Communication methods, devices and systems

Abstract

This disclosure proposes a communication method, apparatus, and system, relating to the field of mobile communication technology. The communication method is executed by a Data Collection Coordination Function (DCCF) network element, including: receiving a data acquisition request sent by a Network Data Analysis Function (NWDAF) network element; determining whether training data corresponding to the data acquisition request has been collected; if no training data corresponding to the data acquisition request has been collected, sending a data subscription request to a Sensing Function (SF) network element; receiving training data sent by the SF network element in response to the data subscription request, and then sending the training data sent by the SF network element to the NWDAF network element. By introducing the DCCF network element, which works in conjunction with the NWDAF and SF network elements to execute the above training data collection process, the efficiency of training data collection is improved, thereby enhancing the performance and response speed of the integrated sensing network.

Description

Technical Field

[0001] This disclosure relates to the field of mobile communication technology, and in particular to a communication method, apparatus and system. Background Technology

[0002] With the development of wireless communication technology and the increasing demand for high-quality data transmission, communication systems are evolving towards higher levels. Against this backdrop, the integration of sensing and communication technologies has become a highly anticipated cutting-edge technology. The core idea of ​​sensing integration is to utilize radio frequency (RF) signals to simultaneously achieve sensing and communication functions. This allows us to achieve real-time environmental monitoring and rapid data transmission without adding extra hardware burdens, and can be used to optimize network resource allocation and improve overall network efficiency.

[0003] In addition, the integrated sensing technology can provide users with richer and more accurate services, such as location-based personalized recommendations and intelligent traffic management, thereby significantly improving the user experience and providing strong technical support for various intelligent applications.

[0004] In the research of sensor network architecture, a sensing function (SF) can be introduced into the core network to collect and process environmental sensing data, and a network data analytics function (NWDAF) can be introduced to perform model training, inference and judgment, and intelligent prediction.

[0005] Among related technologies, intelligent perception based on artificial intelligence / machine learning (AI / ML) models is achieved through the collaboration of core network elements such as SF and NWDAF. Summary of the Invention

[0006] This disclosure provides a communication method, apparatus, and system.

[0007] According to a first aspect of this disclosure, a communication method is provided, executed by a Data Collection Coordination Function (DCCF) network element, comprising: receiving a data acquisition request sent by a Network Data Analysis Function (NWDAF) network element, wherein the data acquisition request is used to request the acquisition of training data required for training a machine learning model; determining whether training data corresponding to the data acquisition request has been collected; if training data corresponding to the data acquisition request has not been collected, sending a data subscription request to a Sensing Function (SF) network element; receiving training data sent by the SF network element in response to the data subscription request, and sending the training data sent by the SF network element to the NWDAF network element, wherein the NWDAF network element is used to train the machine learning model.

[0008] In some embodiments, the communication method further includes: sending the collected training data to the NWDAF network element if the training data has been collected.

[0009] In some embodiments, determining whether training data corresponding to the data acquisition request has been collected includes: determining whether the user device being collected, corresponding to the training data, agrees to have its data collected; and if the user device being collected agrees to have its data collected, determining whether training data corresponding to the data acquisition request has been collected.

[0010] In some embodiments, determining whether the user equipment corresponding to the training data agrees to have its data collected includes: determining the identifier of the user equipment corresponding to the training data based on the data acquisition request; querying the unified data management UDM network element based on the identifier of the user equipment to obtain the subscription information of the user equipment; and determining whether the user equipment agrees to have its data collected based on the subscription information of the user equipment.

[0011] In some embodiments, the contract information includes data type and data collection purpose. Determining whether the user device agrees to have its data collected based on the contract information of the user device includes: if the data type indicates that the user device agrees to the data collection behavior and the data collection purpose indicates that the user device agrees to use the collected data for model training, then the user device agrees to have its data collected; otherwise, the user device does not agree to have its data collected.

[0012] In some embodiments, the communication method further includes: sending a subscription message to the UDM network element when the user equipment being collected agrees to have its data collected, wherein the subscription message is used to instruct the UDM network element to notify the DCCF network element when the subscription information of the user equipment being collected changes.

[0013] In some embodiments, the communication method further includes: sending a response to the NWDAF network element refusing to acquire data when the user equipment being collected does not agree to have its data collected, wherein the response to refusing to acquire data includes a reason for refusal.

[0014] In some embodiments, the communication method further includes: when the data acquisition request includes first storage indication information or the DCCF network element is pre-configured with second storage indication information, after receiving the training data from the SF network element, storing the training data to the Analysis Data Storage Function (ADRF) network element, wherein the first storage indication information and the second storage indication information are used to indicate storing the training data to the ADRF network element.

[0015] According to a second aspect of this disclosure, a communication apparatus is provided, disposed in a data collection coordination function (DCCF) network element, comprising: a module for performing the communication method as described above.

[0016] According to a third aspect of this disclosure, a communication apparatus is provided, disposed in a data collection coordination function (DCCF) network element, comprising: a memory; and a processor coupled to the memory, the processor being configured to execute the communication method as described above based on instructions stored in the memory.

[0017] According to a fourth aspect of this disclosure, a communication system is provided, comprising: a DCCF network element configured to include the communication device as described above; an SF network element configured to collect training data in response to a data subscription request sent by the DCCF network element and to send the training data to the DCCF network element; and an NWDAF network element configured to send a data acquisition request to the DCCF network element and to train a machine learning model based on the training data acquired from the DCCF network element.

