Communication method, communication device, communication system, storage medium, and program product

Abstract

A communication method, a communication device, a communication system, a storage medium, and a program product. The method comprises: on the basis of a trigger waiting duration of a measurement reporting event, determining whether to use a first function and / or a first model for prediction. A terminal autonomously determines, on the basis of a trigger waiting duration of a measurement reporting event, whether to use a first function and / or a first model for prediction, without frequent interaction with a network, thereby reducing the energy consumption of the terminal and reducing the consumption of radio resources.

Description

Communication methods, communication equipment, communication systems, storage media and software products Technical Field

[0001] This disclosure relates to the field of communication technology, and in particular to a communication method, communication device, communication system, storage medium, and program product. Background Technology

[0002] In wireless communication networks, artificial intelligence (AI) can be used for prediction and reasoning to improve system performance. Training AI models requires collecting a large amount of data, and the data required varies depending on the application scenario. Application scenarios can include beam management, channel state information (CSI) reporting, CSI compression, positioning, handover, mobility management, and radio resource management. Summary of the Invention

[0003] This disclosure provides a communication method, communication device, communication system, storage medium, and program product.

[0004] According to a first aspect of the embodiments of this disclosure, a communication method is provided, executed by a terminal, the method comprising:

[0005] Based on the trigger waiting time of the measured reported event, determine whether to use the first function and / or the first model for prediction.

[0006] According to a second aspect of the present disclosure, a communication device is provided that can be used to perform the method described in an optional implementation of the first aspect.

[0007] According to a third aspect of the present disclosure, a communication system is provided, including a terminal and a network device, wherein the terminal is configured to perform the method described in an optional implementation of the first aspect.

[0008] According to a fourth aspect of the present disclosure, a storage medium is provided that stores instructions which, when executed on a communication device, cause the communication device to perform the method as described in an optional implementation of the first aspect.

[0009] According to a fifth aspect of the present disclosure, a program product is provided, including at least one of a program and instructions, wherein the program and instructions, when executed by a communication device, implement the method described in the optional implementation of the first aspect.

[0010] The technical solution provided in this disclosure can produce the following beneficial effects: the terminal determines whether to use the first function and / or the first model for prediction based on the trigger waiting time of the measurement reporting event. The terminal autonomously determines whether to use the first function and / or the first model for prediction based on the trigger waiting time of the measurement reporting event, without frequent interaction with the network, thereby reducing the terminal's energy consumption and minimizing the consumption of wireless resources.

[0011] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit this disclosure. Attached Figure Description

[0012] To more clearly illustrate the technical solutions in the embodiments of this disclosure, the accompanying drawings required for the description of the embodiments are introduced below. The following drawings are only some embodiments of this disclosure and do not impose specific limitations on the protection scope of this disclosure.

[0013] Figure 1A is a schematic diagram of the architecture of a communication system according to an embodiment of the present disclosure.

[0014] Figure 1B is a schematic diagram illustrating a measurement configuration according to an embodiment of the present disclosure.

[0015] Figure 2A is a flowchart illustrating a communication method according to an embodiment of the present disclosure.

[0016] Figure 2B is a schematic diagram illustrating a trigger waiting time according to an embodiment of the present disclosure.

[0017] Figure 2C is a flowchart illustrating a communication method according to an embodiment of the present disclosure.

[0018] Figure 2D is a flowchart illustrating a communication method according to an embodiment of the present disclosure.

[0019] Figure 3 is a schematic diagram of the structure of a terminal proposed in an embodiment of this disclosure.

[0020] Figure 4A is a schematic diagram of the structure of the communication device proposed in an embodiment of this disclosure.

[0021] Figure 4B is a schematic diagram of the chip structure proposed in an embodiment of this disclosure. Detailed Implementation

[0022] This disclosure provides a communication method, communication device, communication system, storage medium, and program product.

[0023] In a first aspect, embodiments of this disclosure provide a communication method executed by a terminal, the method comprising:

[0024] Based on the trigger waiting time of the measured reported event, determine whether to use the first function and / or the first model for prediction.

[0025] In the above embodiments, the terminal autonomously determines whether to use the first function and / or the first model for prediction based on the trigger waiting time of the measurement and reporting event, without having to frequently interact with the network, thereby reducing the terminal's power consumption and the consumption of wireless resources.

[0026] In conjunction with some embodiments of the first aspect, in some embodiments, determining whether to use the first function and / or the first model for prediction based on the triggering wait time of the measured reported event includes:

[0027] If the trigger waiting time is greater than or equal to the first time, and the remaining trigger waiting time is less than or equal to the first time, then it is determined that the first function and / or the first model will be used for prediction; or,

[0028] If the trigger waiting time is less than the first time, it is determined that the first function and / or the first model will be used for prediction.

[0029] In the above embodiments, by dynamically judging the trigger waiting time and / or the remaining trigger waiting time, it is determined whether to use the first function and / or the first model for prediction, so as to ensure that the prediction mechanism is activated in a timely manner when the trigger waiting time is close to the trigger threshold or the trigger waiting time itself is short, thereby improving the timeliness and accuracy of event triggering.

[0030] In conjunction with some embodiments of the first aspect, in some embodiments, the first duration is at least one of the following:

[0031] Network configuration duration;

[0032] The duration of the prediction window during which the first function and / or the first model makes predictions;

[0033] The first function and / or the first model can predict the duration of measurement results or measurement reporting events.

[0034] In the above embodiments, by flexibly configuring the first duration, the rationality and applicability of triggering measurement reporting events are improved.

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

[0036] Based on the first association relationship, the first function and / or the first model determines the first duration; wherein, the first association relationship includes the correspondence between different first functions and / or different first models and the first duration, the first association relationship is provided by a network or server, and the server is a node used to train the first function and / or the first model.

[0037] In the above embodiments, by predefining the association between the first function and / or the first model and the first duration, the first duration can be determined based on the first function and / or the first model. This provides a more accurate and suitable duration standard for determining whether to use the first function and / or the first model for prediction based on the trigger waiting time of the measured reported event, thereby further improving the timeliness and accuracy of event triggering.

[0038] In conjunction with some embodiments of the first aspect, in some embodiments, determining whether to use the first function and / or the first model for prediction based on the triggering wait time of the measured reported event includes:

[0039] Based on the trigger waiting time of the measurement and reporting event and a first condition, determine whether to use the first function and / or the first model for prediction; wherein, the first condition includes conditions that control the first function and / or the first model to make predictions.

[0040] In the above embodiments, the terminal combines the triggering waiting time of the measurement and reporting event with the first condition to make a decision on whether to use the first function and / or the first model, thereby further improving the timeliness and accuracy of event triggering.

[0041] In conjunction with some embodiments of the first aspect, in some embodiments, the method further includes:

[0042] Based on the second association relationship, the first function and / or the first model determine the measurement reporting configuration; wherein, the second association relationship includes the correspondence between different first functions and / or different first models and the measurement reporting configuration;

[0043] The triggering wait time for the measurement reporting event is determined based on the measurement reporting configuration.

[0044] In the above embodiments, by predefining the association between the first function and / or the first model and the measurement reporting configuration, the measurement reporting configuration can be determined based on the first function and / or the first model, thereby determining the trigger waiting time for the measurement reporting event. This allows the setting of the trigger waiting time to adapt to the needs of a specific function or model, further improving the timeliness and accuracy of event triggering.

[0045] In conjunction with some embodiments of the first aspect, in some embodiments, the measurement reporting configuration includes at least one of the following: a measurement index identifier and a reporting configuration index identifier.

[0046] In the above embodiments, by including at least one of the measurement index identifier and the reporting configuration index identifier in the measurement reporting configuration, the measurement reporting process can be more accurately adapted to the requirements of network needs or prediction functions, thereby further improving the accuracy of event triggering.

[0047] In conjunction with some embodiments of the first aspect, in some embodiments, the trigger waiting time for the measurement reporting event has already begun timing.

[0048] In the above embodiments, after the terminal triggers the start of the waiting time, it dynamically triggers a prediction mechanism based on the real-time running status to ensure the timeliness of event triggering and reduce the risk of misjudgment, while also reducing the redundant consumption of network resources.

[0049] In conjunction with some embodiments of the first aspect, in some embodiments, the method further includes:

[0050] If the timing of the trigger wait time for the measurement reporting event stops, the use of the first function and / or the first model for prediction shall cease.

[0051] In the above embodiments, the operation of the first function and / or the first model is terminated after the trigger waiting time is stopped, so as to avoid the consumption of redundant computing resources, ensure the real-time synchronization of prediction behavior and event triggering state, and thus improve the utilization of network resources.

[0052] In conjunction with some embodiments of the first aspect, in some embodiments, the first function and / or the first model includes at least one of the following:

[0053] The network indicates the activation of artificial intelligence (AI) functions and / or AI models;

[0054] Currently available AI features and / or AI models.

