Model monitoring method and apparatus, and storage medium

Abstract

The present disclosure relates to a model monitoring method and apparatus, and a storage medium, the method comprising: performing prediction on a first reference signal on the basis of a first model, and obtaining a prediction result, the first reference signal being used for instructing to monitor the first model; and sending the prediction result to a server, the server being used for monitoring the first model on the basis of the prediction result. In the described embodiment, after performing prediction on the basis of the first reference signal, a terminal sends the prediction result to the server, and subsequently the server can monitor the first model of the terminal on the basis of the prediction result, ensuring that the accuracy of the first model of the terminal meets requirements, and thus ensuring the accuracy and reliability of communication performed by the terminal on the basis of the first model.

Description

Model monitoring method, device and storage medium Technical Field

[0001] The present disclosure relates to the field of communication technologies, and in particular to a model monitoring method, device, and storage medium. Background Art

[0002] With the rapid development of mobile communication technology, artificial intelligence (AI)-based parameter prediction has been added to the technology. Specifically, a model can be configured on a terminal to predict terminal or network device parameters, allowing the terminal to obtain these parameters in advance. However, the accuracy of the model may decrease during use, resulting in inaccurate data prediction.

[0003] Summary of the Invention

[0004] The solution provided by the present disclosure solves the problem that the accuracy of the terminal model may be reduced, ensuring that the terminal model can be monitored, thereby ensuring the accuracy of the first model of the terminal, and further ensuring the reliability of communication between the terminal and the network device.

[0005] The embodiments of the present disclosure provide a model monitoring method, device, and storage medium.

[0006] According to a first aspect of an embodiment of the present disclosure, a model monitoring method is proposed, the method being executed by a terminal, the method comprising:

[0007] Predicting a first reference signal based on a first model to obtain a prediction result, wherein the first reference signal is used to instruct a server to monitor the first model;

[0008] The prediction result is sent to the server.

[0009] According to a second aspect of an embodiment of the present disclosure, a model monitoring method is proposed, the method being executed by a server, the method comprising:

[0010] receiving a prediction result sent by a terminal, where the prediction result is obtained by the terminal predicting a first reference signal based on a first model, and the first reference signal is used to instruct the server to monitor the first model;

[0011] The first model is monitored based on the prediction result.

[0012] According to a third aspect of an embodiment of the present disclosure, a model monitoring method is proposed, the method being executed by an access network device, the method comprising:

[0013] A first reference signal is sent to the terminal, where the first reference signal is used to instruct the server to monitor the first model, wherein the first reference signal includes at least one of SSB (PSS / SSS PBCH Block), CSI-RS (Channel State Information-Reference Signal), or PRS (Positioning Reference Signal).

[0014] According to a fourth aspect of an embodiment of the present disclosure, a model monitoring method is proposed, the method comprising:

[0015] The access network device sends a first reference signal to the terminal, where the first reference signal is used to instruct the server to monitor the first model;

[0016] The terminal predicts the first reference signal based on the first model to obtain a prediction result;

[0017] The terminal sends the prediction result to the server;

[0018] The server receives the prediction result sent by the terminal;

[0019] The server monitors the first model based on the prediction result.

[0020] According to a fifth aspect of an embodiment of the present disclosure, a model monitoring device is provided, comprising:

[0021] a processing module, configured to predict a first reference signal based on a first model to obtain a prediction result, wherein the first reference signal is used to instruct a server to monitor the first model;

[0022] The transceiver module is used to send the prediction result to the server.

[0023] According to a sixth aspect of the embodiments of the present disclosure, a model monitoring device is provided, comprising:

[0024] a transceiver module, configured to receive a prediction result sent by a terminal, where the prediction result is obtained by the terminal predicting a first reference signal based on a first model, and the first reference signal is used to instruct a server to monitor the first model;

[0025] A processing module is used to monitor the first model based on the prediction result.

[0026] According to a seventh aspect of the embodiments of the present disclosure, a model monitoring device is provided, comprising:

[0027] A transceiver module is used to send a first reference signal to the terminal, where the first reference signal is used to instruct the server to monitor the first model, wherein the first reference signal includes at least one of SSB, CSI-RS or PRS.

[0028] According to an eighth aspect of the embodiments of the present disclosure, a model monitoring device is provided, comprising:

[0029] one or more processors;

[0030] Wherein, the model monitoring device is used to execute any one of the methods described in the first aspect.

[0031] According to a ninth aspect of the embodiments of the present disclosure, a model monitoring device is provided, comprising:

[0032] one or more processors;

[0033] Wherein, the model monitoring device is used to execute any method described in the second aspect.

[0034] According to a tenth aspect of an embodiment of the present disclosure, a model monitoring device is provided, comprising:

[0035] one or more processors;

[0036] Wherein, the model monitoring device is used to execute any method described in the third aspect.

[0037] According to an eleventh aspect of the present disclosure, a communication system is provided, including:

[0038] A terminal, an access network device and a server, wherein the terminal is configured to implement the model monitoring method described in the first aspect, the server is configured to implement the model monitoring method described in the third aspect, and the access network device is configured to implement the model monitoring method described in the third aspect.

[0039] According to a ninth aspect of an embodiment of the present disclosure, a storage medium is proposed, wherein the storage medium stores instructions. When the instructions are executed on a communication device, the communication device executes a method as described in any one of the first aspect or the second aspect. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] The drawings described herein are used to provide a further understanding of the embodiments of the present disclosure and constitute a part of the present disclosure. The illustrative embodiments of the embodiments of the present disclosure and their descriptions are used to explain the embodiments of the present disclosure and do not constitute an improper limitation on the embodiments of the present disclosure. In the drawings:

[0041] FIG1 is a schematic diagram of the architecture of a communication system according to an embodiment of the present disclosure;

[0042] FIG2 is an interactive schematic diagram of a model monitoring method according to an embodiment of the present disclosure;

[0043] FIG3A is a flow chart of a model monitoring method according to an embodiment of the present disclosure;

[0044] FIG3B is a flow chart of a model monitoring method according to an embodiment of the present disclosure;

[0045] FIG4A is a flow chart illustrating a model monitoring method according to an embodiment of the present disclosure;

[0046] FIG4B is a flow chart of a model monitoring method according to an embodiment of the present disclosure;

[0047] FIG5A is a flow chart illustrating a model monitoring method according to an embodiment of the present disclosure;

[0048] FIG5B is a flow chart of a model monitoring method according to an embodiment of the present disclosure;

[0049] FIG6 is a flow chart of a model monitoring method according to an embodiment of the present disclosure;

[0050] FIG7A is a schematic structural diagram of a model monitoring device proposed in an embodiment of the present disclosure;

[0051] FIG7B is a schematic structural diagram of a model monitoring device proposed in an embodiment of the present disclosure;

[0052] FIG7C is a schematic structural diagram of a model monitoring device proposed in an embodiment of the present disclosure;

[0053] FIG8A is a schematic structural diagram of a communication device proposed in an embodiment of the present disclosure;

[0054] FIG8B is a schematic diagram of the structure of the chip proposed in an embodiment of the present disclosure. DETAILED DESCRIPTION

[0055] The present disclosure provides a model monitoring method, device, and storage medium.

