CPU quantity determination method, and device, system, storage medium and program product

Abstract

The present disclosure relates to a CPU quantity determination method, and a device, a system, a storage medium and a program product. The CPU quantity determination method comprises: determining a first quantity and / or a second quantity, wherein the first quantity refers to the quantity of CPUs occupied when an i-th piece of channel state information (CSI) is processed in a first processing manner, and the second quantity refers to the quantity of CPUs occupied when the i-th piece of CSI is processed in a second processing manner, i being a positive integer. In the embodiment, both a terminal and a network device can determine the quantity of CPUs occupied when the CSI is processed without using a model and the quantity of CPUs occupied when the CSI is processed using the model, and it can also be ensured that the terminal and the network device have a consistent understanding on the determined quantities of CPUs, such that on the basis of the determined quantities of CPUs, the network device configures for the terminal an appropriate parameter required for CSI reporting, thereby improving the stability of communication between the terminal and the network device.

Description

Methods, equipment, systems, storage media, and software products for determining the number of CPUs. Technical Field

[0001] This disclosure relates to the field of communication technology, and in particular to methods, devices, systems, storage media, and program products for determining the number of channel status information processing units (CPUs). Background Technology

[0002] When processing channel status information (CSI) between a terminal and a network device, it is necessary to ensure that the terminal and the network device have a consistent understanding of the CSI processing procedure so that the network device can configure appropriate CSI reporting parameters for the terminal. Summary of the Invention

[0003] This application solves the problem of how to determine the amount of CPU used when CSI needs to be processed based on a model, and achieves the effect of being able to determine the amount of CPU used when CSI is processed without using a model and when it is processed with a model.

[0004] This disclosure provides a method, apparatus, system, storage medium, and program product for determining the number of CPUs.

[0005] According to a first aspect of the present disclosure, a method for determining the number of CPUs is provided, the method being executed by a terminal, the method comprising:

[0006] Determine a first quantity and / or a second quantity, wherein the first quantity refers to the number of CPUs used when processing the i-th Channel State Information (CSI) using the first processing method, and the second quantity refers to the number of CPUs used when processing the i-th CSI using the second processing method, wherein the first processing method refers to processing CSI without using a model, and the second processing method refers to processing CSI using a model, and i is a positive integer.

[0007] According to a second aspect of the present disclosure, a method for determining the number of CPUs is provided, the method being executed by a network device, the method comprising:

[0008] Determine a first quantity and / or a second quantity, wherein the first quantity refers to the number of CPUs used when processing the i-th Channel State Information (CSI) using the first processing method, and the second quantity refers to the number of CPUs used when processing the i-th CSI using the second processing method, wherein the first processing method refers to processing CSI without using a model, and the second processing method refers to processing CSI using a model, and i is a positive integer.

[0009] According to a third aspect of the present disclosure, a CPU number determination apparatus is provided, the apparatus comprising:

[0010] The processing module is used to determine a first quantity and / or a second quantity, wherein the first quantity refers to the number of CPUs occupied when processing the i-th Channel State Information (CSI) using a first processing method, and the second quantity refers to the number of CPUs occupied when processing the i-th CSI using a second processing method. The first processing method refers to processing CSI without using a model, and the second processing method refers to processing CSI using a model, where i is a positive integer.

[0011] According to a fourth aspect of the present disclosure, a CPU number determination apparatus is provided, the apparatus comprising:

[0012] The processing module is used to determine a first quantity and / or a second quantity, wherein the first quantity refers to the number of CPUs occupied when processing the i-th Channel State Information (CSI) using a first processing method, and the second quantity refers to the number of CPUs occupied when processing the i-th CSI using a second processing method. The first processing method refers to processing CSI without using a model, and the second processing method refers to processing CSI using a model, where i is a positive integer.

[0013] According to a fifth aspect of the present disclosure, a communication device is provided for performing the CPU number determination method as described in the first or second aspect.

[0014] According to a sixth aspect of the present disclosure, a method for determining the number of CPUs is provided for a communication system, the communication system including a terminal and a network device, the terminal being configured to implement the method for determining the number of CPUs as described in the first aspect, and the network device being configured to implement the method for determining the number of CPUs as described in the second aspect.

[0015] According to a seventh aspect of the present disclosure, a communication system is provided, including at least one of a terminal and a network device, wherein the terminal is configured to implement the CPU number determination method as described in the first aspect, and the network device is configured to implement the CPU number determination method as described in the second aspect.

[0016] According to an eighth aspect of the present disclosure, a storage medium is provided that stores instructions that, when executed on a communication device, cause the communication device to perform the CPU number determination method as described in the first or second aspect.

[0017] According to a ninth aspect of the present disclosure, a program product is provided, comprising at least one of a program and instructions, wherein when the program and instructions are executed by a communication device, they implement the CPU number determination method as described in the first or second aspect.

[0018] In the above embodiments, both the terminal and the network device can determine the number of CPUs used when CSI is processed without using the model and the number of CPUs used when CSI is processed with the model. Furthermore, it can ensure that the terminal and the network device have a consistent understanding of the determined number of CPUs, enabling the network device to configure the appropriate parameters required for CSI reporting for the terminal based on the determined number of CPUs, thereby improving the stability of communication between the terminal and the network device. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in the embodiments of this disclosure, the accompanying drawings required for the description of the embodiments are introduced below. The following drawings are only some embodiments of this disclosure and do not impose specific limitations on the protection scope of this disclosure.

[0020] Figure 1A is an exemplary schematic diagram of the architecture of a communication system provided according to an embodiment of the present disclosure.

[0021] Figure 1B is a schematic diagram of CSI prediction provided according to an embodiment of the present disclosure.

[0022] Figure 2 is an interactive schematic diagram of a method for determining the number of CPUs according to an embodiment of the present disclosure.

[0023] Figure 3A is a flowchart illustrating a method for determining the number of CPUs according to an embodiment of the present disclosure.

[0024] Figure 3B is a flowchart illustrating a method for determining the number of CPUs according to an embodiment of the present disclosure.

[0025] Figure 4 is a flowchart illustrating a method for determining the number of CPUs according to an embodiment of the present disclosure.

[0026] Figure 5A is a schematic diagram of the structure of the terminal proposed in an embodiment of this disclosure.

[0027] Figure 5B is a schematic diagram of the structure of the network device proposed in an embodiment of this disclosure.

[0028] Figure 6A is a schematic diagram of the structure of the communication device proposed in an embodiment of this disclosure.

[0029] Figure 6B is a schematic diagram of the chip structure proposed in an embodiment of this disclosure. Detailed Implementation

[0030] This disclosure provides a method, apparatus, system, storage medium, and program product for determining the number of CPUs.

[0031] In a first aspect, embodiments of this disclosure propose a method for determining the number of CPUs, the method being executed by a terminal, the method comprising:

[0032] Send capability indication information to the network device, the capability indication information being used to indicate the terminal's capabilities when processing CSI;

[0033] Based on the capability indication information and / or communication protocol, a first quantity and / or a second quantity are determined. The first quantity refers to the number of CPUs occupied when processing the i-th Channel State Information (CSI) using the first processing method, and the second quantity refers to the number of CPUs occupied when processing the i-th CSI using the second processing method. The first processing method refers to processing CSI without using a model, and the second processing method refers to processing CSI using a model, where i is a positive integer.

[0034] In the above embodiments, both the terminal and the network device can determine the number of CPUs used when CSI is processed without using the model and the number of CPUs used when CSI is processed with the model. Furthermore, it can ensure that the terminal and the network device have a consistent understanding of the determined number of CPUs, enabling the network device to configure the appropriate parameters required for CSI reporting for the terminal based on the determined number of CPUs, thereby improving the stability of communication between the terminal and the network device.

[0035] In conjunction with some embodiments of the first aspect, in some embodiments, the method further includes:

[0036] Send capability indication information to the network device, the capability indication information being used to indicate the terminal's capabilities when processing CSI;

[0037] Determining the first quantity and / or the second quantity includes:

[0038] The first quantity and / or the second quantity are determined based on the capability indication information.

[0039] In the above embodiments, the terminal can indicate its own CSI processing capability through capability indication information, so as to determine the first quantity and the second quantity based on the capability sent by the terminal, thereby ensuring that the terminal and the network device can have a consistent understanding of the determined number of CPUs through the terminal's capability, so that the network device can configure the appropriate parameters required for CSI reporting for the terminal based on the determined number of CPUs, thereby improving the stability of communication between the terminal and the network device.

[0040] In conjunction with some embodiments of the first aspect, in some embodiments, determining the second quantity includes:

[0041] Determine a third quantity for each model among multiple models, and determine a second quantity based on the third quantity for each model; or,

[0042] Determine a fourth quantity corresponding to at least one model, and define the fourth quantity as the second quantity.

[0043] In the above embodiments, the number of each model can be determined, and then the number of CPUs used when processing CSI using the model can be determined based on the number of each model. Alternatively, the number of at least one model can be determined directly as the number of CPUs used when processing CSI using the model. This provides multiple schemes for determining the number of CPUs used when processing CSI using the model, improving the flexibility in determining the number of CPUs used when processing CSI using the model.

[0044] In conjunction with some embodiments of the first aspect, in some embodiments, capability indication information is used to indicate a first coefficient corresponding to each model.

[0045] Determining the third quantity for each of the multiple models includes:

[0046] The third quantity of a model is determined based on the minimum number of CPUs for one of the multiple models and the first coefficient corresponding to that model.

[0047] In conjunction with some embodiments of the first aspect, in some embodiments, capability indication information is used to indicate the minimum number of CPUs for each model among multiple models;

[0048] Determining the third quantity for each of the multiple models includes:

[0049] The third quantity of a model is determined based on the minimum number of CPUs for one of the multiple models and the first coefficient corresponding to that model.

[0050] In the above embodiments, the number of CPUs occupied by each model can be determined by the coefficients corresponding to each model and the minimum number of CPUs for each model. This enables the determination of the number of CPUs occupied when using a model to process CSI based on the number of CPUs occupied by each model, ensuring that subsequent network devices configure appropriate parameters for CSI reporting for the terminal based on the number of CPUs occupied by the model, thereby improving the stability of communication between the terminal and the network devices.

[0051] In conjunction with some embodiments of the first aspect, in some embodiments, capability indication information is used to indicate multiple first coefficient groups, one first coefficient group corresponding to one model among multiple models, and the first coefficient group includes at least one first sub-coefficient, different first sub-coefficients corresponding to different measurement parameters; the measurement parameters include at least one of the number of channel measurement resources, the number of antenna ports, system bandwidth, or a fifth quantity, wherein the fifth quantity refers to the number of CSIs at at least one moment obtained based on model inference;

[0052] Determining the third quantity for each of the multiple models includes:

[0053] Based on the first coefficient group corresponding to one of the multiple models and the measurement parameters corresponding to the first sub-coefficients included in the first coefficient group, the third quantity of the one model is determined.

[0054] In the above embodiments, when multiple models are used, the number of CPUs used when using a model can be determined based on at least one of the following: the number of channel measurement resources, the number of antenna ports, the system bandwidth, or the fifth quantity, as well as the coefficients corresponding to each model. This ensures that subsequent network devices configure the appropriate parameters required for CSI reporting to the terminal based on the number of CPUs used by the model, thereby improving the stability of communication between the terminal and the network devices.

[0055] In conjunction with some embodiments of the first aspect, in some embodiments, capability indication information is used to indicate a second coefficient group corresponding to the model, the second coefficient including at least one second sub-coefficient, different second sub-coefficients corresponding to different measurement parameters;

[0056] Determining the fourth quantity corresponding to at least one model includes:

[0057] The fourth quantity is determined based on the at least one second sub-coefficient and the measurement parameters corresponding to the second sub-coefficient.

[0058] In the above embodiments, for a model, the number of CPUs used when using the model can be determined based on at least one of the number of channel measurement resources, the number of antenna ports, the system bandwidth, or the fifth quantity, as well as the coefficients corresponding to the model. This includes the subsequent network device configuring appropriate parameters for CSI reporting for the terminal based on the number of CPUs used by the model, thereby improving the stability of communication between the terminal and the network device.

[0059] In conjunction with some embodiments of the first aspect, in some embodiments, the capability indication information is used to indicate a plurality of third coefficient groups, one third coefficient group corresponding to one of the plurality of models, the third coefficient group including at least one third sub-coefficient, and different third sub-coefficients corresponding to different channel measurement resource types;

[0060] Determining the third quantity for each of the multiple models includes:

[0061] The third quantity for each model is determined based on the third coefficient group corresponding to one of the multiple models and the number of channel measurement resources for different channel measurement resource types.

[0062] In the above embodiments, when there are multiple models, the number of CPUs used when using a model can be determined based on the channel measurement resource type and the coefficients corresponding to each model. This ensures that subsequent network devices configure the appropriate parameters required for CSI reporting to the terminal based on the number of CPUs used by the model, thereby improving the stability of communication between the terminal and the network devices.

[0063] In conjunction with some embodiments of the first aspect, in some embodiments, the capability indication information is used to indicate a fourth coefficient group corresponding to the model, the fourth coefficient group including at least one fourth sub-coefficient, and different fourth sub-coefficients corresponding to different channel measurement resource types;

[0064] Based on determining at least one fourth quantity corresponding to a model, including:

[0065] The fourth quantity is determined based on the at least one fourth sub-coefficient and the number of channel measurement resources of different channel measurement resource types.

[0066] In the above embodiments, for a single model, the number of CPUs used when using the model can be determined based on the channel measurement resource type and the coefficients corresponding to the model. This improves the stability of communication between the terminal and the network device by allowing subsequent network devices to configure the parameters required for CSI reporting based on the number of CPUs used by the model.

[0067] Furthermore, the above embodiments provide different ways to determine the number of CPUs used when using the model, which improves the flexibility in determining the number of CPUs used when using the model to process CSI.

[0068] In conjunction with some embodiments of the first aspect, in some embodiments, when the fifth quantity is equal to the first value, the first quantity is a predefined value;

[0069] When the fifth quantity is greater than the first value, the first quantity is determined based on the second coefficient and the fifth quantity;

[0070] The fifth quantity refers to the quantity of at least one moment, where at least one moment refers to the moment when CSI is obtained based on model processing.

[0071] In the above embodiments, when the relationship between the time when the CSI is obtained based on the model processing is different from that of the first value, different methods are used to determine the number of CPUs occupied when the model is not used, so as to ensure the accuracy of the determined number of CPUs occupied when the model is not used. This ensures that the subsequent network devices configure the parameters required for CSI reporting for the terminal based on the number of CPUs occupied when the model is not used, thereby improving the stability of communication between the terminal and the network devices.