[0055] In the above embodiments, prediction is made by calling the network to specify activated or currently available AI functions / AI models, thereby achieving flexible adaptation of AI resources, improving prediction accuracy and reducing computational redundancy.

[0056] In conjunction with some embodiments of the first aspect, in some embodiments, the first function and / or the first model is used for at least one of the following:

[0057] Predict cell or beam measurement results;

[0058] Predict whether the reported events meet the reporting conditions.

[0059] In the above embodiments, by predicting cell / beam measurement results or event triggering conditions in real time, changes in network status can be anticipated in advance, thereby reducing measurement reporting delay and improving network performance.

[0060] In a second aspect, embodiments of this disclosure provide a terminal that may include at least one of a transceiver module and a processing module; wherein the terminal may be used to execute an optional implementation of the first aspect.

[0061] Thirdly, embodiments of this disclosure provide a terminal that may include one or more processors; wherein the terminal may be used to execute an optional implementation of the first aspect.

[0062] Fourthly, embodiments of this disclosure provide a communication system that may include a terminal and a network device; wherein the terminal is configured to perform the method described in the optional implementation of the first aspect.

[0063] Fifthly, embodiments of this disclosure provide a storage medium storing instructions that, when executed on a communication device, cause the communication device to perform the method described in the optional implementation of the first aspect.

[0064] In a sixth aspect, embodiments of this disclosure provide a program product that, when executed by a communication device, causes the communication device to perform the method as described in the optional implementation of the first aspect.

[0065] In a seventh aspect, embodiments of this disclosure provide a computer program that, when run on a computer, causes the computer to perform the method as described in an alternative implementation of the first aspect.

[0066] Eighthly, embodiments of this disclosure provide a chip or chip system. The chip or chip system includes processing circuitry configured to perform the methods described in the alternative implementations of the first aspect.

[0067] It is understood that the aforementioned terminals, network devices, communication devices, communication systems, storage media, program products, computer programs, chips, or chip systems can all be used to execute the methods proposed in the embodiments of this disclosure. Therefore, the beneficial effects that can be achieved can be referred to the beneficial effects in the corresponding methods, and will not be repeated here.

[0068] This disclosure provides a communication method, communication device, communication system, storage medium, and program product. In some embodiments, the terms "information transmission method" and "information processing method," "communication method," etc., can be used interchangeably; the terms "information transmission device" and "information processing device," "communication device," "communication equipment," etc., can be used interchangeably; and the terms "information processing system," "communication system," etc., can be used interchangeably.

[0069] This disclosure is not exhaustive, but merely illustrative of some embodiments, and is not intended to limit the scope of protection of this disclosure. Unless otherwise specified, each step in a particular embodiment can be implemented as an independent embodiment, and the steps can be arbitrarily combined. For example, a solution after removing some steps in a particular embodiment can also be implemented as an independent embodiment, and the order of the steps in a particular embodiment can be arbitrarily interchanged. Furthermore, the optional implementation methods in a particular embodiment can be arbitrarily combined; moreover, the embodiments can be arbitrarily combined, for example, some or all steps of different embodiments can be arbitrarily combined, and a particular embodiment can be arbitrarily combined with the optional implementation methods of other embodiments.

[0070] In each of the disclosed embodiments, unless otherwise specified or in case of logical conflict, the terminology and / or descriptions of the embodiments are consistent and can be referenced by each other. Technical features in different embodiments can be combined to form new embodiments based on their inherent logical relationships.

[0071] The terminology used in the embodiments of this disclosure is for the purpose of describing particular embodiments only and is not intended to limit the scope of this disclosure.

[0072] In this embodiment of the disclosure, unless otherwise stated, elements expressed in the singular form, such as "a," "an," "the," "the," "the," "the," "the," "the," "this," etc., can mean "one and only one," or "one or more," "at least one," etc. For example, when using articles such as "a," "an," "the," etc. in translation, the noun following the article can be understood as either a singular expression or a plural expression.

[0073] In some embodiments, "multiple" can refer to two or more.

[0074] In some embodiments, the terms “at least one of”, “one or more”, “a plurality of”, “multiple”, etc., may be used interchangeably.

[0075] In some embodiments, the notation "at least one of A and B", "A and / or B", "A in one case, B in another", "in response to one case A, in response to another case B", etc., may include the following technical solutions depending on the situation: in some embodiments, A (execute A regardless of B); in some embodiments, B (execute B regardless of A); in some embodiments, execution is selected from A and B (A and B are selectively executed); in some embodiments, A and B (both A and B are executed). The same applies when there are more branches such as A, B, C, etc.

[0076] In some embodiments, the notation "A or B" may include the following technical solutions, depending on the situation: in some embodiments, A (execution of A regardless of B); in some embodiments, B (execution of B regardless of A); in some embodiments, execution is selected from A and B (A and B are selectively executed). The same applies when there are more branches such as A, B, C, etc.

[0077] The prefixes "first," "second," etc., used in the embodiments of this disclosure are merely for distinguishing different descriptive objects and do not impose restrictions on the position, order, priority, quantity, or content of the descriptive objects. The description of the descriptive objects is found in the claims or the context of the embodiments, and the use of prefixes should not constitute unnecessary restrictions. For example, if the descriptive object is a "field," the ordinal numbers preceding "field" in "first field" and "second field" do not restrict the position or order of the "fields." "First" and "second" do not restrict whether the "fields" they modify are in the same message, nor do they restrict the order of "first field" and "second field." Similarly, if the descriptive object is a "level," the ordinal numbers preceding "level" in "first level" and "second level" do not restrict the priority between "levels." Furthermore, the number of descriptive objects is not limited by ordinal numbers and can be one or more. For example, in "first device," the number of "devices" can be one or more. Furthermore, the objects modified by different prefixes can be the same or different. For example, if the object being described is "device", then "first device" and "second device" can be the same device or different devices, and their types can be the same or different. Similarly, if the object being described is "information", then "first information" and "second information" can be the same information or different information, and their content can be the same or different.

[0078] In some embodiments, “including A,” “containing A,” “for indicating A,” and “carrying A” can be interpreted as directly carrying A or indirectly indicating A.

[0079] In some embodiments, the terms “in response to…”, “in response to determining…”, “in the case of…”, “when…”, “if…”, “if…”, etc., can be used interchangeably.

[0080] In some embodiments, the terms “greater than,” “greater than or equal to,” “not less than,” “more than,” “more than or equal to,” “not less than,” “higher than,” “higher than or equal to,” “not lower than,” and “above” can be used interchangeably, as can the terms “less than,” “less than or equal to,” “not greater than,” “less than,” “less than or equal to,” “not more than,” “lower than,” “lower than or equal to,” “not higher than,” and “below”.

[0081] In some embodiments, devices, etc., may be interpreted as physical or virtual, and their names are not limited to those described in the embodiments. Terms such as “device,” “equipment,” “circuit,” “network element,” “node,” “function,” “unit,” “section,” “system,” “network,” “chip,” “chip system,” “entity,” and “subject” are interchangeable.

[0082] In some embodiments, "network" can be interpreted as devices included in a network (e.g., access network devices, core network devices, etc.).

[0083] In some embodiments, the terms "Access Network Device (AN Device)," "Radio Access Network Device (RAN Device)," "Base Station (BS)," "Radio Base Station," "Fixed Station," "Node," "Access Point," "Transmission Point (TP)," "Reception Point (RP)," "Transmission / Reception Point (TRP)," "Panel," "Antenna Panel," "Antenna Array," "Cell," "Macro Cell," "Small Cell," "Femto Cell," "Pico Cell," "Sector," "Cell Group," "Serving Cell," "Carrier," "Component Carrier," and "Bandwidth Part (BWP)" can be used interchangeably.

[0084] In some embodiments, the terms "terminal", "terminal device", "user equipment (UE)", "user terminal", "mobile station (MS)", "mobile terminal (MT)", "subscriber station", "mobile unit", "subscriber unit", "wireless unit", "remote unit", "mobile device", "wireless device", "wireless communication device", "remote device", "mobile subscriber station", "access terminal", "mobile terminal", "wireless terminal", "remote terminal", "handset", "user agent", "mobile client", and "client" can be used interchangeably.

[0085] In some embodiments, access network devices, core network devices, or network devices can be replaced with terminals. For example, embodiments of this disclosure can also be applied to structures where communication between access network devices, core network devices, or network devices and terminals is replaced with communication between multiple terminals (e.g., device-to-device (D2D), vehicle-to-everything (V2X), etc.). In this case, the structure can also be configured such that the terminal has all or part of the functions of the access network device. Furthermore, terms such as "uplink" and "downlink" can be replaced with terms corresponding to communication between terminals (e.g., "sidelink"). For example, uplink channel, downlink channel, etc., can be replaced with sidelink channel or direct channel, and uplink link, downlink, etc., can be replaced with sidelink link or direct link.

