Method for transmitting early measurement report, terminal, and network device

Abstract

The present disclosure relates to a method for transmitting an early measurement report (EMR), a terminal, and a network device. The method comprises: when a timer stops operation, determining a valid first EMR on the basis of a prediction result from an AI model, wherein the terminal is in an RRC idle state during operation of the timer; and the terminal entering an RRC connected state and sending the first EMR to a network device. In the method of the present disclosure, a terminal determines a currently valid first EMR on the basis of AI model prediction, and reports the valid first EMR to a network device, so that the network device can always obtain a valid EMR, thereby improving the accuracy of CA or DC configuration.

Description

Method, terminal and network device for transmitting early measurement report Technical Field

[0001] The present disclosure relates to the field of communication technologies, and in particular to a method, a terminal, and a network device for transmitting an Early Measurement Report (EMR). Background Art

[0002] When the terminal is in the Radio Resource Control (RRC) idle state or idle mode, it can perform early measurement on the carrier or cell configured by the network device to obtain EMR. When the terminal enters the RRC connected state or connected mode, it can report the EMR obtained in idle mode to the network device, so that the network device can perform carrier aggregation (CA) or dual connectivity (DC) configuration more quickly.

[0003] Summary of the Invention

[0004] There may be a large interval between the time when the terminal completes EMR-related measurements and the time when the terminal reports EMR. For example, after completing EMR-related measurements, the terminal may not enter the RRC connected state quickly, and thus may not report EMR in a timely manner. This causes the obtained EMR to be no longer accurate or valid, because the EMR at the time the terminal reports the EMR may no longer meet the requirements of the network device or the current communication conditions. If the terminal still reports the EMR obtained by the measurement, it will cause the network device to perform incorrect CA or DC configuration.

[0005] Embodiments of the present disclosure provide a method, a terminal, and a network device for transmitting EMR.

[0006] In a first aspect, an embodiment of the present disclosure provides a method for sending an EMR, performed by a terminal, the method comprising:

[0007] After an end time of a timer, determining a valid first EMR according to a prediction result of an artificial intelligence (AI) model, wherein the terminal is in an RRC idle state during the timer;

[0008] The terminal enters the RRC connected state and sends the first EMR to the network device.

[0009] In a second aspect, an embodiment of the present disclosure provides a method for receiving an EMR, performed by a network device, the method comprising:

[0010] A first EMR sent by a receiving terminal is received, wherein the terminal is in an RRC connected state, and the first EMR is a valid EMR determined by the terminal according to a prediction result of an AI model after an end time of a timer, wherein the terminal is in an RRC idle state during the timer operation.

[0011] In a third aspect, an embodiment of the present disclosure provides a terminal, including:

[0012] a processing module, configured to determine, after an end time of a timer, a valid first EMR according to a prediction result of the AI ​​model, wherein the terminal is in an RRC idle state during the timer running;

[0013] The transceiver module is configured to send the first EMR to the network device when entering the RRC connection state.

[0014] In a fourth aspect, an embodiment of the present disclosure provides a network device, including:

[0015] A transceiver module is configured to receive a first EMR sent by a terminal, wherein the terminal is in an RRC connected state, and the first EMR is a valid EMR determined by the terminal according to a prediction result of an AI model after the end time of a timer, wherein the terminal is in an RRC idle state during the timer operation.

[0016] In a fifth aspect, an embodiment of the present disclosure provides a terminal, including:

[0017] one or more processors;

[0018] The terminal is configured to implement the method described in the first aspect.

[0019] In a sixth aspect, an embodiment of the present disclosure provides a network device, including:

[0020] one or more processors;

[0021] The network device is configured to implement the method described in the second aspect.

[0022] In a seventh aspect, an embodiment of the present disclosure provides a communication system, including a terminal and a network device, wherein:

[0023] The terminal is configured to implement the method according to the first aspect;

[0024] The network device is configured to implement the method according to the second aspect.

[0025] In an eighth aspect, an embodiment of the present disclosure provides a storage medium, wherein the storage medium stores instructions, wherein:

[0026] When the instruction is executed on a communication device, the communication device is caused to execute the method according to the first aspect or the second aspect.

[0027] In a ninth aspect, an embodiment of the present disclosure provides a program product, wherein:

[0028] When the program product is executed by a communication device, the communication device is caused to execute the method according to the first aspect or the second aspect.

[0029] In the embodiment of the present disclosure, the terminal determines the currently valid first EMR based on AI model prediction and reports the valid first EMR to the network device, so that the network device can always obtain the valid EMR, thereby improving the accuracy of CA or DC configuration. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] In order to more clearly illustrate the technical solutions in the embodiments of the present disclosure, the following drawings required for describing the embodiments are introduced. The following drawings are merely some embodiments of the present disclosure and do not impose specific limitations on the protection scope of the present disclosure.

[0031] FIG1a is an exemplary schematic diagram of the architecture of a communication system provided according to an embodiment of the present disclosure;

[0032] FIG1b is a schematic diagram of EMR measurement according to an embodiment of the present disclosure;

[0033] 2a to 2c are exemplary interaction diagrams of a method provided according to an embodiment of the present disclosure;

[0034] Figures 2d to 2f are schematic diagrams of the implementation of the method provided according to an embodiment of the present disclosure;

[0035] FIG3 is an exemplary flowchart of a method provided according to an embodiment of the present disclosure;

[0036] FIG4 is an exemplary flowchart of a method provided according to an embodiment of the present disclosure;

[0037] FIG5a is a schematic structural diagram of a terminal according to an embodiment of the present disclosure;

[0038] FIG5b is a schematic structural diagram of a network device according to an embodiment of the present disclosure;

[0039] FIG6a is a schematic diagram of a communication device according to an embodiment of the present disclosure;

[0040] FIG6 b is a schematic diagram of a communication device according to an embodiment of the present disclosure. DETAILED DESCRIPTION

[0041] Embodiments of the present disclosure provide a method, a terminal, and a network device for transmitting EMR.

[0042] In a first aspect, an embodiment of the present disclosure provides a method for sending an EMR, which is executed by a terminal. The method includes:

[0043] After the end time of the timer, determine a valid first EMR according to the prediction result of the AI ​​model, wherein the terminal is in the RRC idle state during the timer running;

[0044] The terminal enters the RRC connected state and sends a first EMR to the network device.

[0045] In the above embodiment, the terminal determines the currently valid first EMR based on the AI ​​model prediction and reports the valid first EMR to the network device, so that the network device can always obtain the valid EMR, thereby improving the accuracy of CA or DC configuration.

[0046] In conjunction with the embodiments of the first aspect, in some embodiments, the AI ​​model is used to output the prediction result based on the input of the AI ​​model, wherein:

[0047] The input of the AI ​​model is: a first change amount, where the first change amount is a change amount between a measurement result of an early measurement of the serving cell by the terminal during the timer operation and a measurement result of the serving cell measured by the terminal after the end time;

[0048] The prediction result of the AI ​​model is: a second change amount, the second change amount is used to represent the change between the measurement result of the early measurement of the carrier by the terminal during the operation of the timer and the measurement result corresponding to the carrier after the end time, and the carrier is configured by the network device.

[0049] In the above embodiment, the terminal can predict the change amount of the EMR carrier measurement result based on the change amount of the serving cell measurement result based on the AI ​​model, so that the current valid measurement result can be determined based on the change amount.

[0050] In conjunction with the embodiments of the first aspect, in some embodiments, determining the effective first EMR according to the prediction result of the AI ​​model includes:

[0051] determining a first EMR based on the second variation and the second EMR;

[0052] The second EMR includes a measurement result obtained by the terminal performing early measurement on the carrier during the operation of the timer.

[0053] In the above embodiment, the terminal determines an accurate measurement result based on the measurement result before the timer expires and the second variation, thereby reporting a valid first EMR.

[0054] In conjunction with the embodiments of the first aspect, in some embodiments, the method further includes:

[0055] The first change amount is determined according to the measurement result of the serving cell during the timer running period and the measurement result of the serving cell after the end time.

[0056] In the above embodiment, the terminal uses the measurement results of the serving cell before and after the expiration of the timer to obtain the input of the AI ​​model, so as to facilitate the prediction of the second change corresponding to the EMR carrier based on the AI ​​model.