[0018] In some embodiments, the SF network element is configured to: collect the training data according to the perception mode indication information when the data subscription request carries perception mode indication information or the SF network element is pre-configured with perception mode indication information.

[0019] In some embodiments, the SF network element is further configured to send a model subscription request to the NWDAF network element after receiving a service awareness request from an Access and Mobility Management Function (AMF) network element, thereby triggering the NWDAF network element to execute the operation of sending a data acquisition request to the DCCF network element; the NWDAF network element is further configured to send a trained machine learning model to the SF network element; the SF network element is further configured to use the trained machine learning model and the collected perception measurement data to obtain a perception result corresponding to the service awareness request, and send the perception result to the AMF network element.

[0020] According to a fifth aspect of this disclosure, a computer-readable storage medium is provided that stores computer instructions thereon, which, when executed by a processor, implement the communication method as described above.

[0021] According to a sixth aspect of this disclosure, a computer program product is provided having computer instructions stored thereon that, when executed by a processor, implement the communication method as described above.

[0022] Other features and advantages of this disclosure will become clear from the following detailed description of exemplary embodiments with reference to the accompanying drawings. Attached Figure Description

[0023] The accompanying drawings, which form part of this specification, illustrate embodiments of this disclosure and, together with the specification, serve to explain the principles of this disclosure.

[0024] Figure 1 This is a flowchart illustrating a communication method according to some embodiments of the present disclosure;

[0025] Figure 2 This is a flowchart illustrating a communication method according to other embodiments of this disclosure;

[0026] Figure 3 This is a flowchart illustrating a communication method performed by multiple parties according to some embodiments of this disclosure;

[0027] Figure 4 This is a flowchart illustrating a communication method performed by multiple parties according to other embodiments of this disclosure;

[0028] Figure 5 This is a schematic diagram of the structure of a communication device according to some embodiments of the present disclosure;

[0029] Figure 6 This is a schematic diagram of the structure of a communication device according to other embodiments of the present disclosure;

[0030] Figure 7 This is a schematic diagram of the structure of a communication system according to some embodiments of the present disclosure.

[0031] This disclosure can be more clearly understood with reference to the accompanying drawings and the following detailed description. Detailed Implementation

[0032] Various exemplary embodiments of the present disclosure will now be described in detail with reference to the accompanying drawings. It should be noted that, unless otherwise specifically stated, the relative arrangement, numerical expressions, and values ​​of the components and steps set forth in these embodiments do not limit the scope of the present disclosure.

[0033] At the same time, it should be understood that, for ease of description, the dimensions of the various parts shown in the accompanying drawings are not drawn according to actual scale.

[0034] The following description of at least one exemplary embodiment is merely illustrative and is in no way intended to limit this disclosure or its application or use.

[0035] Techniques, methods, and equipment known to those skilled in the art may not be discussed in detail, but where appropriate, such techniques, methods, and equipment should be considered part of the specification.

[0036] In all examples shown and discussed herein, any specific values ​​should be interpreted as merely exemplary and not as limitations. Therefore, other examples of exemplary embodiments may have different values.

[0037] It should be noted that similar labels and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be discussed further in subsequent figures.

[0038] To make the objectives, technical solutions, and advantages of this disclosure clearer, the following detailed description is provided in conjunction with specific embodiments and the accompanying drawings.

[0039] The inventors of this disclosure have discovered that in the process of intelligent sensing based on artificial intelligence / machine learning models, there are problems of resource waste and network overload caused by repeated data collection, which affect the performance and response speed of the integrated sensing network.

[0040] In view of this, this disclosure proposes a communication method, apparatus and system that can solve the problems existing in related technologies and improve the performance and response speed of integrated sensing networks.

[0041] Figure 1 This is a flowchart illustrating a communication method according to some embodiments of the present disclosure. Figure 1 As shown, the communication method is executed by the Data Collection Coordination Function (DCCF) network element, including steps S11 to S14.

[0042] Step S11: Receive the data acquisition request sent by the NWDAF network element.

[0043] In some examples, the Network Data Analytics Function (NWDAF) network element sends a data retrieval request to the DCCF network element before training the machine learning model. This data retrieval request is used to request the training data needed to train the machine learning model.

[0044] The data acquisition request may include at least one of an event identifier, a target user equipment identifier, and a target range. The event identifier indicates the type of sensing service, the target user equipment identifier indicates which user equipment is provided with the sensing service, and the target range indicates the cell where the target user equipment is located. By including this information in the data acquisition request, it facilitates the collection of necessary training data by the DCCF network element. Furthermore, the data acquisition request may also include first storage indication information. This first storage indication information instructs that, in addition to returning the training data to the NWDAF network element, the training data should also be stored in the Analytics Data Repository Function (ADRF) network element.

[0045] Step S12: Determine whether the training data corresponding to the data acquisition request has been collected.

[0046] In some embodiments, step S12 includes: determining whether training data corresponding to the data acquisition request exists locally; if training data corresponding to the data acquisition request exists locally, it indicates that training data corresponding to the data acquisition request has been collected; otherwise, it indicates that training data corresponding to the data acquisition request has not been collected.

[0047] For example, the DCCF network element retrieves local data based on the event identifier carried in the data acquisition request; if training data corresponding to the above information carried in the data acquisition request exists locally, it indicates that the training data corresponding to the data acquisition request has been collected; otherwise, it indicates that the training data corresponding to the data acquisition request has not been collected.