[0086] In some embodiments, the terminal may be replaced by an access network device, a core network device, or a network device. In this case, the access network device, core network device, or network device may also be configured to have all or some of the functions of the terminal.

[0087] In some embodiments, the acquisition of data, information, etc., may comply with the laws and regulations of the country where the location is situated.

[0088] In some embodiments, data, information, etc., may be obtained with the user's consent.

[0089] Furthermore, each element, each row, or each column in the table of this disclosure can be implemented as an independent embodiment, and any combination of any element, any row, or any column can also be implemented as an independent embodiment.

[0090] Figure 1A is a schematic diagram of the architecture of a communication system according to an embodiment of the present disclosure. As shown in Figure 1A, the communication system 100 may include a terminal 101 and a network device 102.

[0091] In some embodiments, terminal 101 may include at least one of the following: mobile phone, wearable device, Internet of Things device, car with communication function, smart car, tablet computer, computer with wireless transceiver function, virtual reality (VR) terminal device, augmented reality (AR) terminal device, wireless terminal device in industrial control, wireless terminal device in self-driving, wireless terminal device in remote medical surgery, wireless terminal device in smart grid, wireless terminal device in transportation safety, wireless terminal device in smart city, and wireless terminal device in smart home, but is not limited thereto.

[0092] In some embodiments, network device 102 may include at least one of access network device and core network device.

[0093] In some embodiments, the access network device may be a node or device that connects a terminal device to a wireless network. The access network device may include, but is not limited to, at least one of the following in a 5G communication system: evolved Node B (eNB), next-generation eNB (ng-eNB), next-generation Node B (gNB), node B (NB), home node B (HNB), home evolved node B (HeNB), radio backhaul device, radio network controller (RNC), base station controller (BSC), base transceiver station (BTS), base band unit (BBU), mobile switching center, base station in a 6G communication system, open RAN, cloud RAN, base station in other communication systems, and access node in a Wi-Fi system.

[0094] In some embodiments, the technical solutions of this disclosure can be applied to the Open RAN architecture. In this case, the interfaces between or within access network devices involved in the embodiments of this disclosure can be transformed into internal interfaces of Open RAN. The processes and information interactions between these internal interfaces can be implemented by software or programs.

[0095] In some embodiments, the access network device may be composed of a central unit (CU) and a distributed unit (DU). The CU may also be called a control unit. The CU-DU structure can separate the protocol layer of the access network device. Some protocol layer functions are centrally controlled by the CU, while the remaining part or all protocol layer functions are distributed in the DU and centrally controlled by the CU. However, this is not the only possibility.

[0096] In some embodiments, the core network equipment may be a single device, multiple devices, or a group of devices. The core network may include at least one of the following: Evolved Packet Core (EPC), 5G Core Network (5GCN), and Next Generation Core (NGC).

[0097] It is understood that the communication system described in this disclosure is for the purpose of more clearly illustrating the technical solutions of this disclosure, and does not constitute a limitation on the technical solutions proposed in this disclosure. As those skilled in the art will know, with the evolution of system architecture and the emergence of new business scenarios, the technical solutions proposed in this disclosure are also applicable to similar technical problems.

[0098] The following embodiments of this disclosure can be applied to the communication system 100 shown in FIG1A, or to some of the main bodies, but are not limited thereto. The main bodies shown in FIG1A are examples. The communication system may include all or some of the main bodies in FIG1A, or it may include other main bodies outside of FIG1A. The number and form of each main body are arbitrary. Each main body may be physical or virtual. The connection relationship between the main bodies is an example. The main bodies may not be connected or may be connected. The connection can be in any way, it can be a direct connection or an indirect connection, it can be a wired connection or a wireless connection.

[0099] The embodiments disclosed herein can be applied to Long Term Evolution (LTE), LTE-Advanced (LTE-A), LTE-Beyond (LTE-B), SUPER 3G, IMT-Advanced, 4th generation mobile communication system (4G), 5th generation mobile communication system (5G), 5G New Radio (NR), Future Radio Access (FRA), New-Radio Access Technology (RAT), New Radio (NR), New Radio Access (NX), Future generation radio access (FX), Global System for Mobile communications (GSM), CDMA2000, Ultra Mobile Broadband (UMB), IEEE 802.11 (Wi-Fi), IEEE 802.16 (WiMAX), and IEEE 802.20, Ultra-Wideband (UWB), Bluetooth (a registered trademark), Public Land Mobile Network (PLMN) networks, Device-to-Device (D2D) systems, Machine-to-Machine (M2M) systems, Internet of Things (IoT) systems, Vehicle-to-Everything (V2X) systems, systems utilizing other communication methods, and next-generation systems built upon them, etc. Furthermore, multiple systems can be combined (e.g., a combination of LTE or LTE-A with 5G).

[0100] In some embodiments of this disclosure, during beam management, the UE can reduce the number of beams measured, and the UE or base station can obtain the optimal beam through AI inference. Beam prediction includes spatial beam prediction and temporal beam prediction. In spatial beam prediction, the UE measures a small number of beams and predicts the measurement results of other beams. In temporal beam prediction, the UE predicts future beam measurement results based on historical beam measurement results.

[0101] During CSI reporting, the UE can compress CSI measurement results using AI and report the compressed CSI measurement results to the base station. The base station then uses AI to reconstruct the original CSI measurement results. This reduces the number of signaling bits required during the reporting process. The base station can also predict future CSI based on historical CSI measurement results reported by the UE.

[0102] During mobility management (i.e., handover), the UE can predict cell measurement results, the target cell for handover, or mobility events. The UE's ability to predict future cell measurement results can be termed temporal prediction. Alternatively, by measuring a subset of cells (cell set A), the UE can predict the measurement results of unmeasured cells (cell set B), which can be termed spatial prediction. Mobility events include the fulfillment of measurement reporting conditions, handover failure, cell dwell time, and radio link failure.

[0103] In some embodiments, AI can be used to predict measurements of cells or beams.

[0104] In some embodiments, in time-domain prediction, historical measurement results are used as input, and the AI ​​outputs future measurement results.

[0105] In some embodiments, the UE continuously performs measurements and predicts future measurement results at each moment. Handover preparation can be triggered in advance or handover can be avoided based on future measurement results, thereby improving mobility performance. Triggering handover preparation in advance can reduce handover failures, while avoiding handover can reduce service interruptions. Figure 1B is a schematic diagram of a measurement configuration according to an embodiment of this disclosure. As shown in Figure 1B, at the moment corresponding to the white square, the UE obtains the measurement result through measurement; at the moment corresponding to the black square, the UE obtains the measurement result through prediction. OW is the observation window, and the measurement values ​​within the observation window serve as the input to AI. PW is the prediction window, and the measurement values ​​within the prediction window are obtained through AI.

[0106] In some embodiments, the UE performs measurements according to the network configuration, which includes a measurement object, a report configuration, and a quantity configuration.

[0107] In some embodiments, the measurement object indicates the frequency to be measured and may include various access technologies, including NR and LTE. Each measurement object is bound to a measurement object index identifier (measObject ID).

[0108] In some embodiments, the network may also indicate a list of cells that can be measured, and the UE will only measure cells in the list. The network may also indicate a list of cells that must be blocked, and the UE will not measure cells in the list.

[0109] In some embodiments, the reporting configuration indicates the type of UE reporting, including periodic reporting and event-based reporting. It carries a reporting timer configuration for triggering measurement reporting; the reporting timers include T321, T322, and TimerToTrigger (TTT). Different reporting configurations can be used for measurement objects of different access technologies, and each reporting configuration is bound to a reporting configuration index identifier (reportconfig ID).

[0110] In some embodiments, the event-based reporting configuration provides the following configuration:

[0111] The signal type that triggers the reporting includes RSRP, RSRQ, or SINR;

[0112] Threshold or bias;

[0113] The reported measurement result types include RSRP, RSRQ, or SINR.

[0114] In some embodiments, the UE compares the relationship between signal measurement results of the serving cell or neighboring cells or the relationship with a threshold. If the threshold requirement is met, the measurement result is reported.

[0115] In some embodiments, event-based measurement reporting includes A1-A6, B1-B2, D1, T1, etc. The A-series events are used for intra-system mobility management, and the B-series events are used for inter-system mobility management. D1 and T1 are used for satellite system mobility management. The A-series reported events are shown below:

[0116] Event A1: The signal quality of the serving cell is higher than the absolute threshold;

[0117] Event A2: The signal quality of the serving cell is below the absolute threshold;

[0118] Event A3: The signal quality of the neighboring cell is one offset value higher than that of PCell / PSCell;

[0119] Event A4: The signal quality of the neighboring cell is higher than the absolute threshold;

[0120] Event A5: The signal quality of PCell / PSCell is below threshold 1, and the signal quality of neighboring cells / SCell is above threshold 2;

[0121] Event A6: The signal quality of the neighboring cell is one offset value higher than that of SCell.

