Communication method and communication device

Abstract

The invention provides a communication method and communication equipment. The method comprises the following steps: a first communication device judges whether first channel data is valid or invalid; wherein under the condition that the first channel data is valid, the first channel data can be used for training the first model, and under the condition that the first channel data is invalid, the first channel data cannot be used for training the first model. The data used for training the first model is screened, and the first channel data can be used for training the first model only when the first channel data is valid. It can be understood that for the training of the first model, the quality of valid channel data is higher than that of invalid channel data. Therefore, based on the method provided by the invention, the low-quality part in the channel data can be effectively filtered out, and the first model is trained by using the channel data with relatively high quality, so that the training effect and performance of the first model are improved.

Description

Communication method and communication device Technical Field

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

[0002] Artificial intelligence (AI) technology in wireless communications requires not only data, but also clean, high-quality data. However, wireless communication systems themselves, particularly the physical layer, are most susceptible to external environmental influences. Directly collected physical layer data, such as channel data, often contains significant noise and exhibits variable quality. Using low-quality channel data directly for model training or tuning can negatively impact model performance.

[0003] Summary of the Invention

[0004] The present application provides a communication method and a communication device. The following introduces various aspects involved in the present application.

[0005] In a first aspect, a communication method is provided, comprising: a first communication device determining whether first channel data is valid or invalid; wherein, when the first channel data is valid, the first channel data can be used to train a first model, and when the first channel data is invalid, the first channel data cannot be used to train the first model.

[0006] According to a second aspect, a communication method is provided, comprising: a second communication device sending first configuration information to a first communication device; wherein, the first configuration information is used to configure the content and / or parameters of a first condition, and when the first channel data satisfies the first condition, the first channel data is valid, and when the first channel data is valid, the first channel data can be used to train a first model, and when the first channel data is invalid, the first channel data cannot be used to train the first model.

[0007] According to a third aspect, a communication device is provided, which is a first communication device, and includes: a judgment unit for judging whether first channel data is valid or invalid; wherein, when the first channel data is valid, the first channel data can be used to train the first model, and when the first channel data is invalid, the first channel data cannot be used to train the first model.

[0008] In a fourth aspect, a communication device is provided, which is a second communication device, and the communication device includes: a second sending unit, used to send first configuration information to the first communication device; wherein the first configuration information is used to configure the content and / or parameters of the first condition, and when the first channel data meets the first condition, the first channel data is valid, and when the first channel data is valid, the first channel data can be used to train the first model, and when the first channel data is invalid, the first channel data cannot be used to train the first model.

[0009] In a fifth aspect, a communication device is provided, comprising a processor and a memory, wherein the memory is used to store one or more computer programs, and the processor is used to call the computer program in the memory so that the terminal device executes part or all of the steps in the methods of the above aspects.

[0010] In a sixth aspect, an embodiment of the present application provides a communication system, which includes the above-mentioned communication device. In another possible design, the system may also include other devices that interact with the communication device in the solution provided in the embodiment of the present application.

[0011] In a seventh aspect, an embodiment of the present application provides a computer-readable storage medium, which stores a computer program, and the computer program enables a communication device to execute part or all of the steps in the methods of the above aspects.

[0012] In an eighth aspect, embodiments of the present application provide a computer program product, wherein the computer program product includes a non-transitory computer-readable storage medium storing a computer program, wherein the computer program is operable to cause a communication device to perform some or all of the steps of the methods described in each of the above aspects. In some implementations, the computer program product may be a software installation package.

[0013] In a ninth aspect, an embodiment of the present application provides a chip comprising a memory and a processor, wherein the processor can call and run a computer program from the memory to implement some or all of the steps described in the methods of the above aspects.

[0014] The data used to train the first model is screened. The first channel data can only be used to train the first model if the first channel data is valid. It is understood that for training the first model, valid channel data is of higher quality than invalid channel data. Therefore, based on the method provided in this application, low-quality channel data can be effectively filtered out, and higher-quality channel data can be used to train the first model, thereby improving the training effect and performance of the first model. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] FIG1 is a schematic diagram of a wireless communication system used in an embodiment of the present application.

[0016] FIG2 is a schematic flowchart of a communication method provided in an embodiment of the present application.

[0017] FIG3A and FIG3B are diagrams respectively showing examples of distribution of power of different channel data in the delay domain.

[0018] FIG4 is a schematic flowchart of another communication method provided in an embodiment of the present application.

[0019] FIG5 is a schematic flowchart of another communication method provided in an embodiment of the present application.

[0020] FIG6 is an example diagram of a method for determining whether the power distribution of first channel data meets a condition provided in the present application.

[0021] FIG7 is a schematic structural diagram of a communication device provided in an embodiment of the present application.

[0022] FIG8 is a schematic structural diagram of another communication device provided in an embodiment of the present application.

[0023] FIG9 is a schematic structural diagram of a device for communication provided in an embodiment of the present application. DETAILED DESCRIPTION

[0024] The technical solution in this application will be described below with reference to the accompanying drawings.

[0025] Communication System

[0026] Figure 1 illustrates a wireless communication system 100 used in an embodiment of the present application. The wireless communication system 100 may include communication devices. For example, the communication devices may include a network device 110 or a terminal device 120. The network device 110 may be a device that communicates with the terminal device 120. The network device 110 may provide communication coverage for a specific geographic area and may communicate with the terminal device 120 within the coverage area.

[0027] FIG1 exemplarily shows a network device and two terminals. Optionally, the wireless communication system 100 may include multiple network devices and each network device may include other numbers of terminal devices within its coverage area, which is not limited in the embodiments of the present application.

[0028] Optionally, the wireless communication system 100 may further include other network entities such as a network controller and a mobility management entity, which is not limited in the embodiment of the present application.

[0029] It should be understood that the technical solutions of the embodiments of the present application can be applied to various communication systems, such as: fifth generation (5G) system or new radio (NR), long term evolution (LTE) system, LTE frequency division duplex (FDD) system, LTE time division duplex (TDD), etc. The technical solutions provided in this application can also be applied to future communication systems, such as the sixth generation mobile communication system, satellite communication system, etc.