[0072] In conjunction with some embodiments of the first aspect, in some embodiments, the capability indication information is used to indicate a first total quantity and / or a second total quantity, wherein the first total quantity refers to the number of CPUs supporting the first processing mode, and the second total quantity refers to the number of CPUs supporting the second processing mode.

[0073] In conjunction with some embodiments of the first aspect, in some embodiments, the first quantity is not greater than the first total quantity, and / or, the second quantity is not greater than the second total quantity.

[0074] In the above embodiments, the terminal may also indicate the total number of CPUs that it supports the first processing method and / or the total number of CPUs that it supports the second processing method, to ensure the integrity of the terminal's own capabilities, thereby preventing the determined number of CPUs from exceeding the number of CPUs that the terminal supports, and improving the stability of subsequent communication between the terminal and network devices.

[0075] In conjunction with some embodiments of the first aspect, in some embodiments, the third total number is greater than the first remaining number and the fourth total number is greater than the second remaining number, and NM low-priority CSIs are not updated, where N is the total number of CSIs and M is the smaller of M1 and M2. The third total number refers to the total number of CPUs occupied by processing N CSIs using the first processing method, the fourth total number refers to the total number of CPUs occupied by processing N CSIs using the second processing method, the first remaining number refers to the difference between the first total number and the number of CPUs already occupied by the first processing method, and the second remaining number refers to the difference between the second total number and the number of CPUs already occupied by the second processing method.

[0076] The number of CPUs used to process M1 high-priority CSIs using the first processing method is no greater than the first remaining number of CPUs, and the number of CPUs used to process M2 high-priority CSIs using the second processing method is no greater than the second remaining number of CPUs.

[0077] In the above embodiment, if the sum of the first number reported by all CSIs is greater than the remaining number using the first processing method, and the sum of the second number reported by all CSIs is greater than the remaining number using the second processing method, it indicates that there are M CSIs that cannot occupy the CPU for processing. Therefore, it is necessary to not update NM CSIs to ensure that M CSIs can be updated, thereby ensuring the stability of CSI updates.

[0078] In conjunction with some embodiments of the first aspect, in some embodiments, the third total number is not greater than the first remaining number and the fourth total number is greater than the second remaining number, the N-M3 lower priority CSIs are not updated, or the N-M3 lower priority CSIs are reverted from the second processing method to the first processing method, and the number of CPUs occupied by processing the M3 higher priority CSIs using the second processing method is not greater than the second remaining number.

[0079] In the above embodiments, if it is determined that the sum of the first quantities reported by all CSIs is not greater than the remaining quantities using the first processing method, and the sum of the second quantities reported by all CSIs is greater than the remaining quantities using the second processing method, it indicates that there are M3 CSIs that cannot occupy the CPU for processing using the second processing method. Therefore, it is necessary to either not update N-M3 CSIs or roll back N-M3 CSIs to be processed using the first processing method to ensure that M3 CSIs can be updated, thereby enabling N-M3 CSIs to be processed and updated using the first processing method, thus improving the stability of CSI updates.

[0080] In conjunction with some embodiments of the first aspect, in some embodiments, NL low-priority CSIs are not updated, the number of CPUs occupied by processing L CSIs using the first processing method is not greater than the first remaining number, and the number of CPUs occupied by processing N-M3 CSIs using the second processing method is not greater than the second remaining number, where L is greater than or equal to M3.

[0081] In the above embodiments, even if N-M3 CSIs fall back to the first processing mode, there is still a situation where the number of CPUs occupied by the first processing mode exceeds the number of CPUs remaining in the first processing mode. In this case, it is necessary to ensure that NL low-priority CSIs are not updated, while L CSIs can be updated, thereby improving the stability of CSI updates.

[0082] In conjunction with some embodiments of the first aspect, in some embodiments, the third total number is greater than the first remaining number and the fourth total number is not greater than the second remaining number, the N-M4 lower priority CSIs are not updated, or the N-M4 lower priority CSIs are replaced by the second processing method by the first processing method, and the number of CPUs occupied by processing the M4 higher priority CSIs using the first processing method is not greater than the second remaining number.

[0083] In the above embodiments, if it is determined that the sum of the first number reported by all CSIs is greater than the remaining number using the first processing method, and the sum of the second number reported by all CSIs is not greater than the remaining number using the second processing method, it indicates that there are M4 CSIs that cannot occupy the CPU for processing using the first processing method. Therefore, it is necessary to either not update N-M4 CSIs or replace N-M4 CSIs with the second processing method to ensure that M4 CSIs can be updated, thereby enabling N-M4 CSIs to be processed and updated using the second processing method, thus improving the stability of CSI updates.

[0084] In conjunction with some embodiments of the first aspect, in some embodiments, NS low-priority CSIs are not updated, the number of CPUs occupied by processing M4 CSIs using the first processing method is not greater than the second remaining number, and the number of CPUs occupied by processing S CSIs using the second processing method is not greater than the second remaining number, where S is greater than or equal to M.

[0085] In the above embodiments, even if N-M4 CSIs are replaced by the second processing method, there is still a situation where the number of CPUs occupied by the second processing method exceeds the number of CPUs remaining in the second processing method. In this case, it is necessary to ensure that N-N lower priority CSIs are not updated, while S CSIs can be updated, thereby improving the stability of CSI updates.

[0086] Secondly, embodiments of this disclosure propose a method for determining the number of CPUs, the method being executed by a network device, the method comprising:

[0087] Determine a first quantity and / or a second quantity, wherein the first quantity refers to the number of CPUs used when processing the i-th Channel State Information (CSI) using the first processing method, and the second quantity refers to the number of CPUs used when processing the i-th CSI using the second processing method, wherein the first processing method refers to processing CSI without using a model, and the second processing method refers to processing CSI using a model, and i is a positive integer.

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

[0089] The terminal receives capability indication information, which indicates the terminal's capability when processing CSI.

[0090] Determining the first quantity and / or the second quantity includes:

[0091] The first quantity and / or the second quantity are determined based on the capability indication information.

[0092] In conjunction with some embodiments of the second aspect, in some embodiments, determining the second quantity includes:

[0093] Determine a third quantity for each model among multiple models, and determine a second quantity based on the third quantity for each model; or,

[0094] Determine a fourth quantity corresponding to at least one model, and define the fourth quantity as the second quantity.

[0095] In conjunction with some embodiments of the second aspect, in some embodiments, capability indication information is used to indicate a first coefficient corresponding to each model.

[0096] Determining the third quantity for each of the multiple models includes:

[0097] The third quantity of a model is determined based on the minimum number of CPUs for one of the multiple models and the first coefficient corresponding to that model.

[0098] In conjunction with some embodiments of the second aspect, in some embodiments, capability indication information is used to indicate the minimum number of CPUs for each model among multiple models;

[0099] Determining the third quantity for each of the multiple models includes:

[0100] The third quantity of a model is determined based on the minimum number of CPUs for one of the multiple models and the first coefficient corresponding to that model.

[0101] In conjunction with some embodiments of the second aspect, in some embodiments, capability indication information is used to indicate multiple first coefficient groups, one first coefficient group corresponding to one model among multiple models, and the first coefficient group includes at least one first sub-coefficient, different first sub-coefficients corresponding to different measurement parameters; the measurement parameters include at least one of the number of channel measurement resources, the number of antenna ports, system bandwidth, or a fifth quantity, wherein the fifth quantity refers to the number of CSIs at at least one moment obtained based on model inference;

[0102] Determining the third quantity for each of the multiple models includes:

[0103] Based on the first coefficient group corresponding to one of the multiple models and the measurement parameters corresponding to the first sub-coefficients included in the first coefficient group, the third quantity of the one model is determined.

[0104] In conjunction with some embodiments of the second aspect, in some embodiments, capability indication information is used to indicate a second coefficient group corresponding to the model, the second coefficient including at least one second sub-coefficient, different second sub-coefficients corresponding to different measurement parameters;

[0105] Determining the fourth quantity corresponding to at least one model includes:

[0106] The fourth quantity is determined based on the at least one second sub-coefficient and the measurement parameters corresponding to the second sub-coefficient.

[0107] In conjunction with some embodiments of the second aspect, in some embodiments, capability indication information is used to indicate multiple third coefficient groups, one third coefficient group corresponding to one of the multiple models, the third coefficient group including at least one third sub-coefficient, different third sub-coefficients corresponding to different channel measurement resource types;

[0108] Determining the third quantity for each of the multiple models includes:

[0109] The third quantity for each model is determined based on the third coefficient group corresponding to one of the multiple models and the number of channel measurement resources for different channel measurement resource types.

[0110] In conjunction with some embodiments of the second aspect, in some embodiments, capability indication information is used to indicate a fourth coefficient group corresponding to the model, the fourth coefficient group including at least one fourth sub-coefficient, different fourth sub-coefficients corresponding to different channel measurement resource types;

[0111] Based on determining at least one fourth quantity corresponding to a model, including:

[0112] The fourth quantity is determined based on the at least one fourth sub-coefficient and the number of channel measurement resources of different channel measurement resource types.

[0113] In conjunction with some embodiments of the second aspect, in some embodiments, the capability indication information further includes a first total quantity and / or a second total quantity, wherein the first total quantity refers to the number of CPUs supporting the first processing mode, and the second total quantity refers to the number of CPUs supporting the second processing mode.

[0114] In conjunction with some embodiments of the second aspect, in some embodiments, the first quantity is not greater than the first total quantity, and / or the second quantity is not greater than the second total quantity.

[0115] In conjunction with some embodiments of the second aspect, in some embodiments, when the fifth quantity is equal to the first value, the first quantity is a predefined value;

[0116] When the fifth quantity is greater than the first value, the first quantity is determined based on the second coefficient and the fifth quantity;

[0117] The fifth quantity refers to the quantity of at least one moment, where at least one moment refers to the moment when CSI is obtained based on model processing.

[0118] In conjunction with some embodiments of the second aspect, in some embodiments, the third total number is greater than the first remaining number and the fourth total number is greater than the second remaining number, and NM low-priority CSIs are not updated, where N is the total number of CSIs and M is the smaller of M1 and M2. The third total number refers to the total number of CPUs occupied by processing N CSIs using the first processing method, the fourth total number refers to the total number of CPUs occupied by processing N CSIs using the second processing method, the first remaining number refers to the difference between the first total number and the number of CPUs already occupied by the first processing method, and the second remaining number refers to the difference between the second total number and the number of CPUs already occupied by the second processing method.

[0119] The number of CPUs used to process M1 high-priority CSIs using the first processing method is no greater than the first remaining number of CPUs, and the number of CPUs used to process M2 high-priority CSIs using the second processing method is no greater than the second remaining number of CPUs.

[0120] In conjunction with some embodiments of the second aspect, in some embodiments, the third total number is not greater than the first remaining number and the fourth total number is greater than the second remaining number, N-M3 lower priority CSIs are not updated, or N-M3 lower priority CSIs are reverted from the second processing method to the first processing method, and the number of CPUs occupied by processing M3 higher priority CSIs using the second processing method is not greater than the second remaining number.

[0121] In conjunction with some embodiments of the second aspect, in some embodiments, NL low-priority CSIs are not updated, the number of CPUs occupied by processing L CSIs using the first processing method is not greater than the first remaining number, and the number of CPUs occupied by processing N-M3 CSIs using the second processing method is not greater than the second remaining number, where L is greater than or equal to M3.

[0122] In conjunction with some embodiments of the second aspect, in some embodiments, the third total number is greater than the first remaining number and the fourth total number is not greater than the second remaining number, the N-M4 lower priority CSIs are not updated, or the N-M4 lower priority CSIs are replaced by the second processing method by the first processing method, and the number of CPUs occupied by processing the M4 higher priority CSIs using the first processing method is not greater than the second remaining number.

[0123] In conjunction with some embodiments of the second aspect, in some embodiments, NS low-priority CSIs are not updated, the number of CPUs occupied by processing M4 CSIs using the first processing method is not greater than the second remaining number, and the number of CPUs occupied by processing S CSIs using the second processing method is not greater than the second remaining number, where S is greater than or equal to M.

[0124] Thirdly, embodiments of this disclosure provide a CPU number determination apparatus, the apparatus comprising:

[0125] The processing module is used to determine a first quantity and / or a second quantity, wherein the first quantity refers to the number of CPUs occupied when processing the i-th Channel State Information (CSI) using a first processing method, and the second quantity refers to the number of CPUs occupied when processing the i-th CSI using a second processing method. The first processing method refers to processing CSI without using a model, and the second processing method refers to processing CSI using a model, where i is a positive integer.

[0126] Fourthly, embodiments of this disclosure provide a device for determining the number of CPUs, the device comprising:

[0127] The processing module is used to determine a first quantity and / or a second quantity, wherein the first quantity refers to the number of CPUs occupied when processing the i-th Channel State Information (CSI) using a first processing method, and the second quantity refers to the number of CPUs occupied when processing the i-th CSI using a second processing method. The first processing method refers to processing CSI without using a model, and the second processing method refers to processing CSI using a model, where i is a positive integer.

[0128] Fifthly, embodiments of this disclosure provide a communication device for performing the CPU number determination method as described in the first or second aspect.

[0129] In a sixth aspect, a communication system is proposed, comprising at least one of a terminal and a network device, wherein the terminal is configured to implement the CPU number determination method as described in the first aspect, and the network device is configured to implement the CPU number determination method as described in the second aspect.

[0130] In a seventh aspect, embodiments of this disclosure provide a method for determining the number of CPUs for a communication system, the communication system including a terminal and a network device, the terminal being configured to implement the method for determining the number of CPUs as described in the first aspect, and the network device being configured to implement the method for determining the number of CPUs as described in the second aspect.

[0131] Eighthly, a storage medium is proposed that stores instructions that, when executed on a communication device, cause the communication device to perform the CPU number determination method as described in the first or second aspect.

[0132] In a ninth aspect, a program product is proposed, comprising at least one of a program and instructions, wherein when the program and instructions are executed by a communication device, they implement the CPU number determination method as described in the first or second aspect.

[0133] It is understood that the aforementioned communication equipment, communication system, storage medium, program product, etc., are all used to execute the methods proposed in the embodiments of this disclosure. Therefore, the beneficial effects they can achieve can be referred to the beneficial effects in the corresponding methods, and will not be repeated here.

