Method of determining information, method of transmitting information, first device and second device

Description

1 / 100 METHOD OF DETERMINING INFORMATION, METHOD OF TRANSMITTING INFORMATION, FIRST DEVICE AND SECOND DEVICE FIELD OF TECHNIQUE

[001] The modalities of this application relate to the field of communication and, in particular, to a method and apparatus for determining information, a method and apparatus for transmitting information, a device, a means and a program product. BACKGROUND

[002] With the continuous development of artificial intelligence (AI) and machine learning (ML) technologies, the integration of communication technologies with AI / ML technology is becoming one of the trends in future communication. To deal with the complexity and diversity of communication system scenarios, an AI / ML model is introduced into a communication system.

[003] During the use of the AI / ML model, a terminal device and a network device are required to monitor the performance of the AI / ML model. SUMMARY

[004] This application provides a method and apparatus for determining information, a method and apparatus for transmitting information, a device, a means and a program product. The technical solutions include at least the following aspects.

[005] In accordance with one aspect of the modalities of this application, a method for determining information is provided. The method is executed by a first device. Petition 870250086682, dated 09 / 25 / 2025, page 8 / 280 2 / 100 and includes:

[006] determine at least one set of time-domain information associated with a first model;

[007] where the first model is an AI model or an ML model and the time domain information is associated with a model monitoring process of the first model.

[008] In accordance with another aspect of the modalities of this application, a method of information transmission is provided. The method is executed by a second device and includes:

[009] transmit the first information to a first device,

[0010] where the initial information is associated with a model monitoring process of a first model and the first model is an AI model or an ML model.

[0011] In accordance with another aspect of the provisions of this application, an information determination device is provided. The device includes:

[0012] a first determination module, configured to determine at least one group of time-domain information associated with a first model,

[0013] where the first model is an AI model or an ML model and the time domain information is associated with a model monitoring process of the first model.

[0014] In accordance with another aspect of the terms of this application, a device is provided for Petition 870250086682, dated 09 / 25 / 2025, page 9 / 280 3 / 100 information transmission. The device includes:

[0015] a first transmission module, configured to transmit the first information to a first device,

[0016] where the initial information is associated with a model monitoring process of a first model and the first model is an AI model or an ML model.

[0017] In accordance with another aspect of the terms of this application, a first device is provided. The first device includes:

[0018] a processor;

[0019] a transceiver connected to the processor; and

[0020] a memory configured to store an instruction executable by the processor,

[0021] where the processor is configured to load and execute the executable instruction to implement the information determination method according to the previous aspects.

[0022] In accordance with another aspect of the terms of this application, a second device is provided. The second device includes:

[0023] a processor;

[0024] a transceiver connected to the processor; and

[0025] a memory configured to store an instruction executable by the processor,

[0026] where the processor is configured to load and execute the executable instruction to implement the information transmission method in accordance with the previous aspects. Petition 870250086682, dated 09 / 25 / 2025, page 10 / 280 4 / 100

[0027] According to another aspect of the embodiments of this application, a computer-readable storage medium is provided. The computer-readable storage medium stores at least one instruction, at least one program segment, or a set of codes or a set of instructions, and at least one instruction, at least one program segment, or the set of codes or the set of instructions is loaded and executed by a processor to cause a first device to implement the method of determining information according to the preceding aspects, and to cause a second device to implement the method of transmitting information according to the preceding aspects.

[0028] According to another aspect of the embodiments of this application, a computer program product or computer program is provided. The computer program product or computer program includes computer instructions stored on a computer-readable storage medium. A processor reads the computer instructions from the computer-readable storage medium and executes the computer instructions to cause a first device to implement the method of determining information according to the preceding aspects and to cause a second device to implement the method of transmitting information according to the preceding aspects.

[0029] The technical solutions provided under the terms of this application may have the following beneficial effects.

[0030] At least one set of time-domain information associated with the first model is determined, Petition 870250086682, dated 09 / 25 / 2025, page 11 / 280 5 / 100 where the first model is an AI model or an ML model, and the time domain information is associated with the model monitoring process of the first model, so that different time domain information associated with different models can be determined, and model monitoring is performed on different models using different time domain information. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] To describe the technical solutions in embodiments of this application more clearly, the following briefly describes the drawings that accompany the drawings necessary to describe the embodiments of this application. Apparently, the drawings that accompany the following description show only some embodiments of this application, and those skilled in the art can still derive other designs from these accompanying drawings without creative effort.

[0032] Figure 1 is a schematic diagram of a network architecture according to an exemplary embodiment of this application.

[0033] Figure 2 is a schematic diagram of a network system architecture according to an exemplary embodiment of this application.

[0034] Figure 3 is a flowchart of a method for determining information according to an exemplary embodiment of this request.

[0035] Figure 4 is a flowchart of a method for determining information according to an exemplary embodiment of this request.

[0036] Figure 5 is a schematic diagram of a resource configuration scheme according to a modality. Petition 870250086682, dated 09 / 25 / 2025, page 12 / 280 6 / 100 copy of this order.

[0037] Figure 6 is a schematic diagram of a resource configuration scheme according to an exemplary embodiment of this application.

[0038] Figure 7 is a schematic diagram of a resource configuration scheme according to an exemplary embodiment of this application.

[0039] Figure 8 is a schematic diagram of a resource configuration scheme according to an exemplary embodiment of this application.

[0040] Figure 9 is a flowchart of a method for determining information according to an exemplary embodiment of this request.

[0041] Figure 10 is a flowchart of a method for determining information according to an exemplary embodiment of this request.

[0042] Figure 11 is a flowchart of a method for determining information according to an exemplary embodiment of this request.

[0043] Figure 12 is a flowchart of a method for determining information according to an exemplary embodiment of this request.

[0044] Figure 13 is a flowchart of a method for determining information according to an exemplary embodiment of this request.

[0045] Figure 14 is a flowchart of a method for transmitting information according to an exemplary embodiment of this request.

[0046] Figure 15 is a flowchart of a method for transmitting information according to a modality. Petition 870250086682, dated 09 / 25 / 2025, page 13 / 280 7 / 100 copy of this order.

[0047] Figure 16 is a flowchart of a method for transmitting information according to an example of how this request is carried out.

[0048] Figure 17 is a flowchart of a method for transmitting information according to an exemplary embodiment of this request.

[0049] Figure 18 is a flowchart of a method for transmitting information according to an exemplary embodiment of this request.

[0050] Figure 19 is a block diagram of an information-determining apparatus according to an exemplary embodiment of this application.

[0051] Figure 20 is a block diagram of an information transmission device according to an exemplary embodiment of this request.

[0052] Figure 21 is a schematic structural diagram of a first device or a second device according to an exemplary embodiment of this application. DESCRIPTION OF MODALITIES

[0053] To make the objectives, technical solutions and advantages of this application clearer, the following describes in detail the implementations of this application with reference to the accompanying drawings.

[0054] The example embodiments are described in detail in this document, and examples of the example embodiments are shown in the accompanying drawings. When the following description refers to the drawings accompanying this document, unless otherwise specified, the same numbers in different accompanying drawings represent an element. Petition 870250086682, dated 09 / 25 / 2025, p. 14 / 280 8 / 100 equal or similar. The implementations described in the following example embodiments do not represent all implementations consistent with this application. Rather, they are merely examples of devices and methods described in detail in the appended claims and which are consistent with some aspects of this application.

[0055] The terms used in this application are intended only to describe specific modalities, but are not intended to limit this application. The singular forms of a / an, said and the / the used in this application and the accompanying claims are also intended to include plural forms, unless the context clearly indicates otherwise. It should also be understood that the term and / or, as used in this document, refers to and includes any or all possible combinations of one or more associated listed items.

[0056] It should be noted that the user information (including, without limitation, user equipment information, user personal information and the like) and data (including, without limitation, data used for analysis, stored data, displayed data and the like) involved in this request are all information and data that have been authorized by a user or fully authorized by all related parties. The collection, use and processing of related data must comply with the relevant laws, regulations and standards of the relevant countries and regions.

[0057] It should be understood that, although terms such as first and second may be used in this application to describe various types of information, this information is not limited to these terms. These terms are used only for Petition 870250086682, dated 09 / 25 / 2025, page 15 / 280 9 / 100 distinguish information of the same type from one another. For example, without departing from the scope of this request, a first parameter may also be referred to as a second parameter, and similarly, a second parameter may also be referred to as a first parameter. Depending on the context, the term "if," as used in this document, may be interpreted as "in the event that," "when," or "in response to the determination that."

[0058] Figure 1 is a schematic diagram of a network architecture 100 according to an exemplary embodiment of this application. The network architecture 100 includes a terminal device 10, an access network device 20, and a main network device 30.

[0059] Terminal device 10 may refer to user equipment (User Equipment, UE), an access terminal, a subscriber unit, a subscriber station, a mobile station, a mobile console, a remote station, a remote terminal, a mobile device, a wireless communication device, a user agent, or a user appliance. Optionally, terminal device 10 may be a mobile phone, a cordless phone, a session initiation protocol phone (Session Initiation Protocol). Session, SIP), a wireless local loop station (Wireless Local Loop, WLL), a personal digital assistant (PDA), a portable device with wireless communication function, a computing device or any other processing device connected to a wireless modem, a vehicle-mounted device, a wearable device, a terminal device in a 5th generation system (5GS), or a terminal device in a Petition 870250086682, dated 09 / 25 / 2025, page 16 / 280 A 10 / 100 public terrestrial mobile network developed in the future (Public Terrestrial Mobile Network, PLMN) or similar, not limited to the embodiments of this application. For ease of description, the devices mentioned above are collectively referred to as a terminal device. Generally, there is a plurality of terminal devices 10. One or more terminal devices 10 may be distributed within each cell managed by the access network device 20.

[0060] Access network device 20 is a device deployed in an access network and configured to provide terminal device 10 with a wireless communication function. Access network device 20 may include various forms of macro base stations, micro base stations, relay nodes, access points, and the like. In systems using different radio access technologies, a device with the function of an access network device may have a different name, for example, referred to as a next-generation B node (gNodeB, gNB) in a 5th generation New Radio system (5G NR). As communication technologies evolve, the name access network device may change. For ease of description, in the embodiments of this application, the aforementioned devices that provide terminal device 10 with a wireless communication function are collectively referred to as access network devices.Optionally, a communication relationship can be established between terminal device 10 and main network device 30 via access network device 20. For example, in a long-term evolution system (Long-Term Evolution, LTE), the access network device 20 could be one or more evolved base stations in a network. Petition 870250086682, dated 09 / 25 / 2025, page 17 / 280 11 / 100 evolved universal terrestrial radio access (Evolved Universal Terrestrial Radio Access Network, EUTRAN) or EUTRAN. In the 5G NR system, the access network device 20 may be one or more gNBs in a radio access network (Radio Access Network, RAN) or RAN. In the embodiments of this application, unless otherwise specified, a network device refers to the access network device 20, such as a base station.

[0061] The core network device 30 is a device deployed in a core network. The main functions of the core network device 30 include providing user connectivity, managing users and rolling services. The core network device also serves as a carrier network to provide an interface to external networks. For example, in the 5G NR system, a core network device includes network elements such as an access and mobility management function network element (Access and Mobility Management Function, AMF), a user plane function network element (User Plane Function, UPF) and a session management function network element (Session Management Function, SMF).

[0062] In some embodiments, the access network device 20 and the main network device 30 communicate with each other using an air interface technology, such as an NG interface in the 5G NR system. The access network device 20 and the terminal device 10 communicate with each other using an air interface technology, such as a Uu interface.

[0063] Figure 2 is a schematic diagram of a 200 network system architecture according to an exemplary embodiment of this application. The system architecture of Petition 870250086682, dated 09 / 25 / 2025, page 18 / 280 The 12 / 100 network 200 includes one terminal device 10, one access network device 20, and one main network device 30.

[0064] The main network device 30 includes at least one of the following: a location management function (Location Management Function, LMF), a network slice selection function (Network Slice Selection Function, NSSF), an authentication server function (Authentication Server Function, AUSF), a unified data management function (Unified Data Management Function, UDM), an AMF, an SMF, a policy control function (Policy Control Function, PCF), a UPF, a detection function (Detection Function, SF), or a network data analysis function (Network Data Analysis Function, NWDAF).

[0065] The UE implements an access stratum connection, exchanges access stratum messages, and performs wireless data transmission with an access network (Access Network, AN) using a Uu interface, and the UE implements a non-access stratum connection (Non-Access Stratum, NAS) and exchanges NAS messages with an AMF using an N1 interface. The AMF is a mobility management function on a core network, and the SMF is a session management function on the core network. In addition to performing mobility management on the UE, the AMF is also responsible for forwarding a message related to session management between the UE and the SMF. PCF is a policy management function on the core network and is responsible for formulating policies related to mobility management, session management, billing, and similar UE functions. PCF performs data transmission with an external application function (Application Function, AF) using an N5 interface. UPF is a function Petition 870250086682, dated 09 / 25 / 2025, page 19 / 280 13 / 100 of the user plane on the main network and performs data transmission with an external data network (Data Network, DN) using an N6 interface and performs data transmission with the AN using an N3 interface.

[0066] In the embodiments of this application, the term 5G NR system may also be referred to as a 5G system or an NR system, and those skilled in the art may understand its meaning. The technical solutions described in the embodiments of this application may be applicable to an LTE system, a 5G NR system, a subsequent evolved system of the 5G NR system, or other communication systems, such as a narrowband Internet of Things (NB-IoT) system, which is not limited in the embodiments of this application.

[0067] The first device or the second device involved in the embodiments of this application includes at least one of the following scenarios:

[0068] Scenario 1: the first device is a terminal device and the second device is a network device;

[0069] Scenario 2: the first device is a network device and the second device is a terminal device;

[0070] Scenario 3: both the first device and the second device are terminal devices; or

[0071] Scenario 4: both the first device and the second device are network devices.

[0072] The network device is an access network device, or a core network device, or a model lifecycle management device. Petition 870250086682, dated 09 / 25 / 2025, page 20 / 280 14 / 100 IA / ML, or an Operations Management and Maintenance (OMM) device.

[0073] The access network device includes at least one of the following:

[0074] a gNB, a centralized unit (Centralized Unit,), a distributed unit (Distributed Unit, DU), a centralized unit control plane (Centralized Unit Control Plane,-CP) or a centralized unit user plane (Centralized Unit User Plane,-UP).

[0075] The primary network device includes at least one of the following: [007 6] an LMF network element, an NSSF network element, an AMF network element, an AUSF network element, a UPF network element, an SMF network element, a PCF network element, a UDM network element, an SF network element or an NWDAF network element.

[0077] With the continuous development of AI / ML technology, the integration of communication technologies with AI / ML technology is becoming one of the trends in future communication. To handle the complexity and diversity of communication system scenarios, an AI / ML model is introduced into a communication system. During the use of the AI / ML model, a terminal device is required to monitor the AI / ML model. When the terminal device monitors the AI / ML model, the network device is also required to perform a corresponding operation. For example, in monitoring processes of some AI / ML models, the network device is required to transmit a reference signal associated with monitoring the model in Petition 870250086682, dated 09 / 25 / 2025, page 21 / 280 15 / 100 a corresponding monitoring time window. If the terminal device and the network device fail to maintain a consistent understanding of the model monitoring order, the reference signal associated with model monitoring may not be transmitted within an actual monitoring time window or may be transmitted outside of a monitoring time window corresponding to the AI / ML model, resulting in failure to monitor the corresponding AI / ML model. For another example, to prevent interfering AI / ML models from operating simultaneously during monitoring, the terminal device and the network device also need to maintain a consistent understanding of the monitoring order of the AI / ML models, so as to know when to accurately suspend the operation of some AI / ML models that affect the monitoring processes of other AI / ML models.Otherwise, AI / ML models that interfere with each other may operate simultaneously during monitoring, concluding that the monitoring results of the AI / ML model may not reflect a real-world situation.

[0078] To avoid the previous situation where the results of AI / ML model performance monitoring are affected, it is necessary to consider how to enable the endpoint device and the network device to maintain a consistent understanding of the model monitoring order in a model monitoring scenario involving a plurality of models, in order to obtain a true and effective model performance monitoring result.