[0056] According to a first aspect of an embodiment of the present disclosure, a model monitoring method is proposed, the method being executed by a terminal, the method comprising:

[0057] Predicting a first reference signal based on a first model to obtain a prediction result, wherein the first reference signal is used to instruct a server to monitor the first model;

[0058] The prediction result is sent to a server, and the server is configured to monitor the first model based on the prediction result.

[0059] In the above embodiment, the terminal performs prediction based on the first reference signal and sends the prediction result to the server. The server can then monitor the first model of the terminal based on the prediction result to ensure that the accuracy of the first model of the terminal meets the requirements, thereby ensuring the accuracy and reliability of the terminal's communication based on the first model.

[0060] In conjunction with some embodiments of the first aspect, in some embodiments, the method further includes:

[0061] Receive the first reference signal sent by the access network device, wherein the first reference signal includes at least one of SSB, CSI-RS or PRS.

[0062] In the above embodiment, the access network device sends the first reference signal to the terminal to ensure that the terminal can predict the first reference signal based on the first model to obtain a prediction result, and then detect the first model based on the prediction result to ensure the accuracy of monitoring the first model.

[0063] In combination with some embodiments of the first aspect, in some embodiments, the first reference signal includes a PRS, and the parameters of the PRS include at least one of a PRS SCS (sub-carrier space), a PRS BW (Bandwidth), a comb size, and a PRS period; or,

[0064] The first reference signal includes an SSB, and a parameter of the SSB includes at least one of a PSS (Primary Synchronization Signal) index and an SSS (Secondary Synchronization Signals) index.

[0065] In the above embodiment, the types of the first reference signal are expanded to ensure the accuracy of the first reference signal.

[0066] In combination with some embodiments of the first aspect, in some embodiments, the access network device includes access network devices corresponding to the current serving cell and the neighboring cell.

[0067] In conjunction with some embodiments of the first aspect, in some embodiments, the method further includes:

[0068] The training result is sent to the server, where the training result is used by the server to train the second model to obtain the first model.

[0069] In the above embodiment, the terminal sends the training result to the server to ensure that the server can train the model to obtain the first model, thereby ensuring the accuracy of the obtained first model.

[0070] In conjunction with some embodiments of the first aspect, in some embodiments, the method further includes:

[0071] Receive the first model sent by the server.

[0072] In the above embodiment, the terminal may perform prediction after receiving the first model, thereby ensuring the accuracy of the prediction result based on the first model.

[0073] In conjunction with some embodiments of the first aspect, in some embodiments, the method further includes:

[0074] receiving a second reference signal sent by an access network device, where the second reference signal is used by the terminal for measurement;

[0075] Sending a measurement result of the second reference signal to the access network device.

[0076] In the above embodiment, the terminal may measure the reference signal and then feed back the measurement result to the access network device to ensure the reliability of communication between the terminal and the access network device.

[0077] In a second aspect, an embodiment of the present disclosure provides a model monitoring method, which is executed by a server and includes:

[0078] receiving a prediction result sent by a terminal, where the prediction result is obtained by the terminal predicting a first reference signal based on a first model, and the first reference signal is used to instruct the server to monitor the first model;

[0079] The first model is monitored based on the prediction result.

[0080] In conjunction with some embodiments of the second aspect, in some embodiments, the method further includes:

[0081] The first reference signal is sent to an access network device, where the access network device is used to send the first reference signal to the terminal; wherein the first reference signal includes at least one of SSB, CSI-RS or PRS.

[0082] In combination with some embodiments of the second aspect, in some embodiments, the first reference signal includes a PRS, and the parameters of the PRS include at least one of a PRS SCS, a PRS BW, a comb size, and a PRS period; or,

[0083] The first reference signal includes an SSB, and a parameter of the SSB includes at least one of a PSS index and an SSS index.

[0084] In combination with some embodiments of the second aspect, in some embodiments, the access network device is an access network device corresponding to a neighboring cell.

[0085] In conjunction with some embodiments of the second aspect, in some embodiments, the method further includes:

[0086] receiving a training result sent by the terminal;

[0087] The second model is trained based on the training result to obtain the first model.

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

[0089] Sending the first model to the terminal.

[0090] In conjunction with some embodiments of the second aspect, in some embodiments, monitoring the first model based on the prediction result includes:

[0091] The first model is monitored based on the prediction result and a reference result corresponding to the first reference signal.

[0092] In conjunction with some embodiments of the second aspect, in some embodiments, monitoring the first model based on the prediction result and a reference result corresponding to the first reference signal includes:

[0093] The difference between the predicted result and the reference result is less than a difference threshold, and the first model is determined to be qualified;

[0094] or,

[0095] If the difference between the predicted result and the reference result is not less than the difference threshold, it is determined that the first model is unqualified.

[0096] In a third aspect, an embodiment of the present disclosure provides a model monitoring method, which is performed by an access network device and includes:

[0097] A first reference signal is sent to the terminal, where the first reference signal is used to instruct the server to monitor the first model; wherein the first reference signal includes at least one of SSB, CSI-RS, or PRS.

[0098] In combination with some embodiments of the third aspect, in some embodiments, the first reference signal includes a PRS, and the parameters of the PRS include at least one of a PRS SCS, a PRS BW, a comb size, and a PRS period; or,

[0099] The first reference signal includes an SSB, and a parameter of the SSB includes at least one of a PSS index and an SSS index.

[0100] In combination with some embodiments of the third aspect, in some embodiments, the access network device is an access network device corresponding to a neighboring cell.

[0101] In conjunction with some embodiments of the third aspect, in some embodiments, the method further includes:

[0102] sending a second reference signal to the terminal, where the second reference signal is used by the terminal to perform measurement;

[0103] receiving a measurement result of the second reference signal sent by the terminal.

[0104] In a fourth aspect, an embodiment of the present disclosure provides a model monitoring method, the method comprising:

[0105] The access network device sends a first reference signal to the terminal, where the first reference signal is used to instruct the server to monitor the first model;

[0106] The terminal predicts the first reference signal based on the first model to obtain a prediction result;

[0107] The terminal sends the prediction result to the server;

[0108] The server receives the prediction result sent by the terminal;

[0109] The server monitors the first model based on the prediction result.

[0110] In a fifth aspect, an embodiment of the present disclosure provides a model monitoring device, which includes at least one of a transceiver module and a processing module; wherein the terminal is used to execute the optional implementation method of the first aspect.

[0111] In a sixth aspect, an embodiment of the present disclosure provides a model monitoring device, which includes at least one of a transceiver module and a processing module; wherein the terminal is used to execute the optional implementation method of the second aspect.

[0112] In a seventh aspect, an embodiment of the present disclosure provides a model monitoring device, which includes at least one of a transceiver module and a processing module; wherein the terminal is used to execute the optional implementation method of the second aspect.

[0113] In an eighth aspect, an embodiment of the present disclosure provides a model monitoring device, comprising:

[0114] one or more processors;

[0115] The model monitoring device is used to execute the method described in any one of the first aspects.

[0116] In a ninth aspect, an embodiment of the present disclosure provides a model monitoring device, comprising:

[0117] one or more processors;

[0118] The model monitoring device is used to execute the method described in any one of the second aspects.

