Performance monitoring method, first device, and second device

Abstract

The present application relates to a performance monitoring method, a first device, a second device, a chip, a computer-readable storage medium, a computer program product, a computer program, and a communication system. The method comprises: a first device receives first data from a second device, wherein the first data is used for the first device to determine a first model, and the first model is used for the first device to perform performance monitoring related to a first task. According to embodiments of the present application, the performance monitoring of the first task does not require transmission of information of a model for executing the first task, and does not require transmission of a large amount of data such as an intermediate processing result and a measurement result in the process of executing the first task, thereby avoiding the privacy and model privatization problems, and reducing signaling overhead.

Description

Performance monitoring method, first device and second device Technical Field

[0001] The present application relates to the field of communications, and more specifically, to a performance monitoring method, a first device, a second device, a chip, a computer-readable storage medium, a computer program product, a computer program, and a communication system. Background Art

[0002] Monitoring the performance of wireless communication solutions helps analyze and optimize network quality and performance. Performance monitoring can be performed by either the network or the terminal. This process involves a lot of additional data transmission, such as measurement data, intermediate processing results from tasks performed collaboratively by the network and the terminal, and information about the computational models used to execute the tasks. This can lead to privacy issues and increase transmission overhead.

[0003] Summary of the Invention

[0004] The embodiments of the present application provide a performance monitoring method that can avoid privacy issues caused by information transmission and reduce transmission overhead.

[0005] This embodiment of the present application provides a performance monitoring method, including:

[0006] The first device receives first data from the second device; wherein the first data is used by the first device to determine a first model; and the first model is used by the first device to perform performance monitoring related to a first task.

[0007] This embodiment of the present application provides a performance monitoring method, including:

[0008] The second device sends first data to the first device; wherein the first data is used by the first device to determine a first model; and the first model is used by the first device to perform performance monitoring related to the first task.

[0009] An embodiment of the present application provides a first device, including:

[0010] The first communication module is used to receive first data from the second device; wherein the first data is used to determine a first model; and the first model is used to perform performance monitoring related to the first task.

[0011] An embodiment of the present application provides a second device, including:

[0012] The second communication module is used to send first data to the first device; wherein the first data is used by the first device to determine a first model; and the first model is used by the first device to perform performance monitoring related to the first task.

[0013] An embodiment of the present application provides a first device, comprising: a transceiver, a processor, and a memory. The memory is configured to store a computer program, the transceiver is configured to communicate with other devices, and the processor is configured to call and execute the computer program stored in the memory, so that the first device performs the aforementioned performance monitoring method.

[0014] An embodiment of the present application provides a second device, comprising: a transceiver, a processor, and a memory. The memory is configured to store a computer program, the transceiver is configured to communicate with other devices, and the processor is configured to call and execute the computer program stored in the memory, so that the second device performs the aforementioned performance monitoring method.

[0015] An embodiment of the present application provides a chip for implementing the above-mentioned performance monitoring method.

[0016] Specifically, the chip includes: a processor, which is used to call and run a computer program from a memory, so that a device equipped with the chip executes the above-mentioned performance monitoring method.

[0017] An embodiment of the present application provides a computer-readable storage medium for storing a computer program. When the computer program is executed by a device, the device executes the above-mentioned performance monitoring method.

[0018] An embodiment of the present application provides a computer program product, including computer program instructions, which enable a computer to execute the above-mentioned performance monitoring method.

[0019] An embodiment of the present application provides a computer program, which, when executed on a computer, enables the computer to execute the above-mentioned performance monitoring method.

[0020] An embodiment of the present application provides a communication system, including a first device and a second device for executing the above-mentioned performance monitoring method.

[0021] In an embodiment of the present application, the second device transmits first data to the first device so that the first device can determine the first model and use the first model to monitor the performance of the first task. Therefore, there is no need to transmit the model used to perform the first task, nor is there any need to transmit a large amount of data such as intermediate processing results and measurement results in the process of performing the first task, thereby avoiding privacy and model privatization issues and reducing signaling overhead. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] FIG1 is a schematic diagram of a communication system according to an embodiment of the present application.

[0023] FIG2 is a schematic diagram of an artificial intelligence-based CSI compression feedback solution in an embodiment of the present application.

[0024] FIG3 is a schematic diagram of an artificial intelligence-based channel estimation solution in an embodiment of the present application.

[0025] FIG4 is a schematic diagram of an artificial intelligence-based positioning solution in an embodiment of the present application.

[0026] FIG5 is a schematic diagram of an artificial intelligence-based beam management solution in an embodiment of the present application.

[0027] FIG6 is a schematic flowchart of a performance monitoring method according to an embodiment of the present application.

[0028] FIG7 is a schematic flowchart of a performance monitoring method according to another embodiment of the present application.

[0029] FIG8 is a schematic diagram of an application example of the performance monitoring method according to an embodiment of the present application.

[0030] FIG9 is a schematic diagram of an example of third data in the performance monitoring method according to an embodiment of the present application.

[0031] FIG10 is a schematic diagram of an example of third data in the performance monitoring method according to an embodiment of the present application.

[0032] FIG11 is a schematic block diagram of a first device according to an embodiment of the present application.

[0033] FIG12 is a schematic block diagram of a second device according to an embodiment of the present application

[0034] FIG13 is a schematic block diagram of a communication device according to an embodiment of the present application.

[0035] FIG14 is a schematic block diagram of a chip according to an embodiment of the present application.

[0036] FIG15 is a schematic block diagram of a communication system according to an embodiment of the present application. DETAILED DESCRIPTION

[0037] The technical solutions in the embodiments of the present application will be described below in conjunction with the drawings in the embodiments of the present application.

[0038] The technical solutions of the embodiments of the present application can be applied to various communication systems, such as: Long Term Evolution (LTE) system, Advanced Long Term Evolution (LTE-A) system, New Radio (NR) system, NR system evolution system, LTE on unlicensed spectrum (LTE-U) system, NR on unlicensed spectrum (NR-based access to unlicensed spectrum, NR-U) system, Non-Terrestrial Networks (NTN) system, Universal Mobile Telecommunication System (UMTS), Wireless Local Area Networks (WLAN), Wireless Fidelity (WiFi), Fifth Generation (5G) system or other communication systems.

[0039] Generally speaking, traditional communication systems support a limited number of connections and are easy to implement. However, with the development of communication technology, mobile communication systems will not only support traditional communications, but will also support, for example, device-to-device (D2D) communication, machine-to-machine (M2M) communication, machine-type communication (MTC), vehicle-to-vehicle (V2V) communication, or vehicle-to-everything (V2X) communication, etc. The embodiments of the present application can also be applied to these communication systems.

[0040] In one embodiment, the communication system in the embodiment of the present application can be applied to a carrier aggregation (CA) scenario, a dual connectivity (DC) scenario, and a standalone (SA) networking scenario.

[0041] In one embodiment, the communication system in the embodiment of the present application can be applied to an unlicensed spectrum, wherein the unlicensed spectrum can also be considered as a shared spectrum; or, the communication system in the embodiment of the present application can also be applied to an authorized spectrum, wherein the authorized spectrum can also be considered as an unshared spectrum.

[0042] The embodiments of the present application describe various embodiments in conjunction with network devices and terminal devices, wherein the terminal device may also be referred to as user equipment (UE), access terminal, user unit, user station, mobile station, mobile station, remote station, remote terminal, mobile device, user terminal, terminal, wireless communication device, user agent or user device, etc.

[0043] The terminal device can be a station (STAION, ST) in a WLAN, a cellular phone, a cordless phone, a Session Initiation Protocol (SIP) phone, a Wireless Local Loop (WLL) station, a Personal Digital Assistant (PDA) device, a handheld device with wireless communication capabilities, a computing device or other processing device connected to a wireless modem, a vehicle-mounted device, a wearable device, a terminal device in a next-generation communication system such as an NR network, or a terminal device in a future evolved Public Land Mobile Network (PLMN) network, etc.

[0044] In an embodiment of the present application, the terminal device can be deployed on land, including indoors or outdoors, handheld, wearable or vehicle-mounted; it can also be deployed on the water surface (such as ships, etc.); it can also be deployed in the air (such as airplanes, balloons and satellites, etc.).

[0045] In an embodiment of the present application, the terminal device may be a mobile phone, 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, a wireless terminal device in a smart grid, a wireless terminal device in transportation safety, a wireless terminal device in a smart city, or a wireless terminal device in a smart home, etc.

[0046] As an example and not a limitation, in the embodiment of the present application, the terminal device may also be a wearable device. Wearable devices may also be called wearable smart devices, which are a general term for wearable devices that are intelligently designed and developed using wearable technology for daily wear, such as glasses, gloves, watches, clothing, and shoes. A wearable device is a portable device that is worn directly on the body or integrated into the user's clothes or accessories. Wearable devices are not only hardware devices, but also achieve powerful functions through software support, data interaction, and cloud interaction. Broadly speaking, wearable smart devices include those that are fully functional, large in size, and can achieve complete or partial functions without relying on smartphones, such as smart watches or smart glasses, as well as those that only focus on a certain type of application function and need to be used in conjunction with other devices such as smartphones, such as various smart bracelets and smart jewelry for vital sign monitoring.

