Data processing method, device, and system and storage medium

Abstract

Embodiments of the present disclosure relate to the technical field of communications, and disclose a data processing method, a device, and a computer readable storage medium. The data processing method comprises: on the basis of a first condition, collecting data and storing same. According to the embodiments of the present disclosure, a UE can be reasonably triggered to perform data collection by collecting and storing data on the basis of the first condition.

Description

Data processing method, device, system and storage medium Technical Field

[0001] The present disclosure relates to the field of communication technology, and in particular to a data processing method, device, system, and storage medium. Background Art

[0002] Machine learning algorithms are one of the most important implementation methods of artificial intelligence technology. Wireless communication networks can use artificial intelligence (AI) for prediction and reasoning, improving system performance.

[0003] Summary of the Invention

[0004] Embodiments of the present disclosure provide a data processing method, device, system, and storage medium.

[0005] According to a first aspect of an embodiment of the present disclosure, a data processing method is provided. The method is executed by a terminal and includes:

[0006] According to the first condition, it is determined to collect data and store the data.

[0007] A second aspect of the present disclosure provides a data processing method, which is executed by a network device and includes:

[0008] Data reported by a terminal is received, where the data is collected and stored by the terminal based on a first condition.

[0009] According to a third aspect of the present disclosure, a terminal is provided, including:

[0010] The first processing module is used to determine to collect data and store the data according to a first condition.

[0011] A fourth aspect of the embodiments of the present disclosure provides a network device, including:

[0012] The second transceiver module is configured to receive data reported by a terminal, where the data is collected and stored by the terminal based on a first condition.

[0013] According to a fifth aspect of the present disclosure, a terminal is provided, including:

[0014] one or more processors;

[0015] The terminal is used to execute the optional implementation of the aforementioned first aspect.

[0016] According to a sixth aspect of the present disclosure, a network device is provided, including:

[0017] one or more processors;

[0018] The network device is used to execute the optional implementation method of the aforementioned second aspect.

[0019] In a seventh aspect of an embodiment of the present disclosure, a communication system is proposed, including a terminal and a network device, wherein the terminal is used to implement the method described in the optional implementation manner of the first aspect, and the network device is used to implement the method described in the optional implementation manner of the second aspect.

[0020] According to an eighth aspect of an embodiment of the present disclosure, a computer-readable storage medium is provided, in which executable instructions are stored. The executable instructions are loaded and executed by the processor to implement the method described in the optional implementation of the first or second aspect above.

[0021] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.

[0023] FIG1 is a schematic structural diagram of a wireless communication system according to an exemplary embodiment;

[0024] FIG2 is a flow chart showing a data processing method according to an exemplary embodiment;

[0025] FIG3 a is a flow chart of a data processing method according to an embodiment of the present disclosure;

[0026] FIG3 b is a flow chart of a data processing method according to an embodiment of the present disclosure;

[0027] FIG3 c is a schematic flow chart of a data processing method according to an embodiment of the present disclosure;

[0028] FIG4 is a flow chart of a data processing method according to an embodiment of the present disclosure;

[0029] FIG5 is a flow chart of a data processing method according to an embodiment of the present disclosure;

[0030] FIG6 a is a schematic structural diagram of a terminal proposed in an embodiment of the present disclosure;

[0031] FIG6 b is a schematic diagram of the structure of a network device proposed in an embodiment of the present disclosure;

[0032] FIG7a is a schematic structural diagram of a communication device proposed in an embodiment of the present disclosure;

[0033] FIG7 b is a schematic structural diagram of a chip proposed in an embodiment of the present disclosure. DETAILED DESCRIPTION

[0034] The embodiments of the present disclosure provide a data processing method, a device, a communication system, and a storage medium.

[0035] In a first aspect, an embodiment of the present disclosure provides a data processing method, which is executed by a terminal and includes:

[0036] According to the first condition, it is determined to collect data and store the data.

[0037] In the above embodiment, by collecting and storing data based on the first condition, the UE can be reasonably triggered to perform data collection.

[0038] In combination with some embodiments of the first aspect, in some embodiments, the method further includes: storing a first application condition when collecting the data.

[0039] In the above embodiment, when data is collected and stored based on the first condition, the application conditions when collecting the data are also stored to provide a more complete data basis for subsequent AI model training.

[0040] In conjunction with some embodiments of the first aspect, in some embodiments, the method further includes:

[0041] First indication information sent by a network device is received, where the first indication information is used to indicate a condition related to the network device when the terminal collects the data.

[0042] In the above embodiment, the application conditions when the instruction storage terminal collects data based on the network side can make the subsequent training of the AI ​​model based on the data more in line with the performance requirements of the network side.

[0043] In combination with some embodiments of the first aspect, in some embodiments, the method further includes: storing an application scenario when collecting the data.

[0044] In the above embodiment, when data is collected and stored based on the first condition, the application scenario when the data is collected is also stored to provide a more complete data basis for subsequent AI model training.

[0045] In conjunction with some embodiments of the first aspect, in some embodiments, the application scenario includes at least one of the following:

[0046] Beam management;

[0047] Channel state information compression;

[0048] Positioning of the terminal;

[0049] Terminal switching;

[0050] Terminal mobility management.

[0051] In conjunction with some embodiments of the first aspect, in some embodiments, the method further includes:

[0052] Receive second indication information sent by a network device, where the second indication information is used to indicate an application scenario when the terminal collects the data.

[0053] In the above embodiment, the application scenario when the network-side instruction storage terminal collects data can make the subsequent data-based AI model training more in line with the performance requirements of the network side.

[0054] In conjunction with some embodiments of the first aspect, in some embodiments, the first condition includes that the performance of the currently activated AI model satisfies the second condition;

[0055] The performance of the AI ​​model meeting the second condition includes at least one of the following:

[0056] The accuracy of the AI ​​model output meets a first preset value;

[0057] The difference between the output value of the AI ​​model and the true value meets the second preset value.

[0058] In the above embodiment, the performance of the currently activated AI model is used as a condition to trigger the UE to collect data. Data corresponding to the performance of the AI ​​model can be collected (for example, data when the performance of the AI ​​model is poor), and then these data are used to train and obtain the corresponding model, and the performance of the system can be improved by using the AI ​​model with better performance.

[0059] In combination with some embodiments of the first aspect, in some embodiments, the first condition includes a change in the second application condition.

[0060] In conjunction with some embodiments of the first aspect, in some embodiments, the change in the second application condition includes:

[0061] The second application condition changes from being satisfied to not being satisfied; or

[0062] The second application condition changes from not being satisfied to being satisfied.

[0063] In the above embodiment, the UE is triggered to collect data based on whether a certain specific application condition sends a change. Data corresponding to the AI ​​application condition can be collected, and then these data are used to train a model corresponding to the AI ​​application condition, thereby improving the performance of the AI ​​model under the specific application condition, so that the AI ​​model can achieve better performance under the specific application condition.

[0064] In combination with some embodiments of the first aspect, in some embodiments, the second application condition includes an application condition corresponding to the currently running AI model.

[0065] In the above embodiment, if the application conditions corresponding to the currently running AI model send changes, the UE is triggered to collect data, and data corresponding to the AI ​​application conditions can be collected, and then these data can be used to train and obtain a model corresponding to the AI ​​application conditions, thereby improving the performance of the AI ​​model under specific application conditions.

[0066] In combination with some embodiments of the first aspect, in some embodiments, the second application condition includes an application condition configured by the network device.

[0067] In the above embodiment, if the application conditions configured by the network device send changes, the UE is triggered to collect data, and data corresponding to the AI ​​application conditions can be collected, and then these data can be used to train and obtain a model corresponding to the AI ​​application conditions, thereby improving the AI ​​model performance under specific application conditions.

[0068] In combination with some embodiments of the first aspect, in some embodiments, the method further includes: reporting the stored data to a network device.

[0069] In conjunction with some embodiments of the first aspect, in some embodiments, reporting the stored data to the network device includes:

[0070] Periodically reporting the stored data to the network device.

[0071] In the above embodiment, periodically reporting the stored data to the network device can effectively save the power consumption of the UE.

[0072] In conjunction with some embodiments of the first aspect, in some embodiments, the method further includes:

[0073] receiving third indication information sent by the network device, where the third indication information is used to instruct the terminal to report the stored data;

[0074] Reporting the stored data to the network device includes:

[0075] Based on the third indication information, the stored data is reported to the network device.

[0076] In the above embodiment, based on reporting the stored data to the network device on the network side, data that meets the requirements of the network side can be reported, and the power consumption of the UE can also be saved.

[0077] In conjunction with some embodiments of the first aspect, in some embodiments, the method further includes:

[0078] Fourth indication information is sent to the network device, where the fourth indication information is used to indicate at least one of a first application condition and an application scenario corresponding to the data.