[0048] For example, the DCCF network element retrieves local data based on the event identifier, target user equipment identifier, and target range carried in the data acquisition request. If training data corresponding to the above information carried in the data acquisition request exists locally, it indicates that training data corresponding to the data acquisition request has been collected; otherwise, it indicates that training data corresponding to the data acquisition request has not been collected.

[0049] In some other embodiments, step S12 includes: determining whether training data corresponding to the data acquisition request exists locally; if it exists, determining whether the training data corresponding to the data acquisition request is available; if the training data existing locally is available, it indicates that the training data corresponding to the data acquisition request has been collected; otherwise, it indicates that the training data corresponding to the data acquisition request has not been collected.

[0050] For example, the DCCF network element retrieves local data based on the event identifier, target user equipment identifier, and target range carried in the data acquisition request. If training data corresponding to the aforementioned information carried in the data acquisition request exists locally, its availability can be determined based on at least one of the following: the acquisition time of the training data and its availability status field. For instance, if the interval between the acquisition time of the training data and the current time is greater than a set threshold, the training data is determined to be unavailable; otherwise, it is determined to be available. Another example is that if the status field of the training data is at the first value, the training data is determined to be available; if the status field is at the second value, the training data is determined to be unavailable.

[0051] Step S13: If no training data corresponding to the data acquisition request has been collected, send a data subscription request to the SF network element.

[0052] In some examples, DCCF network elements can send data subscription requests to SF network elements based on the Nnf_EventExposure_Subscribe service.

[0053] The data subscription request can carry the address indication information of the DCCF network element. By enabling the data subscription request to carry the address indication information of the DCCF network element, the SF network element can accurately and timely return the collected training data to the DCCF network element.

[0054] In some examples, the data subscription request may also carry sensing mode indication information. This sensing mode indication information is used to indicate which sensing mode the SF network element uses to collect training data. For example, the sensing mode indication information can be specifically represented by the value of the sensing mode identifier field. When the sensing mode identifier field has a first value, it indicates that the SF network element uses the base station self-transmitting and self-receiving sensing mode to collect data; when the sensing mode identifier field has a second value, it indicates that the SF network element uses the base station inter-transmitting and receiving sensing mode to collect data; when the sensing mode identifier field has a third value, it indicates that the SF network element uses the user equipment transmitting and receiving sensing mode to collect data; when the sensing mode identifier field has a fourth value, it indicates that the SF network element uses the user equipment self-transmitting and self-receiving sensing mode to collect data; when the sensing mode identifier field has a fifth value, it indicates that the SF network element uses the user equipment inter-transmitting and receiving sensing mode to collect data; and when the sensing mode identifier field has a sixth value, it indicates that the SF network element uses the base station transmitting and receiving sensing mode to collect data. By having the data subscription request carry the perception mode indication information, it is easier for SF network elements to use the perception mode indicated by DCCF network elements to collect training data, which helps to improve the efficiency of training data collection.

[0055] In some examples, the data subscription request may also carry indication information about the devices from which data will be collected. This indication information tells the SF network element which user equipment to collect data from. By including this indication information in the data subscription request, the SF network element can collect training data from devices specified by the DCCF network element without needing to perform a device selection process, thus improving the efficiency of training data collection.

[0056] Step S14: Receive the training data sent by the SF network element and send the training data sent by the SF network element to the NWDAF network element.

[0057] After receiving a data subscription request, the SF network element collects the required training data and sends the collected training data to the DCCF network element. The DCCF network element receives the training data sent by the SF network element and sends it to the NWDAF network element so that the NWDAF network element can train a machine learning model based on this training data.

[0058] In some embodiments, the communication method further includes: when it is determined that training data corresponding to the data acquisition request has been collected, the DCCF network element sends the collected training data to the NWDAF network element.

[0059] In this embodiment of the disclosure, by introducing the DCCF network element, which works in conjunction with the NWDAF network element and the SF network element to execute the above training data collection process, the efficiency of training data collection is improved, thereby improving the performance and response speed of the integrated sensor network.

[0060] Figure 2 This is a flowchart illustrating a communication method according to other embodiments of this disclosure. For example... Figure 2 As shown, the communication method is executed by the DCCF network element, including steps 201 to 210.

[0061] Step 201: Receive the data acquisition request sent by the NWDAF network element.

[0062] In some examples, the data acquisition request includes an event identifier, a target user device identifier, and a target range. Additionally, the data acquisition request may also include first storage indication information.

[0063] Step 202: Determine whether the user device agrees to have its data collected.

[0064] Step 202 can be implemented in various ways. Two implementation methods are described below as examples.

[0065] In the first implementation, step 202 includes: determining the identifier of the user equipment to be collected corresponding to the training data based on the data acquisition request; querying the Unified Data Management (UDM) network element based on the identifier of the user equipment to obtain the subscription information of the user equipment; and determining whether the user equipment agrees to have its data collected based on the subscription information of the user equipment.

[0066] In some examples, the contract information includes data types. In these examples, determining whether the user device consents to the data collection based on the contract information includes: if the data type indicates that the user device consents to the data collection, then the user device consents to the data collection; otherwise, the user device does not consent to the data collection.

[0067] In other examples, the contract information includes the data type and the purpose of data collection. In these examples, determining whether the user device consents to the data collection based on the contract information includes: if the data type indicates that the user device consents to the data collection and the purpose of data collection indicates that the user device consents to the use of the collected data for model training, then the user device consents to the data collection; otherwise, the user device does not consent to the data collection.

