Wireless communication method, terminal device, and network device

Abstract

The present application provides a wireless communication method, a terminal device, and a network device. The method comprises: a terminal device receives first information sent by a network device, the first information being used by the terminal device to determine a radio resource management (RRM) measurement result on the basis of a first model. In embodiments of the present application, the RRM measurement result is determined on the basis of the first model, for example, the RRM measurement result is determined on the basis of an actual measurement result and a prediction result obtained by means of the first model, so that the performance related to RRM measurement can be improved.

Description

Wireless communication method, terminal device and network device Technical Field

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

[0002] Typically, a terminal device performs radio resource management (RRM) and reports measurement results to a network device in the form of a measurement report, so that the network device can make relevant decisions based on the reported content, such as cell switching decisions and beam switching decisions. However, the performance of RRM measurements needs to be further improved.

[0003] Summary of the Invention

[0004] The present application provides a wireless communication method, terminal equipment and network equipment. The various aspects involved in the present application are introduced below.

[0005] In a first aspect, a wireless communication method is provided, including: a terminal device receives first information sent by a network device, where the first information is used by the terminal device to determine a radio resource management (RRM) measurement result based on a first model.

[0006] In a second aspect, a wireless communication method is provided, including: a network device sends first information to a terminal device, where the first information is used by the terminal device to determine a radio resource management RRM measurement result based on a first model.

[0007] According to a third aspect, a terminal device is provided, comprising: a receiving unit for receiving first information sent by a network device, wherein the first information is used by the terminal device to determine a radio resource management RRM measurement result based on a first model.

[0008] In a fourth aspect, a network device is provided, comprising: a sending unit, configured to send first information to a terminal device, wherein the first information is used by the terminal device to determine a radio resource management RRM measurement result based on a first model.

[0009] In a fifth aspect, a terminal device is provided, comprising a processor, a memory, and a communication interface, wherein the memory is used to store one or more computer programs, and the processor is used to call the computer program in the memory so that the terminal device executes part or all of the steps in the method of the first aspect.

[0010] In the sixth aspect, a network device is provided, comprising a processor, a memory, and a communication interface, wherein the memory is used to store one or more computer programs, and the processor is used to call the computer program in the memory so that the network device executes part or all of the steps in the method of the second aspect.

[0011] In a seventh aspect, an embodiment of the present application provides a communication system, which includes the above-mentioned terminal and / or network device. In another possible design, the system may also include other devices that interact with the terminal or network device in the solution provided in the embodiment of the present application.

[0012] In an eighth aspect, an embodiment of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and the computer program enables the terminal to execute part or all of the steps in the above-mentioned first or second aspect method.

[0013] In a ninth aspect, embodiments of the present application provide a computer program product, wherein the computer program product includes a non-transitory computer-readable storage medium storing a computer program, wherein the computer program is operable to cause a terminal to perform some or all of the steps of the method of the first or second aspect described above. In some implementations, the computer program product may be a software installation package.

[0014] In the tenth aspect, an embodiment of the present application provides a chip comprising a memory and a processor, wherein the processor can call and run a computer program from the memory to implement some or all of the steps described in the method of the first or second aspect above.

[0015] In an embodiment of the present application, by determining the RRM measurement results based on the first model, such as determining the RRM measurement results based on the actual measurement results and the prediction results obtained by the first model, it helps to improve the performance related to the RRM measurement. For example, by predicting the measurement results between the sampling time points through the first model, it is equivalent to obtaining more measurement results within the measurement cycle, which helps to improve the accuracy of the RRM measurement results. For example, within the measurement cycle, using the prediction results (obtained based on the first model) to replace some measurement results helps to reduce the sampling behavior of the terminal device, thereby saving the power of the terminal device and extending the battery life. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] FIG1 is a wireless communication system used in an embodiment of the present application.

[0017] FIG2 is an example diagram of a measurement model applicable to an embodiment of the present application.

[0018] FIG3 is a flow chart of a wireless communication method according to an embodiment of the present application.

[0019] FIG4 is a schematic diagram of the algorithm structure of the first model association provided in an embodiment of the present application.

