Communication method and device

Abstract

The present application relates to a communication method and a device. The method comprises: a first device sends first information, the first information being used for determining second information on the basis of a first processing scheme in a second device. According to embodiments of the present application, by means of the first information, the second device can be driven to determine the second information on the basis of the first processing scheme, so that the performance of the first processing scheme is determined.

Description

Communication method and device Technical Field

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

[0002] Artificial intelligence (AI)-based solutions are increasingly being used in wireless communication systems. Performance testing of AI solutions for wireless communication systems can serve as a basis for network adoption and application consideration. Wireless communication system testing solutions typically require hardware support from test equipment.

[0003] Summary of the Invention

[0004] Embodiments of the present application provide a communication method and device that can simplify the testing of processing solutions in a communication system.

[0005] An embodiment of the present application provides a communication method, including:

[0006] The first device sends first information, and the first information is used to determine second information in the second device based on a first processing solution.

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

[0008] The second device receives the first information;

[0009] The second device determines second information from the first information based on the first processing scheme.

[0010] An embodiment of the present application provides a first device, including:

[0011] The sending unit is configured to send first information, where the first information is used to determine second information in the second device based on the first processing solution.

[0012] An embodiment of the present application provides a second device, including:

[0013] a receiving unit, configured to receive first information;

[0014] A processing unit is configured to determine second information according to the first information based on a first processing scheme.

[0015] An embodiment of the present application provides a communication 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 execute the computer program stored in the memory so that the communication device performs the above-mentioned communication method.

[0016] An embodiment of the present application provides a chip for implementing the above-mentioned communication method.

[0017] 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 communication method.

[0018] An embodiment of the present application provides a computer-readable storage medium for storing a computer program, which, when executed by a device, enables the device to execute the above-mentioned communication method.

[0019] An embodiment of the present application provides a computer program product, including computer program instructions, which enable a computer to execute the above-mentioned communication method.

[0020] An embodiment of the present application provides a computer program, which, when executed on a computer, enables the computer to execute the above-mentioned communication method.

[0021] In an embodiment of the present application, the first information can drive the second device to determine the second information based on the first processing solution, and then determine the performance of the first processing solution. BRIEF DESCRIPTION OF THE DRAWINGS

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

[0023] FIG2A is a schematic diagram of the CSI feedback problem.

[0024] FIG2B is a schematic diagram of the channel estimation problem.

[0025] FIG2C is a schematic diagram of the positioning problem.

[0026] FIG2D is a schematic diagram of the beam management problem.

[0027] FIG3 is a schematic flowchart of a communication method according to an embodiment of the present application.

[0028] FIG4 is a schematic flowchart of a communication method according to another embodiment of the present application.

[0029] FIG5 is a schematic flowchart of a communication method according to another embodiment of the present application.

[0030] FIG6 is a schematic flowchart of a communication method according to an embodiment of the present application.

[0031] FIG7 is a schematic flowchart of a communication method according to another embodiment of the present application.

[0032] FIG8 is a schematic flowchart of a communication method according to another embodiment of the present application.

[0033] FIG9 is a first schematic diagram of data interaction between a first device and a second device.

[0034] FIG10 is a second schematic diagram of data interaction between the first device and the second device.

[0035] FIG11 is a schematic block diagram of a first device according to an embodiment of the present application.

[0036] FIG12 is a schematic block diagram of a second device according to an embodiment of the present application.

[0037] FIG13 is a schematic block diagram of a communication device according to an embodiment of the present application.

[0038] FIG14 is a schematic block diagram of a chip according to an embodiment of the present application.

[0039] FIG15 is a schematic block diagram of a communication system according to an embodiment of the present application. DETAILED DESCRIPTION

[0040] 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.

[0041] 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.

[0042] 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.

[0043] 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.

[0044] 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.

[0045] 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.

[0046] 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.

[0047] 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.).

[0048] 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.

[0049] 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.

[0050] 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.

[0051] 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.

[0052] 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.

[0053] 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.

[0054] 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.

[0055] 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.

[0056] 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.

[0057] 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.

[0058] 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.

[0059] 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.

[0060] 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.

[0061] AI-based solutions have a variety of applications in wireless communication systems. For example, AI can be used to implement CSI feedback, as shown in Figure 2A. By introducing an AI encoder and an AI decoder, AI-based CSI information compression and feedback can be achieved. Another example is channel estimation, as shown in Figure 2B. High-performance estimation of a given channel can be achieved through an AI channel estimator. Another example is positioning, as shown in Figure 2C. AI-based positioning algorithms rely on positioning channel information to obtain high-precision positioning results. Another example is beam management, as shown in Figure 2D. Based on known beam information, AI-based beam management algorithms can be used to obtain preferred or more refined beam information, or to predict beam information for future times.

[0062] For AI-based wireless communication solutions, the evaluation and treatment of performance assurance issues of these solutions also need to be considered during actual application.

[0063] For example, for the CSI feedback problem, in actual systems, the performance of CSI compression, recovery, or CSI prediction solutions based on artificial intelligence / machine learning (AI / ML) is often different in different scenarios, different data, different inputs, and different usage conditions. Therefore, it is necessary to monitor and judge the performance of the CSI compression, recovery, or prediction solution based on AI / ML. When the above solution works well, the above solution can be used. However, if the above solution predicts that it will not be able to, or has already failed to provide effective CSI compression, recovery performance, or relatively accurate prediction performance, the above solution cannot be used. For other examples, such as AI / ML-based beam management (time domain-based beam prediction, spatial domain-based beam prediction, etc.), AI / ML-based positioning solutions, AI / ML-based channel estimation, AI / ML-based encoding and decoding solutions, etc., there is also a need for the above-mentioned performance monitoring and judgment.

[0064] Furthermore, when AI-based wireless communication solutions are actually used, it is necessary to consider how to test the performance of wireless AI solutions, so as to serve as a basis for whether the wireless AI solutions are network-based and commercially available. For wireless communication solutions based on wireless AI, the main goals of testing and judging the current wireless AI solutions include: (1) testing and / or judging the working status of the current wireless AI solution, such as whether it works normally in the wireless communication system and whether it can avoid the situation where the wireless AI solution does not fail to work; (2) testing and / or judging the working performance of the current wireless AI solution, such as whether it can bring performance gains in the wireless communication system and whether it can provide better working results.

[0065] However, there are significant challenges in implementing and completing the performance evaluation, testing, and judgment of AI / ML models. Current evaluation and testing hardware configurations struggle to meet the testing requirements of some wireless AI solutions. For example, for beam management, building high-frequency spatial multi-beam and time-domain continuous beams to perform performance testing of beam management use cases requires extremely high test equipment development cycles and deployment costs. Another example is positioning. Current positioning solutions are scenario-based. Building realistic test cases for diverse scenarios incurs significant equipment development, deployment, and operational costs. In addition to hardware limitations such as test equipment that is difficult to implement quickly, testing methodologies also pose limitations. For example, even with scenario-based test equipment, obtaining test tags (such as actual user locations) during testing can be challenging. For example, if the user being tested has accurate positioning results to use as positioning test tags, there is no need to develop and test a separate, error-prone positioning solution. Conversely, if users cannot obtain accurate test labels to judge the quality of positioning test results, the entire testing process and plan will be ineffective because they do not know what results should be compared with after the user test.

[0066] In summary, most wireless communication system test solutions are designed with the expectation of hardware support from test equipment, for example, by simulating actual wireless transmission tasks through signal and information transmission on the air interface. And this hardware-based method of testing and / or evaluating wireless communication solutions may also be used to test and / or evaluate AI-based wireless communication problem solutions. For example, in the communication method of an embodiment of the present application, a method for data-driven evaluation and / or testing of AI / ML models may be included. The method may include a data-driven wireless AI solution performance evaluation solution that relies on test data construction, transmission, and evaluation.

[0067] FIG3 is a schematic flow chart of a communication method 300 according to an embodiment of the present application. The method can optionally be applied to the system shown in FIG1 , but is not limited thereto. The method includes at least part of the following contents.

[0068] S310: The first device sends first information, where the first information is used to determine second information in the second device based on a first processing solution.

[0069] In the embodiments of the present application, if the first device is a test device, the second device may be a device to be tested. For example, if the first device is a UE, the second device may be a network device such as a base station. If the first device is a base station, the second device may be a UE. If the first device is a carrier test device or a manufacturer test device, the second device may be a UE or a base station.