[0047] In an embodiment of the present application, the network device may be a device for communicating with a mobile device. The network device may be an access point (AP) in a WLAN, an evolved base station (eNB or eNodeB) in LTE, or a relay station or access point, or a vehicle-mounted device, a wearable device, and a network device (gNB) in an NR network, or a network device in a future evolved PLMN network or a network device in an NTN network, etc.

[0048] As an example and not a limitation, in an embodiment of the present application, the network device may have a mobile feature, for example, the network device may be a mobile device. Alternatively, the network device may be a satellite or a balloon station. For example, the satellite may be a low earth orbit (LEO) satellite, a medium earth orbit (MEO) satellite, a geostationary earth orbit (GEO) satellite, a high elliptical orbit (HEO) satellite, etc. Optionally, the network device may also be a base station set up in a location such as land or water.

[0049] In an embodiment of the present application, the network device can provide services for a cell, and the terminal device communicates with the network device through the transmission resources used by the cell (for example, frequency domain resources, or spectrum resources). The cell can be a cell corresponding to the network device (for example, a base station). The cell can belong to a macro base station or a base station corresponding to a small cell. The small cells here may include: metro cells, micro cells, pico cells, femto cells, etc. These small cells have the characteristics of small coverage and low transmission power, and are suitable for providing high-speed data transmission services.

[0050] FIG1 exemplarily illustrates a communication system 100. The communication system includes a network device 110 and two terminal devices 120. In one embodiment, the communication system 100 may include multiple network devices 110, and each network device 110 may include a different number of terminal devices 120 within its coverage area, which is not limited in this embodiment of the present application.

[0051] In one embodiment, the communication system 100 may further include other network entities such as a Mobility Management Entity (MME) and an Access and Mobility Management Function (AMF), which is not limited in this embodiment of the present application.

[0052] Among them, the network equipment may include access network equipment and core network equipment. That is, the wireless communication system also includes multiple core networks for communicating with the access network equipment. The access network equipment can be an evolutionary base station (evolutional node B, abbreviated as eNB or e-NodeB) macro base station, micro base station (also called "small base station"), pico base station, access point (AP), transmission point (TP) or new generation base station (new generation Node B, gNodeB), etc. in a long-term evolution (LTE) system, a next-generation (mobile communication system) (next radio, NR) system or an authorized auxiliary access long-term evolution (LAA-LTE) system.

[0053] It should be understood that in the embodiments of the present application, a device having a communication function in a network / system may be referred to as a communication device. Taking the communication system shown in Figure 1 as an example, the communication device may include a network device and a terminal device having a communication function. The network device and the terminal device may be specific devices in the embodiments of the present application and will not be described in detail here. The communication device may also include other devices in the communication system, such as a network controller, a mobility management entity, and other network entities, which are not limited in the embodiments of the present application.

[0054] It should be understood that the terms "system" and "network" are often used interchangeably herein. The term "and / or" is simply a description of an association between related objects, indicating that three possible relationships exist. For example, "A and / or B" can represent: A exists alone, A and B exist simultaneously, or B exists alone. Furthermore, the character " / " generally indicates that the related objects are in an "or" relationship.

[0055] It should be understood that the "indication" mentioned in the embodiments of this application can be a direct indication, an indirect indication, or an indication of an association. For example, "A indicates B" can mean that A directly indicates B, for example, B can be obtained through A; it can also mean that A indirectly indicates B, for example, A indicates C, and B can be obtained through C; it can also mean that there is an association between A and B.

[0056] In the description of the embodiments of the present application, the term "corresponding" may indicate a direct or indirect correspondence between the two, or an association relationship between the two, or a relationship between indication and being indicated, configuration and being configured, etc.

[0057] To facilitate understanding of the technical solutions of the embodiments of the present application, the relevant technologies of the embodiments of the present application are described below. The following relevant technologies can be arbitrarily combined with the technical solutions of the embodiments of the present application as optional solutions, and they all fall within the protection scope of the embodiments of the present application.

[0058] (1) Wireless communication solutions based on AI (Artificial Intelligence)

[0059] Currently, AI-based solutions are increasingly being used in wireless communication systems. For example, artificial intelligence is used to implement CSI (Channel-State Information) feedback. As shown in Figure 2, AI-based CSI information compression feedback is implemented through the introduction of AI encoders and AI decoders. For another example, AI is used to solve channel estimation problems. As shown in Figure 3, an AI channel estimator is used to achieve high-performance estimation of a given channel. For another example, AI is used to solve positioning problems. As shown in Figure 4, an AI-based positioning algorithm is used to rely on positioning channel information to obtain high-precision positioning results. For another example, AI is used to solve beam management problems. As shown in Figure 5, an AI-based beam management algorithm is used to obtain preferred or more refined beam information based on known beam information, or to obtain predictions of beam information for future moments.

[0060] Among the aforementioned AI / ML (Machine Learning)-based wireless communication solutions, there are two main categories. One is single-ended solutions, where AI / ML solutions reside entirely on the UE or network side. For example, beam management-related models are deployed on the UE or network side, or positioning-related models are deployed on the UE or network side. The other is dual-ended solutions, which require cooperation between the UE and the network to execute specific use cases. For example, AI / ML-based CSI compression and recovery solutions are typical dual-ended solutions. Similar AI / ML-based dual-ended solutions can also include AI / ML-based modulation and demodulation solutions, AI / ML-based source (or channel) encoding and decoding solutions, and AI / ML-based transmitter and receiver matching designs. A common feature of these dual-ended solutions is that they require the UE and network to use models deployed on both sides (and these models must be compatible) to jointly complete specific wireless transmission functions. The UE-side model must match the network-side model; otherwise, performance degradation or inoperability may occur.

[0061] 2. Performance Monitoring of Wireless Communication Solutions Based on AI / ML

[0062] In current research, the performance evaluation of AI / ML solutions is primarily defined based on the inference performance of the AI / ML solutions. For example, for CSI compression and recovery solutions, the CSI recovery accuracy achievable by a specific AI / ML solution under specific compression feedback bit conditions can be used as a performance evaluation indicator for the solution. For example, the difference or similarity between ideal CSI information or the CSI information to be compressed and the CSI information obtained through compression and recovery can be used as a performance evaluation indicator. For CSI prediction solutions, similar to CSI compression and recovery solutions, the achievable CSI prediction accuracy of a specific AI / ML solution can be used as a performance evaluation indicator for the solution, for example, by evaluating the difference or similarity between ideal CSI information or target CSI information and the predicted CSI information. In the above-mentioned solutions, the difference evaluation between CSI information is, for example, the NMSE (Normalized Mean Square Error) or MSE (Mean Squared Error) evaluation between CSI information. The similarity evaluation between CSI information is, for example, based on GCS or SGCS. For example, in the beam management solution, it is necessary to evaluate the prediction effect of the beam (such as the measurement error with the ideal beam) to determine whether the AI / ML solution can be used; in the positioning solution, it is also necessary to evaluate the positioning accuracy or some intermediate results of the positioning calculation (such as RSTD (Reference Signal Time Difference) estimation, TOA (Time Of Arrival) estimation) accuracy to determine whether the relevant solution is working properly. In addition, in some of the above solutions, such as CSI-related solutions, beam prediction-related solutions, and codec-related solutions, the system capacity and throughput performance brought by the use of AI / ML solutions can also be used as judgment indicators for the performance evaluation of the corresponding solutions.

[0063] Regarding performance monitoring for the aforementioned AI / ML wireless communication solutions, it's important to note that performance monitoring can be divided into UE-side monitoring and network-side monitoring. UE-side monitoring focuses on the UE itself performing the aforementioned performance monitoring calculations and obtaining performance monitoring results, or other results related to performance monitoring. Network-side monitoring focuses on performance monitoring being performed by the network, which then calculates and obtains performance monitoring results, or other results related to performance monitoring.

[0064] Network-side monitoring requires the UE to transmit a large amount of performance monitoring information to the network (such as tag data that can only be obtained through measurement on the UE side, and network-side model input data output by the UE). This means that a lot of additional data transmission is introduced during the performance monitoring process. In contrast, UE-side monitoring can perform performance monitoring of certain tasks and models locally on the UE, thereby completing specific task and model performance monitoring while avoiding unnecessary performance monitoring data transmission and signaling overhead.

[0065] For UE-side performance monitoring, taking the CSI feedback task as an example, under the assumption of a dual-end model, the UE side needs to be able to obtain the output of the CSI recovery model used on the network side as evaluation data. However, the problem here is that the dual-end model often has one-end model unique to the UE side and the other-end model unique to the network side. For example, the CSI generation model is unique to the UE side, and the CSI recovery model is unique to the network side. For reasons such as model privatization and model privacy, if the UE side cannot obtain the network-side model of the dual-end model from the network side, there is a lack of a complete dual-end model on the UE side, and there is also a lack of a complete dual-end model output result for UE-side performance monitoring of the CSI compression feedback task. A similar situation also exists when the network-side single-end model is expected to perform UE-side performance monitoring.

[0066] The technical solution of the embodiments of the present application can solve at least one of the above problems.