[0020] FIG5 is a schematic diagram of an algorithm structure of a first model association provided in another embodiment of the present application.

[0021] FIG6 is a schematic diagram of a prediction scheme for beam measurement results in an embodiment of the present application.

[0022] FIG7 is a schematic diagram of a prediction scheme for beam measurement results in another embodiment of the present application.

[0023] FIG8 is a schematic diagram of a prediction scheme for beam measurement results in another embodiment of the present application.

[0024] FIG9 takes the measurement results shown in FIG6 as an example to introduce the filtering method of the embodiment of the present application.

[0025] FIG10 is a schematic diagram of a filtering method according to another embodiment of the present application.

[0026] FIG11 is a schematic diagram of a terminal device provided in an embodiment of the present application.

[0027] FIG12 is a schematic diagram of a network device provided in an embodiment of the present application.

[0028] FIG13 is a schematic structural diagram of a device according to an embodiment of the present application. DETAILED DESCRIPTION

[0029] The technical solution in this application will be described below with reference to the accompanying drawings.

[0030] Communication System

[0031] FIG1 is a diagram illustrating an exemplary system architecture of a wireless communication system 100 to which embodiments of the present application may be applied. The wireless communication system 100 may include a network device 110 and a terminal device 120. The network device 110 may be a device that communicates with the terminal device 120. The network device 110 may provide communication coverage for a specific geographic area and may communicate with the terminal device 120 within the coverage area.

[0032] FIG1 exemplarily shows a network device and two terminal devices. Optionally, the wireless communication system 100 may include multiple network devices and each network device may include another number of terminal devices within its coverage area, which is not limited in this embodiment of the present application.

[0033] Optionally, the wireless communication system 100 may further include other network entities such as a network controller and a mobility management entity, which is not limited in the embodiment of the present application.

[0034] It should be understood that the technical solutions of the embodiments of the present application can be applied to various communication systems, such as: fifth generation (5G) system or new radio (NR), long term evolution (LTE) system, LTE frequency division duplex (FDD) system, LTE time division duplex (TDD), wideband code division multiple access (WCDMA) system, etc. The technical solutions provided in this application can also be applied to future communication systems, such as the sixth generation mobile communication system, satellite communication system, etc.

[0035] The terminal device in the embodiments of the present application may also be referred to as user equipment (UE), access terminal, user unit, user station, mobile station, mobile station (MS), mobile terminal (MT), remote station, remote terminal, mobile device, user terminal, terminal, wireless communication device, user agent or user device. The terminal device in the embodiments of the present application may refer to a device that provides voice and / or data connectivity to a user and can be used to connect people, objects and machines, such as a handheld device with wireless connection function, a vehicle-mounted device, etc. The terminal device in the embodiments of the present application can be a mobile phone, a tablet computer, a laptop computer, a PDA, a mobile internet device (MID), a wearable device, a virtual reality (VR) device, an augmented reality (AR) device, a wireless terminal in industrial control, a wireless terminal in self-driving, a wireless terminal in remote medical surgery, a wireless terminal in a smart grid, a wireless terminal in transportation safety, a wireless terminal in a smart city, a wireless terminal in a smart home, etc. Optionally, the UE can be used to act as a base station. For example, the UE can act as a scheduling entity that provides sidelink signals between UEs in V2X or D2D, etc. For example, a cellular phone and a car communicate with each other using sidelink signals. The cellular phone and smart home devices communicate without relaying the communication signal through the base station.