[0070] In an embodiment of the present application, a first device may send first information to a second device. The first information may include test data used to drive a performance evaluation of the first processing solution. The first information may be used to drive the second device to determine second information based on the first processing solution. The second information may be used to evaluate the performance of the first processing solution, eliminating the need to use complex air interface signals and information in communication testing to simulate actual wireless transmission tasks, thereby simplifying the testing and / or evaluation process of the performance of the first processing solution.

[0071] In one embodiment, the first information is the input information of the first processing scheme, or the first information is used to determine the input information of the first processing scheme. Accordingly, the second information may be the output information of the first processing scheme, and may also be referred to as output results, result data, etc. For example, the first processing scheme includes an AI solution for a wireless communication system, such as an AI / ML model for a wireless communication system. The first information may be the input information of the AI / ML model, and after the second device inputs the first information into the AI / ML model, the AI / ML model may output the second information. Alternatively, the second device may determine the input information of the AI / ML model based on the first information, and after the first information is input into the AI / ML model, the AI / ML model may output the second information.

[0072] Figure 4 is a schematic flow chart of a communication method 400 according to another embodiment of the present application. The method may include one or more features of the above-described method 300. In one embodiment, the method further includes: S410, the first device receives the second information, where the second information is related to the performance of the first processing solution. In this embodiment of the present application, the performance of the first processing solution can be evaluated on the first device. The first device can receive the second information from the second device and determine the performance of the first processing solution based on the second information.

[0073] In one embodiment, the method further includes: S420, the first device determining fourth information based on the second information and the third information. For example, after receiving the second information, the first device may evaluate the first processing solution based on the locally known third information and the second information to obtain the fourth information. For example, the device may compare the second information with the third information to determine whether they are identical, or whether the difference is greater than a set threshold or within a set range, thereby determining whether the performance of the first processing solution meets expectations.

[0074] In an embodiment of the present application, a first device (e.g., test equipment, TE) may transmit first information to a second device (e.g., device under test, DUT). The second device may use the first information to determine second information. The second device may transmit the second information to the first device. The first device may use the second information to determine the performance of the first processing solution.

[0075] In the embodiments of the present application, the first device may be a test device, such as one deployed by an operator, a test equipment manufacturer, a base station, or a user equipment (UE). The second device may be a device to be tested, on which the first processing solution, such as the first model, may be executed. The second device may be a user equipment (UE), a base station, or a network device.

[0076] In an embodiment of the present application, the first information may be used as input of the first processing solution (first model), or the first information may be used to determine input information of the first processing solution (first model).

[0077] In an embodiment of the present application, the second information can be used to evaluate the performance of the first processing solution. The first device can use the second information and the third information to evaluate the performance of the first processing solution. The third information can be the expected result of the evaluation. For example, the first model expects to obtain output information after using the first information as input information (or using the first processing solution input information determined by the first information as the first processing solution input information).

[0078] In an embodiment of the present application, the first processing scheme (first model) may include at least one of the following: a base station side task, a UE side task, or a base station and UE side task.

[0079] FIG5 is a schematic flow chart of a communication method 500 according to another embodiment of the present application. The method may include one or more features of the above method 300. In one embodiment, the method further includes:

[0080] S510: The first device sends third information, which is used by the second device to determine fourth information based on the second information and the third information. In this embodiment of the present application, the performance of the first processing solution can be evaluated on the second device. The first device can send the third information to the second device. After receiving the third information, the second device can evaluate the first processing solution based on the second and third information to obtain fourth information.

[0081] In one embodiment, the method further includes: S520, the first device receives the fourth information.

[0082] In one embodiment, the third information is used to represent the expected performance result of the first processing solution; and the fourth information is used to represent the performance evaluation result of the first processing solution.

[0083] In one embodiment, the first information includes performance test data of the first processing solution.

[0084] And / or, the second information includes performance result data of the first processing solution.

[0085] In one embodiment, the third information includes performance tag data of the first processing solution,

[0086] And / or, the fourth information includes performance evaluation data of the first processing solution.

[0087] For example, the third information may include tag data corresponding to the test data (or expected data). The fourth information may include the performance evaluation results of the first processing scheme (or evaluation data). The third information can be determined together with the first information. For example, in a positioning scenario, the UE performs measurements at a certain location A to obtain a reference signal received power (RSRP) measurement value, a reference signal received quality (RSRQ) measurement value, and a received signal strength indicator (RSSI) measurement value. Among them, location A can be saved as a sample of the third information, and the RSRP measurement value, the RSRQ measurement value, and the RSSI measurement value can be saved as a sample of the first information. The first information and the third information can be transmitted to the second device together, or they can be transmitted to the second device separately, or only the first information can be transmitted to the second device but the third information cannot be transmitted to the second device. By transmitting and comparing test data, result data, and tag data between the device to be tested and the test device, the test case of the wireless AI solution can be completed, avoiding the requirements of complex test environments, scenarios, and equipment, and avoiding problems such as tag acquisition and tag transmission required for air interface testing.

[0088] In one embodiment, the first device is a testing device, and the second device is a device to be tested.

[0089] In one embodiment, the first processing scheme (first model) may include at least one of the following: AI / ML-based CSI feedback processing scheme / model; AI / ML-based CSI feedback model network side processing scheme / model; AI / ML-based CSI feedback model terminal side processing scheme / model; AI / ML-based CSI prediction processing scheme / model; AI / ML-based beam management processing scheme / model; AI / ML-based beam prediction processing scheme / model; AI / ML-based positioning processing scheme / model; AI / ML-based channel estimation processing scheme / model; AI / ML-based mobility management processing scheme / model; AI / ML-based resource management processing scheme / model; AI / ML-based encoding and decoding processing scheme / model; AI / ML-based modulation and demodulation processing scheme / model; AI / ML-based channel estimation processing scheme / model.

[0090] In the embodiments of the present application, AI / ML can be understood as AI and / or ML. Scheme / model can be understood as scheme and / or model.

[0091] In one embodiment, the first processing solution includes a positioning solution, and the first information includes at least one of the following information:

[0092] One or more measurement information;

[0093] One or more channel related information;

[0094] Test scenario information;

[0095] Test condition information.

[0096] In one embodiment, the test scenario information and / or the test condition information includes at least one of the following: cell information, channel information, terminal type, and terminal speed information. The following test scenario information and / or test condition information are also similar and will not be repeated.

[0097] In one embodiment, the measurement information includes at least one of the following: RSRP measurement value, RSRQ measurement value, RSSI measurement value, time of arrival (TOA), time difference of arrival (TDOA), reference signal time difference (RSTD), angle of departure (AoD), and angle of arrival (AoA).

[0098] In one embodiment, the channel-related information includes at least one of the following: a channel matrix, channel impulse response (CIR) information, and a power delay profile (PDP).

[0099] In one embodiment, the second information includes predicted positioning results and / or positioning-related indicators.

[0100] In one embodiment, the third information includes expected positioning results and / or positioning-related indicators.

[0101] In one embodiment, the positioning-related indicator includes at least one of the following: TOA, RSTD, AoD, AoA, Line-Of-Sight (LOS) indication, and Non-Line-Of-Sight (NLOS) indication.

[0102] In an embodiment of the present application, the first processing scheme may be a positioning scheme such as an AI / ML positioning model. At least one of one or more measurement information, one or more channel-related information, test scenario information, and test condition information (first information) is input into the positioning scheme, and a predicted positioning result and / or positioning-related indicator (second information) may be output. By comparing the expected positioning result and / or positioning-related indicator (third information) with the predicted positioning result and / or positioning-related indicator, the performance of the positioning scheme may be determined.

[0103] In an embodiment of the present application, the first processing scheme may be a direct positioning scheme, such as a direct positioning model based on AI / ML. The first information may be the input information of the direct positioning scheme. The second information may be the output information of the direct positioning scheme. The second information may be a positioning result (e.g., positioning coordinates). The first information may include multiple test samples. The second information may include multiple result samples. The third information may include multiple positioning tags. For example, the first information includes 100 test samples, one test sample includes 16 types of measurement information, and the second information includes 100 result samples, such as 100 positioning coordinates predicted by the positioning model based on the 100 test samples. If the third information includes 100 positioning tags corresponding to the 100 test samples (e.g., actual coordinates), the predicted positioning coordinates and the actual coordinates corresponding to each test sample are compared respectively to determine the performance of the positioning scheme.

[0104] In an embodiment of the present application, the first processing solution may be an indirect positioning solution, such as an indirect positioning model based on AI / ML. The second information may be output information of the indirect positioning solution. The second information may be positioning-related indicators. Based on the positioning-related indicators, a positioning result (e.g., positioning coordinates) may be obtained by the positioning algorithm. The positioning result is then compared with the positioning label to determine the performance of the positioning solution.