[0067] FIG6 is a schematic flow chart of a performance monitoring method according to an embodiment of the present application. The method can optionally be applied to the system shown in FIG6 , but is not limited thereto. The method includes:

[0068] S610. A first device receives first data from a second device; the first data is used by the first device to determine a first model; and the first model is used by the first device to perform performance monitoring related to a first task.

[0069] Corresponding to the above method, FIG7 is a schematic flow chart of a performance monitoring method according to another embodiment of the present application. The method can optionally be applied to the system shown in FIG7 , but is not limited thereto. The method includes:

[0070] S710. The second device sends first data to the first device; wherein the first data is used by the first device to determine a first model; and the first model is used by the first device to perform performance monitoring related to a first task.

[0071] In the embodiments of the present application, the first device may be any device in a communication system. For example, the first device may be a network device or a terminal device. The second device may be any device in the communication system other than the first device. For example, the second device may be a network device or a terminal device. That is, the application scenario of the embodiments of the present application may be one of the following scenarios:

[0072] Scenario 1: The first device is a terminal device, and the second device is a network device;

[0073] Scenario 2: The first device is a network device, and the second device is a terminal device;

[0074] Scenario 3: The first device is a first terminal device, and the second device is a second terminal device;

[0075] Scenario 4: The first device is a first network device, and the second device is a second network device.

[0076] In an embodiment of the present application, the first model is used for the first device to perform performance monitoring related to the first task. Based on this, the first model can be called a performance monitoring model. Here, the performance monitoring related to the first task can include obtaining performance monitoring indicators of the first task; wherein, the performance monitoring indicators can include evaluation indicators for the performance of the first task, or evaluation indicators for system performance related to the first task. Among them, the evaluation indicators for the performance of the first task are, for example, the processing precision and accuracy of the first task. The evaluation indicators for system performance related to the first task are, for example, system capacity and throughput performance indicators when executing the first task.

[0077] For example, the first task may include a model-based wireless communication solution. Performance monitoring related to the first task may be understood as performance monitoring of the model, such as obtaining evaluation metrics for model performance or obtaining evaluation metrics for system performance related to the model. The model may be an AI / ML-based model or another computational model.

[0078] For example, the first task may be the AI-based CSI information compression feedback, the channel estimation implemented by the AI ​​channel estimator, the AI-based positioning scheme, or the AI-based beam management scheme in the aforementioned related technologies.

[0079] Optionally, the first model may be an AI-based model, such as a machine learning model, a fully connected network model, a convolutional neural network model, a recurrent neural network model, etc. In addition, the first model may be a model that directly outputs performance monitoring indicators, or a model that outputs other information used to determine performance monitoring indicators.

[0080] Optionally, the first data is used to determine the first model, which may refer to the first data being used to indicate the first model, for example, indicating specific parameters of the first model (such as network structure, weights, etc.). Alternatively, the first data is used to indicate data related to the construction of the first model, which may be specifically set according to the function of the first model. It should be noted that the first data may include one or more data, so in some descriptions, the first data may also be referred to as the first data set.

[0081] Optionally, the first data can be transmitted in one or more of the following ways (or carried by one or more of the following messages / channels): broadcast message, RRC (Radio Resource Control) message, MAC CE (MAC Control Element, media access control layer control unit), message in the random access process, DCI (Downlink Control Information, downlink control information), UCI (Uplink Control Information, uplink control information), PDCCH (Physical Downlink Control Channel, physical downlink control channel), PUCCH (Physical Uplink Control Channel, physical uplink control channel), PDSCH (Physical Downlink Shared Channel, physical downlink shared channel), PUSCH (Physical Uplink Shared Channel, physical uplink shared channel), AI / ML dedicated channel, capability indication information, etc.

[0082] Taking the first device as a terminal device and the second device as a network device as an example, the network device can transmit the first data to the terminal device in the following ways: broadcast messages such as MIB (master information block), SIB1 (System Information Block Type 1) or SIBx (System Information Block Type x); RRC messages; MAC CE; DCI; downlink messages in the random access process such as MsgB (message B), Msg2 (message 2) or Msg4 (message 4); PDCCH; PDSCH; AI / ML dedicated downlink channel; capability indication on the network side.

[0083] Optionally, after the above step S610, the performance monitoring method may further include: the first device determining a first model based on the first data, and performing performance monitoring related to the first task based on the first model.

[0084] According to the above method, the second device transmits the first data to the first device so that the first device can determine the first model and use the first model to monitor the performance of the first task. Therefore, there is no need to transmit a large amount of data such as the model used to perform the first task or the intermediate processing results, measurement results, etc. in the process of performing the first task, thereby avoiding privacy and model privatization issues and reducing signaling overhead.

[0085] In some embodiments, the first task includes a wireless communication solution based on the second model in the second device. That is, the performance monitoring associated with the first task may include performance monitoring of the second model in the second device. According to the method of the embodiment of the present application, the second model may not need to be transmitted, thus avoiding privacy issues and model privatization issues caused by transmitting the second model.

[0086] In some embodiments, the wireless communication solution is implemented based on the second device using the second model. Alternatively, the wireless communication solution can be implemented independently based on the second device using the second model, or can be implemented based on the first device using the third model and the second device using the second model.

[0087] Specifically, the wireless communication solution may be a single-ended solution executed by the second device, or a dual-ended solution executed by the first device and the second device.

[0088] For example, the first device is a terminal device, and the second device is a network device. The above-mentioned wireless communication solution can be a beam prediction solution or a positioning solution implemented by the network device using the second model. The embodiment of the present application does not require the terminal device to transmit a large amount of data (such as data obtained through measurement) to the network device, nor does it require the network device to transmit the second model to the terminal device. The terminal device uses the first data to determine the first model, and implements performance monitoring of the solution based on the first model and the local data of the terminal device.

[0089] For another example, the first device is a terminal device and the second device is a network device. The above-mentioned wireless communication solution can be a compression feedback scheme of CSI information implemented by the terminal device using the third model (encoder) and the network device using the second model (decoder). The embodiment of the present application does not require the terminal device to transmit a large amount of data (such as data obtained through measurement, data output by the encoder of the terminal device) to the network device, nor does it require the network device to transmit the decoder to the terminal device. The terminal device uses the first data to determine the first model, and implements performance monitoring of the scheme based on the first model and the local data of the terminal device.

[0090] For another example, the first device is a network device, and the second device is a terminal device. The above-mentioned wireless communication solution can be a compression feedback scheme of CSI information implemented by the terminal device using the second model (encoder) and the network device using the third model (decoder). The embodiment of the present application does not require the terminal device to transmit the encoder to the network device, and does not require the terminal device to transmit the data obtained based on the measurement and the data output by the encoder in the terminal device to the network device. The network device uses the first data to determine the first model, and implements performance monitoring of the scheme based on the first model and the local data of the network device.

[0091] In some embodiments, the first model includes a model having the same functionality as the second model, and / or a model for outputting performance monitoring indicators.

[0092] Specifically, in one embodiment, the first model may include a model having the same function as the second model. The first device may run the first model to obtain processing information of the first model, and obtain the performance monitoring indicator based on the processing information of the first model.

[0093] For example, a first device is deployed with an encoder that outputs a bitstream based on the original channel information, and a second device is deployed with a second decoder (second model) that outputs channel information based on the bitstream. The first and second devices use the encoder and the second decoder to implement CSI compression feedback. On this basis, the first model can be a first decoder that outputs channel information based on the bitstream. Here, the second decoder has the same function as the first decoder, but in fact, the second decoder and the first decoder can be the same model or different models. For example, the second decoder can be different from the first decoder. The channel information output by the second decoder is the original channel information, including channel data of M (an integer greater than or equal to 2) dimensions, that is, the channel state is represented by information of M dimensions; the channel information output by the first decoder is processed data information that has a mapping relationship with the original channel information, including channel data of N (an integer greater than or equal to 2) dimensions, that is, the channel state is represented by information of N dimensions. In this way, the first device can use the first decoder to match the encoder to obtain relevant data for CSI compression feedback and obtain performance monitoring indicators based on this relevant data.

[0094] In another embodiment, the first model may include a model that outputs performance monitoring indicators. For example, if an encoder that outputs a bitstream based on channel information is deployed in the first device, and a decoder that outputs channel information based on the bitstream is deployed in the second device, the second device can transmit the first data to enable the first device to determine a performance monitoring model. The performance monitoring model can output performance monitoring indicators such as accuracy and correctness of the encoder and decoder based on local data of the first device (e.g., measurement data, system performance indicators, etc.).

[0095] For ease of understanding, optional implementations of the first model are described below for a wireless communication solution based on a dual-end model (hereinafter referred to as a dual-end solution) and a wireless communication solution based on a single-end model.

[0096] For a dual-end solution, if the first device uses a third model (the third model is part of the dual-end solution, and its implementation portion can also be referred to as the third solution) and the second device uses a second model (the second model is part of the dual-end solution, and its implementation portion can also be referred to as the second solution), then the first data can be used to construct the second solution / second model on the first device side, or to construct a solution / model with similar functionality to the second solution / second model, or to construct a solution / model that can output performance monitoring results. Thus, the first device does not need to transmit a large amount of intermediate performance monitoring data or tag data to the second device to complete performance monitoring, and the second device does not need to transmit the actual second solution / second model to the first device. Instead, through the transmission of the first data, the first device can complete the construction of a local performance monitoring model (first model). The local performance monitoring model can be a model with equivalent functionality to the model on the second device side, or a model that can directly output performance monitoring results. For example, if the third solution / third model is the coding scheme / model used on the UE side, and the second solution is the decoding scheme / model used on the network side, then the first data is used to construct a decoding scheme / model on the UE side to assist in matching and using the coding scheme / model and performance monitoring on the UE side. For example, the above performance monitoring model can be used for performance monitoring of a network-side CSI recovery solution on the UE side, or performance monitoring of a network-side decoding solution on the UE side.