[0030] The terminal device in the embodiments of the present application may also be referred to as user equipment (UE), access terminal, user unit, user station, mobile station, mobile station (MS), mobile terminal (MT), remote station, remote terminal, mobile device, user terminal, terminal, wireless communication device, user agent or user device. The terminal device in the embodiments of the present application may refer to a device that provides voice and / or data connectivity to a user and can be used to connect people, objects and machines, such as a handheld device with wireless connection function, a vehicle-mounted device, etc. The terminal device in the embodiments of the present application can be a mobile phone, a tablet computer, a laptop computer, a PDA, a mobile internet device (MID), a wearable device, a virtual reality (VR) device, an augmented reality (AR) device, a wireless terminal in industrial control, a wireless terminal in self-driving, a wireless terminal in remote medical surgery, a wireless terminal in a smart grid, a wireless terminal in transportation safety, a wireless terminal in a smart city, a wireless terminal in a smart home, etc. Optionally, the UE can be used to act as a base station. For example, the UE can act as a scheduling entity that provides sidelink signals between UEs in vehicle-to-everything (V2X) or device-to-device (D2D). For example, a cellular phone and a car communicate with each other using sidelink signals. The cellular phone and smart home devices communicate without relaying the communication signal through a base station.

[0031] The network device in the embodiments of the present application may be a device for communicating with a terminal device, and may also be referred to as an access network device or a radio access network device. For example, the network device may be a base station. The network device in the embodiments of the present application may refer to a radio access network (RAN) node (or device) that connects a terminal device to a wireless network. A base station may broadly cover various names as follows, or be replaced with the following names, such as: NodeB, evolved NodeB (eNB), next generation NodeB (gNB), relay station, access point, transmitting and receiving point (TRP), transmitting point (TP), master eNB (MeNB), secondary eNB (SeNB), multi-standard radio (MSR) node, home base station, network controller, access node, wireless node, access point (AP), transmission node, transceiver node, baseband unit (BBU), remote radio unit (RRU), active antenna unit (AAU), remote radio head (RRH), central unit (CU), distributed unit (DU), positioning node, etc. A base station may be a macro base station, a micro base station, a relay node, a donor node, or the like, or a combination thereof. A base station may also refer to a communication module, modem, or chip used to be set in the aforementioned device or apparatus. A base station may also be a mobile switching center and a device that performs base station functions in D2D, V2X, and machine-to-machine (M2M) communications, a network-side device in a 6G network, or a device that performs base station functions in future communication systems. A base station may support networks with the same or different access technologies. The embodiments of this application do not limit the specific technology and specific device form adopted by the network equipment.

[0032] Base stations can be fixed or mobile. For example, a helicopter or drone can be configured to act as a mobile base station, and one or more cells can move based on the location of the mobile base station. In other examples, a helicopter or drone can be configured to act as a device that communicates with another base station.

[0033] In some deployments, the network device in the embodiments of the present application may refer to a CU or a DU, or the network device may include a CU and a DU. The gNB may also include an AAU.

[0034] The network equipment and terminal devices can be deployed on land, including indoors or outdoors, handheld or vehicle-mounted; they can also be deployed on water; they can also be deployed in the air on aircraft, balloons, and satellites. The embodiments of this application do not limit the scenarios in which the network equipment and terminal devices are located.

[0035] It should be understood that all or part of the functions of the communication device in this application can also be implemented through software functions running on hardware, or through virtualization functions instantiated on a platform (such as a cloud platform).

[0036] AI

[0037] In recent years, artificial intelligence (AI) technology has sparked a wave of technological innovation in human society. Deep learning, a key research direction in AI, leverages the powerful nonlinear fitting capabilities of deep artificial neural network models to successfully solve a range of previously intractable problems. In particular, deep learning has been successfully applied in computer vision and natural language processing, even demonstrating performance superior to that of humans. However, unlike traditional engineering solutions, which primarily rely on algorithms, AI technology is highly dependent on data. The availability and quality of data significantly impact the ultimate performance of AI algorithms. For example, the concept of convolutional neural networks was proposed in the 1980s and 1990s, but for a long time, it received little attention. It wasn't until 2012, using the large-scale image dataset ImageNet, that convolutional neural networks achieved a remarkable breakthrough in image recognition. Today, acquiring and constructing large-scale, high-quality datasets is crucial for applying AI in any field. Data is the very foundation of AI. The more data, and the higher the quality, the greater the potential of AI.

[0038] Data cleaning can standardize the collected raw data to improve data quality and, in turn, enhance the effectiveness of AI model training. Specifically, the most basic logic of data cleaning is to identify abnormal samples from the raw data and perform processing such as deletion and replacement. For example, in the field of computer vision, abnormal data can be identified and cleaned through subjective judgment by the human eye or based on some objective evaluation indicators of image quality. Objective evaluation indicators can include, for example, image blur, brightness, color difference, etc. Similar to the field of computer vision, in the field of natural language, abnormal data can be screened and identified based on subjective judgment or objective rules such as grammar and format.

[0039] Wireless communication system based on AI technology

[0040] Future wireless communication systems will evolve towards higher throughput, lower latency, higher reliability, greater number of connections, and improved spectrum utilization. Recent research has demonstrated that AI technology has significant application potential in many areas, including complex environment modeling and learning, complex signal processing, and prediction. This is expected to promote the evolution and transformation of future communication paradigms, thereby spurring the rapid development of wireless AI technology. For example, within the 3rd Generation Partnership Project (3GPP) Release 18 standardization, a study item was established to research and discuss the integration of AI technology into the physical layer of wireless communication systems. This research focuses on use cases such as channel state information (CSI) feedback, beam management, and high-precision positioning. As in other AI application areas, the quantity and quality of datasets are key factors influencing AI performance in wireless communications. Wireless communication systems are undoubtedly data-intensive. Millions of system devices, billions of mobile devices, and, in the future, tens of billions of IoT devices, generate massive amounts of data constantly. Directly using this data for model training can lead to numerous problems.

[0041] The quality of collected physical layer data is affected by the wireless environment in which the data collection device operates. For example, when physical layer data is collected directly by a terminal device, its quality is significantly affected by the wireless environment in which the terminal device operates. For example, for some terminal devices with poor channel quality, the data collected may contain a significant amount of noise. Directly training or tuning a model using this noisy data may hinder performance.

[0042] Therefore, AI technology in the wireless communications field requires not only data but also clean, high-quality data. However, the wireless communications system itself, particularly the physical layer, is most susceptible to external environmental influences. Directly collected physical layer data, such as wireless channel data (also known as channel data or channel samples), often contains significant noise and has variable quality.