[0036] The network device in the embodiments of the present application may be a device for communicating with a terminal device, and may also be referred to as an access network device or a radio access network device. For example, the network device may be a base station. The network device in the embodiments of the present application may refer to a radio access network (RAN) node (or device) that connects a terminal device to a wireless network. A base station can broadly cover various names as follows, or be replaced with the following names, such as: NodeB, evolved NodeB (eNB), next generation NodeB (gNB), relay station, access point, transmission point (TRP), transmission point (TP), master station MeNB, secondary station SeNB, multi-standard radio (MSR) node, home base station, network controller, access node, wireless node, access point (AP), transmission node, transceiver node, baseband unit (BBU), remote radio unit (RRU), active antenna unit (AAU), remote radio head (RRH), central unit (CU), distributed unit (DU), positioning node, etc. A base station can be a macro base station, a micro base station, a relay node, a donor node or the like, or a combination thereof. A base station can also refer to a communication module, a modem or a chip used to be set in the aforementioned device or apparatus. The base station can also be a mobile switching center and a device that performs base station functions in device-to-device D2D, vehicle-to-everything (V2X), and machine-to-machine (M2M) communications, a network-side device in a 6G network, or a device that performs base station functions in future communication systems. The base station can support networks with the same or different access technologies. The embodiments of this application do not limit the specific technology and specific device form used by the network equipment.

[0037] Base stations can be fixed or mobile. For example, a helicopter or drone can be configured to act as a mobile base station, and one or more cells can move based on the location of the mobile base station. In other examples, a helicopter or drone can be configured to act as a device that communicates with another base station.

[0038] In some deployments, the network device in the embodiments of the present application may refer to a CU or a DU, or the network device may include a CU and a DU. The gNB may also include an AAU.

[0039] The network equipment and terminal devices can be deployed on land, including indoors or outdoors, handheld or vehicle-mounted; they can also be deployed on water; they can also be deployed in the air on aircraft, balloons, and satellites. The embodiments of this application do not limit the scenarios in which the network equipment and terminal devices are located.

[0040] It should be understood that all or part of the functions of the communication device in this application can also be implemented through software functions running on hardware, or through virtualization functions instantiated on a platform (such as a cloud platform).

[0041] For ease of understanding, the communication process involved in the embodiments of the present application is introduced below.

[0042] RRM measurements

[0043] In cellular communication systems based on the Third Generation Partnership Project (3GPP), terminal devices typically measure the strength or quality of the wireless signals in their current serving cell and neighboring cells. These measurements are called RRM measurements. After performing RRM measurements, the terminal device reports the measurement details to the network device in the form of a measurement report, enabling the network device to make decisions based on the reported information, such as cell handover and beam switching decisions. The following provides a brief introduction to measurement reports.

[0044] As an implementation manner, the terminal device may report the measurement report to the network via a radio resource control (RRC) message.

[0045] There are many ways to report measurement reports, such as periodic reporting, reporting based on measurement events, and continuing periodic reporting after measurement event reporting. As an example, in a second-generation communication system, measurement reports are always reported according to a certain period, that is, the terminal device periodically reports measurement reports to the network device. As another example, in a third-generation communication system (such as a WCDMA system), a fourth-generation communication system (LTE system), and a fifth-generation communication system (NR system), measurement reports can be reported in any of the three ways mentioned above.

[0046] Regardless of the method used by the terminal device to report the measurement report, the measurement report may include specific measurement events and / or measurement results. As an example, the measurement report may include the signal strength of the cell, such as the reference signal receiving power (RSRP) of the cell, where the RSRP of the cell can be measured in dBm. As another example, the measurement report may include the signal quality of the cell, such as the reference signal receiving quality (RSRQ) of the cell, where the RSRQ of the cell can be measured in db.

[0047] In the measurement report, the cells reported by the terminal device may include the current serving cell and / or neighboring cells. For example, the terminal device may report the signal strength and signal quality of the current serving cell. Alternatively, the terminal device may report the signal strength and signal quality of the current serving cell and neighboring cells.

[0048] The measurement report may include multiple measurement objects, for example, the measurement object may be the same frequency, different frequency, or frequency of different communication systems.

[0049] As mentioned above, the measurement report may include a measurement event. The triggering of the measurement event is described below. In some embodiments, the triggering of the measurement event may include basic elements such as measurement results, comparison parameters, and timers. These basic elements are described below.

[0050] The measurement results may be, for example, measurement results of the serving cell and / or neighboring cells. For example, the measurement results may be signal strength of the serving cell and / or neighboring cells. Alternatively, the measurement results may be signal quality of the serving cell and / or neighboring cells. In standard protocols, generally, a larger numerical value of a dimension of a measurement result indicates a higher signal strength or quality.