[0122] In some embodiments, entry and exit conditions are defined for each event. For a cell that does not meet the measurement reporting conditions, the UE evaluates the cell's entry conditions. For a cell that has already triggered measurement reporting, the UE evaluates the cell's exit conditions. Measurement reporting can be triggered when the entry conditions are met, or when the entry conditions are met continuously during the TTT (Time To Watch) period.

[0123] In some embodiments, the network configures a measurement index identifier (meas id), a reporting configuration index identifier (reportconfigID), and a measurement object index identifier (MeasObjectID) for the UE. By combining the measurement object identifier and the reporting configuration identifier using the measurement index identifier, the UE can determine the reporting method for the measurement object and use the measurement results of the measurement object to evaluate the reporting event and report the measurement results. The UE stores the network-configured measurement index identifier in a local variable (VarMeasConfig). If the reporting configuration corresponding to the measurement index identifier is triggered, the UE stores the measurement index identifier that triggered the measurement reporting and the reporting information in a local variable (VarMeasReportList). The reporting information includes the number of reports, the cell identifier that triggered the measurement reporting, and the measurement identifier that was triggered to report.

[0124] In some embodiments, AI can be used to predict whether the measurement reporting event is met, thus enabling early preparation for switching and improving switching performance.

[0125] In some embodiments, there are two methods for predicting measurement reporting events: direct prediction and indirect prediction. In direct prediction, the AI ​​directly outputs the time or time window at which the measurement reporting event will be satisfied; alternatively, it can also output the probability that the measurement reporting event will be satisfied. In indirect prediction, the AI ​​first outputs the channel measurement results within the PW (Power Window), and then uses the channel measurement results to determine at what time the measurement reporting event will be satisfied.

[0126] In some embodiments, the use and inference of AI may require multiple AI models or AI functions for inference and prediction. An AI function implements a specific purpose and may include one or more AI models. This purpose may be indicated by a specific wireless resource configuration.

[0127] In some embodiments, the management of an AI model or function includes activating, deactivating, and switching the AI ​​model or function.

[0128] In some embodiments, the inference of an AI model or function can run on either the UE side or the network side. Even when the AI ​​model or function runs on the UE side, it still requires the activation of network control functions for activation and switching.

[0129] In some embodiments, the AI ​​model or function can achieve better performance under specific application conditions, which can be divided into network-side conditions and UE-side conditions.

[0130] In some embodiments, the conditions on the UE side may include:

[0131] UE speed;

[0132] Battery level;

[0133] power;

[0134] Computing power can be measured by the number of floating point operations per second (FLOPs).

[0135] Location can refer to a geographical location or a location within a residential area;

[0136] The business type can be audio, video, multimedia, voice, etc.;

[0137] Antenna configuration, including the number of ports;

[0138] Rotational speed;

[0139] Storage space can be measured in bits.

[0140] In some embodiments, network-side conditions may include:

[0141] Community types, such as macro, micro, and dense urban communities;

[0142] Network deployment scenarios, such as indoors and outdoors;

[0143] Wireless channel quality can be determined using RSRP, RSRQ, or SINR.

[0144] The frequency of the cell;

[0145] Location of the residential area;

[0146] Distance between base stations;

[0147] Antenna configuration, including the number of ports and the number of Multiple Input Multiple Output (MIMO) layers;

[0148] Transmission power;

[0149] Numerology.

[0150] In some embodiments, network-side conditions can be bound to an ID, with the network indicating the network-side conditions by providing the ID. The UE does not know which specific network-side conditions the ID represents. When the UE uses AI for inference, it determines whether the current network-indicated ID is consistent with the network ID used when collecting AI function / model training data. If they are inconsistent, it determines that the current AI function / model does not meet the network-side conditions.

[0151] In some embodiments, an AI function is considered applicable when it can begin inference and prediction. The UE can report applicable functions, and the network selects an AI function from among them for management. The UE determines whether an AI function is applicable based on the following conditions: an applicable AI model has been obtained, the network conditions for the AI ​​model are met, and the UE conditions are met. When all three conditions are met, the corresponding AI function is determined to be applicable.

[0152] In some embodiments, during mobility management, event and measurement result prediction, energy consumption caused by UE prediction should be minimized. UEs should initiate AI prediction at the cell edge, as handover typically occurs at the cell edge. Currently, the activation of AI models or functions is controlled by the network. To enable the network to reasonably activate UE prediction, UEs need to report their location or channel measurement results, which increases UE energy consumption and additionally consumes radio resources.

[0153] Figure 2A is a flowchart illustrating a communication method according to an embodiment of the present disclosure. This method can be executed by the aforementioned terminal. As shown in Figure 2A, the method may include:

[0154] Step S2101: Determine the first duration based on the first association, the first function, and / or the first model.

[0155] In some embodiments, the first function and / or the first model may include at least one of the following:

[0156] The network indicates the activation of AI functions and / or AI models;

[0157] Currently available AI features and / or AI models.

[0158] In some embodiments, the first function may be a network-indicated activated AI function, and the first model may be a network-indicated activated AI model.

[0159] In some embodiments, the first function may be a currently available AI function, and the first model may be a currently available AI model.

[0160] In some embodiments, the first duration may be the duration of prediction using a first feature and / or a first model.

[0161] In some embodiments, the first duration is at least one of the following:

[0162] Network configuration duration;

[0163] The duration of the prediction window for the first function and / or the first model to make predictions;

[0164] The first function and / or the first model can predict the duration of measurement results or measurement reporting events.

[0165] In some embodiments, the network may indicate or configure the first duration.

[0166] In some embodiments, the prediction window can be a time window used for prediction by the first function and / or the first model. As shown in Figure 1B, PW is the prediction window, and the first duration can be the duration corresponding to PW.

[0167] In some embodiments, a first function and / or a first model can predict future measurement results or measurement reporting events, and the first duration can be the duration during which the first function and / or the first model can predict the measurement results or measurement reporting events.

[0168] In some embodiments, the duration for which the first function and / or the first model can predict the measurement result or measurement reporting event can be understood as the maximum time range for which the first function and / or the first model can predict the measurement result or measurement reporting event, or the furthest time for which the first function and / or the first model can effectively predict the measurement result or measurement reporting event, or the maximum time range for which the measurement or measurement reporting event predicted by the first function and / or the first model can meet the reliability requirements.

[0169] For example, if the first function and / or the first model can predict the measurement result or measurement reporting event within the next 5 seconds, then the first duration is 5 seconds.

[0170] In some embodiments, the application scenarios of different first functions and / or different first models may be different, and the duration for which the first functions and / or first models in different application scenarios can predict measurement results or measurement reporting events may be different, that is, the first time corresponding to different first functions and / or different first models is different.

[0171] In some embodiments, the first function and / or the first model is used for at least one of the following:

[0172] Predict cell or beam measurement results;

[0173] Predict whether the reported events meet the reporting conditions.

[0174] For example, if the first function and / or the first model is used to predict cell measurement results, the first duration corresponding to the first function and / or the first model is t1; if the first function and / or the first model is used to predict beam measurement results, the first duration corresponding to the first function and / or the first model is t2; if the first function and / or the first model is used to predict whether the measurement reporting event meets the reporting conditions, the first duration corresponding to the first function and / or the first model is t3.

[0175] In some embodiments, the first association relationship includes the correspondence between different first functions and / or different first models and first durations. For example, the first association relationship includes the correspondence between different first functions and first durations; as another example, the first association relationship includes the correspondence between different first models and first durations.

[0176] In some embodiments, the first association may be provided by a network or a server. For example, the network or server may instruct or configure the first association.

[0177] In some embodiments, the server may be a node used to train a first feature and / or a first model.

[0178] In some embodiments, before determining whether to use the first function and / or the first model for prediction, the terminal may determine the first duration corresponding to the first function and / or the first model based on the first association. For example, if the first function and / or the first model is used to predict whether the measurement reporting event meets the reporting conditions, the first duration is determined to be t3.

[0179] It should be noted that the terminal may also obtain the first duration through other methods of related technologies, such as network or higher-level instructions, in which case step S2101 can be omitted.

[0180] Step S2102: Based on the second association relationship, the first function and / or the first model determine the measurement reporting configuration.

[0181] In some embodiments, the measurement reporting configuration may include at least one of the following: measurement index identifier (meas id) and reporting configuration index identifier (reportconfigID).

[0182] In some embodiments, the measurement index identifier is an index value that identifies a measurement task and is used to distinguish different measurement tasks performed by the terminal.

