two distinct RATs may share a radio spectrum or have overlapping radio spectrum using, for example Dynamic Spectrum Sharing (DSS) technologies.
  • DSS Dynamic Spectrum Sharing
  • One of the two base stations in dual connectivity for example, may act as a master, referred to as a Master Node (MN) , whereas the other base station may act as a Secondary Node (SN) .
  • MN Master Node
  • SN Secondary Node
  • the MN and the SN may communicate via various messages over separate communication interface (s) (e.g., a backhaul interface) to effectuate a collaborative effort to configure the cells, CGs, and communication resources within the MN and SN in providing optimal dual connectivity to the mobile terminal, and to facilitate cell switching within the MN and SN or outside of the MN or SN for the mobile terminal when needed.
  • s separate communication interface
  • s e.g., a backhaul interface
  • network configurations may be assisted using Artificial Intelligence (AI) or Machine Learning (ML) models to anticipate or predict future network conditions.
  • AI models may be used for UE trajectory (e.g., UE locations, movement directions) prediction and thereby assist in mobility optimization in serving cell selection and switching and resource configuration and allocation therein, all in advance.
  • An AI model generally contains a large number of model parameters that are determined through a training process where correlations in a set of training data are learned and embedded in the trained model parameters.
  • the trained model parameters may thus be used to generate inference from a set of input dataset that may not have existed in the training dataset.
  • AI models are particularly suitable for situations where there is few trackable deterministic, rule-based, or analytical derivation paths between input data and output.
  • determining adaptive network configuration and provisioning may rely on empirical characteristics and my further require lengthy measurement processes and/or significant amounts of computation power.
  • Such types of configurations and provisioning may include but are not limited to over-the-air interface beam management, channel state information (CSI) feedback compression and decompression, and most relevant to the current disclosure, provisioning of mobility of terminal between various network nodes (e.g., base stations) .
  • CSI channel state information
  • AI technology may be applied to beam management in the over-the-air communication interface.
  • beam management typically relies on the exhaustive searching beam sweeping.
  • the network may perform a full sweep of the beams by sending sufficient number of reference signals.
  • a UE may be configured to monitor and measure each reference signal and then report the measurement result to NW for the NW to decide the best beam for the UE to switch to. This process, however, is resource and power intensive. With trained AI models that embed learned correlation between various network condition parameters, few measurements (or fewer reference signals) may be needed in order to accurately infer the best beams.
  • AI model may help identify inference of best candidate beams using other network conditions and then only sweep and measure the candidate beams to select the beam for use in current communication. Additionally, as beam configuration is closed tied to a location of the UE, AI technology may further be used for inferring or predicting UE trajectory or location, thereby indirectly help selection of best beams.
  • AI technology may be applied to channel state information (CSI) feedback.
  • the CSI feedback may be implemented using a codebook known by UE and NW.
  • the UE may measure the CSI and obtain a measurement result, and then map the measurement result to a closest vector of the codebook, and transmit the index of that vector to the NW in order to save the air-interface resource consumption.
  • the codebook is not unlimited or dynamic changeable over time, there would be always mismatch, thereby causing un-controlled CSI feedback errors as the wireless environment varies.
  • AI thus may be applied to compression-decompression for CSI feedback.
  • a CSI report may be compressed by a UE-side AI model and decompressed by a corresponding NW-side AI model.
  • Such AI models may be initially trained and continuously developed over time and accumulation of network conditions.
  • AI technology may be applied to UE positioning.
  • Traditional approaches for UE positioning depend on PRS or SRS (e.g. DL Positional Reference Signal and uplink Sounding Reference Signal) .
  • the LOS (Line-Of-Sight) beams are the key beams to identify in order to generate the most precise location estimation by triangulation at the NW side.
  • NLOS Non-Line-Of-Sight
  • a trained AI model may identify various pattern and correlation in the PRS and SRS for extracting LOS information and providing more accurate UE positioning.
  • trajectories of a terminal device may be predicted using AI models trained based on historical network data. Correlation between such predicted terminal locations and mobility configuration may be used for the provisioning of the mobility terminal device in terms of selection of base stations to connect to and resource allocation and configuration for the terminal device during mobility of the terminal device.