[0057] In combination with the embodiments of the first aspect, in some embodiments, the time interval between the end time and the time when the terminal enters the RRC connection state meets or does not meet a time threshold (time threshold), and the time threshold is used to indicate the effective duration of the EMR.

[0058] In the above embodiment, the terminal does not need to check the relationship between the time interval and the time threshold, which improves the reporting flexibility of the terminal.

[0059] In conjunction with the embodiments of the first aspect, in some embodiments, the first EMR meets the accuracy requirements defined by the protocol.

[0060] In the above embodiment, the first EMR reported by the terminal meets the measurement accuracy requirement to ensure the accuracy of the configuration of the network device.

[0061] In conjunction with the embodiments of the first aspect, in some embodiments, the AI ​​model is used to output the prediction result based on the input of the AI ​​model, wherein:

[0062] The input of the AI ​​model is: the terminal's measurement results for the serving cell after the end time;

[0063] The prediction results of the AI ​​model are: the measurement results corresponding to the carrier used for early measurement after the end time;

[0064] The first EMR includes input and prediction results.

[0065] In the above embodiment, the terminal can predict the measurement result of the EMR carrier based on the measurement result of the serving cell based on the AI ​​model, so that after stopping the EMR carrier measurement, the terminal can also use the AI ​​method to obtain a valid EMR carrier measurement result and report a valid EMR.

[0066] In combination with the embodiments of the first aspect, in some embodiments, the training data of the AI ​​model includes: measurement results of the serving cell during the timer operation, and measurement results corresponding to the carrier during the timer operation.

[0067] In the above embodiment, the training of the AI ​​model can be performed in advance (off-line training) or online (on-line training), and the terminal uses the trained AI model to obtain accurate prediction results.

[0068] In conjunction with the embodiments of the first aspect, in some embodiments, the AI ​​model is used to output the prediction result based on the input of the AI ​​model, wherein:

[0069] The input of the AI ​​model is: the measurement results of the serving cell corresponding to different time units;

[0070] The prediction result of the AI ​​model is: effective time threshold, which is used to indicate the effective duration of the EMR.

[0071] In the above embodiment, the terminal can obtain the terminal's mobility status based on the measurement results of the serving cell based on the AI ​​model, and predict the time threshold adapted to the mobility status. Thus, the terminal can judge the validity of the EMR based on the time threshold adapted to its own mobility status, thereby improving the rationality and accuracy of the EMR validity judgment, and thereby improving the accuracy of the network device configuration.

[0072] In conjunction with the embodiments of the first aspect, in some embodiments, the method further includes:

[0073] Receiving information sent by a network device for indicating a time threshold, wherein the time threshold is obtained by the network device based on the AI ​​model prediction, and the terminal enters the RRC idle state;

[0074] or,

[0075] Information indicating a time threshold is sent to a network device, wherein the time threshold is obtained by the terminal based on the prediction of the AI ​​model.

[0076] In the above embodiment, the time threshold can be predicted by the network device and notified to the terminal; it can also be predicted by the terminal and reported to the network device; thereby improving the flexibility of predicting the time threshold based on the AI ​​model.

[0077] In conjunction with the embodiments of the first aspect, in some embodiments, the first EMR satisfies the following conditions:

[0078] The first EMR is obtained before an end time, wherein a time interval between the end time and a time when the terminal enters an RRC connected state is less than a time threshold.

[0079] In the above embodiment, the terminal determines the validity of the EMR based on the time threshold predicted by the AI ​​model, ensuring that a valid EMR is reported to improve the accuracy of network device configuration.

[0080] In a second aspect, an embodiment of the present disclosure provides a method for receiving an EMR, performed by a network device, the method comprising:

[0081] A first EMR sent by a receiving terminal is received, wherein the terminal is in an RRC connected state, and the first EMR is a valid EMR determined by the terminal according to a prediction result of an AI model after an end time of a timer, wherein the terminal is in an RRC idle state during the timer operation.

[0082] In conjunction with the embodiments of the second aspect, in some embodiments, the AI ​​model is used to output the prediction result based on the input of the AI ​​model, wherein:

[0083] The input of the AI ​​model is: a first change amount, where the first change amount is a change amount between a measurement result of an early measurement of the serving cell by the terminal during the timer operation and a measurement result of the serving cell measured by the terminal after the end time;

[0084] The prediction result of the AI ​​model is: a second change amount, the second change amount is used to represent the change between the measurement result of the early measurement of the carrier by the terminal during the operation of the timer and the measurement result corresponding to the carrier after the end time, and the carrier is configured by the network device.

[0085] In combination with the embodiments of the second aspect, in some embodiments, the first EMR is determined based on the second change amount and the second EMR, and the second EMR includes a measurement result obtained by the terminal performing early measurement on the carrier during the operation of the timer.

[0086] In combination with the embodiments of the second aspect, in some embodiments, the time interval between the end time and the time when the terminal enters the RRC connection state meets or does not meet the time threshold, and the time threshold is used to indicate the effective duration of the EMR.

[0087] In conjunction with the embodiments of the second aspect, in some embodiments, the first EMR meets the accuracy requirements defined by the protocol.

[0088] In conjunction with the embodiments of the second aspect, in some embodiments, the AI ​​model is used to output the prediction result based on the input of the AI ​​model, wherein:

[0089] The input of the AI ​​model is: the terminal's measurement results for the serving cell after the end time;

[0090] The prediction results of the AI ​​model are: the measurement results corresponding to the carrier used for early measurement after the end time;

[0091] The first EMR includes input and prediction results.

[0092] In combination with the embodiments of the second aspect, in some embodiments, the training data of the AI ​​model includes: measurement results of the serving cell during the timer operation, and measurement results corresponding to the carrier during the timer operation.

[0093] In conjunction with the embodiments of the second aspect, in some embodiments, the AI ​​model is used to output the prediction result based on the input of the AI ​​model, wherein:

[0094] The input of the AI ​​model is: the measurement results of the serving cell corresponding to different time units;

[0095] The prediction result of the AI ​​model is: effective time threshold, which is used to indicate the effective duration of the EMR.

[0096] In conjunction with the embodiments of the second aspect, in some embodiments, the method further includes:

[0097] Sending information indicating a time threshold to the terminal, where the time threshold is obtained by the network device based on the AI ​​model prediction, and the terminal is in an RRC idle state;

[0098] or,

[0099] Information indicating a time threshold is received from a receiving terminal, wherein the time threshold is obtained by the terminal based on a prediction of the AI ​​model.

[0100] In conjunction with the embodiments of the second aspect, in some embodiments, the first EMR satisfies the following conditions:

[0101] The first EMR is obtained before the end time, wherein the time interval between the end time and the time when the terminal enters the RRC connected state is less than a time threshold.

[0102] In a third aspect, an embodiment of the present disclosure provides a terminal, including:

[0103] a processing module, configured to determine, after an end time of a timer, a valid first EMR according to a prediction result of the AI ​​model, wherein the terminal is in an RRC idle state during the timer running;

[0104] The transceiver module is configured to send the first EMR to the network device when entering the RRC connection state.

[0105] In a fourth aspect, an embodiment of the present disclosure provides a network device, including:

[0106] A transceiver module is configured to receive a first EMR sent by a terminal, wherein the terminal is in an RRC connected state, and the first EMR is a valid EMR determined by the terminal according to a prediction result of an AI model after the end time of a timer, wherein the terminal is in an RRC idle state during the timer operation.

[0107] In a fifth aspect, an embodiment of the present disclosure provides a terminal, including:

[0108] one or more processors;

[0109] The terminal is configured to implement the method described in the first aspect.

[0110] In a sixth aspect, an embodiment of the present disclosure provides a network device, including:

[0111] one or more processors;

[0112] The network device is configured to implement the method described in the second aspect.

[0113] In a seventh aspect, an embodiment of the present disclosure provides a communication system, including a terminal and a network device, wherein:

[0114] The terminal is configured to implement the method according to the first aspect;

[0115] The network device is configured to implement the method according to the second aspect.

[0116] In an eighth aspect, an embodiment of the present disclosure provides a storage medium, wherein the storage medium stores instructions, wherein:

[0117] When the instruction is executed on a communication device, the communication device is caused to execute the method according to the first aspect or the second aspect.