[0051] The comparison parameters corresponding to a measurement event may include one or more parameters. For example, the comparison parameters corresponding to a measurement event may include one or more of the following parameters: a threshold, a hysteresis value, an offset value, etc. The comparison parameters corresponding to the measurement event may be compared with the measurement results of the cell to determine whether the entry and / or exit conditions of the measurement event are met. As a possible implementation, the comparison parameters may be compared absolutely with the measurement results of the cell. Absolute comparison may refer to comparing the measurement results of a cell with a threshold. In this case, if the measurement result of the cell is greater than the sum of the threshold and the hysteresis value, the cell is considered to meet the entry conditions for the measurement event; if the measurement result of the cell is less than the difference between the threshold and the hysteresis value, the cell is considered to meet the exit conditions for the measurement event. As another possible implementation, the comparison parameters may be compared relatively with the measurement results of the cell. Relative comparison may refer to comparing the measurement results of neighboring cells with the measurement results of the serving cell. In some embodiments, before comparing the measurement results of neighboring cells with the measurement results of the serving cell, each cell needs to add its own relevant offset value. For the serving cell, the offset value related to the corresponding event needs to be added. In addition, the hysteresis value needs to be considered when comparing the measurement results of neighboring cells with the measurement results of the serving cell. Taking event A3 as an example, the following provides an example of comparing the measurement results of the neighboring cell and the measurement results of the serving cell.

[0052] The entry condition corresponding to event A3 can be expressed as: n +of n >M s +of s +Hys+off_event

[0053] The exit condition corresponding to event A3 can be expressed as: n +of n <M s +of s -Hys+off_event

[0054] Among them, M n Indicates the measurement results of neighboring cells, of n Indicates the offset value of the neighboring cell, M s Indicates the measurement result of the serving cell, s It represents the offset value of the serving cell, Hys represents the hysteresis value, and off_event represents the offset value related to the corresponding event.

[0055] A timer can be used to indicate the robustness of measurement results. For example, the timer can be a time-to-trigger (TTT) timer. In some embodiments, when a cell meets the entry conditions for a measurement event, the TTT timer is started. If the TTT timer expires and the cell continues to meet the entry conditions for the measurement event, the cell is considered to have triggered the measurement event.

[0056] measurement model

[0057] In some communication protocols (such as 3GPP standard specification 38.331 (RRC standard protocol)), the measurement results used for measurement event decision making are filtered by the RRC layer (Layer 3). However, the initial measurement results within the terminal device are physical layer (Layer 1) measurements of a single beam. How the terminal device performs co-frequency and inter-frequency measurements, and how it transitions from beam-based measurement sampling at Layer 1 to making measurement event decisions based on network-configured parameters, can be implemented based on a measurement model, as shown in Figure 2. The following describes the reference points shown in Figure 2.

[0058] Reference point A is where the terminal device performs physical layer measurement sampling. In some embodiments, the terminal device can perform physical layer measurement sampling based on the granularity of the beam. For example, reference point A can be the measurement sampling results of K beams.

[0059] Between reference point A and reference point A1, layer 1 filtering can be performed, that is, the terminal device can perform layer 1 filtering on the measured beam measurement sampling results. Reference point A1 can be the layer 1 filtering result of the beam measurement sampling result, or can be called the layer 1 beam measurement result. It should be noted that the beam measurement result after layer 1 filtering must meet the performance requirements specified in the relevant specifications (such as 3GPP specifications). Generally speaking, the protocol can specify the length of the measurement period under a specific RRC configuration. During the measurement period, the terminal device must perform at least one sampling (or measurement). In some embodiments, the specific number of sampling times of the terminal device in a measurement period is specified. For example, in the test example, the terminal device can perform 4-5 oversampling times in a measurement period.

[0060] Between reference points A1 and B, beam consolidation / selection can be performed. This means that the terminal device can combine the layer 1 beam measurement results and perform a weighted average of the qualified beam measurement results in the cell to obtain a layer 1 cell-level measurement result. The layer 1 cell-level measurement result can represent the cell quality.