[0105] In one embodiment, the first processing scheme includes a beam prediction scheme, and the first information includes at least one of the following:

[0106] Beam measurement information;

[0107] Beam configuration information.

[0108] In one embodiment, the measurement information of the beam includes at least one of the following: an RSRP measurement value, an RSRQ measurement value, and an RSSI measurement value.

[0109] In one embodiment, the configuration information of the beam includes at least one of the following: the transmission time, transmission period, transmission interval, direction, number, frequency, width, and antenna configuration of the beam.

[0110] In one embodiment, the second information includes beam prediction information, such as RSRP prediction value, RSRQ prediction value, and RSSI prediction value.

[0111] In one embodiment, the prediction information of the beam includes at least one of the following: prediction quality information of one or more beams; and best beam prediction information.

[0112] In one embodiment, the third information includes desired information of the beam.

[0113] In one embodiment, the expected beam information includes at least one of the following: expected quality information of one or more beams; expected quality information of the best beam. The expected beam quality information may include actual beam quality information, such as actual RSRP value, actual RSRQ value, actual RSSI value, beam quality indicator, beam ID, etc.

[0114] In an embodiment of the present application, the first processing scheme may be a beam prediction scheme in the spatial domain, such as an AI / ML-based spatial domain beam prediction model. The first processing scheme may be a beam prediction scheme in the time domain, such as an AI / ML-based time domain beam prediction model. The first information may be input information of the beam prediction model or input information used to determine the beam prediction model, and the second information may be output information of the beam prediction model.

[0115] The first information may include multiple test samples. A test sample may include measurement information of M beams, such as channel information H and / or channel eigenvector W. A test sample may also include configuration information of the M beams. For example, a test sample of a spatial domain beam prediction model may include the direction, number, frequency, width, antenna configuration, etc. of the M beams. For another example, a test sample of a time domain beam prediction model may include the transmission time, transmission period, transmission interval, direction, number, frequency, width, antenna configuration, etc. of the M beams.

[0116] The second information may include multiple result samples. One result sample may include N beam quality prediction information, such as RSRP prediction value, RSRQ prediction value, RSSI prediction value, etc. If N is greater than M, the first processing scheme may predict N output beam information based on M input beam information. One result sample may also include best beam prediction information. For example, the best one or K beams in a set of N beams. For another example, the quality prediction results of the best one or K beams, such as RSRP prediction value, RSRQ prediction value, RSSI prediction value, beam quality indicator, beam ID, etc.

[0117] The third information may include actual beam quality information. The third information may include multiple label samples. One label sample may include actual quality information for N beams, such as actual RSRP values, actual RSRQ values, and actual RSSI values. The first device or the second device may compare the second information with the third information, such as the difference between the predicted RSRP value and the actual RSRP value for a particular beam, to evaluate the performance of the beam prediction model.

[0118] In one embodiment, the first processing scheme includes a channel state information (CSI) prediction scheme, and the first information includes at least one of the following:

[0119] one or more CSIs;

[0120] CSI configuration information;

[0121] Test scenario information;

[0122] Test condition information.

[0123] In one embodiment, the second information includes CSI predicted at one or more time instants.

[0124] In one embodiment, the third information includes CSI expected at one or more time instants.

[0125] In an embodiment of the present application, the first processing scheme may be a CSI prediction scheme, such as an AI / ML-based CSI prediction model. The first information may be input information of the CSI prediction scheme. The first information may be output information of the CSI prediction scheme. In some examples, the first information may include multiple test samples. A test sample includes M channel state information, such as channel information H and / or channel eigenvector W. In some examples, the first information may include the configuration of the channel state information, such as time domain transmission information, antenna configuration, transmission configuration, transmission resources, etc. of the M channel state information. The second information may include multiple result samples. A result sample may include L predicted channel state information, such as the channel information H and / or channel eigenvector W predicted at the subsequent L moments. The third information may include multiple label samples. A label sample may include L actual channel state information, such as the actual channel state information at the subsequent L moments, such as channel information H and channel eigenvector W.

[0126] In one embodiment, the first processing scheme includes a CSI compression scheme, and the first information includes at least one of the following:

[0127] one or more CSIs;

[0128] CSI configuration information;

[0129] Test scenario information;

[0130] Test condition information.

[0131] In one embodiment, the second information includes a predicted CSI compression result.

[0132] In one embodiment, the third information includes an expected CSI compression result.

[0133] In an embodiment of the present application, the first processing scheme may be a CSI compression scheme, such as an AI / ML-based CSI compression model. The first information may be input information of the CSI compression scheme. The first information may be output information of the CSI compression scheme. The example of the first information is similar to that of the CSI prediction scheme and is not repeated here. The second information may include multiple result samples. A result sample may include a predicted channel state information compression result, such as a CSI information compression result predicted with K bits or a CSI information compression result predicted with K numbers. The third information may include multiple label samples. A label sample may include an expected channel state information compression result, such as an expected CSI information compression result with K bits or a CSI information compression result expected with K numbers.

[0134] In one embodiment, the first processing scheme includes a CSI recovery scheme, and the first information includes at least one of the following information related to the CSI recovery scheme:

[0135] CSI compression result;

[0136] CSI configuration information;

[0137] Test scenario information;

[0138] Test condition information.

[0139] In one embodiment, the second information includes one or more recovered CSIs.

[0140] In one embodiment, the third information includes one or more desired CSIs.

[0141] In an embodiment of the present application, the first processing scheme may be a CSI recovery scheme, such as an AI / ML-based CSI recovery model. The first information may be input information of the CSI recovery scheme. The first information may be output information of the CSI recovery scheme. The first information may include multiple test samples. One test sample includes a channel state information compression result, such as a CSI information compression result of K bits or a CSI information compression result of K bits. The second information may include multiple result samples. One result sample may include recovered CSI, such as M recovered channel information H and / or channel eigenvectors W. The third information may include multiple label samples. One label sample may include expected CSI, such as M recovered channel information H and / or channel eigenvectors W.

[0142] In some examples, the first processing scheme may include a CSI compression scheme on the UE side, and may also include a CSI recovery scheme on the network side.

[0143] In one embodiment, the CSI includes at least one of the following: channel information and a channel eigenvector. For example, for a CSI prediction model, the first information may include M channel information, and the second information may include L channel information. For another example, for a CSI compression model, the first information may include M channel eigenvectors, and the second information may include M / K channel information.

[0144] In one embodiment, the CSI configuration information includes at least one of the following: time domain transmission information, antenna configuration, transmission configuration, and transmission resources of the CSI. For example, the CSI transmission configuration may include the number of transmission layers, transmission antennas, and transmission frequencies. For another example, the CSI transmission resources may include a time domain channel range, a frequency domain channel range, and the like.

[0145] FIG6 is a schematic flow chart of a communication method 600 according to an embodiment of the present application. The method can optionally be applied to the system shown in FIG1 , but is not limited thereto. The method includes at least part of the following contents.

[0146] S610: The second device receives the first information;

[0147] S620: The second device determines second information according to the first information based on the first processing solution.

[0148] In one embodiment, the first information is input information of the first processing solution, or the first information is used to determine the input information of the first processing solution.

[0149] FIG7 is a schematic flow chart of a communication method 700 according to another embodiment of the present application. The method may include one or more features of the above method 600. In one embodiment, the method further includes:

[0150] S710: The second device sends the second information, where the second information is related to the performance of the first processing solution.

[0151] In one embodiment, the second information is used to determine fourth information in the first device according to the second information and the third information.

[0152] FIG8 is a schematic flow chart of a communication method 800 according to another embodiment of the present application. The method may include one or more features of the above method 600. In one embodiment, the method further includes:

[0153] In one embodiment, the method further comprises:

[0154] S810: The second device receives third information;

[0155] S820: The second device determines fourth information according to the second information and the third information.

[0156] In one embodiment, the method further comprises:

[0157] S830: The second device sends the fourth information.

[0158] In one embodiment, the third information is used to represent the expected performance result of the first processing solution; and the fourth information is used to represent the performance evaluation result of the first processing solution.

[0159] In one embodiment, the first information includes performance test data of the first processing solution.

[0160] And / or, the second information includes performance result data of the first processing solution.

[0161] In one embodiment, the third information includes performance tag data of the first processing solution,

[0162] And / or, the fourth information includes performance evaluation data of the first processing solution.

[0163] In one embodiment, the first processing solution includes a positioning solution, and the first information includes at least one of the following information:

[0164] One or more measurement information;

[0165] One or more channel related information;

[0166] Test scenario information;

[0167] Test condition information.