[0097] For a single-end solution, if the second device uses the second solution / second model, the first data can be used to construct the second solution / second model on the first device side, or to construct a solution / model with similar functions to the second solution / second model, or to construct a solution / model that can output performance monitoring results. Thus, the first device does not need to transmit a large amount of intermediate performance monitoring data and tag data to the network to complete performance monitoring. The second device also does not need to transmit the second solution / second model actually used, but instead, through the transmission of the first data, the first device can complete the construction of a local performance monitoring model. The local performance monitoring model can be a model with the same function as the single-end model on the second device side, or a model that can directly output performance monitoring results. For example, if the second solution / second model is the beam prediction solution / model used on the network side, the first data is used to construct a beam prediction solution / model on the UE side to assist the UE side in directly obtaining performance monitoring results without having to complete performance monitoring of the network side model through frequent transmission of tag data. For example, the above-mentioned performance monitoring model can be a performance monitoring model of the network-side beam prediction solution on the UE side, or a performance monitoring model of the network-side positioning solution on the UE side, etc.

[0098] In some embodiments, the first data is used to indicate the first model. For example, the first data may include parameters of the first model, such as structural parameters (e.g., the number of neural network layers, the number of neurons in each layer, etc.), weight parameters, bias information, etc. In other words, the second device may directly indicate and transmit the first model to the first device.

[0099] In some embodiments, the first data includes second data and third data used to construct the first model, where the second data includes input information of the first model, and the third data includes output information of the first model. In some descriptions, the first data may also be referred to as sample data or training data, i.e., the first data includes sample data used to construct the first model, including input information and output information of the first model, and the first device may construct the first model based on the first data.

[0100] In some embodiments, before the first device receives the first data from the second device, the method further includes: the first device sending first indication information to the second device; wherein the first indication information indicates that the first device has the ability to determine the first model. Accordingly, for the second device, before the second device sends the first data to the first device, the method further includes: the second device receiving the first indication information from the first device; wherein the first indication information indicates that the first device has the ability to determine the first model. Optionally, the second device may send the first data upon receiving the first indication information.

[0101] That is, the first device can report that it has the ability to build a local performance monitoring solution / model. Taking the first device as a terminal device and the second device as a network device as an example, the terminal device can send the first indication information through UE capability reporting, UE information reporting, RRC message, UCI, etc.

[0102] In some embodiments, before the first device receives the first data from the second device, the method further includes: the first device sending second indication information to the second device; wherein the second indication information is used to instruct the second device to send the first data. Correspondingly, for the second device, before the second device sends the first data to the first device, the method further includes: the second device receiving second indication information from the first device; wherein the second indication information is used to instruct the second device to send the first data.

[0103] That is, the first device can request / instruct / trigger the second device to transmit the first data to the first device. For example, if the first device is a terminal device and the second device is a network device, the terminal device can send the second indication information via UE capability reporting, UE information reporting, RRC message, or UCI. Accordingly, the network device can respond to the UE's request and instruct and transmit the first data to the UE.

[0104] In some embodiments, before the first device receives the first data from the second device, the method further includes: the first device sending third indication information to the second device; wherein the third indication information indicates type information of the first data. Correspondingly, for the second device, before the second device sends the first data to the first device, the method further includes: the second device receiving the third indication information from the second device; wherein the third indication information indicates type information of the first data.

[0105] That is, the first device may indicate to the second device the type of first data required by the first device, so that the second device can determine the first data and transmit the first data to the first device. Taking the first device as a terminal device and the second device as a network device as an example, the terminal device may send the third indication information through UE capability reporting, UE information reporting, RRC message, or UCI.

[0106] In other embodiments, before the first device receives the first data from the second device, the method further includes: the first device receiving third indication information from the second device; wherein the third indication information indicates type information of the first data. Correspondingly, for the second device, before the second device sends the first data to the first device, the method further includes: the second device sending third indication information to the first device; wherein the third indication information indicates type information of the first data.

[0107] That is, the second device may indicate the type information of the first data to the first device so that the first device can accurately parse the first data. For example, taking the first device as a terminal device and the second device as a network device, the network device may send the third indication information via an RRC message, DCI, or the like.

[0108] In some embodiments, the type information includes at least one of the following:

[0109] Interface type;

[0110] Channel information type;

[0111] Type of measurement information;

[0112] Quantitative information type.

[0113] Exemplarily, the interface type is, for example, an interface size, a dimension, or an interface associated with a specific transmission configuration, or an interface associated with a specific data type.

[0114] Exemplarily, when the first data includes channel information, the type information indicated by the third indication information may include the channel information type, such as full channel information, channel characteristic vector, associated channel conditions, channel configuration, etc., that is, the third indication information can be used to indicate what type of channel information the first data is (full channel information or channel characteristic vector), and can also be used to indicate the channel conditions, channel configuration, etc. associated with the first data.

[0115] Exemplarily, in the case where the first data includes measurement information, the type information indicated by the third indication information may include the measurement information type, such as the type of measurement, or the type of measurement result such as RSRP (Reference Signal Receiving Power), RSRQ (Reference Signal Receiving Quality), RSSI (Received Signal Strength Indication), etc.

[0116] Exemplarily, in the case where the first data includes quantization information, the type information indicated by the third indication information may include the type of quantization information, such as quantization mode, quantization level, quantization granularity, etc.

[0117] It should be noted that in actual applications, the type information indicated by the third indication information may include one or more of the above types. For example, when the first data includes channel information, the type information indicated by the third indication information may include the interface type and the channel information type; or, when the first data includes channel information and measurement information, the type information indicated by the third indication information may include the channel information type and the measurement information type. In actual applications, the information indicated by the third indication information may be set according to protocol agreements, system agreements, scenario requirements, etc., and not all forms are listed here.

[0118] In some embodiments, before the first device receives the first data from the second device, the method further includes: the first device sending fourth indication information to the second device; wherein the fourth indication information is used to indicate information related to the application of the first model. Correspondingly, for the second device, before the second device sends the first data to the first device, the method further includes: the second device receiving fourth indication information from the first device; wherein the fourth indication information is used to indicate information related to the application of the first model.

[0119] That is to say, the first device can indicate information related to the application of the first model to the second device. Here, the information related to the application of the first model can also be referred to as auxiliary information, conditional information or additional conditional information related to the first model, mainly referring to the solution type, scenario, condition, etc. of the first model application. By transmitting the fourth indication information, the second device determines the model required by the first device, thereby determining the first data and transmitting the first data to the first device. For example, taking the first device as a terminal device and the second device as a network device as an example, the terminal device can send the fourth indication information through UE capability reporting, UE information reporting, RRC message or UCI.

[0120] In other embodiments, before the first device receives the first data from the second device, the method further includes: the first device receiving fourth indication information from the second device; wherein the fourth indication information is used to indicate information related to the application of the first model. Correspondingly, for the second device, before the second device sends the first data to the first device, the method further includes: the second device sending fourth indication information to the first device; wherein the fourth indication information is used to indicate information related to the application of the first model.

[0121] That is, the second device may indicate information related to the application of the first model to the first device. By transmitting the fourth indication information, the first device may use the first model in a specific solution, scenario, or condition based on the information related to the application of the first model. For example, taking the first device as a terminal device and the second device as a network device, the network device may send the fourth indication information via an RRC message or DCI.

[0122] In some embodiments, the information related to the application of the first model includes at least one of the following:

[0123] a solution type for the first task monitored using the first model;

[0124] Application scenario of the first model.

[0125] Exemplarily, the solution type of the first task is, for example, the type of AL / ML model. Specifically, the solution type can be used to characterize whether the first model is a fully connected model, a convolutional neural network model, a recurrent neural network model, or the like.

[0126] Exemplarily, the application scenario of the first model includes, for example, speed information, cell information, transmission configuration information, etc. In other words, the application scenario of the first model can be determined based on one or more of the speed information, cell information, and transmission configuration information, and different speeds, different cells, or different transmission configurations correspond to different application scenarios.

[0127] In some embodiments, before the first device receives the first data from the second device, the method further includes: the first device sending fifth indication information to the second device; wherein the fifth indication information indicates a data ID associated with the first data; the data ID is used by the second device to determine the first data. Correspondingly, for the second device, before the second device sends the first data to the first device, the method further includes: the second device receiving fifth indication information from the first device; wherein the fifth indication information indicates a data ID associated with the first data; the data ID is used by the second device to determine the first data.

[0128] In the above embodiment, the data ID is associated with the first data. Specifically, the data ID can be associated with a specific data type. Based on this, the second device can determine the first data based on the data ID. For example, different types of channel information can be associated with different IDs. When the fifth indication information indicates that the data ID is a first value, the second device can determine that the first data required by the first device is the channel information associated with the first value. The first device indicates the required first data to the second device in the form of a data ID, which can reduce transmission overhead.