[0119] In a tenth aspect, an embodiment of the present disclosure provides a model monitoring device, comprising:

[0120] one or more processors;

[0121] The model monitoring device is used to execute the method described in any one of the third aspects.

[0122] In the eleventh aspect, an embodiment of the present disclosure provides a storage medium storing first information, which enables the communication device to execute a method as described in any one of the first aspect, the second aspect or the third aspect when the first information is run on the communication device.

[0123] In a twelfth 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 any one of the methods described in the first aspect, the second aspect, or the third aspect.

[0124] In a thirteenth aspect, an embodiment of the present disclosure proposes a computer program, which, when executed on a communication device, enables the communication device to execute any one of the methods described in the first aspect, the second aspect, or the third aspect.

[0125] In a fourteenth aspect, an embodiment of the present disclosure provides a chip or a chip system, wherein the chip or chip system includes a processing circuit configured to execute any one of the methods described in the first aspect, the second aspect, or the third aspect.

[0126] It is understandable that the above-mentioned terminals, storage media, program products, computer programs, chips or chip systems are all used to execute the methods 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.

[0127] The present disclosure provides a model monitoring method, device, and storage medium. In some embodiments, the terms "model monitoring method," "information model monitoring method," and "model monitoring method" are interchangeable; the terms "model monitoring device," "information model monitoring device," and "model monitoring device" are interchangeable; and the terms "information processing system," "communication system," and "information processing 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 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 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," "one or more," "a plurality of," "multiple," etc. may be used interchangeably.

[0134] In some embodiments, descriptions such as "at least one of A and B," "A and / or B," "A in one case, B in another case," or "in response to one case A, in response to another case B" may include the following technical solutions depending on the situation: in some embodiments, A (A is executed independently of B); in some embodiments, B (B is executed independently of A); in some embodiments, execution is selected from A and B (A and B are selectively executed); and in some embodiments, A and B (both A and B are executed). The above is also applicable when there are more branches such as A, B, and C.

[0135] In some embodiments, "A or B" and other descriptions may include the following technical solutions depending on the situation: in some embodiments, A (A is executed independently of B); in some embodiments, B (B is executed independently of A); in some embodiments, execution is selected from A and B (A and B are selectively executed). The above is also applicable when there are more branches such as A, B, C, etc.

[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 information" and the "second information" 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 "time / frequency" and "time / frequency domain" refer to the time domain and / or the frequency domain.

[0139] 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.

[0140] 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.

[0141] In some embodiments, devices and equipment can be interpreted as physical or virtual, and their names are not limited to the names recorded in the embodiments. In some cases, they can also be understood as "equipment", "device", "circuit", "network element", "node", "function", "unit", "section", "system", "network", "chip", "chip system", "entity", "subject", etc.

[0142] In some embodiments, "network" can be interpreted as devices included in the network, such as access network equipment, core network equipment, etc.

[0143] In some embodiments, "access network device (AN device)" may also be referred to as "radio access network device (RAN device)", "base station (BS)", "radio base station", "fixed station", and in some embodiments may also be understood as "node", "access point", "transmission point (TP)", "reception point (RP)", "transmission and / or reception point (TRP)" "panel", "antenna panel", "antenna array", "cell", "macro cell", "small cell", "femto cell", "pico cell", "sector", "cell group", "serving cell", "carrier", "component carrier", "bandwidth part (BWP)", etc.

[0144] In some embodiments, "terminal" or "terminal device" may be referred to as "user equipment (terminal)", "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.

[0145] In some embodiments, obtaining data, information, etc. may comply with the laws and regulations of the country where the data is obtained.

[0146] In some embodiments, data, information, etc. may be obtained with the user's consent.

[0147] In addition, each element, each row, or each column in the table of the embodiment of the present disclosure can be implemented as an independent embodiment, and the combination of any elements, any rows, and any columns can also be implemented as an independent embodiment.

[0148] FIG1 is a schematic diagram of the architecture of a communication system according to an embodiment of the present disclosure. As shown in FIG1 , the method provided in the embodiment of the present disclosure can be applied to a communication system 100, which may include a terminal 101 and a network device 102. It should be noted that the communication system 100 may also include other devices, and the present disclosure does not limit the devices included in the communication system 100.

[0149] 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.

[0150] In some embodiments, the network device 102 may include at least one of an access network device, a core network device, and a server.

[0151] In some embodiments, the access network device is, for example, a node or device that connects a terminal to a wireless network. The access network device may include an evolved NodeB (eNB), a next generation eNB (ng-eNB), a next generation NodeB (gNB), a node B (NB), a home node B (HNB), a home evolved node B (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 RAN, a cloud RAN, a base station in other communication systems, or at least one of an access node in a Wi-Fi system, but is not limited thereto. In some embodiments, the access network device may include an access network device of a serving cell and an access network device of a neighboring cell.

[0152] In some embodiments, the server can be understood as a device for artificial intelligence. In some embodiments, the server can train a model based on data so that the trained model has the ability to predict parameters of a terminal or network device. In some embodiments, the server is a device other than an access network device and a core network device. Alternatively, the server can be understood as a cloud network device. This is not limited in the embodiments of the present disclosure. In some embodiments, the server can communicate with the terminal through the access network device. Alternatively, the server can communicate directly with the terminal.

[0153] In some embodiments, the technical solution of the present disclosure can be applied to the Open RAN architecture. In this case, the interfaces between or within the access network devices involved in the embodiments of the present disclosure can be transformed into internal interfaces of the Open RAN, and the processes and information interactions between these internal interfaces can be implemented through software or programs.

[0154] 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 access 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.

[0155] 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).

[0156] 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.

[0157] The following embodiments of the present disclosure may be applied to the communication system 100 shown in FIG1 , or a portion thereof, but are not limited thereto. The entities shown in FIG1 are illustrative only. The communication system may include all or part of the entities shown in FIG1 , or may include other entities outside of FIG1 . The number and form of the entities are arbitrary, and the entities may be physical or virtual. The connection relationships between the entities are illustrative only. The entities may be connected or disconnected, and the connection may be in any manner, including direct or indirect, wired or wireless.

[0158] The embodiments of the present disclosure can 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), systems using other model monitoring methods, and next-generation systems based on these. Furthermore, multiple systems may be combined (for example, a combination of LTE or LTE-A with 5G).

[0159] FIG2 is an interactive diagram of a model monitoring method according to an embodiment of the present disclosure. As shown in FIG2 , the embodiment of the present disclosure relates to a model monitoring method, which includes:

[0160] Step S2101: The terminal sends the training result to the server.

[0161] In some embodiments, the server receives the training result sent by the terminal. In some embodiments, the terminal sends the training result. In some embodiments, the server receives the training result.

[0162] In some embodiments, the training results are used by the server to train the second model to obtain the first model. In some embodiments, the second model is an untrained model, or a trained but incomplete model. In some embodiments, the first model is used to make predictions based on the terminal's measurement results to obtain predicted measurement results. In some embodiments, the first model is an AI model used to make predictions on data.

[0163] In some embodiments, the training result can be understood as a measurement result obtained by the terminal measuring the channel / reference signal, and the obtained measurement result can be used to train the model. In some embodiments, the training result can be multiple measurement results obtained by the terminal measuring the channel / reference signal multiple times.

[0164] In some embodiments, the name of the training result is not limited, and it can be, for example, training data, data used to train a model, measurement results, etc.