[0183] In some embodiments, a measurement index identifier can be bound to a measurement object and a reporting configuration. Each measurement task can be assigned a measurement index identifier, and the terminal can determine the corresponding measurement and reporting process based on the measurement index identifier. For example, the measurement index identifier is 1, the measurement object is a synchronous measurement, the associated reporting configuration is an A3 event, and the trigger waiting time is 320ms.

[0184] In some embodiments, the reporting configuration index identifier is an index value that identifies a reporting configuration and is used to define the triggering conditions for measurement reporting, such as event type, trigger wait time, threshold, etc. For example, the reporting configuration index identifier is 101, the triggering condition is event A3, and the trigger wait time is 320ms.

[0185] In some embodiments, different reporting configurations can be used for measurement objects of different access technologies, and each reporting configuration can be bound to a reporting configuration index identifier.

[0186] In some embodiments, the reporting configuration can also be used to indicate the type of reporting by the terminal. For example, the reporting configuration may include periodic reporting and event-based reporting. The reporting configuration may carry a reporting timer configuration for triggering measurement reporting, wherein the reporting timer may be a TimerToTrigger (trigger timer).

[0187] In some embodiments, the terminal can match the current measurement task according to the measurement index identifier and report the measurement results according to the reporting rules corresponding to the reporting configuration identifier.

[0188] In some embodiments, the application scenarios of different first functions and / or different first models may be different, the measurement objects of the first functions and / or first models in different application scenarios are different, and the reporting configurations corresponding to different measurement objects are different. That is to say, the measurement reporting configurations corresponding to different first functions and / or different first models are different.

[0189] In some embodiments, the second association may include a correspondence between different first functions and / or different first models and measurement reporting configurations.

[0190] In some embodiments, the second association may be network-configured.

[0191] In some embodiments, before determining whether to use the first function and / or the first model for prediction, the terminal may determine the measurement reporting configuration corresponding to the first function and / or the first model based on the second association.

[0192] It should be noted that the terminal can also obtain the measurement reporting configuration through other methods of related technologies, such as network or higher-level instructions, in which case step S2102 can be omitted.

[0193] Step S2103: Determine the trigger waiting time for the measurement reporting event based on the measurement reporting configuration.

[0194] In some embodiments, the trigger wait time is used to trigger a measurement reporting event.

[0195] In some embodiments, the trigger wait time is the wait time between the time when the reported event meets the triggering condition and the time when the reporting action is triggered.

[0196] In some embodiments, the trigger waiting time can be understood as the duration of continuous monitoring of trigger conditions before a measurement reporting event is triggered, or the duration of waiting before a measurement reporting event is triggered. For example, after a measurement reporting event meets the trigger conditions, it needs to be continuously monitored for a period of time. If the measurement reporting event always meets the conditions during this period, the measurement reporting is triggered, and the period of continuous monitoring is the trigger waiting time.

[0197] In some embodiments, the trigger waiting duration can be controlled by a timer, such as a TTT timer. The duration of the TTT timer can be configured to be the trigger waiting duration, which is the entire time period from the start to the end of the TTT timer.

[0198] In some embodiments, the trigger waiting duration may also be referred to as "trigger waiting time", "trigger time", "trigger monitoring duration", "trigger continuous monitoring time", "TTT duration", etc.

[0199] In some embodiments, after the terminal determines the measurement reporting configuration, it can determine the triggering waiting time for the measurement reporting event based on the measurement reporting configuration.

[0200] In some embodiments, if the measurement reporting configuration includes a reporting configuration index identifier, the terminal can determine the trigger waiting time for the measurement reporting event based on the reporting configuration indicated by the reporting configuration index identifier. It should be understood that the terminal can use the trigger waiting time indicated by the measurement reporting configuration as the trigger waiting time for the measurement reporting event. For example, if the terminal determines that the reporting configuration index identifier is 101, it can determine that the trigger waiting time for the measurement reporting event is 320ms.

[0201] In some embodiments, if the measurement reporting configuration includes a measurement index identifier, the terminal can determine the reporting configuration bound to the measurement index identifier and use the trigger waiting time indicated by the reporting configuration as the trigger waiting time for the measurement reporting event. For example, if the terminal determines that the measurement index identifier is 1, it can determine the trigger waiting time for the measurement reporting event as 320ms based on the associated reporting configuration.

[0202] It should be noted that the terminal can also obtain the trigger waiting time of the measurement reporting event through other methods of related technologies, such as network or higher-level indications. In this case, steps S2102 and S2103 can be omitted.

[0203] Step S2104: If the trigger waiting time is greater than or equal to the first time and the remaining trigger waiting time is less than or equal to the first time, determine to use the first function and / or the first model for prediction.

[0204] In some embodiments, the remaining trigger wait time is the time that needs to be waited from the current moment before the measured reported event is triggered.

[0205] In some embodiments, the remaining trigger wait time can be the difference between the duration of the TTT timer and the duration the TTT timer has already run. Figure 2B is a schematic diagram of a trigger wait time according to an embodiment of the present disclosure. As shown in Figure 2B, the duration of the TTT timer, i.e., the trigger wait time, is T0 to T2, the duration the TTT timer has already run, i.e., the duration of waiting, is T0 to T1, and the remaining trigger wait time is T1 to T2.

[0206] In some embodiments, after the terminal determines the first duration and the trigger waiting duration of the measurement reporting event, it can determine whether to use the first function and / or the first model for prediction based on the first duration and the trigger waiting duration of the measurement reporting event.

[0207] In some embodiments, when the trigger waiting time for the measurement and reporting event has already started counting, the terminal initiates a determination on whether to use the first function and / or the first model for prediction.

[0208] In some embodiments, when the trigger wait duration is greater than or equal to a first duration, if the first function and / or the first model are used for prediction when the timer for the trigger wait duration starts, the measurement reporting event in the last period of the trigger wait duration cannot be predicted. For example, if the first duration is 500ms, the first function and / or the first model can predict the measurement reporting event in the next 500ms. If the trigger wait duration is 640ms, if the first function and / or the first model are used for prediction when the timer starts, the measurement reporting event in the first 500ms of the trigger wait duration can be predicted, but the measurement reporting event in the last 140ms cannot be predicted, causing the terminal to be unable to determine in advance whether the measurement reporting event will be triggered. In this case, the terminal can use the first function and / or the first model for prediction some time after the timer starts.

[0209] In some embodiments, if the trigger waiting time is greater than or equal to a first duration, the remaining trigger waiting time can be compared with the first duration. If the remaining trigger waiting time is less than or equal to the first duration, it is determined that a first function and / or a first model will be used for prediction. As shown in Figure 2B, the first duration is PW(T1~T2). Using the first function and / or the first model for prediction after T1 can predict measurement reporting events before T2.

[0210] In some embodiments, the terminal may determine whether to use the first function and / or the first model for prediction based on the first duration, the triggering waiting duration of the measurement reporting event, and the first condition.

[0211] In some embodiments, the first condition includes conditions that control the first function and / or the first model to make predictions. For example, the first condition may include conditions related to wireless channel measurement results, such as wireless channel quality being less than a quality threshold.

[0212] In some embodiments, if the terminal meets a first condition, and the trigger waiting time is greater than or equal to a first duration, and the remaining trigger waiting time is less than or equal to the first duration, it is determined to use the first function and / or the first model for prediction.

[0213] In some embodiments, if the timing of the trigger wait time for the measurement reporting event stops, the use of the first function and / or the first model for prediction is stopped.

[0214] In some embodiments, triggering the stop of the waiting time may include the timer ending, the timer expiring, or the timer stopping.

[0215] For example, if the termination time of the trigger waiting period is within the prediction window of the first function and / or the first model, as shown in Figure 2B, the first function and / or the first model starts prediction after T1, and the time T2 is within the prediction window of the first function and / or the first model, that is, when the timer for triggering the waiting period expires, the first function and / or the first model is making predictions, then the terminal does not need the first function and / or the first model to continue making predictions. In this case, the terminal can stop using the first function and / or the first model for prediction.

[0216] Step S2105: If the trigger waiting time is less than the first time, determine to use the first function and / or the first model for prediction.

[0217] In some embodiments, when the trigger waiting time is less than or equal to a first duration, if a first function and / or a first model are used for prediction when the timer starts, measurement reporting events within the entire trigger waiting time can be predicted. For example, if the first duration is 700ms, the first function and / or the first model can predict measurement reporting events within the next 700ms. If the trigger waiting time is 640ms, and the first function and / or the first model are used for prediction when the timer starts, measurement reporting events within the entire trigger waiting time can be predicted. The terminal can then determine in advance whether to trigger a report based on the predicted measurement reporting events. In this case, the terminal can use the first function and / or the first model for prediction when the timer starts or after a certain period of time.

[0218] In some embodiments, if the terminal meets a first condition and the trigger waiting time is less than a first duration, it is determined to use the first function and / or the first model for prediction.

