A communication method and apparatus

Abstract

A method and apparatus for enabling an analytics service of a data analytics network element to meet requirements of multiple analytics requesting network elements. The method includes receiving, by the data analytics network element, a first request message from a first analytics requesting network element, the first request message requesting a recommended first network parameter, and determining, by the data analytics network element, a third network indicator based on a first network indicator expected by the first analytics requesting network element and a second network indicator expected by a second analytics requesting network element, the third network indicator being a network indicator expected by both the first analytics requesting network element and the second analytics requesting network element. The data analytics network element determines a recommended network parameter based on the third network indicator, thereby enabling the recommended network parameter to meet requirements of the first analytics requesting network element and the second analytics requesting network element for analytics services.

Description

Technical Field

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

[0002] The rapid development of artificial intelligence and big data analytics has provided the foundational technologies for network intelligence. To achieve 5G mobile network intelligence, network data analytics function (NWDAF) network elements and management data analytics system (MDAS) have been defined. NWDAF or MDAS can provide intelligent analysis services for the network, supporting anomaly analysis, optimization, and service level agreement (SLA) assurance; therefore, NWDAF and / or MDAS can be referred to as data analytics network elements.

[0003] Taking NWDAF (Network Data Analyzer) as an example, NWDAF can predict the changing trends of network indicators (i.e., indicators representing the network's operational status) through intelligent analysis services, and the service network elements processing business can adjust the network based on these trends. However, current data analysis network elements do not support analysis requests for related network parameters from multiple network elements, thus failing to meet the analysis needs of multiple network elements. Summary of the Invention

[0004] This application provides a communication method and apparatus that enables the analysis services of a data analysis network element to meet the analysis service requirements of multiple network elements.

[0005] In a first aspect, embodiments of this application provide a communication method, which can be executed by a data analysis network element or a module (such as a chip) applied in the data analysis network element. Taking the execution of the method by a data analysis network element as an example, the method includes: the data analysis network element receiving a first request message and a second request message, wherein the first request message originates from a first analysis request network element and is used to request recommended first network parameters, the first request message including the first network parameters and a first network indicator requested by the first analysis request network element, the first network indicator being a network indicator expected by the first analysis request network element; the second request message originates from a second analysis request network element and is used to request recommended second network parameters, the second request message including the second network parameters and the second network indicator requested by the second analysis request network element, the second network indicator being a network indicator expected by the second analysis request network element. The data analysis network element can also determine a third network indicator based on the first network indicator and the second network indicator, the third network indicator being a network indicator jointly expected by the first analysis request network element and the second analysis request network element. The data analysis network element can also determine recommended third network parameters and recommended fourth network parameters based on the third network indicator, the first network parameters requested by the first analysis request network element, and the second network parameters requested by the second analysis request network element. The data analysis network element can also send recommended third network parameters and recommended fourth network parameters.

[0006] According to the above scheme, the data analysis network element can determine the recommended network parameters based on the network indicators commonly desired by the first analysis request network element and the second analysis request network element, so that the recommended network parameters meet the requirements of the first analysis request network element and the second analysis request network element for the analysis service.

[0007] In one possible design, the predicted network metrics corresponding to the recommended third and fourth network parameters fall within the range of the third network metric. This design allows the recommended network parameters to better align with the expectations of the first and second analysis requesting network elements regarding the network metrics.

[0008] In one possible design, the data analysis network element can also send a first message to the first analysis requesting network element and / or the second analysis requesting network element. This first message modifies the desired network metric to a third network metric. With this design, when the value of the network metric desired by the first analysis requesting network element differs from the value of the metric desired by the second analysis requesting network element, the data analysis network element can determine a commonly desired network metric based on the network metric desired by both elements, thus achieving accurate determination of the third network metric.

[0009] In one possible design, if the first network parameter corresponds to both the third and fourth network parameters, and the second network parameter corresponds to the fourth network parameter, then the data analysis network element can also send the recommended third network parameter to the first analysis request network element, and the data analysis network element can also send the recommended fourth network parameter to the second analysis request network element. With this design, when both the network transmission requested by the first analysis request network element and the network parameters requested by the second analysis request network element include the third network parameter, the first analysis request network element can send the recommended third network parameter to one of the requesting network elements, avoiding redundant adjustments.

[0010] In one possible design, the data analysis network element can also send a second message to the first analysis request network element, which is used by the first analysis request network element to modify the requested network parameters to a third network parameter.

[0011] In one possible design, if the first network parameter corresponds to the third and fourth network parameters, and the second network parameter corresponds to the third and / or fourth network parameters, then the data analysis network element can also send recommended third and fourth network parameters to the first analysis request network element. With this design, when both the network transmission requested by the first analysis request network element and the network parameters requested by the second analysis request network element include the third network parameter, the first analysis request network element can send the recommended third network parameter to one of the requesting network elements, avoiding redundant adjustments.

[0012] In one possible design, the data analysis network element can also send a third message to the second analysis requesting network element. The third message is used to cancel obtaining the recommended network parameters based on the second network parameters requested by the second analysis requesting network element.

[0013] In one possible design, the data analysis network element can send a recommended third network parameter to the first analysis request network element and a recommended fourth network parameter to the second analysis request network element. The recommended third network parameter corresponds to the first network parameter, and the recommended fourth network parameter corresponds to the second network parameter.

[0014] In one possible design, the data analysis network element can also receive a fourth message from the first analysis request network element. This fourth message indicates that the recommended third network parameter is not accepted. The data analysis network element can further determine recommended fifth and sixth network parameters based on the fourth message, the third network indicator, the first network parameter requested by the first analysis request network element, and the second network parameter requested by the second analysis request network element. The recommended fifth network parameter corresponds to the first network parameter, and the recommended sixth network parameter corresponds to the second network parameter. The value of the recommended fifth network parameter is different from the value of the recommended third network parameter. The data analysis request network element can also send the recommended fifth network parameter to the first analysis request network element and the recommended sixth network parameter to the second analysis request network element. With this design, if one of the multiple analysis request network elements rejects the recommended network parameter, the data analysis network element needs to re-determine the recommended network parameters for all analysis request network elements, thereby improving analysis reliability.

[0015] Secondly, embodiments of this application provide a communication method, which can be executed by a first analysis request network element or a module (such as a chip) applied in the first analysis request. Taking the execution of this method by the first analysis request as an example, the method includes: the first analysis request network element can determine a first request message, the first request message being used to request recommended first network parameters, the first request message including the first network parameters required by the first analysis request network element and a first network indicator, the first network indicator being the network indicator expected by the first analysis request network element. The first analysis request network element can also send the first request message to a data analysis network element.

[0016] In one possible design, if the first network parameter corresponds to the third and fourth network parameters, the first analysis requesting network element can also receive a recommended third network parameter from the data analysis network element. The recommended third network parameter is determined based on a third network indicator, the first network parameter requested by the first analysis requesting network element, and the second network parameter requested by the second analysis requesting network element. The third network indicator is a network indicator commonly desired by both the first and second analysis requesting network elements, and is determined based on the first and second network indicators. The second network indicator is the network indicator desired by the second analysis requesting network element.

[0017] In one possible design, the first analysis requesting network element may also receive a first message from the data analysis network element, the first message being used to modify the desired network indicator to a third network indicator. The first analysis requesting network element may also determine, based on the first message, whether to modify the desired network indicator to the third network indicator.

[0018] In one possible design, the first analysis requesting network element can also receive a second message from the data analysis network element, which is used by the first analysis requesting network element to modify the requested network parameters to a third network parameter.

[0019] In one possible design, if the first network parameter corresponds to the third and fourth network parameters, the first analysis requesting network element can also receive recommended third and fourth network parameters from the data analysis network element. The recommended third and fourth network parameters are determined based on the third network indicator, the first network parameter required by the first analysis requesting network element, and the second network parameter required by the second analysis requesting network element. The third network indicator is a network indicator commonly desired by the first and second analysis requesting network elements and is determined based on the first and second network indicators. The second network indicator is a network indicator desired by the second analysis requesting network element.

[0020] In one possible design, the predicted network metrics corresponding to the recommended third network parameters and the recommended fourth network parameters are within the range of the third network parameters. The recommended fourth network parameters are determined based on the third network parameters, the first network parameters required by the first analysis request network element, and the second network parameters required by the second analysis request network element. The fourth network parameters correspond to the second network parameters.

[0021] In one possible design, the first analysis requesting network element may also receive recommended third network parameters from the data analysis network element. The first analysis requesting network element may also send a fourth message to the data analysis network element, indicating that the recommended third network parameters are not accepted. The first analysis requesting network element may also receive recommended fifth network parameters from the data analysis network element. These recommended fifth network parameters correspond to the first network parameters and are determined based on a third network indicator, the first network parameters requested by the first analysis requesting network element, and the second network parameters requested by the second analysis requesting network element. The third network indicator is a network indicator commonly desired by both the first and second analysis requesting network elements, and is determined based on both the first and second network indicators. The second network indicator is a network indicator desired by the second analysis requesting network element.

[0022] Thirdly, embodiments of this application provide a communication method, which can be executed by a second analysis request network element or a module (such as a chip) applied in the second analysis request. Taking the execution of this method by the second analysis request as an example, the method includes: the second analysis request network element can determine a second request message, the second request message being used to request recommended second network parameters, the second request message including the second network parameters and a second network indicator required by the second analysis request network element, the second network indicator being the network indicator expected by the second analysis request network element. The second analysis request network element can also send the second request message to a data analysis network element.

[0023] In one possible design, the second analysis requesting network element may also receive a fourth network parameter recommended by the data analysis network element. The recommended fourth network parameter is determined based on a third network indicator, the first network parameter requested by the first analysis requesting network element, and the second network parameter requested by the second analysis requesting network element. The third network indicator is a network indicator commonly desired by both the first and second analysis requesting network elements, and is determined based on the second and first network indicators. The first network indicator is the network indicator desired by the first analysis requesting network element.

[0024] In one possible design, the second analysis requesting network element may also receive a first message from the data analysis network element, the first message being used to modify the desired network metric to a third network metric. The second analysis requesting network element may also determine, based on the first message, whether to modify the desired network metric to the third network metric.

[0025] In one possible design, the second analysis requesting network element can also receive a third message from the data analysis network element, which is used to cancel obtaining the recommended network parameters based on the second network parameters requested by the second analysis requesting network element.

[0026] In one possible design, the second analysis requesting network element may also receive a recommended fourth network parameter from the data analysis network element. The recommended fourth network parameter is determined based on a third network indicator, a first network parameter requested by the first analysis requesting network element, and a second network parameter requested by the second analysis requesting network element. The third network indicator is a network indicator commonly desired by both the first and second analysis requesting network elements, and is determined based on the second and first network indicators. The first network indicator is the network indicator desired by the first analysis requesting network element. The second analysis requesting network element may also receive a recommended sixth network parameter from the data analysis network element. This recommended sixth network parameter corresponds to the second network parameter and is determined based on the third network indicator, the first network parameter requested by the first analysis requesting network element, and the second network parameter requested by the second analysis requesting network element.