[0165] Step S2102: The server trains the second model based on the training result to obtain the first model.

[0166] In embodiments of the present disclosure, after receiving the training results, the server can train the second model based on the training results to obtain the first model. In some embodiments, the server inputs the training data into the second model, processes the training results based on the second model, and adjusts the parameters of the second model based on the obtained differences to complete the training and obtain the first model.

[0167] In some embodiments, the second model is a neural network model, a convolutional model, or other types of models, which is not limited in the embodiments of the present disclosure.

[0168] Step S2103: The server sends the first model to the terminal.

[0169] In an embodiment of the present disclosure, after the server completes training of the first model, the first model can be sent to the terminal, and the terminal can subsequently perform data prediction based on the first model.

[0170] In some embodiments, the terminal receives the first model sent by the server. In some embodiments, the server sends the first model. In some embodiments, the terminal receives the first model.

[0171] In some embodiments, the server and the terminal may communicate via an access network device. Alternatively, the server and the terminal may communicate directly. Optionally, if the server and the terminal communicate via an access network device, the server may send a first model to the access network device. After receiving the first model, the access network device may forward the first model to the terminal, and the terminal may then receive the first model.

[0172] Step S2104: The first access network device sends a second reference signal to the terminal.

[0173] In some embodiments, the terminal receives a second reference signal sent by the first access network device. In some embodiments, the first access network device sends the second reference signal. In some embodiments, the terminal receives the second reference signal.

[0174] In some embodiments, the second reference signal is used for measurement by the terminal. In some embodiments, the second reference signal is a reference signal transmitted over a channel between the terminal and the first access network device, and the second reference signal indicates the quality of the channel between the terminal and the first access network device.

[0175] In some embodiments, the second reference signal is used for channel estimation or channel detection of the channel, which is not limited in the embodiments of the present disclosure.

[0176] In some embodiments, the second reference signal may include at least one of SSB, CSI-RS, and PRS, which is not limited in the embodiments of the present disclosure.

[0177] Step S2105: The terminal measures the second reference signal to obtain a measurement result.

[0178] In some embodiments, the terminal measures the second reference signal based on the first model to obtain a measurement result. In the embodiments of the present disclosure, the terminal measuring the second reference signal refers to the terminal detecting the signal quality of the second reference signal, or can also be understood as detecting the quality of the second reference signal.

[0179] Step S2106: The terminal sends the measurement result to the first access network device.

[0180] In some embodiments, the first access network device receives the measurement result sent by the terminal. In some embodiments, the terminal sends the measurement result. In some embodiments, the first access network device receives the measurement result.

[0181] In the embodiment of the present disclosure, after measuring the second reference signal sent by the first access network device, the terminal sends the obtained measurement result to the first access network device, ensuring that the first access network device can receive the measurement result.

[0182] In some embodiments, the terminal further sends the measurement result to the access network device, which stores the measurement result. Optionally, the access network device includes a LMF network element, that is, the terminal further sends the measurement result to the LMF network element, which stores the measurement result.

[0183] Step S2107: The server sends a first reference signal to the first access network device.

[0184] In some embodiments, the first access network device receives a first reference signal sent by a server. In some embodiments, the server sends the first reference signal. In some embodiments, the server receives the first reference signal.

[0185] In some embodiments, the server monitors the first model to determine whether the accuracy of the first model meets the requirements. In some embodiments, the server is configured to update the first model if the accuracy of the first model does not meet the requirements. In some embodiments, the server is configured to update the first model of the terminal to ensure that the accuracy of the updated first model meets the requirements.

[0186] In some embodiments, the server sends indication information to the first access network device, where the indication information is used to indicate parameters of the first reference signal. The first access network device can then determine the corresponding first reference signal based on the indication information, and then send the first reference signal to the first access network device.

[0187] In some embodiments, the indication information includes a reference signal identifier, which indicates the corresponding first reference signal. Optionally, the reference signal identifier and the reference signal parameters are in a one-to-one correspondence. Therefore, the corresponding reference signal parameters can be determined based on the reference signal identifier, and the access network device subsequently transmits the reference signal according to the reference signal parameters.

[0188] In some embodiments, the first reference signal includes at least one of an SSB, a CSI-RS, or a PRS. In some embodiments, the type of the first reference signal is not limited, and the server can define the type of reference signal to be sent according to needs.

[0189] For example, if there is a positioning requirement, the server may indicate a PRS to the first access network device. For example, if there is a synchronization requirement, the server may indicate an SSB to the first access network device. It should be noted that the embodiments of the present disclosure are merely examples and are not intended to limit the present disclosure.

[0190] In some embodiments, the first reference signal includes a PRS, and the parameters of the PRS include at least one of a PRS SCS, a PRS BW, a comb size, and a PRS period. In an embodiment of the present disclosure, if the first reference signal is a PRS, the first access network device may send the PRS based on the PRS parameters. In some embodiments, the first access network device stores a correspondence between a PRS identifier and a PRS parameter, and the server can indicate the corresponding PRS parameter by indicating the PRS identifier. For example, PRS identifier 1 corresponds to PRS parameter 1, PRS identifier 2 corresponds to PRS parameter 2, and PRS identifier 3 corresponds to PRS parameter 3.

[0191] For example, see Table 1, which shows the correspondence between PRS identifiers and PRS parameters.

[0192] Table 1

[0193] In some embodiments, the first reference signal includes an SSB, and the parameters of the SSB include at least one of a PSS index or an SSS index. In an embodiment of the present disclosure, if the first reference signal is an SSB, the first access network device may send the SSB based on the parameters of the SSB. In some embodiments, the first access network device stores a correspondence between an SSB identifier and an SSB parameter, and the server can indicate the corresponding SSB parameter by indicating the SSB identifier. For example, SSB identifier 1 corresponds to SSB parameter 1, SSB identifier 2 corresponds to SSB parameter 2, and SSB identifier 3 corresponds to SSB parameter 3.

[0194] For example, see Table 2, which shows the correspondence between SSB identifiers and SSB parameters.

[0195] Table 2

[0196] Step S2108: The first access network device sends a first reference signal to the terminal.

[0197] In some embodiments, the terminal receives a first reference signal sent by a first access network device. In some embodiments, the first access network device sends the first reference signal. In some embodiments, the terminal receives the first reference signal.

[0198] In some embodiments, the access network device includes access network devices corresponding to the current serving cell and the neighboring cell. In some embodiments, the first access network device is an access network device corresponding to the neighboring cell.

[0199] It should be noted that the embodiments of the present disclosure also include a second access network device, which refers to the access network device corresponding to the current serving cell. In some embodiments, the second access network device transmits a third reference signal to the terminal, and the terminal measures the third reference signal to obtain a measurement result. In some embodiments, the terminal transmits the measurement result to the second access network device. In some embodiments, the access network device is the access network device corresponding to the neighboring cell.

[0200] Step S2109: The terminal predicts the first reference signal based on the first model to obtain a prediction result.

[0201] In some embodiments, the first reference signal is used to indicate monitoring of the first model.

[0202] In some embodiments, after receiving the first reference signal, the terminal may predict the first reference signal based on the first model to obtain a prediction result. In some embodiments, the terminal inputs the first reference signal into the first model, processes the first reference signal based on the first model, and obtains a prediction result.