[0043] Wireless channel data implicitly contains rich environmental information, and therefore it will be used in solving many wireless communication physical layer problems using AI. For example, potential AI use cases such as CSI feedback, channel estimation, and positioning may all use channel data during model training. For downlink channel measurements, it is often necessary for the network device to configure and send a reference signal (RS), and then the terminal device to detect the RS to complete the channel measurement and obtain wireless channel data. However, in the channel data measured by the terminal device, there may be some poor quality channel data due to reasons such as measurement position, angle, and poor RS detection effect. Since the form of the channel data itself is ever-changing and disorganized, these poor quality channel data do not have explicit physical meaning.

[0044] FIG2 is a schematic flow chart of a communication method provided in an embodiment of the present application to solve the above problem. The method shown in FIG2 may include step S210.

[0045] Step S210: The first communication device determines whether the first channel data is valid or invalid.

[0046] The first communication device may obtain one or more channel data, and the first channel data may be any one of the one or more channel data. In some embodiments, the first channel data may also be referred to as a first channel sample.

[0047] If the first channel data is valid, the first channel data can be used to train the first model. If the first channel data is invalid, the first channel data cannot be used to train the first model. It is understood that if the first channel data is determined to be valid, the first channel data may be of higher quality; if the first channel data is determined to be invalid, the first channel data may be of lower quality. In other words, based on step S210, the first communications device can clean the first channel data.

[0048] The data used to train the first model is screened. The first channel data can only be used to train the first model if the first channel data is valid. It is understood that for training the first model, valid channel data is of higher quality than invalid channel data. Therefore, based on the method provided in this application, low-quality channel data can be effectively filtered out, and higher-quality channel data can be used to train the first model, thereby improving the training effect and performance of the first model.

[0049] In some embodiments, the first communication device may receive first indication information. The first indication information may be used to indicate whether the first communication device determines whether the first channel data is valid or invalid. In other words, the first indication information may be used to indicate whether the first communication device performs step S210. For example, the first indication information may include an indication of "yes / no" or "on / off". If step S210 does not need to be performed, the first indication information may indicate "off" or "no", and the first communication device may not perform a judgment on whether the first channel data is valid or invalid. If step S210 needs to be performed, the first indication information may indicate "on" or "yes", and the first communication device may not perform a judgment on whether the first channel data is valid or invalid.

[0050] As described above, step S210 actually performs data cleaning on the first channel data. Therefore, in some embodiments, the first indication information may also be referred to as data cleaning indication information.

[0051] The first indication information may be sent by a second communication device. The second communication device may be, for example, a network device. The second communication device may determine whether to request the first communication device based on how the first channel data is used and / or specific requirements, thereby flexibly controlling the first communication device to perform data scrubbing. In some embodiments, the first indication information may be included in the first configuration information.

[0052] Unlike fields like computer vision and natural language processing, wireless physical layer data is difficult to identify anomalies through subjective judgment. Furthermore, there are no mature, standardized, objective evaluation metrics for determining data validity. This application proposes that the validity or invalidity of first channel data can be determined based on a first condition.

[0053] In some embodiments, if the first channel data satisfies a first condition, the first channel data may be valid. The first condition may be related to one or more of the following information: a first indicator, and power distribution of the first channel data.

[0054] The first indicator may be determined based on the RS corresponding to the first channel data. The RS corresponding to the first channel data may be the RS measured to determine the first channel data. Through the RS, the first communication device may measure the first channel data and calculate the first indicator.

[0055] The first indicator may be, for example, one or more of the following indicators: reference signal received power (RSRP), reference signal receiving quality (RSRQ), and received signal strength indicator (RSSI).

[0056] The first indicator may reflect the channel condition and / or the reception effect of the reference signal. For example, the larger the first indicator is, the better the channel condition is and / or the better the reception effect of the reference signal is.

[0057] In some embodiments, the first channel data may be determined to be valid when the first indicator is greater than or equal to a threshold value of the first indicator. Specifically, the first condition may include the first indicator being greater than or equal to the threshold value of the first indicator. In other words, the first channel data may be valid when the channel conditions are good and / or the reference signal reception effect is good. In this case, the measured first channel data may be suitable for training the first model.

[0058] In some embodiments, if the first indicator is less than or equal to a threshold value of the first indicator, the first channel data may be determined to be invalid. In other words, if the channel condition is poor and / or the reference signal reception effect is poor, the measured first channel data may be submerged in noise and unsuitable for training the first model.

[0059] This application does not limit the specific value of the threshold of the first indicator. For example, the threshold of the first indicator can be: -80dBm, -70dBm or -60dBm, etc.

[0060] The power distribution of the first channel data can be used to reflect the energy distribution of different signal transmission paths in the first channel data. For example, the power distribution is the distribution of power in the delay domain. In some embodiments, the delay domain can also be called the time domain.

[0061] In some embodiments, the first channel data may be in the frequency dimension, and the first channel data may be transformed from the frequency domain to the delay domain. For example, the first channel data may be transformed to the delay domain by inverse fast Fourier transform (IFFT).

[0062] In a simple transmission environment, such as one with a line-of-sight (LOS) transmission path, the power distribution will be relatively concentrated. In a complex transmission environment, such as one with only a non-line-of-sight (NLOS) transmission path, the power distribution will be relatively dispersed. The first condition may include: the power distribution of the first channel data is relatively concentrated. That is, if the power distribution or energy distribution of the first channel data is concentrated, the first channel data may be valid.

[0063] Figures 3A and 3B respectively show examples of the power distribution of different channel data in the delay domain. The power distribution in Figure 3A is concentrated and shows a clear pattern, indicating that the channel data clearly reflects the channel characteristics. The power distribution in Figure 3B is chaotic, indicating that the channel data is heavily affected by noise and has poor quality.

[0064] If the power distribution of the first channel data is relatively concentrated, the first channel data conforms to the basic distribution pattern and can be used to train the first model. If the power distribution of the first channel data is too dispersed, the first channel data lacks the basic distribution pattern and may be invalid channel measurement data, and thus cannot be used to train the first model. The following example illustrates how to determine whether the power distribution of the first channel data is concentrated.