[0027] Fourthly, embodiments of this application provide a communication device, which may be a data analysis network element or a module (such as a chip) applied in a data analysis network element. This device has the function of implementing the first aspect described above and any possible design thereof. This function can be implemented by hardware or by hardware executing corresponding software. The hardware or software includes one or more modules corresponding to the above-described function.

[0028] Fifthly, embodiments of this application provide a communication device, which may be an analysis request network element or a module (such as a chip) applied in an analysis request network element. The device has the function of implementing the second aspect described above and any possible design thereof. This function can be implemented in hardware or by hardware executing corresponding software. The hardware or software includes one or more modules corresponding to the above-described function.

[0029] Sixthly, embodiments of this application provide a communication device, which may be an analysis request network element or a module (such as a chip) applied in an analysis request network element. This device has the function of implementing the third aspect described above and any possible design thereof. This function can be implemented in hardware or by hardware executing corresponding software. The hardware or software includes one or more modules corresponding to the above-described function.

[0030] In a seventh aspect, embodiments of this application provide a communication device, including a processor and a memory; the memory is used to store computer instructions required by the processor, and when the device is running, the processor executes the computer instructions stored in the memory to cause the device to perform any implementation method in the first to third aspects and any possible designs described above.

[0031] Eighthly, embodiments of this application provide a communication device including units or means for performing the steps of the first to third aspects and any possible designs thereof.

[0032] Ninthly, embodiments of this application provide a communication device including a processor and an interface circuit. The processor is configured to communicate with other devices via the interface circuit and execute the methods described in the first to third aspects and any possible designs thereof. The processor may include one or more.

[0033] In a tenth aspect, embodiments of this application provide a communication device including a processor coupled to a memory. The processor is configured to invoke a program stored in the memory to execute the methods described in the first to third aspects and any possible designs thereof. The memory may be located within or outside the device. Furthermore, there may be one or more processors.

[0034] Eleventhly, embodiments of this application also provide a computer-readable storage medium storing instructions that, when executed on a communication device, cause the methods described in the first to third aspects and any possible designs thereof to be performed.

[0035] In a twelfth aspect, embodiments of this application also provide a computer program product, which includes a computer program or instructions that, when executed by a communication device, cause the methods in the first to third aspects and any possible designs thereof to be performed.

[0036] In a thirteenth aspect, embodiments of this application also provide a chip system, including: a processor for executing the methods described in the first to third aspects and any possible designs thereof.

[0037] In a fourteenth aspect, embodiments of this application also provide a communication system, including a data analysis network element for implementing the methods in the first aspect and any possible design thereof, a first analysis request network element for implementing the methods in the second aspect and any possible design thereof, and a second analysis request network element for implementing the methods in the third aspect and any possible design thereof.

[0038] The technical effects of any possible design in any of the second to fourteenth aspects above can be found in the description of the technical effects of any possible design in the first aspect above, and will not be repeated here. Attached Figure Description

[0039] Figure 1 This application provides a schematic diagram of the architecture of a communication system.

[0040] Figure 2 A schematic diagram of a machine learning model provided in an embodiment of this application;

[0041] Figure 3 This is a schematic diagram of the architecture of another communication system provided in an embodiment of this application;

[0042] Figure 4 This application provides a flowchart illustrating a communication method.

[0043] Figure 5 A flowchart illustrating another communication method provided in an embodiment of this application;

[0044] Figure 6 A flowchart illustrating another communication method provided in an embodiment of this application;

[0045] Figure 7 A flowchart illustrating another communication method provided in an embodiment of this application;

[0046] Figure 8 This is a schematic diagram of the structure of a communication device provided in an embodiment of this application;

[0047] Figure 9 This is a schematic diagram of another communication device provided in an embodiment of this application. Detailed Implementation

[0048] To make the objectives, technical solutions, and advantages of this application clearer, the application will now be described in further detail with reference to the accompanying drawings.

[0049] Figure 1 This is a schematic diagram of a 5G network architecture based on a service-oriented architecture. Figure 1 The 5G network architecture shown may include terminal devices, access network (AN) devices, and core network devices. Terminal devices access the data network (DN) through access network devices and core network devices. The core network devices include some or all of the following network functions (NFs): unified data management (UDM) network elements, network exposure function (NEF) network elements (not shown in the figure), application function (AF) network elements, policy control function (PCF) network elements, access and mobility management function (AMF) network elements, network slice selection function (NSSF) network elements, session management function (SMF) network elements, user plane function (UPF) network elements, network data analytics function (NWDAF) network elements, and network repository function (NRF) network elements (not shown in the figure).

[0050] Access network equipment can be radio access network (RAN) equipment. Examples include: base stations, evolved NodeBs (eNodeBs), transmission reception points (TRPs), next-generation NodeBs (gNBs) in 5G mobile communication systems, next-generation base stations in the 6th generation (6G) mobile communication systems, base stations in future mobile communication systems, or access nodes in wireless fidelity (WiFi) systems. It can also be a module or unit that performs some of the functions of a base station; for example, it can be a central unit (CU) or a distributed unit (DU). RAN equipment can be macro base stations, micro base stations, indoor stations, relay nodes, or donor nodes. The embodiments of this application do not limit the specific technologies or equipment forms used in the RAN equipment.

[0051] Terminal devices can be user equipment (UE), mobile stations, mobile terminals, etc. They can be widely used in various scenarios, such as device-to-device (D2D), vehicle-to-everything (V2X) communication, machine-type communication (MTC), the Internet of Things (IoT), virtual reality, augmented reality, industrial control, autonomous driving, telemedicine, smart grids, smart furniture, smart offices, smart wearables, smart transportation, and smart cities. Terminal devices can include mobile phones, tablets, computers with wireless transceiver capabilities, wearable devices, vehicles, urban air mobility vehicles (such as drones and helicopters), ships, robots, robotic arms, and smart home devices.

[0052] Access network equipment and terminal equipment can be fixed or mobile. They can be deployed on land, including indoors or outdoors, handheld or vehicle-mounted; they can also be deployed on water; and they can be deployed in the air on aircraft, balloons, and satellites. The embodiments of this application do not limit the application scenarios of the access network equipment and terminal equipment.

[0053] The access management network element (AMF) includes functions such as mobility management and access authentication / authorization. It is primarily used for terminal attachment, mobility management, and tracking area update processes in mobile networks. The AMF terminates non-access stratum (NAS) messages, completes registration management, connection management, and reachability management, allocates tracking area lists (TA lists), and performs mobility management. It also transparently routes session management (SM) messages to the session management network element. In 5G communication systems, the AMF can be an AMF (Advanced Management Function) element. Furthermore, the AMF is responsible for transmitting user policies between terminal devices and the PCF (Programmable Component Provider).

[0054] Session management network elements are primarily used for session management in mobile networks, such as session establishment, modification, and release. Specific functions include assigning Internet Protocol (IP) addresses to terminals and selecting user plane network elements that provide packet forwarding capabilities. In 5G communication systems, the session management network element can be an SMF (Signature Management Function) network element.

[0055] Network slicing selection elements are primarily used to select appropriate network slices for terminal services. In 5G communication systems, network slicing selection elements can be NSSF elements.

[0056] User plane network elements are primarily responsible for processing user packets, such as forwarding, billing, and lawful interception. User plane network elements can serve as Protocol Data Unit (PDU) session anchors (PSAs). In 5G communication systems, user plane network elements can be UPF (User Plane Function Factor) elements. UPFs can communicate directly with the NWDAF (Network Window Controller Area Function) through service-like interfaces, or through other means, such as through the SMF (Software Controller Function) or a private or internal interface with the NWDAF.

[0057] Unified Data Management Network Element: Responsible for managing the terminal's subscription information. In a 5G communication system, the Unified Data Management Network Element can be a UDM network element (hereinafter referred to as UDM).

[0058] Network capability open elements are used to support the opening of capabilities and events. In 5G communication systems, network capability open elements can be NEF elements (hereinafter referred to as NEF).

[0059] Application function network elements are used to convey application-side requests to the network side, such as QoS requirements or user state event subscriptions. Application function network elements can be third-party functional entities or application servers deployed by the operator. In 5G communication systems, application function network elements can be AF network elements (hereinafter referred to as AF).

[0060] Policy control network elements include user subscription data management functions, policy control functions, billing policy control functions, and quality of service (QoS) control. In 5G communication systems, policy control network elements can be PCF network elements (hereinafter referred to as PCF). It should be noted that in actual networks, PCFs may also be divided into multiple entities according to hierarchy or function, such as global PCFs and PCFs within slices, or session management PCFs (SM-PCF) and access management PCFs (AM-PCF).

[0061] Network repository elements provide network element discovery functionality, offering network element information corresponding to the network element type based on requests from other network elements. They also provide network element management services, such as network element registration, updates, deregistration, and network element status subscription and push notifications. In 5G communication systems, network repository elements can be NRF elements (hereinafter referred to as NRFs).

[0062] A data analysis network element can be used to collect, analyze, and predict data. Data collection includes, but is not limited to, at least one of the following: data collected from various other network elements (NFs), such as data collected through the AMF, SMF, PCF, through the NEF, or directly from the AF; or data collected from the operation, administration, and maintenance (OAM) system. This data can be data from terminal devices, access network devices, core network elements, or third-party application devices, or data from terminal devices on the access network device, core network element, or third-party application device. The collected data is then intelligently analyzed, and the analysis results are output. In a 5G communication system, the data analysis network element can be an NWDAF network element (hereinafter referred to as NWDAF). Intelligent analysis refers to the analysis of collected data using intelligent technologies such as artificial intelligence (AI). In this application, intelligent analysis includes, but is not limited to, predicting network indicators and recommending network parameters.

[0063] In this application, the NWDAF can utilize machine learning models for intelligent analysis. The NWDAF can also output recommended values ​​to the various NFs, AFs, or OAMs mentioned above, for use in policy decision-making. In 3GPP Release 17, the training and inference functions of the NWDAF are separated. An NWDAF can support only model training, only data inference, or both. The NWDAF supporting model training can also be called a training NWDAF, or an NWDAF supporting the model training logical function (MTLF) (abbreviated as NWDAF(MTLF)). The training NWDAF can train a model based on acquired data to obtain a trained model. The NWDAF supporting data inference can also be called an inference NWDAF, or an NWDAF supporting the analytics logical function (AnLF) (abbreviated as NWDAF(AnLF)). The inference NWDAF can input input data into the trained model to obtain analysis results or inference data. In this embodiment, a training NWDAF refers to an NWDAF that at least supports model training functionality. As a possible implementation, a training NWDAF can also support data inference functionality. An inference NWDAF refers to an NWDAF that at least supports data inference functionality. As a possible implementation, an inference NWDAF can also support model training functionality. If an NWDAF supports both model training and data inference functionality, then the NWDAF can be called a training NWDAF, an inference NWDAF, a training-inference NWDAF, or simply an NWDAF. In this embodiment, an NWDAF can be a separate network element or can be co-located with other network elements, such as being placed in a PCF network element or an AMF network element.