[0134] This disclosure provides methods, devices, systems, storage media, and program products for determining the number of CPUs. In some embodiments, the terms "CPU number determination method" and "frequency domain method," "communication method," "determination method," and "processing method" may be used interchangeably.

[0135] This disclosure is not exhaustive, but merely illustrative of some embodiments, and is not intended to limit the scope of protection of this disclosure. Unless otherwise specified, each step in a particular embodiment can be implemented as an independent embodiment, and the steps can be arbitrarily combined. For example, a solution after removing some steps in a particular embodiment can also be implemented as an independent embodiment, and the order of the steps in a particular embodiment can be arbitrarily interchanged. Furthermore, the optional implementation methods in a particular embodiment can be arbitrarily combined; moreover, the embodiments can be arbitrarily combined, for example, some or all steps of different embodiments can be arbitrarily combined, and a particular embodiment can be arbitrarily combined with the optional implementation methods of other embodiments. In all embodiments of this disclosure, unless otherwise specified or logically conflicting, the terminology and / or descriptions between the embodiments are consistent and can be mutually referenced. Technical features in different embodiments can be combined to form new embodiments based on their inherent logical relationships.

[0136] The terminology used in the embodiments of this disclosure is for the purpose of describing particular embodiments only and is not intended to limit the scope of this disclosure.

[0137] In this embodiment of the disclosure, unless otherwise stated, elements expressed in the singular form, such as "a," "an," "the," "the," "the," "the," "the," "the," "this," etc., can mean "one and only one," or "one or more," "at least one," etc. For example, when using articles such as "a," "an," "the," etc. in translation, the noun following the article can be understood as either a singular expression or a plural expression.

[0138] In the embodiments disclosed herein, "multiple" refers to two or more.

[0139] In some embodiments, the terms "at least one of A or B, at least one of A and B", "one or more", "a plurality of", "multiple" and the like can be used interchangeably.

[0140] In some embodiments, the notation "at least one of A and B", "A and / or B", "A in one case, B in another", "in response to one case A, in response to another case B", etc., may include the following technical solutions depending on the situation: in some embodiments, A (execute A regardless of whether there is a branch B); in some embodiments, B (execute B regardless of whether there is a branch A); in some embodiments, execution is selected from A and B (A and B are selectively executed); in some embodiments, both A and B are executed. The same applies when there are more branches such as A, B, C, etc.

[0141] In some embodiments, the notation "A or B" may include the following technical solutions, depending on the situation: in some embodiments, A (execute A regardless of whether a branch B exists); in some embodiments, B (execute B regardless of whether a branch A exists); in some embodiments, execution is selected from A and B (A and B are selectively executed). The same applies when there are more branches such as A, B, and C.

[0142] The prefixes "first," "second," etc., used in the embodiments of this disclosure are merely for distinguishing different descriptive objects and do not impose restrictions on the position, order, priority, quantity, or content of the descriptive objects. The description of the descriptive objects is found in the claims or the context of the embodiments, and the use of prefixes should not constitute unnecessary restrictions. For example, if the descriptive object is a "field," the ordinal numbers preceding "field" in "first field" and "second field" do not restrict the position or order of the "fields." "First" and "second" do not restrict whether the "fields" they modify are in the same message, nor do they restrict the order of "first field" and "second field." Similarly, if the descriptive object is a "level," the ordinal numbers preceding "level" in "first level" and "second level" do not restrict the priority between "levels." Furthermore, the number of descriptive objects is not limited by ordinal numbers and can be one or more. For example, in "first device," the number of "devices" can be one or more. Furthermore, the objects modified by different prefixes can be the same or different. For example, if the object being described is "device", then "first device" and "second device" can be the same device or different devices, and their types can be the same or different. Similarly, if the object being described is "information", then "first information" and "second information" can be the same information or different information, and their content can be the same or different.

[0143] In some embodiments, “including A,” “containing A,” “for indicating A,” and “carrying A” can be interpreted as directly carrying A or indirectly indicating A.

[0144] In some embodiments, terms such as "time / frequency" and "time-frequency domain" refer to the time domain and / or frequency domain.

[0145] In some embodiments, terms such as “in response to…”, “in response to determining…”, “in the case of…”, “when…”, “when…”, “if…”, etc. can be used interchangeably. These descriptions all refer to the device making a corresponding action under certain objective circumstances. They do not necessarily limit the time, nor do they require the device to make a judgment action when implementing it, nor do they mean that there must be other limitations.

[0146] In some embodiments, the terms “greater than,” “greater than or equal to,” “not less than,” “more than,” “more than or equal to,” “not less than,” “higher than,” “higher than or equal to,” “not lower than,” and “above” can be used interchangeably, as can the terms “less than,” “less than or equal to,” “not greater than,” “less than,” “less than or equal to,” “not more than,” “lower than,” “lower than or equal to,” “not higher than,” and “below”.

[0147] In some embodiments, devices, etc., may be interpreted as physical or virtual, and their names are not limited to those described in the embodiments. Terms such as “device,” “equipment,” “circuit,” “network element,” “network function,” “network device,” “function,” “node,” “unit,” “section,” “system,” “network,” “chip,” “chip system,” “entity,” and “subject” are interchangeable.

[0148] In some embodiments, "network" can be interpreted as devices included in a network (e.g., access network devices, core network devices, etc.).

[0149] In some embodiments, the terms "access network device (AN device)," "radio access network device (RAN device)," "base station (BS)," "radio base station," "fixed station," "node," "access point," "transmission point (TP)," "reception point (RP)," "transmission / reception point (TRP)," "panel," "antenna panel," "antenna array," "cell," "macro cell," "small cell," "femto cell," "pico cell," "sector," "cell group," "serving cell," "carrier," "component carrier," and "bandwidth part (BWP)" can be used interchangeably.

[0150] In some embodiments, the terms "terminal", "terminal device", "user equipment (UE)", "user terminal", "mobile station (MS)", "mobile terminal (MT)", "subscriber station", "mobile unit", "subscriber unit", "wireless unit", "remote unit", "mobile device", "wireless device", "wireless communication device", "remote device", "mobile subscriber station", "access terminal", "mobile terminal", "wireless terminal", "remote terminal", "handset", "user agent", "mobile client", and "client" can be used interchangeably.

[0151] In some embodiments, access network devices, core network devices, or network devices can be replaced by terminals. For example, embodiments of this disclosure can also be applied to structures where communication between access network devices, core network devices, or network devices and terminals is replaced by communication between multiple terminals (e.g., device-to-device (D2D), vehicle-to-everything (V2X), etc.). In this case, the structure can also be configured such that the terminal has all or part of the functions of the access network device. Furthermore, terms such as "uplink" and "downlink" can be replaced with terms corresponding to communication between terminals (e.g., "sidelink"). For example, uplink channel, downlink channel, etc., can be replaced with sidelink channel, and uplink link, downlink, etc., can be replaced with sidelink link.

[0152] In some embodiments, the terminal may be replaced by an access network device, a core network device, or a network device. In this case, the access network device, core network device, or network device may also be configured to have all or some of the functions of the terminal.

[0153] In some embodiments, the acquisition of data, information, etc., may comply with the laws and regulations of the country where the location is situated.

[0154] In some embodiments, data, information, etc., may be obtained with the user's consent.

[0155] Furthermore, each element, each row, or each column in the table of this disclosure can be implemented as an independent embodiment, and any combination of any element, any row, or any column can also be implemented as an independent embodiment.

[0156] Figure 1A is a schematic diagram of the architecture of a communication system according to an embodiment of the present disclosure.

[0157] As shown in Figure 1A, the communication system 100 includes a terminal 101 and a network device 102.

[0158] In some embodiments, terminal 101 includes, for example, at least one of the following: mobile phone, wearable device, Internet of Things device, car with communication function, smart car, tablet computer, computer with wireless transceiver function, virtual reality (VR) terminal device, augmented reality (AR) terminal device, wireless terminal device in industrial control, wireless terminal device in self-driving, wireless terminal device in remote medical surgery, wireless terminal device in smart grid, wireless terminal device in transportation safety, wireless terminal device in smart city, and wireless terminal device in smart home, but is not limited thereto.

[0159] In some embodiments, the access network device 102 may be a node or device that connects a terminal to a wireless network. The access network device may include at least one of the following in a 5G communication system: an evolved Node B (eNB), a next-generation eNB (ng-eNB), a next-generation Node B (gNB), a node B (NB), a home node B (HNB), a home evolved node B (HeNB), a wireless backhaul device, a radio network controller (RNC), a base station controller (BSC), a base transceiver station (BTS), a base band unit (BBU), a mobile switching center, a base station in a 6G communication system, an open RAN, a cloud RAN, a base station in other communication systems, and an access node in a Wi-Fi system, but is not limited thereto.

[0160] In some embodiments, the technical solutions of this disclosure can be applied to the Open RAN architecture. In this case, the interfaces between or within access network devices involved in the embodiments of this disclosure can be transformed into internal interfaces of Open RAN. The processes and information interactions between these internal interfaces can be implemented by software or programs.

[0161] In some embodiments, the access network device may be composed of a central unit (CU) and a distributed unit (DU). The CU may also be called a control unit. The CU-DU structure can separate the protocol layer of the access network device. Some of the protocol layer functions are centrally controlled by the CU, while the remaining part or all of the protocol layer functions are distributed in the DU and centrally controlled by the CU. However, this is not the only possibility.

[0162] In some embodiments, a core network device may be a single device comprising one or more network elements, or it may be multiple devices or a group of devices, each comprising all or part of the aforementioned one or more network elements. Network elements may be virtual or physical. The core network may include, for example, at least one of the evolved packet core (EPC), 5G core network (5GCN), and next-generation core (NGC).

[0163] It is understood that the communication system described in this disclosure is for the purpose of more clearly illustrating the technical solutions of this disclosure, and does not constitute a limitation on the technical solutions proposed in this disclosure. As those skilled in the art will know, with the evolution of system architecture and the emergence of new business scenarios, the technical solutions proposed in this disclosure are also applicable to similar technical problems.

[0164] The following embodiments of this disclosure can be applied to the communication system 100 shown in FIG1A, or to some of the main bodies, but are not limited thereto. The main bodies shown in FIG1A are illustrative. The communication system may include all or some of the main bodies in FIG1A, or it may include other main bodies outside of FIG1A. The number and form of each main body are arbitrary. Each main body may be physical or virtual. The connection relationship between the main bodies is illustrative. The main bodies may not be connected or may be connected. The connection can be in any way, it can be a direct connection or an indirect connection, it can be a wired connection or a wireless connection.

[0165] The embodiments disclosed herein can be applied to Long Term Evolution (LTE), LTE-Advanced (LTE-A), LTE-Beyond (LTE-B), Super 3G, IMT-Advanced, 4th Generation Mobile Communication System (4G), 5th Generation Mobile Communication System (5G), 5G New Radio (NR), Future Radio Access (FRA), New-Radio Access Technology (RAT), New Radio (NR), New Radio Access (NX), Future Generation Radio Access (FX), Global System for Mobile Communications (GSM), CDMA2000, Ultra Mobile Broadband (UMB), IEEE 802.11 (Wi-Fi), IEEE 802.16 (WiMAX), and IEEE 802.20, ultra-wideband (UWB), Bluetooth (a registered trademark), public land mobile network (PLMN) networks, device-to-device (D2D) systems, machine-to-machine (M2M) systems, internet of things (IoT) systems, vehicle-to-everything (V2X) systems, systems utilizing other communication methods, and next-generation systems built upon them. Furthermore, multiple systems can be combined (e.g., a combination of LTE or LTE-A with 5G).

[0166] In some embodiments, during CSI reporting, CSI calculation may be obtained directly through model inference. CSI calculation may also include both traditional non-artificial intelligence (non-AI) algorithms and artificial intelligence (AI) model inference. Alternatively, CSI calculation may involve multiple AI model inferences. For example, in traditional CSI feedback reporting based on the Rel-18 Type II Doppler codebook, CSI calculation includes at least CSI prediction and CSI measurement. CSI prediction refers to the terminal first configuring channel measurement resources according to the network equipment, then obtaining downlink channel information within the measurement window based on the received CSI-RS, then calculating the channel information for the next N4 time points in a prediction window using the traditional linear minimum mean square error (LMMSE) algorithm, and finally, the terminal measuring the CSI within the prediction window (CSI may include precoding matrix indication (PMI), channel quality indication (CQI), rank indication (RI), etc.) based on the predicted channel information for the N4 time points and reporting it to the network equipment. For example, as shown in Figure 1B, the terminal measures 4 CSIs within a measurement window (1 time slot) and then predicts 4 CSIs within a prediction window (1 time slot).

[0167] In this process, the traditional algorithm for predicting channel information at N4 future time points can be replaced by an AI model based on CSI prediction to further improve the accuracy of the predicted channel information, while CSI measurement still uses the traditional non-AI algorithm. Similarly, CSI measurement can also be replaced by an AI model with a traditional non-AI algorithm. As can be seen from the above, a single CSI report may contain one or more AI models.

[0168] Figure 2 is an interactive schematic diagram of a method for determining the number of CPUs according to an embodiment of the present disclosure. As shown in Figure 2, the embodiments of the present disclosure relate to a method for determining the number of CPUs, the method including:

[0169] Step S2101: The network device sends capability query information.

[0170] In some embodiments, the terminal receives capability query information. It should be noted that this embodiment is described in the case that the network device does not receive capability query information. In another embodiment, the network device may specify the recipient of the capability query information. For example, the network device sends capability query information to the terminal, and the terminal receives the capability query information sent by the network device.

[0171] In some embodiments, the capability query information is used to request the terminal's capabilities, or it can be understood as the capability query information being used to request the terminal to send its own capabilities, or the capability query information being used to request the terminal's ability to process CSI. This disclosure does not limit the function of the capability query information. Furthermore, this disclosure does not limit the name of the capability query information; for example, it may be called capability request information, capability acquisition information, etc.

[0172] In this embodiment of the disclosure, after the terminal receives the capability query information, it can execute the subsequent step S2102.

[0173] In some embodiments, terms such as “send,” “transmit,” “report,” “distribute,” “transmit,” “bidirectional transmission,” “send and / or receive” can be used interchangeably.

[0174] Step S2102: The terminal sends capability indication information.

[0175] In some embodiments, the capability indication information is used to indicate the terminal's capabilities when processing CSI. Alternatively, the capability indication information is used to indicate the capabilities that the terminal itself possesses.