  • the use of AI models for assisting in network configuraiton may thus help reduce the amount of measurements and computation requirement for efficient mobility provisioning.
  • AI/ML models may be trained and managed at the various network nodes described above, and may need to be delivered or transferred to another network nodes.
  • AI models that may be relied on for purpose of assisting with mobility provisional involving dual connectivity they may reside on either an MN or an SN.
  • These AI/ML models may be trained, retrained, updated at the MN or SN and used to perform prediction or inference at the MN or SN.
  • these AI/ML models may be trained, retrained, updated in some other network nodes (such as Operation Administration and Maintenance (OAM) nodes in the core network) and then delivered to the MN or SN to perform prediction or inference at the MN or SN.
  • OAM Operation Administration and Maintenance
  • these AI/ML models may reside in other network nodes (such as Operation Administration and Maintenance (OAM) nodes in the core network) , which may receive input data from the MN or SN, perform prediction and then communicate prediction outcome to the MN or SN.
  • OAM Operation Administration and Maintenance
  • theses AI/ML models may be trained and located in the CUs or trained in OAMs and delivered to the CUs for performing prediction or inference at the CUs.
  • these AI/ML Model may be training at the CUs or OAMs and delivered to the DUs, and the AI/ML Model prediction and inference function may be located in DUs.
  • the AI/ML Model training may be performed/deployed in an OAM, while the model inference may reside and be performed within a RAN node (an MN or SN) .
  • both the AI/ML Model training and the AI/ML Model inference may reside within the RAN (an MN or SN) node.
  • the AI/ML model training may be located in the CU or OAM, whereas the AI/ML Model inference may occur in the CU.
  • the AI/ML model training may be located in the CU or OAM whereas the AI/ML model inference may occur in the DU.
  • AI models may be employed to predict UE trajectories and other information pertaining to the UE or the network. Such predictions may be transmitted from a network node making the predictions to other network nodes involved in the mobility of the UE. For example, such predictions may be communicated from a source network node to candidate target network node (s) in preparation for or during a handover procedure. Such predictions may be used as a basis for a selection of a target network node and for the target network node to select a target serving cell for the UE for mobility purposes.
  • a mechanism may be designed in the coordination between the various network nodes for performing actual measurements corresponding to the AI predictions by appropriate network nodes. Such measurements may be fed back to the network nodes that manage the AI models or the network nodes that perform inferences (the predictions) for evaluation of the prediction performance of the AI models. The evaluation outcome may be further used for future selection of AI models, and for updating and retraining the AI models. For example, for UE mobility provisioning, actual UE trajectories and/or UE network performance may be measured as a feedback.
  • the actually measured feedback UE trajectories and performance may be reported and compared with the trajectories and performance as predicted by the AI models for evaluating the predictive accuracy of the AI models, and for deriving strategies for selecting different AI models for UE trajectory and/or performance prediction in the future and/or for deriving strategies for updating/retraining the existing AI models for predicting UE trajectories and performance.
  • Such a mechanism may involve configuring various types of network measurements and manners in which the network measurements are collected and reported. In addition, such a mechanism may be integrally considered with the normal mobility procedures and configuration based on AI predictions.
  • the general mechanism above for measurement feedback applies to UE mobility provisioning with or without involvement of dual connectivity.
  • An example general procedure may include a first base station (e.g., an NG-RAN node, also referred to as node 1) initiating a message targeting a second base station (e.g., another NG-RAN node, referred to as node 2) as a DATA COLLECTION REQUEST message to request and configure collection and report/feedback of the network measurements (such as UE trajectories and performance) .
  • node 1 may trigger a mobility management request message which may include AI predictions, e.g., predicted UE trajectory information to facilitate, e.g., cell selection for handover.
  • the predicted UE trajectory information may include predicted cell list which the UE may be connected to.
  • the mobility management request message may involve the same ID which is also involved in the DATA COLLECTION REQUEST message above such that the measurement request and the predictions included in the mobility request can be paired and correlated based on the same ID.
  • the target node (e.g., node 2) can prepare for and start collecting the configured measurements (e.g., actual UE trajectory measurements and/or UE performance measurements) , and reporting the feedback to the source node (e.g., node 1) .