[0064] A Domain Provider (DN) is a network located outside of the carrier's network. A carrier's network can connect to multiple DNs, and various services can be deployed on a DN, providing data and / or voice services to terminal devices. For example, a DN might be the private network of a smart factory. Sensors installed in the workshop can act as terminal devices, and a control server for these sensors is deployed within the DN. The control server provides services to the sensors. Sensors can communicate with the control server, receive instructions from it, and transmit the collected sensor data back to the control server accordingly. Another example is a DN serving as an internal office network for a company. Employees' mobile phones or computers can act as terminal devices, accessing information and data resources on the company's internal office network.

[0065] Figure 1 Npcf, Nnef, Namf, Nudm, Nsmf, Naf, Nnssf, and Nnwdaf are the service interfaces provided by PCF, NEF, AMF, UDM, SMF, AF, NSSF, and NWDAF, respectively, used to invoke the corresponding service operations. N1, N2, N3, N4, and N6 are interface sequence numbers, with the following meanings:

[0066] 1) N1: The interface between the AMF and the terminal device, which can be used to transmit non-access stratum (NAS) signaling (such as QoS rules from the AMF) to the terminal device.

[0067] 2) N2: The interface between the AMF and the access network equipment, which can be used to transmit radio bearer control information from the core network side to the access network equipment.

[0068] 3) N3: The interface between the access network device and the UPF, mainly used to transmit uplink and downlink user plane data between the access network device and the UPF.

[0069] 4) N4: The interface between SMF and UPF, which can be used to transmit information between the control plane and the user plane, including the distribution of forwarding rules, QoS rules, traffic statistics rules, etc. from the control plane to the user plane, as well as the reporting of information from the user plane.

[0070] 5) N6: The interface between UPF and DN, used to transmit uplink and downlink user data streams between UPF and DN.

[0071] Figure 1 The service-oriented architecture shown enables the 5G core network to form a flat architecture. Through the control plane signaling bus, control plane network function entities in the same network slice can discover each other through NRF, obtain each other's access address information, and then communicate directly with each other through the control plane signaling bus.

[0072] It is understood that the aforementioned network element or function can be a network component in a hardware device, a software function running on dedicated hardware, or a virtualization function instantiated on a platform (e.g., a cloud platform). As one possible implementation method, the aforementioned network element or function can be implemented by a single device, multiple devices working together, or a functional module within a single device; this application does not specifically limit this.

[0073] As one implementation method, the data analysis network element in this application embodiment can be the aforementioned NWDAF, or a network element with the aforementioned NWDAF function in future communications such as 6G networks. The data analysis network element can also be MDAS. MDAS is a data analysis system deployed on the network management plane, which can be used to collect and analyze management data such as performance statistics, alarms, and operation configurations, and can also output suggestions for resource allocation or configuration optimization. MDAS also has training and inference functions. Compared with NWDAF, MDAS is part of the network management system, often operating offline and not in real-time, providing operators with resource and deployment adjustment and optimization suggestions, and focusing on longer-term trend analysis and optimization suggestions. For ease of explanation, the following description uses NWDAF as an example of the data analysis network element; actions performed by NWDAF in this application can also be performed by MDAS.

[0074] The following explains the intelligent analysis process of NWDAF. NWDAF can collect data from multiple sources and multiple dimensions, perform correlation analysis, output historical statistics, or train and fit a model. Based on the model, it outputs predicted values ​​of network indicators to guide service network elements in adjusting network parameters to optimize network indicators. It should be understood that different network indicators correspond to different network parameters, and network indicators are related to the network operating status. Among them, network indicators include network service evaluation values ​​(hereinafter referred to as service experience), key network performance indicators, or network overhead indicators, etc. Network parameters may include factors such as time, UE location, application location, service flow bit rate, packet latency, and the number of transmitted and retransmitted packets.

[0075] This section uses network metrics as an example of intelligent analysis of business experience (hereinafter referred to as business experience analysis). Business experience refers to the user's evaluation of the experience of accessing services through the network. In this case, network metrics can be a quantitative assessment by the user. This process may include the following steps:

[0076] Step 1, NWDAF first collects the following data:

[0077] (1) Collect service experience scores, the percentage of UEs that achieve the experience score (e.g., the percentage of UEs with excellent service experience quality is not less than 90%), UE IP addresses, and application location information (e.g., data network access identifier (DNAI)). Among these, the experience score is, for example, the mean opinions score (MOS).

[0078] (2) Collect the UE's subscription permanent identifier (SUPI) and UE's location information (such as global cell identifier (GCI)) through the AMF.

[0079] (3) Collect UE's SUPI, PDU session network slice identifier (such as single-network slice selection assistance information (S-NSSAI)), UPF information (such as UPF identifier (ID)), IP filtering information and service flow identifier (QFI) from SMF.

[0080] (4) Collect parameters such as bit rate, end-to-end delay (or packet delay), number of transmitted and retransmitted messages, etc. from the UPF.

[0081] Step 2: NWDAF uses IP filtering information and the UE's IP address to associate data collected from the AF by a UE with data collected from the SMF by the same UE. Then, based on SUPI, it associates location data collected from the AMF by the same UE with session data collected from the SMF. QFI is then used to further associate data collected from the UPF by the same UE with the above data. Similarly, NWDAF performs correlation analysis on data from a large number of UEs.

[0082] Step 3: NWDAF trains and fits a model based on the data described above. For example, a deep learning network can be trained using the data. This deep learning network is, for example... Figure 2 As shown.

[0083] For example, during the training process, NWDAF uses its training function to treat network parameters such as UE location, application location, time, QoS Flow bit rate, packet latency, and the number of transmitted and retransmitted packets as independent variables, and network metrics such as service experience and the percentage of UEs achieving the corresponding service experience as dependent variables. This data, after being processed and correlated, is used to train the deep learning network, resulting in a deep learning model. In other words, during training, the independent variables are network parameters, and the dependent variables are network metrics.

[0084] Step 4: NWDAF sets the trained deep learning model to inference mode (i.e., uses inference function), predicts the most likely range of values ​​for each independent variable in the future based on the historical statistical trends of each independent variable, and then calculates and outputs the predicted result of the dependent variable in the future based on the predicted values ​​of each independent variable through the trained deep learning model.

[0085] Accordingly, through the service experience analysis process, NWDAF can predict the predicted values ​​of network indicators corresponding to network parameters. NWDAF can also send the predicted values ​​to service network elements (or service processing network elements), so that the service network elements can adjust the network parameters according to the predicted values, thereby optimizing the network indicators after the adjustment.

[0086] Specifically, in the service experience analysis process, the service network element may include the Service Management Function (SMF), network parameters may include QoS parameters, and network metrics may include the experience score. The Network Window Function (NWDAF) can output a predicted value of the experience score to the SMF. The SMF can determine adjusted QoS parameters based on the predicted experience score, which may specifically include adjusted bit rate and / or adjusted packet delay. The SMF can also execute the adjusted QoS parameters through the Upgraded Service Function (UPF), thereby improving the service score through QoS parameter optimization.

[0087] However, in the current analysis process, NWDAF cannot analyze request messages from multiple analysis request network elements. It only analyzes each service request separately, which may cause conflicts between the analyses performed by NWDAF for different requests. Therefore, the analysis results cannot simultaneously meet the requirements of all analysis request network elements.

[0088] For example, if the network metrics desired by the network element in the first analysis request are of the same type but different values ​​than those desired by the network element in the second analysis request, this could cause a conflict. For instance, the SMF and AF each request recommended network parameters from the NWDAF. The SMF expects a MOS of at least 4.5, while the AF expects a MOS of at least 4. The NWDAF determines the recommended network parameters for the SMF and AF respectively, and the SMF and AF adjust their parameters accordingly. However, the recommended network parameters for AF may only satisfy a MOS of at least 4, and may not meet the requirement of a MOS of at least 4.5. Therefore, after AF adjusts its parameters according to these recommended parameters, the network's MOS may not reach 4.5, causing the network metric desired by the SMF to be unmet.

[0089] For example, if the first and second analysis requesting network elements request the same recommended value for a network parameter from the NWDAF, and both analysis requesting network elements adjust the network parameter, the actual network performance after adjusting the network parameter may not match the expected network performance.

[0090] To ensure that the analysis results do not meet the requirements of all analysis requesting network elements, this application provides a communication method. This communication method can be executed by a data analysis network element and multiple analysis requesting network elements. For example... Figure 3 As shown, a data analysis network element can be used to perform intelligent analysis of the network based on request messages (or analysis requests) from multiple analysis request network elements, and send analysis results (or response messages corresponding to the request messages, or simply response messages) to the multiple analysis request network elements. For example, the data analysis network element includes NWDAF or MDAS. These multiple analysis request network elements can be network elements within the network to be analyzed, or network elements outside the network. Analysis request network elements can include service network elements used to adjust network parameters based on the analysis results, or they can include other network elements besides service network elements. For example, analysis request network elements can be, for example, AMF, SMF, or AF, etc., without specific limitation. The network can include at least one network element, for example, including... Figure 1 At least one NF in the architecture shown.

[0091] The following is combined Figure 4 This application provides a communication method that may include the following steps:

[0092] S101: The data analysis network element receives a first request message from the first analysis request network element and a second request message from the second analysis request network element.

[0093] The first request message requests recommended first network parameters, including the first network parameters required by the first analysis requesting network element (hereinafter referred to as the required first network parameters) and a first network indicator, wherein the first network indicator is the network indicator expected by the first analysis requesting network element. The second request message requests recommended second network parameters, including the second network parameters required by the second analysis requesting network element (hereinafter referred to as the required second network parameters) and a second network indicator, wherein the second network indicator is the network indicator expected by the second analysis requesting network element. It should be understood that the first network parameter can be an adjustable network parameter of the first analysis requesting network element (or the service network element corresponding to the first analysis requesting network element), and the second network parameter can be an adjustable network parameter of the second analysis requesting network element (or the service network element corresponding to the second analysis requesting network element).

[0094] In this application, the type of the requested second network parameter can be the same as or different from the type of the requested first network parameter. For example, in service experience analysis, the first analysis requesting network element can be an SMF (Supervisory Filter), in which case the requested first network parameter can be bit rate and end-to-end latency. The requested first network parameter can indicate an acceptable bit rate less than or equal to 20 megabits per second (Mbps) and an acceptable end-to-end latency greater than or equal to 20 milliseconds (ms). The second analysis requesting network element can be an AF (Automatic Filter), in which case the requested second network parameter can be a DNAI (Digital Filter), and the type of the requested first network parameter is different from the type of the requested second network parameter. Similarly, the second analysis requesting network element can be a UPF (Upper Filter), in which case the type of the requested second network parameter can be bit rate and end-to-end latency, and the type of the requested first network parameter is the same as the type of the requested second network parameter. Likewise, the values ​​of the requested first network parameter and the requested second network parameter can be the same or different.