[0068] In the second embodiment, step 202 includes: determining the identifier of the user equipment to be collected corresponding to the training data based on the data acquisition request; instructing the SF network element to send a collection authorization request to the user equipment to be collected based on the identifier of the user equipment to be collected; and determining whether the user equipment to be collected agrees to have its data collected based on the collection authorization response returned by the SF network element.

[0069] For example, the DCCF network element first determines the identifier of the user equipment being collected corresponding to the training data based on information such as the event identifier and the target UE identifier carried in the data acquisition request; then it instructs the SF network element to send a collection authorization request to these user equipments; if the SF network element receives a response from these user equipments agreeing to data collection, it sends a first collection authorization response to the DCCF network element so that the DCCF network element knows that these user equipments agree to have their data collected; if the SF network element receives a response from these user equipments rejecting data collection, it sends a second collection authorization response to the DCCF network element so that the DCCF network element knows that these user equipments do not agree to have their data collected.

[0070] In practical implementation, considering that there may be multiple user equipments being collected, the determination result of step 202 can be confirmed as "yes" when at least some of the user equipments agree to have their data collected. Subsequently, the DCCF network element can instruct the SF network element to collect data from these user equipments that have agreed to have their data collected. In addition, in some other embodiments, the determination result of step 202 can also be confirmed as "yes" when all user equipments agree to have their data collected.

[0071] If the result of the judgment in step 202 is yes, proceed to step 203; otherwise, proceed to step 210.

[0072] In some embodiments, the communication method further includes: if the determination result in step 202 is yes, sending a subscription message to the UDM network element. This subscription message instructs the UDM network element to notify the DCCF network element when the subscription information of the user equipment being collected changes. For example, if the user equipment agrees to data collection, the DCCF network element uses the Nudm_SDM_Subscribe service to subscribe to the UDM network element for notifications of changes to the data type and data collection purpose in the user equipment's subscription information. Through these operations, a timely response can be provided after the user equipment changes its subscription information, further improving the security of training data collection.

[0073] In this embodiment of the disclosure, by having the DCCF network element determine whether the user equipment agrees to have its data collected, and then performing subsequent steps such as data collection and returning the collected data to the NWDAF network element after the user equipment agrees to have its data collected, the security of collecting training data in the intelligent sensing process based on machine learning models can be improved, the privacy of user data can be better protected, and the user experience of the integrated sensing network service can be improved.

[0074] Step 203: Determine whether the training data has been collected.

[0075] In step 203, it is determined whether the training data corresponding to the data acquisition request has been collected. For details on how step 203 is executed, please refer to the relevant descriptions in the foregoing embodiments.

[0076] If the result of the judgment in step 203 is yes, proceed to steps 204 and 205; otherwise, proceed to steps 206 to 209.

[0077] In some embodiments, the communication method further includes: if the determination result in step 203 is negative, adding the NWDAF network element to the list of data consumers who have subscribed to the training data.

[0078] Step 204: Send the collected training data to the NWDAF network element.

[0079] In some embodiments, the communication method further includes: when it is determined that training data corresponding to the data acquisition request has been collected, the DCCF network element adds the NWDAF network element to the data consumer list corresponding to the training data. Maintaining the data consumer list facilitates understanding the consumption status of various types of training data.

[0080] Step 205: Store the collected training data into the ADRF network element.

[0081] In some examples, when the data acquisition request includes first storage indication information, the DCCF network element, in addition to returning the collected training data corresponding to the data acquisition request to the NWDAF network element, also stores the collected training data in the ADRF network element according to the first storage indication information. The first storage indication information is used to instruct the training data to be stored in the ADRF network element.

[0082] In other examples, when the DCCF network element is pre-configured with second storage indication information, in addition to returning the collected training data corresponding to the data acquisition request to the NWDAF network element, the DCCF network element also stores the collected training data in the ADRF network element according to the second storage indication information. The second storage indication information is used to instruct the collected training data to be stored in the ADRF network element. By storing the training data in the ADRF network element, long-term storage and analysis of the training data are facilitated, improving the flexibility of the integrated sensing network service.

[0083] It should be noted that this embodiment is illustrated by executing step 204 first and then step 205. In actual implementation, step 205 can be executed first, followed by step 204. Alternatively, steps 204 and 205 can be executed simultaneously.

[0084] Step 206: Send a data subscription request to the SF network element.

[0085] In some examples, the DCCF network element uses the Nnf_EventExposure_Subscribe service to send a data subscription request to the SF network element. This data subscription request may include the address indication information of the DCCF network element.

[0086] Step 207: Receive training data sent by SF network elements.

[0087] After receiving a data subscription request, the SF network element collects data for model training from the user equipment and / or radio access network (RAN) according to the sensing mode (e.g., base station self-transmission and reception sensing mode, inter-base station transmission and reception sensing mode, user equipment transmission to base station reception sensing mode, user equipment self-transmission and reception sensing mode, inter-user equipment transmission and reception sensing mode, and base station transmission to user equipment reception sensing mode). The SF network element then sends the collected training data to the DCCF network element.

[0088] Step 208: Send the training data sent by the SF network element to the NWDAF network element.

[0089] In some examples, the DCCF network element uses the Ndccf_DataManagement_Notify service to send the training data collected by the SF network element to the NWDAF network element.

[0090] Step 209: Store the training data sent by the SF network element to the ADRF network element.

[0091] In some examples, when the data acquisition request includes first storage indication information, the DCCF network element, in addition to returning the training data collected by the SF network element corresponding to the data acquisition request to the NWDAF network element, also stores the aforementioned training data in the ADRF network element according to the first storage indication information. The first storage indication information is used to instruct the training data to be stored in the ADRF network element.