[0079] It should be noted that, in the modalities of this application, the meanings of monitoring, model monitoring, model performance monitoring and monitoring Petition 870250086682, dated 09 / 25 / 2025, page 22 / 280 16 / 100 performance figures may be equivalent, and these terms can be used interchangeably. For ease of description, the term model monitoring is used throughout the following description.

[0080] Figure 3 is a flowchart of a method for determining information according to an exemplary embodiment of this application. The method is executed by a first device and the method includes step 310 below.

[0081] In step 310, at least one group of time-domain / frequency-domain information associated with a first model is determined.

[0082] The first model is an AI model or an ML model, and at least one piece of time-domain or frequency-domain information is associated with a monitoring process of the first model.

[0083] In some embodiments, one or more models to be monitored operate on the first device; the first model includes all, some, or one of the one or more models to be monitored. Optionally, each model to be monitored is an AI / ML model related to mobile communications, such as a Channel State Information Compression (Channel State Information, CSI) feedback model, a beam prediction model, a positioning model, or a mobility control model.

[0084] In some embodiments, time-domain information is time-domain information used to monitor the first model of at least one group of first features; and frequency-domain information is frequency-domain information used to monitor the first model of at least one group of first features. Petition 870250086682, dated 09 / 25 / 2025, page 23 / 280 17 / 100 resources. In some modalities, each first resource includes a time-domain resource segment and / or a frequency-domain resource segment. At least one of the time-domain or frequency-domain information from at least one group of first resources includes all or part of a monitoring resource (for a specific definition, reference is made to the description of the first resources), and the monitoring resource is either a periodic monitoring resource or an aperiodic monitoring resource.

[0085] In some embodiments, the first device determines the time domain information of at least one group of first features associated with the first model. The first features are associated with a monitoring process of the first model. In some embodiments, the first feature is a time-frequency feature or an air interface feature used to monitor the first model. Alternatively, the first feature is a time-frequency feature or an air interface feature used to monitor the performance of the first model.

[0086] In some embodiments, in a case where at least one time-domain information group associated with the first model is a plurality of time-domain information groups, the plurality of time-domain information groups satisfies at least one of the following conditions:

[0087] at least two time-domain information groups in a plurality of time-domain information groups associated with the same model do not Petition 870250086682, dated 09 / 25 / 2025, page 24 / 280 18 / 100 overlap or partially overlap in time domain; or

[0088] at least two groups of time domain information in different time domain information associated with different models do not overlap or partially overlap in time domain.

[0089] In some embodiments, the first device determines at least one group of frequency domain information associated with the first model, and the frequency domain information associated with different first models may be entirely the same; or may be entirely different; or may be partially the same and partially different. This is not limited to embodiments of this application. In some embodiments, the first device determines the frequency domain information of at least one first feature associated with the first model.

[0090] In some modes, time-domain information includes at least one of the following:

[0091] information about the starting location in the time domain;

[0092] time domain end location information; or

[0093] time domain length information.

[0094] In conclusion, according to the method provided in this embodiment, at least one group of time-domain information associated with the first model is determined, where the first model is an AI model or an ML model, and the time-domain information is associated with the model monitoring process of the first model, of Petition 870250086682, dated 09 / 25 / 2025, page 25 / 280 19 / 100 so that different time-domain information associated with different models can be determined, and model monitoring is performed on different models using different time-domain information.

[0095] Figure 4 is a flowchart of a method for determining information according to an exemplary embodiment of this application. The method is executed by a first device and the method includes step 410 below.

[0096] In step 410, time domain information is determined for at least one group of first features associated with a first model.

[0097] The first resources are associated with a first model monitoring process. In some embodiments, the first resource is a time-frequency resource or an air interface resource used to monitor the first model. Alternatively, the first resource is a time-frequency resource or an air interface resource used to monitor the performance of the first model.

[0098] In some embodiments, time-domain information is time-domain information used to monitor the first model of at least one first feature; and frequency-domain information is frequency-domain information used to monitor the first model of at least one first feature. In some embodiments, each first feature includes a time-domain feature segment and / or a frequency-domain feature segment. At least one of the time-domain information or frequency-domain information of at least one group of first features includes all or part Petition 870250086682, dated 09 / 25 / 2025, page 26 / 280 20 / 100 of a monitoring resource (for a specific definition, reference is made to the description of the initial information), and the monitoring resource is either a periodic monitoring resource or an aperiodic monitoring resource.

[0099] In some modalities, the time domain information of the first resources is represented by absolute time, for example, coordinated universal time (Coordinated Universal Time, UTC).

[00100] For example, a start location in the time domain of the first features is 00:00:00 on March 29, 2023, and an end location in the time domain of the first features is 00:00:10 on March 29, 2023.

[00101] In some modalities, the time domain information of the first resources is represented by a time domain unit.

[00102] The time domain unit includes at least one hyperframe number, one system frame number, one subframe group number, one subframe number, one slot group number, one slot number, one symbol group number, or one symbol number. A hyperframe number indicates to which round of features a system frame (system frame number, SFN) belongs. For example, a round of system frame features includes 1024 system frames, and the hyperframe number indicates to which round of 1024 system frame features a current system frame belongs. SFN A belongs. The subframes included in 1024 system frames or in a system frame can be classified into a plurality of groups, and a number for each group of subframes is called the subframe group number. The slots included in a system frame, or in a first semi Petition 870250086682, dated 09 / 25 / 2025, page 27 / 280 21 / 100 frames of a system frame, or in a second half-frame of a system frame, or in a subframe of a system frame, may be classified into a plurality of groups, and a number from each group of bands is referred to as a slot group number. The symbols included in a system frame, or in a first half-frame of a system frame, or in a second half-frame of a system frame, or in a subframe in a system frame or in a slot, may be classified into a plurality of groups, and a number from each group of symbols is referred to as a symbol group number. In this order, the meanings of a system frame and a radio frame are not distinguished.

[00103] For example, a starting location of the first-feature time domain is a 1oslot in a 1oradio frame and a final location of the first-feature time domain is a 3oem in a 1oradio frame.

[00104] In some embodiments, the process of determining, by the first device, the time domain information of at least one group of first features associated with the first model includes at least one of the following solutions:

[00105] Solution 1: The first device determines, based on the first information, the time domain information of at least one group of first features associated with the first model;

[00106] · Solution 2: The first device determines, based on the numbering information associated with the first model, the time-domain information of at least one group of first features associated with the first model; or Petition 870250086682, dated 09 / 25 / 2025, pages 28 / 280 22 / 100

[00107] Solution 3: The first device determines, based on the first information and the numbering information associated with the first model, the time domain information of at least one group of first features associated with the first model.

[00108] The initial information is associated with the model monitoring process of the first model, or the initial information can be used in the model monitoring process of the first model.

[00109] In some embodiments, the first model includes all or some or one of the models to be monitored, the first information includes monitoring resource configuration information, and the first information includes at least one of the following:

[00110] Information 1: a time domain starting point for a monitoring resource,

[00111] wherein the monitoring resource is a resource used to monitor the performance of an AI / ML model, for example, a time-frequency resource or an air interface resource; and the monitoring resource may be classified into an aperiodic monitoring resource and a periodic monitoring resource according to a resource occurrence type;

[00112] Information 2: a final time domain location of a monitoring resource;

[00113] Information 3: a first displacement of time;

[00114] Information 4: total number of monitoring time windows included in an aperiodic monitoring feature; Petition 870250086682, dated 09 / 25 / 2025, page 29 / 280 23 / 100

[00115] Information 5: window length corresponding to a single monitoring time window;

[00116] Information 6: an interval between adjacent monitoring time windows;

[00117] Information 7: a resource repetition period corresponding to a periodic monitoring resource;

[00118] Information 8: a second time shift;

[00119] Information 9: a total number of monitoring time windows included in a single feature replay period within a periodic monitoring feature; or

[00120] Information 10: total number of resource repetition periods corresponding to the periodic monitoring resource.

[00121] The first time offset is a time offset between a starting location in the time domain of the aperiodic monitoring resource and a starting location in the time domain of a corresponding monitoring time window for the aperiodic monitoring resource; the second time offset is a time offset between a starting location in the time domain of a monitoring time window in any resource repetition period within the periodic monitoring resource and a starting location in the time domain of a more recent single resource repetition period within the periodic monitoring resource; and the time domain resources corresponding to the time domain information of at least one group of first resources are included in Petition 870250086682, dated 09 / 25 / 2025, page 30 / 280 24 / 100 monitoring feature or are part of the monitoring feature.

[00122] The first device acquires the first information by means of at least one dedicated signaling procedure, a pre-configuration procedure, a preset procedure, a broadcast (system) message procedure, or a multicast message procedure. For example, the first device receives the first information transmitted by a second device. Certainly, it should also be noted that if the first information includes a plurality of sub-information (i.e., includes at least two pieces of information in information 1 to information 10 mentioned above), it is permitted that a portion of the sub-information included in the first information is obtained in one of the previous ways, while another portion of the sub-information included in the first information is obtained in another of the previous ways.For example, information 1 is acquired through the dedicated signaling procedure, information 3 is acquired in a predefined way, and information 5 is acquired through the system's broadcast message procedure. Certainly, there are many more combinations of methods for acquiring sub-information, which are not listed one by one in this document.

[00123] In some embodiments, the first device transmits the first information to the second device. For example, a network device transmits the first information to a terminal device. In some embodiments, the first device receives the first information transmitted by the second device. For example, a terminal device receives the first Petition 870250086682, dated 09 / 25 / 2025, page 31 / 280 25 / 100 pieces of information transmitted by a network device.

[00124] In some modalities, at least two initial models are associated with the same set of initial information.

[00125] In one example, there is a first model A and a first model B, and both the first model A and the first model B are associated with the first information A. In other words, the second device configures the first information A for the first device, and the first information A includes at least one group of first features associated with the first model A and at least one group of first features associated with the first model B. The first model A and the first model B share the same set of monitoring feature configuration information.

[00126] In some modalities, each of the first models is associated with the respective first information.

[00127] For example, there is a first model A and a first model B, the first model A is associated with the first information A and the first model B is associated with the first information B. In other words, the second device configures the first information A and the first information B for the first device, the first information A is used to configure at least one group of first resources associated with the first model A, the first information B is used to configure at least one group of first resources associated with the first model B, and the first model A and the first model B use different configuration information for monitoring resources. Petition 870250086682, dated 09 / 25 / 2025, page 32 / 280 26 / 100

[00128] The initial information includes at least one of the following four monitoring resource configuration schemes:

[00129] Monitoring Resource Configuration Scheme 1: The first information is used to configure a periodic monitoring resource, and any resource repetition period within the periodic monitoring resource includes a plurality of monitoring time windows. Figure 5 is a schematic diagram of a resource configuration scheme according to an exemplary embodiment of this application.

[00130] In resource configuration scheme 1, the initial information includes at least one of the following:

[00131] Information 1: a time domain starting point for a monitoring resource,

[00132] Information 2: a final time domain location of a monitoring resource;

[00133] Information 5: Window length of a single monitoring time window;

[00134] Information 6: an interval between adjacent monitoring time windows;

[00135] Information 7: a resource repetition period corresponding to a periodic monitoring resource;

[00136] Information 8: a second time shift;

[00137] Information 9: a total number of monitoring time windows included in a single resource replay period within a monitoring resource. Petition 870250086682, dated 09 / 25 / 2025, page 33 / 280 27 / 100 periodic; or

[00138] Information 10: total number of resource repetition periods corresponding to the periodic monitoring resource.

[00139] The second time offset is a time offset between a starting location in the time domain of a 1st monitoring time window in any feature replay period within the periodic monitoring feature and a starting location in the time domain of a last single feature replay period within the periodic monitoring feature; and the time domain features corresponding to the time domain information of at least one group of first features are included in or are part of the monitoring feature.

[00140] The preceding information is described with reference to Figure 5.

[00141] Information 1 corresponds to an instant a, an instant (a+T) or similar, in which a value of a is greater than or equal to 0.

[00142] Information 2 is used to restrict the final time domain location of the periodic monitoring resource.

[00143] Information 5 corresponds to a parameter f, where a value of f is greater than 0.

[00144] Information 6 corresponds to a parameter g, where a value of g is greater than or equal to 0.

[00145] Optionally, if information 6 is defined in a protocol, but a configuration corresponding to information 6 is not provided in a procedure of Petition 870250086682, dated 09 / 25 / 2025, p. 34 / 280 28 / 100 configuration, the first device (a configuration receiver) uses stored information 6 configured in a previous configuration procedure or sets a value of information 6 to 0 by default. If information 6 is not defined in a protocol, it is assumed by default in the protocol that an interval between any two adjacent monitoring time windows in a periodic monitoring resource period is 0, i.e., the adjacent monitoring time windows are contiguously distributed in the time domain.

[00146] Information 7 corresponds to a parameter T, indicating that the same monitoring resource is repeated once in an interval of T.

[00147] Information 8 corresponds to a parameter b, where a value of b is greater than or equal to 0.

[00148] Information 9 indicates information about the total number of monitoring time windows included in a single resource replay period. Figure 5 is used as an example. Each resource replay period includes three monitoring time windows: a monitoring time window 1, a monitoring time window 2, and a monitoring time window 3.

[00149] A function of information 10 is similar to that of information 2, and both information 10 and information 2 can restrict the final location of the time domain of the monitoring resource. Information 10 indirectly indicates the final location of the time domain of the monitoring resource by restricting a number of periods of periodic monitoring resources.

[00150] Resource configuration scheme Petition 870250086682, dated 09 / 25 / 2025, page 35 / 280 29 / 100 Monitoring 2: The initial information is used to configure a periodic monitoring resource, and any resource repetition period within the periodic monitoring resource includes a monitoring time window. Figure 6 is a schematic diagram of a monitoring resource configuration scheme according to an exemplary embodiment of this application.

[00151] In the monitoring resource configuration scheme 2, the initial information includes at least one of the following:

[00152] Information 1: a time domain starting point for a monitoring resource,

[00153] Information 2: a final time domain location of a monitoring resource;

[00154] Information 5: Window length of a single monitoring time window;

[00155] Information 7: a resource repetition period corresponding to a periodic monitoring resource;

[00156] Information 8: a second time shift;

[00157] Information 10: total number of resource repetition periods corresponding to the periodic monitoring resource.

[00158] The second time offset is a time offset between a starting location in the time domain of a 1st monitoring time window in any feature repetition period within the periodic monitoring feature and a starting location in the time domain of a last single feature repetition period within Petition 870250086682, dated 09 / 25 / 2025, page 36 / 280 30 / 100 of the periodic monitoring resource; and the time domain resources corresponding to the time domain information of at least one group of first resources are included in or are part of the monitoring resource.

[00159] The preceding information is described with reference to Figure 6.

[00160] Information 1 corresponds to an instant a, an instant (a+T) or similar, in which a value of a is greater than or equal to 0.

[00161] Information 2 is used to restrict the final time domain location of the periodic monitoring resource.

[00162] Information 5 corresponds to a parameter f, where a value of f is greater than 0.

[00163] Information 7 corresponds to a parameter T, indicating that the same monitoring resource is repeated once in an interval of T.

[00164] Information 8 corresponds to a parameter b, where a value of b is greater than or equal to 0.

[00165] A function of information 10 is similar to that of information 2, and both information 10 and information 2 can restrict the final location of the time domain of the monitoring resource. Information 10 indirectly indicates the final location of the time domain of the monitoring resource by restricting a number of periods of periodic monitoring resources.

[00166] Monitoring Resource Configuration Scheme 3: The initial information is used to configure an aperiodic monitoring resource and any Petition 870250086682, dated 09 / 25 / 2025, page 37 / 280 31 / 100 aperiodic monitoring feature includes a plurality of monitoring time windows. Figure 7 is a schematic diagram of a monitoring feature configuration scheme according to an exemplary embodiment of this application.

[00167] In the monitoring resource configuration scheme 3, the initial information includes at least one of the following:

[00168] Information 1: a time domain starting point for a monitoring resource,

[00169] Information 2: a final time domain location of a monitoring resource;

[00170] Information 3: a first displacement of time;

[00171] Information 4: total number of monitoring time windows included in an aperiodic monitoring feature;

[00172] Information 5: window length of a single monitoring time window; or

[00173] Information 6: an interval between adjacent monitoring time windows.