[0095] In this application, at least one of the network parameters requested by the requesting network element (including the first network parameters requested by the first requesting network element and the second network parameters requested by the second requesting network element) and the network indicators expected by the requesting network element (including the first network indicator and the second network indicator) can be used to determine the analysis result, making the analysis result acceptable to the requesting network element and improving the reliability of the intelligent analysis process. The analysis result may include recommended network parameters, allowing the requesting network element to adjust its network parameters based on these recommended parameters to achieve better network optimization. Specifically, the first network parameters requested by the first requesting network element and the first network indicator expected by the first requesting network element can be used to determine the recommended network parameters for the first requesting network element, and the second network parameters requested by the second requesting network element and the second network indicator expected by the second requesting network element can be used to determine the recommended network parameters for the second requesting network element.

[0096] The network parameters requested by the requesting network element can include the type of network parameters requested, or both the type and value of the requested network parameters. The network parameters requested by the requesting network element can be an acceptable adjustment range for the network parameters for the requesting network element, allowing the data analysis network element to determine recommended network parameters based on this acceptable range, thus preventing the recommended network parameters determined by the data analysis network element from exceeding its acceptable range. It should be understood that the request message can carry a list of network parameters, including at least one requested network parameter.

[0097] The analysis request network element's desired network metric may include the type of the desired network metric, or the type and value (or range) of the desired network metric. The desired network metric can be a value that the analysis request network element hopes the network metric will reach. For example, if the analysis request network element wants to adjust network parameters to achieve a certain network metric value, it can send this value to the data analysis network element, allowing the data analysis network element to predict recommended network parameters to achieve that value. Therefore, the data analysis network element can determine the network parameters that will achieve the desired network metric, and use this information to determine the recommended network parameters. In one possible implementation, the type of the network metric desired by the first analysis request network element is the same as the type of the network metric desired by the second analysis request network element. For example, for service experience analysis, both the type of the network metric desired by the first and second analysis request network elements are experience ratings, such as MOS. In another possible implementation, the type of network metric expected by the first analysis requesting network element in this application may be different from the type of network metric expected by the second analysis requesting network element. For example, for business experience analysis, the type of network metric expected by the first analysis requesting network element may be experience score (such as MOS), while the type of network metric expected by the second analysis requesting network element may be the proportion of business experience quality that meets the standard.

[0098] Taking the first request message as an example, the network metric can be MOS. If the first analysis request network element expects a MOS of not less than 4.5, then the data analysis network element can set network parameters with a MOS of not less than 4.5 and determine the recommended first network parameters based on these network parameters, where 0 ≤ MOS ≤ 5. Furthermore, the MOS expected by the second analysis request network element may be the same as or different from the MOS expected by the first analysis request network element.

[0099] In one possible implementation, the request message (e.g., a first request message and / or a second request message) may further include requirement information for recommended network parameters. This requirement information can be used to indicate the selection of recommended network parameters from the range of network parameters required by the requesting network element and / or the range of network parameters corresponding to the network indicators expected by the requesting network element. Specifically, the requirement information can be used to indicate the maximum or minimum network parameter within the required range of network parameters and / or the range of network parameters corresponding to the network indicators expected by the requesting network element as the recommended network parameter; alternatively, the requirement information can be used to indicate the network parameter corresponding to the maximum or minimum value of the predicted network indicator as the recommended network parameter. Furthermore, the requirement information can also be used in a cost function. This cost function is the objective function used to find the optimal solution using a trained model, used to determine the optimal network parameter as the recommended value from multiple network parameters that satisfy the network indicators expected by the requesting network element. Specifically, the requirement information can be used to indicate that the cost function of the recommended network parameter is minimized, at which point the system overhead corresponding to the recommended network parameter is minimized. For example, the first request message may also include requirement information for the first analysis request network element, which can be used to determine the recommended network parameters corresponding to the first analysis request network element; and / or, the second request message may also include requirement information for the second analysis request network element, which can be used to determine the recommended network parameters corresponding to the second analysis request network element.

[0100] In one possible implementation, if the request message includes the network metric expected by the requesting network element, the request message may also include the expected percentage of the network metric that the network element expects to achieve that expected metric. Taking the network metric MOS as an example, this expected percentage may indicate the expected percentage of the user's MOS that the requesting network element hopes to achieve after adjusting the network parameters according to the analysis results corresponding to the data request message. For example, this expected percentage may be no less than 90%. For example, the first request message may also include the expected percentage of the first requesting network element, and / or the second request message may also include the expected percentage of the second requesting network element.

[0101] In one possible implementation, the request message may also include the analysis type requested by the analysis requesting network element. For example, both the first request message and the second request message carry an analysis type identifier corresponding to the business experience analysis.

[0102] In this application, the request message shown in S101 can be a message requesting a data analysis network element to provide analysis services, or a subscription request requesting to subscribe to analysis services. If it is a message requesting the provision of analysis services, the data analysis network element outputs the analysis results to the analysis requesting network element all at once, based on the request message. If it is a subscription message for analysis services, the data analysis network element outputs the analysis results to the analysis requesting network element multiple times, either periodically or through event triggering, based on the request message, until the analysis requesting network element cancels the subscription.

[0103] If the request message is a subscription request, the request message may also include a subscription identifier to identify the subscription. The analysis request network element can then distinguish different analysis subscriptions by the subscription identifier.

[0104] For example, the first request message from the first analysis request network element may carry a subscription identifier #1, and the second request message from the second analysis request network element may carry a subscription identifier #2. Then, after the data analysis network element receives the subscription, each message transmitted between the first analysis request network element and the data analysis network element may carry the subscription identifier #1, and each message transmitted between the second analysis request network element and the data analysis network element may carry the subscription identifier #2.

[0105] S102: The data analysis network element determines the third network indicator based on the first network indicator and the second network indicator. The third network indicator is the network indicator that the first analysis request network element and the second analysis request network element both expect.

[0106] If the first network metric and the second network metric are the same, then the third network metric can be either the first network metric or the second network metric. For example, taking business experience analysis as an example, if both the first network element metric and the second network metric have a MOS of not less than 4.5, then the third network metric can be a MOS of not less than 4.5.

[0107] If the first and second network metrics are different, the third network metric can be determined based on the first and / or second network metrics. For example, the third network metric can be the intersection of the first and second network metrics. Taking business experience analysis as an example, if the first network metric is MOS not less than 4.5 and the second network metric is MOS not less than 4, then the third network metric can be MOS not less than 45. Alternatively, the third network metric can also be a compromise value between the first and second network metrics, such as MOS not less than 4.5 for the first network metric, MOS not less than 4 for the second network metric, and MOS not less than 4.3 for the third network metric. Furthermore, if no network parameter satisfies the intersection of the first and second network metrics, the data analysis network element can use the union of the first and second network metrics as the third network parameter. Satisfying the intersection of the first and second network metrics means that, even if the independent variable of the trained model includes any network parameter within the range required by the first analysis request network element and any network parameter within the range required by the second analysis request network element, it is impossible for the dependent variable of the model to fall within the intersection of the first and second network metrics.

[0108] It should be understood that if the third network indicator differs from the first network indicator, the data analysis network element can send a first message to the first analysis request network element. This first message is used to modify the desired network indicator to the third network indicator. Similarly, if the third network indicator differs from the second network indicator, the data analysis network element can send a message (which could be the first message or another message) to the second analysis request network element to modify the desired network indicator to the third network indicator.

[0109] Furthermore, if the types of the first network metric and the second network metric are different, the type of the third network metric can be the same as one of the first and second network metric, or the third network metric can include both the first and second network metric. For example, for service experience analysis, if the first analysis requesting network element expects a MOS of no less than 4.5, and the second analysis requesting network element expects a service experience quality compliance rate of no less than 90%, then the third network metric is a MOS of no less than 4.5 for a proportion greater than or equal to 90%.

[0110] S103: The data analysis network element determines recommended third network parameters and recommended fourth network parameters based on the third network indicator, the first network parameters requested by the first analysis request network element, and the second network parameters requested by the second analysis request network element. The recommended third network parameters correspond to the first network parameters, that is, the recommended third network parameters are determined based on the first network parameters; the recommended fourth network parameters correspond to the second network parameters, that is, the recommended fourth network parameters are determined based on the second network parameters.

[0111] In S103, the data analysis network element can determine the recommended network parameters using the trained model and based on the third network metric, the first network parameters requested by the first analysis requesting network element, and the second network parameters requested by the second analysis requesting network element. If no pre-trained model exists, the data analysis network element must first enter the model training phase to obtain a trained model. During the model training phase, the input data consists of data collected by the data analysis network element, including the model's independent variables (including network parameters) and corresponding dependent variables (including network metrics). The output is the structure and internal parameters of the network model, i.e., the trained model. At this point, the data analysis network element obtains the trained model. If the data analysis network element already has a trained model—for example, obtained through a previous training phase or received from another network element or device—then the data analysis network element can use the trained model for inference, prediction, or recommendation. When the model is used for inference and prediction, the model's input data can include independent variables, and the model's output can include dependent variables. When the trained model is used to determine the recommended independent variables, the model's input data may include the predicted dependent variables of the model (including one or more network metrics to be achieved, specifically including a third network metric in S103), and the model's output may include at least one type of recommended independent variable (e.g., including recommended third network parameters and fourth recommended network parameters).

[0112] Furthermore, the data analysis network element can determine the type of network parameters requested by the requesting network element based on the request message. Based on the requested network parameter type, it can select one or more network parameters of the same type as the requested network parameters from multiple types of recommended independent variables in the trained model, and use these as recommended network parameters. In addition, the data analysis network element can also determine other types of recommended network parameters besides the requested type (hereinafter referred to as unrequired network parameters). These unrequired network parameters can take the current value or historical average of the network parameters of that type, or they can take the predicted value of the network parameter of that type with the highest probability of occurrence in the future.

[0113] Taking business experience analysis as an example, if the first analysis requesting network element is SMF, and the network parameters required by SMF include bit rate and end-to-end latency, that is, the first network parameters include bit rate and end-to-end latency, and the second analysis requesting network element is AF, and the network parameters required by AF include DNAI, that is, the second network parameters include DNAI, then the data analysis network element can determine at least one set of network parameters that meet the third network indicator, and each set of network parameters includes at least DNAI, bit rate and end-to-end latency.

[0114] Then, based on the model and the network metrics desired by the one or more analysis requesting network elements, the data analysis network element analyzes and outputs recommended values ​​for one or more corresponding network parameters. These recommended values ​​include those for the requested network parameters, and may also include those for parameters not requested. For example, if the SMF requests a network parameter of bit rate, the data analysis network element can determine the recommended bit rate and the recommended end-to-end delay, and send the recommended bit rate and recommended end-to-end delay to the analysis requesting network element.