[0092] In other examples, when the DCCF network element is pre-configured with second storage indication information, in addition to returning the training data collected by the SF network element corresponding to the data acquisition request to the NWDAF network element, the DCCF network element also stores the aforementioned training data in the ADRF network element according to the second storage indication information. The second storage indication information is used to instruct the training data to be stored in the ADRF network element. By storing the training data in the ADRF network element, long-term storage and analysis of the training data are facilitated, improving the flexibility of the integrated sensor network service.

[0093] It should be noted that this embodiment is illustrated by executing step 208 first and then step 209. In actual implementation, step 209 can be executed first, followed by step 208. Alternatively, steps 208 and 209 can be executed simultaneously.

[0094] Step 210: Send a response to the NWDAF network element to refuse to acquire data.

[0095] The response indicating refusal to collect data includes a reason for the refusal. By sending a response to the NWDAF network element when the user equipment does not agree to data collection, the NWDAF network element can be promptly notified of the data acquisition failure and take other related actions accordingly.

[0096] In this embodiment, by introducing the DCCF network element, which works in conjunction with the NWDAF and SF network elements to execute the above training data collection process, the following technical effects can be achieved: 1. It can effectively alleviate the resource waste and network overload caused by a large number of repetitive training data acquisition requests, and optimize the performance and response speed of the integrated sensor network; 2. By checking whether the user agrees to the data collection before collecting training data, the privacy protection of user data is strengthened; 3. It supports different data collection and processing needs and optional storage for the ADRF network element, providing a flexible data management strategy, while also having good scalability to adapt to future technological developments.

[0097] Figure 3 This is a flowchart illustrating a communication method performed by multiple parties according to some embodiments of this disclosure. For example... Figure 3 As shown, the communication method is jointly executed by multiple network elements such as NWDAF, SF, and DCCF, including steps 301 to 318.

[0098] Step 301: The AF network element sends a service awareness request to the NEF network element.

[0099] In this embodiment of the disclosure, the intelligent sensing process is triggered by the Application Function (AF) network element. In step 301, the AF network element sends a service sensing request to the Network Exposure Function (NEF) network element.

[0100] In some examples, a service awareness request includes a service type, service requirements, and specified awareness node information. The service type indicates the type of awareness service, such as dynamic maps, vehicle tracking, or location services. Service requirements specify the requirements for the awareness service. For example, service requirements may include one or more of the following: awareness resolution, awareness accuracy, awareness duration, target area information, and latency. Specified awareness node information indicates which nodes will be the focus of awareness. For example, the specified awareness node information may be user device information to be sensed.

[0101] In some embodiments, prior to step 301, the communication method further includes: the NWDAF network element and the SF network element registering to the Network Data Analytics Function (NRF) network element respectively.

[0102] In practice, when an NWDAF network element registers with an NRF network element, the registered information may include an identifier indicating the network element's support for AI / machine learning-based perception capabilities, machine learning model filtering information, and first machine learning model interoperability information. The first machine learning model interoperability information may include: a list of vendors sharing machine learning models with the NWDAF network element, the format of the machine learning models, and their operating environment.

[0103] When an SF network element registers with an NRF network element, the registered information may include an identifier indicating the network element's support for AI / machine learning-based perception capabilities, as well as interoperability information for second machine learning models. The second machine learning model interoperability information includes the vendor identifier of the SF network element and the format and operating environment of the machine learning models supported by the SF network element.

[0104] Step 302: The NEF network element sends a service awareness request to the AMF network element.

[0105] In some embodiments, step 302 includes: the NEF network element performing an authorization check on the service awareness request sent by the AF network element; if the authorization check passes, the NEF network element selects an Access and Mobility Management Function (AMF) network element and sends a service awareness request to the selected AMF network element; if the authorization check fails, the NEF network element sends a response indicating that the authorization check has failed to the AF network element.

[0106] The authorization check can be implemented in various ways. For example, the authorization check includes: determining the identifier of the AF network element that sent the service awareness request based on the service awareness request; querying the UDM network element based on the identifier of the AF network element to obtain the query result; determining whether the AF network element is authorized to use the specific awareness service based on the query result, wherein the specific awareness service can be determined based on the service awareness request; if the query result shows that the AF network element is authorized to use the specific awareness service, the authorization check passes; otherwise, the authorization check fails. After the authorization check passes, the NEF network element can select a suitable AMF network element based on the awareness node information, target area information, etc. carried in the service awareness request.

[0107] Step 303: Select SF network element from AMF network element.

[0108] In this step, after receiving a service awareness request, the AMF network element can select a suitable SF network element based on the target area information or target location information carried in the service awareness request.

[0109] Step 304: The AMF network element sends a service awareness request to the SF network element.

[0110] Step 305: The SF network element sends a model subscription request to the NWDAF network element.

[0111] In some examples, after receiving a service awareness request, the SF network element first checks whether a pre-trained model matching the service awareness request already exists. If no pre-trained model matching the service awareness request exists, the SF network element first discovers an NWDAF network element (i.e., an NWDAF network element containing MTLF) that supports model training through the NRF network element, and then executes step 305; if a pre-trained model matching the service awareness request already exists, the SF network element uses the model to perform inference perception to obtain the perception result, and feeds back the perception result to the AF network element through steps 316 to 318.