[0168] In one embodiment, the measurement information includes at least one of the following: RSRP measurement value, RSRQ measurement value, RSSI measurement value, TOA, TDOA, RSTD, AoD, AoA.

[0169] In one embodiment, the channel-related information includes at least one of the following: a channel matrix, CIR information, and PDP.

[0170] In one embodiment, the second information includes predicted positioning results and / or positioning-related indicators.

[0171] In one embodiment, the third information includes expected positioning results and / or positioning-related indicators.

[0172] In one embodiment, the positioning-related indicator includes at least one of the following: TOA, RSTD, AoD, AoA, LOS indication, and NLOS indication.

[0173] In one embodiment, the first processing scheme includes a beam prediction scheme, and the first information includes at least one of the following:

[0174] Beam measurement information;

[0175] Beam configuration information.

[0176] In one embodiment, the measurement information of the beam includes at least one of the following: an RSRP measurement value, an RSRQ measurement value, and an RSSI measurement value.

[0177] In one embodiment, the configuration information of the beam includes at least one of the following: the transmission time, transmission period, transmission interval, direction, number, frequency, width, and antenna configuration of the beam.

[0178] In one embodiment, the second information includes prediction information of the beam.

[0179] In one embodiment, the prediction information of the beam includes at least one of the following: prediction quality information of one or more beams; and best beam prediction information.

[0180] In one embodiment, the third information includes desired information of the beam.

[0181] In one embodiment, the expected information of the beam includes at least one of the following: expected quality information of one or more beams; and expected quality information of the best beam.

[0182] In one embodiment, the first processing scheme includes a CSI prediction scheme, and the first information includes at least one of the following:

[0183] one or more CSIs;

[0184] CSI configuration information;

[0185] Test scenario information;

[0186] Test condition information.

[0187] In one embodiment, the second information includes CSI predicted at one or more time instants.

[0188] In one embodiment, the third information includes CSI expected at one or more time instants.

[0189] In one embodiment, the first processing scheme includes a CSI compression scheme, and the first information includes at least one of the following:

[0190] one or more CSIs;

[0191] CSI configuration information;

[0192] Test scenario information;

[0193] Test condition information.

[0194] In one embodiment, the second information includes a predicted CSI compression result.

[0195] In one embodiment, the third information includes an expected CSI compression result.

[0196] In one embodiment, the first processing scheme includes a CSI recovery scheme, and the first information includes at least one of the following information related to the CSI recovery scheme:

[0197] CSI compression result;

[0198] CSI configuration information;

[0199] Test scenario information;

[0200] Test condition information.

[0201] In one embodiment, the second information includes one or more recovered CSIs.

[0202] In one embodiment, the third information includes one or more desired CSIs.

[0203] In one embodiment, the CSI includes at least one of the following: channel information and a channel eigenvector.

[0204] In one implementation, the CSI configuration information includes at least one of the following: time domain transmission information, antenna configuration, transmission configuration, and transmission resources of the CSI.

[0205] In one implementation, the test scenario information and / or the test condition information includes at least one of the following: cell information, channel information, terminal type, and terminal speed information.

[0206] In one embodiment, the first device is a testing device, and the second device is a device to be tested.

[0207] In one embodiment, the first treatment regimen includes at least one of the following:

[0208] CSI feedback processing solutions / models based on artificial intelligence (AI) / machine learning (ML);

[0209] AI / ML-based CSI feedback model network-side processing solution / model;

[0210] AI / ML-based CSI feedback model terminal-side processing solution / model;

[0211] AI / ML-based CSI prediction processing solutions / models;

[0212] AI / ML-based beam management processing solutions / models;

[0213] AI / ML-based beam prediction processing solutions / models;

[0214] AI / ML-based positioning processing solutions / models;

[0215] AI / ML-based channel estimation processing solutions / models;

[0216] AI / ML-based mobility management processing solutions / models;

[0217] AI / ML-based resource management processing solutions / models;

[0218] AI / ML-based encoding and decoding processing solutions / models;

[0219] AI / ML-based modulation and demodulation processing solutions / models;

[0220] AI / ML-based channel estimation processing solutions / models.

[0221] For specific examples of the second device executing methods 600, 700, and 800 of this embodiment, reference can be made to the relevant descriptions about the second device in the above methods 300, 400, and 500, which will not be repeated here for the sake of brevity.

[0222] The communication method of the embodiment of the present application includes a method for data-driven evaluation and / or testing (which can be referred to as evaluation) of an AI / ML model. By transmitting and comparing test data, result data, and label data between the device to be tested and the test device, the test case of the wireless AI solution is completed, avoiding the needs of complex test environments, scenarios, and equipment, and avoiding the label acquisition and label transmission problems required for air interface testing. Specifically, in an embodiment of the present application, an implementation method for data-driven evaluation of the performance of the test model can be provided, as well as a specific description of the first information (test data), the second information (result data), and the third information (label data) under different typical use cases.

[0223] For example, as shown in FIG9 , the first device and the second device complete the evaluation and testing of the performance of a specific processing solution on the second device through data interaction.

[0224] A first device transmits first information to a second device, where the first information may include at least one of:

[0225] (1) directly as input to the first treatment plan, or

[0226] (2) The second device determines the input information of the first processing solution, and the second device uses the determined input information of the first processing solution as the input of the first processing solution.

[0227] Regarding the first information, for different first processing solutions, the following examples may be included:

[0228] Example 1: For testing a positioning solution, the first information may include:

[0229] The first processing solution is a positioning solution, such as an AI / ML-based positioning model. The first information is input information of the positioning solution.

[0230] The first information may consist of multiple samples, each of which may include one or more of the following information: one or more measurement information, such as RSRP measurement values, RSRQ measurement values, RSSI measurement values, Time of Observation (TOA), Time-Delayed Response (TDOA), RSTD, AoD, and AoA; or one or more channel-related information, such as the channel matrix H, CIR information, and PDP. The first information may consist of the above information from one or more positioning nodes or base stations. The first information may also include test scenario and condition information, such as cell information, channel information, UE type, and UE speed information.

[0231] Example 2: For testing a beam management solution, the first information may include:

[0232] The first processing solution is a spatial-domain beam prediction solution, such as an AI / ML-based spatial-domain beam prediction model. The first information is the input information for the beam prediction solution. The first information may consist of multiple samples, each of which may include one or more of the following: beam measurement information, such as measurement information for M beams, such as RSRP measurement values, RSRQ measurement values, and RSSI measurement values. For example, beam configuration information, such as configuration information for M beams, such as beam direction, number, frequency, width, and antenna configuration.

[0233] The first processing scheme may also be a beam prediction scheme in the time domain, such as a time domain beam prediction model based on AI / ML. The first information is the input information of the beam prediction scheme. The first information may be composed of multiple samples, and each sample may include one or more of the following information: for example, beam measurement information, such as measurement information of M beams, such as RSRP measurement value, RSRQ measurement value, RSSI measurement value, etc. For example, beam configuration information, such as configuration information of M beams, specifically the transmission time, transmission period, transmission interval of M beams, and / or the direction, number, frequency, width, antenna configuration, etc. of M beams. The first information may also include test scenarios and condition information, such as cell information, channel information, UE type, UE speed information, etc.

[0234] Example 3: When testing a CSI prediction solution, the first information-related content may include:

[0235] The first processing solution is a CSI prediction solution, such as a CSI prediction model based on AI / ML. The first information is input information of the CSI prediction solution.

[0236] The first information may be composed of multiple samples, each of which may include one or more of the following information: for example, M channel state information, such as channel information H and channel eigenvector W. For example, the configuration of the channel state information, such as the time domain transmission information, time, period, etc. of the M channel state information, such as the antenna configuration, transmission configuration (such as the number of transmission layers, transmission antennas, transmission frequency, etc.), and transmission resources (such as the time domain channel range and frequency domain channel range) corresponding to the channel state information. It may also include test scenario and / or condition information, such as cell information, channel information, UE type, UE speed information, etc.

[0237] Example 4: When testing a UE-side CSI compression solution, the first information may include:

[0238] The first processing solution is a CSI compression solution on the UE side, such as a CSI compression model based on AI / ML. The first information is input information of the CSI compression solution.

[0239] The first information may consist of multiple samples, each of which may include one or more of the following information: channel state information, such as channel information H and channel eigenvector W. For example, the configuration of the channel state information, such as the antenna configuration corresponding to the channel state information, the transmission configuration (such as the number of transmission layers, transmission antennas, transmission frequencies, etc.), and the transmission resources (such as the time domain channel range and the frequency domain channel range). The first information may also include test scenario and / or condition information, such as cell information, channel information, UE type, UE speed information, etc.