[0061] Between reference point B and reference point C, layer 3 filtering for cell quality may be performed, that is, the terminal device may perform layer 3 filtering on the cell-level measurement result of layer 1 to obtain the cell measurement result of layer 3.

[0062] Between reference points C and D, an evaluation of reporting criteria can be performed. This means that the terminal device judges the measurement results of the serving cell and / or neighboring cells according to certain decision conditions (e.g., decision conditions configured by the network) to determine whether a specific measurement event has occurred. For example, determining whether the measurement result of the neighboring cell is higher than the measurement result of the serving cell by an offset value (i.e., an A3 event).

[0063] It should be noted that other relevant descriptions of FIG2 can be referred to 3GPP protocol TS38.331, which will not be repeated here.

[0064] Based on the above measurement result generation process and measurement event judgment process, a measurement event starts when the entry condition is met. For example, after TTT time has passed, a measurement event judgment result (for example, including whether the measurement event is triggered) can be given.

[0065] Some standards (such as standard specification 38.133) specify the performance indicators of terminal device measurement results, namely the accuracy of the measurement results. Furthermore, these standards specify the length of the measurement period for different measurement scenarios. For example, for intra-frequency measurements in frequency range 1 (FR1), the minimum measurement period is 200ms, assuming there is no discontinuous reception (DRX) and measurement gap. However, the standard specification does not explicitly specify how many measurement results the terminal device ultimately samples within a measurement period, nor how Layer 1 filtering is performed on these measurement results. This is left to the technical implementation, as illustrated by the block diagram between reference points A and A1 in Figure 2. It is important to note that the period for generating L1 measurement values ​​at reference point A1 is the same as the period for generating L3 filtered measurement values ​​at reference point C.

[0066] As mentioned above, when a terminal device measures a cell at the physical layer, the measurement sampling within the measurement period is actually discrete in the time domain. In other words, the measurement value obtained by the terminal device is the measurement result of a specific beam at the sampling time point. As a result, the actual state of the cell between two samplings is unknown. The L1 beam measurement results reported at reference point A1 in the measurement model shown in Figure 2 are filtered based on these sampling results. Due to the loss of some measurement information, such measurement results are often inaccurate.

[0067] In some embodiments, in order to improve the accuracy of the measurement results, the number of sampling times within the measurement cycle can be increased. However, performing a large number of samplings will greatly increase the power consumption of the terminal device, thereby reducing the battery life of the terminal device.

[0068] In order to solve the above problems, an embodiment of the present application provides a wireless communication method, which determines the RRM measurement results based on a first model, such as determining the RRM measurement results based on the actual measurement results and the prediction results obtained through the first model, thereby helping to improve the performance related to the RRM measurement. For example, predicting the measurement results between the sampling time points through the first model is equivalent to obtaining more measurement results within the measurement period, which helps to improve the accuracy of the RRM measurement results. For another example, within the measurement period, using the prediction results (obtained based on the first model) to replace some measurement results helps to reduce the sampling behavior of the terminal device, thereby saving the power of the terminal device and extending the battery life.

[0069] In some implementations, the RRM measurement results may be used for primary cell handover and / or primary / secondary cell handover.

[0070] Another wireless communication method provided by an embodiment of the present application is described below in conjunction with Figure 3. The method shown in Figure 3 is described from the perspective of interaction between a terminal device and a network device, which may be any type of network device and terminal device mentioned above.

[0071] Referring to FIG. 3 , in step S310 , the network device sends first information to the terminal device.

[0072] In some implementations, the first information is used by the terminal device to determine the RRM measurement result based on a first model. The first model may be an artificial intelligence (AI) / machine learning (ML) model. In other words, the first information can be used by the terminal device to determine the RRM measurement result based on AI / ML technology.

[0073] In some embodiments, the network device may indicate whether the terminal device is allowed to determine the RRM measurement result based on the first model. Further, the network device may configure a configuration parameter for the terminal device to determine the RRM measurement result based on the first model, or may determine the RRM measurement result based on the first model according to the terminal device implementation. In some embodiments, the network device may implicitly indicate that the terminal device is allowed to determine the RRM measurement result based on the first model by sending a configuration parameter to the terminal device.