[0079] In the above embodiment, when reporting data to the network side, the application conditions and / or scenarios corresponding to the reported data can also be indicated, which is beneficial for the network side to perform subsequent AI model training.

[0080] In a second aspect, an embodiment of the present disclosure provides a data processing method, which is executed by a network device and includes:

[0081] Data reported by a terminal is received, where the data is collected and stored by the terminal based on a first condition.

[0082] In conjunction with some embodiments of the second aspect, in some embodiments, the receiving data reported by the terminal includes:

[0083] Periodically receive data reported by the terminal.

[0084] In conjunction with some embodiments of the second aspect, in some embodiments, the method further includes:

[0085] Sending third indication information to the terminal, where the third indication information is used to instruct the terminal to report stored data;

[0086] The data reported by the receiving terminal includes:

[0087] Receive data reported by the terminal based on the third indication information.

[0088] In conjunction with some embodiments of the second aspect, in some embodiments, the method further includes:

[0089] receiving fourth indication information sent by the terminal, where the fourth indication information is used to indicate at least one of a first application condition and an application scenario corresponding to the data;

[0090] The first application condition is an application condition corresponding to when the data is collected by the terminal, and the application scenario is an application scenario corresponding to when the data is collected by the terminal.

[0091] In conjunction with some embodiments of the second aspect, in some embodiments, the method further includes:

[0092] First indication information is sent to the terminal, where the first indication information is used to indicate a condition related to a network device when the terminal collects the data.

[0093] In conjunction with some embodiments of the second aspect, in some embodiments, the method further includes:

[0094] Second indication information is sent to the terminal, where the second indication information is used to indicate an application scenario when the terminal collects the data.

[0095] In conjunction with some embodiments of the second aspect, in some embodiments, the application scenario includes at least one of the following:

[0096] Beam management;

[0097] Channel state information compression;

[0098] Positioning of the terminal;

[0099] Terminal switching;

[0100] Terminal mobility management.

[0101] In conjunction with some embodiments of the second aspect, in some embodiments, the first condition includes that the performance of the currently activated AI model satisfies the second condition;

[0102] The performance of the AI ​​model meeting the second condition includes at least one of the following:

[0103] The accuracy of the AI ​​model output meets a first preset value;

[0104] The difference between the output value of the AI ​​model and the true value meets the second preset value.

[0105] In combination with some embodiments of the second aspect, in some embodiments, the first condition includes a change in the second application condition.

[0106] In conjunction with some embodiments of the second aspect, in some embodiments, the change in the second application condition includes:

[0107] The second application condition changes from being satisfied to not being satisfied; or

[0108] The second application condition changes from not being satisfied to being satisfied.

[0109] In combination with some embodiments of the second aspect, in some embodiments, the second application condition includes an application condition corresponding to the currently running AI model.

[0110] In combination with some embodiments of the second aspect, in some embodiments, the second application condition includes an application condition configured by the network device.

[0111] In a third aspect, an embodiment of the present disclosure provides a terminal, including:

[0112] The first processing module is used to determine to collect data and store the data according to a first condition.

[0113] In a fourth aspect, an embodiment of the present disclosure provides a network device, including:

[0114] The second transceiver module is configured to receive data reported by a terminal, where the data is collected and stored by the terminal based on a first condition.

[0115] In a fifth aspect, an embodiment of the present disclosure provides a terminal, including:

[0116] one or more processors;

[0117] The terminal executes the method described in the optional implementation manner of the first aspect.

[0118] According to a sixth aspect of an embodiment of the present disclosure, a network device is provided, including:

[0119] one or more processors;

[0120] In which, the network device executes the method described in the optional implementation manner of the second aspect.

[0121] In the seventh aspect, an embodiment of the present disclosure proposes a communication system, including a terminal and a network device, wherein the terminal is used to implement the method described in the optional implementation mode of the first aspect, and the network device is used to implement the method described in the optional implementation mode of the second aspect.

[0122] In an eighth aspect, an embodiment of the present disclosure proposes a storage medium, which stores instructions. When the instructions are executed on a communication device, the communication device executes the method described in the optional implementation of the first aspect or the second aspect.

[0123] In a ninth aspect, an embodiment of the present disclosure proposes a program product. When the program product is executed by a communication device, the communication device executes the method described in the optional implementation manner of the first aspect or the second aspect.

[0124] In a tenth aspect, an embodiment of the present disclosure proposes a computer program, which, when executed on a computer, enables the computer to execute the method described in the optional implementation of the first aspect or the second aspect.

[0125] In an eleventh aspect, an embodiment of the present disclosure proposes a chip or a chip system, which includes a processing circuit for executing the method described in the optional implementation of the first or second aspect above.

[0126] It is understandable that the above-mentioned apparatus for random access, communication equipment, communication system, storage medium, program product, and computer program are all used to perform the method proposed in the embodiments of the present disclosure. Therefore, the beneficial effects that can be achieved can refer to the beneficial effects of the corresponding methods and will not be repeated here. Among them, the communication equipment can be a terminal or a network device.

[0127] The present disclosure provides data processing methods, apparatuses, communication devices, communication systems, and storage media. In some embodiments, the terms "data processing method," "information processing method," and "for random access" are interchangeable; the terms "apparatus for random access," "information processing apparatus," and "communication apparatus" are interchangeable; and the terms "information processing system" and "communication system" are interchangeable.

[0128] The embodiments of the present disclosure are not exhaustive and are merely illustrative of some embodiments, and are not intended to be a specific limitation on the scope of protection of the embodiments of the present disclosure. In the absence of contradiction, each step in a certain embodiment can be implemented as an independent embodiment, and the steps can be arbitrarily combined. For example, a solution after removing some steps in a certain embodiment can also be implemented as an independent embodiment, and the order of the steps in a certain embodiment can be arbitrarily exchanged. In addition, the optional implementation methods in a certain embodiment can be arbitrarily combined; in addition, the embodiments can be arbitrarily combined. For example, some or all steps of different embodiments can be arbitrarily combined, and a certain embodiment can be arbitrarily combined with the optional implementation methods of other embodiments.

[0129] In each embodiment of the present disclosure, unless otherwise specified or provided for by logic, the terms and / or descriptions between the embodiments are consistent and can be referenced by each other. The technical features in different embodiments can be combined to form a new embodiment based on their inherent logical relationships.

[0130] The terms used in the embodiments of the present disclosure are only for the purpose of describing specific embodiments and are not intended to limit the embodiments of the present disclosure.

[0131] In the embodiments of the present disclosure, unless otherwise specified, elements expressed in the singular, such as "a", "an", "the", "above", "said", "the", "the", etc., may mean "one and only one", or "one or more", "at least one", etc. For example, when using articles such as "a", "an", "the" in English in translation, the noun following the article may be understood as a singular expression or a plural expression.

[0132] In the embodiments of the present disclosure, “plurality” refers to two or more.

[0133] In some embodiments, the terms "at least one of", "at least one of", "at least one of", "one or more", "a plurality of", "multiple", etc. can be used interchangeably.

[0134] In the embodiments of the present disclosure, descriptions such as “at least one of A, B, C…”, “A and / or B and / or C…”, etc. include the situation where any one of A, B, C… exists alone, and also include any combination of any multiple of A, B, C…, and each situation can exist alone; for example, “at least one of A, B, C” includes the situation where A exists alone, B exists alone, C exists alone, the combination of A and B, the combination of A and C, the combination of B and C, and the combination of A, B, and C; for example, A and / or B includes the situation where A exists alone, B exists alone, and the combination of A and B.

[0135] In some embodiments, descriptions such as "in one case A, in another case B," or "in response to one case A, in response to another case B," may include the following technical solutions depending on the situation: executing A independently of B (in some embodiments, A); executing B independently of A (in some embodiments, B); selectively executing A and B (in some embodiments, selecting between A and B); and executing both A and B (in some embodiments, A and B). The same applies when there are more branches, such as A, B, and C.

[0136] The prefixes such as "first" and "second" in the embodiments of the present disclosure are only used to distinguish different description objects and do not constitute any restriction on the position, order, priority, quantity or content of the description objects. For the statement of the description object, please refer to the description in the context of the claims or embodiments, and no unnecessary restriction should be constituted due to the use of prefixes. For example, if the description object is a "field", the ordinal number before the "field" in the "first field" and the "second field" does not limit the position or order between the "fields". "First" and "second" do not limit whether the "fields" they modify are in the same message, nor do they limit the order of the "first field" and the "second field". For another example, if the description object is a "level", the ordinal number before the "level" in the "first level" and the "second level" does not limit the priority between the "levels". For another example, the number of description objects is not limited by the ordinal number and can be one or more. Taking "first device" as an example, the number of "devices" can be one or more. In addition, the objects modified by different prefixes can be the same or different. For example, if the description object is "device", then the "first device" and the "second device" can be the same device or different devices, and their types can be the same or different. For another example, if the description object is "information", then the "first configuration" and the "second configuration" can be the same information or different information, and their contents can be the same or different.