[0176] Optionally, the capability indication information is used to indicate a first total quantity and / or a second total quantity. For example, the capability indication information is used to indicate a first total quantity. Or, for example, the capability indication information is used to indicate a second total quantity. Or, for example, the capability indication information is used to indicate both a first total quantity and a second total quantity.

[0177] Optionally, the first total number refers to the number of CPUs supporting the first processing method. The first processing method refers to the method by which the terminal processes CSI without using a model. For example, the first total number refers to the maximum number of CPUs supported when the terminal processes CSI without using a model.

[0178] In this embodiment of the disclosure, the number of CPUs used when processing CSI using the first processing method is not greater than the first total number, so that the number of CPUs used when the terminal does not use the model to process CSI will not exceed the maximum number supported by the terminal, thus ensuring the stability of the terminal processing CSI.

[0179] Optionally, the second total number refers to the number of CPUs supporting the second processing method. Here, the second processing method refers to the method by which the terminal processes CSI using a model-based approach. For example, the first total number refers to the maximum number of CPUs supported when the terminal processes CSI using a model-based approach.

[0180] In this embodiment of the disclosure, the number of CPUs used when processing CSI using the second processing method is not greater than the second total number, so that the number of CPUs used when the terminal uses the model to process CSI will not exceed the maximum number supported by the terminal, thus ensuring the stability of the terminal processing CSI.

[0181] In step S2103, the terminal and network device determine the first quantity and / or the second quantity.

[0182] In some embodiments, the terminal and network device determine a first quantity. Alternatively, the terminal and network device determine a second quantity. Alternatively, the terminal and network device determine both a first quantity and a second quantity.

[0183] In some embodiments, the terminal and the network device determine the first quantity and / or the second quantity in the same way to ensure that the first quantity determined by the terminal and the network device is the same, and / or that the second quantity is the same, thereby ensuring that there is a consistent understanding between the terminal and the network device, and thus ensuring that the parameters configured by the network device for CSI measurement of the terminal meet the requirements.

[0184] In some embodiments, the terminal and network device determine a first quantity and / or a second quantity based on capability indication information and / or communication protocols.

[0185] In some embodiments, the first quantity refers to the number of CPUs used when processing the i-th CSI using the first processing method, and the second quantity refers to the number of CPUs used when processing the i-th CSI using the second processing method. The first processing method refers to processing CSI without using a model, and the second processing method refers to processing CSI using a model. i is a positive integer.

[0186] Optionally, i is greater than 0 and less than or equal to N. Here, N refers to the total number of CSIs, or N is the total number of CSIs that the terminal needs to send, or N is the total number of CSIs that the terminal needs to report, or N can also be understood as the number of times the terminal needs to trigger CSI reporting.

[0187] In some embodiments, the terminal and network device determine a first quantity based on capability indication information. Alternatively, the terminal and network device determine a second quantity based on capability indication information. Or, the terminal and network device determine both a first quantity and a second quantity based on capability indication information.

[0188] In some embodiments, the terminal and network device determine the first quantity based on a communication protocol. Alternatively, it can be understood that the terminal and network device determine the first quantity through a predefined method. Alternatively, the first quantity is a predefined value. Alternatively, it can be understood that the terminal and network device define the first quantity through negotiation.

[0189] In some embodiments, the terminal and network device determine the second quantity based on a communication protocol. Alternatively, it can be understood that the terminal and network device determine the second quantity through a predefined method. Alternatively, the second quantity is a predefined value. Alternatively, it can be understood that the terminal and network device define the second quantity through negotiation.

[0190] In some embodiments, the terminal and network device determine a first quantity and a second quantity based on a communication protocol. Alternatively, it can be understood that the terminal and network device determine the first quantity and the second quantity through a predefined method. Alternatively, the first quantity and the second quantity are predefined values. Alternatively, it can be understood that the terminal and network device define the first quantity and the second quantity through negotiation.

[0191] In some embodiments, the terminal and network device determine a first quantity based on capability indication information and a communication protocol. Alternatively, the terminal and network device determine a second quantity based on capability indication information and a communication protocol. Or, the terminal and network device determine both a first and a second quantity based on capability indication information and a communication protocol.

[0192] It should be noted that the first quantity and / or the second quantity can be determined solely by a communication protocol between the terminal and the network device. The following explains how to determine the first quantity and / or the second quantity using a communication protocol.

[0193] In some embodiments, the terminal and network device determine a third quantity for each of the multiple models based on a communication protocol, and determine a second quantity based on the third quantity for each model.

[0194] Optionally, when multiple models are used to process CSI on the terminal, a third quantity can be set for each model through a communication protocol, and then a second quantity can be determined based on the third quantity of each model. This third quantity refers to the amount of CPU time occupied by the model when processing CSI. For example, the sum of the third quantities of each model among multiple models can be used to determine the second quantity. For example, the number of CPU times occupied may differ depending on the structure and function of the different models.

[0195] In some embodiments, the terminal and network device determine a fourth quantity corresponding to at least one model based on a communication protocol, and set this fourth quantity as the second quantity. Optionally, if the terminal uses one model to process CSI, the terminal and network device determine a fourth quantity of CPU used by that one model based on a communication protocol, and set this fourth quantity as the second quantity. Optionally, if the terminal uses multiple models to process CSI, the terminal and network device determine a fourth quantity based on a communication protocol, which represents the total number of CPUs used by the multiple models when processing CSI, and set a fourth quantity corresponding to the multiple models as the second quantity.

[0196] It should be noted that the above embodiment is illustrated by taking the determination of the second quantity by the terminal and network device based on a communication protocol. In another embodiment, the first quantity can also be determined by a communication protocol.

[0197] Optionally, the communication protocol specifies a first number of CSIs that the terminal will not use the model for processing. Then, the terminal and network device determine the first number of CSIs that the terminal will not use the model for processing based on the communication protocol. Alternatively, it can be said that the first number of CSIs that will not use the model for processing is a predefined value.

[0198] Optionally, the communication protocol specifies a second number of CSIs processed by the terminal using the model, and then the terminal and network device determine the second number of CSIs processed by the terminal using the model based on the communication protocol. Alternatively, it can be said that the second number of CSIs processed using the model is a predefined value.

[0199] Optionally, the communication protocol specifies a fifth quantity for CSI at at least one time point obtained based on model processing, and different first quantities can be determined when the fifth quantity has different values. For example, when the fifth quantity is equal to the first value, the first quantity is a predefined value. Alternatively, the first quantity is specified based on the communication protocol. Another example is when the fifth quantity is greater than the first value, the first quantity is determined based on a second coefficient and the fifth quantity. This second coefficient can be specified through the communication protocol.

[0200] It should be noted that if the first quantity and / or the second quantity are determined solely based on the communication protocol in this embodiment of the disclosure, then the above steps S2101 and S2102 may not be performed.

[0201] It should be noted that the above embodiments are illustrated using the example of determining the first and second quantities based on a communication protocol. In another embodiment, the first and / or second quantities can also be determined based on capability indication information and a communication protocol.

[0202] In some embodiments, the terminal and network device determine a third quantity for each model among multiple models based on capability indication information and a communication protocol, and determine a second quantity based on the third quantity for each model. Optionally, the capability indication information is used to indicate a first coefficient corresponding to each model, so the third quantity for a model can be determined based on the minimum number of CPUs for that model among multiple models and the first coefficient corresponding to that model. Correspondingly, the third quantity for other models among multiple models can also be determined in a similar manner. The minimum number of CPUs for each model among multiple models is specified by the communication protocol. For example, the minimum number of CPUs for the nth model is... If the first coefficient for each model is ω, then the third coefficient for the nth model is... Rounding down, n represents the nth model among multiple models.

[0203] In some embodiments, the terminal and network device determine a fourth quantity corresponding to at least one model based on capability indication information and a communication protocol, and define the fourth quantity as the second quantity. Optionally, the capability indication information is used to indicate a first coefficient corresponding to a model, the minimum number of CPUs for which the model is specified by the communication protocol, so the fourth quantity of the model can be determined based on the minimum number of CPUs for the model and the first coefficient corresponding to the model. For example, the minimum number of CPUs for a model is... If the first coefficient of a model is ω, then the fourth coefficient is...

[0204] In another embodiment, the terminal and network device may also determine a first quantity and / or a second quantity based on capability indication information.

[0205] In some embodiments, capability indication information is used to indicate a first coefficient corresponding to each model and a minimum number of CPUs for each model among multiple models. Optionally, the terminal and network device determine a third quantity for a model based on the minimum number of CPUs for that model among multiple models and the first coefficient corresponding to that model. Correspondingly, a similar method can be used to determine the third quantity for other models among multiple models. For example, the minimum number of CPUs for the nth model is... If the first coefficient for each model is ω, then the third coefficient for the nth model is...

[0206] In some embodiments, capability indication information is used to indicate multiple first coefficient groups, each first coefficient group corresponding to one of multiple models, and each first coefficient group includes at least one first sub-coefficient, with different first sub-coefficients corresponding to different measurement parameters. The measurement parameters include at least one of the following: the number of channel measurement resources, the number of antenna ports, system bandwidth, or a fifth quantity, where the fifth quantity refers to the number of CSIs at at least one moment obtained based on model inference. For example, the first coefficient group includes at least one of the following: first sub-coefficients corresponding to the number of channel measurement resources, first sub-coefficients corresponding to the number of antenna ports, first sub-coefficients corresponding to the system bandwidth, and first sub-coefficients corresponding to the fifth quantity.

[0207] Optionally, the terminal and network equipment determine the third quantity of a model based on a first coefficient group corresponding to one of the multiple models and the measurement parameters corresponding to the first sub-coefficients included in that first coefficient group. Correspondingly, a similar method can be used to determine the third quantity for other models among the multiple models. For example, if the fifth quantity is represented by N4 and the number of channel measurement resources is represented by K, then the third quantity of the nth model can be... or or Where X1 is the first sub-coefficient corresponding to the number of channel measurement resources, and X2 is the first sub-coefficient corresponding to the fifth quantity.

[0208] In some embodiments, capability indication information is used to indicate a second coefficient group corresponding to a model. The second coefficient group includes at least one second sub-coefficient, and different second sub-coefficients correspond to different measurement parameters. For example, the second coefficient group may include at least one of the following: the second sub-coefficient corresponding to the number of channel measurement resources, the second sub-coefficient corresponding to the number of antenna ports, the second sub-coefficient corresponding to the system bandwidth, and the second sub-coefficient corresponding to a fifth quantity.

[0209] Optionally, the terminal and network device determine the fourth quantity based on at least one second sub-coefficient and the measurement parameters corresponding to the second sub-coefficient. Alternatively, it can be understood that, for a given model, the terminal and network device determine the fourth quantity based on at least one second sub-coefficient of that model and the measurement parameters corresponding to the second sub-coefficient.

[0210] In some embodiments, capability indication information is used to indicate multiple third coefficient groups, where each third coefficient group corresponds to one of multiple models. Each third coefficient group includes at least one third sub-coefficient, and different third sub-coefficients correspond to different channel measurement resource types. These channel measurement resource types include aperiodic channel measurement resources, periodic channel measurement resources, semi-persistent channel measurement resources, etc. For example, an aperiodic channel measurement resource corresponds to one third sub-coefficient, a periodic channel measurement resource corresponds to another third sub-coefficient, and a semi-persistent channel measurement resource corresponds to yet another third sub-coefficient, etc. For example, the number of aperiodic channel measurement resource types is K. s Y1 is a third sub-coefficient corresponding to an aperiodic channel measurement resource. For example, the number of periodic or semi-persistent channel measurement resources is K. p .

[0211] Optionally, the terminal and network equipment determine the third quantity for a given model based on the third coefficient set corresponding to one of the multiple models and the number of channel measurement resources for different channel measurement resource types. Correspondingly, a similar method can be used to determine the third quantity for other models among the multiple models. For example, the third quantity for the nth model is... or,

[0212] It should be noted that if multiple models are used to process CSI in this embodiment of the disclosure, the third quantity for each model can be determined in the same way or in different ways. This embodiment of the disclosure does not limit the way of determining the third quantity for different models.

[0213] In some embodiments, capability indication information is used to indicate a fourth coefficient group corresponding to a model, the fourth coefficient group including at least one fourth sub-coefficient, and different fourth sub-coefficients corresponding to different channel measurement resource types.

[0214] Optionally, the terminal and network equipment determine the fourth quantity based on at least one fourth sub-coefficient and the number of channel measurement resources of different channel measurement resource types.

[0215] It should be noted that the capability indication information also includes a first total quantity and / or a second total quantity. The first total quantity refers to the number of CPUs that support the first processing method, and the second total quantity refers to the number of CPUs that support the second processing method.

[0216] Optionally, the first quantity is not greater than the first total quantity, and / or the second quantity is not greater than the second total quantity. In this embodiment of the disclosure, since there is a maximum number of CPUs occupied by the terminal using the first processing method and a maximum number of CPUs occupied by the second processing method, it is necessary to include the first quantity not being greater than the first total quantity, and / or the second quantity not being greater than the second total quantity, so as to ensure that the terminal has enough CPUs to support CSI processing.

[0217] It should be noted that in this embodiment of the disclosure, if the CPU used by the terminal when processing CSI exceeds the maximum number of CPUs supported by the terminal, then some CSIs need not be updated according to the priority of CSIs. The different situations are described below.

[0218] In some embodiments, if the third total number is greater than the first remaining number and the fourth total number is greater than the second remaining number, NM lower-priority CSIs are not updated. Here, N is the total number of CSIs, M is the smaller of M1 and M2, the third total number refers to the total number of CPUs used to process N CSIs using the first processing method, the fourth total number refers to the total number of CPUs used to process N CSIs using the second processing method, the first remaining number is the difference between the first total number and the number of CPUs already used by the first processing method, and the second remaining number is the difference between the second total number and the number of CPUs already used by the second processing method. The number of CPUs used to process M1 higher-priority CSIs using the first processing method is no greater than the first remaining number, and the number of CPUs used to process M2 higher-priority CSIs using the second processing method is no greater than the second remaining number. Here, N is the maximum number of CSIs the terminal needs to send to the network device. Alternatively, it can be understood as the maximum number of CSIs the terminal needs to report.

[0219] In this embodiment of the disclosure, since the number of CPUs occupied by the first processing method for CSI exceeds the number of CPUs remaining in the terminal when the first processing method is used, and the number of CPUs occupied by the second processing method for CSI also exceeds the number of CPUs remaining in the terminal when the second processing method is used, the terminal needs to select the smaller value from the first processing method and the second processing method. Therefore, it can be ensured that the CSI with higher priority can be updated, while the remaining CSI with lower priority will not be updated.

