Configuration method and communication device

Abstract

The invention provides a configuration method and a communication device, and the method comprises the steps: determining a first time range based on network operation data and network performance demands, and the first time range comprises a first sample time range of sample data and / or a first prediction time range of prediction data; and sending configuration information to a second device, wherein the configuration information is used for indicating the first time range. Through the application, the air interface load and network performance requirements can be reasonably adapted, the sample time range and the prediction time range can be flexibly adjusted, the air interface overhead of interaction sample data can be reduced, and / or the accuracy of the prediction data can be improved.

Description

Technical Field

[0001] The present application relates to the field of communication technology, and in particular to a configuration method and a communication device. Background Art

[0002] Artificial intelligence (AI) is a technology that simulates the human brain to perform complex calculations. With the improvement of data storage and computing power, AI has been increasingly used. The R17 version of the 3rd Generation Partnership Project (3GPP) passed a study item (SI), proposing to apply AI to the new radio (NR) to improve network performance and user experience through intelligent data collection and analysis.

[0003] At present, for AI-based application scenarios on the air interface, the standard discusses the terminal equipment-sided (UE-sided) model / network equipment-sided (NW-sided) model and the two-sided model, that is, the model can be located on the UE side or the network side, and on both the UE side and the network side (models on both sides need to collaborate to meet the requirements), so there are situations where sample data and / or predicted data are interacted on the air interface. However, there is currently a problem of high air interface overhead for interacting sample data, and / or inaccurate predicted data. Summary of the invention

[0004] The embodiments of the present application provide a configuration method and a communication device, which are beneficial to reducing the air interface overhead of interactive sample data and / or improving the accuracy of predicted data based on the method described in the present application.

[0005] In a first aspect, the present application provides a configuration method, which includes: determining a first time range based on network operation data and network performance requirements, the first time range including a first sample time range of sample data and / or a first predicted time range of predicted data; sending configuration information to a second device, the configuration information being used to indicate the first time range.

[0006] Based on the method described in the first aspect, it is possible to reasonably adapt the air interface load and network performance requirements, flexibly adjust the sample time range and the prediction time range, which is conducive to reducing the air interface overhead of the interactive sample data, and / or improving the accuracy of the predicted data.

[0007] In a possible implementation, before sending the configuration information to the second device, the method further includes: sending first information to the second device, the first information including multiple mapping identifiers and a time range corresponding to each of the multiple mapping identifiers; wherein the configuration information includes a mapping identifier corresponding to the first time range, and the first time range is within the time ranges corresponding to the multiple mapping identifiers. Based on this method, it is beneficial to save overhead and reduce latency.

[0008] In a possible implementation, before sending the configuration information to the second device, the method further includes: receiving second information from the second device, the second information including multiple mapping identifiers and a time range corresponding to each of the multiple mapping identifiers; wherein the configuration information includes a mapping identifier corresponding to the first time range, and the first time range is within the time ranges corresponding to the multiple mapping identifiers. Based on this method, it is beneficial to save overhead and reduce latency.

[0009] In a possible implementation, the method further includes: receiving a response message from the second device, the response message being used to indicate that the adjustment of the sample time range of the sample data and / or the prediction time range of the prediction data has been completed. Based on this approach, it is beneficial to improve the reliability of adjusting the sample time range and / or the prediction time range.

[0010] In a possible implementation, the configuration information further includes first indication information, and the first indication information is used to indicate a reason for selecting the first time range. Based on this approach, the reasons for the sample time range and / or the prediction time range can be effectively interactively adjusted.

[0011] In a possible implementation, there are multiple first time ranges, and the configuration information further includes a selection condition corresponding to each first time range. Based on this approach, it is beneficial to improve the flexibility and accuracy of adjusting the sample time range and / or the prediction time range.

[0012] In a possible implementation, the method further includes: receiving third information from the second device, the third information including first data, a first prediction time range corresponding to the first data, and a first selection condition corresponding to the first prediction time range, the first data including sample data and / or prediction data. Based on this approach, the reasons for the sample time range and / or prediction time range can be effectively interactively adjusted.

[0013] In a possible implementation manner, the first information and / or the second information further includes a target model corresponding to each mapping identifier, and a reporting method of sample data and / or predicted data corresponding to each mapping identifier.

[0014] In a second aspect, the present application provides a configuration method, the method comprising: receiving configuration information from a first device, the configuration information being used to indicate a first time range, the first time range comprising a first sample time range of sample data and / or a first prediction time range of prediction data; adjusting the time range of the sample data to the first sample time range, and / or adjusting the time range of the prediction data to the first prediction time range.

[0015] The beneficial effects of the possible implementation methods of the second aspect can be found in the beneficial effects of the possible implementation methods of the first aspect, and will not be repeated here.

[0016] In a possible implementation, before receiving the configuration information from the first device, the method further includes: receiving first information from the first device, the first information including a plurality of mapping identifiers and a time range corresponding to each of the plurality of mapping identifiers.

[0017] In a possible implementation, before receiving the configuration information from the first device, the method further includes: sending second information to the first device, where the second information includes a plurality of mapping identifiers and a time range corresponding to each of the plurality of mapping identifiers.

[0018] In a possible implementation, the method further includes: sending a response message to the first device, where the response message is used to indicate that the adjustment of the sample time range of the sample data and / or the prediction time range of the prediction data has been completed.

[0019] In a possible implementation manner, the configuration information further includes first indication information, where the first indication information is used to indicate a reason for selecting the first time range.

[0020] In a possible implementation, there are multiple first time ranges, and the configuration information also includes a selection condition corresponding to each first time range.

[0021] In one possible implementation, the time range of the sample data is adjusted to a first sample time range, including: when a first selection condition is met, the time range of the sample data is adjusted to a first sample time range corresponding to the first selection condition; and / or, the time range of the predicted data is adjusted to a first predicted time range, including: when the first selection condition is met, the time range of the predicted data is adjusted to a first predicted time range corresponding to the first selection condition.

[0022] In a possible implementation, the method also includes: sending third information to the first device, the third information including first data, a first prediction time range corresponding to the first data, and a first selection condition corresponding to the first prediction time range, the first data including sample data and / or prediction data.

[0023] In a possible implementation manner, the first information and / or the second information further includes a target model corresponding to each mapping identifier, and a reporting method of sample data and / or predicted data corresponding to each mapping identifier.

[0024] In a third aspect, the present application provides a communication device, the communication device comprising a processor, when the processor calls a computer program in a memory, the method described in the first aspect or the second aspect is executed.

[0025] In a fourth aspect, the present application provides a communication device, comprising a processor and a memory, wherein the processor and the memory are coupled; the processor is used to implement the method described in the first aspect or the second aspect.

[0026] In a fifth aspect, the present application provides a communication device, which includes a processor, a memory and a transceiver, and the processor and the memory are coupled; the transceiver is used to send and receive data, and the processor is used to implement the method described in the first aspect or the second aspect.

[0027] In a sixth aspect, the present application provides a chip comprising a processor and an interface, wherein the processor and the interface are coupled; the interface is used to receive or output signals, and the processor is used to execute code instructions so that the method described in the first aspect or the second aspect is executed.

[0028] In a seventh aspect, the present application provides a computer-readable storage medium, in which a computer program or instruction is stored. When the computer program or instruction is executed by a communication device, the method described in the first aspect or the second aspect is implemented.

[0029] In an eighth aspect, the present application provides a communication system, which includes a first device and a second device, the first device is used to execute the method described in the first aspect, and the second device is used to execute the method described in the second aspect.

[0030] In a ninth aspect, the present application provides a computer program product comprising instructions, and when a computer reads and executes the computer program product, the computer executes the method described in the first aspect or the second aspect. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 It is a schematic diagram of a network system architecture provided by an embodiment of the present application;

[0032] Figure 2 is a schematic diagram of a CU-DU architecture provided in an embodiment of the present application;

[0033] Figure 3 is a schematic diagram of a core network architecture provided in an embodiment of the present application;

[0034] Figure 4 It is a schematic diagram of an AI application framework in NR provided in an embodiment of the present application;

[0035] Figure 5 It is a flowchart of a configuration method provided in an embodiment of the present application;

[0036] Figure 6 is a structural diagram of a communication device provided in an embodiment of the present application;

[0037] Figure 7 is a structural diagram of another communication device provided in an embodiment of the present application;

[0038] Figure 8 It is a schematic diagram of the structure of a chip provided in an embodiment of the present application. DETAILED DESCRIPTION

[0039] The terms "first" and "second" and the like in the specification, claims and drawings of this application are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device comprising a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products or devices.