[0112] In other examples, after receiving a service awareness request, the SF network element first determines whether to use a machine learning model-based method to calculate the awareness result. If it determines to use a machine learning model-based method, the SF network element then checks if a pre-trained model matching the service awareness request already exists. If no pre-trained model matching the service awareness request exists, the SF network element first discovers an NWDAF network element (i.e., an NWDAF network element containing MTLF) that supports model training through the NRF network element, and then executes step 305. If a pre-trained model matching the service awareness request exists, the SF network element uses the model to perform inference and perception to obtain the awareness result, and then feeds the awareness result back to the AF network element through steps 316 to 318. Furthermore, if it determines not to use a machine learning model-based method to calculate the awareness result, the traditional algorithm configured internally by the SF network element is used to calculate the awareness result.

[0113] In 305, the SF network element sends a model subscription request to the NWDAF network element through the Nnwdaf_MLModelProvision_Subscribe service. This model subscription request may include machine learning model filtering information and second machine learning model interoperability information.

[0114] Step 306: The NWDAF network element sends a data acquisition request to the DCCF network element.

[0115] After receiving a model subscription request, the NWDAF network element can send a data acquisition request to the DCCF network element through the Ndccf_DataManagement_Subscribe service to request the data needed to train the machine learning model. The data acquisition request may include an event identifier, a target user equipment identifier, and a target range.

[0116] Step 307: The DCCF network element performs a data collection authorization check.

[0117] In this step, the DCCF network element can perform a data collection authorization check as follows: The DCCF network element determines the identifier of the user equipment whose data is being collected based on the data acquisition request; based on the identifier of the user equipment whose data is being collected, it retrieves the subscription information of the user equipment whose data is being collected from the UDM network element; if the subscription information indicates that the user equipment agrees to have its data collected and agrees to use the data for model training, then the data collection authorization check passes; otherwise, the data collection authorization check fails.

[0118] If the data collection authorization check passes, proceed to step 308; otherwise, the DCCF network element sends a response to the NWDAF network element refusing to acquire data.

[0119] In addition, if the data collection authorization check passes, the DCCF network element can also use the Nudm_SDM_Subscribe service to subscribe to notifications of changes in the subscription information of user equipment for the collected data from the UDM network element.

[0120] Step 308: The DCCF network element checks whether training data exists locally.

[0121] In this step, the DCCF network element checks whether there is training data corresponding to the data acquisition request on its local machine; if it does not exist, it indicates that the training data corresponding to the data acquisition request has not yet been collected, and step 309 is executed; if it exists, it indicates that the training data corresponding to the data acquisition request has been collected, and step 312 is executed.

[0122] In addition, if the DCCF network element has already collected the requested training data, the DCCF network element will also add the NWDAF network element that sent the data acquisition request to the data consumer list corresponding to the training data.

[0123] Step 309: The DCCF network element sends a data collection request to the SF network element.

[0124] In this step, the DCCF network element can send a data collection request to the SF network element via the Nnf_EventExposure_Subscribe service. This data collection request may include the address indication information of the DCCF network element. Furthermore, after executing step 309, the DCCF network element can add the NWDAF network element that sent the data acquisition request to the list of data consumers who have subscribed to this training data.

[0125] Step 310: SF network elements collect training data.

[0126] In this step, SF network elements can collect the required training data according to the specified sensing mode. The specified sensing mode can be a base station self-transmitting and receiving sensing mode, an inter-base station transceiver sensing mode, a user equipment transmitting and receiving sensing mode, a user equipment self-transmitting and receiving sensing mode, an inter-user equipment transceiver sensing mode, or a base station transmitting and receiving sensing mode.

[0127] For example, if the sensing mode is a base station self-transmitting and self-receiving sensing mode, the SF network element can collect training data at the base station side; if the sensing mode is an inter-base station transceiver sensing mode, the SF network element can collect training data at multiple base stations; if the sensing mode is a user equipment transmit-to-base station receive-to-sensing mode, the SF network element can collect training data at both the user equipment and base station sides; if the sensing mode is a user equipment self-transmitting and self-receiving sensing mode, the SF network element can collect sensing measurement data at the user equipment side; if the sensing mode is an inter-user equipment transceiver sensing mode, the SF network element can collect sensing measurement data at multiple user equipment sides; if the sensing mode is a base station transmit-to-user equipment receive-to-sensing mode, the SF network element can collect sensing measurement data at both the user side and the base station side.

[0128] Step 311: The SF network element sends training data to the DCCF network element.

[0129] Once the data collection is complete, the SF network element can send the collected training data to the DCCF network element through the Nnf_EventExposeure_Notify service.

[0130] Step 312: The DCCF network element sends training data to the NWDAF network element.

[0131] In this step, the DCCF network element can use the Ndccf_DataManagement_Notify service to send training data to the NWDAF network element. Furthermore, if the data acquisition request sent by the NWDAF network element carries first storage indication information or the DCCF network element has pre-set second storage indication information, the DCCF network element will also store the collected training data in the ADRF network element. The first and second storage indication information are used to instruct the collected training data to be stored in the ADRF network element.

[0132] Step 313: NWDAF network elements train machine learning models.

[0133] In this step, the NWDAF network element trains and updates the machine learning model based on the acquired training data.

[0134] Step 314: The NWDAF network element provides the trained model to the SF network element.

[0135] NWDAF network elements can provide trained machine learning models to SF network elements through the Nnwdaf_MLModelProvision_Notify service.

[0136] Step 315: SF network element collects data and performs model inference.

[0137] After receiving the trained machine learning model, the SF network element collects the data required for perception reasoning and processes the data using the trained machine learning model to obtain the perception result corresponding to the business perception request.

[0138] Step 316: The SF network element sends the sensing results to the AMF network element.