[0065] In some embodiments, the first channel data may include multiple sampling points, and some of the sampling points in the first channel data may constitute a first group of sampling points. The sum of the powers of the first group of sampling points may be a first power, that is, the sum of the powers of the sampling points in the first group of sampling points may be the first power. When the proportion of the first power to the total power of the first channel data is greater than or equal to a first threshold, it can be determined that the power distribution of the first channel data is concentrated. In other words, the first condition may include: the proportion of the first power to the total power of the first channel data is greater than or equal to the first threshold. It can be understood that if the proportion of the first power is large, it can be said that the power distribution of the first channel data is concentrated in the first group of sampling points, that is, it can be considered that the power distribution of the first channel data is concentrated.

[0066] In some embodiments, some sampling points in the first channel data may constitute a second group of sampling points. The sampling points in the second group of sampling points may be different from the sampling points in the first group of sampling points. The sum of the powers of the second group of sampling points may be a second power, that is, the sum of the powers of the sampling points in the second group of sampling points may be the second power. When the proportion of the second power to the total power of the first channel data is less than or equal to the second threshold, it can be determined that the power distribution of the first channel data is concentrated. That is, the first condition may include: the proportion of the second power to the total power of the first channel data is less than or equal to the second threshold. It can be understood that if the proportion of the second power is small, it can be explained that the power distribution of the first channel data is concentrated on sampling points other than the second group of sampling points, that is, the power distribution of the first channel data is concentrated.

[0067] The present application does not limit the specific value of the first threshold or the second threshold. For example, the first threshold or the second threshold can be one of 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 0.95, 0.99, etc.

[0068] As an implementation, the power of each of the first group of sampling points may be greater than or equal to the power of the sampling points other than the first group of sampling points in the first channel data. That is, in terms of latency, if the sampling points in the first channel data are sorted from highest to lowest based on power, the first group of sampling points may be the first one or more sampling points in the reordered sampling points in the first channel data.

[0069] The number of sampling points in the first group of sampling points can satisfy, in terms of latency, the following: the number is M or the percentage of all sampling points in the first channel data is N. Both M and N can be numbers greater than 0. For example, in the case where the sampling points in the first channel data are sorted from highest to lowest based on power, the first group of sampling points can be the first M or the first N percentage of the reordered sampling points in the first channel data.

[0070] As an implementation, the power of each of the second group of sampling points may be less than or equal to the power of the sampling points in the first channel data other than the second group of sampling points. That is, in terms of latency, if the sampling points in the first channel data are sorted from highest to lowest based on power, the second group of sampling points may be one or more of the last sampling points in the reordered first channel data.

[0071] The number of sampling points in the second group of sampling points can satisfy, in terms of latency, a number P or a percentage Q of all sampling points in the first channel data. Both P and Q can be numbers greater than 0. After sorting the sampling points in the first channel data from highest to lowest power, the second group of sampling points can be the last P or the last Q percentage of the reordered sampling points in the first channel data.

[0072] This application does not limit the specific values ​​of M, N, P, or Q. For example, the value of M or P can be one of 32, 64, 96, 128, 160, etc. For example, the value of N or Q can be one of 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 0.95, 0.99, etc.

[0073] This application does not limit the method for obtaining the first and second groups of sampling points. For example, in the delay dimension, the sampling points in the first channel data can be sorted by power to determine the first and / or second groups of sampling points. The sorting method can be, for example, large to small as described above, or small to large. The method for determining the first and / or second groups of sampling points by sorting from small to large is similar to that by sorting from large to small, and will not be further described in this application.

[0074] It should be noted that, in the delay dimension, the sampling point can also be called the delay sampling point.

[0075] In some embodiments, the method shown in FIG. 2 may further include step S205 .

[0076] In step S205 , the first communication device may receive first configuration information.

[0077] The first configuration information can be used to configure the content and / or parameters of the first condition. In other words, the first configuration information can be used to configure conditions and / or indicators related to data cleaning.

[0078] The first condition may include, for example, the information related to the first condition described above. As an implementation, the first configuration information may be used to configure the first condition to be associated with the first indicator and / or the power distribution of the first channel data. For example, the first condition may include: the first indicator being greater than or equal to a threshold of the first indicator; and / or the power distribution of the first channel data being concentrated.

[0079] The parameters of the first condition may include any one or more of the parameters related to the first condition described above. For example, the parameters of the first condition may include: a threshold of the first indicator, a first threshold, a second threshold, one or more of M, N, P, and Q. As an implementation, the first configuration information may be used to indicate that the first condition is related to the first indicator, and may be used to configure which specific first indicator or indicators the first condition is related to. In addition, the first configuration information may also be used to further configure a threshold value for the first indicator.

[0080] The first configuration information may be sent by the second communication device described above. In other words, the content and / or parameters of the first condition may be configured by the second communication device. The second communication device may flexibly control the extent of data scrubbing based on how the first channel data is used, actual needs, and the like.

[0081] The first configuration information can be carried in one or more of the following messages: radio resource control (RRC) message, broadcast message, medium access control element (MAC CE), downlink control information (DCI), etc.

[0082] This application does not limit the operation of the first communication device on the first channel data after data cleaning.

[0083] As an implementation, if the first channel data is valid, the first communications device may transmit the first channel data. A recipient of the first channel data may train the first model based on the first channel data. If the first channel data is invalid, the first communications device may not transmit the first channel data. In this case, the first communications device may not need to upload the invalid channel data, thereby avoiding wasting uplink transmission resources.

[0084] This application does not limit the message that carries the first channel data. For example, the first channel data can be carried through RRC signaling and / or a physical uplink shared channel (PUSCH).

[0085] As an implementation, when the first channel data is valid, the first communications device may train the first model based on the first channel data. In some cases, such as when the first communications device is a terminal device, the training of the first model by the first communications device may be fine-tuning of the first model. When the first channel data is invalid, the first communications device may not train the first model based on the first channel data. Locally training the first model based on valid first channel data can effectively improve the performance of the first model, thereby avoiding the adverse effects of invalid data on the performance of the first model.

[0086] It should be noted that, when the first channel data is invalid, this application does not limit the processing method for the first channel data. For example, the first communication device may discard or delete the invalid first channel data, that is, not use the first channel data to perform the operation performed when the first channel data is valid. Alternatively, the first communication device may replace the invalid first channel data. Alternatively, the first communication device may process the invalid first channel data so that the processed first channel data satisfies the first condition.