[0220] In this context, "updating" means that the terminal can obtain a new CSI using the first and second processing methods and send the obtained CSI to the network device, thus achieving an update. "Not updating" means that the terminal cannot obtain a new CSI using the first and second processing methods, and the terminal can only send the previously obtained CSI to the network device, thus failing to achieve an update.

[0221] In some embodiments, if the third total number is not greater than the first remaining number and the fourth total number is greater than the second remaining number, the N-M3 lower priority CSIs are not updated, or the N-M3 lower priority CSIs are reverted from the second processing method to the first processing method, and the number of CPUs occupied by the second processing method to process the M3 higher priority CSIs is not greater than the second remaining number.

[0222] In this embodiment of the disclosure, the number of CPUs occupied by processing M3 high-priority CSIs using the second processing method is no greater than the second remaining number. Therefore, N-M3 low-priority CSIs cannot be processed using the second processing method. In other words, N-M3 low-priority CSIs cannot be updated, meaning that N-M3 low-priority CSIs are not updated.

[0223] Additionally, if N-M3 lower-priority CSIs cannot be processed using the second processing method, but the first processing method supports processing all CSIs, then the N-M3 lower-priority CSIs processed using the second processing method can be rolled back to the first processing method, which means that the number of updated CSIs can be increased.

[0224] Optionally, NL low-priority CSIs are not updated, the CPU usage for processing L CSIs using the first processing method is no greater than the first remaining CPU, and the CPU usage for processing N-M3 CSIs using the second processing method is no greater than the second remaining CPU, where L is greater than or equal to M3.

[0225] In this embodiment of the disclosure, when N-M3 lower priority CSIs are rolled back to the first processing method, the number of CPUs used by the first processing method may exceed the upper limit of the total number of CPUs used by the terminal supported by the first processing method. Therefore, it is necessary to ensure that NL lower priority CSIs are not updated.

[0226] In some embodiments, if the third total number is greater than the first remaining number and the fourth total number is not greater than the second remaining number, the N-M4 lower priority CSIs are not updated, or the N-M4 lower priority CSIs are replaced by the second processing method instead of the first processing method, and the number of CPUs occupied by processing the M4 higher priority CSIs using the first processing method is not greater than the second remaining number.

[0227] In this embodiment of the disclosure, the number of CPUs occupied by processing M4 high-priority CSIs using the first processing method is no greater than the first remaining number of CPUs. Therefore, N-M4 low-priority CSIs cannot be processed using the first processing method. In other words, N-M4 low-priority CSIs cannot be updated, meaning that N-M4 low-priority CSIs are not updated.

[0228] In addition, if the N-M4 lower priority CSIs cannot be processed using the first processing method, but the second processing method supports processing all CSIs, then the N-M4 lower priority CSIs processed using the first processing method can be replaced by the second processing method, which means that the number of updated CSIs can be increased.

[0229] Optionally, the NS lower-priority CSIs are not updated, the CPU usage for processing M4 CSIs using the first processing method is no greater than the second remaining number, and the CPU usage for processing S CSIs using the second processing method is no greater than the second remaining number, where S is greater than or equal to M.

[0230] In this embodiment of the disclosure, when N-M4 lower priority CSIs are replaced with the second processing method, the number of CPUs used by the second processing method may exceed the upper limit of the total number of CPUs used by the second processing method supported by the terminal. Therefore, it is ensured that N-N lower priority CSIs are not updated.

[0231] The various methods in the above embodiments will be described below by way of example.

[0232] For example, suppose a network device is configured with K ∈ {4,8,12} aperiodic CSI-RS resources. The terminal first estimates the downlink channel information at K time points, then inputs this information into an AI model. The AI ​​model then infers the downlink channel information for the next N4 time points. Based on the downlink channel information at N4 ∈ {1,2,4,8} time points, the terminal calculates the CSI (PMI / RI / CQI) using a traditional non-AI algorithm and reports the CSI to the network device.

[0233] The traditional non-AI algorithm is similar to the first processing method in the above embodiments. The AI ​​model-based reasoning is similar to the second processing method in the above embodiments.

[0234] For N4=1, the number of CPUs used by traditional non-AI algorithms. By predefining, for functions where N4 > 1, the traditional non-AI algorithm requires N4 CPU resources, such as... The value of x is reported through the terminal's capability indication information. Optionally, different values ​​of N4 are all represented as functions of N4.

[0235] For different values ​​of K and / or N4, the number of CPUs used for AI model inference. The UE capability reports an indication to the NW, or a function representing K and / or N4, such as... or The values ​​of X1 and X2 are indicated by the UE capability reporting.

[0236] Optionally, the UE reports the number of CPUs used when the values ​​of indication K and / or N4 are at their minimum. Then, for other K and / or N4 values, the UE reports them. The value of ω is reported through the terminal's capability indication information. Optionally, for different values ​​of N4, different numbers of CPUs are defined for AI model inference, and the number of CPUs used by each model is indicated by the terminal through the capability indication information.

[0237] For N4=1, the number of CPUs used for AI model inference. or For N4>1,

[0238] For example, assuming N4 = 1, the number of CPUs used by the predefined Non-AI algorithm and the number of CPUs used by the AI ​​model inference are defined as shown in Table 1 below.

[0239] Table 1

[0240] Assuming N4>1, the number of CPUs used by the predefined Non-AI algorithm and the number of CPUs used for AI model inference are defined as shown in Table 2 below.

[0241] Table 2

[0242] If the UE uses a bilateral AI model to compress the downlink channel information obtained at N4 time points through the UE-side encoder and report it to the NW, then for the nth CSI report, when N4 = 1, the number of CPUs occupied by the CSI prediction AI model inference is defined. or As an example, the number of CPUs occupied by the CSI compressed AI model in, This indicates the minimum number of CPUs required for CSI compression using the AI ​​model, which can be reported through the terminal's capability indication information. Optionally, the number of CPUs used for CSI compression can be independently indicated through terminal capability reporting. The number of CPUs used in different scenarios is shown in Table 3.

[0243] Table 3

[0244] When N4 > 1, the number of CPUs used by the CSI compressed AI model The value of ω2 is indicated by the UE capability reporting. Optionally, the CSI compression AI model's usage is represented as a function related to the NW configuration parameters associated with the AI ​​model's input / output dimensions. These configuration parameters include at least the number of antenna ports, channel bandwidth, number of channel measurement resources, and the number of times the CSI is output. For example... Where K represents the number of channel measurement resources. The number of CPUs used in different cases is shown in Table 4.

[0245] Table 4

[0246] Assuming NW is configured with one periodic or semi-persistent CSI-RS resource, the number of CPUs used by the CSI prediction AI model. Where Y2 represents the value of the terminal capability reporting indication. K p K represents the activated p The number of periodic CSI-RS resources can also be determined through UE capability reporting or NW configuration indication. Note that the number of CPUs used by the aforementioned non-periodic CSI-RS resources can also be used to determine the number of CPUs used by periodic CSI-RS resources. This is just one way to determine the number of CPUs used when configuring periodic or semi-persistent CSI-RS resources in the NW configuration.

[0247] In some embodiments, terms such as "certain," "preset," "default," "set," "indicated," "a certain," "any," and "first" can be used interchangeably. "Certain A," "preset A," "default A," "set A," "indicated A," "a certain A," "any A," and "first A" can be interpreted as A pre-defined in a protocol or the like, or as A obtained through setting, configuration, or instruction, or as specific A, a certain A, any A, or first A, but are not limited thereto.

[0248] In some embodiments, the names of information, etc., are not limited to the names described in the embodiments. Terms such as "information", "message", "signal", "signaling", "report", "configuration", "indication", "instruction", "command", "channel", "parameter", "domain", "field", "symbol", "symbol", "codebook", "codeword", "codepoint", "bit", "data", "program", and "chip" can be used interchangeably.

[0249] In some embodiments, "acquire," "get," "obtain," "receive," "transmit," "bidirectional transmission," and "send and / or receive" can be used interchangeably and can be interpreted as receiving from other entities, acquiring from protocols, acquiring from higher layers, obtaining through self-processing, or autonomous implementation. Protocols include, for example, at least one of the 3GPP protocol, Wi-Fi protocol, and audio and / or video protocols.

[0250] In some embodiments, the terminal may also send indication information to the network device to indicate at least one of the first parameter, second parameter, or third parameter used.

[0251] In some embodiments, the network device may send indication information to the terminal to indicate at least one of the first parameter, second parameter, or third parameter used.

[0252] In some embodiments, the terms "uplink", "uplink", and "physical uplink" can be used interchangeably, as can the terms "downlink", "downlink", and "physical downlink", as well as the terms "sidelink", "sidelink", "sidelink communication", "sidelink communication", "direct connection", "direct link", "direct communication", and "direct link communication".

[0253] In some embodiments, the terms “downlink control information (DCI),” “downlink (DL) assignment,” “DL DCI,” “uplink (UL) grant,” and “UL DCI” can be used interchangeably.

[0254] In some embodiments, terms such as "physical downlink shared channel (PDSCH)" and "DL data" can be used interchangeably, as can terms such as "physical uplink shared channel (PUSCH)" and "UL data".

[0255] In some embodiments, the terms “radio”, “wireless”, “radio access network (RAN)”, “access network (AN)”, and “RAN-based” can be used interchangeably.

[0256] In some embodiments, terms such as “moment,” “point in time,” “time,” and “time location” can be used interchangeably, as can terms such as “duration,” “segment,” “time window,” “window,” and “time.”

[0257] In some embodiments, the terms "component carrier (CC)," "cell," "frequency carrier," and "carrier frequency" can be used interchangeably.

[0258] In some embodiments, the terms “resource block (RB)”, “physical resource block (PRB)”, “sub-carrier group (SCG)”, “resource element group (REG)”, “PRB pair”, “RB pair”, “resource element (RE)”, and “sub-carrier” can be used interchangeably.

[0259] In some embodiments, terms such as wireless access scheme and waveform can be used interchangeably.

[0260] In some embodiments, the terms "precoding", "precoder", "weight", "precoding weight", "quasi-co-location (QCL)", "transmission configuration indication (TCI) status", "spatial relation", "spatial domain filter", "transmission power", "phase rotation", "antenna port", "antenna port group", "layer", "the number of layers", "rank", "resource", "resource set", "resource group", "beam", "beam width", "beam angular degree", "antenna", "antenna element", and "panel" can be used interchangeably.

[0261] In some embodiments, the terms “frame”, “radio frame”, “subframe”, “slot”, “sub-slot”, “mini-slot”, “symbol”, “symbol”, and “transmission time interval (TTI)” can be used interchangeably.

[0262] In some embodiments, the determination or judgment can be made by a value represented by 1 bit (0 or 1), or by a true or false value (boolean), or by a comparison of numerical values ​​(e.g., a comparison with a predetermined value), but is not limited thereto.

[0263] In some embodiments, "not expecting to receive" can be interpreted as not receiving on time domain resources and / or frequency domain resources, or as not performing subsequent processing on the data and / or instructions received; "not expecting to send" can be interpreted as not sending, or as sending but not expecting the receiver to respond to the sent content.

[0264] In some embodiments, if an arrow in the interaction diagram representing the sending of information, signaling, etc. from one subject to another passes through other subjects, it can be interpreted as the information being forwarded from one subject to another via other subjects, or it can be interpreted as the information being sent from one subject to another without passing through other subjects.

[0265] The communication method involved in the embodiments of this disclosure may include at least one of steps S2101 to S2103. For example, step S2101 may be implemented as a separate embodiment, step S2102 may be implemented as a separate embodiment, step S2103 may be implemented as a separate embodiment, and steps S2101 and S2102 may be implemented as separate embodiments, but are not limited thereto.

[0266] In some embodiments, at least one of steps S2101 to S2103 is optional, and one or more of these steps may be omitted or substituted in different embodiments.

[0267] In some embodiments, the steps and their optional implementations in other embodiments described before or after this embodiment, as well as other related parts in the specification, can be referred to, and will not be repeated here.

[0268] Figure 3A is an interactive schematic diagram illustrating a method for determining the number of CPUs according to an embodiment of the present disclosure. As shown in Figure 3A, the embodiments of the present disclosure relate to a method for determining the number of CPUs, the method including:

[0269] In step S3101, the terminal determines the first quantity and / or the second quantity.

[0270] Wherein, the first quantity refers to the number of CPUs used when processing the i-th Channel State Information (CSI) using the first processing method, and the second quantity refers to the number of CPUs used when processing the i-th CSI using the second processing method. The first processing method refers to the method of processing CSI without using a model, and the second processing method refers to the method of processing CSI using a model. i is a positive integer.

[0271] In some embodiments, step S3101 is similar to step S2102 in the embodiment of FIG2 above, and will not be described again here.

[0272] In some embodiments, the method further includes:

[0273] Send capability indication information to the network device, the capability indication information being used to indicate the terminal's capabilities when processing CSI;

[0274] Determining the first quantity and / or the second quantity includes:

[0275] The first quantity and / or the second quantity are determined based on the capability indication information.

[0276] In some embodiments, determining the second quantity includes:

[0277] Determine a third quantity for each model among multiple models, and determine a second quantity based on the third quantity for each model; or,

[0278] Determine a fourth quantity corresponding to at least one model, and define the fourth quantity as the second quantity.

[0279] In some embodiments, capability indication information is used to indicate a first coefficient corresponding to each model.

[0280] Determining the third quantity for each of the multiple models includes:

[0281] The third quantity of a model is determined based on the minimum number of CPUs for one of the multiple models and the first coefficient corresponding to that model.

[0282] In some embodiments, capability indication information is used to indicate the minimum number of CPUs for each model among a plurality of models;

[0283] Determining the third quantity for each of the multiple models includes:

[0284] The third quantity of a model is determined based on the minimum number of CPUs for one of the multiple models and the first coefficient corresponding to that model.

[0285] In some embodiments, capability indication information is used to indicate multiple first coefficient groups, one first coefficient group corresponding to one model among multiple models, and the first coefficient group includes at least one first sub-coefficient, different first sub-coefficients corresponding to different measurement parameters; the measurement parameters include at least one of the number of channel measurement resources, the number of antenna ports, system bandwidth, or a fifth quantity, wherein the fifth quantity refers to the number of CSIs at at least one moment obtained based on model inference;

[0286] Determining the third quantity for each of the multiple models includes:

[0287] Based on the first coefficient group corresponding to one of the multiple models and the measurement parameters corresponding to the first sub-coefficients included in the first coefficient group, the third quantity of the one model is determined.