[0137] In some embodiments, “including A,” “comprising A,” “used to indicate A,” and “carrying A” can be interpreted as directly carrying A or indirectly indicating A.

[0138] In some embodiments, terms such as "in response to...", "in response to determining...", "in the case of...", "at the time of...", "when...", "if...", "if...", etc. can be used interchangeably.

[0139] In some embodiments, terms such as "greater than", "greater than or equal to", "not less than", "more than", "more than or equal to", "not less than", "higher than", "higher than or equal to", "not less than", and "above" can be replaced with each other, and terms such as "less than", "less than or equal to", "not greater than", "less than", "less than or equal to", "not more than", "lower than", "lower than or equal to", "not higher than", and "below" can be replaced with each other.

[0140] In some embodiments, devices, etc. can be interpreted as physical or virtual, and their names are not limited to the names recorded in the embodiments. Terms such as "device", "equipment", "device", "circuit", "network element", "node", "function", "unit", "section", "system", "network", "chip", "chip system", "entity", and "subject" can be used interchangeably.

[0141] In some embodiments, the terms "access network device (AN device)", "radio access network device (RAN device)", "base station (BS)", "radio base station" "fixed station", "node", "access point", "transmission point (TP)", "reception point (RP)", "transmission / reception point (TRP)", "panel", "antenna panel", "antenna array", "cell", "macro cell", "small cell", "femto cell", "pico cell", "sector", "cell group", "carrier", "component carrier", "bandwidth part (BWP)" and the like may be used interchangeably.

[0142] In some embodiments, the terms "terminal", "terminal device", "user equipment (UE)", "user terminal", "mobile station (MS)", "mobile terminal (MT)", subscriber station, mobile unit, subscriber unit, wireless unit, remote unit, mobile device, wireless device, wireless communication device, remote device, mobile subscriber station, access terminal, mobile terminal, wireless terminal, remote terminal, handset, user agent, mobile client, client, etc. can be used interchangeably.

[0143] In some embodiments, the access network device, the core network device, or the network device can be replaced by a terminal. For example, the various embodiments of the embodiments of the present disclosure can also be applied to a structure in which the communication between the access network device, the core network device, or the network device and the terminal is replaced by communication between multiple terminals (for example, which can also be referred to as device-to-device (D2D), vehicle-to-everything (V2X), etc.). In this case, it can also be set as a structure in which the terminal has all or part of the functions of the access network device. In addition, languages ​​such as "uplink" and "downlink" can also be replaced with languages ​​corresponding to communication between terminals (for example, "side").

[0144] For example, an uplink channel, a downlink channel, etc. may be replaced by a side channel, and an uplink, a downlink, etc. may be replaced by a side link.

[0145] In some embodiments, terms such as "uplink", "uplink", "physical uplink" can be interchangeable with each other, and terms such as "downlink", "downlink", "physical downlink" can be interchangeable with each other, and terms such as "side", "sidelink", "side communication", "sidelink communication", "direct connection", "direct link", "direct communication", "direct link communication" can be interchangeable with each other.

[0146] In some embodiments, the terms "downlink control information (DCI)", "downlink (DL) assignment", "DL DCI", "uplink (UL) grant", "UL DCI" and the like may be used interchangeably.

[0147] In some embodiments, terms such as "physical downlink shared channel (PDSCH)" and "DL data" can be used interchangeably, and terms such as "physical uplink shared channel (PUSCH)" and "UL data" can be used interchangeably.

[0148] In some embodiments, the determination or judgment can be performed by a value represented by 1 bit (0 or 1), or by a true or false value (Boolean value) represented by true or false, or by comparison of numerical values ​​(for example, comparison with a predetermined value), but is not limited thereto.

[0149] In some embodiments, "network" can be interpreted as devices included in the network (eg, access network equipment, core network equipment, etc.).

[0150] In some embodiments, obtaining data, information, etc. may comply with the laws and regulations of the country where the data is obtained.

[0151] In some embodiments, data, information, etc. may be obtained with the user's consent.

[0152] FIG1 is a schematic diagram showing the architecture of a communication system according to an embodiment of the present disclosure.

[0153] As shown in FIG1 , a communication system 100 includes a terminal 101 and a network device 102 .

[0154] In some embodiments, the terminal 101 includes, for example, a mobile phone, a wearable device, an Internet of Things device, a car with communication function, a smart car, a tablet computer, a computer with wireless transceiver function, a virtual reality (VR) terminal device, an augmented reality (AR) terminal device, a wireless terminal device in industrial control, a wireless terminal device in self-driving, a wireless terminal device in remote medical surgery, a wireless terminal device in a smart grid, a wireless terminal device in transportation safety, a wireless terminal device in a smart city, and at least one of a wireless terminal device in a smart home, but is not limited thereto.

[0155] In some embodiments, the network device 102 may include at least one of an access network device and a core network device.

[0156] In some embodiments, the access network device is, for example, a node or device that accesses a terminal to a wireless network. The network device may include an evolved NodeB (eNB), a next generation evolved NodeB (ng-eNB), a next generation NodeB (gNB), a node B (NB), a home node B (HNB), a home evolved nodeB (HeNB), a wireless backhaul device, a radio network controller (RNC), a base station controller (BSC), a base transceiver station (BTS), a base band unit (BBU), a mobile switching center, a base station in a 6G communication system, an open base station (Open RAN), a cloud base station (Cloud RAN), a base station in other communication systems, and at least one of an access node in a wireless fidelity (WiFi) system, but is not limited thereto.

[0157] In some embodiments, the technical solutions of the embodiments of the present disclosure may be applicable to the Open RAN architecture. In this case, the interfaces between or within the network devices involved in the embodiments of the present disclosure may become internal interfaces of the Open RAN, and the processes and information interactions between these internal interfaces may be implemented through software or programs.

[0158] In some embodiments, the access network device can be composed of a centralized unit (CU) and a distributed unit (DU), where the CU can also be called a control unit. The CU-DU structure can be used to split the protocol layer of the network device, with the functions of some protocol layers centrally controlled by the CU, and the functions of the remaining part or all of the protocol layers distributed in the DU, which is centrally controlled by the CU, but is not limited to this.

[0159] In some embodiments, the access network device may be a single device, or may be multiple devices or a group of devices, each including all or part of a first network element, a second network element, etc. The network element may be virtual or physical. The network device may include, for example, at least one of an Evolved Packet Core (EPC), a 5G Core Network (5GCN), and a Next Generation Core (NGC).

[0160] In some embodiments, a core network device may be a device including one or more network elements, or may be multiple devices or device groups, each including all or part of the one or more network elements. The network element may be virtual or physical. The core network may include, for example, at least one of an Evolved Packet Core (EPC), a 5G Core Network (5GCN), and a Next Generation Core (NGC).

[0161] It can be understood that the communication system described in the embodiment of the present disclosure is for the purpose of more clearly illustrating the technical solution of the embodiment of the present disclosure, and does not constitute a limitation on the technical solution proposed in the embodiment of the present disclosure. Ordinary technicians in this field can know that with the evolution of the system architecture and the emergence of new business scenarios, the technical solution proposed in the embodiment of the present disclosure is also applicable to similar technical problems.

[0162] The following embodiments of the present disclosure may be applied to the communication system 100 shown in Figure 1, or a portion thereof, but are not limited thereto. The entities shown in Figure 1 are illustrative only. The communication system may include all or part of the entities shown in Figure 1, or may include other entities outside of Figure 1. The number and form of the entities may be arbitrary. The connection relationship between the entities is illustrative only. The entities may be connected or disconnected, and the connection may be in any manner, including direct or indirect, wired or wireless.

[0163] The embodiments of the present disclosure may be applied to Long Term Evolution (LTE), LTE-Advanced (LTE-A), LTE-Beyond (LTE-B), SUPER 3G, IMT-Advanced, 4th generation mobile communication system (4G), 5th generation mobile communication system (5G), 5G new radio (NR), future radio access (FRA), new radio access technology (RAT), new radio (NR), new radio access (NX), future generation radio access (FX), Global System for Mobile communications (GSM (registered trademark)), CDMA2000, Ultra Mobile Broadband (UMB), IEEE 802.11 (Wi-Fi (registered trademark)), IEEE 802.16 (WiMAX (registered trademark)), IEEE 802.20, Ultra-WideBand (UWB), Bluetooth (registered trademark), Public Land Mobile Network (PLMN) networks, Device-to-Device (D2D) systems, Machine-to-Machine (M2M) systems, Internet of Things (IoT) systems, Vehicle-to-Everything (V2X), other systems utilizing random access, and next-generation systems based on and extending these systems. Furthermore, multiple systems may be combined (for example, a combination of LTE or LTE-A with 5G).