[0219] In some embodiments, if the timing of the trigger wait time for the measurement reporting event stops, the use of the first function and / or the first model for prediction is stopped.

[0220] In some embodiments, triggering the stop of the waiting time may include the timer ending, the timer expiring, or the timer stopping.

[0221] For example, if the termination time of the triggering wait period is within the prediction window of the first function and / or the first model, that is, when the timer expires, the first function and / or the first model is making a prediction, then the terminal does not need the first function and / or the first model to continue making predictions. In this case, the terminal can stop using the first function and / or the first model to make predictions.

[0222] Using the above method, the terminal can autonomously determine whether to use the first function and / or the first model for prediction based on the trigger waiting time of the measurement and reporting event and the first duration, without having to interact frequently with the network, thereby reducing the terminal's energy consumption and the consumption of wireless resources.

[0223] The methods involved in the embodiments of this disclosure may include at least one of the steps S2101 to S2105 described above. For example, step S2101 may be implemented as an independent embodiment, step S2102 may be implemented as an independent embodiment, step S2104 may be implemented as an independent embodiment, step S2105 may be implemented as an independent embodiment, and step S2102 + step S2103 may be implemented as an independent embodiment, but are not limited thereto.

[0224] In some embodiments, the order of any two steps S2101 to S2105 can be interchanged or they can be performed simultaneously. For example, the order of steps S2101 and S2102 can be interchanged or they can be performed simultaneously.

[0225] In some embodiments, steps S2101 to S2105 are optional, and one or more of these steps may be omitted or substituted in different embodiments. For example, steps S2101, S2102, and S2103 are optional, and one or more of these steps may be omitted or substituted in different embodiments.

[0226] In some embodiments, other alternative implementations may be described before or after the specification corresponding to FIG2A.

[0227] In some embodiments, the names of information, etc., are not limited to the names described in the embodiments. Terms such as "information", "message", "signal", "signaling", "report", "configuration", "indication", "instruction", "command", "channel", "parameter", "domain", "field", "symbol", "symbol", "codebook", "codeword", "codepoint", "bit", "data", "program", and "chip" can be used interchangeably.

[0228] In some embodiments, the terms "codebook," "codeword," and "precoding matrix" can be used interchangeably. For example, a codebook can be a collection of one or more codewords / precoding matrices.

[0229] In some embodiments, the terms "uplink", "uplink", and "physical uplink" can be used interchangeably, as can the terms "downlink", "downlink", and "physical downlink", as well as the terms "sidelink", "sidelink", "sidelink communication", "sidelink communication", "direct connection", "direct link", "direct communication", and "direct link communication".

[0230] In some embodiments, the terms “downlink control information (DCI),” “downlink (DL) assignment,” “DL DCI,” “uplink (UL) grant,” and “UL DCI” can be used interchangeably.

[0231] In some embodiments, terms such as "physical downlink shared channel (PDSCH)" and "DL data" can be used interchangeably, as can terms such as "physical uplink shared channel (PUSCH)" and "UL data".

[0232] In some embodiments, the terms “radio”, “wireless”, “radio access network (RAN)”, “access network (AN)”, and “RAN-based” can be used interchangeably.

[0233] In some embodiments, the terms "search space", "search space set", "search space configuration", "search space set configuration", "control resource set (CORESET)", and "CORESET configuration" can be used interchangeably.

[0234] In some embodiments, the terms "synchronization signal (SS)," "synchronization signal block (SSB)," "reference signal (RS)," "pilot," and "pilot signal" can be used interchangeably.

[0235] In some embodiments, terms such as “moment,” “point in time,” “time,” and “time location” can be used interchangeably, as can terms such as “duration,” “segment,” “time window,” “window,” and “time.”

[0236] In some embodiments, the terms "component carrier (CC)," "cell," "frequency carrier," and "carrier frequency" can be used interchangeably.

[0237] In some embodiments, the terms “resource block (RB)”, “physical resource block (PRB)”, “sub-carrier group (SCG)”, “resource element group (REG)”, “PRB pair”, “RB pair”, “resource element (RE)”, and “sub-carrier” can be used interchangeably.

[0238] In some embodiments, terms such as wireless access scheme and waveform can be used interchangeably.

[0239] In some embodiments, the terms "precoding", "precoder", "weight", "precoding weight", "quasi-co-location (QCL)", "transmission configuration indication (TCI) status", "spatial relation", "spatial domain filter", "transmission power", "phase rotation", "antenna port", "antenna port group", "layer", "the number of layers", "rank", "resource", "resource set", "resource group", "beam", "beam width", "beam angle", "antenna", "antenna element", and "panel" can be used interchangeably.

[0240] In some embodiments, the terms “frame”, “radio frame”, “subframe”, “slot”, “sub-slot”, “mini-slot”, “symbol”, “symbol”, and “transmission time interval (TTI)” can be used interchangeably.

[0241] In some embodiments, "acquire," "get," "obtain," "receive," "transmit," "bidirectional transmission," and "send and / or receive" can be used interchangeably and can be interpreted as receiving from other entities, acquiring from protocols, acquiring from higher layers, obtaining through self-processing, or autonomous implementation. Protocols include, for example, at least one of the 3GPP protocol, Wi-Fi protocol, and audio and / or video protocols.

[0242] In some embodiments, terms such as “send,” “transmit,” “report,” “distribute,” “transmit,” “bidirectional transmission,” “send and / or receive” can be used interchangeably.

[0243] In some embodiments, terms such as "certain," "preset," "default," "set," "indicated," "a certain," "any," and "first" can be used interchangeably. "Certain A," "preset A," "default A," "set A," "indicated A," "a certain A," "any A," and "first A" can be interpreted as A pre-defined in a protocol or the like, or as A obtained through setting, configuration, or instruction, or as specific A, a certain A, any A, or first A, but are not limited thereto.

[0244] In some embodiments, the determination or judgment can be made by a value represented by 1 bit (0 or 1), or by a true or false value (boolean), or by a comparison of numerical values ​​(e.g., a comparison with a predetermined value), but is not limited thereto.

[0245] In some embodiments, "not expecting to receive" can be interpreted as not receiving on time domain resources and / or frequency domain resources, or as not performing subsequent processing on the data and / or instructions received; "not expecting to send" can be interpreted as not sending, or as sending but not expecting the receiver to respond to the sent content.

[0246] In some embodiments, if an arrow in the interaction diagram representing the sending of information, signaling, etc. from one subject to another passes through other subjects, it can be interpreted as the information being forwarded from one subject to another via other subjects, or it can be interpreted as the information being sent from one subject to another without passing through other subjects.

[0247] Figure 2C is a flowchart illustrating a communication method according to an embodiment of the present disclosure. This method can be executed by the aforementioned terminal. As shown in Figure 2C, the method may include:

[0248] Step S2301: Based on the second association relationship, the first function and / or the first model determine the measurement reporting configuration.

[0249] The optional implementation of step S2301 can be found in the optional implementation of step S2102 in Figure 2A, and other related parts in the embodiments involved in Figure 2A, which will not be repeated here.

[0250] Step S2302: Determine the trigger waiting time for the measurement reporting event based on the measurement reporting configuration.

[0251] The optional implementation of step S2302 can be found in the optional implementation of step S2103 in Figure 2A, and other related parts in the embodiments involved in Figure 2A, which will not be repeated here.

[0252] Step S2303: Based on the trigger waiting time of the measurement and reporting event and the first condition, determine whether to use the first function and / or the first model for prediction.

[0253] The optional implementation of step S2303 can be found in the optional implementations of steps S2104 and S2105 in Figure 2A, as well as other related parts in the embodiments involved in Figure 2A, which will not be repeated here.

[0254] In some embodiments, if the terminal meets a first condition and the timer for measuring the triggering wait time of the reported event is about to expire, it is determined to use the first function and / or the first model for prediction.

[0255] In some embodiments, the timer expiring soon can be understood as the current time being less than or equal to the timer expiring time threshold. This time threshold can be pre-configured by the network or predetermined by the protocol, for example, the time threshold is 320ms.

[0256] Using the above method, the terminal can autonomously determine whether to use the first function and / or the first model for prediction based on the trigger waiting time of the measurement and reporting event and the first condition, without having to interact frequently with the network, thereby reducing the terminal's energy consumption and the consumption of wireless resources.

[0257] The methods involved in the embodiments of this disclosure may include at least one of the steps S2301 to S2303 described above. For example, step S2301 may be implemented as a standalone embodiment, step S2303 may be implemented as a standalone embodiment, and step S2301 + step S2302 may be implemented as a standalone embodiment, but are not limited thereto.

[0258] In some embodiments, the order of any two steps in steps S2301 to S2303 can be interchanged or they can be performed simultaneously.