[0288] In some embodiments, capability indication information is used to indicate a second coefficient group corresponding to the model, the second coefficient including at least one second sub-coefficient, and different second sub-coefficients corresponding to different measurement parameters;

[0289] Determining the fourth quantity corresponding to at least one model includes:

[0290] The fourth quantity is determined based on the at least one second sub-coefficient and the measurement parameters corresponding to the second sub-coefficient.

[0291] In some embodiments, capability indication information is used to indicate a plurality of third coefficient groups, one third coefficient group corresponding to one of the plurality of models, the third coefficient group including at least one third sub-coefficient, and different third sub-coefficients corresponding to different channel measurement resource types;

[0292] Determining the third quantity for each of the multiple models includes:

[0293] The third quantity for each model is determined based on the third coefficient group corresponding to one of the multiple models and the number of channel measurement resources for different channel measurement resource types.

[0294] In some embodiments, capability indication information is used to indicate a fourth coefficient group corresponding to the model, the fourth coefficient group including at least one fourth sub-coefficient, and different fourth sub-coefficients corresponding to different channel measurement resource types;

[0295] Based on determining at least one fourth quantity corresponding to a model, including:

[0296] The fourth quantity is determined based on the at least one fourth sub-coefficient and the number of channel measurement resources of different channel measurement resource types.

[0297] In some embodiments, the capability indication information is used to indicate a first total quantity and / or a second total quantity, wherein the first total quantity refers to the number of CPUs supporting the first processing mode and the second total quantity refers to the number of CPUs supporting the second processing mode.

[0298] In some embodiments, the first quantity is not greater than the first total quantity, and / or the second quantity is not greater than the second total quantity.

[0299] In some embodiments, when the fifth quantity is equal to the first value, the first quantity is a predefined value;

[0300] When the fifth quantity is greater than the first value, the first quantity is determined based on the second coefficient and the fifth quantity;

[0301] The fifth quantity refers to the quantity of at least one moment, where at least one moment refers to the moment when CSI is obtained based on model processing.

[0302] In some embodiments, the third total number is greater than the first remaining number and the fourth total number is greater than the second remaining number. NM low-priority CSIs are not updated, where N is the total number of CSIs and M is the smaller of M1 and M2. The third total number refers to the total number of CPUs occupied by processing N CSIs using the first processing method, and the fourth total number refers to the total number of CPUs occupied by processing N CSIs using the second processing method. The first remaining number refers to the difference between the first total number and the number of CPUs already occupied by the first processing method, and the second remaining number refers to the difference between the second total number and the number of CPUs already occupied by the second processing method.

[0303] The number of CPUs used to process M1 high-priority CSIs using the first processing method is no greater than the first remaining number of CPUs, and the number of CPUs used to process M2 high-priority CSIs using the second processing method is no greater than the second remaining number of CPUs.

[0304] In some embodiments, the third total number is not greater than the first remaining number and the fourth total number is greater than the second remaining number. The N-M3 lower priority CSIs are not updated, or the N-M3 lower priority CSIs are reverted from the second processing method to the first processing method. The number of CPUs occupied by the second processing method to process the M3 higher priority CSIs is not greater than the second remaining number.

[0305] In some embodiments, NL low-priority CSIs are not updated, the number of CPUs used to process L CSIs using the first processing method is not greater than the first remaining number, and the number of CPUs used to process N-M3 CSIs using the second processing method is not greater than the second remaining number, where L is greater than or equal to M3.

[0306] In some embodiments, the third total number is greater than the first remaining number and the fourth total number is not greater than the second remaining number, and the N-M4 lower priority CSIs are not updated, or the N-M4 lower priority CSIs are replaced by the second processing method by the first processing method, and the number of CPUs occupied by processing the M4 higher priority CSIs using the first processing method is not greater than the second remaining number.

[0307] In some embodiments, NS low-priority CSIs are not updated, the number of CPUs used to process M4 CSIs using the first processing method is no greater than the second remaining number, and the number of CPUs used to process S CSIs using the second processing method is no greater than the second remaining number, where S is greater than or equal to M.

[0308] In some embodiments, the steps and their optional implementations in other embodiments described before or after this embodiment, as well as other related parts in the specification, can be referred to, and will not be repeated here.

[0309] Figure 3B is an interactive schematic diagram illustrating a method for determining the number of CPUs according to an embodiment of the present disclosure. As shown in Figure 3B, the embodiments of the present disclosure relate to a method for determining the number of CPUs, the method including:

[0310] Step S3201: The network device determines the first quantity and / or the second quantity.

[0311] In some embodiments, the first quantity refers to the number of CPUs used when processing the i-th Channel State Information (CSI) using the first processing method, and the second quantity refers to the number of CPUs used when processing the i-th CSI using the second processing method. The first processing method refers to processing CSI without using a model, and the second processing method refers to processing CSI using a model. i is a positive integer.

[0312] Step S3201 is similar to step S2102 in the embodiment of Figure 2 above, and will not be described again here. Step S3202 is similar to step S2103 in the embodiment of Figure 2 above, and will not be described again here.

[0313] In some embodiments, the method further includes:

[0314] The terminal receives capability indication information, which indicates the terminal's capability when processing CSI.

[0315] Determining the first quantity and / or the second quantity includes:

[0316] The first quantity and / or the second quantity are determined based on the capability indication information.

[0317] In some embodiments, determining the second quantity includes:

[0318] Determine a third quantity for each model among multiple models, and determine a second quantity based on the third quantity for each model; or,

[0319] Determine a fourth quantity corresponding to at least one model, and define the fourth quantity as the second quantity.

[0320] In some embodiments, capability indication information is used to indicate a first coefficient corresponding to each model.

[0321] Determining the third quantity for each of the multiple models includes:

[0322] The third quantity of a model is determined based on the minimum number of CPUs for one of the multiple models and the first coefficient corresponding to that model.

[0323] In some embodiments, capability indication information is used to indicate the minimum number of CPUs for each model among a plurality of models;

[0324] Determining the third quantity for each of the multiple models includes:

[0325] The third quantity of a model is determined based on the minimum number of CPUs for one of the multiple models and the first coefficient corresponding to that model.

[0326] In some embodiments, capability indication information is used to indicate multiple first coefficient groups, one first coefficient group corresponding to one model among multiple models, and the first coefficient group includes at least one first sub-coefficient, different first sub-coefficients corresponding to different measurement parameters; the measurement parameters include at least one of the number of channel measurement resources, the number of antenna ports, system bandwidth, or a fifth quantity, wherein the fifth quantity refers to the number of CSIs at at least one moment obtained based on model inference;

[0327] Determining the third quantity for each of the multiple models includes:

[0328] Based on the first coefficient group corresponding to one of the multiple models and the measurement parameters corresponding to the first sub-coefficients included in the first coefficient group, the third quantity of the one model is determined.

[0329] In some embodiments, capability indication information is used to indicate a second coefficient group corresponding to the model, the second coefficient including at least one second sub-coefficient, and different second sub-coefficients corresponding to different measurement parameters;

[0330] Determining the fourth quantity corresponding to at least one model includes:

[0331] The fourth quantity is determined based on the at least one second sub-coefficient and the measurement parameters corresponding to the second sub-coefficient.

[0332] In some embodiments, capability indication information is used to indicate a plurality of third coefficient groups, one third coefficient group corresponding to one of the plurality of models, the third coefficient group including at least one third sub-coefficient, and different third sub-coefficients corresponding to different channel measurement resource types;

[0333] Determining the third quantity for each of the multiple models includes:

[0334] The third quantity for each model is determined based on the third coefficient group corresponding to one of the multiple models and the number of channel measurement resources for different channel measurement resource types.

[0335] In some embodiments, capability indication information is used to indicate a fourth coefficient group corresponding to the model, the fourth coefficient group including at least one fourth sub-coefficient, and different fourth sub-coefficients corresponding to different channel measurement resource types;

[0336] Based on determining at least one fourth quantity corresponding to a model, including:

[0337] The fourth quantity is determined based on the at least one fourth sub-coefficient and the number of channel measurement resources of different channel measurement resource types.

[0338] In some embodiments, the capability indication information further includes a first total number and / or a second total number, wherein the first total number refers to the number of CPUs supporting the first processing mode and the second total number refers to the number of CPUs supporting the second processing mode.

[0339] In some embodiments, the first quantity is not greater than the first total quantity, and / or the second quantity is not greater than the second total quantity.

[0340] In some embodiments, when the fifth quantity is equal to the first value, the first quantity is a predefined value;

[0341] When the fifth quantity is greater than the first value, the first quantity is determined based on the second coefficient and the fifth quantity;

[0342] The fifth quantity refers to the quantity of at least one moment, where at least one moment refers to the moment when CSI is obtained based on model processing.

[0343] In some embodiments, the third total number is greater than the first remaining number and the fourth total number is greater than the second remaining number. NM low-priority CSIs are not updated, where N is the total number of CSIs and M is the smaller of M1 and M2. The third total number refers to the total number of CPUs occupied by processing N CSIs using the first processing method, and the fourth total number refers to the total number of CPUs occupied by processing N CSIs using the second processing method. The first remaining number refers to the difference between the first total number and the number of CPUs already occupied by the first processing method, and the second remaining number refers to the difference between the second total number and the number of CPUs already occupied by the second processing method.

[0344] The number of CPUs used to process M1 high-priority CSIs using the first processing method is no greater than the first remaining number of CPUs, and the number of CPUs used to process M2 high-priority CSIs using the second processing method is no greater than the second remaining number of CPUs.

[0345] In some embodiments, the third total number is not greater than the first remaining number and the fourth total number is greater than the second remaining number. The N-M3 lower priority CSIs are not updated, or the N-M3 lower priority CSIs are reverted from the second processing method to the first processing method. The number of CPUs occupied by the second processing method to process the M3 higher priority CSIs is not greater than the second remaining number.

[0346] In some embodiments, NL low-priority CSIs are not updated, the number of CPUs used to process L CSIs using the first processing method is not greater than the first remaining number, and the number of CPUs used to process N-M3 CSIs using the second processing method is not greater than the second remaining number, where L is greater than or equal to M3.

[0347] In some embodiments, the third total number is greater than the first remaining number and the fourth total number is not greater than the second remaining number, and the N-M4 lower priority CSIs are not updated, or the N-M4 lower priority CSIs are replaced by the second processing method by the first processing method, and the number of CPUs occupied by processing the M4 higher priority CSIs using the first processing method is not greater than the second remaining number.

[0348] In some embodiments, NS low-priority CSIs are not updated, the number of CPUs used to process M4 CSIs using the first processing method is no greater than the second remaining number, and the number of CPUs used to process S CSIs using the second processing method is no greater than the second remaining number, where S is greater than or equal to M.

[0349] In some embodiments, the steps and their optional implementations in other embodiments described before or after this embodiment, as well as other related parts in the specification, can be referred to, and will not be repeated here.

[0350] Figure 4 is a flowchart illustrating a method for determining the number of CPUs according to an embodiment of the present disclosure. As shown in Figure 4, this disclosure relates to a method for determining the number of CPUs, the method including:

[0351] Step S4101: The number of CPUs used by the CSI report is determined by the number of CPUs used by the traditional non-AI algorithm and the number of CPUs used by the AI ​​model inference.

[0352] Optionally, when the CSI in an AI model-based CSI report is obtained based on inference from multiple AI models, the number of CPUs used by the CSI report is determined by the number of CPUs used by each AI model.

[0353] In some embodiments, the UE reporting indication can support the total number N of CPUs N used for simultaneous CSI calculation. CPU and / or N ACPU , where N CPU (First CPU) and N ACPU (Second CPU) represents the total number of CSIs calculated based on the traditional Non-AI algorithm and the total number of CSIs obtained based on AI model inference, respectively.

[0354] Optionally, let the number of CPUs used for the i-th CSI report be denoted as and and Let represent the number of CPUs used by the traditional non-AI algorithm and the number of CPUs used by the AI ​​inference algorithm when calculating the nth CSI, respectively.

[0355] For example, if L CPU ≤N CPU and L ACPU ≤N ACPU When occupied,

[0356] In some embodiments, for the i-th CSI report, if the CSI report is obtained based on inference from multiple AI models, then the CPU usage is defined as follows:

[0357] Alt1: Defines the total number of CPUs used for AI-based inference.

[0358] Alt2: Defined as the sum of the number of CPUs used for each AI-based inference.

[0359] Optionally, the number of each CPU can be determined by one or more combinations of the following methods:

[0360] Option 1: Minimum number of CPUs required for each AI model (AI function) It is indicated by the UE capability reporting, and then by the UE capability reporting, it indicates the value of the additional parameter ω. Different AI model input and / or output dimensions can be associated with different ω values, which determines the number of CPUs used by the AI ​​model. pass Determined together with ω, such as the number of CPUs used.

[0361] Option 2: The number of CPUs used by the AI ​​model is determined based on at least one of the following parameters: the number of channel measurement resources, antenna ports, and system bandwidth related to the input dimension (NW configuration), and / or the number of CSI reporting times (N4 parameters related to the output dimension). The determination method is that the number of CPUs used is expressed as a function of at least one of the above parameters, such as... or X1 and X2 represent the values ​​of the number of different channel measurement resources K and the number of CSI reporting times N4. The values ​​of X1 and X2 are reported to NW through the UE capability reporting.

[0362] Option 3: The number of CPUs used by the AI ​​model is determined based on the time-domain type of the channel measurement resources configured in the NW. For aperiodic channel measurement resources, the number of CPUs used represents the number of aperiodic channel measurement resources, K. s functions, such as The Y1 value is reported to the NW via the UE capability; for periodic / semi-persistent channel measurement resources, the number of CPUs occupied is represented by the number K of active periodic / semi-persistent channel measurement resources. p Alternatively, a function that reports the number of CSI times, N4. or The number K of activated periodic / semi-persistent channel measurement resources P The Y2 and Y3 values ​​can be determined through predefined settings, NW configuration, or UE reporting. The UE capability reports the values ​​to the NW.

[0363] In some embodiments, it is assumed that N CSI reports are included within a certain time frame. These N CSI reports occupy the number of CPUs required for traditional non-AI CSI processing and / or the number of ACPUs required for AI-based CSI processing. Let...