[0164] First, the related technologies in this disclosure are described:

[0165] Machine learning algorithms are one of the most important approaches to implementing artificial intelligence technology. Machine learning uses large amounts of training data to generate models that can then be used to predict events. In many fields, models trained using machine learning can produce highly accurate predictions.

[0166] Wireless communication networks can use artificial intelligence (AI) for prediction and reasoning to improve system performance.

[0167] During beam management, the UE can reduce the number of beams measured. The UE or base station uses an AI model to perform beam prediction to obtain the optimal beam. Beam prediction includes spatial and time domain beam prediction. In spatial beam prediction, the UE measures a small number of beams and predicts the measurement results of other beams. In time domain beam prediction, the UE predicts future beam measurement results based on historical beam measurement results.

[0168] During the Channel State Information (CSI) reporting process, the UE can compress the CSI measurement results using an AI model and report the compressed CSI measurement results to the base station. After receiving the results, the base station can restore the original CSI measurement results using the AI ​​model, thereby reducing the number of signaling bits required during the reporting process. The base station can also predict future CSI based on the historical CSI measurement results reported by the UE.

[0169] During the positioning process, the UE can predict its precise location based on limited measurement results.

[0170] During the mobility process, the UE can predict the handover target cell or mobility event.

[0171] If the AI ​​model training is located on the network side, the UE needs to report the collected data to the network. To avoid frequent reporting of collected data, the UE can store multiple collected data locally and report all stored data to the network in one report.

[0172] In beam management, the model training data may include beam measurement results, beam identifiers, the strongest K beam measurement results and beam identifiers, and the time when the beam measurement results were obtained. The measured beams may be network configurations.

[0173] In CSI compression, the data for model training may include CSI measurement results and the time when the CSI measurement results are obtained.

[0174] In positioning, the data for model training may include channel impulse response measurement results, UE location information, and PRS (Positioning Reference Signal) measurement results.

[0175] In mobility management, the data for model training may include measurement results of the serving cell, measurement results of the target cell, etc.

[0176] AI functionality is a collection of AI models that can be used for specific functions.

[0177] AI models or functions can achieve better performance under specific application conditions. Application conditions can be divided into network-side conditions and UE-side conditions.

[0178] The application conditions of AI models are related to the data used for training. AI models can achieve better performance under the application conditions of training data collection. However, there is no clear regulation on how to trigger the UE to collect AI training data.

[0179] Therefore, the solution provided by the embodiment of the present disclosure provides a data processing method, which enables the UE to collect and store data based on the first condition, and can reasonably trigger data collection to obtain an AI model with better performance.

[0180] Based on the above wireless communication system, various embodiments of the communication method proposed in the present disclosure are described in detail below.

[0181] FIG2 is an interactive diagram of a data processing method according to an embodiment of the present disclosure. As shown in FIG2 , the data processing method is used in a communication system 100, and the method includes:

[0182] S201. The terminal 101 determines to collect and store data based on a first condition.

[0183] In some embodiments, the data is used for training or performance monitoring of AI models.

[0184] In some embodiments, the first condition may include that the performance of the currently activated AI model satisfies the second condition.

[0185] Optionally, if the performance of the currently activated AI model meets the second condition, data is collected and stored.

[0186] In some embodiments, the performance of the AI ​​model satisfies the second condition, including at least one of the following:

[0187] The accuracy of the AI ​​model output meets a first preset value;

[0188] The difference between the output value of the AI ​​model and the true value meets the second preset value.

[0189] Optionally, if the accuracy of the AI ​​model output is less than the first preset value, or the accuracy of the AI ​​model output is greater than the first preset value, or the accuracy of the AI ​​model output is equal to the first preset value, then the performance of the AI ​​model meets the second condition.

[0190] Optionally, if the difference between the output value of the AI ​​model and the true value is less than a second preset value, or the difference between the output value of the AI ​​model and the true value is greater than the second preset value, or the difference between the output value of the AI ​​model and the true value is equal to the second preset value, then the performance of the AI ​​model meets the second condition.

[0191] In some embodiments, at least one of the first preset value and the second preset value may be pre-configured or obtained from a protocol, which is not limited in the embodiments of the present application.

[0192] In some embodiments, the first condition may include a change in the second application condition.

[0193] Optionally, if the second application condition changes, data is collected and stored.

[0194] In some embodiments, the second application condition includes an application condition configured by the network device.

[0195] In some embodiments, the second application condition may include at least one of a condition related to the network device and a condition related to the terminal.

[0196] Optionally, the conditions related to the network device may also be described as network-side conditions; and the conditions related to the terminal may also be described as UE-side conditions.

[0197] Optionally, the application conditions of the network configuration include: conditions on the network side and / or conditions on the UE side.

[0198] In some embodiments, the conditions on the UE side may include: at least one of the UE's speed, power, operating power, computing capability, location, service type, antenna configuration, rotation speed, and the like.

[0199] Optionally, the computing capability of the UE may include, but is not limited to, floating-point operations per second (FLOPs).

[0200] Optionally, the location of the UE may be a geographical location, or may be a location of the UE in a cell, but is not limited thereto.

[0201] Optionally, the service type of the UE may be at least one of audio, video, multimedia, voice, etc., but is not limited thereto.

[0202] Optionally, the antenna configuration of the UE includes, but is not limited to, the number of ports.

[0203] In some embodiments, the network-side conditions may include: cell type, network deployment scenario, wireless channel quality, cell frequency, cell location, distance between base stations, antenna configuration, transmit power, and at least one of subcarrier spacing (Numerology).

[0204] Optionally, the cell type may include macro cell (Macro), micro cell (Micro), dense urban cell (dense urban), etc., but is not limited thereto.

[0205] Optionally, network deployment scenarios include indoor and outdoor.

[0206] Optionally, the wireless channel quality may be determined by any one of RSRP (Reference Signal Received Power), RSRQ (Reference Signal Received Quality), and SINR (Signal to Interference plus Noise Ratio).

[0207] Optionally, the antenna configuration may include the number of ports and the number of MIMO (Multiple-Input Multiple-Output) layers.

[0208] In some embodiments, the change in the second application condition includes:

[0209] The second application condition changes from being satisfied to not being satisfied; or

[0210] The second application condition changes from not being satisfied to being satisfied.

[0211] Exemplarily, assuming that the second application condition is a condition on the UE side, for example, the battery level is 60%, then the change in the second application condition may include: the UE's battery level changes from less than 60% (for example, 20%) to 60% and above, or from 60% to less than 60% (for example, 59%).

[0212] For example, if the battery level of the UE changes from 20% to 60%, or from 60% to 59%, data is collected and stored.

[0213] In some embodiments, the second application condition includes an application condition corresponding to the currently running AI model.

[0214] Optionally, there is a corresponding relationship between the AI ​​model and the application conditions, which can also be understood as: there is a binding relationship or mapping relationship between the AI ​​model and the application conditions.

[0215] Optionally, the AI ​​model can be bound to at least one application condition.

[0216] Exemplarily, the application conditions bound to AI model 1 include the UE's speed, power, operating power, location, and service type, as well as at least one of the network deployment scenario, wireless channel quality, and the frequency of the cell.

[0217] Optionally, data is collected and stored when the application conditions bound to the AI ​​model change.

[0218] In some embodiments, when there are multiple application conditions bound to the AI ​​model, if at least one of the multiple application conditions changes, the UE is triggered to collect data.

[0219] Optionally, when one of the multiple application conditions bound to the AI ​​model changes, the UE is triggered to collect data.

[0220] Optionally, when multiple application conditions bound to the AI ​​model change, the UE is triggered to collect data.

[0221] S202. The terminal 101 stores at least one of the first application condition and the application scenario when collecting data.

[0222] In some embodiments, the terminal may store the first application condition when collecting data.

[0223] In some embodiments, the first application condition may include at least one of a condition related to the network device and a condition related to the terminal.

[0224] Optionally, the conditions related to the network device may also be described as network-side conditions; and the conditions related to the terminal may also be described as UE-side conditions.

[0225] Optionally, the specific contents of the conditions on the network side and the conditions on the UE side can refer to the relevant description in the above S201 and will not be repeated here.

[0226] In some embodiments, the terminal may store the application scenario when collecting data.

[0227] In some embodiments, the application scenario includes at least one of the following:

[0228] Beam management;

[0229] Channel state information compression;

[0230] Positioning of the terminal;

[0231] Terminal switching;

[0232] Terminal mobility management.