[0118] In a ninth aspect, an embodiment of the present disclosure provides a program product, wherein:

[0119] When the program product is executed by a communication device, the communication device is caused to execute the method according to the first aspect or the second aspect.

[0120] In a tenth aspect, an embodiment of the present disclosure proposes a computer program, which, when executed on a computer, enables the computer to execute the method described in the optional implementation of the first and second aspects.

[0121] In an eleventh aspect, an embodiment of the present disclosure provides a chip or a chip system, wherein the chip or chip system includes a processing circuit configured to execute the method described in the optional implementation of the first and second aspects above.

[0122] It is understandable that the above-mentioned terminals, network devices, communication systems, storage media, program products, computer programs, chips, or chip systems are all used to perform the methods proposed in the embodiments of the present disclosure. Therefore, the beneficial effects that can be achieved can refer to the beneficial effects of the corresponding methods and will not be repeated here.

[0123] The embodiments of the present disclosure are not exhaustive and are merely illustrative of some embodiments, and are not intended to be a specific limitation on the scope of protection of the present disclosure. In the absence of contradiction, each step in a certain 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 certain embodiment can also be implemented as an independent embodiment, and the order of the steps in a certain embodiment can be arbitrarily exchanged. In addition, the optional implementation methods in a certain embodiment can be arbitrarily combined; in addition, the embodiments can be arbitrarily combined. For example, some or all steps of different embodiments can be arbitrarily combined, and a certain embodiment can be arbitrarily combined with the optional implementation methods of other embodiments.

[0124] In each embodiment of the present disclosure, unless otherwise specified or provided for by logic, the terms and / or descriptions between the embodiments are consistent and can be referenced by each other. The technical features in different embodiments can be combined to form a new embodiment based on their inherent logical relationships.

[0125] The terms used in the embodiments of the present disclosure are only for the purpose of describing specific embodiments and are not intended to limit the present disclosure.

[0126] In the embodiments of the present disclosure, unless otherwise specified, elements expressed in the singular, such as "a", "an", "the", "above", "said", "the", "the", etc., may mean "one and only one", or "one or more", "at least one", etc. For example, when using articles such as "a", "an", "the" in English in translation, the noun following the article may be understood as a singular expression or a plural expression.

[0127] In the embodiments of the present disclosure, “plurality” refers to two or more.

[0128] In some embodiments, the terms "at least one," "one or more," "a plurality of," "multiple," etc. may be used interchangeably.

[0129] In some embodiments, descriptions such as "at least one of A and B," "A and / or B," "A in one case, B in another case," or "in response to one case A, in response to another case B" may include the following technical solutions depending on the situation: in some embodiments, A (A is executed independently of B); in some embodiments, B (B is executed independently of A); in some embodiments, execution is selected from A and B (A and B are selectively executed); and in some embodiments, A and B (both A and B are executed). The above is also applicable when there are more branches such as A, B, and C.

[0130] In some embodiments, "A or B" and other descriptions may include the following technical solutions depending on the situation: in some embodiments, A (A is executed independently of B); in some embodiments, B (B is executed independently of A); in some embodiments, execution is selected from A and B (A and B are selectively executed). The above is also applicable when there are more branches such as A, B, C, etc.

[0131] The prefixes such as "first" and "second" in the embodiments of the present disclosure are only used to distinguish different description objects and do not constitute any restriction on the position, order, priority, quantity or content of the description objects. For the statement of the description object, please refer to the description in the context of the claims or embodiments, and no unnecessary restriction should be constituted due to the use of prefixes. For example, if the description object is a "field", the ordinal number before the "field" in the "first field" and the "second field" does not limit the position or order between the "fields". "First" and "second" do not limit whether the "fields" they modify are in the same message, nor do they limit the order of the "first field" and the "second field". For another example, if the description object is a "level", the ordinal number before the "level" in the "first level" and the "second level" does not limit the priority between the "levels". For another example, the number of description objects is not limited by the ordinal number and can be one or more. Taking "first device" as an example, the number of "devices" can be one or more. In addition, the objects modified by different prefixes can be the same or different. For example, if the description object is "device", then the "first device" and the "second device" can be the same device or different devices, and their types can be the same or different; for another example, if the description object is "information", then the "first information" and the "second information" can be the same information or different information, and their contents can be the same or different.

[0132] In some embodiments, “including A,” “comprising A,” “used to indicate A,” and “carrying A” can be interpreted as directly carrying A or indirectly indicating A.

[0133] In some embodiments, terms such as "in response to...", "in response to determining...", "in the case of...", "at the time of...", "when...", "if...", "if...", etc. can be used interchangeably.

[0134] In some embodiments, terms such as "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 less than", and "above" can be replaced with each other, and terms such as "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" can be replaced with each other.

[0135] In some embodiments, devices and equipment can be interpreted as physical or virtual, and their names are not limited to the names recorded in the embodiments. In some cases, they can also be understood as "equipment", "device", "circuit", "network element", "node", "function", "unit", "section", "system", "network", "chip", "chip system", "entity", "subject", etc.

[0136] In some embodiments, "network" can be interpreted as devices included in the network, such as access network equipment, core network equipment, etc.

[0137] In some embodiments, "access network device (AN device)" may also be referred to as "radio access network device (RAN device)", "base station (BS)", "radio base station", "fixed station", and in some embodiments may also be understood as "node", "access point", "transmission point (TP)", "reception point (RP)", "transmission and / or 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", "bandwidth part (BWP)", etc.

[0138] In some embodiments, "terminal" or "terminal device" may be referred to as "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, client, etc.

[0139] In some embodiments, obtaining data, information, etc. may comply with the laws and regulations of the country where the data is obtained.

[0140] In some embodiments, data, information, etc. may be obtained with the user's consent.

[0141] In addition, each element, each row, or each column in the table of the embodiment of the present disclosure can be implemented as an independent embodiment, and the combination of any elements, any rows, and any columns can also be implemented as an independent embodiment.

[0142] FIG1a is a schematic diagram showing the architecture of a communication system according to an embodiment of the present disclosure.

[0143] As shown in FIG. 1 a , a communication system 100 includes a terminal 101 and a network device 102 .

[0144] In some embodiments, the terminal 101 includes, for example, a mobile phone, a wearable device, an Internet of Things device, a car with communication function, a smart car, a tablet computer, a computer with wireless transceiver function, a virtual reality (VR) terminal device, an augmented reality (AR) terminal device, a wireless terminal device in industrial control, a wireless terminal device in self-driving, a wireless terminal device in remote medical surgery, a wireless terminal device in a smart grid, a wireless terminal device in transportation safety, a wireless terminal device in a smart city, and at least one of a wireless terminal device in a smart home, but is not limited thereto.

[0145] In some embodiments, when the network device 102 is a network device, the network device may include at least one of an access network device and a core network device.

[0146] In some embodiments, the access network device is, for example, a node or device that accesses a terminal to a wireless network. The access network device may include an evolved NodeB (eNB), a next generation evolved NodeB (ng-eNB), a next generation NodeB (gNB), a node B (NB), a home node B (HNB), a home evolved nodeB (HeNB), a wireless backhaul device, a radio network controller (RNC), a base station controller (BSC), a base transceiver station (BTS), a base band unit (BBU), a mobile switching center, a base station in a 6G communication system, an open base station (Open RAN), a cloud base station (Cloud RAN), a base station in other communication systems, and at least one of an access node in a wireless fidelity (WiFi) system, but is not limited thereto.

[0147] In some embodiments, the technical solution of the present disclosure can be applied to the Open RAN architecture. In this case, the interfaces between or within the access network devices involved in the embodiments of the present disclosure can be transformed into internal interfaces of the Open RAN, and the processes and information interactions between these internal interfaces can be implemented through software or programs.

[0148] In some embodiments, the access network device can be composed of a centralized unit (CU) and a distributed unit (DU), where the CU can also be called a control unit. The CU-DU structure can be used to split the protocol layer of the access network device, with the functions of some protocol layers centrally controlled by the CU, and the functions of the remaining part or all of the protocol layers distributed in the DU, which is centrally controlled by the CU, but is not limited to this.

[0149] In some embodiments, the core network device can be a device including one or more network elements, or it can be multiple devices or device groups, each including all or part of one or more network elements. The network element can be virtual or physical. The core network includes, for example, at least one of the Evolved Packet Core (EPC), the 5G Core Network (5GCN), and the Next Generation Core (NGC). Alternatively, the core network device refers to a network element with a specific function, such as the Access Management Function (AMF), the Service Management Function (SMF), etc.