[0129] In other embodiments, before the first device receives the first data from the second device, the method further includes: the first device receiving fifth indication information from the second device; wherein the fifth indication information indicates a data ID associated with the first data; and the data ID is used by the first device to determine the first data. Accordingly, for the second device, before the second device sends the first data to the first device, the method further includes: the second device sending fifth indication information to the first device; wherein the fifth indication information indicates a data ID associated with the first data; and the data ID is used by the first device to determine the first data.

[0130] In the above embodiment, the second device indicates to the first device the data ID associated with the first data. Based on this, the first device can determine the data type of the first data. In this way, when the first device receives a message carrying the first data, it can extract the first data from it. In some scenarios, there is no need to specifically send the first data, reducing signaling overhead.

[0131] To facilitate understanding of the technical solutions of the embodiments of the present application, the following provides an application example of the performance monitoring method and the first data therein. In this application example, the first device is a terminal device (UE) and the second device is a network device.

[0132] Figure 8 is a schematic diagram of the application example. Specifically, in the application example, the performance monitoring method includes: the network device indicates / transmits first data (first data set) to the UE, and the first data is used by the UE to build a performance monitoring model related to the first task.

[0133] In this application example, taking the first task including a CSI compression feedback solution based on a dual-end model as an example, a specific example of the first data is provided as follows:

[0134] The first data may be composed of second data and third data. The second data is input information of the performance monitoring model, for example, it may be processed channel information (e.g., compressed, quantized, etc.), specifically in the form of a bit stream of length N. The third data is output information of the performance monitoring model, for example, it may be original channel information (referring to the form of original data obtained through channel estimation) or processed channel information (also referred to as recovered channel information, i.e., channel information in another form that has a mapping relationship with the original channel information).

[0135] Specifically, the third data may be in the following forms:

[0136] The third data may be original channel information. A single sample of the original channel information is composed of a channel data set of dimension M. For example, when M is 2, a single sample of the original channel information is a data set of dimension 2, which is a matrix having P first granularities in the first dimension and Q second granularities in the second dimension (i.e., the matrix is ​​a P-row, Q-column matrix), P and Q may be equal or unequal, and the specific numerical value in the matrix indicates the quality of the channel. For another example, when M is 3, a single sample of the channel data is a data set of dimension 3, which has P first granularities in the first dimension, Q second granularities in the second dimension, and R third granularities in the third dimension. P / Q / R may be equal or unequal, and the specific numerical value in the three-dimensional data set indicates the quality of the channel. For another example, when M is 4, a single sample of channel data is a data set of 4 dimensions, which has P first granularities in the first dimension, Q second granularities in the second dimension, R third granularities in the third dimension, and S fourth granularities in the fourth dimension. P / Q / R / S may be equal or unequal, and the specific numerical values ​​in the four-dimensional data set indicate the quality of the channel.

[0137] The above-mentioned M-dimensional channel data set may include channel data / channel quality related to one or more of the following information. In other words, the M dimensions may be used to represent one or more of the following information, namely:

[0138] (1) Time domain information. This includes time information, delay information, and the number of time domain sampling points. The corresponding time domain information granularity can be a specific time granularity, such as milliseconds or microseconds, or a specific number of time slots, half frames, or frames.

[0139] (2) Frequency domain information, such as frequency information, number of frequency domain sampling points, etc. For example, a specific frequency granularity can be used as the frequency domain information granularity.

[0140] (3) Spatial information. For example, angle information, specifically including incident angle information or other angle information. For example, a specific angle granularity can be used as the spatial information granularity.

[0141] (4) Antenna information. For example, information about the transmitting antenna, receiving antenna, and pairing of the transmitting and receiving antennas. The granularity of the antenna information is the specific antenna granularity or the pairing granularity formed by the pairing method between the transmitting antenna and the receiving antenna.

[0142] (5) Real and imaginary part information of data. For example, when the channel quality information is in the form of a complex number and needs to be represented by a real part and an imaginary part, the real part information and the imaginary part information can be respectively represented by the real part and the imaginary part of the channel information.

[0143] A specific example of the third data is shown in FIG9 . In this example, M=3, which means that the channel data is composed of three dimensions, namely, time domain information p, spatial information q, and real and imaginary part information.

[0144] The third data may also be processed channel information obtained after specific processing of the original channel information. A single sample of the processed channel information is composed of a data set of dimension M, and the data in the data set includes the processed data obtained after specific processing of the original channel information. For example, when M is 2, a single sample of the processed channel information is a processed data set of dimension 2, which is a matrix with P first granularities in the first dimension and Q second granularities in the second dimension. P and Q may be equal or unequal. The specific numerical values ​​in the matrix indicate the processed data representing the quality of the channel. For another example, when M is 3, a single sample of the processed channel information is a data set of dimension 3, which has P first granularities in the first dimension, Q second granularities in the second dimension, and R third granularities in the third dimension. P / Q / R may be equal or unequal. The specific numerical values ​​in this three-dimensional set indicate the processed data representing the quality of the channel.

[0145] The above-mentioned M-dimensional channel data set may include channel data / channel quality related to one or more of the following information. In other words, the M dimensions may be used to represent one or more of the following information, namely:

[0146] (1) Processed channel information (i.e., processed data) of a specific size obtained after a specific mathematical transformation of the channel information, such as processed channel information obtained by methods such as eigendecomposition and vector space mapping.

[0147] (2) Time domain information.

[0148] (3) Frequency domain information.

[0149] (4) Spatial information.

[0150] (5) Antenna information.

[0151] (6) Information on the real and virtual parts of the data.

[0152] Among them, the time domain information, frequency domain information, space information, antenna information, and data real and virtual part information are specifically as described above and will not be repeated here.

[0153] A specific example of the third data is shown in FIG10 , in which M=2, that is, the processed channel information is composed of two dimensions, namely, the channel feature vector of length P obtained after processing, and the real and imaginary parts of the feature vector.

[0154] It can be seen that the form of the above-mentioned first data is different from the form of the data that needs to be transmitted in the model performance monitoring in the related art. The beneficial effect of the embodiment of the present application is mainly to ensure the construction of the local performance monitoring model of the first device through the indication and transmission of the first data set, thereby avoiding the privacy protection and model privatization problems brought about by the second device on the opposite end directly transmitting the actual used model to the first device on the one hand, and on the other hand, avoiding the large amount of data reporting, label reporting, and corresponding transmission and signaling overhead required for performance monitoring on the second device side. Specifically, in the embodiment of the present application, through the indication and transmission of the first data, the first device can locally construct a performance monitoring model equivalent to the actual use model of the second device, so that the results of the performance monitoring model can be used more flexibly and on demand to achieve local performance monitoring.

[0155] FIG11 is a schematic block diagram of a first device 1100 according to an embodiment of the present application. The first device 1100 may include:

[0156] The first communication module 1110 is configured to receive first data from a second device, wherein the first data is used to determine a first model; and the first model is used to perform performance monitoring related to the first task.

[0157] In one embodiment, the first task includes a wireless communication solution based on a second model in the second device.

[0158] In one embodiment, the wireless communication solution is implemented based on the second device using the second model.

[0159] In one embodiment, the wireless communication solution is implemented based on the first device using the third model and the second device using the second model.

[0160] In one embodiment, the first model includes a model having the same function as the second model, and / or a model for outputting performance monitoring indicators.

[0161] In one embodiment, the first data is used to indicate a first model.

[0162] In one embodiment, the first data includes second data and third data used to construct the first model, the second data includes input information of the first model, and the third data includes output information of the first model.

[0163] In one embodiment, the first communication module 1110 is further configured to:

[0164] Sending first indication information to the second device; wherein the first indication information is used to indicate that the first device has the ability to determine the first model.

[0165] In one embodiment, the first communication module 1110 is further configured to:

[0166] Send second indication information to the second device; wherein the second indication information is used to instruct the second device to send the first data.

[0167] In one embodiment, the first communication module 1110 is further configured to:

[0168] Send third indication information to the second device; wherein the third indication information is used to indicate type information of the first data.

[0169] In one embodiment, the first communication module 1110 is further configured to:

[0170] Receive third indication information from the second device; wherein the third indication information is used to indicate type information of the first data.

[0171] In one embodiment, the type information includes at least one of the following:

[0172] Interface type;

[0173] Channel information type;

[0174] Type of measurement information;

[0175] Quantitative information type.

[0176] In one embodiment, the first communication module 1110 is further configured to:

[0177] Send fourth indication information to the second device; wherein the fourth indication information is used to indicate information related to the application of the first model.

[0178] In one embodiment, the first communication module 1110 is further configured to:

[0179] Receive fourth indication information from the second device; wherein the fourth indication information is used to indicate information related to the application of the first model.

[0180] In one embodiment, the information related to the application of the first model includes at least one of the following:

[0181] a solution type for the first task monitored using the first model;

[0182] Application scenario of the first model.

[0183] In one embodiment, the first communication module 1110 is further configured to:

[0184] Send fifth indication information to the second device; wherein the fifth indication information is used to indicate a data identification ID associated with the first data; and the data ID is used by the second device to determine the first data.