[0087] The first channel data can be acquired by the first communications device. That is, the first communications device can perform data collection to acquire the first communications data. In some embodiments, the second communications device can send second configuration information to the first communications device. The second configuration information can be used to instruct the first communications device to perform channel measurement. For example, the second configuration information can be used to configure the RS. Based on the RS, the first communications device can perform a channel measurement process to acquire the first channel data. Figure 4 illustrates the first channel data collection process, using the first communications device as a terminal device and the second communications device as a network device as an example.

[0088] The method shown in FIG. 4 may include step S410 and step S420 .

[0089] In step S410, the terminal device receives the second configuration information. Correspondingly, the network device sends the second configuration information.

[0090] The second configuration information can be used to configure the RS. The network device configures the RS through the second configuration information so that the terminal device can collect the first channel data.

[0091] Step S420: The terminal device receives the RS. Correspondingly, the network device sends the RS.

[0092] The network device may send the RS according to the second configuration information. The terminal device may receive or detect the RS according to the second configuration information.

[0093] In step S430, the terminal device completes channel measurement based on the detected RS. Based on the channel measurement process in step S430, the terminal device can collect first channel data.

[0094] For ease of understanding, the communication method provided by the embodiment of the present application is described below with reference to Figure 5. The first communication device may be the terminal device in Figure 5, and the second communication device may be the network device in Figure 5. The method shown in Figure 5 may include steps S510 to S560.

[0095] Step S510: The terminal device receives first configuration information sent by the network device.

[0096] The first configuration information can be used to configure the content and / or parameters of the first condition. The first condition is related to data cleaning. In other words, the first configuration information can be used to configure data cleaning related conditions and / or indicators.

[0097] The first configuration information may include data cleaning instruction information. The data cleaning instruction information is used to instruct the terminal device whether to perform data cleaning.

[0098] Step S520: The terminal device receives second configuration information sent by the network device. The second configuration information can be used to configure the RS.

[0099] In step S530, the network device sends an RS according to the second configuration. The RS is used by the terminal device to complete the collection and cleaning of the first channel data.

[0100] In step S540 , the terminal device completes channel measurement based on the detected RS, thereby collecting first channel data.

[0101] The terminal device can determine whether to perform data cleaning based on the data cleaning instruction information. If data cleaning is not required, the terminal device can directly send the first channel data to the network device and / or use the first channel data to fine-tune the first model. If data cleaning is required, the terminal device can determine whether each channel data or sample is valid or invalid based on the first condition indicated by the network device. Channel data that meets the first condition can be determined to be valid; channel data that does not meet the first condition can be determined to be invalid.

[0102] The first condition may include, for example, one or more of the following conditions: the first indicator is greater than or equal to a threshold value of the first indicator; the power distribution of the first channel data meets the condition. The first configuration information may configure one or more of the above conditions to belong to the first condition and the corresponding threshold value.

[0103] The first indicator may include: one or more of RSRP, RSRQ, and RSSI. When the channel condition is too bad or the RS reception effect is poor, the measured first channel data may be submerged in the noise and unsuitable for training the first model. The network device may specify a specific threshold value X for the first indicator in the first configuration information. X may be, for example, -80dBm, -70dBm, or -60dBm. When the first indicators corresponding to the first channel data are all greater than or equal to X, the first channel data may be determined to be valid. In the case where the first indicator corresponding to the first channel data is less than or equal to X, the first channel data may be discarded.

[0104] FIG6 exemplarily shows the steps of determining whether the power distribution of the first channel data satisfies the conditions.

[0105] Step 1: Convert the first channel data from the frequency domain to the delay domain using IFFT. There are no strict restrictions on whether additional mathematical processing is performed on the antenna dimensions.

[0106] Step 2: Reorder the samples by energy within the delay domain. This is explained below using the order of largest to smallest as an example. It is understood that the order of smallest to largest can also be used, and the first condition can be adjusted accordingly. This application will not elaborate further.

[0107] Step 3: For the reordered first channel data, determine whether the first channel data is valid according to the first condition and indicator parameters configured in the first configuration information. The first condition may include, for example, one or more of conditions 1 to 4. Conditions 1 to 4 are all related to the power ratio of some sampling points in the first channel data.

[0108] Condition 1: In the latency dimension, the power of the first N sampling points corresponding to the first channel data and its proportion to the total power of the sample is greater than a first threshold Y. Both N and Y are configurable by the network device. N and Y indicate a ratio. For example, N and Y can be any of 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 0.95, and 0.99.

[0109] Condition 2: In the delay dimension, the power of the first M sampling points of the first channel data and its proportion to the total power of the first channel data is greater than a first threshold Y. Both M and Y can be configured by the network device. M can be used to indicate the number of sampling points. The value of M can be, for example, 32, 64, 96, 128, or 160. Y can be used to indicate a ratio. The value of Y can be, for example, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 0.95, or 0.99.

[0110] Condition 3: In the latency dimension, the power of the last Q portion of the first channel data and its proportion to the total power of the first channel data are less than a second threshold, Z. Both Q and Z can be configured by the network device. Both Q and Z can be used to indicate a ratio. For example, the values ​​of Q and Z can be 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 0.95, or 0.99.

[0111] Condition 4: In the latency dimension, the power of the last P sampling points on the first channel data and its proportion to the total energy of the first channel data is less than a second threshold Z. Both P and Z can be configured by the network device. P can indicate the number of sampling points. The value of P can be, for example, 32, 64, 96, 128, 160, etc. Z can indicate a ratio. The value of Z can be, for example, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 0.95, or 0.99.

[0112] In the case where it is determined that the first channel data is valid, the method shown in FIG5 may include step S560.

[0113] Step S560 may include step S561 and / or step S562.

[0114] Step S561: The terminal device fine-tunes the first model based on the valid first channel data.

[0115] Step S562: The terminal device sends valid first channel data to the network device. For example, the first channel data may be carried by RRC signaling or PUSCH.

[0116] It should be noted that the first model described herein may be a model for communication. For example, the first model may include one or more of a channel state information feedback model, a beam management model, and a high-precision positioning model. In some embodiments, the first model may be an AI model. For example, the first model may include a machine learning model. Alternatively, the first model may include a neural network model.