[0203] Step S21010: The terminal sends the prediction result to the server.

[0204] In some embodiments, the server receives the prediction result sent by the terminal. In some embodiments, the terminal sends the prediction result. In some embodiments, the server receives the prediction result.

[0205] In some embodiments, the terminal sends the prediction result to the first access network device. After receiving the prediction result, the first access network device forwards the prediction result to the server, and the server can receive the prediction result.

[0206] Step S21011: The server monitors the first model based on the prediction result.

[0207] In the embodiment of the present disclosure, after the server receives the prediction result, since the prediction result is predicted by the first model, the server can determine the accuracy of the first model's prediction based on the prediction result, ensuring that the first model can be monitored based on the prediction result.

[0208] In some embodiments, the first model is monitored based on the predicted result and a reference result corresponding to the first reference signal. In some embodiments, the reference result corresponding to the first reference signal is a standard reference result corresponding to the first reference signal. That is, if the predicted result is similar to or identical to the reference result, it can be determined that the accuracy of the first model meets the requirements; if the predicted result is different from the reference result, it can be determined that the accuracy of the first model does not meet the requirements.

[0209] In some embodiments, monitoring the first model based on the predicted result and a reference result corresponding to the first reference signal includes determining that the first model is qualified if a difference between the predicted result and the reference result is less than a difference threshold. In some embodiments, the difference threshold is specified by a communication protocol or configured by a server, and is not limited in the present disclosure.

[0210] In some embodiments, monitoring the first model based on the prediction result and a reference result corresponding to the first reference signal includes: if a difference between the prediction result and the reference result is not less than a difference threshold, determining that the first model is unqualified.

[0211] It should be noted that the above embodiment uses the difference between the predicted result and the reference result and the difference threshold as an example for explanation. In another embodiment, the similarity between the predicted result and the reference result can also be calculated. If the similarity is greater than the similarity threshold, it means that the first model is qualified. If the similarity is not greater than the similarity threshold, it means that the first model is unqualified.

[0212] In some embodiments, if the server determines that the first model is unqualified, the server will update the first model of the terminal to ensure that the accuracy of the first model meets the requirements.

[0213] It should be noted that at least one of the predicted results or reference results is a range, not a specific value.

[0214] 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", "symbol", "codeword", "codebook", "codeword", "codepoint", "bit", "data", "program", and "chip" can be used interchangeably.

[0215] 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.

[0216] In some embodiments, "obtain", "get", "get", "receive", "transmit", "bidirectional transmission", "send and / or receive" can be interchangeable, and can be interpreted as receiving from other entities, obtaining from protocols, obtaining from higher layers, obtaining by self-processing, autonomous implementation, etc.

[0217] In some embodiments, terms such as "send", "transmit", "report", "download", "transmit", "bidirectional transmission", "send and / or receive" can be used interchangeably.

[0218] In some embodiments, terms such as "moment", "time point", "time", and "time position" can be replaced with each other, and terms such as "duration", "period", "time window", "window", and "time" can be replaced with each other.

[0219] In some embodiments, terms such as "certain", "preset", "preset", "setting", "indicated", "some", "any", and "first" can be interchangeable. "Specific A", "preset A", "preset A", "setting A", "indicated A", "some 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, some A, any A, or first A, etc., but not limited to this.

[0220] The model monitoring method involved in the embodiments of the present disclosure may include at least one of steps S2101 to S21011. For example, step S2101 can be implemented as an independent embodiment, step S2102 can be implemented as an independent embodiment, step S2103 can be implemented as an independent embodiment, step S2104 can be implemented as an independent embodiment, step S2105 can be implemented as an independent embodiment, step S2106 can be implemented as an independent embodiment, step S2107 can be implemented as an independent embodiment, step S2108 can be implemented as an independent embodiment, step S2109 can be implemented as an independent embodiment, step S21010 can be implemented as an independent embodiment, step S21011 can be implemented as an independent embodiment, steps S2101-S2103 can be implemented as independent embodiments, steps S2104-S2106 can be implemented as independent embodiments, and steps S2107-S21011 can be implemented as independent embodiments, but the present invention is not limited thereto.

[0221] In some embodiments, step S2101 is optional, and one or more of these steps may be omitted or replaced in different embodiments.

[0222] In some embodiments, step S2102 is optional, and one or more of these steps may be omitted or replaced in different embodiments.

[0223] In some embodiments, step S2103 is optional, and one or more of these steps may be omitted or replaced in different embodiments.

[0224] In some embodiments, step S2104 is optional, and one or more of these steps may be omitted or replaced in different embodiments.

[0225] In some embodiments, step S2105 is optional, and one or more of these steps may be omitted or replaced in different embodiments.

[0226] In some embodiments, step S2106 is optional, and one or more of these steps may be omitted or replaced in different embodiments.

[0227] In some embodiments, step S2107 is optional, and one or more of these steps may be omitted or replaced in different embodiments.

[0228] In some embodiments, step S2108 is optional, and one or more of these steps may be omitted or replaced in different embodiments.

[0229] In some embodiments, step S2109 is optional, and one or more of these steps may be omitted or replaced in different embodiments.

[0230] In some embodiments, step S21010 is optional, and one or more of these steps may be omitted or replaced in different embodiments.

[0231] In some embodiments, step S21011 is optional, and one or more of these steps may be omitted or replaced in different embodiments.

[0232] In some embodiments, step S2101 and step S2102 are optional, and one or more of these steps may be omitted or replaced in different embodiments.

[0233] In some embodiments, step S2101 and step S2103 are optional, and one or more of these steps may be omitted or replaced in different embodiments.

[0234] In some embodiments, step S2101 and step S2104 are optional, and one or more of these steps may be omitted or replaced in different embodiments.

[0235] In some embodiments, step S2102 and step S2103 are optional, and one or more of these steps may be omitted or replaced in different embodiments.

[0236] In some embodiments, step S2102 and step S2104 are optional, and one or more of these steps may be omitted or replaced in different embodiments.

[0237] In some embodiments, step S2103 and step S2104 are optional, and one or more of these steps may be omitted or replaced in different embodiments.

[0238] In some embodiments, reference may be made to other optional implementations described before or after the description corresponding to FIG. 2 .

[0239] FIG3A is a flow chart of a model monitoring method according to an embodiment of the present disclosure, which is applied to a terminal. As shown in FIG3A , the embodiment of the present disclosure relates to a model monitoring method, which includes:

[0240] Step S3101: The terminal sends the training results to the server.

[0241] The optional implementation of step S3101 can refer to the optional implementation of step S2101 in Figure 2 and other related parts in the embodiment involved in Figure 2, which will not be repeated here.

[0242] Step S3102: The terminal measures the second reference signal to obtain a measurement result.

[0243] The optional implementation of step S3102 can refer to the optional implementation of step S2105 in Figure 2 and other related parts in the embodiment involved in Figure 2, which will not be repeated here.

[0244] Step S3103: The terminal sends the measurement result to the first access network device.

[0245] The optional implementation of step S3103 can refer to the optional implementation of step S2106 in Figure 2 and other related parts in the embodiment involved in Figure 2, which will not be repeated here.

[0246] Step S3104: The terminal predicts the first reference signal based on the first model to obtain a prediction result.