[0115] For example, after the data analysis network element can determine at least one set of network parameters that meet the third network metric, the data analysis network element can further determine a set of network parameters from the at least one set of network parameters based on the bit rate and end-to-end delay values ​​required by the SMF and the DNAI value required by the AF. The bit rate and end-to-end delay in this set of network parameters are recommended third network parameters, and the DNAI in this set of network parameters is recommended fourth network parameters. For example, in the set of network parameters determined by the data analysis network element, the bit rate value is within the range of the bit rate required by the SMF, the end-to-end delay value is within the range of the end-to-end delay required by the SMF, and the DNAI is within the range of the DNAI required by the AF.

[0116] In one possible implementation, the dependent variable of the data analysis network element may further include the predicted proportion of the network metric reaching the third network metric. This predicted proportion indicates the percentage by which the actual network metric is expected to reach the third network metric after adjustments using both the recommended third and fourth network parameters. The data analysis network element may then send the third network metric and the predicted proportion. The predicted proportion may be equal to or greater than the expected proportion carried in the first request message, or it may be less than the expected proportion carried in the first request message; alternatively, the predicted proportion may be equal to or greater than the expected proportion carried in the second request message, or it may be less than the expected proportion carried in the second request message. The predicted proportion helps the analysis requesting network element determine whether to accept the recommended network parameters and make adjustments.

[0117] It should be understood that the training process of the model described here can be performed within the data analysis network element, or other network elements can obtain the trained model through training and then send the model to the data analysis network element. If the data analysis network element determines the model, it can collect data and train the model according to a certain period, thus eliminating the need to retrain the model every time network intelligent analysis is performed.

[0118] S104: The data analysis network element sends the recommended third network parameters and the recommended fourth network parameters.

[0119] In one possible implementation, the data analysis network element may send a first analysis result to a first analysis request network element or a second analysis request network element. This first analysis result may include recommended third network parameters and / or recommended fourth network parameters. Furthermore, the first analysis result may also include at least one of the required third or fourth network parameters, the third network indicator, and the prediction ratio.

[0120] use Figure 4 The method shown allows a data analysis network element to receive service analysis request messages from multiple analysis request network elements. Based on the network indicators required by one of the service analysis request network elements, the recommended network parameters for the two analysis request network elements can be determined. This avoids the network performance degradation or service interruption caused by multiple analysis request network elements adjusting network parameters according to different network indicator targets, thereby improving the reliability of intelligent analysis.

[0121] The following example uses NWDAF as the data analysis network element, SMF as the first analysis request network element, and AF as the second analysis request network element. Figure 5 A communication method provided in an embodiment of this application will be described.

[0122] like Figure 5 As shown, the method may include the following steps:

[0123] S201: SMF sends a subscription request to NWDAF.

[0124] The subscription request may include an analysis type identifier corresponding to the business experience analysis, the network metrics expected by the SMF, and the network parameters required by the SMF. For example, the network metric expected by the SMF is a MOS greater than 4.0, and the network parameters required by the SMF include bit rate.

[0125] In one possible implementation, the subscription message may also carry a subscription identifier.

[0126] Accordingly, NWDAF receives the request message.

[0127] S202: NWDAF sends a response message to SMF regarding the subscription request.

[0128] This response message can be used to indicate a successful subscription. The response message for the subscription request may include the subscription identifier from S201.

[0129] Prior to S202, NWDAF could execute S202 after confirming acceptance of the subscription request.

[0130] In one possible implementation, NWDAF may also store the subscription content of SMF after accepting the subscription request of SMF. The subscription content includes, but is not limited to, the service type identifier, the network metrics expected by SMF, the network parameters required by SMF, and the subscription identifier in the subscription request.

[0131] Accordingly, SMF receives a response message for the subscription request.

[0132] S203: AF sends a subscription request to NWDAF via NEF.

[0133] The subscription request may include the analysis type identifier corresponding to the business experience analysis, the network metrics expected by AF, and the network parameters required by AF. For example, the network metric expected by AF is MOS greater than 4.5, and the network parameters required by AF include DNAI.

[0134] In one possible implementation, the subscription message may also carry a subscription identifier.

[0135] Accordingly, the NWDAF receives the request message and stores the subscription content corresponding to the AF, including but not limited to the service type identifier, the network parameters required by the AF, the network metrics expected by the AF, and the subscription identifier.

[0136] S204: NWDAF determines that the service type requested by SMF is the same as the service type requested by AF, but the network metrics expected by SMF are inconsistent with the network metrics expected by AF. NWDAF further determines that the network metric commonly expected by SMF and AF is MOS greater than 4.0.

[0137] If NWDAF determines that the analysis type identifier in the subscription request of S201 is the same as the analysis type identifier in the subscription request of S203, and the network metric expected by SMF in the subscription request of S201 is different from the network metric expected by AF in S203, then NWDAF can determine that the analysis type requested by SMF and AF is the same but the expected network metrics are inconsistent.

[0138] S205: NWDAF sends a first message to AF via NEF, which is used to modify the desired network metric to MOS greater than 4.0. This first message may also carry the subscription identifier from S204.

[0139] Accordingly, AF receives the first message.

[0140] S206: The AF sends an updated subscription request to the NWDAF via the NEF, carrying a desired network metric indicating a MOS greater than 4.0. The updated subscription request may carry the subscription identifier shown in S204.

[0141] Accordingly, the NWDAF receives the updated subscription request and updates the AF's subscription content according to the updated subscription request. The updated AF subscription content includes the service type identifier, the network metrics expected by the AF (the values ​​in the subscription request updated in S206), the network parameters required by the AF, and the subscription identifier.

[0142] S207: NWDAF determines that the network metrics expected by the SMF subscription and the AF subscription are the same, and determines the recommended network parameters based on the expected network metrics, the network parameters required by the SMF, and the network parameters required by the AF.

[0143] For example, the recommended network parameters include: a recommended bit rate of 14 Mbps and a recommended DNAI identifier of DNAI#1.

[0144] Optionally, NWDAF can associate the recommended bit rate with the identifier of SMF and the subscription identifier in S201, and associate the recommended DNAI with the identifier of AF and the subscription identifier in S204.

[0145] S208: NWDAF sends the recommended bit rate to SMF.

[0146] Specifically, NWDAF can send the recommended bit rate and the subscription identifier in S201 to SMF.

[0147] Accordingly, the recommended bit rate for SMF reception.

[0148] S209: NWDAF sends the recommended DNAI to AF via NEF.

[0149] Specifically, NWDAF can send the recommended DNAI and subscription identifier in S204 to AF via NEF.

[0150] Accordingly, AF receives the recommended DNAI.

[0151] based on Figure 5The process shown illustrates that when multiple analysis request network elements receive analysis requests, if the NWDAF determines that the service type identifiers of the multiple analysis requests are the same, but the expected network metric values ​​are different, then the NWDAF can determine the network metric commonly expected by the multiple analysis request network elements. Determining the recommended network parameters based on this commonly expected network metric can avoid conflicts when different analysis request network elements adjust their network parameters.

[0152] In one possible implementation, if the type of the first network parameter coincides with the type of the second network parameter, for example, the type of the first network parameter (or some network parameters included in the first network parameter) is the same as the type of the second network parameter (or some network parameters included in the second network parameter), then in S104, the data analysis network element can send recommended network parameters to the first analysis request network element and / or the second analysis request network element. At this time, the type of recommended network parameters obtained by the first analysis request network element may be different from the type of the first network parameter, and / or, the type of recommended network parameters obtained by the second analysis request network element may be different from the type of the second network parameter.

[0153] The implementation of S104 will be illustrated below with examples of different cases, including whether the types of the first network parameter and the types of the second network parameter overlap.

[0154] Case 1: The first network parameter corresponds to the third network parameter, the second network parameter corresponds to the fourth network parameter, and the first network parameter does not overlap with the second network parameter. In S104, the data analysis network element can send the recommended third network parameter to the first analysis request network element and send the recommended fourth network parameter to the second analysis request network element.

[0155] It should be understood that when network parameter A is the same as network parameter B, for ease of explanation, network parameter A can be said to correspond to network parameter B. Network parameter A and network parameter B can include at least one type of network parameter. For example, if network parameter A and network parameter B both include network parameters a and b, then network parameter A can be said to correspond to network parameter B, and / or network parameter A (or network parameter B) can correspond to network parameters a and b.

[0156] Case 2: The first network parameter corresponds to the third and fourth network parameters, the second network parameter corresponds to the fourth network parameter, and there is overlap between the first and second network parameters, while the third and fourth network parameters do not overlap.

[0157] In scenario 2, after determining the recommended third and fourth network parameters, the data analysis network element can recommend the network parameters using any of the following methods:

[0158] In Method 1, the data analysis network element can send the recommended third network parameters and the recommended fourth network parameters to the first analysis request network element. In this case, it is not necessary to send the recommended third network parameters and the recommended fourth network parameters to the second analysis request network element.

[0159] For example, the first analysis requesting network element is the SMF, and the first network parameter requested by the SMF includes the bit rate. The second analysis requesting network element is the UPF, and the second network parameter requested by the UPF includes the bit rate and the end-to-end delay. Therefore, both the first network parameter requested by the SMF and the second network parameter requested by the UPF include the bit rate. In Mode 1, the data analysis network element can send the recommended bit rate and recommended end-to-end delay to the SMF, and send the recommended bit rate to the UPF.

[0160] As can be seen in Method 1, the network parameters recommended by the data analysis network element to the first analysis request network element and the second analysis request network element are of the same type as the network parameters required by the first analysis request network element and the second analysis request network element, respectively, so that the recommended network parameters can meet the requirements of the analysis request network element.

[0161] Method 2: The data analysis network element can send recommended third network parameters to the first analysis request network element and recommended fourth network parameters to the second analysis request network element.

[0162] For example, the first analysis requesting network element is the UPF, and the first network parameters requested by the UPF include the bit rate and end-to-end delay. The second analysis requesting network element is the SMF, and the second network parameter requested by the SMF includes the bit rate. Therefore, both the first network parameter requested by the UPF and the second network parameter requested by the SMF include the bit rate. In mode 2, the data analysis network element can send the recommended end-to-end delay to the UPF and the recommended bit rate to the SMF.

[0163] Furthermore, in Method 2, since the recommended fourth network parameter is not sent to the first analysis requesting network element according to the first analysis request, the data analysis network element can send a second message to the first analysis requesting network element. This second message can be used to cancel the first analysis requesting network element's request (or subscription) for the requested fourth network parameter, or to modify the network parameter requested by the first analysis requesting network element to a third network parameter, or to indicate that the recommended fourth network parameter has been sent to the second analysis requesting network element, or to instruct the second analysis requesting network element to adjust the network parameters according to the recommended fourth network parameter. For example, continuing with the previous example, the data analysis network element can also send a second message to the UPF to indicate the cancellation of the UPF's request for the recommended bit rate.