[0117] The method embodiment of the present application is described in detail above in conjunction with Figures 1 to 6 , and the device embodiment of the present application is described in detail below in conjunction with Figures 7 to 9 . It should be understood that the description of the method embodiment corresponds to the description of the device embodiment, and therefore, for portions not described in detail, reference can be made to the above method embodiment.

[0118] FIG7 is a schematic structural diagram of a communication device 700 provided in an embodiment of the present application. The communication device 700 is a first communication device and includes a determination unit 710 .

[0119] The judgment unit 710 is used to judge whether the first channel data is valid or invalid; wherein, when the first channel data is valid, the first channel data can be used to train the first model; when the first channel data is invalid, the first channel data cannot be used to train the first model.

[0120] In some embodiments, the first channel data is valid if it satisfies a first condition, and the first condition is related to one or more of the following information: a first indicator, which is determined based on a reference signal corresponding to the first channel data; and power distribution of the first channel data.

[0121] In some embodiments, the first indicator includes one or more of the following indicators: RSRP, RSRQ, RSSI.

[0122] In some embodiments, the power distribution is the distribution of power in the delay domain.

[0123] In some embodiments, when the first condition is related to the power distribution, the first condition includes one or more of the following: the proportion of the first power to the total power of the first channel data is greater than or equal to a first threshold; the proportion of the second power to the total power of the first channel data is less than or equal to a second threshold; wherein the first power is the sum of the powers of a first group of sampling points in the first channel data, and the second power is the sum of the powers of a second group of sampling points in the first channel data.

[0124] In some embodiments, the power of the first group of sampling points is greater than or equal to the power of the sampling points other than the first group of sampling points in the first channel data, and the number of the first group of sampling points satisfies, in terms of delay, the following conditions: the number is M or the proportion of all sampling points in the first channel data is N; the power of the second group of sampling points is less than or equal to the power of the sampling points other than the second group of sampling points in the first channel data, and the number of the second group of sampling points satisfies, in terms of delay, the number is P or the proportion of all sampling points in the first channel data is Q.

[0125] In some embodiments, the communication device 700 further includes: a first receiving unit, configured to receive first configuration information; wherein the first configuration information is used to configure the content and / or parameters of the first condition.

[0126] In some embodiments, when the first channel data is valid, the communication device 700 further includes: a first sending unit for sending the first channel data; and / or a training unit for training the first model based on the first channel data.

[0127] In some embodiments, the communication device 700 further includes: a second receiving unit, configured to receive first indication information, where the first indication information is used to indicate whether the first communication device determines whether the first channel data is valid or invalid.

[0128] In some embodiments, the first model is an AI model.

[0129] FIG8 is a schematic structural diagram of a communication device 800 provided in an embodiment of the present application. The communication device 800 is a second communication device and may include a second sending unit 810.

[0130] The second sending unit 810 is used to send first configuration information to the first communication device; wherein, the first configuration information is used to configure the content and / or parameters of the first condition. When the first channel data meets the first condition, the first channel data is valid. When the first channel data is valid, the first channel data can be used to train the first model. When the first channel data is invalid, the first channel data cannot be used to train the first model.

[0131] In some embodiments, the first condition is related to one or more of the following information: a first indicator, which is determined based on a reference signal corresponding to the first channel data; and power distribution of the first channel data.

[0132] In some embodiments, the first indicator includes one or more of the following indicators: RSRP, RSRQ, RSSI.

[0133] In some embodiments, the power distribution is the distribution of power in the delay domain.

[0134] In some embodiments, when the first condition is related to the power distribution, the first condition includes one or more of the following: the proportion of the first power to the total power of the first channel data is greater than or equal to a first threshold; the proportion of the second power to the total power of the first channel data is less than or equal to a second threshold; wherein the first power is the sum of the powers of a first group of sampling points in the first channel data, and the second power is the sum of the powers of a second group of sampling points in the first channel data.

[0135] In some embodiments, the power of the first group of sampling points is greater than or equal to the power of the sampling points other than the first group of sampling points in the first channel data, and the number of the first group of sampling points satisfies, in terms of delay, the following conditions: the number is M or the proportion of all sampling points in the first channel data is N; the power of the second group of sampling points is less than or equal to the power of the sampling points other than the second group of sampling points in the first channel data, and the number of the second group of sampling points satisfies, in terms of delay, the number is P or the proportion of all sampling points in the first channel data is Q.

[0136] In some embodiments, when the first channel data is valid, the communication device further includes: a third receiving unit, configured to receive the first channel data.

[0137] In some embodiments, the communication device 800 further includes: a third sending unit, configured to send first indication information to the first communication device, wherein the first indication information is used to indicate to the first communication device whether to determine whether the first channel data is valid or invalid.

[0138] In some embodiments, the first model is an AI model.

[0139] In an optional embodiment, the second sending unit 810 may be a transceiver 930, and the determining unit 720 may be a processor 910. The communication device 700 or the communication device 800 may further include a memory 920, as specifically shown in FIG9 .

[0140] Figure 9 is a schematic block diagram of a communication device according to an embodiment of the present application. The dashed lines in Figure 9 indicate that the unit or module is optional. The device 900 can be used to implement the method described in the above method embodiment. The device 900 can be a chip, a terminal device, or a network device.

[0141] The device 900 may include one or more processors 910. The processor 910 may support the device 900 to implement the method described in the method embodiment above. The processor 910 may be a general-purpose processor or a special-purpose processor. For example, the processor may be a central processing unit (CPU). Alternatively, the processor may be another general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic device, discrete hardware component, etc. The general-purpose processor may be a microprocessor or the processor may be any conventional processor, etc.

[0142] The apparatus 900 may further include one or more memories 920. The memories 920 store programs that can be executed by the processor 910, causing the processor 910 to perform the methods described in the above method embodiments. The memories 920 may be independent of the processor 910 or integrated into the processor 910.

[0143] The apparatus 900 may further include a transceiver 930. The processor 910 may communicate with other devices or chips via the transceiver 930. For example, the processor 910 may transmit and receive data with other devices or chips via the transceiver 930.

[0144] The present application also provides a computer-readable storage medium for storing a program. The computer-readable storage medium can be applied to a terminal or network device provided in the present application, and the program enables a computer to execute the method performed by the terminal or network device in each embodiment of the present application.

[0145] The present application also provides a computer program product. The computer program product includes a program. The computer program product can be applied to a terminal or network device provided in the present application, and the program causes a computer to execute the method performed by the terminal or network device in each embodiment of the present application.