[0185] In one embodiment, the first communication module 1110 is further configured to:

[0186] Receive fifth indication information from the second device; wherein the fifth indication information is used to indicate a data ID associated with the first data; and the data ID is used by the first device to determine the first data.

[0187] The first device 1100 of the embodiment of the present application can implement the corresponding functions of the first device in the aforementioned method embodiment. The processes, functions, implementation methods and beneficial effects corresponding to the various modules (sub-modules, units or components, etc.) in the first device 1100 can be found in the corresponding descriptions in the above-mentioned method embodiments, which will not be repeated here. It should be noted that the functions described in the various modules (sub-modules, units or components, etc.) in the first device 1100 of the application embodiment can be implemented by different modules (sub-modules, units or components, etc.) or by the same module (sub-module, unit or component, etc.).

[0188] FIG12 is a schematic block diagram of a second device 1200 according to an embodiment of the present application. The second device 1200 may include:

[0189] The second communication module 1210 is used to send first data to the first device; wherein the first data is used by the first device to determine a first model; and the first model is used by the first device to perform performance monitoring related to the first task.

[0190] In one embodiment, the first task includes a wireless communication solution based on a second model in the second device.

[0191] In one embodiment, the wireless communication solution is implemented based on the second device using the second model.

[0192] In one embodiment, the wireless communication solution is implemented based on the first device using the third model and the second device using the second model.

[0193] In one embodiment, the first model includes a model having the same function as the second model, and / or a model for outputting performance monitoring indicators.

[0194] In one embodiment, the first data is used to indicate a first model.

[0195] In one embodiment, the first data includes second data and third data used to construct the first model, the second data includes input information of the first model, and the third data includes output information of the first model.

[0196] In one embodiment, the second communication module 1210 is further configured to:

[0197] First indication information is received from a first device, wherein the first indication information is used to indicate that the first device has the ability to determine a first model.

[0198] In one embodiment, the second communication module 1210 is further configured to:

[0199] Receive second indication information from the first device; wherein the second indication information is used to instruct the second device to send the first data.

[0200] In one embodiment, the second communication module 1210 is further configured to:

[0201] Receive third indication information from the second device; wherein the third indication information is used to indicate type information of the first data.

[0202] In one embodiment, the second communication module 1210 is further configured to:

[0203] Send third indication information to the first device; wherein the third indication information is used to indicate type information of the first data.

[0204] In one embodiment, the type information includes at least one of the following:

[0205] Interface type;

[0206] Channel information type;

[0207] Type of measurement information;

[0208] Quantitative information type.

[0209] In one embodiment, the second communication module 1210 is further configured to:

[0210] Receive fourth indication information from the first device; wherein the fourth indication information is used to indicate information related to the application of the first model.

[0211] In one embodiment, the second communication module 1210 is further configured to:

[0212] Send fourth indication information to the first device; wherein the fourth indication information is used to indicate information related to the application of the first model.

[0213] In one embodiment, the information related to the application of the first model includes at least one of the following:

[0214] a solution type for the first task monitored using the first model;

[0215] Application scenario of the first model.

[0216] In one embodiment, the second communication module 1210 is further configured to:

[0217] Receive fifth indication information from the first device; wherein the fifth indication information is used to indicate a data ID associated with the first data; and the data ID is used by the second device to determine the first data.

[0218] In one embodiment, the second communication module 1210 is further configured to:

[0219] Send fifth indication information to the first device; wherein the fifth indication information is used to indicate a data ID associated with the first data; the data ID is used by the first device to determine the first data.

[0220] The second device 1200 of the embodiment of the present application can implement the corresponding functions of the second device in the aforementioned method embodiment. The processes, functions, implementation methods and beneficial effects corresponding to the various modules (sub-modules, units or components, etc.) in the second device 1200 can be found in the corresponding descriptions in the above-mentioned method embodiments, which will not be repeated here. It should be noted that the functions described in the various modules (sub-modules, units or components, etc.) in the second device 1200 of the application embodiment can be implemented by different modules (sub-modules, units or components, etc.) or by the same module (sub-module, unit or component, etc.).

[0221] Figure 13 is a schematic structural diagram of a communication device 1300 according to an embodiment of the present application. The communication device 1300 includes a processor 1310, which can call and execute a computer program from a memory to enable the communication device 1300 to implement the method in the embodiment of the present application.

[0222] In one embodiment, the communication device 1300 may further include a memory 1320. The processor 1310 may call and execute a computer program from the memory 1320 to enable the communication device 1300 to implement the method in the embodiment of the present application.

[0223] The memory 1320 may be a separate device independent of the processor 1310 , or may be integrated into the processor 1310 .

[0224] In one embodiment, the communication device 1300 may further include a transceiver 1330 , and the processor 1310 may control the transceiver 1330 to communicate with other devices. Specifically, the transceiver 1330 may send information or data to other devices, or receive information or data sent by other devices.

[0225] The transceiver 1330 may include a transmitter and a receiver. The transceiver 1330 may further include an antenna, and the number of antennas may be one or more.

[0226] In one embodiment, the communication device 1300 may be the second device of the embodiment of the present application, and the communication device 1300 may implement the corresponding processes implemented by the second device in each method of the embodiment of the present application. For the sake of brevity, they will not be repeated here.

[0227] In one embodiment, the communication device 1300 may be the first device of the embodiment of the present application, and the communication device 1300 may implement the corresponding processes implemented by the first device in each method of the embodiment of the present application. For the sake of brevity, they will not be repeated here.

[0228] 14 is a schematic structural diagram of a chip 1400 according to an embodiment of the present application. The chip 1400 includes a processor 1410, which can call and execute a computer program from a memory to implement the method according to the embodiment of the present application.

[0229] In one embodiment, the chip 1400 may further include a memory 1420. The processor 1410 may call and execute a computer program from the memory 1420 to implement the method executed by the first device or the second device in the embodiment of the present application.

[0230] The memory 1420 may be a separate device independent of the processor 1410 , or may be integrated into the processor 1410 .

[0231] In one embodiment, the chip 1400 may further include an input interface 1430. The processor 1410 may control the input interface 1430 to communicate with other devices or chips, and specifically, may obtain information or data sent by other devices or chips.

[0232] In one embodiment, the chip 1400 may further include an output interface 1440. The processor 1410 may control the output interface 1440 to communicate with other devices or chips, and specifically, may output information or data to other devices or chips.

[0233] In one embodiment, the chip can be applied to the first device in the embodiment of the present application, and the chip can implement the corresponding processes implemented by the first device in each method of the embodiment of the present application. For the sake of brevity, it will not be repeated here.

[0234] In one embodiment, the chip can be applied to the second device in the embodiments of the present application, and the chip can implement the corresponding processes implemented by the second device in each method of the embodiments of the present application. For the sake of brevity, they will not be repeated here.

[0235] The chips used in the first device and the second device may be the same chip or different chips.

[0236] It should be understood that the chip mentioned in the embodiments of the present application can also be called a system-level chip, a system chip, a chip system or a system-on-chip chip, etc.

[0237] The processor mentioned above may be a general-purpose processor, a digital signal processor (DSP), a field programmable gate array (FPGA), an application specific integrated circuit (ASIC), or other programmable logic devices, transistor logic devices, discrete hardware components, etc. The general-purpose processor mentioned above may be a microprocessor or any conventional processor, etc.

[0238] The memory mentioned above may be a volatile memory or a non-volatile memory, or may include both volatile and non-volatile memories. The non-volatile memory may be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or a flash memory. The volatile memory may be a random access memory (RAM).

[0239] It should be understood that the above-mentioned memories are exemplary but not restrictive. For example, the memories in the embodiments of the present application may also be static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link dynamic random access memory (SLDRAM), and direct RAM RAM (DR RAM), etc. In other words, the memories in the embodiments of the present application are intended to include, but are not limited to, these and any other suitable types of memories.

[0240] FIG15 is a schematic block diagram of a communication system 1500 according to an embodiment of the present application. The communication system 1500 includes a first device 1100 and a second device 1200 .

[0241] The first device 1100 receives first data from the second device 1200 ; wherein the first data is used by the first device 1100 to determine a first model; and the first model is used by the first device 1100 to perform performance monitoring related to a first task.

[0242] The second device 1200 sends first data to the first device 1100; wherein the first data is used by the first device 1100 to determine a first model; and the first model is used by the first device 1100 to perform performance monitoring related to the first task.

[0243] The first device 1100 can be used to implement the corresponding functions implemented by the first device in the above method, and the second device 1200 can be used to implement the corresponding functions implemented by the second device in the above method. For the sake of brevity, they are not described here in detail.

[0244] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When software is used for implementation, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function in accordance with the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from a website, computer, server or data center by wired (such as coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (such as infrared, wireless, microwave, etc.) mode to another website, computer, server or data center. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more available media integrations. The available medium may be a magnetic medium (eg, a floppy disk, a hard disk, a magnetic tape), an optical medium (eg, a DVD), or a semiconductor medium (eg, a solid state disk (SSD)).

[0245] It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0246] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0247] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any modifications or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in the present application should be included within the scope of protection of the present application. Therefore, the scope of protection of the present application should be based on the scope of protection of the claims.