[0247] The optional implementation of step S3104 can refer to the optional implementation of step S2109 in Figure 2 and other related parts in the embodiment involved in Figure 2, which will not be repeated here.

[0248] Step S3105: The terminal sends the prediction result to the server.

[0249] The optional implementation of step S3105 can refer to the optional implementation of step S21010 in Figure 2 and other related parts in the embodiment involved in Figure 2, which will not be repeated here.

[0250] The model monitoring method involved in the embodiments of the present disclosure may include at least one of steps S3101 to S3105. For example, step S3101 may be implemented as an independent embodiment, step S3102 may be implemented as an independent embodiment, step S3103 may be implemented as an independent embodiment, step S3104 may be implemented as an independent embodiment, and step S3105 may be implemented as an independent embodiment.

[0251] FIG3B is a flow chart of a model monitoring method according to an embodiment of the present disclosure, which is applied to a terminal. As shown in FIG3B , the embodiment of the present disclosure relates to a model monitoring method, which includes:

[0252] Step S3201: The terminal predicts a first reference signal based on a first model to obtain a prediction result.

[0253] In some embodiments, the first reference signal is used to indicate monitoring of the first model.

[0254] The optional implementation of step S3201 can refer to the optional implementation of step S2106 in Figure 2, step S3104 in Figure 3A, and other related parts in the embodiments involved in Figures 2 and 3A, which will not be repeated here.

[0255] Step S3202: The terminal sends the prediction result to the server, and the server is used to monitor the first model based on the prediction result.

[0256] The optional implementation of step S3202 can refer to the optional implementation of step S2109 in Figure 2, step S3105 in Figure 3A, and other related parts in the embodiments involved in Figures 2 and 3A, which will not be repeated here.

[0257] FIG4A is a flow chart of a model monitoring method according to an embodiment of the present disclosure, which is applied to a server. As shown in FIG4A , the embodiment of the present disclosure relates to a model monitoring method, which includes:

[0258] Step S4101: The server trains the second model based on the training results to obtain the first model.

[0259] The optional implementation of step S4101 can be found in step S2102 of FIG. 2 and other related parts of the embodiment involved in FIG. 2 , which will not be described in detail here.

[0260] Step S4102: The server sends the first model to the terminal.

[0261] The optional implementation of step S4102 can be found in step S2103 of FIG. 2 and other related parts of the embodiment involved in FIG. 2 , which will not be described in detail here.

[0262] Step S4103: The server sends a first reference signal to the first access network device.

[0263] The optional implementation of step S4103 can be found in step S2107 of FIG. 2 and other related parts of the embodiment involved in FIG. 2 , which will not be described in detail here.

[0264] Step S4104: The server monitors the first model based on the prediction result.

[0265] The optional implementation of step S4104 can be found in step S21011 of FIG. 2 and other related parts of the embodiment involved in FIG. 2 , which will not be described in detail here.

[0266] The model monitoring method involved in the embodiments of the present disclosure may include at least one of steps S4101 to S4104. For example, step S4101 may be implemented as an independent embodiment, step S4102 may be implemented as an independent embodiment, step S4103 may be implemented as an independent embodiment, and step S4104 may be implemented as an independent embodiment.

[0267] FIG4B is a flow chart of a model monitoring method according to an embodiment of the present disclosure, which is applied to a server. As shown in FIG4B , the embodiment of the present disclosure relates to a model monitoring method, which includes:

[0268] Step S4201: The server receives the prediction result sent by the terminal.

[0269] In some embodiments, the prediction result is obtained by the terminal predicting a first reference signal based on a first model, and the first reference signal is used to indicate monitoring of the first model.

[0270] The optional implementation of step S4201 can be found in step S2107 of FIG. 2 and other related parts of the embodiment involved in FIG. 2 , which will not be described in detail here.

[0271] Step S4202: The server monitors the first model based on the prediction result.

[0272] The optional implementation of step S4202 can be found in step S21011 of FIG. 2 and other related parts of the embodiment involved in FIG. 2 , which will not be described in detail here.

[0273] FIG5A is a flow chart of a model monitoring method according to an embodiment of the present disclosure, which is applied to a first access network device. As shown in FIG5A , the embodiment of the present disclosure relates to a model monitoring method, which includes:

[0274] Step S5101: The first access network device sends a second reference signal to the terminal.

[0275] The optional implementation of step S5101 can be found in step S2104 of FIG. 2 and other related parts of the embodiment involved in FIG. 2 , which will not be described in detail here.

[0276] Step S5102: The first access network device sends a first reference signal to the terminal.

[0277] The optional implementation of step S5102 can be found in step S2108 of FIG. 2 and other related parts of the embodiment involved in FIG. 2 , which will not be described in detail here.

[0278] The model monitoring method involved in the embodiment of the present disclosure may include at least one of steps S5101 and S5102. For example, step S5101 may be implemented as an independent embodiment, and step S5102 may be implemented as an independent embodiment.

[0279] FIG5B is a flow chart of a model monitoring method according to an embodiment of the present disclosure, which is applied to a server. As shown in FIG4B , the embodiment of the present disclosure relates to a model monitoring method, which includes:

[0280] Step S5201: A first access network device sends a first reference signal to a terminal.

[0281] The optional implementation of step S5201 can be found in step S2108 of FIG. 2 and other related parts of the embodiment involved in FIG. 2 , which will not be described in detail here.

[0282] FIG6 is a flow chart of a model monitoring method according to an embodiment of the present disclosure. As shown in FIG6 , the embodiment of the present disclosure relates to a model monitoring method, which includes:

[0283] Step S6101: The access network device sends a first reference signal to the terminal, where the first reference signal is used to instruct monitoring of a first model.

[0284] Optional implementations of step S6101 may refer to step S2108 in FIG. 2 , step S5102 in FIG. 5A , and other related parts in the embodiments involved in FIG. 2 and FIG. 5A , which will not be described in detail here.

[0285] Step S6102: The terminal predicts a first reference signal based on the first model to obtain a prediction result, where the first reference signal is used to indicate monitoring of the first model.

[0286] Optional implementations of step S6102 may refer to step S2109 in FIG. 2 , step S3104 in FIG. 3A , and other related parts in the embodiments involved in FIG. 2 and FIG. 3A , which will not be described in detail here.

[0287] Step S6103: The terminal sends the prediction result to the server, and the server is used to monitor the first model based on the prediction result.

[0288] Optional implementations of step S6103 may refer to step S21010 in FIG. 2 , step S4105 in FIG. 3A , and other related parts in the embodiments involved in FIG. 2 and FIG. 3A , which will not be described in detail here.

[0289] Step S6104: The server receives the prediction result sent by the terminal.

[0290] Optional implementations of step S6104 may refer to step S21010 in FIG. 2 , step S4105 in FIG. 3A , and other related parts in the embodiments involved in FIG. 2 and FIG. 4A , which will not be described in detail here.

[0291] Step S6105: The server monitors the first model based on the prediction result.

[0292] Optional implementations of step S6105 may refer to step S21011 in FIG. 2 , step S4104 in FIG. 4A , and other related parts in the embodiments involved in FIG. 2 and FIG. 4A , which will not be described in detail here.