[0150] It can be understood that the communication system described in the embodiment of the present disclosure is for the purpose of more clearly illustrating the technical solution of the embodiment of the present disclosure, and does not constitute a limitation on the technical solution provided by the embodiment of the present disclosure. Ordinary technicians in this field can know that with the evolution of the system architecture and the emergence of new business scenarios, the technical solution provided by the embodiment of the present disclosure is also applicable to similar technical problems.

[0151] The following embodiments of the present disclosure may be applied to the communication system 100 shown in FIG. 1 a , or a partial body thereof, but are not limited thereto.

[0152] The entities shown in Figure 1a are examples. The communication system may include all or part of the entities in Figure 1a, or may include other entities outside Figure 1a. The number and form of the entities are arbitrary. The connection relationship between the entities is an example. The entities may be connected or disconnected, and the connection may be in any manner, which may be direct or indirect, and may be wired or wireless.

[0153] The embodiments of the present disclosure 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 (registered trademark)), CDMA2000, Ultra Mobile Broadband (UMB), IEEE 802.11 (Wi-Fi (registered trademark)), IEEE 802.16 (WiMAX (registered trademark)), IEEE 802.20, Ultra-WideBand (UWB), Bluetooth (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 utilizing other communication processing methods, and next-generation systems based on and extending these. Furthermore, multiple systems may be combined (for example, a combination of LTE or LTE-A with 5G).

[0154] In an embodiment of the present disclosure, as shown in FIG1b , before time T1, i.e., while timer T331 (T331timer) is running, terminal 101 is in idle mode. The terminal may perform early measurements of the network (NW), such as carriers or cells configured by network device 102, to obtain EMR. This idle measurement is also referred to as an EMR measurement, and terminal 101 may store the EMR measurement result. Starting at time T1, i.e., when timer T331 expires or times out, terminal 101 ceases EMR measurement to save power. At time T2, i.e., when terminal 101 enters connected mode, terminal 101 may report the EMR measurement results taken in idle mode.

[0155] In Release 16 (Rel-16 or R16), terminal 101 reports EMR measurement results directly after entering connected mode. However, there may be a long period of time between the expiration of T331 and the entry of terminal 101 into connected mode. For example, the interval between T1 and T2 may be very long, and the measurement results obtained before T1 may no longer be accurate.

[0156] In R18, terminal 101 can check whether the measurement result is valid based on a time threshold configured by network device 102. For example, if the time difference between T1 and T2 is less than the time threshold, terminal 101 will assume the measurement result is valid. Otherwise, terminal 101 will consider the measurement result invalid and may not report the invalid result. If terminal 101 does not report the EMR, network device 102 will configure terminal 101 to perform measurements after entering connected mode, which will result in a significant delay in CA configuration.

[0157] Furthermore, network device 102 faces significant challenges in configuring the time length corresponding to the time threshold. For example, if the time threshold is short (e.g., 5 seconds), the EMR measurement results will be invalid in most cases because the transition from T1 to T2 will last a considerable amount of time. This will cause terminal 101 to no longer report EMRs, rendering idle mode measurement results useless. For another example, if the time threshold is long (e.g., several minutes), accurate measurement results may not be filtered out due to the excessive time, resulting in inaccurate reported measurement results.

[0158] In the disclosed embodiment, the accuracy of the EMR measurement results helps to establish CA more quickly when the terminal 101 enters the connected mode. If the EMR measurement results are inaccurate, the network device 102 will configure an incorrect CA. Therefore, the method of reporting EMR by the terminal 101 needs to be enhanced.

[0159] FIG2a is an interactive diagram illustrating a method for transmitting EMR according to an embodiment of the present disclosure. As shown in FIG2a , an embodiment of the present disclosure relates to a method for transmitting EMR, the method comprising:

[0160] Step S2101: While the timer is running, the terminal 101 performs early measurement.

[0161] In some embodiments, the timer is timer T331, which is used to indicate the duration for the terminal 101 to perform EMR measurement.

[0162] Optionally, during the timer running period, terminal 101 is in the RRC idle state. For example, referring to FIG2 d , terminal 101 enters the idle state at time T0, and the timer may be started. The timer running period may be from time T0 to time T1, and the timer running period may be from time T0 to time T1.

[0163] In some embodiments, the terminal 101 performing early measurement may also be referred to as performing EMR measurement.

[0164] Optionally, the EMR measurement of terminal 101 may include measurement of a serving cell and measurement of a configured carrier or neighboring cell, where the serving cell and the carrier or neighboring cell have different frequencies. Accordingly, terminal 101 may perform EMR measurement to obtain measurement results of the serving cell and measurement results of the carrier or neighboring cell.

[0165] Optionally, when the timer ends, the terminal 101 will stop measuring the carrier or neighboring cells, but will keep measuring the serving cell.

[0166] In some embodiments, the network device 102 may configure a carrier or cell configured by EMR for the terminal 101, where the carrier or cell may be a neighboring cell of the serving cell of the terminal 101. For example, referring to the example of FIG2d , the network device 102 may configure carriers CC1 and CC2 to be measured.

[0167] Optionally, the terminal 101 may perform EMR measurement between time T0 and T1, such as performing EMR measurement on CC1 (EMR CC1 measurement) and CC2 (EMR CC2 measurement), and performing serving cell measurement. The serving cell measurement is not restricted by the timer.

[0168] In some embodiments, the measurement result performed by terminal 101 may be a reference signal received power (RSRP). For example, the measurement result between time T0 and time T1 includes: the RSRP of the serving cell, the RSRP of CC1, and the RSRP of CC2. The RSRP of CC1 and the RSRP of CC2 are collectively referred to as the RSRP of the EMR carrier or cell or the measurement result of the EMR carrier or cell.

[0169] In some embodiments, when the timer expires, such as at time T1, the terminal 101 may save the obtained RSRP. For example, the measurement result of the serving cell is recorded as RSRP serving_T1 , the measurement result of EMR carrier or cell is recorded as RSRP EMR_T1 .

[0170] In step S2102, the terminal 101 determines a first variation based on the measurement result of the serving cell during the timer running period and the measurement result of the serving cell after the end time.

[0171] In some embodiments, as shown in FIG2d , the end time is T1. After the timer expires, such as between T1 and T2, the terminal 101 still performs the measurement of the serving cell, but stops the EMR measurement of EMR carriers or cells such as CC1 and CC2.

[0172] Optionally, the measurement result obtained by the terminal 101 performing serving cell measurement between time T1 and T2 can be recorded as RSRP serving_T1～T2 .

[0173] Optionally, the terminal 101 may determine a first change amount at time T2, and the first change amount may be (RSRP serving_T1～T2 - RSRP serving_T1 ).

[0174] Optionally, at time T2, terminal 101 enters a connected state.

[0175] In some embodiments, the AI ​​model may be configured on the terminal 101 or network device 102 side.

[0176] Optionally, the input of the AI ​​model is: a first change amount, where the first change amount is a change amount of a serving cell measurement result;

[0177] The prediction result of the AI ​​model is: the second change amount, which is the change amount of the measurement result corresponding to the carrier configured by the network device for early measurement.

[0178] For example, after determining the first change amount, the terminal 101 converts the first change amount (RSRP serving_T1～T2 - RSRP serving_T1 ) is input to the AI ​​model, and the prediction result is output by the AI ​​model to predict the RSRP change of the cell / carrier of the EMR. If the prediction result is the second change amount, it is recorded as RSRP EMR_variation .

[0179] In some embodiments, the training of the AI ​​model can be done in advance (off line) or online before each application (on line).

[0180] In some embodiments, the change trends of the serving cell measurement result of terminal 101 and the EMR carrier or cell measurement result are consistent or similar, so the change amount of the EMR carrier or cell measurement result can be predicted based on the change amount of the serving cell measurement result.

[0181] In step S2103 , the terminal 101 determines the first EMR according to the second variation and the second EMR.

[0182] Optionally, the second EMR includes a measurement result obtained by the terminal performing early measurement on the carrier during the timer running.

[0183] Optionally, the first EMR is used to indicate a valid EMR.