[0233] Optionally, the terminal may store application conditions and / or application scenarios when collecting the data while collecting and storing the data based on the first condition.

[0234] For example, if the first condition is that data is collected and stored when the UE's battery level changes from 20% to 60%, or from 60% to 59%, then the application condition when collecting the data is: the UE's battery level is 60%. While collecting and storing the data, the terminal may store the application condition that the UE's battery level is 60%.

[0235] Optionally, in this embodiment, the above step S202 can be omitted.

[0236] In some embodiments, before step S202, the method may further include:

[0237] S204 , the network device 102 sends a first message to the terminal 101 .

[0238] In some embodiments, the first message carries first indication information for indicating conditions related to the network device when the terminal collects data.

[0239] In some embodiments, step S202 may include:

[0240] The terminal stores the conditions related to the network device when collecting data based on the first indication information.

[0241] Optionally, the first message may be a system message or a radio resource control (Radio Resource Control, RRC) reconfiguration message.

[0242] In some embodiments, if the first message is an RRC reconfiguration message, the message also carries second indication information for indicating an application scenario when the terminal collects data.

[0243] In some embodiments, step S202 may include:

[0244] The terminal stores the application scenario when collecting data based on the second indication information.

[0245] Exemplarily, the second indication information indicates that the application scenario when the terminal collects data is the terminal's positioning. Then, when the terminal collects and stores data based on the first condition, the application scenario corresponding to the data may be stored as the terminal's positioning.

[0246] In some embodiments, the names of information, etc. are not limited to the names described in the embodiments, and terms such as "information", "message", "signal", "signaling", "report", "configuration", "indication", "instruction", "command", "channel", "parameter", "domain", "field", "symbol", and "data" can be used interchangeably.

[0247] In some embodiments, terms such as "send", "transmit", "report", "download", "transmit", "bidirectional transmission", "send and / or receive" can be used interchangeably.

[0248] S203 , the terminal 101 reports the stored data to the network device 102 .

[0249] In some embodiments, the terminal may periodically report stored data to the network device.

[0250] In some embodiments, the period for reporting data by the terminal may be pre-configured or obtained from a protocol, which is not limited in the embodiments of the present application.

[0251] In some embodiments, before step S203, the method may further include:

[0252] S205 . The terminal 101 receives the second message sent by the network device 102 .

[0253] In some embodiments, the second message carries third indication information for instructing the terminal to report the stored data.

[0254] In some embodiments, the above step S203 may include:

[0255] The terminal reports the stored data to the network device based on the third indication information.

[0256] Optionally, when the terminal receives the third indication information sent by the network side, the stored data is reported to the terminal.

[0257] In some embodiments, the third indication information may further include application conditions and / or application scenarios corresponding to the data that needs to be reported by the terminal.

[0258] Optionally, the network side may instruct the terminal to report data of specific application conditions and / or specific application scenarios.

[0259] Exemplarily, the network side instructs the terminal to report data corresponding to application scenario 1. Then, the terminal reports data 1 to the network side according to the instruction. The application scenario when collecting data 1 is application scenario 1.

[0260] In some embodiments, after step S203, the method may further include:

[0261] S206 . Terminal 101 sends a third message to network device 102 .

[0262] In some embodiments, the third message carries fourth indication information for indicating at least one of the first application condition and the application scenario corresponding to the data.

[0263] Optionally, when reporting data to the network device, the terminal may also send an indication to the network device of application conditions and / or application scenarios corresponding to the reported data.

[0264] For example, if the terminal reports data 1, 2, and 3 to the network side, it can also report application condition 1 corresponding to data 1, application condition 2 and application scenario 1 corresponding to data 2, and application scenario 2 corresponding to data 3 to the network side.

[0265] In some embodiments, terms such as "certain", "preset", "preset", "setting", "indicated", "a certain", "any", and "first" can be interchangeable. "Specific A", "preset A", "preset A", "setting A", "indicated A", "a certain A", "any A", and "first A" can be interpreted as A pre-specified in a protocol, etc., or as A obtained through setting, configuration, or indication, etc., or as specific A, a certain A, any A, or first A, etc., but not limited to this.

[0266] In some embodiments, terms such as "in the case of", "at the time of", "when", "if", and "if" can be used interchangeably.

[0267] The method involved in the embodiments of the present disclosure may include at least one of steps S201 to S206. For example, step S201 can be implemented as an independent embodiment, steps S201 and S203 can be implemented as independent embodiments, steps S201, S202, and S203 can be implemented as independent embodiments, steps S201, S202, S203, and S204 can be implemented as independent embodiments, steps S201, S202, S203, and S206 can be implemented as independent embodiments, and steps S201, S202, S203, S205, and S206 can be implemented as independent embodiments, but are not limited thereto.

[0268] In some embodiments, step S202 is optional, and one or more of these steps may be omitted or replaced in different embodiments.

[0269] In some embodiments, step S204 is optional, and one or more of these steps may be omitted or replaced in different embodiments.

[0270] In some embodiments, step S205 is optional, and one or more of these steps may be omitted or replaced in different embodiments.

[0271] In some embodiments, step S206 is optional, and one or more of these steps may be omitted or replaced in different embodiments.

[0272] FIG3a is a flow chart of a data processing method according to an embodiment of the present disclosure. As shown in FIG3a , the data processing method can be executed by the terminal 101, and the method includes:

[0273] S301. According to a first condition, determine to collect and store data.

[0274] The optional implementation of step S301 can refer to the optional implementation of step S201 in Figure 2 and other related parts in the embodiment involved in Figure 2, which will not be repeated here.

[0275] In some embodiments, the data is used for training or performance monitoring of AI models.

[0276] In some embodiments, the first condition may include that the performance of the currently activated AI model satisfies the second condition.

[0277] In some embodiments, the first condition may include a change in the second application condition.

[0278] S302: Report the stored data to the network device.

[0279] The optional implementation of step S302 can refer to the optional implementation of step S203 in FIG. 2 and other related parts in the embodiment involved in FIG. 2 , which will not be described in detail here.

[0280] The method involved in the embodiment of the present disclosure may include at least one of steps S301 to S302. For example, step S301 may be implemented as an independent embodiment, but is not limited thereto.

[0281] In some embodiments, step S302 is optional, and one or more of these steps may be omitted or replaced in different embodiments.

[0282] FIG3b is a flow chart of a communication method according to an embodiment of the present disclosure. As shown in FIG3b , the communication method can be executed by the terminal 101, and the method includes:

[0283] S311. According to the first condition, determine to collect and store data.

[0284] The optional implementation of step S311 can refer to the optional implementation of step S201 in Figure 2 and other related parts in the embodiment involved in Figure 2, which will not be repeated here.

[0285] S312: Store at least one of the first application condition and the application scenario when collecting data.

[0286] In some embodiments, the first application condition may include at least one of a condition related to the network device and a condition related to the terminal.

[0287] In some embodiments, the application scenario includes at least one of the following:

[0288] Beam management;

[0289] Channel state information compression;

[0290] Positioning of the terminal;

[0291] Terminal switching;

[0292] Terminal mobility management.

[0293] The optional implementation of step S312 can refer to the optional implementation of step S202 in Figure 2 and other related parts in the embodiment involved in Figure 2, which will not be repeated here.

[0294] In some embodiments, before step S312, the following steps may also be included:

[0295] S310 (not shown in the figure): obtain the first message.

[0296] In some embodiments, the first message sent by the network device may be received, and the first message sent by other devices may also be received.

[0297] The optional implementation of step S310 can refer to the optional implementation of step S204 in FIG2 and other related parts in the embodiment involved in FIG2 , which will not be described in detail here.

[0298] In some embodiments, the first message carries first indication information for indicating conditions related to the network device when the terminal collects data.

[0299] In some embodiments, step S312 may include: storing, based on the first indication information, conditions related to the network device when collecting data.

[0300] Optionally, the first message may be a system message or an RRC reconfiguration message.

[0301] In some embodiments, if the first message is an RRC reconfiguration message, the message also carries second indication information for indicating an application scenario when the terminal collects data.

[0302] In some embodiments, step S312 may include: storing the application scenario when collecting data based on the second indication information.

[0303] Exemplarily, the second indication information indicates that the application scenario when the terminal collects data is terminal positioning. Then, when the terminal collects and stores data based on the first condition, the application scenario corresponding to the data may be stored as terminal positioning.

[0304] S313: Report the stored data and at least one of the first application condition and the application scenario to the network device.

[0305] The optional implementation of step S313 can refer to the optional implementation of steps S203 and S206 in Figure 2, and other related parts in the embodiment involved in Figure 2, which will not be repeated here.

[0306] The method involved in the embodiment of the present disclosure may include at least one of steps S311 to S313. For example, step S311 may be implemented as an independent embodiment, and steps S311 and S313 may be implemented as independent embodiments, but are not limited thereto.