  • the configured measurements e.g., actual UE trajectory measurements and/or UE performance measurements
  • an efficient communication procedure between various network nodes including the source MN, the source SN, the candidate target MNs, and candidate target SNs associated with the candidate target MNs, may be integrally designed with the dual connectivity mobility procedure, as described in further detail below.
  • UE mobility in a dual connect scenario may involve at least two network nodes, referred to as a first network node and a second network node (or network node 1 and network node 2) , as illustrated in the example procedure of FIG. 4.
  • the first network node and the second network node may each be any base station involved in the UE mobility provisioning above.
  • Each of the first network node and the second network node can establish a connection with a UE (alternatively referred to as a wireless terminal, a terminal, a wireless terminal device, and the like) .
  • the actual roles of the first network node and the second network node are further illustrated later in additional specific embodiments.
  • FIG. 4 shows the example general integral procedure for configuring, requesting, and reporting network measurements described above and for provisioning an AI-assisted UE mobility procedure between the first network node 402 and the second network node 404.
  • the example procedure of FIG. 4 may include several example steps as described in detail below.
  • the first network node 402 may initiate a Data Collection Request message to the second network node 404 to request a collecting and reporting of measurements.
  • the Data Collection Request message may include at least one of the following configurations or information elements (IEs) :
  • a Registration Request for Data Collection which may indicate network data that are to be measured, collected, and reported.
  • the Registration Request for Data Connection may include a bitmap with a plurality of bits corresponding to a set of data items to be measured, collected, and reported.
  • Each of the plurality of bits in the bitmap as included in the Registration Request for Data Collection may indicate whether a corresponding data item of the set of data items is to be measured, collected, and reported.
  • one bit in the example bitmap may be associated with and is used to indicate whether UE trajectories are to be measured, collected, and reported.
  • another bit in the bitmap above may indicate whether the UE performance feedback is to be measured, collected, and reported.
  • another bit in the bitmap above may indicate whether the UE traffic is to be measured, collected, and reported.
  • another bit in the bitmap above within the Registration Request for Data Collection may indicate whether secondary cell group (SCG) information associated with the UE is to be measured, collected, and reported.
  • SCG secondary cell group
  • Reporting Periodicity which may be used for reporting of requested objects.
  • the second network node 404 report measurements above according to this reporting periodicity. Otherwise, if this IE is not present in the Data Collection Request message, the measurements may be considered non-periodic and may be measured and collected and reported as a one-time measurement.
  • Number of Visited PSCell (s) , which may indicate a maximum number of PSCells that the UE will move through at which the data collection and measurement should be reported.
  • ⁇ Configuration for UE trajectory measurement/collection/report which may be used to configure the measurement, collection and/or report of UE trajectories.
  • ⁇ Configuration for UE performance feedback measurement/collection/report which may be used to configure the measurement of the UE performance feedback, and the collection or reporting of the UE performance feedback measurement.
  • Configuration for UE traffic data measurement/collection/report which may be used to configure the measurement, collection, and/or report of UE traffic.
  • Such configuration may specify a timing for the UE traffic data measurement/collection/report.
  • such configuration may specify a duration for the UE traffic data measurement and collection. Such duration may be specified with a start time and an end time. Alternatively, such duration may be specified with a start time and time length. Alternatively, such duration may be specified with a time length and an end time.
  • the second network node 404 may receive the Data Collection Request and proceed to configure, prepare for, and allocate resources for the requested data measurement, collection, and report.
  • the second network node 404 may respond to the first network node 402 via a Data Collection Response message to indicate to the first network node 402 that the requested information is successfully initiated and configured.
  • the first network node 402 may initiate a mobility management procedure for the UE by transmitting a Mobility Management Procedure Request to the second network node 404.
  • the Mobility Management Procedure Request message may include at least one of the following predicted information items by the AI functions pertaining to UE mobility involving due connectivity:
  • ⁇ Predicted UE trajectory which may include at least one of:
  • a predicted PSCell List including PSCell IDs which UE will be connected to, as predicted by the AI models.
  • a predicted PCell List including PCell IDs which UE will be connected to, as predicted by the AI models.