[0184] In some embodiments, the second EMR includes the measurement result of the terminal 101 between time T0 and T1, for example, the second EMR includes the RSRP of the serving cell and the RSRP of the EMR carrier or cell. Since the terminal 101 can always measure the serving cell, the second EMR includes the RSRP of the EMR carrier or cell, that is, the RSRP EMR_T1 For example.

[0185] Optionally, the second change amount predicted by the AI ​​model is RSRP EMR_variation , based on the prediction results of the AI ​​model, the RSRP of the changed or updated EMR carrier or cell is: RSRP EMR_new =RSRP EMR_T1 +RSRP EMR_variation The first EMR includes the RSRP of the updated EMR carrier or cell.

[0186] Optionally, the first EMR may further include the RSRP of the serving cell most recently measured by the terminal.

[0187] Step S2104 : Terminal 101 sends a first EMR to network device 102 .

[0188] Optionally, the terminal 101 may be a new capability terminal supporting the above-mentioned AI model enhancement.

[0189] Optionally, this capability may be recorded as an advanced EMR capability.

[0190] In some embodiments, the terminal 101 may update and report the RSRP of the EMR carrier or cell based on the AI ​​model.

[0191] In some embodiments, the terminal 101 does not need to check whether the time interval between the times T1 and T2 is less than the time threshold.

[0192] Optionally, the time interval between the end time and the time when the terminal enters the RRC connected state meets or does not meet a time threshold, and the time threshold is used to indicate the valid duration of the EMR.

[0193] In some embodiments, the first EMR meets a measurement accuracy requirement defined by a protocol. For example, the RSRP of the EMR carrier or cell to be reported in the first EMR meets a threshold defined by a protocol, or meets a signal-to-noise ratio defined by a protocol.

[0194] Optionally, if the first EMR does not meet the accuracy requirement defined by the protocol, it will be considered invalid and the terminal 101 will not report it.

[0195] In some embodiments, the network device receives a first EMR and may perform CA configuration according to the first EMR.

[0196] In some embodiments, the names of information, etc. are not limited to the names described in the embodiments, and terms such as "information", "message", "signal", "signaling", "report", "configuration", "indication", "instruction", "command", "channel", "parameter", "domain", and "field" can be used interchangeably.

[0197] In some embodiments, "obtain", "get", "get", "receive", "transmit", "bidirectional transmission", "send and / or receive" can be interchangeable, and can be interpreted as receiving from other entities, obtaining from protocols, obtaining from higher layers, obtaining by self-processing, autonomous implementation, etc.

[0198] In some embodiments, terms such as "send", "transmit", "report", "download", "transmit", "bidirectional transmission", "send and / or receive" can be used interchangeably.

[0199] In some embodiments, the terms "radio", "wireless", "radio access network (RAN)", "access network (AN)", "RAN-based" and the like may be used interchangeably.

[0200] In some embodiments, terms such as "moment", "time point", "time", and "time position" can be replaced with each other, and terms such as "duration", "period", "time window", "window", and "time" can be replaced with each other.

[0201] In some embodiments, the terms "component carrier (CC)", "cell", "frequency carrier", "carrier frequency" and the like can be used interchangeably.

[0202] In some embodiments, terms such as "certain", "preset", "preset", "setting", "indicated", "a certain", "any", and "first" can be interchangeable. "Specific A", "preset A", "preset A", "setting A", "indicated A", "a certain A", "any A", and "first A" can be interpreted as A pre-specified in a protocol, etc., or as A obtained through setting, configuration, or indication, etc., or as specific A, a certain A, any A, or first A, etc., but not limited to this.

[0203] In some embodiments, the determination or judgment can be performed by a value represented by 1 bit (0 or 1), or by a true or false value (Boolean value) represented by true or false, or by comparison of numerical values ​​(for example, comparison with a predetermined value), but is not limited thereto.

[0204] 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 after receiving it; "not expecting to send" can be interpreted as not sending, or as sending but not expecting the recipient to respond to the content sent.

[0205] The method involved in the embodiment of the present disclosure may include at least one of steps S2101 to S2104; for example, the method includes steps S2103 to S2104.

[0206] In some embodiments, at least one of steps S2101 to S2102 is optional, and one or more of these steps may be omitted or replaced in different embodiments.

[0207] In some embodiments, reference may be made to other optional implementations described before or after the description corresponding to FIG. 2 a .

[0208] FIG2b is an interactive diagram illustrating a method for transmitting EMR according to an embodiment of the present disclosure. As shown in FIG2b , an embodiment of the present disclosure relates to a method for transmitting EMR, the method comprising:

[0209] Step S2201: While the timer is running, the terminal 101 performs EMR measurement.

[0210] In some embodiments, the implementation of step S2201 can refer to the optional implementation of step S2101 and will not be repeated here.

[0211] In step S2202 , the terminal 101 determines a valid first EMR according to the AI ​​model.

[0212] Optionally, the first EMR may include a measurement result of a valid serving cell and / or a measurement result of a valid EMR carrier or cell.

[0213] In some embodiments, terminal 101 determines the measurement results of the EMR carrier or cell predicted by the AI ​​model.

[0214] In some embodiments, the input of the AI ​​model is: the measurement result of the serving cell after the end time; the prediction result of the AI ​​model is: the measurement result corresponding to the carrier used for early measurement after the end time; wherein the first EMR includes the input and the prediction result.

[0215] Optionally, in combination with the description of the foregoing embodiment and with reference to FIG2e , the end time is T1.

[0216] Optionally, in combination with the description of the foregoing embodiment and with reference to FIG2e , between time T1 and T2 , the terminal 101 will still perform measurements of the serving cell, and the measurement results of the serving cell during this time, such as the RSRP of the serving cell, can be used as input to the AI ​​model.

[0217] Optionally, the output result of the model is a measurement result of the EMR carrier or cell, such as the RSRP of the EMR carrier or cell, that is, the RSRP of the EMR carrier or cell valid during the time period from T1 to T2.

[0218] Optionally, the first EMR includes the measurement result of the serving cell in the time period from T1 to T2 and the measurement result of the EMR carrier or cell predicted by the AI ​​model.

[0219] In some embodiments, as shown in FIG2e , before applying the AI ​​model, that is, before the inference phase of the AI ​​model, the terminal 101 may perform model training. For example, the terminal 101 may perform online training of the model between time T0 and T1.

[0220] Optionally, the training data of the AI ​​model includes: measurement results of the serving cell during the timer operation, and measurement results corresponding to the carrier during the timer operation.

[0221] In one example, as shown in Figure 2e, terminal 101 measures the RSRP of the serving cell and the EMR carrier or cell from time T0 to T1. Terminal 101 performs online training of an AI model based on these two RSRP values. During the training process, the input of the AI ​​model is the RSRP of the serving cell measured from time T0 to T1, and the output is the RSRP of the EMR carrier or cell from time T0 to T1.

[0222] In some embodiments, the variation trends of the serving cell measurement result of the terminal 101 and the EMR carrier or cell measurement result are consistent or similar, and thus the EMR carrier or cell measurement result can be predicted based on the serving cell measurement result.

[0223] Step S2203 : Terminal 101 sends a first EMR to network device 102 .

[0224] Optionally, the implementation of step S2203 may refer to the optional implementation of step S2104, which will not be repeated here.

[0225] Optionally, after time T2, for the new capability terminal 101, the terminal 101 will report the RSRP of the valid or updated EMR carrier or cell through the first EMR.

[0226] The method involved in the embodiment of the present disclosure may include at least one of steps S2201 to S2203; for example, the method includes steps S2202 to S2203.

[0227] In some embodiments, step S2201 is optional, and one or more of these steps may be omitted or replaced in different embodiments.

[0228] In some embodiments, reference may be made to other optional implementations described before or after the description corresponding to FIG. 2 b .

[0229] FIG2c is an interactive diagram illustrating a method for transmitting EMR according to an embodiment of the present disclosure. As shown in FIG2b , an embodiment of the present disclosure relates to a method for transmitting EMR, the method comprising:

[0230] Step S2301 : The network device 102 sends information indicating a time threshold to the terminal 101 .

[0231] Optionally, when the terminal 101 enters the RRC idle state, the network device 102 indicates a time threshold to the terminal 101.

[0232] In some embodiments, the time threshold is determined based on AI model prediction.