[00174] The first time offset is a time offset between a starting location in the time domain of the aperiodic monitoring feature and a starting location in the time domain of a monitoring time window corresponding to the aperiodic monitoring feature; and the time domain features corresponding to the time domain information of at least one group of first features are included in or are part of the monitoring feature. Petition 870250086682, dated 09 / 25 / 2025, page 38 / 280 32 / 100

[00175] The preceding information is described with reference to Figure 7.

[00176] Information 1 corresponds to a moment a, in which a value is greater than or equal to 0.

[00177] Information 2 is used to restrict the final time domain location of the monitoring resource.

[00178] Information 3 corresponds to a value of a parameter b, where a value of b is greater than or equal to 0.

[00179] Optionally, if information 3 is defined in a protocol, but a configuration corresponding to information 3 is not provided in a configuration procedure, the first device (a configuration receiver) uses stored information 3 configured in a previous configuration procedure or sets a value of information 3 to 0 by default. If information 3 is not defined in a protocol, it is assumed by default in the protocol that a time offset between a start location in the time domain of the aperiodic monitoring resource and a start location in the time domain of a monitoring time window corresponding to the aperiodic monitoring resource is 0, that is, both time domain start locations correspond to the same time domain location.

[00180] Information 4 corresponds to a total number of monitoring time windows. For example, if there is a monitoring time window 1 for a monitoring time window 5 in Figure 7, a value of information 4 is 5.

[00181] Information 5 corresponds to a parameter f, where a value of f is greater than 0.

[00182] Information 6 corresponds to a parameter Petition 870250086682, dated 09 / 25 / 2025, p. 39 / 280 33 / 100 g, where a value of g is greater than or equal to 0.

[00183] Optionally, if information 6 is defined in a protocol, but a configuration corresponding to information 6 is not provided in a configuration procedure, the first device (a configuration receiver) uses stored information 6 configured in a previous configuration procedure or sets a value of information 6 to 0 by default. If information 6 is not defined in a protocol, it is assumed by default in the protocol that an interval between any two adjacent monitoring time windows is 0, i.e., the adjacent monitoring time windows are contiguously distributed in the time domain.

[00184] Monitoring Resource Configuration Scheme 4: The first information is used to configure an aperiodic monitoring resource, and any aperiodic monitoring resource includes a monitoring time window. Figure 8 is a schematic diagram of a monitoring resource configuration scheme according to an exemplary embodiment of this application.

[00185] In the monitoring resource configuration scheme 4, the initial information includes at least one of the following:

[00186] Information 1: a time domain starting point for a monitoring resource,

[00187] Information 2: a final time domain location of a monitoring resource;

[00188] Information 3: a first time shift; or

[00189] Information 5: window length of a Petition 870250086682, dated 09 / 25 / 2025, page 40 / 280 34 / 100 single monitoring time window.

[00190] The first time offset is a time offset between a starting location in the time domain of the aperiodic monitoring feature and a starting location in the time domain of a monitoring time window corresponding to the aperiodic monitoring feature; and the time domain features corresponding to the time domain information of at least one group of first features are included in or are part of the monitoring feature.

[00191] The preceding information is described with reference to Figure 8.

[00192] Information 1 corresponds to a moment a, in which a value is greater than or equal to 0.

[00193] Information 2 is used to restrict the final time domain location of the monitoring resource.

[00194] Information 3 corresponds to a value of a parameter b, where a value of b is greater than or equal to 0.

[00195] Optionally, if information 3 is defined in a protocol, but a configuration corresponding to information 3 is not provided in a configuration procedure, the first device (a configuration receiver) uses stored information 3 configured in a previous configuration procedure or sets a value for information 3 to 0 by default. If information 3 is not defined in a protocol, it is assumed by default in the protocol that there is a time offset between a start location in the time domain of the aperiodic monitoring resource and a start location in the time domain of a monitoring time window corresponding to the monitoring resource. Petition 870250086682, dated 09 / 25 / 2025, page 41 / 280 35 / 100 aperiodic is 0, meaning that both starting points of the time domain correspond to the same time domain location.

[00196] Information 5 corresponds to a parameter f, where a value of f is greater than 0.

[00197] At least one of the time domain start location information or the time domain end location information of at least one group of first features associated with the first model is determined based on the four previous monitoring feature configuration schemes and the numbering information associated with the first model, which includes at least one of the following four cases.

[00198] Case 1: At least one of the time domain start location information or the time domain end location information of at least one group of first features associated with the first model is determined based on the first information (corresponding to the monitoring feature configuration scheme 1) and the numbering information associated with the first model.

[00199] In some embodiments, the first model is a plurality of models, the first model includes a target model, and the target model is one of the plurality of first models.

[00200] In some embodiments, the sequence number information for at least one monitoring time window associated with the target model is determined based on the numbering information associated with the target model.

[00201] Optionally, the number information associated with the target model is logical numbering information that uniquely identifies the target model of a Petition 870250086682, dated 09 / 25 / 2025, page 42 / 280 36 / 100 plurality of models. For example, the plurality of models is three models and the logical numbering information is 0, 1, and 2.

[00202] Optionally, the monitoring time window sequence number information can be considered as numbering information obtained by sequentially numbering a plurality of monitoring time windows belonging to the same monitoring resource. For example, if a periodic monitoring resource resource period includes nine monitoring time windows, the sequence number information will be 0, 1, 2, 3, 4, 5, 6, 7, and 8.

[00203] In some embodiments, the sequence number information for at least one monitoring time window associated with the target model is determined based on a fifth remainder and the numbering information associated with the target model.

[00204] The fifth remainder is a value obtained by performing a modulo operation on a total number of first models and a sequence number associated with any monitoring time window in at least one monitoring time window, and the fifth remainder is the same as the numbering information associated with the target model.

[00205] The numbering information associated with the target model is associated with one or more monitoring time windows included in the periodic monitoring feature, and an association relationship is determined according to the following formula: c = d mod n

[00206] Where, c denotes the information of Petition 870250086682, dated 09 / 25 / 2025, p. 43 / 280 37 / 100 numbering associated with the target model, d denotes a sequence number associated with any monitoring time window included in the monitoring resource, n denotes a total number of models or a total number of models involved in the allocation of monitoring resources, and mod denotes a module operator.

[00207] For example, there are three initial models (i.e., n = 3), and the model identifier values ​​are sequentially '10', '15', and '20'. A feature repetition period of the periodic monitoring feature includes nine monitoring time windows, with sequence numbers being sequentially 0, 1, 2, 3, 4, 5, 6, 7, and 8. Furthermore, based on any of the methods for acquiring the numbering information associated with the first model presented below, the numbering information associated with the first three models is sequentially determined as 0, 1, and 2, i.e., the values ​​of c are sequentially 0, 1, and 2.

[00208] According to the formula above, the sequence numbers (i.e., d values) associated with the monitoring time windows associated with the first model corresponding to model identifier '10' are 0, 3, and 6; the sequence numbers associated with the monitoring time windows associated with the first model corresponding to model identifier '15' are 1, 4, and 7; and the sequence numbers associated with the monitoring time windows associated with the first model corresponding to model identifier '20' are 2, 5, and 8. The above method is used in each feature repetition period of the periodic monitoring feature to determine the sequence number information. Petition 870250086682, dated 09 / 25 / 2025, page 44 / 280 38 / 100 of at least one monitoring time window associated with the target model.

[00209] (1) Absolute time, such as UTC, is used to represent the time domain start location information and / or the time domain end location information of at least one group of first features associated with the first model.

[00210] The first model includes a target model, and the time domain information of at least one group of first features associated with the target model is determined based on at least one of the following pieces of information:

[00211] a first sum, where the first sum is a sum of the time domain start location (represented by a parameter a) of the monitoring feature and a second time offset (represented by a parameter b);

[00212] a second sum, where the second sum is the sum of the window length (represented by a parameter f) a single monitoring time window and an interval (represented by a parameter g) between adjacent monitoring time windows;

[00213] a first difference, wherein the first difference is a difference between a sequence number corresponding to an nth group of the first features associated with the target model and a first value;

[00214] a second difference, wherein the second difference is a difference between a sequence number corresponding to a qth feature repetition period within the periodic monitoring feature and the first value;

[00215] a first product, in which the first Petition 870250086682, dated 09 / 25 / 2025, page 45 / 280 39 / 100 product is a product of the first difference, the second sum, and a total quantity of first models;

[00216] A second product, wherein the second product is a product of the numbering information associated with the target model and the second sum;

[00217] A third product, wherein the third product is a product of the second difference and a repetition period of the feature corresponding to the periodic monitoring feature; or

[00218] a third sum, wherein the third sum is the sum of the first sum, the first product, the second product, and the third product.

[00219] The second time offset is a time offset between a starting location in the time domain of a 1st monitoring time window in any feature repetition period within the periodic monitoring feature and a starting location in the time domain of a last single feature repetition period within the periodic monitoring feature, where eeq are positive integers. The description is provided using an example where the first value is 1.

[00220] A t1 time domain starting point of at least one group of first features associated with the target model includes the third sum and can be expressed by the following formula: t1 = (a+b) + (e-1) xn χ (f+g) + c χ (f+g) + (q-1)xT

[00221] A final t2 time domain location of at least one group of first features associated with the target model includes a sum of the third sum and the window length of a single monitoring time window and may be Petition 870250086682, dated 09 / 25 / 2025, p. 46 / 280 40 / 100 expressed by the following formula: t2 = (a+b) + (e-1) χ n χ (f+g) + c χ (f+g) + f + (q-1)xT

[00222] Where a denotes the starting point of the time domain of the monitoring resource; b denotes the second time offset; e denotes a sequence number of a monitoring time window (i.e., a group sequence number of the first resources) associated with the same target model in chronological order, for example, if the sequence numbers of the monitoring time windows associated with the target model are sequentially 2, 5, and 8, then the values ​​of e will be sequentially 1, 2, and 3; n denotes the total number of models or a total number of models involved in monitoring resource allocation; f denotes the window length of a single monitoring time window; g denotes the interval between adjacent monitoring time windows; c denotes the numbering information associated with the target model; q denotes a sequence number corresponding to the qth resource repetition period;and T denotes the repetition period of the feature corresponding to the periodic monitoring feature.

[00223] Each fixed value of c corresponds to a target model, for example, a value of 0 for c corresponds to model A. For each fixed value of q (the values ​​of q are sequentially 1, 2, 3, ..., to indicate the resource allocation of the monitoring time windows included in the qth resource repetition period), depending on the variation in the values ​​of e (the values ​​of e are sequentially 1, 2, 3, ...), a time domain start location of each group of first resources (in the case of the monitoring resource configuration scheme 1, each group of first resources). Petition 870250086682, dated 09 / 25 / 2025, page 47 / 280 41 / 100 corresponds to a monitoring time window) associated with model A within the qth feature repetition period and / or a final time domain location of each group of first features associated with model A within the qth feature repetition period can be obtained sequentially.

[00224] The time domain locations corresponding to t1 and t2 must not exceed the restrictions relating to the final location of the time domain monitoring resource (corresponding to information 2) and / or the total number of repetition periods of the resource corresponding to the periodic monitoring resource (corresponding to information 10).

[00225] For example, in Figure 5, a = 0, b = 0, n = 3, f = 2, g = 1, and T = 10.

[00226] A value of 0 for c corresponds to a model A, a first group of first features associated with model A corresponds to a monitoring time window 1, and t1 and t2 of the first group of first features associated with model A are, respectively, the following: t1 = 0 + 0 + (1-1) x 3 x (2+1) + 0 x (2+1) + (1-1) x 10 = 0 and t2 = 0 + 0 + (1-1) x 3 x (2+1) + 0 x (2+1) + 2 + (1-1) x 10 = 2.

[00227] A value of c 1 corresponds to a model B, a first group of first features associated with model B corresponds to a monitoring time window 2, and t1 and t2 of the first group of first features associated with model B are, respectively, the following: t1 = 0 + 0 + (1-1) x 3 x (2+1) + 1 x (2+1) + (1-1) x 10 = 3 and t2 = 0 + 0 + (1-1) x 3 x (2+1) + 1 x (2+1) + 2 + (1-1) x 10 = 5.

[00228] A value of 2 for c corresponds to a C model, Petition 870250086682, dated 09 / 25 / 2025, p. 48 / 280 42 / 100 a first group of first features associated with model C corresponds to a monitoring time window 3 and t1 and t2 of the first group of first features associated with model C are respectively the following: t1 = 0 + 0 + (1-1) χ 3 χ (2+1) + 2 χ (2+1) + (1-1) χ 10 = 6 and t2 = 0 + 0 + (1-1) χ 3 χ (2+1) + 2 χ (2+1) + 2 + (1-1) χ 10 = 8.

[00229] (2) A time-domain unit, such as a system frame number or a numerical slot value, is used to represent the time-domain start location information and / or the time-domain end location information of at least one group of first features associated with the first model.

[00230] The first model includes a target model, and the time domain starting point of at least one group of first features associated with the target model is determined based on at least one of the following pieces of information:

[00231] a second sum, where the second sum is the sum of the window length (represented by a parameter f) a single monitoring time window and an interval (represented by a parameter g) between adjacent monitoring time windows;

[00232] a second product, wherein the second product is a product of numbering information (represented by a parameter c) associated with the target model and the second sum, and the second product is designated by z, wherein z is greater than or equal to 0;

[00233] a fourth sum, wherein the fourth sum is the sum of the second product and a value of the first slot number, and the value of the first slot number is denoted as k, where k is a positive integer; Petition 870250086682, dated 09 / 25 / 2025, page 49 / 280 43 / 100

[00234] a second numerical slot value (represented by a parameter h), wherein the second numerical slot value is a value obtained by performing a modulo operation on the fourth sum and a total quantity (represented by a parameter M, wherein there is certainly a correspondence between a value of M and a subcarrier spacing parameter) of slots included in each radio frame;

[00235] A first quotient, wherein the first quotient is a quotient obtained by dividing the second product by a total number of slots included in each radio frame;

[00236] a first integer value, where the first integer value is a floor operation value of the first quotient;

[00237] a third difference, wherein the third difference is a difference between a first radio frame number and a first parameter (represented by a parameter p), and the first radio frame number is denoted as SFN; or

[00238] a first remainder, where the first remainder is a value obtained by performing a modulo operation on the third difference and an occurrence period (represented by a parameter T1) of the first features associated with the target model.

[00239] The first slot number value represents a numerical value of a slot in a radio frame corresponding to a time domain start location of a monitoring time window in any feature repetition period within the monitoring feature. Petition 870250086682, dated 09 / 25 / 2025, page 50 / 280 44 / 100 periodic or aperiodic monitoring resource; the first radio frame number represents a radio frame number to which a time domain start location of at least one group of first features associated with the target model belongs; and the first parameter represents a numeric value of a radio frame to which a time domain start location of a 1st monitoring time window belongs in any feature repetition period within the periodic monitoring resource or the aperiodic monitoring resource, or represents a value obtained by performing a modulo operation on a numeric value of a radio frame to which a time domain start location of a 1st monitoring time window in any feature repetition period within the periodic monitoring resource belongs and a feature repetition period corresponding to the periodic monitoring resource.

[00240] Value of the second slot number h = (z+k) mod M.

[00241] The first SFN radio frame number is calculated according to the following formula: (SFN-p) mod T1 = FLOOR(z / M), or (SFN-p+w) mod T1 = FLOOR(z / M)

[00242] T1 denotes the occurrence period of the first features associated with the target model; the values ​​of the occurrence periods of the first features associated with different models may be identical or different; M indicates the total number of slots included in each radio frame; mod denotes a modulo operation function; FLOOR denotes a floor operation function; a value of k is equal to a slot number in a radio frame corresponding to a location of Petition 870250086682, dated 09 / 25 / 2025, page 51 / 280 45 / 100 time domain at an instant (a + b) in Figure 5; and a value of p is equal to a numerical value of a radio frame to which the time domain location at instant (a + b) in the Figure belongs, or a value of p is equal to a value obtained by performing a mod T operation on a number of a radio frame to which the time domain location at instant (a + b) in Figure 5 belongs, where w is a constant greater than or equal to 0, for example, w = 1024.

[00243] In one implementation, the values ​​of aeb are 0. In this case, the parameter k = 0 and the parameter p = 0.

[00244] The values ​​of he SFN must not exceed the constraints at the final location of the time-domain monitoring resource (corresponding to information 2) and / or the total number of resource repetition periods corresponding to the periodic monitoring resource (corresponding to information 10).