Claims

1. A performance monitoring method, comprising: A first device receives first data from a second device; wherein, the first data is used by the first device to determine a first model; the first model is used by the first device to perform performance monitoring related to a first task.

2. The method according to claim 1, wherein, The first task includes a wireless communication solution based on a second model in the second device.

3. The method according to claim 2, wherein, The wireless communication solution is implemented based on the second device using the second model.

4. The method according to claim 2, wherein, The wireless communication solution is implemented based on the first device using a third model and the second device using the second model.

5. The method according to any one of claims 2-4, wherein, The first model includes a model having the same function as the second model, and / or a model for outputting performance monitoring metrics.

6. The method according to any one of claims 1-5, wherein, The first data is used to indicate the first model.

7. The method according to any one of claims 1-5, wherein, The first data includes second data and third data for constructing the first model, the second data includes input information of the first model, and the third data includes output information of the first model.

8. The method according to any one of claims 1-7, wherein, Before the first device receives the first data from the second device, the method further includes: The first device sends first indication information to the second device; wherein, the first indication information is used to indicate that the first device has the ability to determine the first model.

9. The method according to any one of claims 1-8, wherein, Before the first device receives the first data from the second device, the method further includes: The first device sends second indication information to the second device; wherein, the second indication information is used to indicate the second device to send the first data.

10. The method according to any one of claims 1-9, wherein, Before the first device receives the first data from the second device, the method further includes: The first device sends third indication information to the second device; wherein, the third indication information is used to indicate the type information of the first data.

11. The method according to any one of claims 1-9, wherein, Before the first device receives the first data from the second device, the method further includes: The first device receives third indication information from the second device; wherein, the third indication information is used to indicate the type information of the first data.

12. The method according to claim 10 or 11, wherein, The type information includes at least one of the following: Interface type; Channel information type; Measurement information type; Quantization information type.

13. The method according to any one of claims 1-12, wherein, Before the first device receives the first data from the second device, the method further includes: The first device sends fourth indication information to the second device; wherein, the fourth indication information is used to indicate information related to the application of the first model.

14. The method according to any one of claims 1-12, wherein, Before the first device receives the first data from the second device, the method further includes: The first device receives fourth indication information from the second device; wherein, the fourth indication information is used to indicate information related to the application of the first model.

15. The method according to claim 13 or 14, wherein, The information related to the application of the first model includes at least one of the following: The scenario type of the first task monitored by using the first model; The application scenario of the first model.

16. The method according to any one of claims 1-15, wherein, Before the first device receives the first data from the second device, the method further includes: The first device sends fifth indication information to the second device; wherein, the fifth indication information is used to indicate the data identification ID associated with the first data; the data ID is used for the second device to determine the first data.

17. The method according to any one of claims 1-15, wherein, Before the first device receives the first data from the second device, the method further includes: The first device receives fifth indication information from the second device; wherein, the fifth indication information is used to indicate the data ID associated with the first data; the data ID is used for the first device to determine the first data.

18. A performance monitoring method, including: The second device sends first data to the first device; wherein, the first data is used for the first device to determine a first model; the first model is used for the first device to perform performance monitoring related to a first task.

19. The method according to claim 18, wherein, The first task includes a wireless communication solution based on a second model in the second device.

20. The method according to claim 19, wherein, The wireless communication solution is implemented based on the second device using the second model.

21. The method according to claim 19, wherein, The wireless communication solution is implemented based on the first device using a third model and the second device using the second model.

22. The method according to any one of claims 19-21, wherein, The first model includes a model having the same function as the second model, and / or, a model for outputting performance monitoring metrics.

23. The method according to any one of claims 18-22, wherein, The first data is used to indicate the first model.

24. The method according to any one of claims 18-22, wherein, The first data includes second data and third data for constructing the first model, the second data includes input information of the first model, and the third data includes output information of the first model.

25. The method according to any one of claims 18-24, wherein, before the second device sends the first data to the first device, the method further includes: the second device receives first indication information from the first device; wherein, the first indication information is used to indicate that the first device has the ability to determine the first model.

26. The method according to any one of claims 18-25, wherein, before the second device sends the first data to the first device, the method further includes: the second device receives second indication information from the first device; wherein, the second indication information is used to indicate that the second device sends the first data.

27. The method according to any one of claims 18-26, wherein, before the second device sends the first data to the first device, the method further includes: the second device receives third indication information from the second device; wherein, the third indication information is used to indicate type information of the first data.

28. The method according to any one of claims 18-26, wherein, before the second device sends the first data to the first device, the method further includes: the second device sends third indication information to the first device; wherein, the third indication information is used to indicate type information of the first data.

29. The method according to claim 27 or 28, wherein, the type information includes at least one of the following: interface type; channel information type; measurement information type; quantization information type.

30. The method according to any one of claims 18-29, wherein, before the second device sends the first data to the first device, the method further includes: the second device receives fourth indication information from the first device; wherein, the fourth indication information is used to indicate information related to the application of the first model.

31. The method according to any one of claims 18-29, wherein, before the second device sends the first data to the first device, the method further includes: the second device sends fourth indication information to the first device; wherein, the fourth indication information is used to indicate information related to the application of the first model.

32. The method according to claim 30 or 31, wherein, the information related to the application of the first model includes at least one of the following: the scheme type of the first task monitored by using the first model; the application scenario of the first model.

33. The method according to any one of claims 18-32, wherein, before the second device sends the first data to the first device, the method further includes: The second device receives fifth indication information from the first device; wherein, the fifth indication information is used to indicate the data ID associated with the first data; the data ID is used by the second device to determine the first data.

34. The method according to any one of claims 18 - 32, wherein, before the second device sends the first data to the first device, the method further includes: The second device sends fifth indication information to the first device; wherein, the fifth indication information is used to indicate the data ID associated with the first data; the data ID is used by the first device to determine the first data.

35. A first device, comprising: A first communication module, configured to receive first data from a second device; wherein, the first data is used to determine a first model; the first model is used to perform performance monitoring related to a first task.

36. The first device according to claim 35, wherein, The first task includes a wireless communication solution based on a second model in the second device.

37. The first device according to claim 36, wherein, The wireless communication solution is implemented based on the second device using the second model.

38. The first device according to claim 36, wherein, The wireless communication solution is implemented based on the first device using a third model and the second device using the second model.

39. The first device according to any one of claims 36 - 38, wherein, The first model includes a model having the same function as the second model, and / or a model for outputting performance monitoring metrics.

40. The first device according to any one of claims 35 - 39, wherein, The first data is used to indicate the first model.

41. The first device according to any one of claims 35 - 39, wherein, The first data includes second data and third data for constructing the first model, the second data includes input information of the first model, and the third data includes output information of the first model.

42. The first device according to any one of claims 35 - 41, wherein, The first communication module is further configured to: Send first indication information to the second device; wherein, the first indication information is used to indicate that the first device has the ability to determine the first model.

43. The first device according to any one of claims 35 - 42, wherein, The first communication module is further configured to: Send second indication information to the second device; wherein, the second indication information is used to indicate the second device to send the first data.

44. The first device according to any one of claims 35 - 43, wherein, The first communication module is further configured to: Send third indication information to the second device; wherein, the third indication information is used to indicate the type information of the first data.

45. The first device according to any one of claims 35 - 43, wherein, The first communication module is further configured to: Receive third indication information from the second device; wherein, the third indication information is used to indicate the type information of the first data.

46. The first device according to claim 44 or 45, wherein, the type information includes at least one of the following: Interface type; Channel information type; Measurement information type; Quantization information type.

47. The first device according to any one of claims 35-46, wherein, the first communication module is further configured to: Send fourth indication information to the second device; wherein, the fourth indication information is used to indicate information related to the application of the first model.

48. The first device according to any one of claims 35-46, wherein, the first communication module is further configured to: Receive fourth indication information from the second device; wherein, the fourth indication information is used to indicate information related to the application of the first model.

49. The first device according to claim 47 or 48, wherein, the information related to the application of the first model includes at least one of the following: The scheme type of the first task monitored by using the first model; The application scenario of the first model.

50. The first device according to any one of claims 35-49, wherein, the first communication module is further configured to: Send fifth indication information to the second device; wherein, the fifth indication information is used to indicate the data identification ID associated with the first data; the data ID is used for the second device to determine the first data.

51. The first device according to any one of claims 35-49, wherein, the first communication module is further configured to: Receive fifth indication information from the second device; wherein, the fifth indication information is used to indicate the data ID associated with the first data; the data ID is used for the first device to determine the first data.

52. A second device, comprising: A second communication module, configured to send first data to a first device; wherein, the first data is used for the first device to determine a first model; the first model is used for the first device to perform performance monitoring related to a first task.

53. The second device according to claim 52, wherein, the first task includes a wireless communication solution based on a second model in the second device.

54. The second device according to claim 53, wherein, the wireless communication solution is implemented based on the second device using the second model.

55. The second device according to claim 53, wherein, the wireless communication solution is implemented based on the first device using a third model and the second device using the second model.

56. The second device according to any one of claims 53-55, wherein, the first model includes a model having the same function as the second model, and / or, a model for outputting performance monitoring metrics.