[0307] In some embodiments, step S312 is optional, and one or more of these steps may be omitted or replaced in different embodiments.

[0308] FIG3c is a flow chart of a communication method according to an embodiment of the present disclosure. As shown in FIG3c, the communication method can be executed by the terminal 101, and the method includes:

[0309] S321. According to the first condition, determine to collect and store data.

[0310] Optional implementations of step S321 may refer to the optional implementations of step S201 in FIG. 2 , step S301 in FIG. 3 a , step S311 in FIG. 3 b , and other related parts in the embodiments involved in FIG. 2 and FIG. 3 a - 3 b , which will not be described in detail here.

[0311] In some embodiments, the method further includes: storing the first application condition when collecting the data.

[0312] In some embodiments, the method further includes: receiving first indication information sent by a network device, where the first indication information is used to indicate a condition related to the network device when the terminal collects the data.

[0313] In some embodiments, the method further includes: storing the application scenario when collecting the data.

[0314] In some embodiments, the application scenario includes at least one of the following:

[0315] Beam management;

[0316] Channel state information compression;

[0317] Positioning of the terminal;

[0318] Terminal switching;

[0319] Terminal mobility management.

[0320] In some embodiments, the method further includes: receiving second indication information sent by a network device, where the second indication information is used to indicate an application scenario when the terminal collects the data.

[0321] The optional implementation of the above optional embodiment can refer to the optional implementation of steps S202 and S204 in Figure 2, step S312 in Figure 3b, and other related parts in the embodiments involved in Figures 2 and 3b, which will not be repeated here.

[0322] In some embodiments, the first condition includes the performance of the currently activated AI model satisfying the second condition;

[0323] The performance of the AI ​​model meeting the second condition includes at least one of the following:

[0324] The accuracy of the AI ​​model output meets a first preset value;

[0325] The difference between the output value of the AI ​​model and the true value meets the second preset value.

[0326] In some embodiments, the first condition includes a change in the second application condition.

[0327] In some embodiments, the change in the second application condition includes:

[0328] The second application condition changes from being satisfied to not being satisfied; or

[0329] The second application condition changes from not being satisfied to being satisfied.

[0330] In some embodiments, the second application condition includes an application condition corresponding to the currently running AI model.

[0331] In some embodiments, the second application condition includes an application condition configured by the network device.

[0332] In some embodiments, the method further includes: reporting the stored data to a network device.

[0333] For the optional implementation of the above optional embodiment, reference may be made to the optional implementation of step S203 in FIG2 , step S302 in FIG3a , step S313 in FIG3b , and other related parts in the embodiments involved in FIG2 and FIG3a - 3b , which will not be described in detail here.

[0334] In some embodiments, reporting the stored data to the network device includes: periodically reporting the stored data to the network device.

[0335] In some embodiments, the method further comprises:

[0336] receiving third indication information sent by the network device, where the third indication information is used to instruct the terminal to report the stored data;

[0337] Then, reporting the stored data to the network device includes: reporting the stored data to the network device based on the third indication information.

[0338] The optional implementation of the above optional embodiment can refer to the optional implementation of step S205 in Figure 2, step S313 in Figure 3b, and other related parts in the embodiments involved in Figures 2 and 3b, which will not be repeated here.

[0339] In some embodiments, the method further includes: sending fourth indication information to the network device, where the fourth indication information is used to indicate at least one of the first application condition and the application scenario corresponding to the data.

[0340] The optional implementation of the above optional embodiment can refer to the optional implementation of step S206 in Figure 2 and other related parts of the embodiment involved in Figure 2, which will not be repeated here.

[0341] FIG4 is a flow chart of a communication method according to an embodiment of the present disclosure. As shown in FIG4 , the method according to the embodiment of the present disclosure is executed by the network device 102, and the method includes:

[0342] S401: Receive data reported by a terminal.

[0343] In some embodiments, data is collected and stored by the terminal based on the first condition.

[0344] The optional implementation of step S401 can refer to the optional implementation of step S203 in FIG. 2 and other related parts in the embodiment involved in FIG. 2 , which will not be described in detail here.

[0345] In some embodiments, receiving data reported by a terminal includes periodically receiving data reported by a terminal.

[0346] In some embodiments, the method further includes: sending third indication information to the terminal, the third indication information being used to instruct the terminal to report the stored data;

[0347] Receiving data reported by the terminal includes: receiving data reported by the terminal based on the third indication information.

[0348] The optional implementation of the above optional embodiment can refer to the optional implementation of step S205 in Figure 2, step S313 in Figure 3b, and other related parts in the embodiments involved in Figures 2 and 3b, which will not be repeated here.

[0349] In some embodiments, the method further includes: receiving fourth indication information sent by the terminal, where the fourth indication information is used to indicate at least one of a first application condition and an application scenario corresponding to the data.

[0350] In some embodiments, the first application condition is an application condition corresponding to when the data is collected by the terminal, and the application scenario is an application scenario corresponding to when the data is collected by the terminal.

[0351] The optional implementation of the above optional embodiment can refer to the optional implementation of step S206 in Figure 2 and other related parts of the embodiment involved in Figure 2, which will not be repeated here.

[0352] In some embodiments, the method further includes: sending first indication information to the terminal, where the first indication information is used to indicate a condition related to a network device when the terminal collects the data.

[0353] In some embodiments, the method further includes: sending second indication information to the terminal, where the second indication information is used to indicate an application scenario when the terminal collects the data.

[0354] The optional implementation of the above optional embodiment can refer to the optional implementation of steps S202 and S204 in Figure 2, step S312 in Figure 3b, and other related parts in the embodiments involved in Figures 2 and 3b, which will not be repeated here.

[0355] In some embodiments, the application scenario includes at least one of the following:

[0356] Beam management;

[0357] Channel state information compression;

[0358] Positioning of the terminal;

[0359] Terminal switching;

[0360] Terminal mobility management.

[0361] In some embodiments, the first condition includes the performance of the currently activated AI model meeting the second condition;

[0362] The performance of the AI ​​model meeting the second condition includes at least one of the following:

[0363] The accuracy of the AI ​​model output meets a first preset value;

[0364] The difference between the output value of the AI ​​model and the true value meets the second preset value.

[0365] In some embodiments, the first condition includes a change in the second application condition.

[0366] In some embodiments, the change in the second application condition includes:

[0367] The second application condition changes from being satisfied to not being satisfied; or

[0368] The second application condition changes from not being satisfied to being satisfied.

[0369] In some embodiments, the second application condition includes an application condition corresponding to the currently running AI model.

[0370] In some embodiments, the second application condition includes an application condition configured by the network device.

[0371] FIG5 is a flow chart of a communication method according to an embodiment of the present disclosure. As shown in FIG5 , the method according to the embodiment of the present disclosure is used in a communication system 100, and the method includes:

[0372] S501. The terminal determines to collect and store data according to a first condition.

[0373] Optional implementations of step S501 may refer to the optional implementations of step S203 in FIG. 2 , step S301 in FIG. 3a , step S311 in FIG. 3b , and step S321 in FIG. 3c , as well as other related parts in the embodiments involved in FIG. 2 and FIG. 3a to 3c , which will not be described in detail here.

[0374] S502: The network device receives data reported by the terminal.

[0375] The optional implementation of step S502 can refer to the optional implementation of step S203 in Figure 2, step S302 in Figure 3a, step S313 in Figure 3b, step S401 in Figure 4, and other related parts in the embodiments involved in Figures 2, 3a~3b, and 4, which will not be repeated here.

[0376] In some embodiments, the above method may include the method described in the above embodiments of the communication system side, terminal side, network equipment side, core network equipment side, etc., which will not be repeated here.

[0377] The present disclosure also provides an optional implementation scheme, in which the UE in the connected state collects and stores data when the first condition is met.

[0378] Optionally, the data can be used for AI model training.

[0379] In some embodiments, the UE stores the application conditions when collecting data.

[0380] Optionally, the application conditions include network side conditions and / or UE side conditions.

[0381] In some embodiments, the UE receives first indication information sent by the network side, where the first indication information is used to indicate a current network side condition.

[0382] Optionally, the first indication information may be carried via system information or an RRC reconfiguration message.

[0383] Optionally, the UE may store an application condition for collecting data based on the first indication information, where the application condition is a current network side condition.

[0384] In some embodiments, the UE stores the application scenario when collecting data (which may correspond to the first application condition mentioned above).

[0385] Optionally, the application scenarios may include beam management, CSI compression, positioning, switching, mobility management, etc.

[0386] Optionally, the application scenario of the collected data is indicated by the network side.

[0387] Optionally, the network side may carry second indication information through an RRC reconfiguration message, where the second indication information is used to indicate an application scenario when the UE collects data.