[0240] Example 5: When testing a network-side CSI recovery solution, the first information-related content may include:

[0241] The first processing solution is a CSI recovery solution on the network side, such as a CSI recovery model based on AI / ML. The first information is input information of the CSI recovery solution.

[0242] The first information may be composed of multiple samples, each of which may include one or more of the following information: for example, a channel state information compression result, such as a CSI information compression result of K bits or a CSI information compression result of K pieces. For example, the configuration of the channel state information, such as the antenna configuration corresponding to the channel state information, the transmission configuration (such as the number of transmission layers, transmission antennas, transmission frequencies, etc.), and the transmission resources (such as the time domain channel range and the frequency domain channel range). The first information may also include test scenario and / or condition information, such as cell information, channel information, UE type, UE speed information, etc.

[0243] In the embodiment of the present application, the purpose of the evaluation and testing work may include testing whether the first processing solution running on the second device can work properly and whether it can achieve good results. After the second device obtains the above-mentioned input information, the second device can execute the first processing solution and obtain the corresponding output information of the first processing solution for the first information, that is, the second information.

[0244] Regarding the second information, for different first processing solutions, the following examples may be included:

[0245] Example 1: For testing a positioning solution, the second information may include:

[0246] The first processing solution can be a direct positioning solution, such as an AI / ML-based direct positioning model. The second information is the output information of the positioning solution. The second information is the positioning result, such as the positioning coordinates. The second information can be composed of multiple samples, each sample being a positioning result corresponding to each sample in the first information.

[0247] The first processing solution may be an indirect positioning solution, such as an AI / ML-based indirect positioning model. The second information may be the output information of the positioning solution. The second information may be positioning-related indicators, such as ToA, RSTD, AoD, AoA, LOS indication, NLOS indication, etc. The second information may be a positioning result, such as a positioning result (e.g., positioning coordinates) obtained by a positioning algorithm based on the output information of the first positioning solution.

[0248] Example 2: For testing a beam management solution, the second information may include:

[0249] The first processing scheme is a beam prediction scheme in the spatial domain, such as an AI / ML-based spatial domain beam prediction model. The second information is the output information of the beam prediction scheme. The second information can be composed of multiple samples, and each sample can include one or more of the following information: for example, beam measurement information, such as N beam quality prediction information, such as RSRP prediction value, RSRQ prediction value, RSSI prediction value, etc. If N is greater than M, it is possible to predict N output beam information based on M input beam information. For example, the best beam information, for example, is the best 1 or K beams in the N beam set, for example, it can be the quality prediction result of the best 1 or K beams, such as RSRP prediction value, RSRQ prediction value, RSSI prediction value, beam quality indicator, beam ID, etc.

[0250] The first processing scheme may also be a beam prediction scheme in the time domain, such as an AI / ML-based time domain beam prediction model. The second information is the output information of the beam prediction scheme. The second information may be composed of multiple samples, each of which may include one or more of the following information: beam prediction information, such as beam quality prediction information for the next L time moments, such as RSRP prediction value, RSRQ prediction value, RSSI prediction value, beam quality indication information, and optimal beam ID.

[0251] Example 3: For testing a CSI prediction solution, the second information may include:

[0252] The first processing solution is a CSI prediction solution, such as an AI / ML-based CSI prediction model. The second information is the output information of the CSI prediction solution. The second information may consist of multiple samples, each of which may include one or more of the following information: for example, L channel state information, such as channel state information at the next L time points, specifically channel information H, channel eigenvector W, etc.

[0253] Example 4: When testing a UE-side CSI compression solution, the second information may include:

[0254] The first processing scheme is a CSI compression scheme on the UE side, such as an AI / ML-based CSI compression model. The second information is the output information of the CSI compression scheme. The second information may consist of multiple samples, each of which may include one or more of the following information: for example, a channel state information compression result, such as a K-bit CSI information compression result or a K-number CSI information compression result.

[0255] Example 5: When testing a network-side CSI recovery solution, the second information may include:

[0256] The first processing solution is a network-side CSI recovery solution, such as an AI / ML-based CSI recovery model. The second information is the output information of the CSI recovery solution. The second information consists of multiple samples, each of which may include one or more of the following information: channel state information, specifically channel information H and channel eigenvector W.

[0257] The second device can transmit the second information to the first device, and the first device can use the second information to determine the performance of the first processing solution. The first device can compare the difference between the second information and the third information to determine the working status and working effect of the first processing solution and whether the first processing solution can be used. For example, if the difference between the second information and the third information is too large, such as greater than a certain threshold indicator, the first processing solution is determined to be unusable. Otherwise, the first processing solution is determined to be usable.

[0258] The third information can be used to determine the working status and effectiveness of the first treatment solution. The third information can be the expected output of the first treatment solution corresponding to the first information. Since the second information is the actual output of the first treatment solution corresponding to the first information, the difference between the second information and the third information can be used to determine the working status and effectiveness of the first treatment solution.

[0259] Regarding the third information, for different first processing solutions, the following examples may be included:

[0260] Example 1: For testing of positioning solutions, the third information related content may include:

[0261] The first processing solution may be a direct positioning solution, and the third information is a positioning result, such as an actual position of the positioning.

[0262] The first processing scheme may be an indirect positioning scheme, and the third information may be a positioning result, such as the actual position of the positioning; the third information may also be positioning-related indicators, such as ToA, RSTD, AoD, AoA, LOS indication, NLOS indication expected value, etc.

[0263] The third information may be composed of a plurality of samples, each sample being actual position information corresponding to each sample of the first information.

[0264] Example 2: For testing a beam management solution, the third information may include:

[0265] The first processing scheme is a beam prediction scheme in the spatial domain, such as an AI / ML-based spatial domain beam prediction model. The third information is actual beam quality information, i.e., beam quality label information. The third information may be composed of multiple samples, each of which may include one or more of the following information: for example, beam measurement information, such as actual quality information of N beams, specifically, actual RSRP value, actual RSRQ value, actual RSSI value, etc. For example, optimal beam information, such as the actual best 1 or K beams in a set of N beams, for example, the actual quality results of the best 1 or K beams, such as actual RSRP value, actual RSRQ value, actual RSSI value, beam quality indicator, beam ID, etc.

[0266] The first processing solution may also be a time-domain beam prediction solution, such as an AI / ML-based time-domain beam prediction model. The third information may be actual beam quality information (or actual beam quality information, actual beam quality information, etc.), i.e., beam quality label information. The third information may be composed of multiple samples, each of which may include one or more of the following information: actual beam quality information, such as actual beam quality information at the next L moments, such as the actual RSRP value, the actual RSRQ value, the actual RSSI value, beam quality indication information, and the best beam ID.

[0267] Example 3: For testing of a CSI prediction solution, the third information may include:

[0268] The first processing solution is a CSI prediction solution, such as an AI / ML-based CSI prediction model. The third information is actual CSI information. The third information may consist of multiple samples, each of which may include one or more of the following: L actual channel state information, such as channel state information at the next L time points, specifically channel information H, channel eigenvector W, etc.

[0269] Example 4: When testing a UE-side CSI compression solution, the third information may include:

[0270] The first processing scheme is a CSI compression scheme on the UE side, such as an AI / ML-based CSI compression model. The third information is the expected output information of the first CSI compression scheme. The third information consists of multiple samples, each of which may include one or more of the following information: for example, the expected channel state information compression result corresponding to the first information, such as a K-bit CSI information compression result or a K-number CSI information compression result.

[0271] Example 5: When testing a network-side CSI recovery solution, the third information may include:

[0272] The first processing solution is a network-side CSI recovery solution, such as an AI / ML-based CSI recovery model. The third information is the expected output information of the first CSI recovery solution. The third information may consist of multiple samples, each of which may include one or more of the following: expected channel state information corresponding to the first information, such as channel information H and channel eigenvector W.

[0273] The first device may pre-construct the first information and the expected output result of the first processing solution corresponding to the first information. Alternatively, the third device may transmit the first information and the expected output result of the first processing solution corresponding to the first information to the first device. The third device may be a UE, a network device, or a third-party data acquisition node. The third device may be the first device or the second device, or a device different from the first device and the second device.

[0274] In addition, as shown in Figure 10, the first device can also transmit the third information to the second device. The second device judges the performance of the first processing solution based on the second information and the third information, and the second device transmits the performance evaluation result of the first processing solution (fourth information) to the first device.