[0233] In some embodiments, the input of the AI ​​model is: measurement results of the serving cell corresponding to different time units; the prediction result of the AI ​​model is: an effective time threshold, which is used to indicate the effective duration of the EMR.

[0234] Optionally, the time unit may be a time slot, and the measurement result may be RSRP. The measurement results of different time units may express RSRP changes caused by changes in the mobility state of terminal 101. Therefore, the measurement results of the serving cell in different time units may represent the mobility state of terminal 101, such as the moving distance or speed.

[0235] Optionally, as shown in FIG. 2 f , the network device 102 may predict the time threshold before the terminal 101 enters the idle state, that is, predict the time threshold before time T0 .

[0236] Optionally, network device 102 may configure the predicted time threshold for terminal 101 at time T0, which may be more suitable for the terminal in the mobility state. For example, if terminal 101 is moving faster, the predicted time threshold may be shorter to ensure the validity and accuracy of the measurement result.

[0237] In some embodiments, terminal 101 receives the time threshold.

[0238] In some embodiments, step S2301 may be omitted. For example, if the terminal 101 predicts the time threshold by itself and reports the time threshold to the network device, step S2301 may be omitted and replaced by step S2302.

[0239] In step S2302 , the terminal 101 sends information indicating a time threshold to the network device 102 .

[0240] Optionally, as shown in FIG2f , the method for predicting the time threshold on the terminal side may refer to the method on the network device 102 side, which will not be repeated here.

[0241] Step S2303: While the timer is running, the terminal 101 performs EMR measurement.

[0242] In some embodiments, the implementation of step S2303 can refer to the optional implementation of step S2101 and will not be repeated here.

[0243] Optionally, as shown in FIG2f , terminal 101 measures the serving cell and the EMR carrier or cell before time T1 and stores all measurement results. The EMR may include the measurement results of the serving cell and the EMR carrier or cell between time T0 and T1.

[0244] Step S2304: Terminal 101 determines a valid first EMR according to a time threshold.

[0245] Optionally, when the time interval between the time T1 when the EMR is obtained and the time T2 when the terminal 101 enters the connected state is less than a time threshold, the EMR is valid, that is, the first EMR.

[0246] Optionally, the first EMR satisfies:

[0247] It is obtained before the end time, and the time interval between the end time and the time when the terminal enters the RRC connected state is less than the time threshold.

[0248] The end time is T1.

[0249] Step S2305 : Terminal 101 sends a first EMR to network device 102 .

[0250] Optionally, the implementation of step S2305 can refer to the optional implementation of step S2104, which will not be repeated here.

[0251] The method involved in the embodiment of the present disclosure may include at least one of steps S2301 to S2305.

[0252] In some embodiments, steps S2301 and S2302 are parallel solutions, and either one of them can be executed.

[0253] In some embodiments, step S2303 is optional, and one or more of these steps may be omitted or replaced in different embodiments.

[0254] In some embodiments, reference may be made to other optional implementations described before or after the description corresponding to FIG. 2c.

[0255] FIG3 is a flow chart of a method for sending an EMR according to an embodiment of the present disclosure. As shown in FIG3 , an embodiment of the present disclosure relates to a method for sending an EMR, which is executed by a terminal 101 and includes:

[0256] Step S3101: After the end time of the timer, determine the valid first EMR based on the prediction result of the artificial intelligence AI model.

[0257] In some embodiments, the implementation of step S3101 can refer to the implementation of steps S2102 to S2103, and will not be repeated here.

[0258] In some embodiments, the implementation of step S3101 can refer to the implementation of step S2202 and will not be repeated here.

[0259] In some embodiments, the implementation of step S3101 may refer to the implementation of steps S2301 and S2304, or refer to the implementation of steps S2302 and S2304, and will not be repeated here.

[0260] Optionally, the terminal is in an RRC idle state during the timer running.

[0261] Step S3102: Enter the RRC connection state and send a first EMR to the network device 102.

[0262] In some embodiments, the implementation of step S3102 may refer to the implementation of step S2104, S2203 or S2305, and will not be repeated here.

[0263] In some embodiments, reference may be made to other optional implementations described before or after the description corresponding to FIG. 3 .

[0264] FIG4 is a flow chart of a method for receiving an EMR according to an embodiment of the present disclosure. As shown in FIG4 , an embodiment of the present disclosure relates to a method for receiving an EMR, which is performed by a network device 102 and includes:

[0265] Step S4101: Receive the first EMR sent by terminal 101.

[0266] In some embodiments, the implementation of step S4101 may refer to the implementation of step S2104, S2203 or S2305, and will not be repeated here.

[0267] Optionally, the terminal is in an RRC connected state, and the first EMR is a valid EMR determined by the terminal according to the prediction result of the AI ​​model after the end time of the timer, wherein the terminal is in an RRC idle state during the timer running.

[0268] In some embodiments, reference may be made to other optional implementations described before or after the description corresponding to FIG. 4 .

[0269] In the method of the embodiment of the present disclosure, UE capabilities and UE behaviors are defined for enhanced EMR reporting. The UE can predict the RSRP of the carrier / cell configured for EMR based on the RSRP measurement of the serving cell through an AI method, and then the UE reports the updated EMR result when entering the connected mode; alternatively, the NW or UE predicts the mobility state of the UE through an AI method to ensure that the time threshold is correct.

[0270] Optionally, UE corresponds to the terminal 101 in the aforementioned embodiment, and NW corresponds to the network device 102 in the aforementioned embodiment. To facilitate understanding of the embodiments of the present disclosure, some specific implementation plans are listed below:

[0271] Implementation 1: EMR RSRP Change Prediction

[0272] Referring to Figure 2d, the UE behavior includes:

[0273] During T0-T1: the UE measures the serving cell and carrier / cell of the EMR;

[0274] At time T1: UE stores the RSRP results of the serving cell and carrier / cell of the EMR, e.g. RSRP serving_T1 and RSRP EMR_T1 ;

[0275] During T1-T2: UE measures the serving cell

[0276] At T2, terminal 101 may perform the following steps 1 to 4:

[0277] Step 1: The UE calculates the RSRP change of the serving cell;

[0278] Step 2: The UE inputs the RSRP change of the serving cell into the AI ​​model and uses the AI ​​model to predict the RSRP change of the EMR cell / carrier, such as RSRP EMR_variation ;

[0279] Step 3: The UE calculates the updated RSRP of the EMR cell / carrier and reports it, for example:

[0280] RSRP EMR_new =RSRP EMR_T1 +RSRP EMR_variation ;

[0281] Step 4: For new-capability UEs, the UE reports the RSRP of the serving cell and the EMR cell / carrier.

[0282] Optionally, through the above steps, the new RSRP of the EMR carrier / cell will be updated and reported, and the UE does not need to check whether the time interval is less than the time threshold configured for validity.

[0283] Optionally, the measurement reporting requirement may be that for UEs supporting advanced EMR capabilities, the UE shall be able to report valid measurement results upon RRC establishment completion. A measurement result is considered valid if the following conditions are met:

[0284] The measurement results meet the measurement accuracy requirements of the measurement instance;

[0285] Otherwise, the measurement result is considered invalid. The UE shall not report invalid measurement results.

[0286] Implementation 2: RSRP Prediction for EMR

[0287] Referring to Figure 2e, the UE behavior is as follows:

[0288] Step 1: From T0 to T1, the UE obtains the RSRP from the serving cell and the EMR carrier / cell. The UE can perform online training on the AI ​​model. The input and output of the AI ​​model are the RSRP of the serving cell and the RSRP of the EMR carrier / cell, respectively.

[0289] Step 2: From T1 to T2, the UE will still perform RSRP measurement on the serving cell and stop measuring the EMR carrier / cell.

[0290] The UE will apply the AI ​​model based on the measurements of the serving cell to predict the RSRP of the EMR carrier / cell.

[0291] Step 3: After T2, for new-capability UEs, the UE will report the updated RSRP of the EMR carrier / cell via the new updated RSRP.

[0292] Implementation 3: Time threshold prediction for EMR

[0293] As shown in Figure 2f, before the UE enters idle mode, the NW can predict the UE's mobility status through the AI ​​model and then configure Tthreshold. Refer to the following steps:

[0294] Step 1: Before the UE enters the idle mode, the NW can predict the UE's mobility state and then determine the effective time threshold.