[0293] In some embodiments, the above method may include the methods of the above embodiments of the communication system side, terminal side, network device side, etc., which will not be repeated here.

[0294] In the embodiments of the present disclosure, some or all of the steps and their optional implementations may be arbitrarily combined with some or all of the steps in other embodiments, or may be arbitrarily combined with the optional implementations of other embodiments.

[0295] 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.

[0296] 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), which realizes the functions of some or all of the above units or modules by designing the logical relationship of the components in the circuit; for example, in another implementation, the above-mentioned hardware circuit can be realized by a programmable logic device (PLD). Taking a field programmable gate array (FPGA) as an example, it can include a large number of logic gate circuits, and the connection relationship between the logic gate circuits is configured by configuring the configuration file, thereby realizing the functions of some or all of the above units or modules. All units or modules of the above devices can be realized in the form of software called by the processor, or in the form of hardware circuits, or in part by the form of software called by the processor, and the rest by hardware circuits.

[0297] In the embodiments 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-mentioned hardware circuit is fixed or reconfigurable. For example, the processor is a hardware circuit implemented by 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 and implementing 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 an ASIC, such as a neural network processing unit (NPU), a tensor processing unit (TPU), a deep learning processing unit (DPU), etc.

[0298] Figure 7A is a structural diagram of the model monitoring device proposed in an embodiment of the present disclosure. As shown in Figure 7A, the model monitoring device 7100 may include: at least one of a transceiver module 7101, a processing module 7102, etc. In some embodiments, the processing module 7102 is used to predict the first reference signal based on the first model to obtain a prediction result, and the first reference signal is used to indicate monitoring of the first model. The transceiver module 7101 is used to send the prediction result to the server, and the server is used to monitor the first model based on the prediction result. Optionally, the above-mentioned transceiver module 7101 is used to execute at least one of the communication steps such as sending and / or receiving executed by the terminal in any of the above methods (for example, step S2101 but not limited to this), which will not be repeated here. Optionally, the above-mentioned processing module is used to execute at least one of the other steps executed by the terminal in any of the above methods, which will not be repeated here.

[0299] Optionally, the processing module 7102 is used to execute at least one of the communication steps such as processing performed by the terminal in any of the above methods, which will not be repeated here.

[0300] Figure 7B is a structural diagram of the model monitoring device proposed in an embodiment of the present disclosure. As shown in Figure 7B, the model monitoring device 7200 may include: at least one of a transceiver module 7201, a processing module 7202, etc. In some embodiments, the transceiver module 7201 is used to receive a prediction result sent by a terminal, and the prediction result is obtained by the terminal predicting a first reference signal based on a first model, and the first reference signal is used to indicate monitoring of the first model. In some embodiments, the processing module 7202 is used to monitor the first model based on the prediction result. Optionally, the above-mentioned transceiver module is used to execute at least one of the communication steps such as sending and / or receiving (such as step S2102 but not limited thereto) executed by the network device in any of the above methods, which will not be repeated here.

[0301] Optionally, the processing module 7202 is used to execute at least one of the communication steps such as processing performed by the network device in any of the above methods, which will not be repeated here.

[0302] In some embodiments, the transceiver module may include a transmitting module and / or a receiving module, and the transmitting module and the receiving module may be separate or integrated. Optionally, the transceiver module may be interchangeable with the transceiver.

[0303] In some embodiments, the processing module can be a single module or can include multiple submodules. Optionally, the multiple submodules respectively execute all or part of the steps required to be executed by the processing module. Optionally, the processing module can be interchangeable with the processor.

[0304] Figure 7C is a schematic diagram of the structure of a model monitoring device proposed in an embodiment of the present disclosure. As shown in Figure 7C, model monitoring device 7300 may include at least one of: a transceiver module 7301, a processing module 7302, etc. In some embodiments, transceiver module 7301 is configured to send a first reference signal to a terminal, where the first reference signal is used to indicate monitoring of the first model. Optionally, the transceiver module is configured to perform at least one of the communication steps, such as sending and / or receiving, performed by the network device in any of the above methods, and will not be further described here.

[0305] Optionally, the processing module 7302 is used to execute at least one of the communication steps such as processing performed by the network device in any of the above methods, which will not be repeated here.

[0306] In some embodiments, the transceiver module may include a transmitting module and / or a receiving module, and the transmitting module and the receiving module may be separate or integrated. Optionally, the transceiver module may be interchangeable with the transceiver.

[0307] In some embodiments, the processing module can be a single module or can include multiple submodules. Optionally, the multiple submodules respectively execute all or part of the steps required to be executed by the processing module. Optionally, the processing module can be interchangeable with the processor.

[0308] Figure 8A is a schematic diagram of the structure of a communication device 8100 proposed in an embodiment of the present disclosure. Communication device 8100 can be a network device (e.g., an access network device, a core network device, etc.), a terminal, 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 8100 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.

[0309] As shown in FIG8A , the communication device 8100 includes one or more processors 8101. The processor 8101 may be a general-purpose processor or a dedicated processor, for example, a baseband processor or a central processing unit. The baseband processor may be used to process communication protocols and communication data, and the central processing unit may be used to control a model monitoring device (e.g., a base station, a baseband chip, a terminal, a terminal chip, a DU or a CU, etc.), execute programs, and process program data. The communication device 8100 is used to perform any of the above methods.

[0310] In some embodiments, the communication device 8100 further includes one or more memories 8102 for storing instructions. Optionally, all or part of the memories 8102 may be located outside the communication device 8100.

[0311] In some embodiments, the communication device 8100 further includes one or more transceivers 8103. When the communication device 8100 includes one or more transceivers 8103, the transceiver 8103 performs at least one of the communication steps such as sending and / or receiving in the above method (for example, step S2101, step S2102, step S2103, step S2104, but not limited thereto).

[0312] In some embodiments, a transceiver may include a receiver and / or a transmitter. The receiver and transmitter 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.

[0313] In some embodiments, the communication device 8100 may include one or more interface circuits 8104. Optionally, the interface circuit 8104 is connected to the memory 8102. The interface circuit 8104 may be configured to receive signals from the memory 8102 or other devices, and may be configured to send signals to the memory 8102 or other devices. For example, the interface circuit 8104 may read instructions stored in the memory 8102 and send the instructions to the processor 8101.

[0314] The communication device 8100 described in the above embodiment may be a network device or a terminal, but the scope of the communication device 8100 described in the present disclosure is not limited thereto, and the structure of the communication device 8100 may not be limited by FIG. 8A. 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, an intelligent terminal, 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.

[0315] FIG8B is a schematic diagram of the structure of a chip 8200 according to an embodiment of the present disclosure. If the communication device 8100 can be a chip or a chip system, please refer to the schematic diagram of the structure of the chip 8200 shown in FIG8B , but the present disclosure is not limited thereto.

[0316] The chip 8200 includes one or more processors 8201 , and the chip 8200 is configured to execute any of the above methods.

[0317] In some embodiments, the chip 8200 further includes one or more interface circuits 8202. Optionally, the interface circuit 8202 is connected to the memory 8203. The interface circuit 8202 can be used to receive signals from the memory 8203 or other devices, and can be used to send signals to the memory 8203 or other devices. For example, the interface circuit 8202 can read instructions stored in the memory 8203 and send the instructions to the processor 8201.