[0139] Step 317: The AMF network element sends the sensing results to the NEF network element.

[0140] Step 318: The NEF network element sends the sensing results to the AF network element.

[0141] In this embodiment, by collaboratively executing the above processes through SF network elements, NWDAF network elements, and DCCF network elements, machine learning-based intelligent sensing can be achieved, improving the data fusion and intelligent analysis capabilities of the integrated sensing network and providing the possibility of obtaining more accurate sensing results. Simultaneously, collaborative data collection through SF and DCCF network elements helps optimize network resource allocation, thereby improving overall network efficiency and effectively alleviating network overload caused by numerous repetitive data acquisition requests, thus contributing to optimized network performance and response speed. Furthermore, by introducing a data collection authorization check process before data collection, user data privacy protection can be strengthened. In addition, the communication method of this embodiment supports different data collection and processing needs, as well as optional storage for ADRF network elements, providing a flexible data management strategy and possessing good scalability to adapt to future technological developments.

[0142] Figure 4 This is a flowchart illustrating a communication method performed by multiple parties according to other embodiments of this disclosure. For example... Figure 4 As shown, the communication method is jointly executed by multiple network elements such as the NWDAF network element, SF network element, and DCCF network element, including steps 401 to 416. The communication method of this embodiment is similar to... Figure 3 The main difference between the communication methods shown is that the communication method in this embodiment is triggered and executed by the user equipment, while... Figure 3 The communication method shown is triggered by the AF network element.

[0143] Step 401: The UE sends a service awareness request to the AMF network element.

[0144] Step 402: Select SF network element for AMF network element.

[0145] Step 403: The AMF network element sends a service awareness request to the SF network element.

[0146] Steps 404 to 414 and Figure 3 Steps 305 to 315 in the process shown are the same and will not be repeated below.

[0147] Step 415: The SF network element sends the sensing results to the AMF network element.

[0148] Step 416: The AMF network element sends the sensing results to the UE.

[0149] In this embodiment of the disclosure, by combining the sensing data collection and reasoning capabilities of the sensing network element SF with the model training capabilities of the NWDAF network element and the data collection coordination capabilities of the DCCF network element, machine learning-based intelligent sensing can be realized more efficiently, improving the performance and response speed of the integrated sensing network, supporting the development of various intelligent sensing applications, and promoting the intelligent evolution of the network.

[0150] Figure 5 This is a schematic diagram of the structure of a communication device according to some embodiments of the present disclosure. For example... Figure 5 As shown, the communication device 50 is installed in the DCCF network element and is used to execute the communication method described above. The device specifically includes a receiving module 51, a judging module 52, a subscription module 53, and a data transceiver module 54.

[0151] The receiving module 51 is configured to receive data acquisition requests sent by the NWDAF network element. These data acquisition requests are used to request training data needed for training a machine learning model.

[0152] The judgment module 52 is configured to determine whether the training data corresponding to the data acquisition request has been collected.

[0153] The subscription module 53 is configured to send a data subscription request to the SF network element when no training data corresponding to the data acquisition request has been collected.

[0154] The data transceiver module 54 is configured to receive training data sent by the SF network element in response to a data subscription request, and to send the training data sent by the SF network element to the NWDAF network element. The NWDAF network element is used to train the machine learning model.

[0155] In some embodiments, the data transceiver module 54 is further configured to: send the collected training data to the NWDAF network element if the training data corresponding to the data acquisition request has been collected.

[0156] In the embodiments of this disclosure, the above-mentioned device helps to improve the efficiency of training data collection, thereby improving the performance and response speed of the sensor network.

[0157] Figure 6 This is a schematic diagram of the structure of a communication device according to other embodiments of this disclosure. For example... Figure 6 As shown, the communication device 60 includes a memory 61 and a processor 62 coupled to the memory 61. The memory 61 is used to store instructions for executing embodiments of the communication method. The processor 62 is configured to execute the communication method in any of the embodiments of this disclosure based on the instructions stored in the memory 61.

[0158] Figure 7 This is a schematic diagram of the structure of a communication system according to some embodiments of this disclosure. For example... Figure 7 As shown, the communication system 70 includes NWDAF network element 71, DCCF network element 72, and SF network element 73.

[0159] NWDAF network element 71 is configured to send a data acquisition request to DCCF network element 72. The data acquisition request is used to request training data required for training a machine learning model.

[0160] DCCF network element 72 is configured to include the communication device described above for performing the communication method described above. For example, DCCF network element 72 receives a data acquisition request sent by NWDAF network element 71; determines whether training data corresponding to the data acquisition request has been collected; if training data corresponding to the data acquisition request has not been collected, sends a data subscription request to SF network element 73; receives the training data sent by SF network element 73 in response to the data subscription request, and sends the training data sent by SF network element 73 to NWDAF network element 71.

[0161] SF network element 73 is configured to collect training data in response to a data subscription request sent by DCCF network element 72, and send the training data to DCCF network element 72.

[0162] In some examples, SF network element 73 is configured to collect training data based on the perception mode indication information when the data subscription request carries perception mode indication information or when the SF network element is pre-configured with perception mode indication information.

[0163] The NWDAF network element 71 is also configured to train a machine learning model based on training data obtained from the DCCF network element 72.