[0295] Step 2: When the UE enters the idle mode, the NW will configure the valid time threshold.

[0296] Step 3: The UE will measure all CCs before T1 and store all results.

[0297] Step 4: At T2, the UE checks the duration between T1 and T2. If the duration is less than Tthreshold, the result is valid and the UE reports the result.

[0298] Optionally, it is also possible that the UE predicts the time threshold and feeds it back to the NW.

[0299] The embodiments of the present disclosure further provide an apparatus for implementing any of the above methods. For example, an apparatus is provided, comprising units or modules for implementing each step performed by a terminal in any of the above methods. For another example, another apparatus is provided, comprising units or modules for implementing each step performed by a network device (e.g., an access network device, a core network function node, a core network device, etc.) in any of the above methods.

[0300] It should be understood that the division of the various units or modules in the above device is merely a division of logical functions. In actual implementation, they may be fully or partially integrated into a physical entity, or they may be physically separated. In addition, the units or modules in the device may be implemented in the form of a processor calling software: for example, the device includes a processor, the processor is connected to a memory, and the memory stores instructions. The processor calls the instructions stored in the memory to implement any of the above methods or implement the functions of the various units or modules of the above device, wherein the processor is, for example, a general-purpose processor, such as a central processing unit (CPU) or a microprocessor, and the memory is a memory within the device or a memory outside the device. Alternatively, the units or modules in the device can be implemented in the form of hardware circuits, and the functions of some or all of the units or modules can be realized by designing the hardware circuits. The above-mentioned hardware circuits can be understood as one or more processors; for example, in one implementation, the above-mentioned hardware circuit is an application-specific integrated circuit (ASIC), which realizes the functions of some or all of the above units or modules by designing the logical relationship of the components in the circuit; for example, in another implementation, the above-mentioned hardware circuit can be realized by a programmable logic device (PLD). Taking a field programmable gate array (FPGA) as an example, it can include a large number of logic gate circuits, and the connection relationship between the logic gate circuits is configured by configuring the configuration file, thereby realizing the functions of some or all of the above units or modules. All units or modules of the above devices can be realized in the form of software called by the processor, or in the form of hardware circuits, or in part by the form of software called by the processor, and the rest by hardware circuits.

[0301] In the embodiments of the present disclosure, the processor is a circuit with signal processing capabilities. In one implementation, the processor can be a circuit with instruction reading and execution 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 relationship of the hardware circuit. The logical relationship of the above-mentioned hardware circuit is fixed or reconfigurable. For example, the processor is a hardware circuit implemented by 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 implementing the hardware circuit configuration 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 a hardware circuit designed for artificial intelligence, which can be understood as an ASIC, such as a neural network processing unit (NPU), a tensor processing unit (TPU), a deep learning processing unit (DPU), etc.

[0302] Figure 5a is a schematic diagram of the structure of a terminal proposed in an embodiment of the present disclosure. As shown in Figure 5a, terminal 5100 may include at least one of a transceiver module 5101 and a processing module 5102. In some embodiments, processing module 5102 is configured to determine a valid first EMR based on the prediction result of the AI ​​model after a timer expires, wherein the terminal is in an RRC idle state during the timer. Transceiver module 5101 is configured to send the first EMR to a network device upon entering an RRC connected state.

[0303] Optionally, the transceiver module 5101 is configured to execute at least one of the communication steps of sending and / or receiving performed by the terminal 101 in any of the above methods, which are not described in detail here. Optionally, the processing module 5102 is configured to execute at least one of the other steps performed by the terminal 101 in any of the above methods, which are not described in detail here.

[0304] Figure 5b is a schematic diagram of the structure of a terminal proposed in an embodiment of the present disclosure. As shown in Figure 5b, network device 5200 may include at least one of a transceiver module 5201 and a processing module 5202. In some embodiments, transceiver module 5201 is configured to receive a first EMR sent by a terminal, wherein the terminal is in an RRC connected state, and the first EMR is a valid EMR determined by the terminal based on the prediction result of the AI ​​model after the end time of a timer, wherein the terminal is in an RRC idle state during the timer.

[0305] Optionally, the transceiver module 5201 is configured to execute at least one of the communication steps of sending and / or receiving performed by the network device 102 in any of the above methods, which are not described in detail here. Optionally, the processing module 5202 is configured to execute at least one of the other steps performed by the network device 102 in any of the above methods, which are not described in detail here.

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

[0307] In some embodiments, the processing module can be a single module or include multiple submodules. Optionally, the multiple submodules each execute all or part of the steps required to be executed by the processing module. Optionally, the processing module and the processor can be interchangeable.

[0308] Figure 6a is a schematic diagram of the structure of a communication device 6100 proposed in an embodiment of the present disclosure. Communication device 6100 can be a network device (e.g., an access network device, a core network device, etc.), a terminal (e.g., a user equipment, etc.), a chip, a chip system, or a processor that supports a network device implementing any of the above methods, or a chip, a chip system, or a processor that supports a terminal implementing any of the above methods. Communication device 6100 can be used to implement the methods described in the above method embodiments. For details, please refer to the description of the above method embodiments.

[0309] As shown in Figure 6a, the communication device 6100 includes one or more processors 6101. The processor 6101 can be a general-purpose processor or a dedicated processor, for example, a baseband processor or a central processing unit. The baseband processor can be used to process the communication protocol and communication data, and the central processing unit can be used to control the communication device (such as a base station, a baseband chip, a terminal device, a terminal device chip, a DU or a CU, etc.), execute programs, and process program data. Optionally, the communication device 6100 is used to perform any of the above methods. Optionally, one or more processors 6101 are used to call instructions to enable the communication device 6100 to perform any of the above methods.

[0310] In some embodiments, the communication device 6100 further includes one or more transceivers 6102. When the communication device 6100 includes one or more transceivers 6102, the transceiver 6102 performs at least one of the communication steps, such as sending and / or receiving, in the above-described method, and the processor 6101 performs at least one of the other steps. In an optional embodiment, the transceiver may include a receiver and / or a transmitter, and the receiver and transmitter may be separate or integrated. Optionally, the terms transceiver, transceiver unit, transceiver, transceiver circuit, interface circuit, and interface may be used interchangeably; the terms transmitter, transmitting unit, transmitter, and transmitting circuit may be used interchangeably; and the terms receiver, receiving unit, receiver, and receiving circuit may be used interchangeably.

[0311] In some embodiments, the communication device 6100 further includes one or more memories 6103 for storing data. Alternatively, all or part of the memories 6103 may be located outside the communication device 6100. In alternative embodiments, the communication device 6100 may include one or more interface circuits 6104. Optionally, the interface circuits 6104 are connected to the memories 6103 and may be configured to receive data from the memories 6103 or other devices, or to send data to the memories 6103 or other devices. For example, the interface circuits 6104 may read data stored in the memories 6103 and send the data to the processor 6101.

[0312] The communication device 6100 described in the above embodiment may be a network device or a terminal, but the scope of the communication device 6100 described in the present disclosure is not limited thereto, and the structure of the communication device 6100 may not be limited by FIG. 6a. The communication device may be an independent device or may be part of a larger device. For example, the communication device may be: 1) an independent integrated circuit IC, or a chip, or a chip system or subsystem; (2) a collection of one or more ICs, optionally, the above IC collection may also include a storage component for storing data or programs; (3) an ASIC, such as a modem; (4) a module that can be embedded in other devices; (5) a receiver, a terminal device, an intelligent terminal device, a cellular phone, a wireless device, a handheld device, a mobile unit, an in-vehicle device, a network device, a cloud device, an artificial intelligence device, etc.; (6) others, etc.

[0313] FIG6b is a schematic diagram of the structure of a chip 6200 according to an embodiment of the present disclosure. If the communication device 6100 can be a chip or a chip system, reference can be made to the schematic diagram of the structure of the chip 6200 shown in FIG6b , but the present disclosure is not limited thereto.

[0314] The chip 6200 includes one or more processors 6201. The chip 6200 is configured to execute any of the above methods.