[00245] The time domain start location of at least one group of first features associated with the target model includes time domain locations indicated by the first radio frame number and the second slot numeric value.

[00246] The first model includes a target model, and the final time domain location of at least one group of first features associated with the target model is determined based on at least one of the following pieces of information:

[00247] a second sum, where the second sum is the sum of the window length (represented by a parameter f) a single monitoring time window and an interval (represented by a parameter g) between adjacent monitoring time windows; Petition 870250086682, dated 09 / 25 / 2025, page 52 / 280 46 / 100

[00248] a second product, wherein the second product is a product of the numbering information (represented by a parameter c) associated with the target model and the second sum;

[00249] a fifth sum, wherein the fifth sum is the sum of the second product and the length of the window of a single monitoring time window, and the fifth sum is denoted as z, wherein z is greater than or equal to 0;

[00250] a sixth sum, wherein the sixth sum is the sum of the fifth sum and the value of the first slot number, and the value of the first slot number is denoted as k, where k is a positive integer;

[00251] a third numeric slot value (represented by a parameter h), wherein the third numeric slot value is a value obtained by performing a modulo operation on the sixth sum and a total quantity (represented by a parameter M) of slots included in each radio frame;

[00252] a second quotient, wherein the second quotient is a quotient obtained by dividing the fifth sum by the total number of bands included in each radio frame;

[00253] a second integer value, where the second integer value is a floor operation value of the second quotient;

[00254] a fourth difference, wherein the fourth difference is a difference between a second radio frame number and a first parameter (represented by a parameter p), and the second radio frame number is represented by SFN; or

[00255] a second remainder, where the second remainder is Petition 870250086682, dated 09 / 25 / 2025, page 53 / 280 47 / 100 is a value obtained by performing a modulo operation on the fourth difference and a period of occurrence (represented by a parameter T1) of the first features associated with the target model.

[00256] The first slot number value represents a numerical value of a slot in a radio frame corresponding to a time domain start location of a 1. Monitoring time window in any feature repetition period within the periodic monitoring feature or the aperiodic monitoring feature; the second radio frame number represents a radio frame number to which a time domain start location of at least one group of first features associated with the target model belongs;and the first parameter represents a numeric value of a radio frame to which a time domain start location of a 1st monitoring time window belongs in any feature repetition period within the periodic monitoring feature or the aperiodic monitoring feature, or represents a value obtained by performing a modulo operation on a numeric value of a radio frame to which a time domain start location of a 1st monitoring time window belongs in any feature repetition period within the periodic monitoring feature and a feature repetition period corresponding to the periodic monitoring feature.

[00257] Third numerical value of slot h = (z+k) mod M.

[00258] The second SFN radio frame number is calculated according to the following formula: (SFN-p) mod T1 = FLOOR(z / M), or Petition 870250086682, dated 09 / 25 / 2025, page 54 / 280 48 / 100 (SFN-p+w) mod T1 = FLOOR(z / M)

[00259] T1 denotes the occurrence period of the first features associated with the target model; the values ​​of the occurrence periods of the first features associated with different models may be identical or different; M indicates the total number of slots included in each radio frame; mod denotes a modulo operation function; FLOOR denotes a floor operation function; a value of k is equal to a slot number in a radio frame corresponding to a time domain location at instant (a + b) in Figure 5; and a value of p is equal to a numerical value of a radio frame to which the time domain location at instant (a + b) in Figure 5 belongs, or a value of p is equal to a value obtained by performing a mod T operation on a radio frame number to which the time domain location at instant (a + b) in Figure 5 belongs, where w is a constant greater than or equal to 0, for example, w = 1024.

[00260] In one implementation, the values ​​of aeb are 0. In this case, the parameter k = 0 and the parameter p = 0.

[00261] The values ​​of he SFN must not exceed the constraints at the final location of the time-domain monitoring resource (corresponding to information 2) and / or the total number of resource repetition periods corresponding to the periodic monitoring resource (corresponding to information 10).

[00262] A final time-domain location of at least one group of first features associated with the target model includes time-domain locations indicated by the second radio frame number and the third slot numeric value.

[00263] Optionally, T1 denotes a difference of Petition 870250086682, dated 09 / 25 / 2025, page 55 / 280 49 / 100 time between two adjacent resources (or monitoring time windows) associated with a target model, and T1 is configured at a granularity of a model identifier, or a group of model identifiers, or a device.

[00264] The parameter T1 is determined in at least one of the following ways:

[00265] • a pre-definition procedure;

[00266] • a pre-configuration procedure;

[00267] • a dedicated unicast signaling procedure;

[00268] • a multicast signaling procedure; or

[00269] • a broadcast signaling procedure (including the form of system broadcast messages).

[00270] Optionally, the parameter n is determined in at least one of the following ways:

[00271] • a pre-configuration procedure;

[00272] • a dedicated unicast signaling procedure;

[00273] • a multicast signaling procedure; or

[00274] • a broadcast signaling procedure (including the form of system broadcast messages).

[00275] Case 2: At least one of the Time domain start location information or time domain end location information for at least one group of first features associated with the first model is determined based on the first information (corresponding to the monitoring feature configuration scheme 2) and the numbering information associated with Petition 870250086682, dated 09 / 25 / 2025, page 56 / 280 50 / 100 first model.

[00276] The first model includes at least two first models and the at least two first models include a target model.

[00277] (1) Absolute time, such as UTC, is used to represent the time domain start location information and / or the time domain end location information of at least one group of first features associated with the first model.

[00278] The first model includes a target model, and the time domain information of at least one group of first features associated with the target model is determined based on at least one of the following pieces of information:

[00279] a first sum, where the first sum is a sum of the time domain start location (represented by a parameter a) of the monitoring feature and a second time offset (represented by a parameter b);

[00280] a first difference, wherein the first difference is a difference between a sequence number corresponding to an nth group of the first features associated with the target model and a first value;

[00281] a second difference, wherein the second difference is a difference between a sequence number corresponding to a qth feature repetition period within the periodic monitoring feature and the first value;

[00282] Seventh sum, where the seventh sum is the sum of the durations, respectively, for performing a single monitoring operation in the first models, and is expressed y?!r ί in Petition 870250086682, dated 09 / 25 / 2025, page 57 / 280 51 / 100

[00283] a fourth product, wherein the fourth product is a product of the first difference and the seventh sum;

[00284] an eighth sum, wherein the eighth sum is the sum of the durations, respectively, for performing a single monitoring operation in the first models, from an Io (a resource allocation order of each first model is determined based on the numbering information associated with the first model) first model for the model Σσ r jí=0;

[00285] A third product, wherein the third product is a product of the second difference and a repetition period of the feature (represented by a parameter T) corresponding to the periodic monitoring feature; or

[00286] a ninth sum, wherein the ninth sum is a sum of the first sum, the fourth product, the eighth sum, and the third product.

[00287] The second time offset is a time offset between a starting location in the time domain of a monitoring time window in any feature repetition period within the periodic monitoring feature and a starting location in the time domain of a last single feature repetition period within the periodic monitoring feature, where eeq are positive integers. The description is provided using an example where the first value is 1.

[00288] A tl time domain starting point of at least one group of first features associated with the target model includes the ninth sum and can be expressed by the following formula: tl = (a+b) + (e-1) χ ^í=i^ + + (q-1) χ T Petition 870250086682, dated 09 / 25 / 2025, page 58 / 280 52 / 100

[00289] A final time domain location t2 of at least one group of first features associated with the target model includes a sum of the ninth sum and duration to perform a single monitoring operation on the target model and can be expressed by the following formula: t2 = (a+b) + (e-1) χ + + L(c+i) + (q-1) x T

[00290] Where a denotes the starting point of the time domain of the monitoring resource; b denotes the second time offset; e denotes a group sequence number of the first resources associated with the same target model in chronological order, where the values ​​of e are sequentially 1, 2, and 3; n denotes the total number of models or a total number of models participating in resource allocation monitoring; c denotes the numbering information associated with the target model; Li denotes information about the duration of the execution of a single monitoring operation on a model with the value of c equal to (i-1) (a value of i is 1, 2, ..., n); L(C+i) denotes information about the duration of a single monitoring operation on the target model (for example, the numerical values ​​respectively associated with models A, B, and C are sequentially 0, 1, and 2, and the durations, respectively, to execute a single monitoring operation on the models are sequentially 5 ms, 10 ms, and 15 ms, then Li = 5, L2 = 10, and L3 = 15, with Lo defined as 0); and T denotes the repetition period of the feature corresponding to the periodic monitoring feature.

[00291] Each fixed value of c corresponds to a target model, for example, a value of 0 of c corresponds to model A. For each fixed value of q (the values ​​of q are Petition 870250086682, dated 09 / 25 / 2025, p. 59 / 280 53 / 100 sequentially 1, 2, 3, ..., to indicate the allocation of monitoring resources included in the qth resource repetition period), depending on the variation in the values ​​of e (the values ​​of e are sequentially 1, 2, 3, ...), a time domain start location of each group of first resources associated with model A within the qth resource repetition period and / or a time domain end location of each group of first resources associated with model A within the qth resource repetition period can be obtained sequentially.

[00292] The time domain locations corresponding to t1 and t2 must not exceed the restrictions relating to the final location of the time domain monitoring resource (corresponding to information 2) and / or the total number of repetition periods of the resource corresponding to the periodic monitoring resource (corresponding to information 10).

[00293] For example, in Figure 6, a = 0, b = 0, n = 3, a value of 0 for c corresponds to the target model, T = 20, L1 = 5, L2 = 3, L3 = 2, L0 = 0 and the time domain start locations t1 and t2 of the first group of first features associated with the target model are, respectively, the following: t1 = 0 + 0 + (1-1) x (5+3+2) + Lq + (1-1) x 20 = 0 and t2 = 0 + 0 + (1-1) x (5+3+2) + Lq + L1 + (1-1) x 20 = 5.

[00294] (2) A time-domain unit, such as a system frame number or a numerical slot value, is used to represent the time-domain start location information and / or the time-domain end location information of at least one group of first features associated with the first model. Petition 870250086682, dated 09 / 25 / 2025, p. 60 / 280 54 / 100

[00295] The first model includes a target model, the time-domain information of at least one group of first features associated with the target model is represented by a time-domain unit, and the time-domain information of at least one group of first features associated with the target model is determined based on at least one of the following pieces of information:

[00296] an eighth sum, wherein the eighth sum is the sum of the durations, respectively, for carrying out a single monitoring operation on the first models, from a first model to the target model, and the eighth sum is Σσ rj θ indicated as z, where ze greater than or equal to 0 ;

[00297] a tenth sum, wherein the tenth sum is the sum of the eighth sum and the value of the first slot number, and the value of the first slot number is denoted as k, wherein k is a positive integer;

[00298] a value of the fourth slot number (represented by a parameter h), wherein the value of the fourth slot number is a value obtained by performing a modulo operation on the tenth sum and a total number of slots included in each radio frame;

[00299] a third quotient, wherein the third quotient is a quotient obtained by dividing the eighth sum by a total quantity (represented by a parameter M) of slots included in each radio frame;

[00300] a third integer value, where the third integer value is a floor operation value of the third quotient;

[00301] a fifth difference, where the fifth Petition 870250086682, dated 09 / 25 / 2025, page 61 / 280 The 55 / 100 difference is the difference between a third radio frame number and a first parameter (represented by a parameter p), and the third radio frame number is represented by SFN; or

[00302] a third remainder, wherein the third remainder is a value obtained by performing a modulo operation on the fifth difference and an occurrence period (represented by a parameter T1) of the first features associated with the target model.

[00303] The first slot number value represents a numerical value of a slot in a radio frame corresponding to a time domain start location of a monitoring time window in any feature repetition period within the periodic monitoring feature or the aperiodic monitoring feature; the third radio frame number represents a radio frame number to which a time domain start location of at least one group of first features associated with the target model belongs;and the first parameter represents a numeric value of a radio frame to which a time domain start location of a 1st monitoring time window belongs in any feature repetition period within the periodic monitoring feature or the aperiodic monitoring feature, or represents a value obtained by performing a modulo operation on a numeric value of a radio frame to which a time domain start location of a 1st monitoring time window belongs in any feature repetition period within the periodic monitoring feature and a feature repetition period corresponding to the periodic monitoring feature. Petition 870250086682, dated 09 / 25 / 2025, page 62 / 280 56 / 100

[00304] Value of the fourth slot number h = (z + k) mod M.

[00305] The third radio frame number (SFN) is calculated according to the following formula: (SFN-p) mod T1 = FLOOR(z / M), or (SFN-p+w) mod T1 = FLOOR(z / M)

[00306] T1 denotes the occurrence period of the first features associated with the target model; the values ​​of the occurrence periods of the first features associated with different models may be identical or different; M indicates the total number of slots included in each radio frame; mod denotes a modulo operation function; FLOOR denotes a floor operation function; a value of k is equal to a slot number in a radio frame corresponding to a time domain location at an instant (a + b) in Figure 6; and a value of p is equal to a numerical value of a radio frame to which the time domain location at instant (a + b) in the Figure belongs, or a value of p is equal to a value obtained by performing a mod T operation on a radio frame number to which the time domain location at instant (a + b) in Figure 6 belongs, where w is a constant greater than or equal to 0, for example, w = 1024.

[00307] In one implementation, the values ​​of aeb are 0. In this case, the parameter k = 0 and the parameter p = 0.

[00308] The values ​​of he SFN must not exceed the constraints at the final location of the time-domain monitoring resource (corresponding to information 2) and / or the total number of resource repetition periods corresponding to the periodic monitoring resource (corresponding to information 10). Petition 870250086682, dated 09 / 25 / 2025, page 63 / 280 57 / 100

[00309] The time domain start location of at least one group of first features associated with the target model includes time domain locations indicated by the third radio frame number and the value of the fourth slot number.

[00310] The first model includes a target model, the time-domain information of at least one group of first features associated with the target model is represented by a time-domain unit, and the time-domain information of at least one group of first features associated with the target model is determined based on at least one of the following pieces of information:

[00311] an eighth sum, wherein the eighth sum is the sum of the durations, respectively, for carrying out a single monitoring operation on the first models, from the first model to the target model, and the eighth sum is expressed by

[00312] an eleventh sum, wherein the eleventh sum is the sum of the eighth sum and the duration (represented by a parameter L(C+i)) for performing a single monitoring operation on the target model, and the eleventh sum is indicated as z, wherein z is greater than or equal to 0;

[00313] a twelfth sum, wherein the twelfth sum is the sum of the eleventh sum and the value of the first slot number, and the value of the first slot number is denoted as k, wherein k is a positive integer;

[00314] a fifth numeric slot value (represented by a parameter h), where the fifth numeric slot value is a value obtained by executing a Petition 870250086682, dated 09 / 25 / 2025, page 64 / 280 58 / 100 modulo operation in the twelfth sum and a total quantity (represented by a parameter M) of slots included in each radio frame;

[00315] a fourth quotient, wherein the fourth quotient is a quotient obtained by dividing the eleventh sum by a total number of bands included in each radio frame;

[00316] a fourth integer value, where the fourth integer value is a floor operation value of the fourth quotient;

[00317] a sixth difference, wherein the sixth difference is a difference between a fourth radio frame number and a first parameter (represented by a parameter p), and the fourth radio frame number is represented by SFN; or

[00318] a fourth remainder, where the fourth remainder is a value obtained by performing a modulo operation on the sixth difference and an occurrence period (represented by a parameter T1) of the first features associated with the target model.

[00319] The first slot number value represents a numerical value of a slot in a radio frame corresponding to a time domain start location of a monitoring time window in any feature repetition period within the periodic monitoring feature or the aperiodic monitoring feature; the fourth radio frame number represents a radio frame number to which a time domain start location of at least one group of first features associated with the target model belongs; and the first parameter represents a value Petition 870250086682, dated 09 / 25 / 2025, page 65 / 280 59 / 100 numeric value of a radio frame to which a time domain start location of a 1st monitoring time window belongs in any feature repetition period within the periodic monitoring feature or the aperiodic monitoring feature, or represents a value obtained by performing a modulo operation on a numeric value of a radio frame to which a time domain start location of a 1st monitoring time window belongs in any feature repetition period within the periodic monitoring feature and a feature repetition period corresponding to the periodic monitoring feature.

[00320] Value of the fifth slot number h = (z+k) mod M.