  • a predicted Cell List including Cell IDs which UE will be connected to without dual connectivity, as predicted by the AI models.
  • a predicted number of PSCell (s) to be prepare which indicates a predicted maximum number of PSCells that a target SN may prepare.
  • Predicted UE traffic information by the AI models which may include at least one of a predicted uplink Usage Count, and/or predicted downlink Usage Count for the UE.
  • the Mobility Management Procedure Request message may further include a Data Collection ID in addition to the prediction information items above, which may include the Measurement ID for the first network node (node 1) and the measurement ID for the second network node (node 2) described above, for the purposes of correlating the data measurement and collection request above in Step 1 with the mobility procedure requested in Step 2.
  • a Data Collection ID in addition to the prediction information items above, which may include the Measurement ID for the first network node (node 1) and the measurement ID for the second network node (node 2) described above, for the purposes of correlating the data measurement and collection request above in Step 1 with the mobility procedure requested in Step 2.
  • the second network node may report to a source base station (e.g., the first network node 402) after completion of the mobility management procedure, via, for example, a Data Collection Reporting procedure, the requested information items configured via the network Data Collection Request of Step 1 corresponding to the RAN node 1 Measurement ID and the RAN node 2 Measurement ID therein.
  • a source base station e.g., the first network node 402
  • the requested information items configured via the network Data Collection Request of Step 1 corresponding to the RAN node 1 Measurement ID and the RAN node 2 Measurement ID therein.
  • the second network node 404 may receive the Mobility Management Procedure Request from the first network node 402 and acknowledge by transmitting a Mobility Management Procedure Acknowledgement message to the first network node 402.
  • the Mobility Management Procedure Acknowledgement message may be used to confirm that the mobility management procedure has been or is being prepared by the second network node 404 according to the Mobility Management Procedure Request.
  • the second network node 404 may then perform the requested mobility management procedure, taking into consideration of the predicted information included in the Mobility Management Procedure Request above, with or without assistance from other additional network nodes, and then transmit a Mobility Management Procedure Complete message to the first network node 402.
  • This message may indicate to the first network node 402 whether the configuration requested by the first network node 402 in the Mobility Management Procedure Request has been completed and has been applied by the UE.
  • This message may include one or more Data Collection IDs, including the RAN node 1 Measurement ID and RAN node 2 Measurement ID described above for correlating the message to the earlier data collection request message in Step 1, which was separate from the mobility management procedure request.
  • the second network node 404 may trigger a Data Collection Update message to report the requested information items for report in the Data Collection Request message of Step 1 above.
  • the Data Collection Update message may include one or more measured UE performance feedback information items, one or more measured UE trajectory information items, or one or more UE traffic information items.
  • the one or more measured UE performance feedback information items in the Data Collection Update message above may, for example, include at least one of:
  • the one or more measured UE trajectory information items in the Data Collection Update message above may, for example, include at least one of:
  • Measured PSCell List including IDs of PSCells served by an SN (e.g., the second network node) ;
  • Measured PCell List including IDs of PCells served by an MN (e.g., the first network node) ;
  • Measured UE Location List includes the geographic coordinates of the UE locations.
  • the one or more measured UE traffic information items in the Data Collection Update message above may, for example, include at least one of an uplink Usage Count and/or a downlink Usage Count for the UE.
  • the procedure described in FIG. 4 may be UE specific and may be applied to each mobility management or mobility provisioning procedure.
  • predictions provided by AI models for assisting mobility provisioning of a UE may be utilized in a mobility management procedure.
  • network measurement such as UE trajectories, UE performance, and UE traffic may be configured, performed, and reported between the various network nodes involved in provisioning the UE mobility, particularly involving dual connectivity, so as to be used as feedback for evaluating predictive performance of the AI models and for future selection and training of more accurate AI models.
  • the first network node 402 and the second network node 404 above in FIG. 4 may be any access network nodes or base station involved in the mobility provisioning and management of the UE. Each of these network nodes may be associated with one or more cells.
  • the various additional example implementations below apply the general procedure of FIG. 4 in various mobility management/provisioning scenarios involving dual connectivity.
  • the term “mobility management procedure” or “mobility provisional procedure” may refer to a procedure that can in some way affect connectivity of the UE during mobility, and may include but is not limited to MN initiated SN addition, MN initiated SN modification, handover from a source MN to a target MN.