[0315] In some embodiments, chip 6200 further includes one or more interface circuits 6202. Terms such as interface circuit, interface, and transceiver pins may be used interchangeably. In some embodiments, chip 6200 further includes one or more memories 6203 for storing data. Alternatively, all or part of memory 6203 may be located external to chip 6200. Optionally, interface circuit 6202 is connected to memory 6203 and may be used to receive data from memory 6203 or other devices, or may be used to send data to memory 6203 or other devices. For example, interface circuit 6202 may read data stored in memory 6203 and send the data to processor 6201.

[0316] In some embodiments, the interface circuit 6202 performs at least one of the communication steps, such as sending and / or receiving, in the above-described method. For example, the interface circuit 6202 performing the communication steps, such as sending and / or receiving, in the above-described method means that the interface circuit 6202 performs data exchange between the processor 6201, the chip 6200, the memory 6203, or the transceiver device. In some embodiments, the processor 6201 performs at least one of the other steps.

[0317] The modules and / or devices described in various embodiments, such as virtual devices, physical devices, and chips, can be arbitrarily combined or separated according to circumstances. Optionally, some or all steps can also be performed collaboratively by multiple modules and / or devices, which is not limited here.

[0318] The present disclosure also proposes a storage medium having instructions stored thereon. When the instructions are executed on the communication device 6100, the communication device 6100 executes 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 is not limited thereto and may also be a storage medium readable by other devices. Optionally, the storage medium may be a non-transitory storage medium, but is not limited thereto and may also be a transient storage medium.

[0319] The present disclosure also provides a program product, which, when executed by the communication device 6100, enables the communication device 6100 to perform any of the above methods. Optionally, the program product is a computer program product.

[0320] The present disclosure also proposes a computer program, which, when executed on a computer, causes the computer to perform any one of the above methods. Industrial Applicability

[0321] The terminal determines the currently valid first EMR based on AI model prediction and reports the valid first EMR to the network device, so that the network device can always obtain the valid EMR, improving the accuracy of CA or DC configuration.

Claims

1. A method for sending an early measurement report, performed by a terminal, the method comprising: After the end time of the timer, determine a valid first EMR according to a prediction result of the artificial intelligence AI model, wherein during the timer running, the terminal is in a radio resource control RRC idle state; The terminal enters the RRC connected state and sends the first EMR to the network device.

2. The method according to claim 1, wherein The AI model is used to output the prediction result based on the input of the AI model, wherein: The input of the AI model is: a first change amount, where the first change amount is a change amount between a measurement result of an early measurement of the serving cell by the terminal during the timer running period and a measurement result of the serving cell measured by the terminal after the end time; The prediction result is: a second change amount, which is used to represent the change amount between the measurement result of the early measurement of the carrier by the terminal during the operation of the timer and the measurement result corresponding to the carrier after the end time, and the carrier is configured by the network device.

3. The method according to claim 2, wherein: Determining a valid first EMR based on the prediction result of the AI model includes: determining the first EMR based on the second variation and the second EMR; The second EMR includes a measurement result obtained by the terminal performing early measurement on the carrier during the running of the timer.

4. The method according to any one of claims 2 to 3, wherein: The time interval between the end time and the time when the terminal enters the RRC connected state meets or does not meet a time threshold, where the time threshold is used to indicate the valid duration of the EMR.

5. The method according to any one of claims 2 to 3, wherein: The first EMR meets the accuracy requirements defined by the protocol.

6. The method of claim 1, wherein: The AI model is used to output the prediction result based on the input of the AI model, wherein: The input of the AI model is: the measurement result of the terminal on the serving cell after the end time; The prediction result is: a measurement result corresponding to the carrier used for early measurement after the end time; The first EMR includes the input and the prediction result.

7. The method according to claim 6, wherein: The training data of the AI model includes: the measurement result of the serving cell during the operation of the timer, and the measurement result corresponding to the carrier during the operation of the timer.

8. The method of claim 1, wherein: The AI model is used to output the prediction result based on the input of the AI model, wherein: The input of the AI model is: measurement results of the serving cell corresponding to different time units; The prediction result is: a valid time threshold, where the time threshold is used to indicate the valid duration of the EMR.

9. The method of claim 8, wherein: The method further comprises: Receiving information sent by the network device for indicating the time threshold, wherein the time threshold is obtained by the network device based on the AI model prediction, and the terminal enters the RRC idle state; or, Information indicating the time threshold is sent to the network device, wherein the time threshold is obtained by the terminal based on the AI model prediction.

10. The method of claim 8, wherein: The first EMR meets the following conditions: The first EMR is obtained before the end time, wherein a time interval between the end time and the time when the terminal enters the RRC connected state is less than the time threshold.

11. A method for receiving an early measurement report, performed by a network device, the method comprising: A first EMR sent by a receiving terminal is received, wherein the terminal is in an RRC connected state, and the first EMR is a valid EMR determined by the terminal according to a prediction result of an AI model after an end time of a timer, wherein the terminal is in an RRC idle state during the timer operation.

12. The method of claim 11, wherein: The AI model is used to output the prediction result based on the input of the AI model, wherein: The input of the AI model is: a first change amount, where the first change amount is a change amount between a measurement result of an early measurement of the serving cell by the terminal during the timer running period and a measurement result of the serving cell measured by the terminal after the end time; The prediction result is: a second change amount, which is used to represent the change amount between the measurement result of the early measurement of the carrier by the terminal during the operation of the timer and the measurement result corresponding to the carrier after the end time, and the carrier is configured by the network device.

13. The method of claim 12, wherein: The first EMR is determined according to the second change and a second EMR, and the second EMR includes a measurement result obtained by the terminal performing early measurement on the carrier during the operation of the timer.

14. The method according to any one of claims 12 to 13, wherein: The time interval between the end time and the time when the terminal enters the RRC connected state meets or does not meet a time threshold, where the time threshold is used to indicate the valid duration of the EMR.

15. The method according to any one of claims 12 to 13, wherein: The first EMR meets the accuracy requirements defined by the protocol.

16. The method of claim 11, wherein: The AI model is used to output the prediction result based on the input of the AI model, wherein: The input of the AI model is: the measurement result of the terminal on the serving cell after the end time; The prediction result is: a measurement result corresponding to the carrier used for early measurement after the end time; The first EMR includes the input and the prediction result.

17. The method of claim 16, wherein: The training data of the AI model includes: the measurement result of the serving cell during the operation of the timer, and the measurement result corresponding to the carrier during the operation of the timer.

18. The method of claim 11, wherein: The AI model is used to output the prediction result based on the input of the AI model, wherein: The input of the AI model is: measurement results of the serving cell corresponding to different time units; The prediction result is: a valid time threshold, where the time threshold is used to indicate the valid duration of the EMR.

19. The method of claim 18, wherein: The method further comprises: Sending information indicating the time threshold to the terminal, wherein the time threshold is obtained by the network device based on the AI model prediction, and the terminal is in an RRC idle state; or, Receive information sent by the terminal to indicate the time threshold, wherein the time threshold is obtained by the terminal based on the AI model prediction.

20. The method of claim 18, wherein: The first EMR meets the following conditions: The first EMR is obtained by the terminal before the end time; The time interval between the end time and the time when the terminal enters the RRC connected state is less than the time threshold.

21. A terminal comprising: a processing module, configured to determine, after an end time of a timer, a valid first EMR according to a prediction result of the AI model, wherein the terminal is in an RRC idle state during the timer running; The transceiver module is configured to send the first EMR to the network device when entering the RRC connection state.

22. A network device comprising: A transceiver module is configured to receive a first EMR sent by a terminal, wherein the terminal is in an RRC connected state, and the first EMR is a valid EMR determined by the terminal according to a prediction result of an AI model after the end time of a timer, wherein the terminal is in an RRC idle state during the timer operation.

23. A terminal comprising: one or more processors; The terminal is configured to implement the method according to any one of claims 1 to 10.

24. A network device comprising: one or more processors; The network device is configured to implement the method according to any one of claims 11 to 20.

25. A communication system comprising a terminal and a network device, wherein: The terminal is configured to implement the method according to any one of claims 1 to 10; The network device is configured to implement the method according to any one of claims 11 to 20.

26. A storage medium storing instructions, wherein: When the instruction is executed on a communication device, the communication device is caused to perform the method according to any one of claims 1 to 10 or any one of claims 11 to 20.

27. A program product, wherein When the program product is executed by a communication device, the communication device is caused to execute the method according to any one of claims 1 to 10 or any one of claims 11 to 20.

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