[0164] Method 3: The data analysis network element can send the recommended third network parameters and the recommended fourth network parameters to the first analysis request network element. In this case, it is not necessary to send the recommended third network parameters and the recommended fourth network parameters to the second analysis request network element.

[0165] For example, the first analysis requesting network element is the UPF, and the first network parameters requested by the UPF include the bit rate and end-to-end delay. The second analysis requesting network element is the SMF, and the second network parameter requested by the SMF includes the bit rate. Therefore, both the first network parameter requested by the UPF and the second network parameter requested by the SMF include the bit rate. In mode 3, the data analysis network element can send the recommended bit rate and recommended end-to-end delay to the UPF. In this case, the data analysis network element does not need to send the recommended bit rate to the SMF.

[0166] Furthermore, in Method 3, since the recommended network parameters corresponding to the second network parameters are not sent to the second analysis requesting network element according to the second analysis request, the data analysis network element can send a third message to the second analysis requesting network element. This third message can be used to cancel the second analysis requesting network element's request (or subscription) for the recommended fourth network parameters, or it can be used to indicate that the requested fourth network parameters have been sent to the first analysis requesting network element, or it can be used to indicate that the first analysis requesting network element should adjust the network parameters according to the recommended fourth network parameters. For example, continuing with the previous example, the data analysis network element can also send a third message to the SMF to indicate the cancellation of the SMF's request for the recommended bit rate.

[0167] According to methods 2 and 3, when the data analysis network element determines that there is overlap between the first network parameter and the second network parameter, it will not send the recommended overlapping network parameter to both analysis request network elements. Instead, it will send the recommended overlapping network parameter to one of the analysis request network elements to avoid both analysis request network elements adjusting according to the recommended network parameter, which would cause excessive adjustment of the network parameter.

[0168] The following example uses NWDAF as the data analysis network element, UPF as the first analysis request network element, and SMF as the second analysis request network element. Figure 6 Another communication method provided in the embodiments of this application will be described.

[0169] like Figure 6 As shown, the method may include the following steps:

[0170] S301: SMF sends a subscription request to NWDAF.

[0171] The subscription request may include an analysis type identifier corresponding to the business experience analysis, the network metrics expected by the SMF, and the network parameters required by the SMF. For example, the network metric expected by the SMF is a MOS greater than 4.0, and the network parameters required by the SMF include bit rate.

[0172] In one possible implementation, the subscription message may also carry a subscription identifier.

[0173] Accordingly, NWDAF receives the request message.

[0174] S302: NWDAF sends a response message to SMF regarding the subscription request.

[0175] This response message can be used to indicate a successful subscription. The response message for the subscription request may include the subscription identifier from S301.

[0176] Prior to S302, NWDAF could execute S302 after confirming acceptance of the subscription request.

[0177] In one possible implementation, NWDAF may also store the subscription content of SMF after accepting the subscription request of SMF. The subscription content includes, but is not limited to, the service type identifier, the network metrics expected by SMF, the network parameters required by SMF, and the subscription identifier in the subscription request.

[0178] Accordingly, SMF receives a response message for the subscription request.

[0179] S303: UPF sends a subscription request to NWDAF.

[0180] The subscription request may include the analysis type identifier corresponding to the business experience analysis, the network metrics expected by the UPF, and the network parameters required by the AF. For example, the network metrics expected by the UPF are MOS greater than 4.0, and the network parameters required by the UPF include bit rate and end-to-end latency.

[0181] In one possible implementation, the subscription message may also carry a subscription identifier.

[0182] Accordingly, NWDAF receives the request message and stores the subscription content corresponding to UPF, including but not limited to storing the service type identifier, the network parameters required by UPF, the network metrics expected by UPF, and the subscription identifier.

[0183] S304: NWDAF determines that the service type requested for analysis by SMF is the same as the service type requested for analysis by UPF, and that the network parameters requested by SMF and AF overlap. The overlapping network parameter is the bit rate.

[0184] Specifically, if NWDAF determines that the analysis type identifier in the subscription request of S301 is the same as the analysis type identifier in the subscription request of S303, and the network parameters required by SMF in the subscription request of S301 and the network parameters required by UPF in S303 both include the same type of network parameters (bit rate), then NWDAF can determine that the service type requested by SMF is the same as the service type requested by UPF, and the network parameters requested by SMF overlap with the network parameters requested by AF.

[0185] S305: NWDAF sends a second message to UPF, which is used by UPF to modify the requested network parameters to end-to-end latency.

[0186] Alternatively, a third message can be used to instruct the SMF to adjust the bit rate according to the recommended bit rate.

[0187] For example, the third message may include at least one of the following: the subscription identifier in S304, an identifier indicating that there is something to be confirmed (i.e., the network parameters of the modified requirements need to be confirmed), information on modifying the network parameters to end-to-end latency, and the identifier of SMF.

[0188] Accordingly, the UPF receives the first message.

[0189] S306: The UPF sends an updated subscription request to the NWDAF, which carries a required network metric indicating that MOS is greater than 4.0. The updated subscription request may carry the subscription identifier shown in S204.

[0190] Accordingly, NWDAF receives the updated subscription request and updates the UPF's subscription content based on the updated subscription request. The updated UPF subscription content includes the service type identifier, the network metrics expected by the UPF (the values ​​in the subscription request updated in S206), the network parameters required by the UPF, and the subscription identifier.

[0191] In another possible example, the NWDAF may also send a notification of a requested network parameter conflict to the SMF. This notification may carry at least one of the subscription identifier from S301, the conflicting transmission (here, the bit rate), and the UPF identifier, allowing the SMF to decide whether to change the requested network parameters. If the SMF decides not to change the network parameters requested by the SMF, the SMF may notify the UPF that the recommended bit rate is no longer being requested by the UPF. In this case, the UPF can execute S306, and S305 is not required.

[0192] In another possible example, if the SMF decides to change the network parameters required by the SMF, the SMF can send a message to the NWDAF to cancel its subscription to the recommended bit rate. The NWDAF can then send the recommended bit rate to the UPF, which will adjust the bit rate accordingly. In this case, steps S305 and S306 do not need to be executed.

[0193] S307: NWDAF determines that the network parameters required in the SMF subscription and the UPF subscription do not overlap, and determines the recommended network parameters based on the expected network metrics, the network parameters required by the SMF, and the network parameters required by the UPF.

[0194] Optionally, NWDAF can associate the recommended bit rate with the identifier of SMF and the subscription identifier in S301, and associate the recommended end-to-end delay with the identifier of UPF and the subscription identifier in S304.

[0195] S308: NWDAF sends the recommended bit rate to SMF.

[0196] Specifically, NWDAF can send the recommended bit rate and the subscription identifier in S201 to SMF.

[0197] Accordingly, the recommended bit rate for SMF reception.

[0198] S309: NWDAF sends the recommended end-to-end latency and the subscription identifier from S304 to UPF.

[0199] Accordingly, the UPF receives the recommended end-to-end latency.

[0200] use Figure 6 As shown in the process, NWDAF can decide whether to obtain the recommended bit rate from either SMF or UPF when both SMF and UPF request the recommended bit rate, thus avoiding recommendation conflicts.

[0201] In one possible implementation, after S104, if the recommended third network parameter and the recommended fourth network parameter are sent to the first analysis request network element and the second analysis request network element, respectively, then if the first analysis request network element or the second analysis request network element does not accept the recommended network parameter from the data analysis network element, the data analysis network element can re-determine the recommended network parameter corresponding to the first analysis request network element (hereinafter referred to as the recommended fifth network parameter) and the recommended network parameter corresponding to the second analysis request network element (hereinafter referred to as the recommended sixth network parameter). It should be understood that the recommended fifth network parameter corresponds to the first network parameter; that is, the recommended fifth network parameter is determined based on the first network parameter. Similarly, the recommended sixth network parameter corresponds to the second network parameter; that is, the recommended sixth network parameter is determined based on the second network parameter.

[0202] Specifically, the data analysis network element can determine, based on the fourth message from the first analysis requesting network element, that the first analysis requesting network element does not accept the recommended third network parameter. For example, the fourth message can be used to instruct the first analysis requesting network element not to accept the recommended third network parameter, or it can be used to instruct the first analysis requesting network element to request a re-determination of the recommended network parameter (such as re-determination of the recommended third network parameter or the recommended first network parameter). If the analysis requesting network element determines that it cannot adjust the network parameter according to the type or value of the recommended network parameter, it can determine that it does not accept the recommended network parameter.

[0203] The data analysis network element can re-determine the recommended network parameters based on the fourth information. In one possible implementation, the data analysis network element can use the historical average or maximum likelihood value of the unacceptable network parameter as the recommended fifth network parameter, and determine the recommended sixth network parameter based on the recommended fifth network parameter. For example, a network parameter belonging to the same group as the recommended network parameter and of the same type as the second network parameter can be used as the recommended sixth network parameter, wherein the recommended fifth network parameter and the recommended sixth network parameter belong to a group of network parameters that can satisfy the third network metric.

[0204] Furthermore, the data analysis network element can also determine a set of network parameters from at least one set of network parameters that satisfy the third network metric, and use the network parameters in that set that are of the same type as the first network parameters as recommended fifth network parameters, and the network parameters in that set that are of the same type as the second network parameters as recommended sixth network parameters. Alternatively, the data analysis network element can re-determine the updated third network metric based on the first and second network metrics, and then determine the recommended fifth and sixth network parameters based on the updated third network metric. For details on how to implement this, please refer to the description of determining the recommended third and fourth network parameters based on the third network metric.

[0205] Similarly, if the second analysis requesting network element does not accept the recommended fourth network parameter, the second analysis requesting network element can send a message to the data analysis network element to indicate that it does not accept the recommended fourth network parameter, and the data analysis network element can re-determine the recommended network parameter based on the message.

[0206] The following example uses NWDAF as the data analysis network element, UPF as the first analysis request network element, and SMF as the second analysis request network element. Figure 7 Another communication method provided in the embodiments of this application will be described.

[0207] like Figure 7 As shown, the communication method provided in this application embodiment may include the following steps:

[0208] S401: NWDAF sends the recommended end-to-end delay to UPF and the recommended bit rate to SMF.

[0209] The recommended end-to-end latency and recommended bit rate meet the network metrics that both UPF and SMF expect. For example, the recommended end-to-end latency is 10ms and the recommended bit rate is 5Mbps.

[0210] For example, the implementation of S401 can be found in [reference needed]. Figure 6 The explanation in the document.

[0211] S402: After receiving the recommended end-to-end latency, the UPF determines that the recommended end-to-end latency is unacceptable.

[0212] In one possible implementation, although the recommended end-to-end latency value is within the range of the end-to-end latency required by the UPF, the UPF is unable to adjust the end-to-end latency to the recommended value based on the current network operation, and therefore determines that the end-to-end latency is unacceptable.