[0364] N CPU and respectively denote the total non-AI based CPU and AI based CPU.(N CPU and (These represent the total number of CPUs based on AI and those not based on AI, respectively)

[0365] L1 and L2 respectively denote the CPU used by non-AI and AI-based CPUs.

[0366] In some embodiments, how should UE behavior be defined, if... and / or

[0367] Optionally, the following processing methods can be used for the same period of time.

[0368] Case 1: If and Of the N CSI reports, NM lower-priority CSI reports will not be updated.

[0369] Case 2: if and Of the N CSI reports, NM lower-priority CSI reports are not updated, or AI-based CSI processing reverts to traditional non-AI processing methods, and the reversion still results in... Otherwise, the lower-priority CSI reports among the N CSI reports will not be updated until the total number of CPUs used by all CSI reports is no greater than N. CPU -L1.

[0370] Case 3: if and Of the N CSI reports, NM lower-priority CSI reports are not updated, or traditional non-AI CSI processing is replaced with AI-based CSI processing, and this ensures... Otherwise, the CSI reports with lower priority among the N CSI reports will not be updated until the total number of ACPUs occupied by all CSI reports is no greater than [a certain value].

[0371] Example:

[0372] Assuming the NW is configured with K aperiodic CSI-RS resources ∈ {4,8,12}, the UE first estimates the downlink channel information at K time points, then inputs this information into an AI model. The AI ​​model then infers the downlink channel information for the next N4 time points. Based on this N4 ∈ {1,2,4,8} downlink channel information, the UE calculates CSIs such as PMI / RI / CQI using traditional non-AI algorithms and reports the CSIs to the NW.

[0373] For N4=1, the number of CPUs used by traditional non-AI algorithms. By predefining, for functions where N4 > 1, the traditional non-AI algorithm requires N4 CPU resources, such as... The value of x is indicated by the UE capability report. Optionally, different values ​​of N4 are all represented as functions of N4.

[0374] For different values ​​of K and / or N4, the number of CPUs used for AI model inference. The UE capability reports an indication to the NW, or a function representing K and / or N4, such as... or The values ​​of X1 and X2 are indicated by the UE capability reporting.

[0375] Optionally, the UE reports the number of CPUs used when the values ​​of indication K and / or N4 are at their minimum. Then, for other K and / or N4 values, the UE reports them. The value of ω is indicated by the UE capability reporting. Optionally, for different N4 values, different numbers of CPUs are defined for AI model inference, and the number of CPUs occupied by each model is indicated by the UE independently.

[0376] For N4=1, the number of CPUs used for AI model inference. or For N4>1,

[0377] For example, assuming N4 = 1, the number of CPUs used by the predefined Non-AI algorithm and the number of CPUs used by the AI ​​model inference are defined as shown in Table 1.

[0378] Assuming N4>1, the number of CPUs used by the predefined Non-AI algorithm and the number of CPUs used for AI model inference are defined as shown in Table 2 below.

[0379] If the UE uses a bilateral AI model to compress the downlink channel information obtained at N4 time points through the UE-side encoder and report it to the NW, then for the nth CSI report, when N4 = 1, the number of CPUs occupied by the CSI prediction AI model inference is defined. or As an example, the number of CPUs occupied by the CSI compressed AI model in, This indicates the minimum number of CPUs required for CSI compression using an AI model, which can be reported via UE capabilities. Optionally, the number of CPUs used for CSI compression can be independently indicated via UE capabilities.

[0380] When N4 > 1, the number of CPUs used by the CSI compressed AI model The value of ω2 is indicated by the UE capability reporting. Optionally, the CSI compression AI model's usage is represented as a function related to the NW configuration parameters associated with the AI ​​model's input / output dimensions. These configuration parameters include at least the number of antenna ports, channel bandwidth, number of channel measurement resources, and the number of times the CSI is output. For example... Where K represents the number of channel measurement resources.

[0381] Assuming NW is configured with one periodic or semi-persistent CSI-RS resource, the number of CPUs used by the CSI prediction AI model. Where Y2 represents the value of the UE capability reporting indication. K p K represents the activated p The number of periodic CSI-RS resources can also be determined through UE capability reporting or NW configuration indication. Note that the number of CPUs used by the aforementioned non-periodic CSI-RS resources can also be used to determine the number of CPUs used by periodic CSI-RS resources. This is just one way to determine the number of CPUs used when configuring periodic or semi-persistent CSI-RS resources in the NW configuration.

[0382] In some embodiments, the steps and their optional implementations in other embodiments described before or after this embodiment, as well as other related parts in the specification, can be referred to, and will not be repeated here.

[0383] This disclosure also proposes an apparatus (also referred to as a communication device, etc.) for implementing any of the above methods. For example, an apparatus is proposed that includes units or modules for implementing the steps performed by the terminal in any of the above methods. Furthermore, another apparatus is proposed that includes units or modules for implementing the steps performed by a network device (e.g., an access network device, a core network functional node, a core network device, etc.) in any of the above methods.

[0384] It should be understood that the division of units or modules in the above device is only a logical functional division. In actual implementation, they can be fully or partially integrated into a single physical entity, or they can be physically separated. Furthermore, the units or modules in the device can be implemented by a processor calling software: for example, the device includes a processor connected to a memory containing instructions. The processor calls the instructions stored in the memory to implement any of the above methods or to implement the functions of the units or modules in the above device. The processor can be, for example, a general-purpose processor, such as a Central Processing Unit (CPU) or a microprocessor, and the memory can be internal or external to the device. Alternatively, the units or modules in the device can be implemented in the form of hardware circuits. The functionality of some or all of the units or modules can be achieved through the design of these hardware circuits, which can be understood as one or more processors. For example, in one implementation, the hardware circuit is an application-specific integrated circuit (ASIC). The functionality of some or all of the units or modules is achieved through the design of the logical relationships between the components within the circuit. In another implementation, the hardware circuit can be implemented using a programmable logic device (PLD). Taking a field-programmable gate array (FPGA) as an example, it can include a large number of logic gates. The connection relationships between the logic gates are configured through configuration files, thereby achieving the functionality of some or all of the units or modules. All units or modules of the above device can be implemented entirely through processor-called software, entirely through hardware circuits, or partially through processor-called software with the remaining parts implemented through hardware circuits.

[0385] In this embodiment, the processor is a circuit with signal processing capabilities. In one implementation, the processor can be a circuit with instruction read and execute capabilities, such as a Central Processing Unit (CPU), a microprocessor, a graphics processing unit (GPU) (which can be understood as a microprocessor), or a digital signal processor (DSP). In another implementation, the processor can implement certain functions through the logical relationships of hardware circuits. The logical relationships of the aforementioned hardware circuits are fixed or reconfigurable. For example, the processor is a hardware circuit implemented using an application-specific integrated circuit (ASIC) or a programmable logic device (PLD), such as an FPGA. In a reconfigurable hardware circuit, the process of the processor loading a configuration document and configuring the hardware circuit can be understood as the process of the processor loading instructions to implement the functions of some or all of the above units or modules. Furthermore, it can also be a hardware circuit designed for artificial intelligence, which can be understood as an ASIC, such as a Neural Network Processing Unit (NPU), a Tensor Processing Unit (TPU), or a Deep Learning Processing Unit (DPU).

[0386] Figure 5A is a schematic diagram of the terminal structure proposed in an embodiment of this disclosure. Terminal 5100 is used to execute any of the above methods. In some embodiments, as shown in Figure 5A, terminal 5100 may include at least one of a transceiver module 5101, a processing module 5102, etc. In some embodiments, the processing module 5102 is used to determine a first quantity and / or a second quantity, where the first quantity refers to the number of CPUs occupied when processing the i-th Channel State Information (CSI) using a first processing method, and the second quantity refers to the number of CPUs occupied when processing the i-th CSI using a second processing method. The first processing method refers to processing CSI without using a model, and the second processing method refers to processing CSI using a model, where i is a positive integer. Optionally, the transceiver module is used to execute at least one of the communication steps such as sending and / or receiving performed by terminal 101 in any of the above methods, which will not be elaborated here. Optionally, the processing module is used to execute at least one of the other steps performed by terminal 5100 in any of the above methods, which will not be elaborated here.

[0387] Figure 5B is a schematic diagram of the structure of a network device proposed in an embodiment of this disclosure. The network device 5200 is used to execute any of the above methods. In some embodiments, as shown in Figure 5B, the network device 5200 may include at least one of a transceiver module 5201, a processing module 5202, etc. In some embodiments, the processing module 5202 is used to determine a first quantity and / or a second quantity, where the first quantity refers to the number of CPUs occupied when processing the i-th Channel State Information (CSI) using a first processing method, and the second quantity refers to the number of CPUs occupied when processing the i-th CSI using a second processing method. The first processing method refers to processing CSI without using a model, and the second processing method refers to processing CSI using a model, where i is a positive integer. Optionally, the transceiver module is used to execute at least one of the communication steps (e.g., step S2104, but not limited thereto) performed by the network device 5200 in any of the above methods, which will not be elaborated here. Optionally, the processing module is used to execute at least one of other steps (e.g., step S2105, but not limited thereto) performed by the network device 5200 in any of the above methods, which will not be elaborated here.

[0388] In some embodiments, the transceiver module may include a transmitting module and / or a receiving module, which may be separate or integrated. Optionally, the transceiver module may be interchangeable with a transceiver.

[0389] In some embodiments, the processing module may be a single module or may include multiple sub-modules. Optionally, the multiple sub-modules may each perform all or part of the steps required by the processing module.

[0390] In some embodiments, the processing module can be replaced by the processor, and the transceiver module can be replaced by the transceiver.

[0391] Figure 6A is a schematic diagram of the structure of the communication device 6100 proposed in an embodiment of this disclosure. The communication device 6100 can be a network device (e.g., access network device, core network device, etc.), a terminal (e.g., user equipment, etc.), a chip, chip system, or processor that supports the network device in implementing any of the above methods, or a chip, chip system, or processor that supports the terminal in implementing any of the above methods. The communication device 6100 can be used to implement the methods described in the above method embodiments; for details, please refer to the descriptions in the above method embodiments.

[0392] As shown in Figure 6A, the communication device 6100 is used to execute any of the above methods. In some embodiments, the communication device 6100 includes one or more processors 6101. The processor 6101 may be a general-purpose processor or a special-purpose processor, such as a baseband processor or a central processing unit. The baseband processor may be used to process communication protocols and communication data, and the central processing unit may be used to control communication devices (e.g., base stations, baseband chips, terminal devices, terminal device chips, DUs or CUs, etc.), execute programs, and process program data. Optionally, the communication device 6100 is used to execute any of the above methods. Optionally, one or more processors 6101 are used to invoke instructions to cause the communication device 6100 to execute any of the above methods.

[0393] In some embodiments, the communication device 6100 further includes one or more transceivers 6102. When the communication device 6100 includes one or more transceivers 6102, the transceiver 6102 performs at least one of the communication steps (e.g., steps S2103, S2104, but not limited thereto) in the above method, such as sending and / or receiving, and the processor 6101 performs at least one of other steps (e.g., steps S2101, S2102, S2105, but not limited thereto). In optional embodiments, the transceiver may include a receiver and / or a transmitter, which may be separate or integrated. Optionally, the terms transceiver, transceiver unit, transceiver, transceiver circuit, interface circuit, interface, etc., can be used interchangeably; the terms transmitter, sending unit, transmitter, sending circuit, etc., can be used interchangeably; the terms receiver, receiving unit, receiver, receiving circuit, etc., can be used interchangeably.

[0394] In some embodiments, the communication device 6100 further includes one or more memories 6103 for storing data and / or instructions. Optionally, one or more processors 6101 are used to invoke instructions stored in the memory 6103 to cause the communication device 6100 to perform any of the above methods. Optionally, all or part of the memory 6103 may also be located outside the communication device 6100. In an optional embodiment, the communication device 6100 may include one or more interface circuits 6104. Optionally, the interface circuit 6104 is connected to the memory 6102 and can be used to receive data and / or instructions from the memory 6102 or other devices, and can be used to send data and / or instructions to the memory 6102 or other devices. For example, the interface circuit 6104 can read data and / or instructions stored in the memory 6102 and send the data and / or instructions to the processor 6101.

[0395] The communication device 6100 described in the above embodiments may be a network device or a terminal, but the scope of the communication device 6100 described in this disclosure is not limited thereto, and the structure of the communication device 6100 may not be limited by FIG. 6A. The communication device may be a standalone device or a part of a larger device. For example, the communication device may be: (1) a standalone integrated circuit IC, or chip, or chip system or subsystem; (2) a collection of one or more ICs, optionally, the IC collection may also include storage components for storing data, programs and / or instructions; (3) an ASIC, such as a modem; (4) a module that can be embedded in other devices; (5) a receiver, terminal device, smart terminal device, cellular phone, wireless device, handheld device, mobile unit, vehicle device, network device, cloud device, artificial intelligence device, etc.; (6) others, etc.

[0396] Figure 6B is a schematic diagram of the structure of chip 6200 according to an embodiment of this disclosure. For cases where the communication device 6100 can be a chip or a chip system, please refer to the schematic diagram of chip 6200 shown in Figure 6B, but it is not limited thereto.

[0397] Chip 6200 includes one or more processors 6201. Chip 6200 is used to perform any of the methods described above.

[0398] In some embodiments, chip 6200 further includes one or more interface circuits 6202. Optionally, terms such as interface circuit, interface, and transceiver pin can be used interchangeably. In some embodiments, chip 6200 further includes one or more memories 6203 for storing data and / or instructions. Optionally, all or part of the memories 6203 may be located outside of chip 6200. Optionally, interface circuit 6202 is connected to memory 6203, and interface circuit 6202 can be used to receive data and / or instructions from memory 6203 or other devices, and interface circuit 6202 can be used to send data and / or instructions to memory 6203 or other devices. For example, interface circuit 6202 can read data and / or instructions stored in memory 6203 and send the data and / or instructions to processor 6201.

[0399] In some embodiments, the interface circuit 6202 performs at least one of the communication steps (e.g., steps S2103, S2104, but not limited thereto) in the above-described method, such as sending and / or receiving. For example, the interface circuit 6202 performing the communication steps (e.g., sending and / or receiving) in the above-described method means that the interface circuit 6202 performs data and / or instruction interaction between the processor 6201, the chip 6200, the memory 6203, or the transceiver device. In some embodiments, the processor 6201 performs at least one of other steps (e.g., steps S2101, S2102, but not limited thereto).