[0040] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0041] In the present application, "at least one (item)" means one or more, "more than one" means two or more, "at least two (items)" means two or three and more than three, and "and / or" is used to describe the corresponding relationship of associated objects, indicating that three relationships may exist. For example, "A and / or B" can mean: only A exists, only B exists, and A and B exist at the same time, where A and B can be singular or plural. The character " / " generally indicates that the objects associated before and after are in an "or" relationship. "At least one of the following items" or similar expressions refers to any combination of these items, including any combination of single items or plural items. For example, at least one of a, b or c can mean: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, c can be single or multiple.

[0042] In order to better understand the embodiments of the present application, the system architecture involved in the embodiments of the present application is first introduced below:

[0043] The technical solution of the embodiment of the present application can be applied to various communication systems, such as satellite communication systems and traditional mobile communication systems. Among them, the satellite communication system can be integrated with the traditional mobile communication system (i.e., the ground communication system). Mobile communication systems include, for example, wireless local area network (WLAN) communication system, wireless fidelity (Wi-Fi) system, long term evolution (LTE) system, LTE frequency division duplex (FDD) system, LTE time division duplex (TDD), fifth generation (5G) system or new radio (NR), and other future communication systems, such as the sixth generation (6G) system, etc., and also support communication systems that integrate multiple wireless technologies, for example, it can also be applied to non-terrestrial networks (NTN) such as drones, satellite communication systems, and high altitude platform stations (HAPS) communications. The system integrates ground mobile communication networks. It is understandable that the system architecture described in the embodiments of the present application is for more clearly illustrating the technical solutions of the embodiments of the present application, and does not constitute a limitation on the technical solutions provided in the embodiments of the present application.

[0044] See also Figure 1 , Figure 1Schematic diagram of a network system architecture provided by an embodiment of the present application. Figure 1 As shown, the next generation mobile communication network architecture formulated by the 3rd generation partnership project (3GPP) standard is called the 5G network architecture. Terminal devices can access the wireless network to obtain services from the external network (such as the data network (DN)) through the wireless network, or communicate with other devices through the wireless network, such as communicating with other terminal devices. The wireless network includes a (radio) access network ((radio) access network, (R) AN) and a core network (CN), wherein the (R) AN (hereinafter described as RAN) is used to access the terminal device to the wireless network, and the CN is used to manage the terminal device and provide a gateway for communication with the DN. The following are respectively Figure 1 The terminal equipment, RAN, CN and DN involved in the network architecture are explained in detail.

[0045] 1. Terminal equipment

[0046] Terminal equipment includes equipment that provides voice and / or data connectivity to users. For example, a terminal device is a device with wireless transceiver functions, which can be deployed on land, including indoors or outdoors, handheld, wearable or vehicle-mounted; it can also be deployed on the water (such as ships, etc.); it can also be deployed in the air (such as airplanes, balloons and satellites, etc.). Terminal equipment can specifically refer to user equipment (UE), access terminal, subscriber unit, user station, mobile station, remote station, remote terminal, mobile device, user terminal, wireless communication equipment, user agent or user device. The terminal device may also be a satellite phone, a cellular phone, a smart phone, a wireless data card, a wireless modem, a machine type communication device, a cordless phone, a session initiation protocol (SIP) phone, a wireless local loop (WLL) station, a PDA, a handheld device with wireless communication function, a computing device or other processing device connected to a wireless modem, a vehicle-mounted device, a communication device carried on a high-altitude aircraft, a wearable device, a drone, a robot, a terminal in device-to-device (D2D) communication, a terminal in vehicle to everything (V2X), a virtual reality (VR) terminal device, an augmented reality (AR) terminal device, a wireless terminal in industrial control, a wireless terminal in self driving, a wireless terminal in remote medical, a wireless terminal in smart grid, a wireless terminal in transportation safety, a wireless terminal in smart city, a smart home, etc. The present application does not limit the wireless terminals in the home or the terminal devices in the future communication network. The terminal may also be fixed or mobile. In addition, in the present application, when not specifically stated, "terminal device" may refer to the terminal device itself or a component in the terminal device, such as a chip system, SoC, which may be installed in the terminal device. It is understood that all or part of the functions of the terminal in the present application may also be implemented by software functions running on hardware, or by virtualization functions instantiated on a platform (such as a cloud platform). The terminal device in the present application may be a terminal for 5G or a terminal for 6G, and the present application does not limit this.

[0047] 2. RAN

[0048] The RAN may include one or more RAN devices (or access network devices). The interface between the access network device and the terminal device may be a Uu interface (or air interface). Of course, in communications that evolve after 5G, the names of these interfaces may remain unchanged, or may be replaced by other names, and this application does not limit this.

[0049] Access network equipment refers to the node or device that connects the terminal device to the wireless network. Access network equipment includes, but is not limited to: next generation node B (gNB), evolved node B (eNB), next generation eNB (ng-eNB), wireless backhaul equipment, radio network controller (RNC), node B (NB), home evolved node B (HeNB) or home node B (HNB), baseband unit (BBU), transmitting and receiving point (TRP), transmitting point (TP), mobile switching center, device-to-device (D2D), vehicle-to-everything (V2X), machine-to-machine (M2M) communication equipment that performs base station functions, etc. It can also include cloud radio access network (cloud radio access network). The RAN in this application may be a RAN for 5G or a RAN for 6G, and this application does not limit this.

[0050] like Figure 2As shown, taking RAN including gNB as an example, RAN can be connected to the core network (for example, it can be the core network of LTE, it can also be the core network of 5G, etc.). CU and DU can be understood as the division of base stations (such as gNB) from the perspective of logical functions. CU and DU can be physically separated or deployed together. Multiple DUs can share one CU. Of course, one DU can also be connected to multiple CUs ( Figure 2 . (not shown). The CU and DU may be connected via an interface, such as an F1 interface. The CU and DU may be divided according to the protocol layer of the wireless network. For example, one possible division method is that the CU is used to perform the functions of the radio resource control (RRC) layer, the service data adaptation protocol (SDAP) layer, and the packet data convergence protocol (PDCP) layer, while the DU is used to perform the functions of the radio link control (RLC) layer, the media access control (MAC) layer, the physical layer, etc. It can be understood that the division of the CU and DU processing functions according to this protocol layer is only an example, and it can also be divided in other ways. For example, the CU or DU can be divided into functions with more protocol layers. For example, the CU or DU can also be divided into partial processing functions with protocol layers. In one design, some functions of the RLC layer and the functions of the protocol layers above the RLC layer are set in the CU, and the remaining functions of the RLC layer and the functions of the protocol layers below the RLC layer are set in the DU. In another design, the functions of the CU or DU can also be divided according to the service type or other system requirements. For example, according to the latency division, the functions that need to meet the latency requirements are set in the DU, and the functions that do not need to meet the latency requirements are set in the CU. In another design, the CU can also have one or more functions of the core network. One or more CUs can be set centrally or separately. For example, the CU can be set on the network side for centralized management. The DU can have multiple RF functions, or the RF function can be set remotely.

[0051] The functions of CU can be implemented by one entity or by different entities. For example, the functions of CU can be further divided, for example, the control plane (CP) and the user plane (UP) are separated, that is, the control plane (CU-CP) of CU and the user plane (CU-UP) of CU. For example, CU-CP and CU-UP can be implemented by different functional entities and connected through the E1 interface. CU-CP and CU-UP can be coupled with DU to jointly complete the functions of the base station. The control plane CU-CP of CU also includes a further divided architecture, that is, the existing CU-CP is further divided into CU-CP1 and CU-CP2. Among them, CU-CP1 includes various radio resource management functions, and CU-CP2 only includes RRC functions and PDCP-C functions (that is, the basic functions of control plane signaling at the PDCP layer).