[0146] The embodiments of the present application also provide a computer program. The computer program can be applied to the terminal or network device provided in the embodiments of the present application, and the computer program enables a computer to execute the method performed by the terminal or network device in each embodiment of the present application.

[0147] It should be understood that the terms "system" and "network" in this application can be used interchangeably. In addition, the terms used in this application are only used to explain the specific embodiments of this application and are not intended to limit this application. The terms "first", "second", "third", and "fourth" in the specification and claims of this application and the accompanying drawings are used to distinguish different objects rather than to describe a specific order. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions.

[0148] In the embodiments of this application, the term "indication" may refer to a direct indication, an indirect indication, or an indication of an association. For example, "A indicates B" may refer to a direct indication of B, e.g., B can obtain information through A; it may refer to an indirect indication of B, e.g., A indicates C, e.g., B can obtain information through C; or it may refer to an association between A and B.

[0149] In the embodiment of the present application, "B corresponding to A" means that B is associated with A and B can be determined based on A. However, it should be understood that determining B based on A does not mean determining B based solely on A, but B can also be determined based on A and / or other information.

[0150] In 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 indication, configuration and configuration, etc.

[0151] In the embodiments of the present application, "pre-definition" or "pre-configuration" may be implemented by pre-storing corresponding codes, tables, or other methods that can be used to indicate relevant information in a device (e.g., a terminal device and a network device). The present application does not limit the specific implementation method. For example, pre-definition may refer to information defined in a protocol.

[0152] In the embodiments of the present application, the “protocol” may refer to a standard protocol in the communications field, for example, it may include an LTE protocol, an NR protocol, and related protocols used in future communication systems, and the present application does not limit this.

[0153] In the embodiments of this application, the term "and / or" is simply a description of the association relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this document generally indicates that the related objects are in an "or" relationship.

[0154] In 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.

[0155] In the several embodiments provided in this application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are merely schematic. For example, the division of the units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0156] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0157] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0158] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. 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 one website, computer, server or data center to another website, computer, server or data center via a wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) method. The computer-readable storage medium can be any available medium that can be read by a computer or a data storage device such as a server or data center that includes one or more available media integrated therein. The available medium may be a magnetic medium (eg, a floppy disk, a hard disk, a magnetic tape), an optical medium (eg, a digital versatile disc (DVD)), or a semiconductor medium (eg, a solid state disk (SSD)).

[0159] 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 changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in 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 communication method, characterized in that: The method comprises: The first communication device determines whether the first channel data is valid or invalid; In which, when the first channel data is valid, the first channel data can be used to train the first model; when the first channel data is invalid, the first channel data cannot be used to train the first model.

2. The method according to claim 1, characterized in that If the first channel data satisfies a first condition, the first channel data is valid, and the first condition is related to one or more of the following information: a first indicator, where the first indicator is determined based on a reference signal corresponding to the first channel data; The power distribution of the first channel data.

3. The method according to claim 2, characterized in that The first indicator includes one or more of the following indicators: reference signal received power RSRP, reference signal received quality RSRQ, and received signal strength indication RSSI.

4. The method according to claim 2 or 3, characterized in that The power distribution is the distribution of power in the delay domain.

5. The method according to any one of claims 2 to 4, characterized in that When the first condition is related to the power distribution situation, the first condition includes one or more of the following: A proportion of the first power to the total power of the first channel data is greater than or equal to a first threshold; A proportion of the second power to the total power of the first channel data is less than or equal to a second threshold; The first power is the sum of powers of a first group of sampling points in the first channel data, and the second power is the sum of powers of a second group of sampling points in the first channel data.

6. The method according to claim 5, characterized in that The powers of the first group of sampling points are all greater than or equal to the powers of the sampling points other than the first group of sampling points in the first channel data, and the number of the first group of sampling points satisfies, in terms of delay, the following conditions: the number is M or the proportion of all sampling points in the first channel data is N; The power of the second group of sampling points is less than or equal to the power of the sampling points other than the second group of sampling points in the first channel data, and the number of the second group of sampling points satisfies, in the delay dimension: the number is P or the proportion of all sampling points in the first channel data is Q.

7. The method according to any one of claims 2 to 6, characterized in that Also includes: The first communication device receives first configuration information; The first configuration information is used to configure the content and / or parameters of the first condition.

8. The method according to any one of claims 1 to 7, characterized in that When the first channel data is valid, the method further includes: The first communication device sends the first channel data; and / or, Based on the first channel data, the first communications device trains the first model.

9. The method according to any one of claims 1 to 8, characterized in that Also includes: The first communication device receives first indication information, where the first indication information is used to indicate whether the first communication device determines whether first channel data is valid or invalid.

10. The method according to any one of claims 1 to 9, characterized in that The first model is an artificial intelligence AI model.

11. A communication method, characterized in that: The method comprises: The second communication device sends first configuration information to the first communication device; In which, the first configuration information is used to configure the content and / or parameters of the first condition. When the first channel data meets the first condition, the first channel data is valid. When the first channel data is valid, the first channel data can be used to train the first model. When the first channel data is invalid, the first channel data cannot be used to train the first model.

12. The method according to claim 11, characterized in that The first condition is related to one or more of the following information: a first indicator, where the first indicator is determined based on a reference signal corresponding to the first channel data; The power distribution of the first channel data.

13. The method according to claim 12, characterized in that The first indicator includes one or more of the following indicators: reference signal received power RSRP, reference signal received quality RSRQ, and received signal strength indication RSSI.

14. The method according to claim 12 or 13, characterized in that The power distribution is the distribution of power in the delay domain.

15. The method according to any one of claims 12 to 14, characterized in that When the first condition is related to the power distribution situation, the first condition includes one or more of the following: A proportion of the first power to the total power of the first channel data is greater than or equal to a first threshold; A proportion of the second power to the total power of the first channel data is less than or equal to a second threshold; The first power is the sum of powers of a first group of sampling points in the first channel data, and the second power is the sum of powers of a second group of sampling points in the first channel data.

16. The method according to claim 15, characterized in that The powers of the first group of sampling points are all greater than or equal to the powers of the sampling points other than the first group of sampling points in the first channel data, and the number of the first group of sampling points satisfies, in terms of delay, the following conditions: the number is M or the proportion of all sampling points in the first channel data is N; The power of the second group of sampling points is less than or equal to the power of the sampling points other than the second group of sampling points in the first channel data, and the number of the second group of sampling points satisfies, in the delay dimension: the number is P or the proportion of all sampling points in the first channel data is Q.