[0388] In some embodiments, the first condition may include that the performance of the currently activated AI model satisfies the second condition.

[0389] Optionally, the performance of the AI ​​model can be determined by whether the accuracy of the output meets a certain threshold condition. For example, the accuracy of the AI ​​model output is less than a threshold value (which may correspond to the first preset value mentioned above).

[0390] Optionally, the performance of the AI ​​model can be determined by comparing the output with the true value. For example, the difference between the output value of the AI ​​model and the true value is greater than a preset value (which may correspond to the second preset value mentioned above).

[0391] In some embodiments, the first condition may be an application condition (which may correspond to the second application condition mentioned above) that changes, and the application condition may be a network side condition or a UE side condition.

[0392] As an embodiment, the application condition may change from being satisfied to being not satisfied, or from being not satisfied to being satisfied.

[0393] As an embodiment, the application condition may be an application condition bound to a currently running AI model.

[0394] As an embodiment, the application condition may be an application condition configured by a network.

[0395] In some embodiments, the UE reports the stored data to the network side.

[0396] In some embodiments, the UE may also indicate application conditions and / or application scenarios corresponding to the stored data.

[0397] Optionally, the UE may send fourth indication information to the network side, where the fourth indication information is used to indicate application conditions and / or application scenarios corresponding to the data.

[0398] In some embodiments, the reporting of the data may be triggered periodically or based on receiving a reporting indication sent by the network side.

[0399] Optionally, the UE may receive third indication information sent by the network side, where the third indication information is used to instruct the UE to report stored data.

[0400] The embodiments of the present disclosure further provide an apparatus for implementing any of the above methods. For example, an apparatus is provided, comprising units or modules for implementing each step performed by a terminal in any of the above methods. For another example, another apparatus is provided, comprising units or modules for implementing each step performed by a network device (e.g., an access network device, a core network function node, a core network device, etc.) in any of the above methods.

[0401] It should be understood that the division of the various units or modules in the above device is merely a division of logical functions. In actual implementation, they may be fully or partially integrated into a physical entity, or they may be physically separated. In addition, the units or modules in the device may be implemented in the form of a processor calling software: for example, the device includes a processor, the processor is connected to a memory, and the memory stores instructions. The processor calls the instructions stored in the memory to implement any of the above methods or implement the functions of the various units or modules of the above device, wherein the processor is, for example, a general-purpose processor, such as a central processing unit (CPU) or a microprocessor, and the memory is a memory within the device or a memory outside the device. Alternatively, the units or modules in the device can be implemented in the form of hardware circuits, and the functions of some or all of the units or modules can be realized by designing the hardware circuits. The above-mentioned hardware circuits can be understood as one or more processors; for example, in one implementation, the above-mentioned hardware circuit is an application-specific integrated circuit (ASIC), and the functions of some or all of the above units or modules are realized by designing the logical relationship of the elements in the circuit; for example, in another implementation, the above-mentioned hardware circuit can be implemented by a programmable logic device (PLD), taking a field programmable gate array (FPGA) as an example, which can include a large number of logic gate circuits, and the connection relationship between the logic gate circuits is configured by a configuration file, thereby realizing the functions of some or all of the above units or modules.

[0402] All units or modules of the above devices can be implemented in the form of software called by the processor, or in the form of hardware circuits, or partially implemented in the form of software called by the processor, and the remaining part implemented in the form of hardware circuits. In the embodiment of the present disclosure, the processor is a circuit with signal processing capabilities. In one implementation, the processor can be a circuit with instruction reading and execution capabilities, such as a central processing unit (CPU), a microprocessor, a graphics processing unit (GPU) (which can be understood as a microprocessor), or a digital signal processor (DSP); in another implementation, the processor can implement certain functions through the logical relationship of the hardware circuit. The logical relationship of the above hardware circuit is fixed or reconfigurable, such as a hardware circuit implemented by a processor as an application-specific integrated circuit (ASIC) or a programmable logic device (PLD), such as an FPGA. In a reconfigurable hardware circuit, the process of the processor loading a configuration document to implement the hardware circuit configuration can be understood as the process of the processor loading instructions to implement the functions of some or all of the above units or modules. In addition, it can also be a hardware circuit designed for artificial intelligence, which can be understood as ASIC, such as a neural network processing unit (NPU), a tensor processing unit (TPU), a deep learning processing unit (DPU), etc.

[0403] FIG6 a is a schematic diagram of the structure of a terminal proposed in an embodiment of the present disclosure. As shown in FIG6 a , the terminal may include at least one of: a first transceiver module 611 , a first processing module 612 , and the like.

[0404] In some embodiments, the first processing module 612 is configured to determine to collect data and store the data according to a first condition.

[0405] Optionally, the first transceiver module 611 is used to execute steps related to signaling performed by the terminal 101 in any of the above methods, for example, at least one of steps S204, S205, and S206 shown in FIG2 , which will not be repeated here.

[0406] Optionally, the first transceiver module 611 is further configured to execute steps related to communication performed by the terminal 101 in any of the above methods, such as step S203 shown in FIG. 2 , which will not be described in detail here.

[0407] Optionally, the first processing module 612 is used to execute the storage-related steps executed by the terminal 101 in any of the above methods, for example, step S202 shown in FIG. 2 , which will not be repeated here.

[0408] FIG6 b is a schematic diagram of the structure of a network device according to an embodiment of the present disclosure. As shown in FIG6 b , the network device includes at least one of a second transceiver module 621 and a second processing module 622 .

[0409] In some embodiments, the second transceiver module 621 is used to receive data reported by the terminal, and the data is collected and stored by the terminal based on the first condition.

[0410] Optionally, the second transceiver module 621 is used to execute steps related to signaling performed by the network device 102 in any of the above methods, for example, at least one of steps S204, S205, and S206 shown in FIG2 , which will not be repeated here.

[0411] Optionally, the second transceiver module 621 is further configured to execute steps related to communication performed by the network device 102 in any of the above methods, such as step S203 shown in FIG. 2 , which will not be described in detail here.

[0412] Figure 7a is a schematic diagram of the structure of a communication device 7100 proposed in an embodiment of the present disclosure. Communication device 7100 can be a network device (e.g., an access network device, a core network device, etc.), a terminal (e.g., a user equipment, etc.), a chip, a chip system, or a processor that supports a network device to implement any of the above methods, or a chip, a chip system, or a processor that supports a terminal to implement any of the above methods. Communication device 7100 can be used to implement the methods described in the above method embodiments. For details, please refer to the description of the above method embodiments.

[0413] As shown in Figure 7a, the communication device 7100 includes one or more processors 7101. The processor 7101 can be a general-purpose processor or a dedicated processor, for example, a baseband processor or a central processing unit. The baseband processor can be used to process communication protocols and communication data, and the central processing unit can be used to control the communication device (such as a base station, baseband chip, terminal device, terminal device chip, DU or CU, etc.), execute programs, and process program data. The processor 7101 is used to call instructions to enable the communication device 7100 to perform any of the above methods.

[0414] In some embodiments, the communication device 7100 further includes one or more transceivers 7103. When the communication device 7100 includes one or more transceivers 7103, the transceiver 7103 performs at least one of the communication steps such as sending and / or receiving in the above method (for example, at least one of steps S203, S204, S205, and S206 shown in FIG2 , but not limited thereto), and the processor 7101 performs at least one of the other steps (for example, at least one of steps S201 and S202 shown in FIG2 , but not limited thereto). In an optional embodiment, the transceiver may include a receiver and / or a transmitter, and the receiver and transmitter may be separate or integrated. Optionally, the terms transceiver, transceiver unit, transceiver, transceiver circuit, interface circuit, and interface may be interchangeable, the terms transmitter, transmitting unit, transmitter, and transmitting circuit may be interchangeable, and the terms receiver, receiving unit, receiver, and receiving circuit may be interchangeable.

[0415] In some embodiments, the communication device 7100 further includes one or more memories 7102 for storing instructions. Optionally, all or part of the memories 7102 may be located outside the communication device 7100.

[0416] In some embodiments, the communication device 7100 further includes one or more transceivers 7103. When the communication device 7100 includes one or more transceivers 7103, the communication steps such as sending and receiving in the above method are performed by the transceiver 7103, and the other steps are performed by the processor 7101.

[0417] In some embodiments, a transceiver may include a receiver and a transmitter, which may be separate or integrated. Optionally, the terms transceiver, transceiver unit, transceiver, and transceiver circuit may be used interchangeably; the terms transmitter, transmitting unit, transmitter, and transmitting circuit may be used interchangeably; and the terms receiver, receiving unit, receiver, and receiving circuit may be used interchangeably.