  • the general procedure of FIG. 4 may be applied to an MN initiated SN addition procedure for a specific UE together with the data collection request and reporting procedure, as shown in FIG. 5.
  • the first network node 402 of FIG. 4 may be implemented as an MN in FIG. 5, whereas the second network node 404 of FIG. 4 may be implemented as an SN in FIG. 5 to be added for serving the UE as a secondary node associated with the MN.
  • the Mobility Management Procedure, the Mobility Management Procedure Request message, the Mobility Management Procedure Acknowledge message, and the Mobility Management Procedure Complete Message of FIG. 4 may be respectively implemented in FIG. 5 as SN Addition Procedure, SN Addition Request message, SN Addition Request Acknowledge Message, and SN Reconfiguration Complete message.
  • the Data Collection Request message may contain similar information element with respect to the configuration of data measurement, collection, and report for network data feedback in facilitating evaluation of the AI models involved in generating prediction for assisting with the SN addition procedure.
  • the SN addition Request may, include prediction and identification information elements similar to that of the Mobility MANAGEMENT Procedure Request of FIG. 4, as described in detail above.
  • the Data collection Update message may include similar reporting information items related to requested measurements to the Data Collection Update message of FIG. 4, as described above, including for example, UE trajectory measurement, UE performance measurement, UE traffic information, and the like.
  • the general procedure of FIG. 4 may be applied to an MN initiated SN modification procedure for a specific UE together with the data collection request and reporting procedure, as shown in FIG. 6.
  • the first network node 402 of FIG. 4 may be implemented as an MN in FIG. 6, whereas the second network node 404 of FIG. 4 may be implemented as an SN in FIG. 6 to be modified for serving the UE as a secondary node associated with the MN.
  • the Mobility Management Procedure, the Mobility Management Procedure Request message, the Mobility Management Procedure Acknowledge message, and the Mobility Management Procedure Complete Message of FIG. 4 may be respectively implemented in FIG. 5 as SN Modification Procedure, SN Modification Request message, SN Modification Request Acknowledge Message, and SN Reconfiguration Complete message.
  • the Data Collection Request message may contain similar information element with respect to the configuration of data measurement, collection, and report for network data feedback in facilitating evaluation of the AI models involved in generating prediction for assisting with the SN modification procedure.
  • the SN Modification Request may, include prediction and identification information elements similar to that of the Mobility MANAGEMENT Procedure Request of FIG. 4, as described in detail above.
  • the Data collection Update message may include similar reporting information items related to requested measurements to the Data Collection Update message of FIG. 4, as described above, including for example, UE trajectory measurement, UE performance measurement, UE traffic information, and the like.
  • the general procedure of FIG. 4 may be applied to an inter-MN handover procedure for a specific UE together with the data collection request and reporting procedure, as shown in FIG. 7.
  • the first network node 402 of FIG. 4 may be implemented as a source MN of FIG. 7, whereas the second network node 404 of FIG. 4 may be implemented as a target MN of FIG. 7 to which the UE is being handed over by the source MN.
  • the Mobility Management Procedure, the Mobility Management Procedure Request message, the Mobility management Procedure Acknowledge message of FIG. 4 may be respectively implemented in FIG. 7 as handover Procedure, Handover Request message, Handover Request Acknowledge Message.
  • the example procedure of FIG. 7 further involves a source SN and a target SN associated with the target MN.
  • the Mobility Management Procedure Complete message of FIG. 4 would be transmitted from the target SN to the target MN in Step 12 of FIG. 7 as a SN Reconfiguration Complete message.
  • the example inter-MN handover procedure of FIG. 7 includes the following steps.
  • the source MN may initiate a Data Collection Request message to the target MN to request a collecting and reporting of measurements.
  • the Data Collection Request message may include at least one of the information elements similar to that included in the Data Collection Request message of FIG. 4 as described in detail above.
  • the target MN may receive the Data Collection Request and proceed to configure, prepare for, and allocate resources for the requested data measurement, collection, and report.
  • the target MN may respond to the source MN via a Data Collection Response message to indicate to the source MN that the requested information is successfully initiated and configured.