[00321] The fourth radio frame number (SFN) is calculated according to the following formula: (SFN-p) mod T1 = FLOOR(z / M), or (SFN-p+w) mod T1 = FLOOR(z / M)

[00322] T1 denotes the occurrence period of the first features associated with the target model; the values ​​of the occurrence periods of the first features associated with different models may be identical or different; M indicates the total number of slots included in each radio frame; mod denotes a modulo operation function; FLOOR denotes a floor operation function; a value of k is equal to a slot number in a radio frame corresponding to a time domain location at instant (a + b) in Figure 6; and a value of p is equal to a numerical value of a radio frame to which the time domain location at instant (a + b) in the Figure belongs, or a value of p is equal to a value obtained by performing a mod T operation on a number of a radio frame. Petition 870250086682, dated 09 / 25 / 2025, page 66 / 280 60 / 100 radio to which the time domain location at instant (a + b) in Figure 6 belongs, L(c+1) denotes information about the duration of the execution of a single monitoring operation on the target model, where w is a constant greater than or equal to 0, for example, w = 1024.

[00323] In one implementation, the values ​​of aeb are 0. In this case, the parameter k = 0 and the parameter p = 0.

[00324] The values ​​of he SFN must not exceed the constraints at the final location of the time-domain monitoring resource (corresponding to information 2) and / or the total number of resource repetition periods corresponding to the periodic monitoring resource (corresponding to information 10).

[00325] Optionally, T1 denotes a time difference between two adjacent first features associated with a target model, and T1 is configured at a granularity of a model identifier, or a group of model identifiers, or a device.

[00326] The parameter T1 is determined in at least one of the following ways:

[00327] - a pre-definition procedure;

[00328] - a pre-configuration procedure;

[00329] - a dedicated signaling procedure unicast;

[00330] - a multicast signaling procedure; or

[00331] - a broadcast signaling procedure (including the form of system broadcast messages).

[00332] Optionally, the parameter n is determined in at least one of the following ways: Petition 870250086682, dated 09 / 25 / 2025, page 67 / 280 61 / 100

[00333] - a pre-configuration procedure;

[00334] - a dedicated unicast signaling procedure;

[00335] - a multicast signaling procedure; or

[00336] - a broadcast signaling procedure. (including the form of system broadcast messages).

[00337] Optionally, a value of the Li or L(c+1) parameter is set at a granularity of a model identifier, or a group of model identifiers, or a device, and the value of Li or L(c+1) is determined in at least one of the following ways:

[00338] - a pre-definition procedure;

[00339] - a pre-configuration procedure;

[00340] - a dedicated unicast signaling procedure;

[00341] - a multicast signaling procedure; or

[00342] - a broadcast signaling procedure (including the form of system broadcast messages).

[00343] For example, the first device learns, through a signaling procedure, by monitoring the resource duration to perform a single monitoring operation on each model. The description is provided using three models as an example. The durations of the monitoring resources, respectively, to perform a single monitoring operation on the models are sequentially L1, L2, and L3.

[00344] The first device learns, through a signaling procedure, ratio information Petition 870250086682, dated 09 / 25 / 2025, page 68 / 280 62 / 100 time of a monitoring resource that each model expects to occupy. The description is provided using three models as an example. The time ratio information of the monitoring resources that the three models respectively expect to occupy are sequentially 25%, 50%, and 25%, so Li = 0.25 x total duration of a single monitoring operation, L2 = 0.5 x total duration of a single monitoring operation, L3 = 0.25 x total duration of a single monitoring operation.

[00345] Case 3: At least one of the time domain start location information or the time domain end location information of at least one group of first features associated with the first model is determined based on the first information (corresponding to the monitoring feature configuration scheme 3) and the numbering information associated with the first model.

[00346] Optionally, the first model includes a target model and the sequence number information for at least one monitoring time window associated with the target model is determined based on the numbering information associated with the target model.

[00347] The numbering information associated with the target model is associated with one or more monitoring time windows included in the aperiodic monitoring feature, and an association relationship is determined according to the following formula: c = d mod n

[00348] Where, c denotes the numbering information associated with the target model, d denotes a sequence number associated with any monitoring time window. Petition 870250086682, dated 09 / 25 / 2025, p. 69 / 280 63 / 100 included in the monitoring resource, n denotes a total number of models or a total number of models involved in the allocation of monitoring resources, and mod denotes a module operator.

[00349] For a specific method of calculating the value of d, reference is made to the description of the corresponding section in Case 1. The details are not described again in this document.

[00350] (1) Absolute time, such as UTC, is used to represent the time domain start location information and / or the time domain end location information of at least one group of first features associated with the first model.

[00351] The first model includes a target model, and the time domain information of at least one group of first features associated with the target model is determined based on at least one of the following pieces of information:

[00352] a first sum, wherein the first sum is a sum of the time domain start location (represented by a parameter a) of the monitoring feature and a second time offset (represented by a parameter b);

[00353] a second sum, where the second sum is the sum of the window length (represented by a parameter f) a single monitoring time window and an interval (represented by a parameter g) between adjacent monitoring time windows;

[00354] a first difference, wherein the first difference is a difference between a sequence number corresponding to an nth group of the first features associated with the target model and a first value; Petition 870250086682, dated 09 / 25 / 2025, pp. 70 / 280 64 / 100

[00355] a second difference, wherein the second difference is a difference between a sequence number corresponding to a qth feature repetition period within the periodic monitoring feature and the first value;

[00356] a first product, wherein the first product is a product of the first difference, the second sum and a total quantity of first models;

[00357] A second product, wherein the second product is a product of the numbering information associated with the target model and the second sum; or

[00358] a thirteenth sum ((a+b) + (e-1) xnx (f+g) + cx (f+g)), where the thirteenth sum is the sum of the first sum, the first product and the second product.

[00359] The second time offset is a time offset between a time domain start location of the aperiodic monitoring feature and a time domain start location of a 1a monitoring time window corresponding to the aperiodic monitoring feature, where eeq are positive integers. The description is provided using an example where the first value is 1.

[00360] A t1 time domain starting location of at least one group of first features associated with the target model includes the thirteenth sum and can be expressed by the following formula: t1 = (a+b) + (e-1) xnx (f+g) + cx (f+g)

[00361] A final t2 time domain location of at least one group of first features associated with the target model includes a sum of the thirteenth sum and the length Petition 870250086682, dated 09 / 25 / 2025, page 71 / 280 65 / 100 of the window of a single monitoring time window and can be expressed by the following formula: t2 = (a+b) + (e-1) χ n χ (f+g) + cχ(f+g) + f

[00362] Where a denotes the starting point of the time domain of the monitoring resource; b denotes the second time offset; e denotes a sequence number of a monitoring time window (i.e., a group sequence number of the first resources) associated with the same target model in chronological order, for example, if the sequence numbers of the monitoring time windows associated with the target model are sequentially 2, 5, and 8, then the values ​​of e will be sequentially 1, 2, and 3; n denotes the total number of models or a total number of models participating in resource allocation monitoring; f denotes the window length of a single monitoring time window; g denotes the interval between adjacent monitoring time windows; ec denotes the numbering information associated with the target model.

[00363] Each fixed value of c corresponds to a target model, for example, a value of 0 of c corresponds to a model A and, depending on the variation in the values ​​of e (the values ​​of e are sequentially 1, 2, 3, ...), a time domain start location of each group of first features (each monitoring time window) associated with model A and / or a time domain end location of each group of first features (each monitoring time window) associated with model A can be obtained sequentially.

[00364] The time domain locations corresponding to t1 and t2 must not exceed a constraint on the final time domain location of the monitoring resource. Petition 870250086682, dated 09 / 25 / 2025, page 72 / 280 66 / 100 (corresponding to information 2).

[00365] For example, in Figure 7, a = 0, b = 0, n = 3, f = 2 and g = 1. A value of 0 for c corresponds to a model A, a first group of first features associated with model A corresponds to a monitoring time window 1, and t1 and t2 of the first group of first features associated with model A are respectively as follows: t1 = 0 + 0 + (1-1) χ 3 χ (2 + 1) + 0 χ (2 + 1) = 0 and t2 = 0 + 0 + (1-1) χ 3 χ (2 + 1) + 0 χ (2 + 1) + 2 = 2.

[00366] A value 1 of c corresponds to a model B, a first group of first features associated with model B corresponds to a monitoring time window 2, and t1 and t2 of the first group of first features associated with model B are respectively the following: t1 = 0 + 0 + (1-1) χ 3 χ (2+1) + 1 χ (2+1) = 3 and t2 = 0 + 0 + (1-1) χ3 χ (2+1) + χ (2+1) + 2 = 5.

[00367] A value 2 of c corresponds to a model C, a first group of first features associated with model C corresponds to a monitoring time window 3, and t1 and t2 of the first group of first features associated with model C are respectively as follows: t1 = 0 + 0 + (1-1) χ 3 χ (2 + 1) + 2 χ (2 + 1) = 6 and t2 = 0 + 0 + (1-1) χ 3 χ (2 + 1) + 2 χ (2+1) + 2 = 8.

[00368] (2) A time-domain unit, such as a system frame number or a numerical slot value, is used to represent the time-domain start location information and / or the time-domain end location information of at least one group of first features associated with the first model.

[00369] Reference is made to the description in Case 1: Petition 870250086682, dated 09 / 25 / 2025, page 73 / 280 67 / 100 A time-domain unit, such as a system frame number or a numerical slot value, is used to represent the time-domain start location information and / or the time-domain end location information of at least one group of first features associated with the first model. The details are not described again in this document.

[00370] Optionally, T1 denotes a time difference between two adjacent first features (or monitoring time windows) associated with a target model, and T1 is configured at a granularity of a model identifier, or a group of model identifiers, or a device.

[00371] The parameter T1 is determined in at least one of the following ways:

[00372] a pre-definition procedure;

[00373] a pre-configuration procedure;

[00374] a dedicated unicast signaling procedure;

[00375] a multicast signaling procedure; or

[00376] a broadcast signaling procedure (including the form of system broadcast messages).

[00377] Optionally, the parameter n is determined in at least one of the following ways:

[00378] a pre-configuration procedure;

[00379] a dedicated unicast signaling procedure;

[00380] a multicast signaling procedure; or

[00381] a broadcast signaling procedure. (including the form of system broadcast messages). Petition 870250086682, dated 09 / 25 / 2025, page 74 / 280 68 / 100

[00382] Case 4: At least one of the time domain start location information or the time domain end location information of at least one group of first features associated with the first model is determined based on the first information (corresponding to the monitoring feature configuration scheme 4) and the numbering information associated with the first model.

[00383] The first model includes a target model.

[00384] (1) Absolute time, such as UTC, is used to represent the time domain start location information and / or the time domain end location information of at least one group of first features associated with the first model.

[00385] The first model includes a target model, the time domain information of at least one group of first features associated with the target model is represented by absolute time, and the time domain information of at least one group of first features associated with the target model is determined based on at least one of the following pieces of information:

[00386] a first sum, wherein the first sum is a sum of the time domain start location (represented by a parameter a) of the monitoring feature and a second time offset (represented by a parameter b);

[00387] a first difference, wherein the first difference is a difference between a sequence number corresponding to an nth group of the first features associated with the target model and a first value;

[00388] Seventh sum, where the seventh sum is the sum of the durations, respectively, for the performance of a single Petition 870250086682, dated 09 / 25 / 2025, page 75 / 280 69 / 100 monitoring operation in the first models, and is expressed in A=i;

[00389] a fourth product, wherein the fourth product is a product of the first difference and the seventh sum;

[00390] an eighth sum, wherein the eighth sum is a sum of the durations, respectively, for performing a single monitoring operation on the first models from a 1st (an order of resource allocation of each first model is determined based on the numbering information associated with the first model) first model to Σσ r Ji=° ;

[00391] a fourteenth sum ((a+b) + (e-1) χ Σ” I1 I τ+ emgUe the fourteenth sum is the sum of the first sum, the fourth product and the eighth sum.

[00392] The second time offset is a time offset between a time domain start location of the aperiodic monitoring feature and a time domain start location of a time monitoring slab corresponding to the aperiodic monitoring feature, where eeq are positive integers. The description is provided using an example where the first value is 1.

[00393] A tl time domain starting point of at least one group of first features associated with the target model includes the fourteenth sum and can be expressed by the following formula: tl = (a+b) + (e-1) χ Σί=ι£ί + Σί=ο£-ί

[00394] A final t2 time domain location of at least one group of first features associated with the model Petition 870250086682, dated 09 / 25 / 2025, page 76 / 280 70 / 100 target includes a sum of the fourteenth sum and duration to perform a single monitoring operation on the target model and can be expressed by the following formula: t2 = (a+b) + (e-1) χ ^í=i^ + Σί=(}ί-ί + l(c+i)

[00395] Where a denotes the starting point of the time domain of the monitoring resource; b denotes the second time offset; e denotes a group sequence number of the first resources associated with the same target model in chronological order, where the values ​​of e are sequentially 1, 2, and 3; n denotes the total number of models or a total number of models participating in resource allocation monitoring; c denotes the numbering information associated with the target model; Li denotes information about the duration of a single monitoring operation on a model with a value of c equal to (i-1) (a value of i is 1, 2, ..., n); and L(C+i) denotes information about the duration of a single monitoring operation on the target model (for example, values ​​of numbers associated respectively with models A, B and C are sequentially 0, 1 and 2, and the durations, respectively, to execute a single monitoring operation on the models are sequentially 5 ms, 10 ms and 15 ms, then Li = 5, L2 = 10 and L3 = 15, with Lo defined as 0).

[00396] Each fixed value of c corresponds to a target model, for example, a value of 0 of c corresponds to model A and, depending on the variation in the values ​​of e (the values ​​of e are sequentially 1, 2, 3, a time domain start location of each group of first features associated with model A and / or a time domain end location of each Petition 870250086682, dated 09 / 25 / 2025, p. 77 / 280 71 / 100 of the first group of features associated with model A can be obtained sequentially.

[00397] The time domain locations corresponding to t1 and t2 must not exceed a constraint at the final time domain location of the monitoring resource (corresponding to information 2).

[00398] For example, in Figure 8, a = 0, b = 0, n = 3, a value of 0 for c corresponds to the target model, Li = 5, L2 = 3, L3 = 2, L0 = 0 and the time domain start locations t1 and t2 of the first group of first features associated with the target model are, respectively, the following: t1 = 0 + 0 + (1-1) x (5+3+2) + Lo = 0 and t2 = 0 + 0 + (1-1) x (5+3+2) + Lq + Li = 5.

[00399] (2) A time-domain unit, such as a system frame number or a numerical slot value, is used to represent the time-domain start location information and / or the time-domain end location information of at least one group of first features associated with the first model.

[00400] Reference is made to the description in Case 2: a time-domain unit, such as a system frame number or a numerical slot value, is used to represent the time-domain start location information and / or the time-domain end location information of at least one group of first features associated with the first model. The details are not described again in this document.

[00401] Optionally, T1 denotes a time difference between two adjacent first features associated with a target model, and T1 is configured at a granularity of a model identifier, or a group of identifiers. Petition 870250086682, dated 09 / 25 / 2025, pp. 78 / 280 72 / 100 model, or a device.

[00402] The parameter T1 is determined in at least one of the following ways:

[00403] - a pre-definition procedure;

[00404] - a pre-configuration procedure;

[00405] - a dedicated unicast signaling procedure;

[00406] - a multicast signaling procedure; or

[00407] - a broadcast signaling procedure (including the form of system broadcast messages).

[00408] Optionally, the parameter n is determined in at least one of the following ways:

[00409] - a pre-configuration procedure;

[00410] - a dedicated unicast signaling procedure;

[00411] - a multicast signaling procedure; or

[00412] - a broadcast signaling procedure (including the form of system broadcast messages).

[00413] Optionally, a value of the parameter Li or L(c+i) is configured at a granularity of a model identifier, or a group of model identifiers, or a device, and the value of Li or L(c+1) is determined in at least one of the following ways:

[00414] - a pre-definition procedure;

[00415] - a pre-configuration procedure;

[00416] - a dedicated unicast signaling procedure;

[00417] - a multicast signaling procedure; Petition 870250086682, dated 09 / 25 / 2025, pp. 79 / 280 73 / 100 or

[00418] - a broadcast signaling procedure (including the form of system broadcast messages).