[0259] In some embodiments, steps S2301 to S2303 are all optional steps. For example, steps S2301 and S2302 are optional, and one or more of these steps may be omitted or substituted in different embodiments.

[0260] Figure 2D is a flowchart illustrating a communication method according to an embodiment of the present disclosure. This method can be executed by the aforementioned terminal. As shown in Figure 2D, the method may include:

[0261] Step S2401: Based on the trigger waiting time of the measurement and reporting event, determine whether to use the first function and / or the first model for prediction.

[0262] The optional implementation of step S2401 can be found in the optional implementations of step S2104 and step S2105 in Figure 2A, step S2303 in Figure 2C, and other related parts in the embodiments involved in Figures 2A and 2C, which will not be repeated here.

[0263] In some embodiments, determining whether to use the first function and / or the first model for prediction based on the trigger wait time of the measured reported event includes:

[0264] If the trigger waiting time is greater than or equal to the first time, and the remaining trigger waiting time is less than or equal to the first time, then it is determined that the first function and / or the first model will be used for prediction; or,

[0265] If the trigger waiting time is less than the first time, it is determined that the first function and / or the first model will be used for prediction.

[0266] In some embodiments, the first duration is at least one of the following:

[0267] Network configuration duration;

[0268] The duration of the prediction window during which the first function and / or the first model makes predictions;

[0269] The first function and / or the first model can predict the duration of measurement results or measurement reporting events.

[0270] In some embodiments, the method further includes:

[0271] Based on the first association relationship, the first function and / or the first model determines the first duration; wherein, the first association relationship includes the correspondence between different first functions and / or different first models and the first duration, the first association relationship is provided by a network or server, and the server is a node used to train the first function and / or the first model.

[0272] In some embodiments, determining whether to use the first function and / or the first model for prediction based on the trigger wait time of the measured reported event includes:

[0273] Based on the trigger waiting time of the measurement and reporting event and a first condition, determine whether to use the first function and / or the first model for prediction; wherein, the first condition includes conditions that control the first function and / or the first model to make predictions.

[0274] In some embodiments, the method further includes:

[0275] Based on the second association relationship, the first function and / or the first model determine the measurement reporting configuration; wherein, the second association relationship includes the correspondence between different first functions and / or different first models and the measurement reporting configuration;

[0276] The triggering wait time for the measurement reporting event is determined based on the measurement reporting configuration.

[0277] In some embodiments, the measurement reporting configuration includes at least one of the following: a measurement index identifier and a reporting configuration index identifier.

[0278] In some embodiments, the trigger wait time for the measurement reporting event has already started timing.

[0279] In some embodiments, the method further includes:

[0280] If the timing of the trigger wait time for the measurement reporting event stops, the use of the first function and / or the first model for prediction shall cease.

[0281] In some embodiments, the first function and / or the first model includes at least one of the following:

[0282] The network indicates the activation of artificial intelligence (AI) functions and / or AI models;

[0283] Currently available AI features and / or AI models.

[0284] In some embodiments, the first function and / or the first model is used for at least one of the following:

[0285] Predict cell or beam measurement results;

[0286] Predict whether the reported events meet the reporting conditions.

[0287] In some embodiments, this disclosure provides a method for controlling AI inference to reduce the power consumption and additional wireless resource consumption of the UE.

[0288] In some embodiments, the UE determines to use an AI model or function to make a prediction based on the fact that the remaining TTT of the measured reported event is less than or equal to a first duration, and obtains the prediction result.

[0289] In some embodiments, the AI ​​model or function is used to predict future cell or beam measurement results, or to predict whether future measurement reporting events will be met.

[0290] In some embodiments, the first duration can be a duration configured by the network, or it can be the length of the prediction window (PW) predicted by the AI. The first duration can also be the furthest time that the AI ​​can predict for the measurement result or the measurement reporting event.

[0291] In some embodiments, the first duration is determined by the UE based on an AI model or function. The correspondence between the first duration and the AI ​​model or function can be provided by the network or a server. The server is the node that trains the model.

[0292] In some embodiments, the AI ​​model or function is an AI model or function activated by a network instruction.

[0293] In some embodiments, the AI ​​model or function is a currently available AI model or function.

[0294] In some embodiments, the Measurement Reporting Time Tolerance (TTT) for the measurement reporting event has started running, meaning that the entry conditions for measurement reporting have been met.

[0295] In some embodiments, as shown in Figure 2B, when the first duration is PW, the TTT has already run for the duration of T1-T0, and the remaining TTT duration is T2-T1. The UE uses AI for prediction only after T1.

[0296] In some embodiments, if the UE determines that the first duration is less than or equal to the TTT, then if the remaining TTT duration is less than or equal to the first duration, it determines to perform prediction. The remaining TTT duration is the TTT timer duration minus the duration the TTT has already run. If the UE determines that the first duration is greater than the TTT, it determines that prediction can be performed.

[0297] In some embodiments, if the network is also configured with other conditions controlling AI predictions, such as conditions based on wireless channel measurements, then in this case, the time condition and other conditions must be met simultaneously for prediction to occur. If any one condition is not met, no prediction is made.

[0298] In some embodiments, the correspondence between the AI ​​model or function and the measurement reporting event is configured via a network.

[0299] In some embodiments, the network can configure a mapping between AI models or functions and measurement reporting configurations to determine the corresponding Time To Day (TTT). The measurement reporting configuration can be a measurement index identifier (meas id) or a reporting configuration index identifier (reportconfig ID).

[0300] In some embodiments, if the TTT operation stops, the UE stops performing AI predictions.

[0301] In some embodiments of this disclosure, a communication system is provided, which may include a terminal and a network device, wherein the terminal may execute the communication methods performed by the terminal in the foregoing embodiments of this disclosure.

[0302] This disclosure also proposes an apparatus for implementing any of the above methods. For example, an apparatus is proposed that includes units or modules for implementing the steps performed by the terminal in any of the above methods.

[0303] It should be understood that the division of units or modules in the above device is only a logical functional division. In actual implementation, they can be fully or partially integrated into a single physical entity, or they can be physically separated. Furthermore, the units or modules in the device can be implemented by a processor calling software: for example, the device includes a processor connected to a memory containing instructions. The processor calls the instructions stored in the memory to implement any of the above methods or to implement the functions of the units or modules in the above device. The processor can be, for example, a general-purpose processor, such as a Central Processing Unit (CPU) or a microprocessor, and the memory can be internal or external to the device. Alternatively, the units or modules in the device can be implemented in the form of hardware circuits. The functionality of some or all of the units or modules can be achieved through the design of these hardware circuits, which can be understood as one or more processors. For example, in one implementation, the hardware circuit is an Application-Specific Integrated Circuit (ASIC), and the functionality of some or all of the units or modules is achieved through the design of the logical relationships between the components within the circuit. In another implementation, the hardware circuit can be implemented using a Programmable Logic Device (PLD), such as a Field Programmable Gate Array (FPGA), which can include a large number of logic gates. The connection relationships between the logic gates are configured through configuration files, thereby achieving the functionality of some or all of the units or modules. All units or modules of the above device can be implemented entirely through processor-called software, entirely through hardware circuits, or partially through processor-called software with the remaining parts implemented through hardware circuits.

[0304] In this embodiment, the processor is a circuit with signal processing capabilities. In one implementation, the processor can be a circuit with instruction read and execute capabilities, such as a Central Processing Unit (CPU), a microprocessor, a Graphics Processing Unit (GPU) (which can be understood as a microprocessor), or a Digital Signal Processor (DSP). In another implementation, the processor can implement certain functions through the logical relationships of hardware circuits. The logical relationships of the aforementioned hardware circuits are fixed or reconfigurable. For example, the processor is a hardware circuit implemented using an Application-Specific Integrated Circuit (ASIC) or a Programmable Logic Device (PLD), such as an FPGA. In a reconfigurable hardware circuit, the process of the processor loading a configuration document and configuring the hardware circuit can be understood as the process of the processor loading instructions to implement the functions of some or all of the above units or modules. In addition, it can also be hardware circuits designed for artificial intelligence, which can be understood as ASICs, such as Neural Network Processing Units (NPUs), Tensor Processing Units (TPUs), and Deep Learning Processing Units (DPUs).

[0305] Figure 3 is a schematic diagram of the structure of a terminal according to an embodiment of this disclosure. As shown in Figure 3, the terminal 101 may include at least one of a processing module 3101, a transceiver module 3102, etc. In some embodiments, the processing module 3101 is configured to determine whether to use a first function and / or a first model for prediction based on the trigger waiting time of the measured reported event. Optionally, the transceiver module 3102 may be used to perform at least one of the communication steps such as sending and / or receiving performed by the terminal 101 in any of the above methods, which will not be elaborated here. Optionally, the processing module 3101 may be used to perform at least one of other steps performed by the terminal 101 in any of the above methods (e.g., steps S2101, S2102, S2103, S2104, S2105, S2301, S2302, S2303, S2401, but not limited thereto), which will not be elaborated here.