  • the target MN may initiate a Data Collection Request message to the target SN to request the measurement, collection, and reporting of the information.
  • the Data Collection Request message may include at least one of the information items similar to those included in the Data Collection Request message of FIG. 4 as described in detail above.
  • the target SN may respond to the target MN via a Data Collection Response message to indicate to the target MN that the requested information is successfully initiated and configured.
  • the source MN may start the handover procedure by initiating, e.g., an Xn Handover Preparation procedure.
  • the Handover Request Message may include, in addition other information items, the AI-predicted information items and measurement IDs similar to the information items included in the Mobility Management Procedure Request message of FIG. 4 as described in detail above.
  • the target MN may trigger an SN Addition Request message to the target SN.
  • the SN addition Request message may include, in addition to other information elements, AI-predicted information items and measurement IDs similar to those included in the Mobility Management Procedure Request of FIG. 4 as described in detail above.
  • the target SN may transmit an SN Addition Request Acknowledge message to the target MN to confirm to the target MN about the SN addition preparation.
  • the target MN may transmit a Handover Request Acknowledge message to the source MN to inform the source MN about the prepared resources at the target MN.
  • the source MN may send an SN Release Request message to the source SN including, for example, a cause for the release indicating master cell group (MCG) mobility.
  • the source SN may further acknowledge the release request.
  • the target MN may transmit an SN Reconfiguration Complete message to the target SN to indicate whether the configuration requested by the target SN was applied by the UE.
  • This message may include the measurement ID for associated with the source MN and the measurement ID associated with the target MN.
  • the target SN may trigger a Data Collection Update message to the target MN to report the requested information upon the request, including at least one of the information items similar to those included in the Data Collection Update message of FIG. 4, as described in detail above.
  • the target MN may trigger a Data Collection Update message to the source MN to report the requested information upon the request, including at least one of the information items similar to those included in the Data Collection Update message of FIG. 4, as described in detail above.
  • the UE may be currently communicating with a base station without dual connectively and may change to a dual connectivity mode by being hand over to a target MN.
  • the general procedure of FIG. 4 may be applied to such a scenario, as shown in FIG. 8.
  • the first network node 402 of FIG. 4 may be implemented as a non-DC network node of FIG. 8, whereas the second network node 404 of FIG. 4 may be implemented as a target MN in FIG. 8 for handover of the UE.
  • the Mobility Management Procedure, the Mobility Management Procedure Request message, and the Mobility Management Procedure Acknowledge message of FIG. 4 may be respectively implemented in FIG. 8 as a handover Procedure, Handover Request message, and Handover Request Acknowledge Message.
  • the example procedure of FIG. 8 further involves a target SN associated with the target MN.
  • the Mobility Management Procedure Complete message of FIG. 4 would be transmitted from the target SN to the target MN in Step 9 of FIG. 7 as a SN Reconfiguration Complete message.
  • the example inter-MN handover procedure of FIG. 8 may include the following steps.
  • the non-DC network node may initiate a Data Collection Request message to the target MN to request a collecting and reporting of measurements.
  • the Data Collection Request message may include at least one of the information elements similar to that included in the Data Collection Request message of FIG. 4 as described in detail above.
  • the target MN may receive the Data Collection Request and proceed to configure, prepare for, and allocate resources for the requested data measurement, collection, and report.
  • the target MN may respond to the non-DC network node via a Data Collection Response message to indicate to the non-DC network node that the requested information is successfully initiated and configured.
  • the target MN may initiate a Data Collection Request message to the target SN to request the measurement, collection, and reporting of the information.
  • the Data Collection Request message may include at least one of the information items similar to those included in the Data Collection Request message of FIG. 4 as described in detail above.
  • the target SN may respond to the target MN via a Data Collection Response message to indicate to the target MN that the requested information is successfully initiated and configured.
  • the non-DC network node may start the handover procedure by initiating, e.g., an Xn Handover Preparation procedure.
  • the Handover Request Message may include, in addition other information items, the AI-predicted information items and measurement IDs similar to the information items included in the Mobility Management Procedure Request message of FIG. 4 as described in detail above.
  • the target MN may trigger an SN Addition Request message to the target SN.