[0418] Optionally, the communication device 7100 further includes one or more interface circuits 7104, which are connected to the memory 7102. The interface circuits 7104 may be configured to receive signals from the memory 7102 or other devices, and may be configured to send signals to the memory 7102 or other devices. For example, the interface circuits 7104 may read instructions stored in the memory 7102 and send the instructions to the processor 7101.

[0419] The communication device 7100 described in the above embodiment may be a network device or a terminal, but the scope of the communication device 7100 described in the embodiment of the present disclosure is not limited thereto, and the structure of the communication device 7100 may not be limited by FIG. 7a. The communication device may be an independent device or may be part of a larger device. For example, the communication device may be: 1) an independent integrated circuit IC, or a chip, or a chip system or subsystem; (2) a collection of one or more ICs, optionally, the above IC collection may also include a storage component for storing data or programs; (3) an ASIC, such as a modem; (4) a module that can be embedded in other devices; (5) a receiver, a terminal device, an intelligent terminal device, a cellular phone, a wireless device, a handheld device, a mobile unit, an in-vehicle device, a network device, a cloud device, an artificial intelligence device, etc.; (6) others, etc.

[0420] FIG7 b is a schematic diagram of the structure of a chip 7200 according to an embodiment of the present disclosure. If the communication device 7100 can be a chip or a chip system, reference can be made to the schematic diagram of the structure of the chip 7200 shown in FIG7 b , but the present disclosure is not limited thereto.

[0421] The chip 7200 includes one or more processors 7201. The chip 7200 is configured to execute any of the above methods.

[0422] In some embodiments, chip 7200 further includes one or more interface circuits 7202. Optionally, terms such as interface circuit, interface, and transceiver pins may be used interchangeably. In some embodiments, chip 7200 further includes one or more memories 7203 for storing data. Optionally, all or part of memory 7203 may be located outside chip 7200. Optionally, interface circuit 7202 is connected to memory 7203 and may be used to receive data from memory 7203 or other devices, or may be used to send data to memory 7203 or other devices. For example, interface circuit 7202 may read data stored in memory 7203 and send the data to processor 7201.

[0423] In some embodiments, the interface circuit 7202 performs at least one of the communication steps such as sending and / or receiving in the above method (for example, at least one of steps S203, S204, S205, and S206 shown in FIG2 , but not limited thereto). The interface circuit 7202 performing the communication steps such as sending and / or receiving in the above method, for example, means that the interface circuit 7202 performs data exchange between the processor 7201, the chip 7200, the memory 7203, or the transceiver device. In some embodiments, the processor 7201 performs at least one of the other steps (for example, at least one of steps S201 and S202 shown in FIG2 , but not limited thereto).

[0424] The present disclosure also provides a program product, which, when executed by the communication device 7100, enables the communication device 7100 to perform any of the above methods. Optionally, the program product is a computer program product.

[0425] The present disclosure also proposes a computer program, which, when executed on a computer, causes the computer to perform any one of the above methods.

[0426] The technical solutions described in the embodiments of the present disclosure can be arbitrarily combined without conflict.

[0427] Other embodiments of the present invention will readily occur to those skilled in the art after considering the specification and practicing the invention disclosed herein. This disclosure is intended to cover any variations, uses, or adaptations of the invention that follow from the general principles of the invention and include common knowledge or customary techniques in the art not disclosed herein. The description and examples are to be considered as exemplary only, with the true scope and spirit of the invention being indicated by the following claims.

[0428] It should be understood that the present invention is not limited to the exact construction described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present invention is limited only by the appended claims.

Claims

1. A data processing method, characterized in that, The method is executed by a terminal, and the method includes: Determine to collect data and store the data according to a first condition.

2. The method according to claim 1, wherein The method further includes: Store a first application condition when the data is collected.

3. The method according to claim 2, wherein The method further includes: Receive first indication information sent by a network device, where the first indication information is used to indicate a condition related to the network device when the terminal collects the data.

4. The method according to any one of claims 1 to 3, characterized in that The method further includes: Store an application scenario when the data is collected.

5. The method according to claim 4, wherein The application scenario includes at least one of the following: Beam management; Channel state information compression; Positioning of the terminal; Handover of the terminal; Mobility management of the terminal.

6. The method according to claim 4, characterized in that The method further includes: Receive second indication information sent by the network device, where the second indication information is used to indicate the application scenario when the terminal collects the data.

7. The method according to any one of claims 1-6, characterized in that, The first condition includes that the performance of the currently activated AI model meets a second condition; Wherein, the performance of the AI model meeting the second condition includes at least one of the following: The accuracy rate of the output of the AI model meets a first preset value; The difference between the output value and the true value of the AI model meets a second preset value.

8. The method according to any one of claims 1-6, characterized in that, The first condition includes that a second application condition changes.

9. The method according to claim 8, wherein The change of the second application condition includes: The second application condition changes from being satisfied to not being satisfied; or, The second application condition changes from not being satisfied to being satisfied.

10. The method according to claim 8 or 9, characterized in that, The second application condition includes an application condition corresponding to the currently running AI model.

11. The method according to claim 8 or 9, characterized in that, The second application condition includes an application condition configured by the network device.

12. The method according to any one of claims 1-11, characterized in that, The method further includes: Report the stored data to the network device.

13. The method according to claim 12, characterized in that, The reporting the stored data to the network device includes: Periodically report the stored data to the network device.

14. The method according to claim 12, characterized in that, The method further includes: Receive third indication information sent by the network device, where the third indication information is used to indicate that the terminal reports the stored data; The reporting the stored data to the network device includes: Based on the third indication information, report the stored data to the network device.

15. The method according to any one of claims 12 - 14, characterized in that, The method further includes: Send fourth indication information to the network device, where the fourth indication information is used to indicate at least one of the first application condition and the application scenario corresponding to the data.

16. A data processing method, characterized in that, The method is executed by a network device, and the method includes: Receive data reported by a terminal, where the data is collected and stored by the terminal based on a first condition.

17. The method according to claim 16, wherein The receiving the data reported by the terminal includes: Periodically receive the data reported by the terminal.

18. The method according to claim 16, wherein The method further includes: Send third indication information to the terminal, where the third indication information is used to indicate that the terminal reports the stored data; The receiving the data reported by the terminal includes: Receive the data reported by the terminal based on the third indication information.

19. The method according to any one of claims 16 - 18, wherein, The method further includes: Receive fourth indication information sent by the terminal, where the fourth indication information is used to indicate at least one of the first application condition and the application scenario corresponding to the data; The first application condition is the application condition corresponding to when the data is collected by the terminal, and the application scenario is the application scenario corresponding to when the data is collected by the terminal.

20. The method according to claim 19, wherein The method further includes: Send first indication information to the terminal, where the first indication information is used to indicate conditions related to a network device when the terminal collects the data.

21. The method according to claim 19, wherein The method further includes: Send second indication information to the terminal, where the second indication information is used to indicate an application scenario when the terminal collects the data.

22. The method according to claim 19 or 21, characterized in that, The application scenario includes at least one of the following: Beam management; Channel state information compression; Positioning of the terminal; Handover of the terminal; Mobility management of the terminal.

23. The method according to any one of claims 16-22, characterized in that, The first condition includes that the performance of the currently activated AI model meets a second condition; Wherein, the performance of the AI model meeting the second condition includes at least one of the following: The accuracy rate of the output of the AI model meets a first preset value; The difference between the output value and the true value of the AI model meets a second preset value.

24. The method according to any one of claims 16 - 22, characterized in that, The first condition includes that a second application condition changes.

25. The method according to claim 24, wherein The change of the second application condition includes: The second application condition changes from being met to not being met; or, The second application condition changes from not being met to being met.

26. The method according to claim 24 or 25, characterized in that, The second application condition includes application conditions corresponding to the currently running AI model.

27. The method according to claim 24 or 25, characterized in that, The second application condition includes application conditions configured by the network device.

28. A terminal, characterized in that, Includes: A first processing module, configured to determine to collect and store the data according to the first condition.

29. A network device, characterized in that, Includes: A second transceiver module, configured to receive data reported by the terminal, where the data is collected and stored by the terminal based on the first condition.

30. A terminal, characterized in that, Includes: One or more processors; Wherein, the terminal is configured to execute the data processing method according to any one of claims 1 to 15.

31. A network device, characterized in that, Includes: One or more processors; Wherein, the network device is configured to execute the data processing method according to any one of claims 16 to 27.

32. A communication system, characterized in that, Includes: A terminal and a network device, wherein the terminal is configured to implement the method according to any one of claims 1 to 15, and the network device is configured to implement the method according to any one of claims 16 to 27.

33. A computer-readable storage medium, characterized in that, An executable instruction is stored in the computer-readable storage medium, and the executable instruction is loaded and executed by a processor to implement the method according to any one of claims 1 to 15, or claims 16 to 27.

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