[0052] 3. CN

[0053] The CN may include one or more CN devices (which may be understood as network element devices or network function (NF)). In the following text, the CN devices are collectively referred to as core network elements.

[0054] See also Figure 3 , Figure 3 A schematic diagram of a core network architecture provided for this application, Figure 3 The CN in Figure 1 is a schematic diagram of the CN in the 5G network architecture. Figure 3The CN shown includes multiple CN devices: network slice selection function (NSSF), network exposure function (NEF), network function repository function (NRF), policy control function (PCF), unified data management (UDM), application function (AF), network slice specific authentication and authorization function (NSSAAF), authentication server function (AUSF), access and mobility management function (AMF), session management function (SMF), user plane function (UPF), service communication proxy (SCP), and network slice admission control function (NSACF).

[0055] in:

[0056] AMF is a control plane function provided by the operator network, responsible for access control and mobility management of terminal devices accessing the operator network, such as mobility status management, allocation of user temporary identities, authentication and authorization of users, etc.

[0057] SMF is a control plane function provided by the operator network, responsible for managing the protocol data unit (PDU) session of the terminal device. A PDU session is a channel for transmitting PDUs. The terminal device needs to transmit PDUs to and from the DN through the PDU session. SMF is responsible for establishing, maintaining and deleting PDU sessions. SMF includes session management (such as session establishment, modification and release, including tunnel maintenance between UPF and RAN), UPF selection and control, service and session continuity (SSC) mode selection, roaming and other session-related functions.

[0058] PCF is a control plane function provided by the operator, including user subscription data management function, policy control function, charging policy control function, quality of service (QoS) control, etc. It is mainly used to provide PDU session policies to SMF. Among them, the policy may include charging-related policies, QoS-related policies, and authorization-related policies.

[0059] UPF is a gateway provided by the operator and is the gateway for the operator network to communicate with the DN. UPF includes user-plane related functions such as packet routing and transmission, packet detection, QoS processing, uplink packet detection, and downlink packet storage.

[0060] UDM is mainly used to manage the user's contract data and authentication data, as well as to perform authentication credit processing, user identity processing, access authorization, registration / mobility management, subscription management, and short message management. In some embodiments, UDM may also include a unified data repository (UDR). Alternatively, in other embodiments, the 3GPP SBA of the 5G system may also include a UDR. Among them, UDR is used to provide storage and retrieval for PCF policies, storage and retrieval of open structured data, and storage of user information requested by application functions.

[0061] It should be noted that the above CN equipment can also be called network element or functional network element. In the 5G communication system, each functional network element can be Figure 3 The names of the functional network elements shown in the figure may still be the same in the communication system evolved after 5G (such as 6G communication system). Figure 3 The names of the functional network elements shown in the figure may also have other names. For example, in a 5G communication system, the user plane function may be a UPF. In a communication system evolved after 5G (such as a 6G communication system), the user plane function may still be a UPF, or may have other names, which is not limited in this application.

[0062] It should also be noted that in the 5G communication system, the functions implemented by each functional network element can be as follows: Figure 3 As shown, they are independent. In the communication system evolved after 5G (such as 6G communication system), each functional network element can still be Figure 3 The shown state is independent, but it can also be realized by integrated functional network elements. Figure 3For example, in a 5G communication system, user-plane related functions are implemented by UPF, and access and mobility management related functions are implemented by AMF. In a communication system that evolves after 5G (such as a 6G communication system), user-plane related functions may still be implemented by UPF, and access and mobility management related functions may still be implemented by AMF. Alternatively, user-plane related functions and access and mobility management related functions may also be implemented by an integrated functional network element at the same time, which is not limited in this application.

[0063] Figure 3 Among them, Npcf, Nudm, Naf, Namf, Nsmf, N1, N2, N3, N4, and N6 are interface serial numbers. The meanings of these interface serial numbers can be found in the definitions in the relevant standard protocols and are not limited here.

[0064] 4.DN

[0065] DN, also known as packet data network (PDN), is a network located outside the operator network. The operator network can access multiple DNs. Application servers corresponding to various services can be deployed in the DN to provide a variety of possible services for terminal devices.

[0066] In order to facilitate understanding of the solution provided by the embodiment of the present application, the following introduces the relevant concepts involved in the embodiment of the present application:

[0067] 1. Artificial intelligence (AI)

[0068] AI is a technology that simulates the human brain to perform complex calculations. With the improvement of data storage and computing power, AI has been increasingly used. 3GPP's R17 version passed a study item (SI), proposing to apply AI to NR to improve network performance and user experience through intelligent data collection and analysis. Based on the discussion of the 3GPP RAN3 working group, a preliminary framework for the application of AI in NR was defined, such as Figure 4As shown, Data Collection stores data inputs from gNB, gNB-CU, gNB-DU, UE or other management entities as a database for AI model training and data analysis and reasoning. Model Training analyzes the training data (Training Data) provided by Data Collection to provide the optimal AI model. Model Inference uses the AI ​​model to provide reasonable AI-based predictions (i.e., prediction data) for network operation based on the inference data (Inference Data) provided by Data Collection, or guides the network to make policy adjustments. The relevant policy adjustments are uniformly planned by the Actor entity and sent to multiple network entities for operation. At the same time, after the relevant policies are applied, the specific performance of the network will be entered into the database again for storage.

[0069] In the embodiment of the present application, the AI ​​module is a module with machine learning computing capabilities. In a wireless communication system, the AI ​​module may be located in an AI acceleration module (OCP accelerator module, OAM), in an access network device (such as gNB) (the separation architecture is located in the CU), in some UEs, or as a network element entity AIC alone. The main function of the AI ​​module in the wireless communication system is to perform a series of AI calculations such as model building, training approximation, and reinforcement learning based on input data (in a wireless communication system, input data generally refers to network operation data provided by the RAN side or monitored by OAM, such as network load, channel quality, etc.). The trained model provided by the AI ​​module has a prediction function for network changes on the RAN side, and can usually be used for load prediction, UE trajectory prediction, etc. In addition, the AI ​​module can also perform policy reasoning from the perspectives of network energy saving and mobility optimization based on the prediction results of the trained model on the RAN network performance, so as to obtain reasonable and efficient energy saving strategies, mobility optimization strategies, etc. When the AI ​​module is located in OAM, its communication with the gNB on the RAN side can reuse the current northbound interface; when the AI ​​module is located in the gNB or CU, it can reuse the current F1, Xn, Uu and other interfaces; when the AI ​​module becomes an independent network entity, it is necessary to re-establish the communication link to the OAM and RAN side, such as based on a wired link or a wireless link. When the CP and UP of the CU are separated, the CP is usually responsible for receiving the AI ​​model and the subsequent reasoning and policy generation functions of the AI. When the CU-CP is further divided into CU-CP1 and CU-CP2, CU-CP1 is usually responsible for receiving the model and the subsequent reasoning functions of the AI, and generating specific interactive signaling, which is sent by CU-CP2.

[0070] 2. AI-based use cases

[0071] Currently, 3GPP has designed several basic application scenarios for the application of AI on the RAN side from working groups such as RAN3 and RAN1. RAN3 includes energy saving, load balancing, and mobility optimization, and RAN1 includes channel state information-reference signal (CSI-RS) feedback enhancement, beam management enhancement, and positioning accuracy enhancement. The following briefly introduces the basic principles of several use cases.

[0072] (1) Energy saving: The base station collects its own and neighboring cell's load, energy consumption, energy efficiency information, UE trajectory information, measurement results, etc., predicts the direction of its own load, and combines the cell's purpose, key performance indicators (KPI) requirements, etc., to take appropriate energy-saving measures in a timely manner without affecting network coverage and user access. The simplest energy-saving strategy includes directly deactivating the cell. Other energy-saving strategies include carrier shutdown, channel shutdown, time slot shutdown, transmission power reduction, etc. More complex energy-saving strategies also include a combination of the above energy-saving measures. When network coverage is affected or cannot meet UE access and service requirements, it is necessary to modify the current energy-saving strategy or directly return to normal working state, and consider re-predicting the load or changing the AI ​​model used for re-inference.