57. The second device according to any one of claims 52-56, wherein, the first data is used to indicate the first model.

58. The second device according to any one of claims 52-56, Among them, the first data includes second data and third data for constructing the first model, the second data includes input information of the first model, and the third data includes output information of the first model.

59. The second device according to any one of claims 52 - 59, wherein, the second communication module is further configured to: receive first indication information from the first device; wherein, the first indication information is used to indicate that the first device has the ability to determine the first model.

60. The second device according to any one of claims 52 - 59, wherein, the second communication module is further configured to: receive second indication information from the first device; wherein, the second indication information is used to indicate that the second device sends the first data.

61. The second device according to any one of claims 52 - 60, wherein, the second communication module is further configured to: receive third indication information from the second device; wherein, the third indication information is used to indicate type information of the first data.

62. The second device according to any one of claims 52 - 60, wherein, the second communication module is further configured to: send third indication information to the first device; wherein, the third indication information is used to indicate type information of the first data.

63. The second device according to claim 61 or 62, wherein, the type information includes at least one of the following: interface type; channel information type; measurement information type; quantization information type.

64. The second device according to any one of claims 52 - 63, wherein, the second communication module is further configured to: receive fourth indication information from the first device; wherein, the fourth indication information is used to indicate information related to the application of the first model.

65. The second device according to any one of claims 52 - 63, wherein, the second communication module is further configured to: send fourth indication information to the first device; wherein, the fourth indication information is used to indicate information related to the application of the first model.

66. The second device according to claim 64 or 65, wherein, the information related to the application of the first model includes at least one of the following: the scheme type of the first task monitored by using the first model; the application scenario of the first model.

67. The second device according to any one of claims 52 - 66, wherein, the second communication module is further configured to: receive fifth indication information from the first device; wherein, the fifth indication information is used to indicate the data ID associated with the first data; the data ID is used for the second device to determine the first data.

68. The second device according to any one of claims 52 - 66, wherein, the second communication module is further configured to: send fifth indication information to the first device; wherein, the fifth indication information is used to indicate the data ID associated with the first data; the data ID is used for the first device to determine the first data.

69. A first device, comprising: A transceiver, a processor, and a memory. The memory is used to store a computer program. The transceiver is used to communicate with other devices. The processor is used to call and run the computer program stored in the memory so that the first device receives first data from the second device. Wherein, the first data is used for the first device to determine a first model. The first model is used for the first device to perform performance monitoring related to a first task.

70. The first device according to claim 69, wherein, the first task includes a wireless communication solution based on a second model in the second device.

71. The first device according to claim 70, wherein, the wireless communication solution is implemented based on the second device using the second model.

72. The first device according to claim 70, wherein, the wireless communication solution is implemented based on the first device using a third model and the second device using the second model.

73. The first device according to any one of claims 70-72, wherein, the first model includes a model having the same function as the second model, and / or a model for outputting performance monitoring metrics.

74. The first device according to any one of claims 69-73, wherein, the first data is used to indicate the first model.

75. The first device according to any one of claims 69-73, wherein, the first data includes second data and third data for constructing the first model. The second data includes input information of the first model. The third data includes output information of the first model.

76. The first device according to any one of claims 69-75, wherein, the processor is further used to cause the first device to perform: sending first indication information to the second device. Wherein, the first indication information is used to indicate that the first device has the ability to determine the first model.

77. The first device according to any one of claims 69-76, wherein, the processor is further used to cause the first device to perform: sending second indication information to the second device. Wherein, the second indication information is used to indicate the second device to send the first data.

78. The first device according to any one of claims 69-77, wherein, the processor is further used to cause the first device to perform: sending third indication information to the second device. Wherein, the third indication information is used to indicate the type information of the first data.

79. The first device according to any one of claims 69-77, wherein, the processor is further used to cause the first device to perform: receiving third indication information from the second device. Wherein, the third indication information is used to indicate the type information of the first data.

80. The first device according to claim 78 or 79, wherein, the type information includes at least one of the following: interface type; channel information type; measurement information type; quantization information type.

81. The first device according to any one of claims 69 - 80, wherein, the processor is further configured to cause the first device to perform: sending fourth indication information to the second device; wherein, the fourth indication information is used to indicate information related to the application of the first model.

82. The first device according to any one of claims 69 - 80, wherein, the processor is further configured to cause the first device to perform: receiving fourth indication information from the second device; wherein, the fourth indication information is used to indicate information related to the application of the first model.

83. The first device according to claim 81 or 82, wherein, the information related to the application of the first model includes at least one of the following: the scenario type of the first task monitored by using the first model; the application scenario of the first model.

84. The first device according to any one of claims 69 - 83, wherein, the processor is further configured to cause the first device to perform: sending fifth indication information to the second device; wherein, the fifth indication information is used to indicate the data identification ID associated with the first data; the data ID is used for the second device to determine the first data.

85. The first device according to any one of claims 69 - 83, wherein, the processor is further configured to cause the first device to perform: receiving fifth indication information from the second device; wherein, the fifth indication information is used to indicate the data ID associated with the first data; the data ID is used for the first device to determine the first data.

86. A second device, comprising: a transceiver, a processor, and a memory, the memory is used to store a computer program, the transceiver is used to communicate with other devices, and the processor is used to call and run the computer program stored in the memory, so that the second device sends first data to a first device; wherein, the first data is used for the first device to determine a first model; the first model is used for the first device to perform performance monitoring related to a first task.

87. The second device according to claim 86, wherein, the first task includes a wireless communication solution based on a second model in the second device.

88. The second device according to claim 87, wherein, the wireless communication solution is implemented based on the second device using the second model.

89. The second device according to claim 87, wherein, the wireless communication solution is implemented based on the first device using a third model and the second device using the second model.

90. The second device according to any one of claims 87 - 89, wherein, the first model includes a model having the same function as the second model, and / or, a model for outputting performance monitoring metrics.

91. The second device according to any one of claims 86 - 90, wherein, the first data is used to indicate the first model.

92. The second device according to any one of claims 86 - 90, wherein, The first data includes second data and third data for constructing the first model, the second data includes input information of the first model, and the third data includes output information of the first model.

93. The second device according to any one of claims 86-92, wherein the processor is further configured to cause the second device to perform: Receiving first indication information from the first device; Wherein, The first indication information is used to indicate that the first device has the ability to determine the first model.

94. The second device according to any one of claims 86-93, Wherein, The processor is further configured to cause the second device to perform: Receiving second indication information from the first device; wherein the second indication information is used to indicate that the second device sends the first data.

95. The second device according to any one of claims 86-94, Wherein, The processor is further configured to cause the second device to perform: Receiving third indication information from the second device; wherein the third indication information is used to indicate type information of the first data.

96. The second device according to any one of claims 86-94, Wherein, The processor is further configured to cause the second device to perform: Sending third indication information to the first device; wherein the third indication information is used to indicate type information of the first data.

97. The second device according to claim 95 or 96, Wherein, The type information includes at least one of the following: Interface type; Channel information type; Measurement information type; Quantization information type.

98. The second device according to any one of claims 86-97, Wherein, The processor is further configured to cause the second device to perform: Receiving fourth indication information from the first device; wherein the fourth indication information is used to indicate information related to the application of the first model.

99. The second device according to any one of claims 86-97, Wherein, The processor is further configured to cause the second device to perform: Sending fourth indication information to the first device; wherein the fourth indication information is used to indicate information related to the application of the first model.

100. The second device according to claim 98 or 99, Wherein, The information related to the application of the first model includes at least one of the following: The scheme type of the first task monitored by using the first model; The application scenario of the first model.

101. The second device according to any one of claims 86-100, Wherein, The processor is further configured to cause the second device to perform: Receiving fifth indication information from the first device; wherein the fifth indication information is used to indicate the data ID associated with the first data; the data ID is used for the second device to determine the first data.

102. The second device according to any one of claims 86-100, Wherein, The processor is further configured to cause the second device to perform: Send fifth indication information to the first device; wherein, the fifth indication information is used to indicate the data ID associated with the first data; the data ID is used for the first device to determine the first data.

103. A chip, comprising: A processor, configured to call and run a computer program from a memory, so that a device installed with the chip executes the method according to any one of claims 1 to 17.

104. A chip, comprising: A processor, configured to call and run a computer program from a memory, so that a device installed with the chip executes the method according to any one of claims 18 to 34.

105. A computer-readable storage medium, configured to store a computer program, and when the computer program is run by a device, the device executes the method according to any one of claims 1 to 17.

106. A computer-readable storage medium, configured to store a computer program, and when the computer program is run by a device, the device executes the method according to any one of claims 18 to 34.

107. A computer program product, comprising computer program instructions, and the computer program instructions cause a computer to execute the method according to any one of claims 1 to 17.

108. A computer program product, comprising computer program instructions, and the computer program instructions cause a computer to execute the method according to any one of claims 18 to 34.

109. A computer program, the computer program causes a computer to execute the method according to any one of claims 1 to 17.

110. A computer program, the computer program causes a computer to execute the method according to any one of claims 18 to 34.

111. A communication system, comprising: A first device, configured to execute the method according to any one of claims 1 to 17; A second device, configured to execute the method according to any one of claims 18 to 34.

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