[00419] For example, the first device learns, through a signaling procedure, by monitoring the resource duration to perform a single monitoring operation on each model. The description is provided using three models as an example. The durations of the monitoring resources, respectively, to perform a single monitoring operation on the models are sequentially L1, L2, and L3.

[00420] The first device learns, through a signaling procedure, time-rate information of a monitoring resource that each model expects to occupy. The description is provided using three models as an example. The time-rate information of the monitoring resources that the three models respectively expect to occupy are sequentially 25%, 50%, and 25%, so Li = 0.25 x total duration of a single monitoring operation, L2 = 0.5 x total duration of a single monitoring operation, L3 = 0.25 x total duration of a single monitoring operation.

[00421] In conclusion, according to the method provided in this embodiment, time domain information is determined for at least one group of first features associated with the first model, where the first features are associated with the model monitoring process of the first model, so that the time domain locations associated with the model monitoring processes of different models can be determined, thus being beneficial for the first device and the second Petition 870250086682, dated 09 / 25 / 2025, page 80 / 280 74 / 100 devices maintain consistency in the model monitoring order.

[00422] According to the method provided in this embodiment, the time domain information of at least one group of first features associated with the first model is determined according to the four monitoring feature configuration schemes, thus implementing flexible allocation for a plurality of first models in different monitoring feature configuration schemes.

[00423] According to the method provided in this modality, at least two initial models are associated with the same set of initial information, thus reducing the overall system resource expenditure for monitoring processes.

[00424] According to the method provided in this modality, each first model is associated with its respective first information, thus reducing the complexity of resource allocation.

[00425] Figure 9 is a flowchart of a method for determining information according to an exemplary embodiment of this application. The method is executed by a first device and the method includes step 910 below.

[00426] In step 910, the first device acquires the first information.

[00427] In some embodiments, early information is used to determine time-domain and / or frequency-domain information for at least one group of early features associated with a first model. For a detailed description of early information Petition 870250086682, dated 09 / 25 / 2025, page 81 / 280 For 75 / 100 information, see the corresponding description of step 410 in Figure 4. The details are not described again in this document.

[00428] In conclusion, according to the method provided in this embodiment, the time domain information of at least one group of first features associated with the first model is determined based on the first information and / or numbering information associated with the first model, where the first model is an AI model or an ML model, and the time domain information is associated with a model monitoring process of the first model, so that the time domain locations of at least one group of first features associated with different models can be determined, thus being beneficial for the first device and the second device to maintain consistency in the model monitoring order.

[00429] In some embodiments, the numbering information (or so-called logical number information, i.e., the c parameter) associated with the first model can be determined using at least one of the following three methods:

[00430] (1) determine, based on second information, the numbering information associated with the first model;

[00431] (2) determine, based on third-party information, the numbering information associated with the first model; or

[00432] (3) determine, in a predefined manner, the numbering information associated with the first model.

[00433] For the determinant manner (1), the Figure Petition 870250086682, dated 09 / 25 / 2025, page 82 / 280 76 / 100 is a flowchart of a method for determining information according to an exemplary embodiment of this application. The method is executed by a first device and the method includes step 1010 below.

[00434] In step 1010, the first device receives the second piece of information transmitted by a second device.

[00435] In some embodiments, the first device receives the second piece of information transmitted by the second device. For example, a terminal device receives the second piece of information transmitted by a network device.

[00436] In some embodiments, the first device transmits the second piece of information to the second device. For example, a network device transmits the second piece of information to a terminal device.

[00437] In some forms, the first device determines, based on the explicit configuration of the second information, the numbering information associated with the first model.

[00438] In some embodiments, the second information includes model identifier information from the first model and at least one numbering information.

[00439] The first device determines, based on a first association relation, the numbering information associated with the first model, where the first association relation is an association relation between the model identifier information of the first model and at least one numbering information.

[00440] Model identifier information Petition 870250086682, dated 09 / 25 / 2025, page 83 / 280 77 / 100 are used to identify different models, and the numbering information is used to indicate numbers associated with different models.

[00441] In some modalities, the first association relation includes at least one of the following:

[00442] - information relating to the model identifier is associated with a numbering information;

[00443] - information relating to the model identifier is associated with a plurality of numbering information;

[00444] - a plurality of model identifier information is associated with a numbering information; or

[00445] a plurality of model identifier information is associated with a plurality of numbering information.

[00446] For example, the description is provided using an example in which the numbering information is logical numbering information. An example of the first association relation is shown in Table 1. TABLE 1 Model identifier associated with the first model. Logical numbering information. Model identifier 1: A value of 1. Model identifier 2: A value of 3 or 4... ... Model identifier n: A value of 2 Petition 870250086682, dated 09 / 25 / 2025, page 84 / 280 78 / 100

[00447] In Table 1, a model identifier associated with the first model included in each row is associated with at least one logical numbering piece of information. For example, a model identifier 1 is associated with a logical numbering piece of information with a value of 1, and a model identifier 2 is associated with two logical numbering pieces of information with values ​​of 3 and 4, respectively. There are other examples of the first association relationship, and the examples are not listed one by one in this document. A value of n is a positive integer.

[00448] In some embodiments, the first device receives, in at least one of the following ways, the second piece of information transmitted by the second device:

[00449] - a pre-configuration procedure;

[00450] - a dedicated unicast signaling procedure;

[00451] - a multicast signaling procedure; or

[00452] - a broadcast signaling procedure (including the form of system broadcast messages).

[00453] For the determination method (2), Figure 11 is a flowchart of a method for determining information according to an exemplary embodiment of this application. The method is executed by a first device and the method includes the following step 1110.

[00454] In step 1110, the first device receives the third piece of information transmitted by a second device.

[00455] In some modes, the first device receives the third piece of information transmitted by Petition 870250086682, dated 09 / 25 / 2025, page 85 / 280 79 / 100 second device. For example, a terminal device receives third-party information transmitted by a network device.

[00456] In some embodiments, the first device transmits the third piece of information to the second device. For example, a network device transmits the third piece of information to a terminal device.

[00457] In some embodiments, the first device determines, based on the implicit configuration of the third information, the numbering information associated with the first model.

[00458] In some embodiments, the third information includes model identifier information for at least one first model.

[00459] The first device determines, based on a second association relation, the number information associated with the first model, where the second association relation is an association relation between the location information of the model identifier information of the first model in the third information and the numbering information associated with the first model.

[00460] Model identifier information is used to identify different models, and numbering information is used to indicate numbers associated with different models.

[00461] In some embodiments, the model identifier information of the first model is configured in the form of list parameters, where each element in the list parameters corresponds to a model identifier and the location information of each element in the parameters of Petition 870250086682, dated 09 / 25 / 2025, page 86 / 280 80 / 100 lists correspond to the numbering information of the first model.

[00462] For example, the description is provided using an example in which the numbering information is logical numbering information. An example of the second association relation is shown in Table 2. TABLE 2 1st element: model identifier 1 2nd element: model identifier 2nd element: model identifier n

[00463] In Table 2, a plurality of model identifier information forms parameter information in a list. A first element in the list corresponds to a model identifier 1, and a sequence number locating the first element in the list parameters is 1. In this case, a logical numbering information value corresponding to the first element is considered to be 0 (or 1); similarly, a logical numbering information value corresponding to a model identifier 2 is 1 (or 2); and, by analogy, a logical numbering information value corresponding to a model identifier n is n-1 (or n), where a value of n is a positive integer.

[00464] In some embodiments, the first device receives, in at least one of the following ways, the second piece of information transmitted by the second device:

[00465] - a pre-configuration procedure;

[00466] - a dedicated signaling procedure Petition 870250086682, dated 09 / 25 / 2025, page 87 / 280 81 / 100 unicast;

[00467] - a multicast signaling procedure; or

[00468] - a broadcast signaling procedure (including the form of system broadcast messages).

[00469] For the determinant method (3), in some embodiments, the first device that determines, in the predefined manner, the numbering information associated with the first model includes at least one of the following methods***:

[00470] @ determine, based on an information value of the model identifier of the first model, the numbering information associated with the first model; or

[00471] @ determine, based on the monitoring priority information associated with the first model, the numbering information associated with the first model.

[00472] In the default manner @, the numbering information associated with the first model is determined based on the value of the model identifier information of the first model.

[00473] For example, there are three initial models, and the model identifier information values ​​for the first three models are sequentially '2', '8', and '30'. Therefore, a first model with a model identifier information value equal to '2' corresponds to a numbering information value of '0' (or '1'); a first model with a model identifier information value equal to '8' corresponds to a numbering information value of '1' (or '2'); and a first model with a model identifier information value equal to '30' corresponds to a value of Petition 870250086682, dated 09 / 25 / 2025, pp. 88 / 280 82 / 100 numbering information '2' (or '3').

[00474] In the default manner @, the numbering information associated with the first model is determined based on the monitoring priority information associated with the first model.

[00475] For example, there are three initial models, and the monitoring priority information values ​​for the first three models are sequentially '3', '9', and '15'. Therefore, a first model with a monitoring priority information value equal to '3' corresponds to a numbering information value of '0' (or '1'); a first model with a monitoring priority information value equal to '9' corresponds to a numbering information value of '1' (or '2'); and a first model with a monitoring priority information value equal to '15' corresponds to a numbering information value of '2' (or '3').

[00476] In some embodiments, the numbering information associated with the first model may be determined partly based on the configuration of the second or third information and partly based on the predefined method. This is not limited to this application.

[00477] In some embodiments, Figure 12 is a flowchart of a method for determining information according to an exemplary embodiment of this application. The method is executed by a first device and the method includes the following step 1210.

[00478] In step 1210, the first device transmits the first capacity information to a second device. Petition 870250086682, dated 09 / 25 / 2025, page 89 / 280 83 / 100

[00479] The initial capacity information is used to indicate a related capacity of the first device in the model monitoring.

[00480] In some modes, the initial capacity information includes at least one of the following:

[00481] a method of allocating a monitoring resource based on numbering information should be supported;

[00482] a method of allocating a periodic monitoring resource based on numbering information should be supported;

[00483] a method of allocating a first monitoring resource based on numbering information should be supported;

[00484] a method for allocating a second monitoring resource based on numbering information should be supported;

[00485] a method of allocating an aperiodic monitoring resource based on numbering information should be supported;

[00486] a method of allocating a third monitoring resource based on numbering information should be supported;

[00487] a method for allocating a fourth monitoring resource based on numbering information should be supported;

[00488] whether a monitoring resource allocation mode based on independent monitoring resource configuration should be supported; or

[00489] a mode of resource allocation of Petition 870250086682, dated 09 / 25 / 2025, pp. 90 / 280 84 / 100 monitoring supported.

[00490] The first monitoring resource is a periodic monitoring resource, any resource repetition period within the periodic monitoring resource includes a plurality of monitoring time windows, and the allocation mode of the first monitoring resource corresponds to resource configuration scheme 1 in the mode shown in Figure 5.

[00491] The second monitoring resource is a periodic monitoring resource, any resource repetition period within the periodic monitoring resource includes a monitoring time window, and the allocation mode of the second monitoring resource corresponds to the resource configuration scheme 2 in the mode shown in Figure 6.

[00492] The third monitoring resource is an aperiodic monitoring resource, any aperiodic monitoring resource includes a plurality of monitoring time windows, and the allocation mode of the third monitoring resource corresponds to the resource configuration scheme 3 in the mode shown in Figure 7.

[00493] The fourth monitoring resource is an aperiodic monitoring resource, any aperiodic monitoring resource includes a monitoring time window, and the allocation mode of the fourth monitoring resource corresponds to the resource configuration scheme 4 in the mode shown in Figure 8.

[00494] In conclusion, according to the method provided in this modality, the first capacity information is transmitted, so that the second device Petition 870250086682, dated 09 / 25 / 2025, pp. 91 / 280 85 / 100 determines whether the first device supports a related monitoring resource allocation mode, and therefore the second device configures a corresponding monitoring resource, thus avoiding the configuration of inappropriate monitoring resources for the first device.

[00495] In some embodiments, Figure 13 is a flowchart of a method for determining information according to an exemplary embodiment of this application. The method is executed by a first device and the method includes the following step 1310.

[00496] In step 1310, the first device receives secondary capacity information transmitted by a second device.

[00497] Second capacity information is used to indicate a related capacity of the second device in model monitoring.

[00498] In some modes, the secondary capacity information includes at least one of the following:

[00499] a method of allocating a monitoring resource based on numbering information should be supported;

[00500] a periodic monitoring resource allocation mode based on numbering information must be supported;

[00501] a method of allocating a first monitoring resource based on numbering information should be supported;

[00502] a method for allocating a second monitoring resource based on numbering information should be supported; Petition 870250086682, dated 09 / 25 / 2025, page 92 / 280 86 / 100

[00503] a method of allocating an aperiodic monitoring resource based on numbering information should be supported;

[00504] a third-party monitoring resource allocation method based on numbering information should be supported;

[00505] a method for allocating a fourth monitoring resource based on numbering information should be supported;

[00506] whether a monitoring resource allocation mode based on independent monitoring resource configuration should be supported; or

[00507] a supported monitoring resource allocation mode.

[00508] The first monitoring resource is a periodic monitoring resource, any resource repetition period within the periodic monitoring resource includes a plurality of monitoring time windows, and the allocation mode of the first monitoring resource corresponds to resource configuration scheme 1 in the mode shown in Figure 5.

[00509] The second monitoring resource is a periodic monitoring resource, any resource repetition period within the periodic monitoring resource includes a monitoring time window, and the allocation mode of the second monitoring resource corresponds to the resource configuration scheme 2 in the mode shown in Figure 6.

[00510] The third monitoring feature is an aperiodic monitoring feature, any feature of Petition 870250086682, dated 09 / 25 / 2025, page 93 / 280 87 / 100 aperiodic monitoring includes a plurality of monitoring time windows, and the allocation mode of the third monitoring resource corresponds to the resource configuration scheme 3 in the mode shown in Figure 7.

[00511] The fourth monitoring resource is an aperiodic monitoring resource, any aperiodic monitoring resource includes a monitoring time window, and the allocation mode of the fourth monitoring resource corresponds to the resource configuration scheme 4 in the mode shown in Figure 8.

[00512] In conclusion, according to the method provided in this embodiment, the second capacity information is received, so that the first device determines whether the second device supports a related monitoring resource allocation mode and, therefore, the first device configures or requests a corresponding monitoring resource, thus avoiding the configuration of inappropriate monitoring resources for the first device or the second device.

[00513] In the previous embodiment, the embodiment corresponding to Figure 4, the embodiment corresponding to Figure 9, and the embodiment corresponding to Figure 10 can be implemented in combination.

[00514] The mode corresponding to Figure 4, the mode corresponding to Figure 9, and the mode corresponding to Figure 11 can be implemented in combination.

[00515] The modality corresponding to Figure 4, the modality corresponding to Figure 9, the modality corresponding to Figure 10, the modality corresponding to Petition 870250086682, dated 09 / 25 / 2025, pp. 94 / 280 88 / 100 Figure 12 and the modality corresponding to Figure 13 can be implemented in combination.

[00516] The modality corresponding to Figure 4, the modality corresponding to Figure 9, the modality corresponding to Figure 11, the modality corresponding to Figure 12, and the modality corresponding to Figure 13 can be implemented in combination, which is not limited in this request.

[00517] Figure 14 is a flowchart of a method for transmitting information according to an exemplary embodiment of this request. The method is executed by a second device and includes the following step 1410.

[00518] In step 1410, the second device transmits the first information to a first device.

[00519] The initial information is associated with a model monitoring process of a first model, and the first model is an AI model or an ML model.

[00520] The initial information includes at least one of the following:

[00521] a time domain start location of a monitoring resource;

[00522] a final time domain location of a monitoring resource;

[00523] a first time shift;

[00524] a total number of monitoring time windows included in an aperiodic monitoring feature;

[00525] a single time window duration for monitoring;

[00526] an interval between time windows of Petition 870250086682, dated 09 / 25 / 2025, page 95 / 280 89 / 100 adjacent monitoring;

[00527] a feature repetition period corresponding to a periodic monitoring feature;

[00528] a second time shift;

[00529] a total number of monitoring time windows included in a single feature replay period within a periodic monitoring feature; or

[00530] a total number of resource repetition periods corresponding to the periodic monitoring resource.