[0073] (2) Load balancing: The base station collects its own and neighboring cell's load, energy consumption, energy efficiency information, UE's trajectory information, measurement results, etc., predicts the direction of its own load, and reasonably selects some UEs to switch to neighboring cells or receive UEs from neighboring cells in combination with the cell's purpose, KPI requirements, etc., so that the load level between base stations in the entire cell is close, reducing the situation where some base stations are overloaded and affect normal services while some base stations are idle. However, since the accuracy of the prediction is not 100%, it may lead to unreasonable UE selection or unreasonable switching target cells, switching failure or UE service being affected, or inaccurate load prediction leading to poor load balancing effect, or temporary abnormal load changes causing the original load balancing strategy to no longer apply. At this time, it is necessary to exit or modify the current load balancing strategy, and consider re-predicting the load or changing the AI ​​model used for re-reasoning.

[0074] (3) Mobility optimization: The base station collects historical trajectory information of the UE and combines it with the UE's measurement information to predict the UE's future trajectory. Based on the predicted trajectory, it determines in advance whether the UE should switch, sends the switching configuration in advance, and informs the target cell to prepare access resources, thereby reducing the delay of the UE during the switching process and reducing the probability of switching and access failure. However, since the trajectory prediction accuracy is not 100%, when the predicted trajectory is wrong, it will cause UE switching failure and service interruption. In this case, it is necessary to consider retraining the model and reasoning based on abnormal situations, or consider replacing the model to avoid similar abnormal situations in subsequent UEs.

[0075] (4) CSI-RS feedback enhancement: The main process of current CSI-RS feedback enhancement is as follows: First, a dictionary is exchanged between the base station and the UE. Usually, the base station has trained a model in advance based on the UE capabilities and its own requirements. Then, an encoder and quantizer tool are sent to the UE. Then, the UE compresses and quantizes the matrix to be fed back according to the measured channel matrix results and the existing dictionary, and transmits the result to the base station. Finally, the base station recovers the original channel matrix based on the dictionary and the data reported by the UE.

[0076] (5) Beam scanning enhancement: The main process of current beam management enhancement is as follows: first, the initial model is generated, that is, a certain number of UEs report the results of full-beam scanning of the synchronization signal block (SSB) to train a sparse scanning matrix, which is usually unique to each cell; then, the base station sends the sparse model to the UE (through system information block (SIB) messages, etc.), and the UE performs P1 beam scanning based on this matrix; finally, based on the UE's sparse scanning results, the base station infers the optimal CSI-RS beam and starts P2 scanning of the UE, and the UE feeds back the optimal CSI-RS beam ID.

[0077] (6) Positioning enhancement: The main process of enhancing positioning accuracy is as follows: First, use a reference UE controlled by the operator to collect raw data; then, the LMF and gNB train models respectively. The LMF model can infer the final positioning (longitude and latitude, etc.), and the gNB model can infer the line of sight (LOS) path / non-line of sight (NLOS) path judgment results.

[0078] 3. Sample time range between sample data and sample data, and forecast time range between forecast data and forecast data

[0079] When training an AI model, sample data is needed as input data for model training, as well as historical correctly labeled data (ground-truth data). Supervised machine learning will label the training data, and the correctly labeled data will be called ground truth. Ground truth is a reference standard, generally used for error quantification and to verify the accuracy of classification algorithms. When reasoning, the AI ​​model also needs prediction data (i.e., reasoning data) as input data for model reasoning (for example, when reasoning about trajectories, historical trajectory data is needed as input).

[0080] The richness of sample data will have a significant impact on the model training effect, prediction accuracy, etc. Generally speaking, the longer the time span of the sample data (that is, the larger the sample time range of the sample data), the more sample data, and the richer the types, the better the model training and prediction effects will be. However, if the sample data is transmitted over the air interface (for example, the model is located on the gNB side and the UE needs to provide sample data), it will also bring higher air interface overhead.

[0081] For the prediction time range of the AI ​​model, such as UE trajectory prediction, the larger the prediction time range (i.e., predicting the trajectory 2 seconds later at 0 seconds vs. predicting the trajectory 1 second later at 0 seconds, the former is considered to have a larger prediction time range in this application), the more reference information can be provided for network performance adjustment, but the accuracy of the prediction data will also be worse. Therefore, in order to ensure network performance, it is necessary to select a reasonable prediction time range.

[0082] At present, for AI-based application scenarios based on the air interface, the standard discusses the terminal equipment side (user equipment-sided, UE-sided) model / network equipment side model (network-sided, NW-sided) and two-sided model, that is, the AI ​​model can be located on the UE side or the network side, or on both the UE side and the network side (models on both sides need to collaborate to meet the needs), so there are situations where sample data and / or prediction data are interacted on the air interface. Taking the NW-sided model as an example, the base station requires the UE to provide sample data when training the model and using the local model for prediction. Although the type of sample data is discussed in the standard, there is no discussion on the sample time range of the sample data, and there is no related signaling and process support for its adjustment, resulting in the inability to dynamically adjust the time range of the sample data according to the air interface load and the requirements for training and prediction performance, resulting in a large air interface overhead for interactive sample data.

[0083] Taking the UE-sided model as an example, the UE's prediction data can be sent to the base station as an important input for the base station to optimize the network. Different prediction time ranges will lead to different prediction accuracy, and different scenarios and network optimization goals will also have different prediction results. The accuracy and time length are also different, but the current standards do not discuss how to dynamically adjust the prediction time range, so there will be problems with inaccurate prediction data.

[0084] In order to reduce the air interface overhead of interactive sample data and / or improve the accuracy of predicted data, the present application provides a configuration method and a communication device. The configuration method and the communication device provided in the embodiments of the present application are further described in detail below.

[0085] Figure 5 is a flow chart of a configuration method provided in an embodiment of the present application. Figure 5 As shown, the configuration method includes the following steps S501 to S503. Figure 5 The method shown may be performed by a first device and a second device. Figure 5 The execution subject of the method shown may be a chip in the first device and a chip in the second device, which is not limited in the embodiments of the present application. Figure 5 The first device and the second device are used as the execution subjects of the method for example. The first device may be the access network device (i.e., RAN) mentioned above, and the second device may be the terminal device mentioned above; or, the first device may be the terminal device mentioned above, and the second device may be the access network device (i.e., RAN) mentioned above. The embodiment of the present application is described by taking the AI ​​module located in the first device as an example.

[0086] It should be noted that, taking the access network device as a gNB as an example, when the first device is an access network device and the second device is a terminal device, the module for judging and deciding the adjustment scheme of the sample time range and the prediction time range can be located in the gNB or gNB-CU; the gNB-CP or gNB-CU-CP or gNB-CU-CP1 processes and generates the adjustment scheme; the gNB-CP or gNB-CU-CP or gNB-CU-CP2 sends the generated adjustment scheme to the terminal device. When the first device is a terminal device and the second device is an access network device, the module for the access network device to interact with the terminal device about the adjustment scheme of the sample time range and the prediction time range can be located in the gNB or gNB-CU, and the module for the access network device to generate the prediction result can be located in the gNB, gNB-CU or gNB-DU, or it can be a separate AI function node, or it can be a core network, OAM, etc., and this application does not impose any restrictions on this.

[0087] S501. A first device determines a first time range based on network operation data and network performance requirements, where the first time range includes a first sample time range of sample data and / or a first prediction time range of prediction data.

[0088] S502: The first device sends configuration information to the second device, where the configuration information is used to indicate the first time range. Correspondingly, the second device receives the configuration information from the first device.

[0089] S503: The second device adjusts the time range of the sample data to the first sample time range, and / or adjusts the time range of the prediction data to the first prediction time range.

[0090] In the embodiment of the present application, the network operation data here may refer to data such as air interface load and channel quality. The network performance requirements here may refer to requirements for air interface transmission resources, accuracy of predicted data, etc. The first device may dynamically adjust the sample time range of the sample data and / or the predicted time range of the predicted data in combination with the current network operation data and network performance requirements to obtain the first sample time range of the sample data and / or the first predicted time range of the predicted data, i.e., the first time range; then the first device sends the adjusted first time range to the second device through configuration information for configuration, so as to reasonably adapt to the air interface load and network performance requirements, and realize flexible adjustment of the sample time range and the predicted time range, which is conducive to reducing the air interface overhead of the interactive sample data, and / or improving the accuracy of the predicted data.