[0213] For example, if the UPF does not currently support 10ms end-to-end latency, then the UPF can determine that the recommended end-to-end latency is unacceptable.

[0214] S403: The UPF sends a fourth message to the NWDAF, which indicates that the UPF does not accept the recommended end-to-end delay.

[0215] Accordingly, NWDAF receives the fourth message.

[0216] S404: NWDAF uses the historical average of the recommended bit rate as the updated end-to-end delay, and determines the updated bit rate that meets network metrics based on the updated end-to-end delay.

[0217] S405: NWDAF sends an updated end-to-end delay to UPF.

[0218] Accordingly, the UPF receives the updated end-to-end latency.

[0219] S406: NWDAF sends an updated bit rate to SMF.

[0220] Accordingly, the SMF receives the updated bit rate.

[0221] use Figure 7As shown in the process, NWDAF can redetermine the recommended bit rate and end-to-end delay if UPF does not accept the recommended end-to-end delay, and indicate the recommended bit rate and recommended end-to-end delay to SMF and UPF respectively, thus avoiding network parameter adjustments and results that do not meet the expected network performance.

[0222] Figure 8 and Figure 9 The diagram illustrates the possible communication devices provided in the embodiments of this application. These communication devices can be used to implement the functions of the data analysis network element or analysis request network element in the above method embodiments, and thus can also achieve the beneficial effects of the above method embodiments. In the embodiments of this application, the communication device can be a data analysis network element or analysis request network element, or it can be a module (such as a chip) applied to the data analysis network element or analysis request network element.

[0223] like Figure 8 As shown, the communication device 800 includes a processing unit 810 and a transceiver unit 820. The communication device 800 is used to implement the functions of the data analysis network element or the analysis request network element in the above method embodiments.

[0224] In the first embodiment, the communication device is used to implement the function of the data analysis network element in the above method embodiment. The transceiver unit 820 can be used to receive a first request message and a second request message. The first request message comes from the first analysis request network element and is used to request recommended first network parameters. The first request message includes the first network parameters and a first network indicator required by the first analysis request network element. The first network indicator is the network indicator expected by the first analysis request network element. The second request message comes from the second analysis request network element and is used to request recommended second network parameters. The second request message includes the second network parameters and a second network indicator required by the second analysis request network element. The second network indicator is the network indicator expected by the second analysis request network element. The data analysis network element can also determine a third network indicator based on the first and second network indicators. The third network indicator is the network indicator commonly expected by the first and second analysis request network elements. The processing unit 810 can be used to determine recommended third and fourth network parameters based on the third network indicator, the first network parameters requested by the first analysis request network element, and the second network parameters requested by the second analysis request network element. The transceiver unit 820 can also be used to send the recommended third and fourth network parameters.

[0225] As one possible implementation, the predicted network metrics corresponding to the recommended third network parameters and the recommended fourth network parameters are within the range of the third network metric.

[0226] As one possible implementation, the transceiver unit 820 can also be used to send a first message to the first analysis requesting network element and / or the second analysis requesting network element, the first message being used to modify the desired network indicator to a third network indicator.

[0227] In one possible design, if the first network parameter corresponds to the third and fourth network parameters, and the second network parameter corresponds to the fourth network parameter, then the transceiver unit 820 can also be used to send the recommended third network parameter to the first analysis requesting network element, and the transceiver unit 820 can also be used to send the recommended fourth network parameter to the second analysis requesting network element.

[0228] In one possible design, the transceiver unit 820 can also be used to send a second message to the first analysis requesting network element, the second message being used by the first analysis requesting network element to modify the requested network parameters to a third network parameter.

[0229] In one possible design, if the first network parameter corresponds to the third and fourth network parameters, and the second network parameter corresponds to the third and / or fourth network parameters, then the transceiver unit 820 can also be used to send the recommended third and fourth network parameters to the first analysis request network element.

[0230] In one possible design, the transceiver unit 820 can also be used to send a third message to the second analysis requesting network element, the third message being used to cancel obtaining the recommended network parameters based on the second network parameters requested by the second analysis requesting network element.

[0231] In one possible design, the transceiver unit 820 can also be used to send a recommended third network parameter to the first analysis requesting network element and a recommended fourth network parameter to the second analysis requesting network element, wherein the recommended third network parameter corresponds to the first network parameter and the recommended fourth network parameter corresponds to the second network parameter.

[0232] In one possible design, transceiver unit 820 can also receive a fourth message from the first analysis requesting network element, the fourth message indicating that the recommended third network parameter is not accepted. Processing unit 810 can further determine recommended fifth and sixth network parameters based on the fourth message, the third network indicator, the first network parameter requested by the first analysis requesting network element, and the second network parameter requested by the second analysis requesting network element. The recommended fifth network parameter corresponds to the first network parameter, and the recommended sixth network parameter corresponds to the second network parameter. The value of the recommended fifth network parameter is different from the value of the recommended third network parameter. Transceiver unit 820 can also be used to send the recommended fifth network parameter to the first analysis requesting network element and the recommended sixth network parameter to the second analysis requesting network element.

[0233] In the second embodiment, the communication device is used to implement the function of the first analysis request network element in the above method embodiment. The processing unit 810 can then be used to determine a first request message. The first request message requests recommended first network parameters. The first request message includes the first network parameters and a first network indicator required by the first analysis request network element. The first network indicator is the network indicator expected by the first analysis request network element. The transceiver unit 820 can also be used to send the first request message to the data analysis network element.

[0234] In one possible design, if the first network parameter corresponds to the third network parameter and the fourth network parameter, the transceiver unit 820 can also be used to receive the recommended third network parameter from the data analysis network element. The recommended third network parameter is determined based on a third network indicator, the first network parameter requested by the first analysis requesting network element, and the second network parameter requested by the second analysis requesting network element. The third network indicator is a network indicator commonly desired by both the first and second analysis requesting network elements, and is determined based on the first and second network indicators. The second network indicator is the network indicator desired by the second analysis requesting network element.

[0235] In one possible design, the transceiver unit 820 can also be used to receive a first message from the data analysis network element, the first message being used to modify the desired network indicator to the third network indicator. The processing unit 810 can also determine whether to modify the desired network indicator to the third network indicator based on the first message.

[0236] In one possible design, the transceiver unit 820 can also be used to receive a second message from the data analysis network element, the second message being used by the first analysis request network element to modify the requested network parameters to the third network parameters.

[0237] In one possible design, if the first network parameter corresponds to the third network parameter and the fourth network parameter, the transceiver unit 820 can also be used to receive the recommended third network parameter and the recommended fourth network parameter from the data analysis network element. The recommended third network parameter and the recommended fourth network parameter are determined based on a third network indicator, the first network parameter requested by the first analysis request network element, and the second network parameter requested by the second analysis request network element. The third network indicator is a network indicator commonly expected by the first analysis request network element and the second analysis request network element, and is determined based on the first network indicator and the second network indicator. The second network indicator is a network indicator expected by the second analysis request network element.

[0238] In one possible design, the predicted network metrics corresponding to the recommended third network parameters and the recommended fourth network parameters are within the range of the third network metric.

[0239] In one possible design, transceiver unit 820 can also be used to receive recommended third network parameters from the data analysis network element. Transceiver unit 820 can also be used to send a fourth message to the data analysis network element, the fourth message indicating that the recommended third network parameters are not accepted. Transceiver unit 820 can also be used to receive recommended fifth network parameters from the data analysis network element, the recommended fifth network parameters corresponding to the first network parameters, the recommended fifth network parameters being determined based on a third network indicator, the first network parameters requested by the first analysis requesting network element, and the second network parameters requested by the second analysis requesting network element. The third network indicator is a network indicator commonly desired by the first analysis requesting network element and the second analysis requesting network element, the third network indicator being determined based on the first network indicator and the second network indicator, the second network indicator being the network indicator desired by the second analysis requesting network element.

[0240] In the third embodiment, the communication device is used to implement the function of the second analysis request network element in the above method embodiment. The processing unit 810 can be used to determine a second request message. The second request message requests recommended second network parameters. The second request message includes the second network parameters and second network indicators required by the second analysis request network element, where the second network indicator is the network indicator expected by the second analysis request network element. The transceiver unit 820 can be used to send the second request message to the data analysis network element.

[0241] In one possible design, the transceiver unit 820 can also be used to receive recommended fourth network parameters from the data analysis network element. The recommended fourth network parameters are determined based on a third network indicator, the first network parameters requested by the first analysis requesting network element, and the second network parameters requested by the second analysis requesting network element. The third network indicator is a network indicator commonly desired by both the first and second analysis requesting network elements, and is determined based on the second and first network indicators. The first network indicator is the network indicator desired by the first analysis requesting network element.

[0242] In one possible design, the transceiver unit 820 can also be used to receive a first message from the data analysis network element, the first message being used to modify the desired network metric to the third network metric. The processing unit 810 can be used to determine, based on the first message, whether to modify the desired network metric to the third network metric.

[0243] In one possible design, the transceiver unit 820 can also be used to receive a third message from the data analysis network element, the third message being used to cancel obtaining the recommended network parameters based on the second network parameters requested by the second analysis request network element.

[0244] In one possible design, the transceiver unit 820 can also be used to receive recommended fourth network parameters from the data analysis network element. The recommended fourth network parameters are determined based on a third network indicator, a first network parameter requested by the first analysis requesting network element, and a second network parameter requested by the second analysis requesting network element. The third network indicator is a network indicator commonly desired by both the first and second analysis requesting network elements, and is determined based on the second and first network indicators. The first network indicator is the network indicator desired by the first analysis requesting network element. The transceiver unit 820 can also be used to receive recommended sixth network parameters from the data analysis network element. The recommended sixth network parameter corresponds to the second network parameter and is determined based on the third network indicator, the first network parameter requested by the first analysis requesting network element, and the second network parameter requested by the second analysis requesting network element.

[0245] A more detailed description of the processing unit 810 and the transceiver unit 820 can be obtained directly from the relevant descriptions in the above method embodiments, and will not be repeated here.

[0246] like Figure 9 As shown, the communication device 900 includes a processor 910. As one implementation, the communication device 900 also includes an interface circuit 920, which is coupled to the processor 910. It is understood that the interface circuit 920 can be a transceiver or an input / output interface. As another implementation, the communication device 900 may also include a memory 930 for storing instructions executed by the processor 910, or storing input data required by the processor 910 to execute instructions, or storing data generated after the processor 910 executes instructions.

[0247] When the communication device 900 is used to implement the above method embodiment, the processor 910 is used to implement the function of the processing unit 810, and the interface circuit 920 is used to implement the function of the transceiver unit 820.

[0248] It is understood that the processor in the embodiments of this application can be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. A general-purpose processor can be a microprocessor or any conventional processor.