[0275] When targeting a given wireless communication function or task, it is necessary to consider the process for evaluating the performance of the AI / ML solution, and through this process, to complete the judgment of the performance of the currently available AI / ML solution. The current hardware configuration for evaluation and testing is difficult to meet the testing requirements of some wireless AI solutions. In addition to hardware limitations such as test equipment that are difficult to implement in a short period of time, there are also limitations on the test method. For example, for some use cases, even if scenario-based test equipment and test environments can be built, it is still a difficult task to obtain test tags during the test. Through the data-driven evaluation test method given in the embodiments of the present application, the construction and transmission of test input data sets, test result data sets, test tag data sets, etc. can be used instead of the method of simulating actual wireless transmission tasks through the hardware support of the test equipment and the transmission of signals and information on the air interface, thereby making it easier for many wireless communication solutions that are highly dependent on test equipment and test scenarios, especially AI-based wireless communication solutions, to perform performance and function testing.

[0276] 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:

[0277] The sending unit 1101 is configured to send first information, where the first information is used to determine second information in a second device based on a first processing solution.

[0278] In one embodiment, the first information is input information of the first processing solution, or the first information is used to determine the input information of the first processing solution.

[0279] In one embodiment, the first device further includes:

[0280] The receiving unit 1102 is configured to receive the second information, where the second information is related to the performance of the first processing solution.

[0281] In one embodiment, the first device further includes:

[0282] The processing unit 1103 is configured to determine fourth information according to the second information and the third information.

[0283] In one implementation, the sending unit 1101 is further configured to send third information, where the third information is used to determine fourth information in the second device according to the second information and the third information.

[0284] In one implementation, the receiving unit 1102 is further configured to receive the fourth information.

[0285] In one embodiment, the third information is used to represent the expected performance result of the first processing solution; and the fourth information is used to represent the performance evaluation result of the first processing solution.

[0286] In one embodiment, the first information includes performance test data of the first processing solution, and / or the second information includes performance result data of the first processing solution.

[0287] In one embodiment, the third information includes performance tag data of the first processing solution, and / or the fourth information includes performance evaluation data of the first processing solution.

[0288] In one embodiment, the first processing solution includes a positioning solution, and the first information includes at least one of the following information:

[0289] One or more measurement information;

[0290] One or more channel related information;

[0291] Test scenario information;

[0292] Test condition information.

[0293] In one embodiment, the measurement information includes at least one of the following: a reference signal received power RSRP measurement value, a reference signal received quality RSRQ measurement value, a received signal strength indication RSSI measurement value, an arrival time TOA, an arrival time difference TDOA, a reference signal time difference RSTD, an angle of departure AoD, and an angle of arrival AoA.

[0294] In one embodiment, the channel-related information includes at least one of the following: a channel matrix, channel impulse response CIR information, and a power delay profile PDP.

[0295] In one embodiment, the second information includes predicted positioning results and / or positioning-related indicators.

[0296] In one embodiment, the third information includes expected positioning results and / or positioning-related indicators.

[0297] In one embodiment, the positioning-related indicator includes at least one of the following: TOA, RSTD, AoD, AoA, line-of-sight LOS indication, and non-line-of-sight NLOS indication.

[0298] In one embodiment, the first processing scheme includes a beam prediction scheme, and the first information includes at least one of the following:

[0299] Beam measurement information;

[0300] Beam configuration information.

[0301] In one embodiment, the measurement information of the beam includes at least one of the following: an RSRP measurement value, an RSRQ measurement value, and an RSSI measurement value.

[0302] In one embodiment, the configuration information of the beam includes at least one of the following: the transmission time, transmission period, transmission interval, direction, number, frequency, width, and antenna configuration of the beam.

[0303] In one embodiment, the second information includes prediction information of the beam.

[0304] In one embodiment, the prediction information of the beam includes at least one of the following: prediction quality information of one or more beams; and best beam prediction information.

[0305] In one embodiment, the third information includes desired information of the beam.

[0306] In one embodiment, the expected information of the beam includes at least one of the following: expected quality information of one or more beams; and expected quality information of the best beam.

[0307] In one embodiment, the first processing scheme includes a channel state information (CSI) prediction scheme, and the first information includes at least one of the following:

[0308] one or more CSIs;

[0309] CSI configuration information;

[0310] Test scenario information;

[0311] Test condition information.

[0312] In one embodiment, the second information includes CSI predicted at one or more time instants.

[0313] In one embodiment, the third information includes CSI expected at one or more time instants.

[0314] In one embodiment, the first processing scheme includes a CSI compression scheme, and the first information includes at least one of the following:

[0315] one or more CSIs;

[0316] CSI configuration information;

[0317] Test scenario information;

[0318] Test condition information.

[0319] In one embodiment, the second information includes a predicted CSI compression result.

[0320] In one embodiment, the third information includes an expected CSI compression result.

[0321] In one embodiment, the first processing scheme includes a CSI recovery scheme, and the first information includes at least one of the following information related to the CSI recovery scheme:

[0322] CSI compression result;

[0323] CSI configuration information;

[0324] Test scenario information;

[0325] Test condition information.

[0326] In one embodiment, the second information includes one or more recovered CSIs.

[0327] In one embodiment, the third information includes one or more desired CSIs.

[0328] In one embodiment, the CSI includes at least one of the following: channel information and a channel eigenvector.

[0329] In one implementation, the CSI configuration information includes at least one of the following: time domain transmission information, antenna configuration, transmission configuration, and transmission resources of the CSI.

[0330] In one implementation, the test scenario information and / or the test condition information includes at least one of the following: cell information, channel information, terminal type, and terminal speed information.

[0331] In one embodiment, the first device is a testing device, and the second device is a device to be tested.

[0332] In one embodiment, the first treatment regimen includes at least one of the following:

[0333] CSI feedback processing solutions / models based on artificial intelligence (AI) / machine learning (ML);

[0334] AI / ML-based CSI feedback model network-side processing solution / model;

[0335] AI / ML-based CSI feedback model terminal-side processing solution / model;

[0336] AI / ML-based CSI prediction processing solutions / models;

[0337] AI / ML-based beam management processing solutions / models;

[0338] AI / ML-based beam prediction processing solutions / models;

[0339] AI / ML-based positioning processing solutions / models;

[0340] AI / ML-based channel estimation processing solutions / models;

[0341] AI / ML-based mobility management processing solutions / models;

[0342] AI / ML-based resource management processing solutions / models;

[0343] AI / ML-based encoding and decoding processing solutions / models;

[0344] AI / ML-based modulation and demodulation processing solutions / models;

[0345] AI / ML-based channel estimation processing solutions / models.

[0346] 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.).

[0347] 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:

[0348] Receiving unit 1201, configured to receive first information;

[0349] The processing unit 1202 is configured to determine second information according to the first information based on a first processing solution.

[0350] In one embodiment, the first information is input information of the first processing solution, or the first information is used to determine the input information of the first processing solution.

[0351] In one embodiment, the second device further includes:

[0352] The sending unit 1203 is configured to send the second information, where the second information is related to the performance of the first processing solution.

[0353] In one embodiment, the second information is used to determine fourth information in the first device according to the second information and the third information.

[0354] In one embodiment, the receiving unit 1201 is further configured to receive third information;

[0355] The processing unit is further configured to determine fourth information based on the second information and the third information.

[0356] In one implementation, the sending unit 1203 is further configured to send the fourth information.

[0357] In one embodiment, the third information is used to represent the expected performance result of the first processing solution; and the fourth information is used to represent the performance evaluation result of the first processing solution.

[0358] In one embodiment, the first information includes performance test data of the first processing solution, and / or the second information includes performance result data of the first processing solution.

[0359] In one embodiment, the third information includes performance tag data of the first processing solution, and / or the fourth information includes performance evaluation data of the first processing solution.

[0360] In one embodiment, the first processing solution includes a positioning solution, and the first information includes at least one of the following information:

[0361] One or more measurement information;

[0362] One or more channel related information;

[0363] Test scenario information;

[0364] Test condition information.

[0365] In one embodiment, the measurement information includes at least one of the following: RSRP measurement value, RSRQ measurement value, RSSI measurement value, TOA, TDOA, RSTD, AoD, AoA.

[0366] In one embodiment, the channel-related information includes at least one of the following: a channel matrix, CIR information, and PDP.

[0367] In one embodiment, the second information includes predicted positioning results and / or positioning-related indicators.

[0368] In one embodiment, the third information includes expected positioning results and / or positioning-related indicators.

[0369] In one embodiment, the positioning-related indicator includes at least one of the following: TOA, RSTD, AoD, AoA, LOS indication, and NLOS indication.

[0370] In one embodiment, the first processing scheme includes a beam prediction scheme, and the first information includes at least one of the following:

[0371] Beam measurement information;

[0372] Beam configuration information.