  • the SN addition Request message may include, in addition to other information elements, AI-predicted information items and measurement IDs similar to those included in the Mobility Management Procedure Request of FIG. 4 as described in detail above
  • the target SN may transmit an SN Addition Request Acknowledge message to the target MN to confirm to the target MN about the SN addition preparation.
  • the target MN may transmit a Handover Request Acknowledge message to the source MN to inform the source MN about the prepared resources at the target MN.
  • the target MN may transmit an SN Reconfiguration Complete message to the target SN to indicate whether the configuration requested by the target SN was applied by the UE.
  • This message may include the measurement ID for associated with the source MN and the measurement ID associated with the target MN.
  • the target SN may trigger a Data Collection Update message to the target MN to report the requested information upon the request, including at least one of the information items similar to those included in the Data Collection Update message of FIG. 4, as described in detail above.
  • the target MN may trigger a Data Collection Update message to the non-DC network node to report the requested information upon the request, including at least one of the information items similar to those included in the Data Collection Update message of FIG. 4, as described in detail above.
  • the general procedure of FIG. 4 may be applied to an SN initiated SN modification procedure for a specific UE together with the data collection request and reporting procedure, as shown in FIG. 9.
  • the first network node 402 of FIG. 4 may be implemented as an SN in FIG. 9, whereas the second network node 404 of FIG. 4 may be implemented as an MN in FIG.
  • the SN of FIG. 9 may initiate an SN modification procedure for serving the UE as a secondary node associated with the MN.
  • the Mobility Management Procedure, the Mobility Management Procedure Request message, and the Mobility Management Procedure Complete Message of FIG. 4 may be respectively implemented in FIG. 9 as SN Initiated Modification Procedure, SN Modification Required message, and SN Modification Confirm Message.
  • the Data Collection Request message may contain similar information element with respect to the configuration of data measurement, collection, and report for network data feedback in facilitating evaluation of the AI models involved in generating prediction for assisting with the SN modification procedure.
  • the SN Modification Required message may, include prediction and identification information elements similar to that of the Mobility MANAGEMENT Procedure Request of FIG. 4, as described in detail above.
  • the Data collection Update message may include similar reporting information items related to requested measurements to the Data Collection Update message of FIG. 4, as described above, including for example, UE trajectory measurement, UE performance measurement, UE traffic information, and the like.
  • terms, such as “a, ” “an, ” or “the, ” may be understood to convey a singular usage or to convey a plural usage, depending at least in part upon context.
  • the term “based on” may be understood as not necessarily intended to convey an exclusive set of factors and may, instead, allow for existence of additional factors not necessarily expressly described, again, depending at least in part on context.

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Abstract

La présente divulgation concerne de manière générale une double connectivité (DC) sans fil intelligente et concerne spécifiquement des procédés et des dispositifs de réseau pour la collecte et le rapport de données de réseau pour aider à des fonctions d'intelligence artificielle (IA) pour une DC dans des systèmes de communication sans fil cellulaire. Par exemple, lorsque des modèles d'IA sont utilisés pour faciliter une procédure de mobilité dans des scénarios impliquant une DC, une mesure de réseau et des procédures de rapport entre un nœud maître source (MN), un ou plusieurs nœuds secondaires (SN), un MN cible et un ou plusieurs SN cibles peuvent être mis en œuvre pour mesurer et collecter des données de réseau à des fins d'évaluation des performances des modèles d'IA et pour déclencher la mise à jour et la conservation des modèles d'IA. De telles mesures et de tels rapports de données de réseau peuvent être configurés de telle sorte que les divers nœuds de réseau peuvent être prêts pour de telles mesures de données de réseau avant une procédure de mobilité et peuvent fournir un rapport en temps opportun et adapté. De telles mesures de données de réseau peuvent en particulier concerner des trajectoires mesurées et des performances de réseau de dispositifs terminaux, par rapport à des trajectoires et des performances prédites par IA pour les dispositifs terminaux.
PCT/CN2024/085751 2024-04-03 2024-04-03 Collecte et rapport de données pour aider à des fonctions d'intelligence artificielle dans une connectivité double sans fil Pending WO2025156418A1 (fr)

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