[0249] The method steps in the embodiments of this application can be implemented in hardware or by a processor executing software instructions. The software instructions can consist of corresponding software modules, which can be stored in random access memory, flash memory, read-only memory, programmable read-only memory, erasable programmable read-only memory, electrically erasable programmable read-only memory, registers, hard disks, portable hard disks, CD-ROMs, or any other form of storage medium known in the art. An exemplary storage medium is coupled to a processor, enabling the processor to read information from and write information to the storage medium. Of course, the storage medium can also be a component of the processor. The processor and storage medium can reside in an ASIC. Alternatively, the ASIC can reside in a base station or terminal. Of course, the processor and storage medium can also exist as discrete components in the base station or terminal.

[0250] In the above embodiments, implementation can be achieved entirely or partially through software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented entirely or partially in the form of a computer program product. The computer program product includes one or more computer programs or instructions. When the computer program or instructions are loaded and executed on a computer, the processes or functions described in the embodiments of this application are performed entirely or partially. The computer can be a general-purpose computer, a special-purpose computer, a computer network, a base station, a user equipment, or other programmable device. The computer program or instructions can be stored in a computer-readable storage medium or transferred from one computer-readable storage medium to another. For example, the computer program or instructions can be transferred from one website, computer, server, or data center to another website, computer, server, or data center via wired or wireless means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that integrates one or more available media. The available medium can be a magnetic medium, such as a floppy disk, hard disk, or magnetic tape; it can also be an optical medium, such as a digital video optical disc; or it can be a semiconductor medium, such as a solid-state drive. The computer-readable storage medium may be a volatile or non-volatile storage medium, or may include both types of storage media.

[0251] In the various embodiments of this application, unless otherwise specified or in case of logical conflict, the terminology and / or descriptions of different embodiments are consistent and can be referenced by each other. The technical features of different embodiments can be combined to form new embodiments according to their inherent logical relationship.

[0252] In this application, "at least one" means one or more, and "more than one" means two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, or B alone, where A and B can be singular or plural. In the textual description of this application, the character " / " generally indicates an "or" relationship between the preceding and following related objects; in the formulas of this application, the character " / " indicates a "division" relationship between the preceding and following related objects.

[0253] It is understood that the various numerical designations used in the embodiments of this application are merely for descriptive convenience and are not intended to limit the scope of the embodiments of this application. The order of the process numbers described above does not imply the order of execution; the execution order of each process should be determined by its function and internal logic.

Claims

1. A communication method, characterized in that, include: The data analysis network element receives a first request message and a second request message. The first request message comes from the first analysis request network element and is used to request recommended first network parameters. The first request message includes the first network parameters and a first network indicator required by the first analysis request network element. The first network indicator is the network indicator expected by the first analysis request network element. The second request message comes from the second analysis request network element and is used to request recommended second network parameters. The second request message includes the second network parameters and a second network indicator required by the second analysis request network element. The second network indicator is the network indicator expected by the second analysis request network element. The data analysis network element determines a third network indicator based on the first network indicator and the second network indicator. The third network indicator is a network indicator that is jointly expected by the first analysis request network element and the second analysis request network element. The data analysis network element determines the recommended third network parameters and the recommended fourth network parameters based on the third network indicator, the first network parameters requested by the first analysis request network element, and the second network parameters requested by the second analysis request network element. The data analysis network element sends the recommended third network parameters and the recommended fourth network parameters.

2. The method as described in claim 1, characterized in that, The predicted network metrics corresponding to the recommended third network parameters and the recommended fourth network parameters are within the range of the third network metric.

3. The method as described in claim 1 or 2, characterized in that, The method further includes: The data analysis network element sends a first message to the first analysis request network element and / or the second analysis request network element, the first message being used to modify the desired network indicator to a third network indicator.

4. The method as described in claim 1 or 2, characterized in that, The first network parameter corresponds to the third network parameter and the fourth network parameter, and the second network parameter corresponds to the fourth network parameter; The data analysis network element sends the recommended third network parameters and the recommended fourth network parameters, including: The data analysis network element sends the recommended third network parameters to the first analysis request network element; The data analysis network element sends the recommended fourth network parameters to the second analysis request network element.

5. The method as described in claim 4, characterized in that, The method further includes: The data analysis network element sends a second message to the first analysis request network element, the second message being used by the first analysis request network element to modify the requested network parameters to the third network parameters.

6. The method as described in claim 1 or 2, characterized in that, The first network parameter corresponds to the third network parameter and the fourth network parameter, and the second network parameter corresponds to the third network parameter and / or the fourth network parameter; The data analysis network element sends the recommended third network parameters and the recommended fourth network parameters, including: The data analysis network element sends the recommended third network parameter and the recommended fourth network parameter to the first analysis request network element.

7. The method as described in claim 6, characterized in that, The method further includes: The data analysis network element sends a third message to the second analysis request network element, the third message being used to cancel obtaining the recommended network parameters based on the second network parameters requested by the second analysis request network element.

8. The method according to any one of claims 1, 2, 5, and 7, characterized in that, The data analysis network element sends the recommended third network parameters and the recommended fourth network parameters, including: The data analysis network element sends the recommended third network parameters to the first analysis request network element; The data analysis network element sends the recommended fourth network parameters to the second analysis request network element; The recommended third network parameter corresponds to the first network parameter, and the recommended fourth network parameter corresponds to the second network parameter.

9. The method as described in claim 8, characterized in that, The method further includes: The data analysis network element receives a fourth message from the first analysis request network element, the fourth message being used to indicate that the recommended third network parameters are not accepted; The data analysis network element determines recommended fifth network parameters and recommended sixth network parameters based on the fourth message, the third network indicator, the first network parameters requested by the first analysis request network element, and the second network parameters requested by the second analysis request network element. The recommended fifth network parameter corresponds to the first network parameter, and the recommended sixth network parameter corresponds to the second network parameter. The value of the recommended fifth network parameter is different from the value of the recommended third network parameter. The data analysis network element sends the recommended fifth network parameter to the first analysis request network element; The data analysis network element sends the recommended sixth network parameter to the second analysis request network element.

10. A communication method, characterized in that, include: The first analysis requesting network element determines a first request message. The first request message is used to request recommended first network parameters. The first request message includes the first network parameters and first network indicators required by the first analysis requesting network element. The first network indicator is the network indicator expected by the first analysis requesting network element. The first analysis request network element sends the first request message to the data analysis network element; Wherein, the first analysis requesting network element receives recommended third network parameters from the data analysis network element. The recommended third network parameters correspond to the first network parameters requested by the first analysis requesting network element. The recommended third network parameters are determined based on a third network indicator, the first network parameters requested by the first analysis requesting network element, and the second network parameters requested by the second analysis requesting network element. The third network indicator is a network indicator jointly desired by the first analysis requesting network element and the second analysis requesting network element. The third network indicator is determined based on the first network indicator and the second network indicator. The second network indicator is a network indicator desired by the second analysis requesting network element.

11. The method as described in claim 10, characterized in that, The method further includes: The first analysis request network element receives a first message from the data analysis network element, the first message being used to modify the desired network indicator to the third network indicator. The first analysis requesting network element determines, based on the first message, whether to modify the network indicator expected by the first analysis requesting network element to the third network indicator.

12. The method as described in claim 10, characterized in that, The method further includes: The first analysis requesting network element receives a second message from the data analysis network element, the second message being used by the first analysis requesting network element to modify the requested network parameters to the third network parameters.

13. The method as described in claim 12, characterized in that, The predicted network metrics corresponding to the recommended third network parameters and the recommended fourth network parameters are within the range of the third network parameters. The recommended fourth network parameters are determined based on the third network parameters, the first network parameters required by the first analysis request network element, and the second network parameters required by the second analysis request network element. The fourth network parameters correspond to the second network parameters.

14. The method according to any one of claims 10-13, characterized in that, The method further includes: The first analysis request network element receives recommended third network parameters from the data analysis network element; The first analysis request network element sends a fourth message to the data analysis network element, the fourth message being used to indicate that the recommended third network parameters are not accepted; The first analysis requesting network element receives a recommended fifth network parameter from the data analysis network element. The recommended fifth network parameter corresponds to the first network parameter. The recommended fifth network parameter is determined based on a third network indicator, the first network parameter required by the first analysis requesting network element, and the second network parameter required by the second analysis requesting network element. The third network indicator is a network indicator jointly desired by the first analysis requesting network element and the second analysis requesting network element. The third network indicator is determined based on the first network indicator and the second network indicator. The second network indicator is a network indicator desired by the second analysis requesting network element.

15. A communication method, characterized in that, include: The second analysis requesting network element determines the second request message, which is used to request recommended second network parameters. The second request message includes the second network parameters and second network indicators required by the second analysis requesting network element, and the second network indicator is the network indicator expected by the second analysis requesting network element. The second analysis request network element sends the second request message to the data analysis network element; The second analysis requesting network element receives a recommended fourth network parameter from the data analysis network element. The recommended fourth network parameter is determined based on a third network indicator, a first network parameter requested by the first analysis requesting network element, and a second network parameter requested by the second analysis requesting network element. The third network indicator is a network indicator jointly desired by the first analysis requesting network element and the second analysis requesting network element. The third network indicator is determined based on the first network indicator and the second network indicator. The first network indicator is a network indicator desired by the first analysis requesting network element.

16. The method as described in claim 15, characterized in that, The method further includes: The second analysis request network element receives a first message from the data analysis network element, the first message being used to modify the desired network indicator to the third network indicator; The second analysis requesting network element determines, based on the first message, whether to modify the network indicator expected by the second analysis requesting network element to the third network indicator.

17. The method as described in claim 15, characterized in that, The method further includes: The second analysis requesting network element receives a third message from the data analysis network element, the third message being used to cancel obtaining recommended network parameters based on the second network parameters requested by the second analysis requesting network element.

18. The method as described in claim 15 or 16, characterized in that, The method further includes: The second analysis requesting network element receives a recommended fourth network parameter from the data analysis network element. The recommended fourth network parameter is determined based on a third network indicator, a first network parameter requested by the first analysis requesting network element, and a second network parameter requested by the second analysis requesting network element. The third network indicator is a network indicator that both the first analysis requesting network element and the second analysis requesting network element expect. The third network indicator is determined based on the second network indicator and the first network indicator. The first network indicator is a network indicator that the first analysis requesting network element expects. The second analysis requesting network element receives a recommended sixth network parameter from the data analysis network element. The recommended sixth network parameter corresponds to the second network parameter and is determined based on the third network indicator, the first network parameter requested by the first analysis requesting network element, and the second network parameter requested by the second analysis requesting network element.

19. A communication device, characterized in that, It includes a processor and a memory; the memory is used to store computer instructions, and the processor executes the computer instructions stored in the memory to cause the apparatus to perform the method of any one of claims 1 to 18.

20. A communication system, characterized in that, include: A data analysis network element, used to perform the method described in any one of claims 1 to 9; as well as The first analysis request element is used to perform the method described in any one of claims 10 to 14; as well as The second analysis request element is used to perform the method described in any one of claims 15 to 18.

21. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program or instructions that, when executed by a communication device, implement the method as described in any one of claims 1 to 18.

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