[00531] The first time offset is a time offset between a time domain start location of the aperiodic monitoring resource and a time domain start location of a 1st monitoring time window corresponding to the aperiodic monitoring resource; the second time offset is a time offset between a time domain start location of a 1st monitoring time window in any resource repetition period within the periodic monitoring resource and a time domain start location of a last single resource repetition period within the periodic monitoring resource; and the time domain resources corresponding to the time domain information of at least one group of first resources are included in or are part of the monitoring resource.

[00532] For a description of specific implementation details, reference is made to the corresponding description of step 410 in Figure 4, and the details are not described again in this document.

[00533] Figure 15 is a flowchart of a method Petition 870250086682, dated 09 / 25 / 2025, page 96 / 280 90 / 100 of information transmission according to an exemplary embodiment of this request. The method is executed by a second device and includes the following step 1510.

[00534] In step 1510, the second device transmits second or third information to a first device.

[00535] Second or third information is used to determine the numbering information of a first model. Second information is used to determine the numbering information of the first model in an explicit configuration manner, and third information is used to determine the numbering information of the first model in an implicit configuration manner.

[00536] For specific implementation details, see step 1010 in Figure 10 or step 1110 in Figure 11. The details are not described again in this document.

[00537] Figure 16 is a flowchart of a method for transmitting information according to an exemplary embodiment of this request. The method is executed by a second device and includes the following step 1610.

[00538] In step 1610, the second device determines at least one group of time-domain information associated with a first model.

[00539] Time domain information is associated with a monitoring process of the first model.

[00540] For specific implementation details, see step 410 in Figure 4. Details Petition 870250086682, dated 09 / 25 / 2025, page 97 / 280 91 / 100 are not described again in this document.

[00541] Figure 17 is a flowchart of a method for transmitting information according to an exemplary embodiment of this request. The method is executed by a second device and includes the following step 1710.

[00542] In step 1710, the second device receives the first capacity information transmitted by a first device.

[00543] The initial capacity information is used to indicate a related capacity of the first device in the model monitoring.

[00544] In some modes, the initial capacity information includes at least one of the following:

[00545] a method of allocating a monitoring resource based on numbering information should be supported;

[00546] a method of allocating a periodic monitoring resource based on numbering information should be supported;

[00547] a method of allocating a first monitoring resource based on numbering information should be supported;

[00548] a method for allocating a second monitoring resource based on numbering information should be supported;

[00549] a method of allocating an aperiodic monitoring resource based on numbering information should be supported;

[00550] a third-party monitoring resource allocation method should be supported based on information from Petition 870250086682, dated 09 / 25 / 2025, pp. 98 / 280 92 / 100 numbering;

[00551] a method for allocating a fourth monitoring resource based on numbering information should be supported;

[00552] whether a monitoring resource allocation mode based on independent monitoring resource configuration should be supported; or

[00553] a supported monitoring resource allocation mode.

[00554] The first monitoring resource is a periodic monitoring resource, and any resource repetition period within the periodic monitoring resource includes a plurality of monitoring time windows; the second monitoring resource is the periodic monitoring resource, and any resource repetition period within the periodic monitoring resource includes a monitoring time window; the third monitoring resource is an aperiodic monitoring resource, and any aperiodic monitoring resource includes a plurality of monitoring time windows; and the fourth monitoring resource is the aperiodic monitoring resource, and any aperiodic monitoring resource includes a monitoring time window.

[00555] For specific implementation details, see step 1210 in Figure 12. The details are not described again in this document.

[00556] Figure 18 is a flowchart of a method for transmitting information according to an exemplary embodiment of this request. The method is executed by a second device and includes the following step 1810. Petition 870250086682, dated 09 / 25 / 2025, page 99 / 280 93 / 100

[00557] In step 1810, the second device transmits secondary capacity information to a first device.

[00558] In some embodiments, the second capacity information is used to indicate a related capacity of the second device in a model monitoring dimension.

[00559] The second capacity information includes at least one of the following:

[00560] a mode for allocating a monitoring resource based on numbering information should be supported;

[00561] a method of allocating a periodic monitoring resource based on numbering information should be supported;

[00562] a method of allocating a first monitoring resource based on numbering information should be supported;

[00563] a method for allocating a second monitoring resource based on numbering information should be supported;

[00564] a method of allocating an aperiodic monitoring resource based on numbering information should be supported;

[00565] a third-party monitoring resource allocation method based on numbering information should be supported;

[00566] a method for allocating a fourth monitoring resource based on numbering information should be supported;

[00567] should support an allocation mode of a Petition 870250086682, dated 09 / 25 / 2025, pages 100 / 280 94 / 100 monitoring feature based on independent monitoring feature configuration; or

[00568] a supported monitoring resource allocation mode.

[00569] The first monitoring resource is a periodic monitoring resource, and any resource repetition period within the periodic monitoring resource includes a plurality of monitoring time windows; the second monitoring resource is the periodic monitoring resource, and any resource repetition period within the periodic monitoring resource includes a monitoring time window; the third monitoring resource is an aperiodic monitoring resource, and any aperiodic monitoring resource includes a plurality of monitoring time windows; and the fourth monitoring resource is the aperiodic monitoring resource, and any aperiodic monitoring resource includes a monitoring time window.

[00570] For specific implementation details, see step 1310 in Figure 13. The details are not described again in this document.

[00571] Any information involved in the previous modes is carried by any of the following messages, or any message involved in the previous modes is any of the following:

[00572] an LPP message, a NAS message, an RRC message, a Media Access Control Element (MAC CE) message, a Downlink Control Information (DCI) message, a Petition 870250086682, dated 09 / 25 / 2025, pp. 101 / 280 95 / 100 uplink control information message (Uplink Control Information, UCI), a physical uplink control channel message (Physical Uplink Control Channel, PUCCH), a physical uplink shared channel message (Physical Uplink Shared Channel, PUSCH), an inter-node message, an Xn interface message, an F1 interface message, an E1 interface message, an NG interface message, or a core network bus message.

[00573] Optionally, any information involved in the previous modes is carried by any of the following messages, or any message involved in the previous modes is any of the following:

[00574] a unicast message, a multicast message or a broadcast message.

[00575] Unicast (one-to-one) message: an information source transmits a unicast message using a unicast channel. Only a terminal device or network device to which a corresponding unicast resource has been allocated can attempt to receive the unicast message, and the unicast message can also be called dedicated signaling.

[00576] Multicast message (one-to-multiple): an information source transmits a multicast message using a multicast channel, a terminal device or a network device that is within the coverage of the multicast signal and is a member of the group may attempt to receive the multicast message, and the terminal device or network device acquires a resource related to the multicast channel by joining a group. Petition 870250086682, dated 09 / 25 / 2025, page 102 / 280 96 / 100

[00577] Broadcast message (one-to-any): an information source transmits a broadcast message using a broadcast channel, and any terminal device or network device within the coverage of the broadcast signal can attempt to receive the broadcast message.

[00578] Figure 19 is a block diagram of an information determination apparatus according to an exemplary embodiment of this application. The apparatus includes a determination module 1910, an acquisition module 1920, and a transmission module 1930. A function of the determination module 1910 is implemented by a processor in a first device, while functions of the acquisition module 1920 and the transmission module 1930 are implemented by a transceiver in the first device.

[00579] The determination module 1910 is configured to execute step 410 in the previous mode shown in Figure 4.

[00580] Acquisition module 1920 is configured to execute step 910 in the previous mode shown in Figure 9, step 1010 in the previous mode shown in Figure 10, step 1110 in the previous mode shown in Figure 11, and step 1310 in the mode shown in Figure 13.

[00581] Transmission module 1930 is configured to execute step 1210 in the previous mode shown in Figure 12.

[00582] Figure 20 is a block diagram of an information transmission apparatus according to an exemplary embodiment of this application. The apparatus includes a transmission module 2010, a determination module 2020 and Petition 870250086682, dated 09 / 25 / 2025, page 103 / 280 97 / 100 a receiving module 2030. A function of the determination module 2020 is implemented by a processor in a first device, while functions of the transmission module 2010 and the receiving module 2030 are implemented by a transceiver in a second device.

[00583] Transmission module 2010 is configured to execute step 1410 in the previous mode shown in Figure 14, step 1510 in the previous mode shown in Figure 15, and step 1810 in the previous mode shown in Figure 18.

[00584] The 2020 determination module is configured to execute step 1610 in the previous mode shown in Figure 16.

[00585] The 2030 reception module is configured to execute step 1710 in the previous mode shown in Figure 17.

[00586] Figure 21 is a schematic structural diagram of a first device or a second device 2100 according to an exemplary embodiment of this application. The first device or the second device includes a processor 2101, a receiver 2102, a transmitter 2103, a memory 2104 and a bus 2105.

[00587] The 2101 processor includes one or more processing cores. The 2101 processor executes various functional applications and information processing through the execution of a software program and a module. In some embodiments, the 2101 processor can be configured to implement functions and steps of the earlier 1910 determination module and 2020 determination module.

[00588] Receiver 2102 and transmitter 2103 can Petition 870250086682, dated 09 / 25 / 2025, page 104 / 280 98 / 100 to be implemented as a communication component, the communication component can be a communication chip and the communication component can be called a transceiver. In some embodiments, the transceiver can be configured to implement functions and steps of the 1920 acquisition module, the 1930 transmission module, the 2010 transmission module, and the 2030 reception module.

[00589] Memory 2104 is connected to the processor 2101 using the 2105 bus.

[00590] Memory 2104 can be configured to store at least one instruction, and processor 2101 is configured to execute at least one instruction, to implement the steps in the modes of the previous method.

[00591] In addition, the 2104 memory can be implemented using any type of volatile or non-volatile storage device, or a combination thereof. Volatile or non-volatile storage devices include, without limitation: a magnetic disk, an optical disk, an electrically erasable programmable read-only memory (Electrically Erasable Programmable Read-Only Memory, EEPROM), an erasable programmable read-only memory (EPROM), a static random access memory (SRAM), a read-only memory (ROM), a magnetic memory, a flash memory, and a programmable read-only memory (PROM).

[00592] In some embodiments, receiver 2102 receives signals / data independently, or processor 2101 controls receiver 2102 to receive signals / data, or the Petition 870250086682, dated 09 / 25 / 2025, page 105 / 280 99 / 100 Processor 2101 requests that receiver 2102 receive signals / data, or processor 2101 cooperates with receiver 2102 to receive signals / data.

[00593] In some embodiments, transmitter 2103 transmits signals / data independently, or processor 2101 controls transmitter 2103 to transmit signals / data, or processor 2101 requests transmitter 2103 to transmit signals / data, or processor 2101 cooperates with transmitter 2103 to transmit signals / data.

[00594] In an exemplary embodiment, a computer-readable storage medium is additionally provided. The computer-readable storage medium stores at least one instruction, at least one program segment, or a set of codes or instruction set, and the at least one instruction, at least one program segment, or the set of codes or instruction set is loaded and executed by a processor to implement the information determination method and the information transmission method provided in the previous embodiments of the method.

[00595] In one embodiment, a computer program product or a computer program is additionally provided. The computer program product or the computer program, when executed on a processor, causes a first device to execute the information determination method provided in the previous method embodiments, and a second device to execute the information transmission method provided in the previous method embodiments.

[00596] Someone skilled in the art might understand that Petition 870250086682, dated 09 / 25 / 2025, page 106 / 280 100 / 100 All or some of the steps in the previous modes can be implemented by hardware or by a program that instructs the related hardware. The program can be stored on a computer-readable storage medium. The computer-readable storage medium can be read-only memory, a magnetic disk, an optical disk, or similar.

[00597] The foregoing descriptions are merely optional modalities of this application, but are not intended to limit it. Any modifications, equivalent substitutions, improvements and the like made without departing from the spirit and principle of this application shall be within the scope of protection of this application. Petition 870250086682, dated 09 / 25 / 2025, page 107 / 280

Claims

1 / 24 CLAIMS 1. INFORMATION DETERMINATION METHOD, wherein the method is characterized by being executed by a first device and wherein the method comprises: determining at least one group of time-domain information associated with a first model; wherein the first model is an AI model of artificial intelligence or a ML model of machine learning, and the time-domain information is associated with a monitoring process of the first model; wherein the determination of at least one group of time-domain information associated with the first model comprises: determining time-domain information of at least one group of first features associated with the first model, wherein the first features are associated with the monitoring process of the first model.

2. METHOD, according to claim 1, characterized by the determination of time domain information of at least one group of first resources associated with the first model comprising: determining, based on the first information, the time domain information of at least one group of first resources associated with the first model; or determining, based on the numbering information associated with the first model, the time domain information of at least one group of first resources associated with the first model; or determining, based on the first information and the numbering information associated with the first model, the time domain information of at least one group of first resources associated with the first model, wherein the first information is associated with the model monitoring process of the first model;wherein the first piece of information comprises at least one of the following: a time domain start location of a monitoring resource; a time domain end location of a monitoring resource; a first time offset; a total number of monitoring time windows comprised within an aperiodic monitoring resource; a window duration of a single monitoring time window; an interval between adjacent monitoring time windows; a resource repetition period corresponding to a periodic monitoring resource; a second time offset; a total number of monitoring time windows comprised within a single resource repetition period within a periodic monitoring resource;a total number of feature repetition periods corresponding to the periodic monitoring feature, wherein the first time offset is a time offset between a time domain start location of the aperiodic monitoring feature and a time domain start location of a 1st monitoring time window corresponding to the aperiodic monitoring feature; the second time offset is a time offset between a time domain start location of a 1st monitoring time window in any feature repetition period within the periodic monitoring feature and a time domain start location of a last feature repetition period within the periodic monitoring feature;and time-domain resources corresponding to the time-domain information of at least one group of first resources are included in or are part of the monitoring resource.

3. METHOD, according to claim 1 or 2, characterized in that each group of time-domain information in the time-domain information of at least one group of first features comprises at least one of the following: time-domain start location information of the first features; time-domain end location information of the first features; or time-domain length information of the first features.

4. METHOD, according to claim 2, characterized by further comprising: determining, based on second information, the numbering information associated with the first model; or determining, based on third information, the numbering information associated with the first model; or Petition 870250086682, dated 09 / 25 / 2025, page 110 / 280 4 / 24 determining, in a predefined manner, the numbering information associated with the first model; wherein the second information comprises model identifier information and at least one numbering information of the first model;wherein the determination, based on the second piece of information, of the numbering information associated with the first model comprises: determining, based on a first association relation, the numbering information associated with the first model, wherein the first association relation is an association relation between the model identifier information of the first model and at least one piece of numbering information; or wherein the third piece of information comprises model identifier information of at least one first model;wherein the determination, based on third-party information, of the numbering information associated with the first model comprises: determining, based on a second association relation, the numbering information associated with the first model, wherein the second association relation is an association relation between the location information of the model identifier information of the first model in the third-party information and the numbering information associated with the first model; or wherein the determination, in a predefined manner, of the numbering information associated with the first model comprises: determining, based on a value of the model identifier information of the first model, the numbering information associated with the first model; or determining, based on the monitoring priority information associated with the first model, the numbering information associated with the first model.

5. METHOD, according to any one of claims 2 to 4, characterized in that the first information comprises a periodic monitoring feature, and any feature repetition period within the periodic monitoring feature comprises a plurality of monitoring time windows; or in that the first information comprises a periodic monitoring feature and any feature repetition period within the periodic monitoring feature comprises a monitoring time window; or in that the first information comprises an aperiodic monitoring feature and any aperiodic monitoring feature comprises a plurality of monitoring time windows; or in that the first information comprises an aperiodic monitoring feature and any aperiodic monitoring feature comprises a monitoring time window.