[0400] The modules and / or devices described in the various embodiments, such as virtual devices, physical devices, and chips, can be combined or separated arbitrarily as needed. Optionally, some or all steps can also be performed collaboratively by multiple modules and / or devices, which is not limited here.

[0401] This disclosure also proposes a storage medium storing instructions that, when executed on a communication device, cause the communication device to perform any of the above methods. Optionally, the storage medium is an electronic storage medium. Optionally, the storage medium is a computer-readable storage medium, but not limited thereto; it may also be a storage medium readable by other devices. Optionally, the storage medium may be a non-transitory storage medium, but not limited thereto; it may also be a temporary storage medium.

[0402] This disclosure also proposes a program product, including a program and / or instructions, which, when executed by a communication device, cause the communication device to perform any of the above methods. Optionally, the program product is a computer program product. Optionally, the program product is stored on the storage medium.

[0403] This disclosure also proposes a computer program that, when run on a computer, causes the computer to perform any of the above methods.

Claims

1. A method for determining the number of channel state information processing units (CPUs), wherein, The method is executed by a terminal, and the method includes: Determine a first quantity and / or a second quantity, wherein the first quantity refers to the number of CPUs used when processing the i-th Channel State Information (CSI) using the first processing method, and the second quantity refers to the number of CPUs used when processing the i-th CSI using the second processing method, wherein the first processing method refers to processing CSI without using a model, and the second processing method refers to processing CSI using a model, and i is a positive integer.

2. The method according to claim 1, wherein, The method further includes: Send capability indication information to the network device, the capability indication information being used to indicate the terminal's capabilities when processing CSI; Determining the first quantity and / or the second quantity includes: The first quantity and / or the second quantity are determined based on the capability indication information.

3. The method according to claim 1 or 2, wherein, Determine the second quantity, including: Determine a third quantity for each model among multiple models, and determine a second quantity based on the third quantity for each model; or, Determine a fourth quantity corresponding to at least one model, and define the fourth quantity as the second quantity.

4. The method according to claim 3, wherein, Capability indication information is used to indicate the first coefficient corresponding to each model. Determining the third quantity for each of the multiple models includes: The third quantity of a model is determined based on the minimum number of CPUs for one of the multiple models and the first coefficient corresponding to that model.

5. The method according to claim 3, wherein, Capability indicator information is used to indicate the minimum number of CPUs for each model among multiple models; Determining the third quantity for each of the multiple models includes: The third quantity of a model is determined based on the minimum number of CPUs for one of the multiple models and the first coefficient corresponding to that model.

6. The method according to claim 3, wherein, Capability indication information is used to indicate multiple first coefficient groups, one first coefficient group corresponds to one model among multiple models, and the first coefficient group includes at least one first sub-coefficient, different first sub-coefficients correspond to different measurement parameters; the measurement parameters include at least one of the following: number of channel measurement resources, number of antenna ports, system bandwidth, or a fifth quantity, wherein the fifth quantity refers to the number of CSIs at at least one moment obtained based on model inference; Determining the third quantity for each of the multiple models includes: Based on the first coefficient group corresponding to one of the multiple models and the measurement parameters corresponding to the first sub-coefficients included in the first coefficient group, the third quantity of the one model is determined.

7. The method according to claim 3, wherein, The capability indication information is used to indicate a second coefficient group corresponding to the model, the second coefficient including at least one second sub-coefficient, and different second sub-coefficients correspond to different measurement parameters; Determining the fourth quantity corresponding to at least one model includes: The fourth quantity is determined based on the at least one second sub-coefficient and the measurement parameters corresponding to the second sub-coefficient.

8. The method according to claim 3, wherein, Capability indication information is used to indicate multiple third coefficient groups, one third coefficient group corresponds to one of the multiple models, and the third coefficient group includes at least one third sub-coefficient, with different third sub-coefficients corresponding to different channel measurement resource types; Determining the third quantity for each of the multiple models includes: The third quantity for each model is determined based on the third coefficient group corresponding to one of the multiple models and the number of channel measurement resources for different channel measurement resource types.

9. The method according to claim 3, wherein, Capability indication information is used to indicate a fourth coefficient group corresponding to the model, the fourth coefficient group including at least one fourth sub-coefficient, and different fourth sub-coefficients correspond to different channel measurement resource types; Based on determining at least one fourth quantity corresponding to a model, including: The fourth quantity is determined based on the at least one fourth sub-coefficient and the number of channel measurement resources of different channel measurement resource types.

10. The method according to any one of claims 2 to 9, wherein, The capability indication information is used to indicate a first total quantity and / or a second total quantity, wherein the first total quantity refers to the number of CPUs supporting the first processing method, and the second total quantity refers to the number of CPUs supporting the second processing method.

11. The method according to claim 10, wherein, The first quantity is not greater than the first total quantity, and / or the second quantity is not greater than the second total quantity.

12. The method according to claim 1, wherein, When the fifth quantity equals the first quantity, the first quantity is a predefined value; When the fifth quantity is greater than the first value, the first quantity is determined based on the second coefficient and the fifth quantity; The fifth quantity refers to the quantity of at least one moment, where at least one moment refers to the moment when CSI is obtained based on model processing.

13. The method according to any one of claims 1 to 12, wherein, The third total number is greater than the first remaining number and the fourth total number is greater than the second remaining number. NM low-priority CSIs are not updated, where N is the total number of CSIs and M is the smaller of M1 and M2. The third total number refers to the total number of CPUs used to process N CSIs using the first processing method, and the fourth total number refers to the total number of CPUs used to process N CSIs using the second processing method. The first remaining number refers to the difference between the first total number and the number of CPUs already used by the first processing method, and the second remaining number refers to the difference between the second total number and the number of CPUs already used by the second processing method. The number of CPUs used to process M1 high-priority CSIs using the first processing method is no greater than the first remaining number of CPUs, and the number of CPUs used to process M2 high-priority CSIs using the second processing method is no greater than the second remaining number of CPUs.

14. The method according to any one of claims 1 to 12, wherein, The third total number is not greater than the first remaining number and the fourth total number is greater than the second remaining number. The N-M3 lower priority CSIs are not updated, or the N-M3 lower priority CSIs are reverted from the second processing method to the first processing method. The number of CPUs occupied by the second processing method to process the M3 higher priority CSIs is not greater than the second remaining number.

15. The method according to claim 14, wherein, NL low-priority CSIs are not updated. The CPU usage for processing L CSIs using the first processing method is no greater than the first remaining CPU usage. The CPU usage for processing N-M3 CSIs using the second processing method is no greater than the second remaining CPU usage, where L is greater than or equal to M3.

16. The method according to any one of claims 1 to 12, wherein, If the third total number is greater than the first remaining number and the fourth total number is not greater than the second remaining number, the N-M4 lower priority CSIs are not updated, or the N-M4 lower priority CSIs are replaced by the second processing method instead of the first processing method. The number of CPUs occupied by the first processing method to process the M4 higher priority CSIs is not greater than the second remaining number.

17. The method according to claim 16, wherein, NS low-priority CSIs are not updated. The CPU usage for processing M4 CSIs using the first processing method is no greater than the second remaining CPU usage. The CPU usage for processing S CSIs using the second processing method is no greater than the second remaining CPU usage, where S is greater than or equal to M.

18. A method for determining the number of CPUs, wherein, The method is performed by a network device, and the method includes: Determine a first quantity and / or a second quantity, wherein the first quantity refers to the number of CPUs used when processing the i-th Channel State Information (CSI) using the first processing method, and the second quantity refers to the number of CPUs used when processing the i-th CSI using the second processing method, wherein the first processing method refers to processing CSI without using a model, and the second processing method refers to processing CSI using a model, and i is a positive integer.

19. The method according to claim 18, wherein, The method further includes: The terminal receives capability indication information, which indicates the terminal's capability when processing CSI. Determining the first quantity and / or the second quantity includes: The first quantity and / or the second quantity are determined based on the capability indication information.

20. The method according to claim 18 or 19, wherein, Determine the second quantity, including: Determine a third quantity for each model among multiple models, and determine a second quantity based on the third quantity for each model; or, Determine a fourth quantity corresponding to at least one model, and define the fourth quantity as the second quantity.

21. The method according to claim 20, wherein, Capability indication information is used to indicate the first coefficient corresponding to each model. Determining the third quantity for each of the multiple models includes: The third quantity of a model is determined based on the minimum number of CPUs for one of the multiple models and the first coefficient corresponding to that model.

22. The method according to claim 20, wherein, Capability indicator information is used to indicate the minimum number of CPUs for each model among multiple models; Determining the third quantity for each of the multiple models includes: The third quantity of a model is determined based on the minimum number of CPUs for one of the multiple models and the first coefficient corresponding to that model.

23. The method according to claim 20, wherein, Capability indication information is used to indicate multiple first coefficient groups, one first coefficient group corresponds to one model among multiple models, and the first coefficient group includes at least one first sub-coefficient, different first sub-coefficients correspond to different measurement parameters; the measurement parameters include at least one of the following: number of channel measurement resources, number of antenna ports, system bandwidth, or a fifth quantity, wherein the fifth quantity refers to the number of CSIs at at least one moment obtained based on model inference; Determining the third quantity for each of the multiple models includes: Based on the first coefficient group corresponding to one of the multiple models and the measurement parameters corresponding to the first sub-coefficients included in the first coefficient group, the third quantity of the one model is determined.

24. The method of claim 20, wherein, The capability indication information is used to indicate a second coefficient group corresponding to the model, the second coefficient including at least one second sub-coefficient, and different second sub-coefficients correspond to different measurement parameters; Determining the fourth quantity corresponding to at least one model includes: The fourth quantity is determined based on the at least one second sub-coefficient and the measurement parameters corresponding to the second sub-coefficient.

25. The method according to claim 20, wherein, Capability indication information is used to indicate multiple third coefficient groups, one third coefficient group corresponds to one of the multiple models, and the third coefficient group includes at least one third sub-coefficient, with different third sub-coefficients corresponding to different channel measurement resource types; Determining the third quantity for each of the multiple models includes: The third quantity for each model is determined based on the third coefficient group corresponding to one of the multiple models and the number of channel measurement resources for different channel measurement resource types.

26. The method of claim 20, wherein, Capability indication information is used to indicate a fourth coefficient group corresponding to the model, the fourth coefficient group including at least one fourth sub-coefficient, and different fourth sub-coefficients correspond to different channel measurement resource types; Based on determining at least one fourth quantity corresponding to a model, including: The fourth quantity is determined based on the at least one fourth sub-coefficient and the number of channel measurement resources of different channel measurement resource types.

27. The method according to any one of claims 19 to 26, wherein, The capability indication information also includes a first total number and / or a second total number, wherein the first total number refers to the number of CPUs supporting the first processing method, and the second total number refers to the number of CPUs supporting the second processing method.

28. The method according to claim 27, wherein, The first quantity is not greater than the first total quantity, and / or the second quantity is not greater than the second total quantity.

29. The method according to claim 18, wherein, When the fifth quantity equals the first quantity, the first quantity is a predefined value; When the fifth quantity is greater than the first value, the first quantity is determined based on the second coefficient and the fifth quantity; The fifth quantity refers to the quantity of at least one moment, where at least one moment refers to the moment when CSI is obtained based on model processing.

30. The method according to any one of claims 18 to 29, wherein, The third total number is greater than the first remaining number and the fourth total number is greater than the second remaining number. NM low-priority CSIs are not updated, where N is the total number of CSIs and M is the smaller of M1 and M2. The third total number refers to the total number of CPUs used to process N CSIs using the first processing method, and the fourth total number refers to the total number of CPUs used to process N CSIs using the second processing method. The first remaining number refers to the difference between the first total number and the number of CPUs already used by the first processing method, and the second remaining number refers to the difference between the second total number and the number of CPUs already used by the second processing method. The number of CPUs used to process M1 high-priority CSIs using the first processing method is no greater than the first remaining number of CPUs, and the number of CPUs used to process M2 high-priority CSIs using the second processing method is no greater than the second remaining number of CPUs.

31. The method according to any one of claims 18 to 29, wherein, The third total number is not greater than the first remaining number and the fourth total number is greater than the second remaining number. The N-M3 lower priority CSIs are not updated, or the N-M3 lower priority CSIs are reverted from the second processing method to the first processing method. The number of CPUs occupied by the second processing method to process the M3 higher priority CSIs is not greater than the second remaining number.

32. The method according to claim 31, wherein, NL low-priority CSIs are not updated. The CPU usage for processing L CSIs using the first processing method is no greater than the first remaining CPU usage. The CPU usage for processing N-M3 CSIs using the second processing method is no greater than the second remaining CPU usage, where L is greater than or equal to M3.

33. The method according to any one of claims 18 to 29, wherein, If the third total number is greater than the first remaining number and the fourth total number is not greater than the second remaining number, the N-M4 lower priority CSIs are not updated, or the N-M4 lower priority CSIs are replaced by the second processing method instead of the first processing method. The number of CPUs occupied by the first processing method to process the M4 higher priority CSIs is not greater than the second remaining number.

34. The method according to claim 33, wherein, NS low-priority CSIs are not updated. The CPU usage for processing M4 CSIs using the first processing method is no greater than the second remaining CPU usage. The CPU usage for processing S CSIs using the second processing method is no greater than the second remaining CPU usage, where S is greater than or equal to M.

35. A communication device, wherein, The communication device is used to execute the CPU number determination method according to any one of claims 1-17 and 18-34.

36. A method for determining the number of CPUs, used in a communication system, the communication system comprising a terminal and network equipment, wherein, The method includes: The terminal and the network device determine a first quantity and / or a second quantity. The first quantity refers to the number of CPUs occupied when processing the i-th Channel State Information (CSI) using a first processing method. The second quantity refers to the number of CPUs occupied when processing the i-th CSI using a second processing method. The first processing method refers to processing CSI without using a model. The second processing method refers to processing CSI using a model. i is a positive integer.

37. A communication system, wherein, The device includes at least one of a terminal and a network device, wherein the terminal is configured to implement the CPU number determination method according to any one of claims 1-17, and the network device is configured to implement the CPU number determination method according to any one of claims 18-34.

38. A storage medium storing instructions, wherein, When the instruction is executed on the communication device, the communication device performs the CPU number determination method as described in any one of claims 1-34.

39. A program product comprising at least one of a program and instructions, wherein, When at least one of the programs or instructions is executed by the communication device, the method for determining the number of CPUs as described in any one of claims 1-34 is implemented.

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