[0373] In one embodiment, the measurement information of the beam includes at least one of the following: an RSRP measurement value, an RSRQ measurement value, and an RSSI measurement value.

[0374] In one embodiment, the configuration information of the beam includes at least one of the following: the transmission time, transmission period, transmission interval, direction, number, frequency, width, and antenna configuration of the beam.

[0375] In one embodiment, the second information includes prediction information of the beam.

[0376] In one embodiment, the prediction information of the beam includes at least one of the following: prediction quality information of one or more beams; and best beam prediction information.

[0377] In one embodiment, the third information includes desired information of the beam.

[0378] In one embodiment, the expected information of the beam includes at least one of the following: expected quality information of one or more beams; and expected quality information of the best beam.

[0379] In one embodiment, the first processing scheme includes a CSI prediction scheme, and the first information includes at least one of the following:

[0380] one or more CSIs;

[0381] CSI configuration information;

[0382] Test scenario information;

[0383] Test condition information.

[0384] In one embodiment, the second information includes CSI predicted at one or more time instants.

[0385] In one embodiment, the third information includes CSI expected at one or more time instants.

[0386] In one embodiment, the first processing scheme includes a CSI compression scheme, and the first information includes at least one of the following:

[0387] one or more CSIs;

[0388] CSI configuration information;

[0389] Test scenario information;

[0390] Test condition information.

[0391] In one embodiment, the second information includes a predicted CSI compression result.

[0392] In one embodiment, the third information includes an expected CSI compression result.

[0393] In one embodiment, the first processing scheme includes a CSI recovery scheme, and the first information includes at least one of the following information related to the CSI recovery scheme:

[0394] CSI compression result;

[0395] CSI configuration information;

[0396] Test scenario information;

[0397] Test condition information.

[0398] In one embodiment, the second information includes one or more recovered CSIs.

[0399] In one embodiment, the third information includes one or more desired CSIs.

[0400] In one embodiment, the CSI includes at least one of the following: channel information and a channel eigenvector.

[0401] In one implementation, the CSI configuration information includes at least one of the following: time domain transmission information, antenna configuration, transmission configuration, and transmission resources of the CSI.

[0402] In one implementation, the test scenario information and / or the test condition information includes at least one of the following: cell information, channel information, terminal type, and terminal speed information.

[0403] In one embodiment, the first device is a testing device, and the second device is a device to be tested.

[0404] In one embodiment, the first treatment regimen includes at least one of the following:

[0405] CSI feedback processing solutions / models based on artificial intelligence (AI) / machine learning (ML);

[0406] AI / ML-based CSI feedback model network-side processing solution / model;

[0407] AI / ML-based CSI feedback model terminal-side processing solution / model;

[0408] AI / ML-based CSI prediction processing solutions / models;

[0409] AI / ML-based beam management processing solutions / models;

[0410] AI / ML-based beam prediction processing solutions / models;

[0411] AI / ML-based positioning processing solutions / models;

[0412] AI / ML-based channel estimation processing solutions / models;

[0413] AI / ML-based mobility management processing solutions / models;

[0414] AI / ML-based resource management processing solutions / models;

[0415] AI / ML-based encoding and decoding processing solutions / models;

[0416] AI / ML-based modulation and demodulation processing solutions / models;

[0417] AI / ML-based channel estimation processing solutions / models.

[0418] 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.).

[0419] 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.

[0420] 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.

[0421] The memory 1320 may be a separate device independent of the processor 1310 , or may be integrated into the processor 1310 .

[0422] 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, to send information or data to other devices, or to receive information or data sent by other devices.

[0423] 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.

[0424] 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.

[0425] 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.

[0426] 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.

[0427] 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.

[0428] The memory 1420 may be a separate device independent of the processor 1410 , or may be integrated into the processor 1410 .

[0429] 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.

[0430] 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.

[0431] In one embodiment, the chip can be applied to the network 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.

[0432] In one embodiment, the chip can be applied to the terminal device in the embodiment of the present application, and the chip can implement the corresponding processes implemented by the second device in each method of the embodiment of the present application. For the sake of brevity, it will not be repeated here.

[0433] The chips used in the first device and the second device may be the same chip or different chips.

[0434] 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.

[0435] 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.

[0436] 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).

[0437] 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.

[0438] 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 1510 and a second device 1520 .

[0439] The first device 1510 is configured to send first information, where the first information is used to determine second information in a second device based on a first processing solution.

[0440] The second device 1520 is configured to receive the first information and determine the second information according to the first information based on the first processing solution.

[0441] The first device 1510 can be used to implement the corresponding functions implemented by the first device in the above method, and the second device 1520 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.

[0442] 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)).

[0443] 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.

[0444] 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.

[0445] The above is only a specific embodiment of the present application, but the scope of protection of this application is not limited to this. Any changes or substitutions that can be easily conceived by any person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of this application. Therefore, the scope of protection of this application should be based on the scope of protection of the claims.

Claims

1. A communication method, comprising: The first device sends first information, where the first information is used to determine second information in the second device based on a first processing solution.

2. The method according to claim 1, wherein The first information is input information of the first processing solution, or the first information is used to determine input information of the first processing solution.

3. The method according to claim 1 or 2, wherein: The method further comprises: The first device receives the second information, where the second information is related to the performance of the first processing solution.

4. The method according to claim 3, wherein: The method further comprises: The first device determines fourth information according to the second information and the third information.

5. The method according to claim 1 or 2, wherein: The method further comprises: The first device sends third information, where the third information is used by the second device to determine fourth information according to the second information and the third information.

6. The method according to claim 5, wherein: The method further includes: the first device receiving the fourth information.

7. The method according to any one of claims 4 to 6, wherein The third information is used to represent the expected performance result of the first processing solution; and the fourth information is used to represent the performance evaluation result of the first processing solution.

8. The method according to any one of claims 4 to 7, wherein The first information includes performance test data of the first processing solution, and / or the second information includes performance result data of the first processing solution.

9. The method according to any one of claims 4 to 8, wherein The third information includes performance tag data of the first processing solution, and / or the fourth information includes performance evaluation data of the first processing solution.

10. The method according to any one of claims 4 to 9, wherein The first processing solution includes a positioning solution, and the first information includes at least one of the following information: One or more measurement information; One or more channel related information; Test scenario information; Test condition information.

11. The method according to claim 10, wherein: The measurement information includes at least one of the following: a reference signal received power RSRP measurement value, a reference signal received quality RSRQ measurement value, a received signal strength indication RSSI measurement value, an arrival time TOA, an arrival time difference TDOA, a reference signal time difference RSTD, an angle of departure AoD, and an angle of arrival AoA.

12. The method according to claim 10, wherein: The channel-related information includes at least one of the following: a channel matrix, channel impulse response CIR information, and a power delay profile PDP.

13. The method according to any one of claims 10 to 12, wherein The second information includes predicted positioning results and / or positioning-related indicators.

14. The method according to any one of claims 10 to 13, wherein The third information includes expected positioning results and / or positioning-related indicators.

15. The method according to claim 14, wherein The positioning related indicators include at least one of the following: TOA, RSTD, AoD, AoA, line-of-sight LOS indication, and non-line-of-sight NLOS indication.

16. The method according to any one of claims 4 to 9, wherein The first processing scheme includes a beam prediction scheme, and the first information includes at least one of the following: measurement information of the beam; configuration information of the beam.

17. The method according to claim 16, wherein The measurement information of the beam includes at least one of the following: an RSRP measurement value, an RSRQ measurement value, and an RSSI measurement value.

18. The method according to claim 16, wherein The configuration information of the beam includes at least one of the following: the transmission time, transmission period, transmission interval, direction, number, frequency, width, and antenna configuration of the beam.

19. The method according to any one of claims 16 to 18, wherein The second information includes prediction information of the beam.

20. The method according to claim 19, wherein The prediction information of the beam includes at least one of the following: prediction quality information of one or more beams; and optimal beam prediction information.

21. The method according to any one of claims 16 to 20, wherein The third information includes desired information of the beam.

22. The method according to claim 21, wherein The expected information of the beam includes at least one of the following: expected quality information of one or more beams; and expected quality information of the best beam.

23. The method according to any one of claims 4 to 9, wherein The first processing scheme includes a channel state information (CSI) prediction scheme, and the first information includes at least one of the following: one or more CSIs; CSI configuration information; Test scenario information; Test condition information.

24. The method according to claim 23, wherein The second information includes CSI predicted at one or more time instants.

25. The method according to claim 23 or 24, wherein The third information includes CSI expected at one or more time instants.