[0164] In some embodiments, SF network element 73 is further configured to send a model subscription request to NWDAF network element 71 after receiving a service awareness request sent by AMF network element, so as to trigger NWDAF network element 71 to perform the operation of sending a data acquisition request to DCCF network element; NWDAF network element 71 is further configured to send a trained machine learning model to SF network element 73; SF network element 73 is further configured to use the trained machine learning model and the collected perception measurement data to obtain the perception result corresponding to the service awareness request, and send the perception result to AMF network element.

[0165] In some embodiments, the communication system may further include functions for performing, such as Figure 3 or Figure 4 Other network elements or devices in the process shown.

[0166] In this embodiment of the disclosure, the above system can improve the efficiency of training data collection, thereby improving the performance and response speed of the sensor network.

[0167] Various aspects of this disclosure are described herein with reference to flowchart illustrations and / or block diagrams of methods, apparatus, and computer program products according to embodiments of this disclosure. It should be understood that each block of the flowchart illustrations and / or block diagrams, and combinations thereof, can be implemented by computer-readable program instructions.

[0168] These computer-readable program instructions are provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable device to produce a machine, such that execution of the instructions by the processor produces means for implementing the functions specified in one or more boxes of the flowchart and / or block diagram.

[0169] These computer-readable program instructions may also be stored in a computer-readable storage medium. These instructions cause a computer to work in a particular manner to produce an article of manufacture, including instructions that implement the functions specified in one or more boxes in a flowchart and / or block diagram.

[0170] This disclosure may take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects.

[0171] The communication methods, apparatus, and systems according to this disclosure have now been described in detail. To avoid obscuring the concept of this disclosure, some details known in the art have not been described. Those skilled in the art can fully understand how to implement the technical solutions disclosed herein based on the above description.

Claims

1. A communication method, executed by a Data Collection Coordination Function (DCCF) network element, comprising: Receive data acquisition request sent by the Network Data Analysis Function (NWDAF) network element, wherein the data acquisition request is used to request the acquisition of training data required for training a machine learning model; Based on the data acquisition request, determine the identifier of the user equipment to be collected corresponding to the training data; query the unified data management UDM network element based on the identifier of the user equipment to obtain the subscription information of the user equipment; and determine whether the user equipment agrees to have its data collected based on the subscription information of the user equipment. If the user equipment being collected agrees to have its data collected, it is determined whether training data corresponding to the data acquisition request has already been collected; In the absence of collecting training data corresponding to the data acquisition request, a data subscription request is sent to the SF network element of the sensing function, wherein the data subscription request carries at least one of sensing mode indication information and indication information of the device to be collected; The system receives training data sent by the SF network element in response to the data subscription request, and sends the training data sent by the SF network element to the NWDAF network element, wherein the NWDAF network element is used to train the machine learning model. If the user equipment being collected does not agree to have its data collected, a response to refuse to obtain data is sent to the NWDAF network element, wherein the response to refuse to obtain data includes a reason for refusal.

2. The communication method according to claim 1 further includes: If the training data has been collected, the collected training data is sent to the NWDAF network element.

3. The communication method according to claim 1, wherein, The contract information includes data type and data collection purpose. The step of determining whether the user device agrees to have its data collected based on the contract information of the user device being collected includes: If the data type indicates that the user device agrees to the data collection and the purpose of the data collection indicates that the user device agrees to use the collected data for model training, then the user device being collected agrees to the data collection; otherwise, the user device being collected does not agree to the data collection.

4. The communication method according to claim 1 further includes: If the user equipment being collected agrees to have its data collected, a subscription message is sent to the UDM network element. The subscription message is used to instruct the UDM network element to notify the DCCF network element when the subscription information of the user equipment being collected changes.

5. The communication method according to any one of claims 1 to 4, further comprising: If the data acquisition request includes first storage indication information or the DCCF network element is pre-configured with second storage indication information, after receiving the training data from the SF network element, the training data is stored in the ADRF network element, wherein the first storage indication information and the second storage indication information are used to indicate that the training data is stored in the ADRF network element.

6. A communication device, disposed in a data collection coordination function (DCCF) network element, comprising: A module for performing the communication method as described in any one of claims 1 to 5.

7. A communication device, disposed in a data collection coordination function (DCCF) network element, comprising: Memory; as well as A processor coupled to the memory, the processor being configured to execute the communication method as described in any one of claims 1 to 5 based on instructions stored in the memory.

8. A communication system, comprising: DCCF network element, configured to include the communication device as described in claim 6 or 7; The SF network element is configured to collect training data in response to a data subscription request sent by the DCCF network element, and to send the training data to the DCCF network element. The NWDAF network element is configured to send a data acquisition request to the DCCF network element and to train a machine learning model based on the training data acquired from the DCCF network element.

9. The communication system according to claim 8, wherein, The SF network element is configured as follows: When the data subscription request carries perception mode indication information or the SF network element is pre-configured with perception mode indication information, the training data is collected according to the perception mode indication information.

10. The communication system according to claim 8, wherein: The SF network element is also configured to send a model subscription request to the NWDAF network element after receiving a service awareness request sent by the Access and Mobility Management Function (AMF) network element, so as to trigger the NWDAF network element to perform the operation of sending a data acquisition request to the DCCF network element. The NWDAF network element is also configured to send the trained machine learning model to the SF network element; The SF network element is also configured to use the trained machine learning model and the collected perception measurement data to obtain the perception result corresponding to the service perception request, and send the perception result to the AMF network element.

11. A computer-readable storage medium having stored thereon computer instructions that, when executed by a processor, implement the communication method as described in any one of claims 1 to 5.

12. A computer program product having stored computer instructions thereon, which, when executed by a processor, implement the communication method as described in any one of claims 1 to 5.

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