6. METHOD, according to claim 5, characterized in that the first model comprises a target model, wherein the time domain information of at least one group of first features associated with the target model is represented by absolute time and the time domain information of at least one group of first features associated with the target model is determined based on at least one of the following: a first sum, wherein the first sum is the sum of a time domain start location of a monitoring feature and a second time offset; a second sum, wherein the second sum is the sum of a window length of a single monitoring time window and an interval between adjacent monitoring time windows;a first difference, where the first difference is a difference between a sequence number corresponding to the nth group of the first features associated with the target model and a first value; a second difference, where the second difference is a difference between a sequence number corresponding to the qth feature repetition period within the periodic monitoring feature and the first value; a first product, where the first product is a product of the first difference, the second sum, and a total number of first models; a second product, where the second product is a product of the numbering information associated with the target model and the second sum; and a third product, where the third product is a product of the second difference and a feature repetition period corresponding to the periodic monitoring feature;or a third sum, wherein the third sum is the sum of the first sum, the first product, the second product, and the third product, wherein the second time offset is a time offset between a time domain start location of a first monitoring time window in any feature repetition period within the periodic monitoring feature and a time domain start location of a last single feature repetition period within the periodic monitoring feature, where eeq are positive integers; wherein a time domain start location of at least one group of first features associated with the target model comprises the third sum; and / or a time domain end location of at least one group of first features associated with the target model comprises a sum of the third sum and the window length of a single monitoring time window;or wherein the first model comprises a target model, the time domain information of at least one group of first features associated with the target model is represented by a time domain unit, and the time domain information of at least one group of first features associated with the target model is determined based on at least one of the following pieces of information: a second sum, wherein the second sum is the sum of the window length of a single monitoring time window and an interval between adjacent monitoring time windows; a second product, wherein the second product is a product of the numbering information associated with the target model and the second sum, and the second product is denoted as z, wherein z is greater than or equal to 0;a fourth sum, wherein the fourth sum is the sum of the second product and a first numerical slot value, and the first numerical slot value is denoted as k, where k is a positive integer; a second numerical slot value, wherein the second numerical slot value is a value obtained by performing a modulo operation on the fourth sum and a total number of slots included in each radio frame; a first quotient, wherein the first quotient is a quotient obtained by dividing the second product by a total number of slots included in each radio frame; a first integer value, wherein the first integer value is a base operation value of the first quotient; a third difference, wherein the third difference is the difference between a first radio frame number and a first parameter, and the first radio frame number is denoted as SFN;a first remainder, wherein the first remainder is a value obtained by performing a modulo operation on the third difference and in a period of occurrence of the first features associated with the target model, wherein the first numerical value of the slot represents a numerical value of a slot in a radio frame corresponding to a time domain start location of a 1st monitoring time window in any feature repetition period within the periodic monitoring feature or the aperiodic monitoring feature; the first Petition 870250086682, dated 09 / 25 / 2025, page 115 / 280 9 / 24 radio frame number represents a number of a radio frame to which a time domain start location of at least one group of first features associated with the target model belongs;and the first parameter represents a numeric value of a radio frame to which a time domain start location of a 1st monitoring time window belongs in any feature repetition period within the periodic monitoring feature or the aperiodic monitoring feature, or represents a value obtained by performing a modulo operation on a numeric value of a radio frame to which a time domain start location of a P monitoring time window belongs in any feature repetition period within the periodic monitoring feature and a feature repetition period corresponding to the periodic monitoring feature; wherein the time domain start location of at least one group of first features associated with the target model comprises time domain locations indicated by the first radio frame number and the second numeric slot value;or wherein the first model comprises a target model, the time domain information of at least one group of first features associated with the target model is represented by a time domain unit, and the time domain information of at least one group of first features associated with the target model is determined based on at least one of the following pieces of information: a second sum, wherein the second sum is the sum of a window length of a single monitoring time window and an interval between adjacent monitoring time windows; a second product, wherein the second product is a product of the numbering information associated with the target model and the second sum; a fifth sum, wherein the fifth sum is the sum of the second product and the window length of a single monitoring time window, and the fifth sum is denoted as z, wherein z is greater than or equal to 0;a sixth sum, wherein the sixth sum is the sum of the fifth sum and the first numerical slot value, and the first numerical slot value is denoted as k, where k is a positive integer; a third numerical slot value, wherein the third numerical slot value is a value obtained by performing a modulo operation on the sixth sum and the total number of slots contained in each radio frame; a second quotient, wherein the second quotient is a quotient obtained by dividing the fifth sum by the total number of slots contained in each radio frame; a second integer value, wherein the second integer value is a base operation value of the second quotient; a fourth difference, wherein the fourth difference is a difference between a second radio frame number and a first parameter, and the second radio frame number is represented by SFN;or a second remainder, wherein the second remainder is a value obtained by performing a modulo operation on the fourth difference and in a period of occurrence of the first features associated with the target model, as per Petition 870250086682, dated 09 / 25 / 2025, page 117 / 280 11 / 24, wherein the first numerical slot value represents a numerical value of a slot in a radio frame corresponding to a time domain start location of a 1st monitoring time window in any feature repetition period within the periodic monitoring feature or the aperiodic monitoring feature; the second radio frame number represents a radio frame number to which a time domain start location of at least one group of first features associated with the target model belongs;and the first parameter represents a numeric value of a radio frame to which a time domain start location of a 1st monitoring time window belongs in any feature repetition period within the periodic monitoring feature or the aperiodic monitoring feature, or represents a value obtained by performing a modulo operation on a numeric value of a radio frame to which a time domain start location of a 1st monitoring time window belongs in any feature repetition period within the periodic monitoring feature and a feature repetition period corresponding to the periodic monitoring feature; wherein a time domain end location of at least one group of first features associated with the target model comprises time domain locations indicated by the second radio frame number and the third numeric slot value.

7. METHOD, according to claim 5, characterized in that the first model comprises a target model, wherein the time domain information of at least one group of first features associated with the target model is represented by absolute time and the time domain information of at least one group of first features associated with the target model is determined based on at least one of the following pieces of information: a first sum, wherein the first sum is the sum of a time domain start location of a monitoring feature and a second time offset; a first difference, wherein the first difference is a difference between a sequence number corresponding to an nth group of first features associated with the target model and a first value;a second difference, where the second difference is a difference between a sequence number corresponding to a qth feature repetition period within the periodic monitoring feature and the first value; a seventh sum, where the seventh sum is a sum of the durations, respectively, for performing a single monitoring operation on the first models; a fourth product, where the fourth product is a product of the first difference and the seventh sum; an eighth sum, where the eighth sum is a sum of durations, respectively, for performing a single monitoring operation on the first models from a first model to the target model; a third product, where the third product is a product of the second difference and a feature repetition period corresponding to the periodic monitoring feature;or a ninth sum, wherein the ninth sum is the sum of the first sum, the fourth product, the eighth sum, and the third product; wherein the second time offset is a time offset between a time domain start location of a first monitoring time window in any feature repetition period within the periodic monitoring feature and a time domain start location of a last single feature repetition period within the periodic monitoring feature, where eeq are positive integers; wherein a time domain start location of at least one group of first features associated with the target model comprises the ninth sum; and / or a time domain end location of at least one group of first features associated with the target model comprises a sum of the ninth sum and the duration for performing a single monitoring operation on the target model;or wherein the first model comprises a target model, the time domain information of at least one group of first features associated with the target model is represented by a time domain unit, and the time domain information of at least one group of first features associated with the target model is determined based on at least one of the following: an eighth sum, wherein the eighth sum is a sum of the durations, respectively, for performing a single monitoring operation on the first models, starting from a first model to the target model, and the eighth sum is denoted as z, wherein z is greater than or equal to 0; a tenth sum, wherein the tenth sum is the sum of the eighth sum and the first numerical slot value, and the first numerical slot value is denoted by k, wherein k is a positive integer;a fourth numerical slot value, wherein the fourth numerical slot value is a value obtained by performing a modulo operation on the tenth sum and the total number of slots included in each radio frame; a third quotient, wherein the third quotient is a quotient obtained by dividing the eighth sum by the total number of slots included in each radio frame; a third integer value, wherein the third integer value is a base operation value of the third quotient; a fifth difference, wherein the fifth difference is the difference between a third radio frame number and a first parameter, and the third radio frame number is represented by SFN;a third remainder, wherein the third remainder is a value obtained by performing a modulo operation on the fifth difference and in a period of occurrence of the first features associated with the target model, wherein the first numerical value of the slot represents a numerical value of a slot in a radio frame corresponding to a time domain start location of a 1st monitoring time window in any feature repetition period within the periodic monitoring feature or the aperiodic monitoring feature; the third radio frame number represents a radio frame number to which a time domain start location of at least one group of first features associated with the target model belongs;and the first parameter represents a numeric value of a radio frame to which a time domain start location of a 1st monitoring time window belongs in any feature repetition period within the periodic monitoring feature or the aperiodic monitoring feature, or represents a value obtained by performing a modulo operation on a numeric value of a radio frame to which a time domain start location of a P monitoring time window belongs in any feature repetition period within the periodic monitoring feature and a feature repetition period corresponding to the periodic monitoring feature; wherein the time domain start location of at least one group of first features associated with the target model comprises time domain locations indicated by the third radio frame number and the fourth slot number value;or wherein the first model comprises a target model, the time domain information of at least one group of first features associated with the target model is represented by a time domain unit, and the time domain information of at least one group of first features associated with the target model is determined based on at least one of the following: an eighth sum, wherein the eighth sum is a sum of the durations, respectively, for the execution of a single monitoring operation on the first models, starting from a first model to the target model; an eleventh sum, wherein the eleventh sum is a sum of the eighth sum and the duration for the execution of a single monitoring operation on the target model, and the eleventh sum is denoted as z, wherein z is greater than or equal to 0;a twelfth sum, wherein the twelfth sum is the sum of the eleventh sum and the first numerical slot value, and the first numerical slot value is denoted as k, where k is a positive integer; a fifth numerical slot value, wherein the fifth numerical slot value is a value obtained by performing a modulo operation on the twelfth sum and the total number of slots included in each radio frame; a fourth quotient, wherein the fourth quotient is a quotient obtained by dividing the eleventh sum by the total number of slots included in each radio frame; a fourth integer value, wherein the fourth integer value is a base operation value of the fourth quotient; a sixth difference, wherein the sixth difference is the difference between a fourth radio frame number and a first parameter, and the fourth radio frame number is represented by SFN;or a fourth remainder, wherein the fourth remainder is a value obtained by performing a modulo operation on the sixth difference and within a period of occurrence of the first features associated with the target model, wherein the first numerical value of the slot represents a numerical value of a slot in a radio frame corresponding to a time domain start location of a 1st monitoring time window in any period of feature repetition within the periodic monitoring feature or the aperiodic monitoring feature; the fourth radio frame number represents a radio frame number to which a time domain start location of at least one group of first features associated with the target model belongs;and the first parameter represents a numeric value of a radio frame to which a time domain start location of a 1st monitoring time window belongs in any feature repetition period within the periodic monitoring feature or the aperiodic monitoring feature, or represents a value obtained by performing a modulo operation on a numeric value of a radio frame to which a time domain start location of an M monitoring time window belongs in any feature repetition period within the periodic monitoring feature and a feature repetition period corresponding to the periodic monitoring feature; wherein a time domain end location of at least one group of first features associated with the target model comprises time domain locations indicated by the fourth radio frame number and the fifth slot number value.

8. METHOD, according to claim 5, characterized in that the first model comprises a target model, wherein the time domain information of at least one group of first features associated with the target model is represented by absolute time and the time domain information of at least one group of first features associated with the target model is determined based on at least one of the following: Petition 870250086682, dated 09 / 25 / 2025, page 124 / 280 18 / 24 a first sum, wherein the first sum is the sum of a time domain start location of a monitoring feature and a second time offset; a second sum, wherein the second sum is the sum of a window length of a single monitoring time window and an interval between adjacent monitoring time windows;a first difference, where the first difference is a difference between a sequence number corresponding to the nth group of the first features associated with the target model and a first value; a second difference, where the second difference is a difference between a sequence number corresponding to the qth feature repetition period within the periodic monitoring feature and the first value; a first product, where the first product is a product of the first difference, the second sum, and a total number of first models; a second product, where the second product is a product of the numbering information associated with the target model and the second sum;and a thirteenth sum, wherein the thirteenth sum is the sum of the first sum, the first product, and the second product, wherein the second time offset is a time offset between a time domain start location of the aperiodic monitoring feature and a time domain start location of a first monitoring time window corresponding to the aperiodic monitoring feature, where eeq are positive integers; Petition 870250086682, dated 09 / 25 / 2025, pp. 125 / 280 19 / 24 wherein a time domain start location of at least one group of first features associated with the target model comprises the thirteenth sum; and / or a time domain end location of at least one group of first features associated with the target model comprises a sum of the thirteenth sum and the window length of a single monitoring time window.

9. METHOD, according to claim 5, characterized in that the first model comprises a target model, wherein the time domain information of at least one group of first features associated with the target model is represented by absolute time and the time domain information of at least one group of first features associated with the target model is determined based on at least one of the following pieces of information: a first sum, wherein the first sum is the sum of a time domain start location of a monitoring feature and a second time offset; a first difference, wherein the first difference is a difference between a sequence number corresponding to an nth group of the first features associated with the target model and a first value; a seventh sum, wherein the seventh sum is a sum of the durations, respectively, for performing a single monitoring operation on the first models;a fourth product, wherein the fourth product is a product of the first difference and the seventh sum; an eighth sum, wherein the eighth sum is a sum of durations, respectively, to perform a single monitoring operation on the first models from a first model to the target model; a fourteenth sum, wherein the fourteenth sum is the sum of the first sum, the fourth product, and the eighth sum; wherein the second time offset is a time offset between a time domain start location of the aperiodic monitoring feature and a time domain start location of a first monitoring time window corresponding to the aperiodic monitoring feature, where eeq are positive integers; wherein a time domain start location of at least one group of first features associated with the target model comprises the fourteenth sum;and / or a final time domain location of at least one group of first features associated with the target model comprises a sum of the fourteenth sum and the duration for the execution of a single monitoring operation on the target model.

10. METHOD, according to any one of claims 5, 6 or 8, characterized in that the first model comprises a target model, and in which the method further comprises: determining, based on the numbering information associated with the target model, sequence number information for at least one monitoring time window associated with the target model; in which the determination, based on the numbering information associated with the target model, of the sequence number information for at least one monitoring time window associated with the target model comprises: determining, based on a fifth remainder and on Petition 870250086682, dated 09 / 25 / 2025, p.127 / 280 21 / 24 numbering information associated with the target model, the sequence number information of at least one monitoring time window associated with the target model, wherein the fifth remainder is a value obtained by performing a modulo operation on a sequence number associated with any monitoring time window in at least one monitoring time window and a total number of first models, and the fifth remainder is the same as the numbering information associated with the target model.

11. INFORMATION TRANSMISSION METHOD, the method being characterized by being executed by a second device and comprising: transmitting the first information to a first device, where the first information is associated with a model monitoring process of a first model, and the first model is an AI (artificial intelligence) model or a ML (machine learning) model.

12. METHOD, according to claim 11, characterized by further comprising: receiving the first capacity information transmitted by the first device, wherein the first capacity information is used to indicate a related capacity of the first device in the model monitoring; wherein the first capacity information comprises at least one of the following: whether it must support a mode of allocating a monitoring resource based on numbering information; whether it must support a mode of allocating a periodic monitoring resource based on numbering information; whether it must support a mode of allocating a first monitoring resource based on numbering information; whether it must support a mode of allocating a second monitoring resource based on numbering information;whether it should support an allocation mode for an aperiodic monitoring resource based on numbering information; whether it should support an allocation mode for a third monitoring resource based on numbering information; whether it should support an allocation mode for a fourth monitoring resource based on numbering information; whether it should support an allocation mode for a monitoring resource based on independent configuration of monitoring resources; or a supported monitoring resource allocation mode where the first monitoring resource is a periodic monitoring resource and any resource repetition period within the periodic monitoring resource comprises a plurality of monitoring time windows; the second monitoring resource is the periodic monitoring resource and any resource repetition period within the periodic monitoring resource comprises a monitoring time window;The third monitoring resource is an aperiodic monitoring resource, and any aperiodic monitoring resource comprises a plurality of monitoring time windows; and the fourth monitoring resource is the aperiodic monitoring resource, and any aperiodic monitoring resource comprises a monitoring time window.

13. METHOD, according to claim 11 or 12, characterized in that the first device and the second device meet one of the following configurations: the first device is a terminal device and the second device is a network device; or the first device is a network device and the second device is a terminal device; or both the first device and the second device are network devices; or both the first device and the second device are terminal devices.

14. FIRST DEVICE characterized by comprising: a processor; and a memory configured to store an instruction executable by the processor, wherein the processor is configured to load and execute the executable instruction to cause the first device to implement the information determination method, as defined in any one of claims 1 to 10.

15. SECOND DEVICE characterized by comprising: a processor; and a memory configured to store an instruction executable by the processor, wherein the processor is configured to load and execute the executable instruction to cause the second device to implement the information transmission method as defined in any one of claims 11 to 13.

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