[0306] In some embodiments, the transceiver module may include a transmitting module and / or a receiving module, which may be separate or integrated. Optionally, the transceiver module may be interchangeable with a transceiver.

[0307] In some embodiments, the processing module may be a single module or may include multiple sub-modules. Optionally, the multiple sub-modules may each perform all or part of the steps required by the processing module. Optionally, the processing module may be interchangeable with a processor.

[0308] Figure 4A is a schematic diagram of the structure of the communication device 4100 proposed in an embodiment of this disclosure. The communication device 4100 can be a network device (e.g., access network device, core network device, etc.), a terminal (e.g., user equipment, etc.), a chip, chip system, or processor that supports the first device in implementing any of the above methods, or a chip, chip system, or processor that supports the terminal in implementing any of the above methods. The communication device 4100 can be used to implement the methods described in the above method embodiments; for details, please refer to the descriptions in the above method embodiments.

[0309] As shown in Figure 4A, the communication device 4100 includes one or more processors 4101. The processor 4101 can be a general-purpose processor or a dedicated processor, such as a baseband processor or a central processing unit (CPU). The baseband processor can be used to process communication protocols and communication data, while the CPU can be used to control communication devices (e.g., base stations, baseband chips, IoT devices, IoT device chips, DUs or CUs, etc.), execute programs, and process program data. The communication device 4100 is used to execute any of the above methods.

[0310] In some embodiments, the communication device 4100 further includes one or more memories 4102 for storing instructions. Optionally, all or part of the memories 4102 may also be located outside the communication device 4100.

[0311] In some embodiments, the communication device 4100 further includes one or more transceivers 4103. When the communication device 4100 includes one or more transceivers 4103, the transceivers 4103 perform at least one of the communication steps such as sending and / or receiving in the above method, and the processor 4101 performs at least one of other steps (e.g., steps S2101, S2102, S2103, S2104, S2105, S2301, S2302, S2303, S2401, but not limited thereto).

[0312] In some embodiments, a transceiver may include a receiver and / or a transmitter, which may be separate or integrated. Optionally, the terms transceiver, transceiver unit, transceiver, transceiver circuit, etc., may be used interchangeably; the terms transmitter, transmitting unit, transmitter, transmitting circuit, etc., may be used interchangeably; and the terms receiver, receiving unit, receiver, receiving circuit, etc., may be used interchangeably.

[0313] In some embodiments, the communication device 4100 may include one or more interface circuits. Optionally, the interface circuit is connected to the memory 4102, and the interface circuit can be used to receive signals from the memory 4102 or other devices, and can be used to send signals to the memory 4102 or other devices. For example, the interface circuit can read instructions stored in the memory 4102 and send the instructions to the processor 4101.

[0314] The communication device 4100 described in the above embodiments may be a first device or an Internet of Things (IoT) device, but the scope of the communication device 4100 described in this disclosure is not limited thereto, and the structure of the communication device 4100 may not be limited by FIG4A. The communication device may be a standalone device or may be part of a larger device. For example, the communication device may be: (1) a standalone integrated circuit IC, or chip, or chip system or subsystem; (2) a collection of one or more ICs, optionally, the IC collection may also include storage components for storing data and programs; (3) an ASIC, such as a modem; (4) a module that can be embedded in other devices; (5) a receiver, IoT device, smart IoT device, cellular phone, wireless device, handheld device, mobile unit, vehicle device, first device, cloud device, artificial intelligence device, etc.; (6) others, etc.

[0315] Figure 4B is a schematic diagram of the structure of chip 4200 according to an embodiment of this disclosure. For cases where the communication device 4100 can be a chip or a chip system, please refer to the schematic diagram of chip 4200 shown in Figure 4B, but it is not limited thereto.

[0316] Chip 4200 includes one or more processors 4201, which are used to perform any of the above methods.

[0317] In some embodiments, chip 4200 further includes one or more interface circuits 4203. Optionally, the interface circuit 4203 is connected to memory 4202, and the interface circuit 4203 can be used to receive signals from memory 4202 or other devices, and the interface circuit 4203 can be used to send signals to memory 4202 or other devices. For example, the interface circuit 4203 can read instructions stored in memory 4202 and send the instructions to processor 4201.

[0318] In some embodiments, the interface circuit 4203 performs at least one of the communication steps such as sending and / or receiving in the above method, and the processor 4201 performs at least one of other steps (e.g., steps S2101, S2102, S2103, S2104, S2105, S2301, S2302, S2303, S2401, but not limited thereto).

[0319] In some embodiments, the terms interface circuit, interface, transceiver pin, transceiver, etc., can be used interchangeably.

[0320] In some embodiments, chip 4200 further includes one or more memories 4202 for storing instructions. Optionally, all or part of the memories 4202 may be located outside of chip 4200.

[0321] This disclosure also proposes a storage medium storing instructions that, when executed on the communication device 4100, cause the communication device 4100 to perform any of the above methods. Optionally, the storage medium is an electronic storage medium. Optionally, the storage medium is a computer-readable storage medium, but not limited thereto; it may also be a storage medium readable by other devices. Optionally, the storage medium may be a non-transitory storage medium, but not limited thereto; it may also be a temporary storage medium.

[0322] This disclosure also provides a program product that, when executed by the communication device 4100, causes the communication device 4100 to perform any of the above methods. Optionally, the program product may be a computer program product.

[0323] This disclosure also proposes a computer program that, when run on a computer, causes the computer to perform any of the above methods.

Claims

1. A communication method, characterized in that, The method, executed by a terminal, includes: Based on the trigger waiting time of the measured reported event, determine whether to use the first function and / or the first model for prediction.

2. The method according to claim 1, characterized in that, The step of determining whether to use the first function and / or the first model for prediction based on the trigger waiting time of the measured reported event includes: If the trigger waiting time is greater than or equal to the first time, and the remaining trigger waiting time is less than or equal to the first time, then it is determined that the first function and / or the first model will be used for prediction; or, If the trigger waiting time is less than the first time, it is determined that the first function and / or the first model will be used for prediction.

3. The method according to claim 2, characterized in that, The first duration is at least one of the following: Network configuration duration; The duration of the prediction window during which the first function and / or the first model makes predictions; The first function and / or the first model can predict the duration of measurement results or measurement reporting events.

4. The method according to claim 2 or 3, characterized in that, The method further includes: Based on the first association relationship, the first function and / or the first model determines the first duration; wherein, the first association relationship includes the correspondence between different first functions and / or different first models and the first duration, the first association relationship is provided by a network or server, and the server is a node used to train the first function and / or the first model.

5. The method according to any one of claims 1-4, characterized in that, The step of determining whether to use the first function and / or the first model for prediction based on the trigger waiting time of the measured reported event includes: Based on the trigger waiting time of the measurement and reporting event and a first condition, determine whether to use the first function and / or the first model for prediction; wherein, the first condition includes conditions that control the first function and / or the first model to make predictions.

6. The method according to any one of claims 1-5, characterized in that, The method further includes: Based on the second association relationship, the first function and / or the first model determine the measurement reporting configuration; wherein, the second association relationship includes the correspondence between different first functions and / or different first models and the measurement reporting configuration; The triggering wait time for the measurement reporting event is determined based on the measurement reporting configuration.

7. The method according to claim 6, characterized in that, The measurement reporting configuration includes at least one of the following: measurement index identifier and reporting configuration index identifier.

8. The method according to any one of claims 1-7, characterized in that, The trigger wait time for the measurement reporting event has started counting down.

9. The method according to any one of claims 1-8, characterized in that, The method further includes: If the timing of the trigger wait time for the measurement reporting event stops, the use of the first function and / or the first model for prediction shall cease.

10. The method according to any one of claims 1-9, characterized in that, The first function and / or the first model includes at least one of the following: The network indicates the activation of artificial intelligence (AI) functions and / or AI models; Currently available AI features and / or AI models.

11. The method according to any one of claims 1-10, characterized in that, The first function and / or the first model is used for at least one of the following: Predict cell or beam measurement results; Predict whether the reported events meet the reporting conditions.

12. A communication device, characterized in that, The communication device is used to perform the communication method according to any one of claims 1-11.

13. A communication system, characterized in that, It includes a terminal and a network device, wherein the terminal is configured to implement the communication method according to any one of claims 1-11.

14. A storage medium storing instructions, characterized in that, When the instruction is executed on the communication device, the communication device performs the communication method as described in any one of claims 1-11.

15. A program product comprising at least one of a program and instructions, characterized in that, When at least one of the programs or instructions is executed by a communication device, it implements the steps of the method described in any one of claims 1-11.

Images