26. The method according to any one of claims 4 to 9, wherein The first processing scheme includes a CSI compression scheme, and the first information includes at least one of the following: one or more CSIs; CSI configuration information; Test scenario information; Test condition information.

27. The method according to claim 26, wherein The second information includes a predicted CSI compression result.

28. The method according to claim 26 or 27, wherein The third information includes an expected CSI compression result.

29. The method according to any one of claims 4 to 9, wherein The first processing scheme includes a CSI recovery scheme, and the first information includes at least one of the following information related to the CSI recovery scheme: CSI compression result; CSI configuration information; Test scenario information; Test condition information.

30. The method according to claim 29, wherein The second information includes one or more recovered CSIs.

31. The method according to claim 29 or 30, wherein The third information includes one or more desired CSIs.

32. The method according to any one of claims 23 to 31, wherein The CSI includes at least one of the following: channel information and a channel characteristic vector.

33. The method according to any one of claims 23 to 31, wherein The CSI configuration information includes at least one of the following: time domain transmission information, antenna configuration, transmission configuration, and transmission resources of the CSI.

34. The method according to any one of claims 10 to 15, 23 to 31, wherein The test scenario information and / or the test condition information includes at least one of the following: cell information, channel information, terminal type, and terminal speed information.

35. The method according to any one of claims 1 to 34, wherein The first device is a testing device, and the second device is a device to be tested.

36. The method according to any one of claims 1 to 9, wherein The first treatment scheme includes at least one of the following: CSI feedback processing solutions / models based on artificial intelligence (AI) / machine learning (ML); AI / ML-based CSI feedback model network-side processing solution / model; AI / ML-based CSI feedback model terminal-side processing solution / model; AI / ML-based CSI prediction processing solutions / models; AI / ML-based beam management processing solutions / models; AI / ML-based beam prediction processing solutions / models; AI / ML-based positioning processing solutions / models; AI / ML-based channel estimation processing solutions / models; AI / ML-based mobility management processing solutions / models; AI / ML-based resource management processing solutions / models; AI / ML-based encoding and decoding processing solutions / models; AI / ML-based modulation and demodulation processing solutions / models; AI / ML-based channel estimation processing solutions / models.

37. A communication method comprising: The second device receives the first information; The second device determines second information from the first information based on a first processing scheme.

38. The method of claim 37, wherein: The first information is input information of the first processing solution, or the first information is used to determine input information of the first processing solution.

39. The method according to claim 37 or 38, wherein The method further comprises: The second device sends the second information, where the second information is related to the performance of the first processing solution.

40. The method of claim 39, wherein The second information is used to determine fourth information in the first device according to the second information and the third information.

41. The method according to claim 37 or 38, wherein The method further comprises: The second device receives third information; The second device determines fourth information according to the second information and the third information.

42. The method according to claim 41, wherein The method further includes: the second device sending the fourth information.

43. The method according to any one of claims 40 to 42, wherein The third information is used to represent the expected performance result of the first processing solution; and the fourth information is used to represent the performance evaluation result of the first processing solution.

44. The method according to any one of claims 40 to 41, wherein The first information includes performance test data of the first processing solution, and / or the second information includes performance result data of the first processing solution.

45. The method according to any one of claims 40 to 44, wherein The third information includes performance tag data of the first processing solution, and / or the fourth information includes performance evaluation data of the first processing solution.

46. ​​The method according to any one of claims 40 to 45, wherein The first processing solution includes a positioning solution, and the first information includes at least one of the following information: One or more measurement information; One or more channel related information; Test scenario information; Test condition information.

47. The method of claim 46, wherein The measurement information includes at least one of the following: RSRP measurement value, RSRQ measurement value, RSSI measurement value, TOA, TDOA, RSTD, AoD, AoA.

48. The method of claim 46, wherein The channel-related information includes at least one of the following: a channel matrix, CIR information, and PDP.

49. The method according to any one of claims 46 to 48, wherein The second information includes predicted positioning results and / or positioning-related indicators.

50. The method according to any one of claims 46 to 49, wherein The third information includes expected positioning results and / or positioning-related indicators.

51. The method of claim 50, wherein: The positioning related indicators include at least one of the following: TOA, RSTD, AoD, AoA, LOS indication, NLOS indication.

52. The method according to any one of claims 40 to 45, wherein The first processing scheme includes a beam prediction scheme, and the first information includes at least one of the following: measurement information of the beam; configuration information of the beam.

53. The method of claim 52, wherein: The measurement information of the beam includes at least one of the following: an RSRP measurement value, an RSRQ measurement value, and an RSSI measurement value.

54. The method of claim 52, wherein: The configuration information of the beam includes at least one of the following: the transmission time, transmission period, transmission interval, direction, number, frequency, width, and antenna configuration of the beam.

55. The method according to any one of claims 52 to 54, wherein The second information includes prediction information of the beam.

56. The method of claim 55, wherein: The prediction information of the beam includes at least one of the following: prediction quality information of one or more beams; and optimal beam prediction information.

57. The method according to any one of claims 52 to 56, wherein The third information includes desired information of the beam.

58. The method of claim 57, wherein The expected information of the beam includes at least one of the following: expected quality information of one or more beams; and expected quality information of the best beam.

59. The method according to any one of claims 40 to 45, wherein The first processing scheme includes a CSI prediction scheme, and the first information includes at least one of the following: one or more CSIs; CSI configuration information; Test scenario information; Test condition information.

60. The method of claim 59, wherein The second information includes CSI predicted at one or more time instants.

61. The method according to claim 59 or 60, wherein The third information includes CSI expected at one or more time instants.

62. The method according to any one of claims 40 to 45, wherein The first processing scheme includes a CSI compression scheme, and the first information includes at least one of the following: one or more CSIs; CSI configuration information; Test scenario information; Test condition information.

63. The method of claim 62, wherein: The second information includes a predicted CSI compression result.

64. The method according to claim 62 or 63, wherein The third information includes an expected CSI compression result.

65. The method according to any one of claims 40 to 45, wherein The first processing scheme includes a CSI recovery scheme, and the first information includes at least one of the following information related to the CSI recovery scheme: CSI compression result; CSI configuration information; Test scenario information; Test condition information.

66. The method of claim 65, wherein The second information includes one or more recovered CSIs.

67. The method according to claim 65 or 66, wherein The third information includes one or more desired CSIs.

68. The method according to any one of claims 59 to 67, wherein The CSI includes at least one of the following: channel information and a channel characteristic vector.

69. The method according to any one of claims 59 to 67, wherein The CSI configuration information includes at least one of the following: time domain transmission information, antenna configuration, transmission configuration, and transmission resources of the CSI.

70. The method according to any one of claims 46 to 51, 59 to 67, wherein The test scenario information and / or the test condition information includes at least one of the following: cell information, channel information, terminal type, and terminal speed information.

71. The method of any one of claims 37 to 70, wherein The first device is a testing device, and the second device is a device to be tested.

72. The method of any one of claims 37 to 45, wherein The first treatment scheme includes at least one of the following: CSI feedback processing solutions / models based on artificial intelligence (AI) / machine learning (ML); AI / ML-based CSI feedback model network-side processing solution / model; AI / ML-based CSI feedback model terminal-side processing solution / model; AI / ML-based CSI prediction processing solutions / models; AI / ML-based beam management processing solutions / models; AI / ML-based beam prediction processing solutions / models; AI / ML-based positioning processing solutions / models; AI / ML-based channel estimation processing solutions / models; AI / ML-based mobility management processing solutions / models; AI / ML-based resource management processing solutions / models; AI / ML-based encoding and decoding processing solutions / models; AI / ML-based modulation and demodulation processing solutions / models; AI / ML-based channel estimation processing solutions / models.

73. A first device comprising: The sending unit is configured to send first information, where the first information is used to determine second information in the second device based on the first processing solution.

74. A second device comprising: a receiving unit, configured to receive first information; A processing unit is configured to determine second information according to the first information based on a first processing scheme.

75. A communication device comprising: A transceiver, a processor and a memory, wherein 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 communication device performs the method as described in any one of claims 1 to 72.

76. A chip comprising: A processor, configured to call and execute a computer program from a memory, so that a device equipped with the chip executes a method as claimed in any one of claims 1 to 72.

77. A computer-readable storage medium for storing a computer program, which, when executed by a device, causes the device to perform the method according to any one of claims 1 to 72.

78. A computer program product comprising computer program instructions for causing a computer to perform the method of any one of claims 1 to 72.

79. A computer program causing a computer to perform the method of any one of claims 1 to 72.

80. A communication system comprising: A first device, configured to perform the method according to any one of claims 1 to 36; A second device is configured to perform the method according to any one of claims 37 to 72.

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