[0091] For example, assuming that the first device determines that using a shorter time range / coarser precision sample based on the current network operation data can make the model output meet the network performance requirements, the second device can be instructed to report a shorter time range / coarser precision sample data, that is, shorten the sample time range of the sample data, thereby saving air interface overhead, storage overhead and hardware overhead. Conversely, assuming that there is still margin in air interface transmission resources, and the first device determines that a longer time range / more precise sample is required to make the model output meet the network performance requirements, the second device can be instructed to report a longer time range / more precise sample data, that is, increase the sample time range of the sample data.

[0092] For another example, assuming that the first device determines that the current prediction time range is too long based on the current network operation data, resulting in the accuracy of the prediction data not meeting the network performance requirements, the second device can be instructed to report the prediction results of a shorter time range, that is, shorten the prediction time range of the prediction data; or, the first device determines that the second device needs to provide prediction data for a longer time range based on the current network operation data, so that the first device can make performance change judgments for a longer time period, and the second device can be instructed to report prediction data for a longer time range, that is, increase the prediction time range of the prediction data.

[0093] Taking the second device providing a historical trajectory for the first device to predict the trajectory of the second device as an example, the first time range can be configured with reference to Table 1 below. In Table 1, when the first device determines that the second device is in a high-speed state and the air interface signaling load is heavy according to the current network operation data, the adjustment scheme adopted by the first device can be to increase the sample time range and reduce the accuracy requirement on the basis of meeting the network performance requirements. When the first device determines that the second device is in a high-speed state and the air interface signaling load is light according to the current network operation data, the adjustment scheme adopted by the first device is to increase the sample time range and appropriately improve the accuracy requirement on the basis of meeting the network performance requirements. When the first device determines that the second device is in a low-speed state and the air interface signaling load is heavy according to the current network operation data, the adjustment scheme adopted by the first device is to reduce the sample time range and reduce the accuracy requirement on the basis of meeting the network performance requirements. When the first device determines that the second device is in a low-speed state and the air interface signaling load is light according to the current network operation data, the adjustment scheme adopted by the first device is to appropriately adjust to meet the network performance requirements.

[0094] Table 1

[0095] Scenario Adjustment plan The second device is in high-speed state and the air interface signaling load is heavy. Increase the sample time range and reduce the accuracy requirement The second device is in high-speed state and the air interface signaling load is light Increase the sample time range and appropriately improve the accuracy requirements The second device is in a low speed state and the air interface signaling load is heavy. Reduce the sample time range and reduce the accuracy requirements The second device is in low speed state and the air interface signaling load is light Sizing to meet network performance needs

[0096] For example, assuming that the current sample time range is the historical trajectory of the first 30 seconds before the current trajectory prediction is executed, and the current accuracy requirement is 3 decimal places. If the first device determines that the second device is in a high-speed state and the air interface signaling load is heavy based on the current network operation data, then the sample time range can be adjusted to the historical trajectory of the first 40 seconds before the current trajectory prediction is executed (i.e., the first sample time range) on the basis of meeting the network performance requirements, and the accuracy is adjusted to 2 decimal places, that is, the adjustment scheme adopted is to increase the sample time range and reduce the accuracy requirement.

[0097] If the first device determines that the second device is in a high-speed state based on the current network operation data and the air interface signaling load is light, then on the basis of meeting the network performance requirements, the sample time range can be adjusted to the historical trajectory of the first 40 seconds before executing this trajectory prediction (i.e., the first sample time range), and the accuracy is adjusted to 4 decimal places. That is, the adjustment plan adopted is to increase the sample time range and appropriately increase the accuracy requirements.

[0098] If the first device determines that the second device is in a low-speed state and the air interface signaling load is heavy based on the current network operation data, then the sample time range can be adjusted to the historical trajectory of the first 20 seconds before executing this trajectory prediction (i.e., the first sample time range) on the basis of meeting the network performance requirements, and the accuracy is adjusted to 2 decimal places. That is, the adjustment plan adopted is to reduce the sample time range and lower the accuracy requirements.

[0099] If the first device determines that the second device is in a low-speed state and the air interface signaling load is light based on the current network operation data, the sample time range and accuracy can be appropriately adjusted to meet the network performance requirements. For example, the sample time range can be adjusted to the historical trajectory of the first 35 seconds of the execution of this trajectory prediction (i.e., the first sample time range), and the accuracy is adjusted to 3 decimal places.

[0100] In a possible implementation, before the first device sends configuration information to the second device, the first device and the second device may agree on a representation method for the sample time range and / or the prediction time range, for example, they may agree to use a mapping identifier to indicate the time range, or they may directly indicate a specific time range, which is not limited here. The two representation methods are described below.

[0101] Method 1: directly indicate a specific time range (ie, sample time range and / or forecast time range).

[0102] In a specific implementation, after the first device determines the first time range to be adjusted, the first device can directly carry the specific first time range in the configuration information; after the second device receives the configuration information, it can parse the first time range from the configuration information for configuration. Based on this approach, it is helpful to reduce the processing burden of the first device.

[0103] Method 2: The first device and the second device agree to use a mapping identifier to indicate a time range (ie, a sample time range and / or a prediction time range).

[0104] In the specific implementation, due to the large amount of information in the specific time range, frequent interaction of the original time range configuration in the air interface will introduce a lot of overhead, increased latency and other problems. Therefore, it is possible to consider using a mapping identifier (Index) to indicate different time ranges. For this method, the first device and the second device need to interact with the mapping relationship between the mapping identifier and the time range. The mapping relationship here can be sent to the second device after the first device is configured, or it can be sent to the first device after the second device is configured, which is not limited here. These two situations are described below. Among them, the time range here can include a sample time range and / or a predicted time range.

[0105] Case 1: The first device sends first information to the second device, the first information includes multiple mapping identifiers and a time range corresponding to each of the multiple mapping identifiers; wherein the configuration information includes the mapping identifier corresponding to the first time range, and the first time range is within the time ranges corresponding to the multiple mapping identifiers. Accordingly, the second device receives the first information from the first device.

[0106] Optionally, the first information also includes a target model corresponding to each mapping identifier, and a reporting method of sample data and / or predicted data corresponding to each mapping identifier.

[0107] For situation 1, the first information here can be considered as the mapping relationship between the mapping identifier and the time range determined by the first device according to its own capabilities, network performance, etc. The first information may include multiple mapping identifiers, the time range (sample time range and / or prediction time range) corresponding to each mapping identifier in the multiple mapping identifiers, the target model corresponding to each mapping identifier, the reporting method of the sample data and / or prediction data corresponding to each mapping identifier, etc. After the first device configures the first information, it can send the first information to the second device, so that the first device and the second device exchange the mapping relationship between the mapping identifier and the time range. After the first device determines the first time range, when sending the configuration information to the second device, it can use the mapping identifier corresponding to the first time range in the first information to indicate; when the second device receives the mapping identifier in the configuration information, it can find the corresponding time range in the mapping relationship according to the mapping identifier, that is, the first time range.

[0108] The target model refers to a specific model or AI function. For UE-sided and two-sided models, it indicates the model corresponding to a specific identifier on the terminal device side, or the model set corresponding to a certain AI function; for NW-sided models, it indicates the model corresponding to a certain identifier on the access network device side, or the model combination corresponding to a certain AI function.

[0109] The time range (i.e., the sample time range and / or the prediction time range) can be a specific time length, or it can be the starting time point or the ending time point of the time corresponding to the sample data and / or the prediction data. With respect to the sample time range, for example, in the UE-sided and two-sided models, when the terminal device performs CSI channel prediction, assuming that the time range is xms, it can be indicated that each time the terminal device performs CSI channel prediction, the sample time range used is all CSI channel measurement results within the first x ms of the prediction; for the NW-sided model, when the access network device performs beam prediction, assuming that the time range is time point y, it can be indicated that the terminal device needs to report the beam measurement results starting from time point y.