17. The method according to any one of claims 11 to 16, characterized in that When the first channel data is valid, the method further includes: The second communication device receives the first channel data.

18. The method according to any one of claims 11 to 17, characterized in that Also includes: The second communication device sends first indication information to the first communication device, where the first indication information is used to indicate to the first communication device whether to determine whether the first channel data is valid or invalid.

19. The method according to any one of claims 11 to 18, characterized in that The first model is an artificial intelligence AI model.

20. A communication device, characterized in that: The communication device is a first communication device, and the communication device includes: a judging unit, configured to judge whether the first channel data is valid or invalid; In which, when the first channel data is valid, the first channel data can be used to train the first model; when the first channel data is invalid, the first channel data cannot be used to train the first model.

21. The communication device according to claim 20, wherein: If the first channel data satisfies a first condition, the first channel data is valid, and the first condition is related to one or more of the following information: a first indicator, where the first indicator is determined based on a reference signal corresponding to the first channel data; The power distribution of the first channel data.

22. The communication device according to claim 21, wherein: The first indicator includes one or more of the following indicators: reference signal received power RSRP, reference signal received quality RSRQ, and received signal strength indication RSSI.

23. The communication device according to claim 21 or 22, characterized in that The power distribution is the distribution of power in the delay domain.

24. The communication device according to any one of claims 21 to 23, characterized in that: When the first condition is related to the power distribution situation, the first condition includes one or more of the following: A proportion of the first power to the total power of the first channel data is greater than or equal to a first threshold; A proportion of the second power to the total power of the first channel data is less than or equal to a second threshold; The first power is the sum of powers of a first group of sampling points in the first channel data, and the second power is the sum of powers of a second group of sampling points in the first channel data.

25. The communication device according to claim 24, characterized in that The powers of the first group of sampling points are all greater than or equal to the powers of the sampling points other than the first group of sampling points in the first channel data, and the number of the first group of sampling points satisfies, in terms of delay, the following conditions: the number is M or the proportion of all sampling points in the first channel data is N; The power of the second group of sampling points is less than or equal to the power of the sampling points other than the second group of sampling points in the first channel data, and the number of the second group of sampling points satisfies, in the delay dimension: the number is P or the proportion of all sampling points in the first channel data is Q.

26. The communication device according to any one of claims 21 to 25, characterized in that: Also includes: A first receiving unit, configured to receive first configuration information; The first configuration information is used to configure the content and / or parameters of the first condition.

27. The communication device according to any one of claims 20 to 26, characterized in that: When the first channel data is valid, the communication device further includes: a first sending unit, configured to send the first channel data; and / or, A training unit is used to train the first model based on the first channel data.

28. The communication device according to any one of claims 20 to 27, characterized in that: Also includes: The second receiving unit is configured to receive first indication information, where the first indication information is used to indicate whether the first communication device determines whether the first channel data is valid or invalid.

29. The communication device according to any one of claims 20 to 28, characterized in that: The first model is an artificial intelligence AI model.

30. A communication device, characterized in that: The communication device is a second communication device, and the communication device includes: A second sending unit, configured to send first configuration information to the first communication device; In which, the first configuration information is used to configure the content and / or parameters of the first condition. When the first channel data meets the first condition, the first channel data is valid. When the first channel data is valid, the first channel data can be used to train the first model. When the first channel data is invalid, the first channel data cannot be used to train the first model.

31. The communication device according to claim 30, wherein: The first condition is related to one or more of the following information: a first indicator, where the first indicator is determined based on a reference signal corresponding to the first channel data; The power distribution of the first channel data.

32. The communication device according to claim 31, wherein The first indicator includes one or more of the following indicators: reference signal received power RSRP, reference signal received quality RSRQ, and received signal strength indication RSSI.

33. The communication device according to claim 31 or 32, characterized in that The power distribution is the distribution of power in the delay domain.

34. The communication device according to any one of claims 31 to 33, characterized in that When the first condition is related to the power distribution situation, the first condition includes one or more of the following: A proportion of the first power to the total power of the first channel data is greater than or equal to a first threshold; A proportion of the second power to the total power of the first channel data is less than or equal to a second threshold; The first power is the sum of powers of a first group of sampling points in the first channel data, and the second power is the sum of powers of a second group of sampling points in the first channel data.

35. The communication device according to claim 34, characterized in that The powers of the first group of sampling points are all greater than or equal to the powers of the sampling points other than the first group of sampling points in the first channel data, and the number of the first group of sampling points satisfies, in terms of delay, the following conditions: the number is M or the proportion of all sampling points in the first channel data is N; The power of the second group of sampling points is less than or equal to the power of the sampling points other than the second group of sampling points in the first channel data, and the number of the second group of sampling points satisfies, in the delay dimension: the number is P or the proportion of all sampling points in the first channel data is Q.

36. The communication device according to any one of claims 30 to 35, characterized in that: When the first channel data is valid, the communication device further includes: The third receiving unit is configured to receive the first channel data.

37. The communication device according to any one of claims 30 to 36, characterized in that: Also includes: The third sending unit is configured to send first indication information to the first communication device, where the first indication information is used to indicate to the first communication device whether to determine whether the first channel data is valid or invalid.

38. The communication device according to any one of claims 30 to 37, characterized in that: The first model is an artificial intelligence AI model.

39. A communication device, characterized in that: The communication device comprises a memory and a processor, wherein the memory is used to store a program, and the processor is used to call the program in the memory so as to enable the communication device to execute the method according to any one of claims 1 to 19.

40. A device, characterized in that The device comprises a processor configured to call a program from a memory so as to enable the device to execute the method according to any one of claims 1 to 19.

41. A chip, characterized in that: The device comprises a processor configured to call a program from a memory so that a device equipped with the chip executes the method according to any one of claims 1 to 19.

42. A computer-readable storage medium, characterized in that A program is stored thereon, the program causing a computer to execute the method according to any one of claims 1 to 19.

43. A computer program product, characterized in that The method comprises a program for causing a computer to execute the method according to any one of claims 1 to 19.

44. A computer program, characterized in that The computer program causes a computer to execute the method according to any one of claims 1 to 19.

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