[0318] In some embodiments, the interface circuit 8202 performs at least one of the communication steps such as sending and / or receiving in the above method, and the processor 8201 performs at least one of the other steps.

[0319] In some embodiments, terms such as interface circuit, interface, transceiver pin, and transceiver may be used interchangeably.

[0320] In some embodiments, the chip 8200 further includes one or more memories 8203 for storing instructions. Alternatively, all or part of the memories 8203 may be outside the chip 8200.

[0321] The present disclosure also proposes a storage medium having instructions stored thereon, which, when executed on the communication device 8100, causes the communication device 8100 to execute any of the above methods. Optionally, the storage medium is an electronic storage medium. Optionally, the storage medium is a computer-readable storage medium, but is not limited thereto, and may also be a storage medium readable by other devices. Optionally, the storage medium may be a non-transitory storage medium, but is not limited thereto, and may also be a temporary storage medium.

[0322] The present disclosure also provides a program product, which, when executed by the communication device 8100, enables the communication device 8100 to perform any of the above methods. Optionally, the program product is a computer program product.

[0323] 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.

Claims

1. A model monitoring method, characterized in that, The method is executed by a terminal, and the method includes: Predicting a first reference signal based on a first model to obtain a prediction result, where the first reference signal is used to instruct a server to monitor the first model; Sending the prediction result to the server.

2. The method according to claim 1, wherein The method further includes: Receiving the first reference signal sent by an access network device; where the first reference signal includes at least one of a synchronization signal block (SSB), a channel state information reference signal (CSI-RS), or a positioning reference signal (PRS).

3. The method according to claim 2, wherein The first reference signal includes a PRS, and the parameters of the PRS include at least one of a PRS subcarrier spacing (SCS), a PRS bandwidth (BW), a comb size, and a PRS period; or, The first reference signal includes an SSB, and the parameters of the SSB include at least one of a primary synchronization signal (PSS) index or a secondary synchronization signal (SSS) index.

4. The method according to claim 2 or 3, characterized in that, The access network device includes access network devices corresponding to a current serving cell and neighboring cells.

5. The method according to any one of claims 1 to 4, characterized in that The method further includes: Sending a training result to the server, where the training result is used by the server to train a second model to obtain the first model.

6. The method according to any one of claims 1 to 5, characterized in that The method further includes: Receiving the first model sent by the server.

7. The method according to any one of claims 1 to 6, characterized in that, The method further includes: Receiving a second reference signal sent by an access network device, where the second reference signal is used for the terminal to perform measurements; Sending a measurement result of the second reference signal to the access network device.

8. A model monitoring method, characterized in that, The method is executed by a server, and the method includes: Receiving a prediction result sent by a terminal, where the prediction result is obtained by the terminal predicting a first reference signal based on a first model, and the first reference signal is used to instruct the server to monitor the first model; Monitoring the first model based on the prediction result.

9. The method according to claim 8, wherein The method further includes: Sending the first reference signal to an access network device, where the first reference signal includes at least one of a synchronization signal block (SSB), a channel state information reference signal (CSI-RS), or a positioning reference signal (PRS).

10. The method according to claim 9, wherein The first reference signal includes a PRS, and the parameters of the PRS include at least one of a PRS subcarrier spacing (SCS), a PRS bandwidth (BW), a comb size, and a PRS period; or, The first reference signal includes an SSB, and the parameters of the SSB include at least one of a primary synchronization signal (PSS) index or a secondary synchronization signal (SSS) index.

11. The method according to claim 9 or 10, characterized in that, The access network device is an access network device corresponding to a neighboring cell.

12. The method according to any one of claims 8 to 11, characterized in that, The method further includes: Receiving the training result sent by the terminal; Training a second model based on the training result to obtain the first model.

13. The method according to any one of claims 8 to 12, characterized in that, The method further includes: Sending the first model to the terminal.

14. The method according to any one of claims 8 to 13, characterized in that The monitoring the first model based on the prediction result includes: Monitoring the first model based on the prediction result and a reference result corresponding to the first reference signal.

15. The method according to claim 14, wherein The monitoring the first model based on the prediction result and a reference result corresponding to the first reference signal includes: If the difference between the predicted result and the reference result is less than the difference threshold, it is determined that the first model is qualified; Or, If the difference between the predicted result and the reference result is not less than the difference threshold, it is determined that the first model is unqualified.

16. A model monitoring method, characterized in that, The method is executed by an access network device, and the method includes: Sending a first reference signal to a terminal, where the first reference signal is used to instruct a server to monitor the first model, and where the first reference signal includes at least one of a synchronization signal block SSB, a channel state information reference signal CSI-RS, or a positioning reference signal PRS.

17. The method according to claim 16, wherein The first reference signal includes PRS, and the parameters of the PRS include at least one of a PRS subcarrier spacing SCS, a PRS bandwidth BW, a comb size, and a PRS period; or, The first reference signal includes SSB, and the parameters of the SSB include at least one of a primary synchronization signal PSS index or a secondary synchronization signal SSS index.

18. The method according to claim 16 or 17, characterized in that, The access network device is an access network device corresponding to a neighboring cell.

19. The method according to any one of claims 16 to 18, characterized in that, The method further includes: Sending a second reference signal to the terminal, where the second reference signal is used for the terminal to perform measurements; Receiving a measurement result of the second reference signal sent by the terminal.

20. A model monitoring method, characterized in that, The method includes: An access network device sends a first reference signal to a terminal, where the first reference signal is used to instruct a server to monitor the first model; The terminal predicts the first reference signal based on a first model to obtain a predicted result; The terminal sends the predicted result to the server; The server receives the predicted result sent by the terminal; The server monitors the first model based on the predicted result.

21. A model monitoring device, characterized in that, The model monitoring device includes: A processing module, configured to predict a first reference signal based on a first model to obtain a predicted result, where the first reference signal is used to instruct a server to monitor the first model; A transceiver module, configured to send the predicted result to the server.

22. A model monitoring device, characterized in that, The model monitoring device includes: A transceiver module, configured to receive a predicted result sent by a terminal, where the predicted result is obtained by the terminal predicting a first reference signal based on a first model, and the first reference signal is used to instruct the server to monitor the first model; A processing module, configured to monitor the first model based on the predicted result.

23. A model monitoring device, characterized in that, The model monitoring device includes: A transceiver module, configured to send a first reference signal to a terminal, where the first reference signal is used to instruct to monitor the first model, and where the first reference signal includes at least one of a synchronization signal block SSB, a channel state information reference signal CSI-RS, or a positioning reference signal PRS.

24. A model monitoring device, characterized in that, The model monitoring device includes: One or more processors; Wherein, the processor is configured to execute the model monitoring method according to any one of claims 1 to 7 or 8 to 15 or 16 to 19.

25. A communication system, characterized in that, It includes a terminal, an access network device, and a server. Among them, the terminal is configured to implement the model monitoring method described in any one of claims 1 to 7, the server is configured to implement the model monitoring method described in any one of claims 8 to 15, and the access network device is configured to implement the model monitoring method described in any one of claims 16 to 19.

26. A storage medium, the storage medium stores instructions, characterized in that, When the instruction runs on the communication device, it causes the communication device to execute the model monitoring method described in any one of claims 1 to 19.

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