[0110] For the prediction time range, in the UE-sided or two-sided model, the terminal device is required to provide one or more prediction data from the time the terminal device reports the prediction data to a specific time. For example, if the prediction data provided by the terminal device is reported at time t, it is necessary to report one or more prediction data from time t to time t+z, or it can be the prediction data of time z reported at time t.

[0111] The reporting method of sample data and / or predicted data refers to the way in which the terminal device reports the sample data and / or predicted data. For example, the reporting method can be CP or UP. Among them, CP refers to the control plane method, that is, reporting through RRC messages, which can indicate which specific RRC message the second device reports in, and whether it can be sent through RRC segmented messages; UP refers to the user plane method, that is, reporting through user plane data. In addition, it can also include accuracy requirements, that is, indicating the sample data and / or preset data reported by the second device, and how accurate it should be, such as indicating how many bits are used to represent it, or indicating how many decimal places are required to be accurate.

[0112] Taking Table 2 as an example, when the mapping identifier is 0, the target model (or AI function) is: A (or AI function identifier a), the sample time range and / or prediction time range is: xms and / or time point t, and the reporting method of sample data and / or prediction data is: CP, and the accuracy is required to be 3 decimal places. When the mapping identifier is 1, the target model (or AI function) is: B (or AI function identifier b), the sample time range and / or prediction time range is: yms and / or time point t, and the reporting method of sample data and / or prediction data is: UP, and the accuracy is required to be 3 decimal places.

[0113] Table 2

[0114]

[0115] Case 2: The second device sends second information to the first device, the second information including multiple mapping identifiers and a time range corresponding to each of the multiple mapping identifiers; wherein the configuration information includes a mapping identifier corresponding to a first time range, and the first time range is within the time ranges corresponding to the multiple mapping identifiers. Accordingly, the first device receives the second information from the second device.

[0116] Optionally, the second information also includes a target model corresponding to each mapping identifier, and a reporting method of sample data and / or prediction data corresponding to each mapping identifier.

[0117] For situation 2, the second information here can be considered as the mapping relationship between the mapping identifier and the time range determined by the second device according to its own capabilities, network performance, etc. The second information may include multiple mapping identifiers, the time range (sample time range and / or prediction time range) corresponding to each mapping identifier in the multiple mapping identifiers, the target model corresponding to each mapping identifier, and the reporting method of the sample data and / or prediction data corresponding to each mapping identifier. After the second device configures the second information, it can send the second information to the first device, and the first device finally confirms it, so that the first device and the second device exchange the mapping relationship between the mapping identifier and the time range. The mapping relationship here can refer to the description in the above situation 1, and will not be repeated here. After the first device determines the first time range, when sending the configuration information to the second device, it can use the mapping identifier corresponding to the first time range in the second information to indicate; the second device receives the mapping identifier in the configuration information, and can find the corresponding time range in the mapping relationship according to the mapping identifier, that is, the first time range.

[0118] In a possible implementation, the method further includes: the second device sends a response message to the first device, the response message being used to indicate that the adjustment of the sample time range of the sample data and / or the prediction time range of the prediction data has been completed. Accordingly, the first device receives a response message from the second device. It can be understood that after the second device completes the adjustment of the sample time range and / or the prediction time range according to the configuration information sent by the first device, a response message (such as an (acknowledgement, ACK) message) can be fed back to the second device to indicate that the adjustment has been completed. Based on this approach, it is beneficial to improve the reliability of adjusting the sample time range and / or the prediction time range.

[0119] In a possible implementation, the configuration information further includes first indication information, and the first indication information is used to indicate the reason for selecting the first time range. It can be understood that after the first device determines the first time range, it can further indicate the reason for selecting the first time range, such as the requirement for accuracy, limited air interface transmission resources, etc. Based on this method, the reasons for the sample time range and / or the prediction time range can be effectively interactively adjusted.

[0120] In a possible implementation, there are multiple first time ranges, and the configuration information further includes a selection condition corresponding to each first time range. Based on this approach, it is beneficial to improve the flexibility and accuracy of adjusting the sample time range and / or the prediction time range.

[0121] Optionally, when the second device adjusts the time range of sample data to a first sample time range, a specific implementation method may be: when the first selection condition is met, the second device adjusts the time range of sample data to a first sample time range corresponding to the first selection condition; and / or, when the second device adjusts the time range of prediction data to a first prediction time range, a specific implementation method may be: when the first selection condition is met, the second device adjusts the time range of prediction data to a first prediction time range corresponding to the first selection condition.

[0122] It can be understood that the first device can filter out multiple first time ranges and send them to the second device, and indicate the selection condition corresponding to each first time range. After the second device receives the multiple first time ranges in the configuration information, it can make a judgment and selection based on the current actual situation (such as network performance, operating environment, etc.) and the selection condition corresponding to each first time range. Assuming that the first selection condition is met, the second device can adjust the time range of the sample data to the first sample time range corresponding to the first selection condition, and / or adjust the time range of the predicted data to the first predicted time range corresponding to the first selection condition. Among them, when the first device is an access network device and the second device is a terminal device, the selection conditions here may be air interface load (for example, the threshold of physical resource block (PRB) utilization), the threshold of terminal device speed, the type of channel environment in which the terminal device is located, the threshold of predicted data accuracy, etc., which are not limited here; when the first device is a terminal device and the second device is an access network device, the selection conditions here may be air interface load (for example, the threshold of PRB utilization), the number of transmission ports of the access network device, the type of channel environment in which the access network device is located, the threshold of predicted data accuracy, etc., which are not limited here.

[0123] For example, assume that the configuration information sent by the first device includes two first time ranges, namely, the first time range 1 and the first time range 2. The first time range 1 includes the first sample time range 1 and the first prediction time range 1, and the first time range 2 includes the first sample time range 2 and the first prediction time range 2. Among them, the first selection condition corresponding to the first time range 1 is that the PRB utilization is greater than the first threshold value; the second selection condition corresponding to the first time range 2 is that the PRB utilization is less than or equal to the first threshold value. After the second device receives the configuration information, it detects that the current PRB utilization is greater than the first threshold value, that is, the first selection condition is met, then the second device adjusts the time range of the sample data to the first sample time range 1 in the first time range 1, and / or adjusts the time range of the predicted data to the first prediction time range 1 in the first time range 1.

[0124] Further optionally, the method further includes: the second device sends third information to the first device, the third information includes first data, a first prediction time range corresponding to the first data, and a first selection condition corresponding to the first prediction time range, the first data includes sample data and / or prediction data. Accordingly, the first device receives the third information from the second device. Based on this approach, the reasons for the sample time range and / or prediction time range can be effectively interactively adjusted.

[0125] It can be understood that, after the second device makes a judgment and selection among multiple first time ranges based on the current actual situation (such as network performance, operating environment, etc.) and the selection conditions corresponding to each first time range, it can further indicate to the first device the first time range used by the first data and the reason for using the first time range (i.e., the selection conditions are met) when reporting the first data (i.e., sample data and / or predicted data).

[0126] It should be noted that, when the first device is an access network device and the second device is a terminal device, the configuration information may be sent by the first device to the second device through RRC reconfiguration or broadcast message. When the first device is a terminal device and the second device is an access network device, the configuration information may be sent by the first device to the second device through RRC reconfiguration or mobility optimization report.

[0127] It can be seen that based on the method described in the present application, the first device can dynamically adjust the first time range based on network operation data and network performance requirements, and the first time range includes the first sample time range of sample data and / or the first prediction time range of predicted data; the first device sends configuration information to the second device, and the configuration information is used to indicate the first time range. Accordingly, after the second device receives the configuration information from the first device, it can adjust the time range of the sample data to the first sample time range, and / or adjust the time range of the predicted data to the first prediction time range. In this way, it is possible to reasonably adapt the air interface load and network performance requirements, and flexibly adjust the sample time range and the prediction time range, which is conducive to reducing the air interface overhead of the interactive sample data, and / or improving the accuracy of the predicted data.

[0128] See also Figure 6 , Figure 6 A schematic structural diagram of a communication device 600 according to an embodiment of the present application is shown. Figure 6 The communication device shown may be the first device or the second device, or may be a device in the first device or the second device, or may be a device that can be used in conjunction with the first device or the second device. Figure 6 As shown, the communication device 600 may include a communication unit 601 and a processing unit 602. The processing unit 602 is used for data processing. The communication unit 601 is used for communication. Optionally, the communication unit 601 integrates a receiving unit and a sending unit. The communication unit 601 may also be referred to as a transceiver unit. Alternatively, the communication unit 601 may also be split into a receiving unit and a sending unit.

[0129] In one implementation, the communication device 600 may be a first device, or a device in the first device, or a device that can be used in conjunction with the first device, wherein:

[0130] A processing unit 602 is configured to determine a first time range based on network operation data and network performance requirements, where the first time range includes a first sample time range of sample data and / or a first prediction time range of prediction data;

[0131] The communication unit 601 is used to send configuration information to the second device, where the configuration information is used to indicate the first time range.

[0132] In one possible implementation, the communication unit 601, before sending configuration information to the second device, is also used to: send first information to the second device, the first information including multiple mapping identifiers and a time range corresponding to each of the multiple mapping identifiers; wherein the configuration information includes a mapping identifier corresponding to the first time range, and the first time range is within the time range corresponding to the multiple mapping identifiers.

[0133] In one possible implementation, the communication unit 601, before sending configuration information to the second device, is also used to: receive second information from the second device, the second information including multiple mapping identifiers and a time range corresponding to each of the multiple mapping identifiers; wherein the configuration information includes a mapping identifier corresponding to the first time range, and the first time range is within the time range corresponding to the multiple mapping identifiers.

[0134] In a possible implementation, the communication unit 601 is further used to: receive a response message from the second device, where the response message is used to indicate that the adjustment of the sample time range of the sample data and / or the prediction time range of the prediction data has been completed.

[0135] In a possible implementation manner, the configuration information further includes first indication information, where the first indication information is used to indicate a reason for selecting the first time range.

[0136] In a possible implementation, there are multiple first time ranges, and the configuration information also includes a selection condition corresponding to each first time range.

[0137] In one possible implementation, the communication unit 601 is also used to: receive third information from the second device, the third information including first data, a first prediction time range corresponding to the first data, and a first selection condition corresponding to the first prediction time range, the first data including sample data and / or prediction data.

[0138] In a possible implementation manner, the first information and / or the second information further includes a target model corresponding to each mapping identifier, and a reporting method of sample data and / or predicted data corresponding to each mapping identifier.

[0139] In one implementation, the communication device 600 may be a second device, or a device in the second device, or a device that can be used in conjunction with the second device, wherein:

[0140] A communication unit 601 is configured to receive configuration information from a first device, where the configuration information is used to indicate a first time range, where the first time range includes a first sample time range of sample data and / or a first prediction time range of prediction data;

[0141] The processing unit 602 is configured to adjust the time range of the sample data to the first sample time range, and / or adjust the time range of the prediction data to the first prediction time range.

[0142] In a possible implementation, before receiving the configuration information from the first device, the communication unit 601 is further configured to: receive first information from the first device, where the first information includes multiple mapping identifiers and a time range corresponding to each of the multiple mapping identifiers.

[0143] In a possible implementation, before receiving the configuration information from the first device, the communication unit 601 is further configured to: send second information to the first device, where the second information includes multiple mapping identifiers and a time range corresponding to each of the multiple mapping identifiers.

[0144] In a possible implementation, the communication unit 601 is further used to: send a response message to the first device, where the response message is used to indicate that the adjustment of the sample time range of the sample data and / or the prediction time range of the prediction data has been completed.

[0145] In a possible implementation manner, the configuration information further includes first indication information, where the first indication information is used to indicate a reason for selecting the first time range.

[0146] In a possible implementation, there are multiple first time ranges, and the configuration information also includes a selection condition corresponding to each first time range.

[0147] In one possible implementation, the processing unit 602, when adjusting the time range of the sample data to the first sample time range, is specifically used to: when the first selection condition is met, adjust the time range of the sample data to the first sample time range corresponding to the first selection condition; and / or, the processing unit 602, when adjusting the time range of the prediction data to the first prediction time range, is specifically used to: when the first selection condition is met, adjust the time range of the prediction data to the first prediction time range corresponding to the first selection condition.

[0148] In one possible implementation, the communication unit 601 is further used to: send third information to the first device, the third information including first data, a first prediction time range corresponding to the first data, and a first selection condition corresponding to the first prediction time range, the first data including sample data and / or prediction data.

[0149] In a possible implementation manner, the first information and / or the second information further includes a target model corresponding to each mapping identifier, and a reporting method of sample data and / or predicted data corresponding to each mapping identifier.

[0150] Figure 7A schematic diagram of the structure of another communication device is given. The communication device 700 may be the first device or the second device in the above method embodiment, or may be a chip, a chip system, or a processor that supports the first device or the second device to implement the above method. The communication device may be used to implement the method described in the above method embodiment, and the details may refer to the description in the above method embodiment.

[0151] The communication device 700 may include one or more processors 701. The processor 701 may be a general-purpose processor or a dedicated processor, etc. For example, it may be a baseband processor or a central processing unit. The baseband processor may be used to process the communication protocol and communication data, and the central processing unit may be used to control the communication device (such as a base station, a baseband chip, a terminal, a terminal chip, a DU or a CU, etc.), execute a software program, and process the data of the software program.

[0152] Optionally, the communication device 700 may include one or more memories 702, on which instructions 704 may be stored, and the instructions may be executed on the processor 701, so that the communication device 700 performs the method described in the above method embodiment. Optionally, data may also be stored in the memory 702. The processor 701 and the memory 702 may be provided separately or integrated together.

[0153] Optionally, the communication device 700 may further include a transceiver 705 and an antenna 706. The transceiver 705 may be referred to as a transceiver unit, a transceiver, or a transceiver circuit, etc., for implementing a transceiver function. The transceiver 705 may include a receiver and a transmitter, the receiver may be referred to as a receiver or a receiving circuit, etc., for implementing a receiving function; the transmitter may be referred to as a transmitter or a transmitting circuit, etc., for implementing a transmitting function. Among them, Figure 6 The processing unit 602 shown may be a processor 701. The communication unit 601 may be a transceiver 705.

[0154] In another possible design, the processor 701 may include a transceiver for implementing the receiving and sending functions. For example, the transceiver may be a transceiver circuit, or an interface, or an interface circuit. The transceiver circuit, interface, or interface circuit for implementing the receiving and sending functions may be separate or integrated. The above-mentioned transceiver circuit, interface, or interface circuit may be used for reading and writing code / data, or the above-mentioned transceiver circuit, interface, or interface circuit may be used for transmitting or delivering signals.

[0155] In another possible design, optionally, the processor 701 may store an instruction 703, and the instruction 703 runs on the processor 701, so that the communication device 700 can execute the method described in the above method embodiment. The instruction 703 may be solidified in the processor 701, in which case the processor 701 may be implemented by hardware.

[0156] In another possible design, the communication device 700 may include a circuit that can implement the functions of sending or receiving or communicating in the aforementioned method embodiments. The processor and transceiver described in the embodiments of the present application can be implemented in an integrated circuit (IC), an analog IC, a radio frequency integrated circuit RFIC, a mixed signal IC, an application specific integrated circuit (ASIC), a printed circuit board (PCB), an electronic device, etc. The processor and transceiver can also be manufactured using various IC process technologies, such as complementary metal oxide semiconductor (CMOS), N-type metal oxide semiconductor (nMetal-oxide-semiconductor, NMOS), P-type metal oxide semiconductor (positive channelmetal oxide semiconductor, PMOS), bipolar junction transistor (Bipolar Junction Transistor, BJT), bipolar CMOS (BiCMOS), silicon germanium (SiGe), gallium arsenide (GaAs), etc.

[0157] The communication device described in the above embodiments may be an SMF, a server, a first AMF, a second AMF, a UDM or a PCF, but the scope of the communication device described in the embodiments of the present application is not limited thereto, and the structure of the communication device may not be limited thereto. Figure 7 The communication device may be an independent device or may be part of a larger device. For example, the communication device may be:

[0158] (1) Independent integrated circuit IC, or chip, or chip system or subsystem;

[0159] (2) having a set of one or more ICs, and optionally, the IC set may also include a storage component for storing data and instructions;

[0160] (3) ASIC, such as modem (MSM);

[0161] (4) Modules that can be embedded in other devices;

[0162] (5) Receivers, terminals, smart terminals, cellular phones, wireless devices, handheld devices, mobile units, vehicle-mounted devices, network devices, cloud devices, artificial intelligence devices, etc.;

[0163] (6)Others

[0164] For the case where the communication device may be a chip or a chip system, see Figure 8 Schematic diagram of the chip structure shown. Figure 8 The chip 800 shown includes a processor 801 and an interface 802. Optionally, it may also include a memory 803. The number of the processor 801 may be one or more, and the number of the interface 802 may be multiple.

[0165] For the case where the chip is used to implement the first device or the second device in the embodiment of the present application:

[0166] The interface 802 is used to receive or output signals;

[0167] The processor 801 is used to execute data processing operations of the first device or the second device.

[0168] It is understandable that some optional features in the embodiments of the present application may be implemented independently in certain scenarios without relying on other features, such as the solution on which they are currently based, to solve corresponding technical problems and achieve corresponding effects, or may be combined with other features according to needs in certain scenarios. Accordingly, the communication device provided in the embodiments of the present application may also implement these features or functions accordingly, which will not be described in detail here.

[0169] It should be understood that the processor in the embodiment of the present application can be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method embodiment can be completed by an integrated logic circuit of hardware in the processor or an instruction in the form of software. The above processor can be a general-purpose processor, a digital signal processor (digital signal processor, DSP), an application specific integrated circuit (application specific integrated circuit, ASIC), a field programmable gate array (field programmable gate array, FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components.

[0170] It can be understood that the memory in the embodiments of the present application can be a volatile memory or a non-volatile memory, or can include both volatile and non-volatile memories. Among them, the non-volatile memory can be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or a flash memory. The volatile memory can be a random access memory (RAM), which is used as an external cache. By way of example and not limitation, many forms of RAM are available, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), and direct RAM (DR RAM). It should be noted that the memory of the systems and methods described herein is intended to include, but is not limited to, these and any other suitable types of memory.

[0171] The present application also provides a computer-readable medium, in which a computer program or instruction is stored. When the computer program or instruction is executed by a communication device, the functions of any of the above method embodiments are implemented.

[0172] The present application also provides a computer program product including instructions, and when a computer reads and executes the computer program product, the computer implements the functions of any of the above method embodiments.

[0173] The present application provides a communication system, which includes a first device and a second device; wherein the first device is used to execute the method executed by the first device in the above embodiment, and the second device is used to execute the method executed by the second device in the above embodiment.

[0174] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer instructions are loaded and executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium, for example, the computer instructions may be transmitted from a website site, computer, server or data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (digital subscriber line, DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) mode to another website site, computer, server or data center. The computer-readable storage medium may be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more available media integrated. The available medium may be a magnetic medium (eg, a floppy disk, a hard disk, a magnetic tape), an optical medium (eg, a high-density digital video disc (DVD)), or a semiconductor medium (eg, a solid state disk (SSD)).

[0175] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A configuration method, characterized in that: The method comprises: Determine a first time range based on network operation data and network performance requirements, the first time range comprising a first sample time range of sample data and / or a first prediction time range of prediction data; Configuration information is sent to the second device, where the configuration information is used to indicate the first time range.

2. The method according to claim 1, characterized in that Before sending the configuration information to the second device, the method further includes: Sending first information to a second device, where the first information includes a plurality of mapping identifiers and a time range corresponding to each of the plurality of mapping identifiers; The configuration information includes a mapping identifier corresponding to the first time range, and the first time range is located in the time ranges corresponding to the multiple mapping identifiers.

3. The method according to claim 1, characterized in that Before sending the configuration information to the second device, the method further includes: receiving second information from a second device, where the second information includes a plurality of mapping identifiers and a time range corresponding to each of the plurality of mapping identifiers; The configuration information includes a mapping identifier corresponding to the first time range, and the first time range is located in the time ranges corresponding to the multiple mapping identifiers.

4. The method according to any one of claims 1 to 3, characterized in that The method further comprises: A response message is received from the second device, where the response message is used to indicate that adjustment of the sample time range of the sample data and / or the prediction time range of the prediction data has been completed.

5. The method according to any one of claims 1 to 4, characterized in that The configuration information also includes first indication information, where the first indication information is used to indicate a reason for selecting the first time range.

6. The method according to any one of claims 1 to 4, characterized in that There are multiple first time ranges, and the configuration information also includes a selection condition corresponding to each first time range.

7. The method according to claim 6, characterized in that The method further comprises: Receive third information from the second device, the third information including first data, a first prediction time range corresponding to the first data, and a first selection condition corresponding to the first prediction time range, the first data including sample data and / or prediction data.

8. The method according to any one of claims 2 to 7, characterized in that: The first information and / or the second information also includes a target model corresponding to each mapping identifier, and a reporting method of sample data and / or predicted data corresponding to each mapping identifier.

9. A configuration method, characterized in that: The method comprises: Receiving configuration information from a first device, the configuration information being used to indicate a first time range, the first time range comprising a first sample time range of sample data and / or a first prediction time range of prediction data; The time range of the sample data is adjusted to the first sample time range, and / or the time range of the prediction data is adjusted to the first prediction time range.

10. The method according to claim 9, characterized in that Before receiving the configuration information from the first device, the method further includes: First information is received from a first device, where the first information includes a plurality of mapping identifiers and a time range corresponding to each of the plurality of mapping identifiers.

11. The method according to claim 9, characterized in that Before receiving the configuration information from the first device, the method further includes: Second information is sent to the first device, where the second information includes a plurality of mapping identifiers and a time range corresponding to each of the plurality of mapping identifiers.

12. The method according to any one of claims 9 to 11, characterized in that: The method further comprises: A response message is sent to the first device, where the response message is used to indicate that adjustment of the sample time range of the sample data and / or the prediction time range of the prediction data has been completed.

13. The method according to any one of claims 9 to 12, characterized in that: The configuration information also includes first indication information, where the first indication information is used to indicate a reason for selecting the first time range.

14. The method according to any one of claims 9 to 12, characterized in that: There are multiple first time ranges, and the configuration information also includes a selection condition corresponding to each first time range.

15. The method according to claim 14, characterized in that The step of adjusting the time range of the sample data to the first sample time range includes: When the first selection condition is met, the time range of the sample data is adjusted to a first sample time range corresponding to the first selection condition; and / or, The step of adjusting the time range of the prediction data to the first prediction time range includes: When the first selection condition is met, the time range of the predicted data is adjusted to a first prediction time range corresponding to the first selection condition.

16. The method according to claim 15, characterized in that The method further comprises: Sending third information to the first device, the third information including first data, a first prediction time range corresponding to the first data, and a first selection condition corresponding to the first prediction time range, the first data including sample data and / or prediction data.

17. The method according to any one of claims 10 to 16, characterized in that The first information and / or the second information also includes a target model corresponding to each mapping identifier, and a reporting method of sample data and / or predicted data corresponding to each mapping identifier.

18. A communication system, characterized in that: The method comprises a first device and a second device; wherein the first device is used to execute the method according to any one of claims 1 to 8, and the second device is used to execute the method according to any one of claims 9 to 17.

19. A communication device, characterized in that: The method comprises a unit for executing the method according to any one of claims 1 to 8, or comprises a unit for executing the method according to any one of claims 9 to 17.

20. A communication device, characterized in that: The method comprises a processor and a memory, wherein the processor and the memory are coupled, and the processor is used to implement the method according to any one of claims 1 to 8, or the processor is used to implement the method according to any one of claims 9 to 17.

21. A chip, characterized in that: It comprises a processor and an interface, wherein the processor and the interface are coupled; the interface is used to receive or output signals, and the processor is used to execute code instructions so that the method described in any one of claims 1 to 8 is executed, or so that the method described in any one of claims 9 to 17 is executed.

22. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions, which, when called by the computer, enable the computer to execute the method described in any one of claims 1 to 8, or enable the computer to execute the method described in any one of claims 9 to 17.

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