[0074] Taking into account the above-mentioned various implementations, the first information may include one or more of the following: indication information indicating whether the terminal device is capable of determining the RRM measurement result based on the first model; and configuration information for the terminal device to determine the RRM measurement result based on the first model. The following provides examples of various situations in which the first information may be used.

[0075] As an implementation method, the first information may include the above-mentioned indication information to indicate whether the terminal device is allowed to determine the RRM measurement result based on the first model. By sending this indication information to the terminal device, it helps to improve the flexibility of the system, such as flexibly selecting whether to determine the RRM measurement result based on the first model. For example, the first information may be 1 bit, and different values ​​of the 1 bit indicate whether the terminal device is allowed to determine the RRM measurement result based on the first model.

[0076] Optionally, the network device may determine whether to allow the terminal device to determine the RRM measurement result based on the first model based on the accuracy requirement of the RRM measurement result, the capability information of the terminal device, the type of the terminal device, and pre-configuration information. Further, based on the determination result of the network device, the above-mentioned indication information is sent to the terminal device.

[0077] In order to save signaling overhead, whether the terminal device is allowed to determine the RRM measurement result based on the first model can be indicated by whether the first information is sent. For example, if the terminal device is not allowed to determine the RRM measurement result based on the first model, the network device may not send the first information; if the terminal device is allowed to determine the RRM measurement result based on the first model, the network device may send the first information. In other words, if the network device sends the first information, it means that the terminal device is allowed to determine the RRM measurement result based on the first model. For another example, if the terminal device is allowed to determine the RRM measurement result based on the first model, the network device may not send the first information; if the terminal device is not allowed to determine the RRM measurement result based on the first model, the network device may send the first information. In other words, if the network device sends the first information, it means that the terminal device is not allowed to determine the RRM measurement result based on the first model.

[0078] Optionally, a default method for the terminal device to determine the RRM measurement result can be predefined or configured, such as determining the RRM measurement result based on the first model by default, or not determining the RRM measurement result based on the first model by default, that is, determining the RRM measurement result in a traditional manner. Generally, the terminal device can determine the RRM measurement result in a default manner. In this case, if the network device sends the first information to the terminal device, the first information is used to instruct the terminal device to determine the RRM measurement result using a non-default method.

[0079] As an implementation manner, the first information may include configuration information for determining the RRM measurement result based on the first model, such as the first information may include configuration parameters for determining the RRM measurement result based on the first model. In some cases, the configuration information may implicitly indicate that the terminal device is allowed to determine the RRM measurement result based on the first model.

[0080] As an implementation manner, the first information may include the above-mentioned indication information and configuration information for determining the RRM measurement result based on the first model. The above-mentioned indication information and configuration information may be carried in the same message or signaling, or in different messages or signaling.

[0081] The configuration information for determining the RRM measurement result based on the first model may include multiple types, or in other words, the configuration information may be used to configure multiple parameters. The configuration information is introduced below.

[0082] In some embodiments, the configuration information is used to configure an algorithm structure associated with the first model, and the algorithm structure is used to determine the function of the first model. The first model can be used to predict any one or more parameters involved in the process of determining the RRM measurement result. Referring again to Figure 2, the process parameters for determining the RRM measurement result in the related art include beam measurement sampling results, L1 beam measurement results, L1 cell measurement results, and L3 cell measurement results. Based on this, the function of the first model may, for example, include the first model being used to generate one or more of the following: a predicted value of the beam measurement result; a predicted value of the layer 1 cell measurement result; and a predicted value of the layer 3 cell measurement result; wherein the beam measurement result includes a beam measurement sampling result and / or a layer 1 beam measurement result.

[0083] The measurement model mentioned in Figure 2 can be understood as an algorithmic structure. The algorithmic structure associated with the first model can refer to the measurement model that includes the first model. For example, the algorithmic structure associated with the first model can include the position of the first model in the measurement model, such as the connection between the output of the first model and other modules or signals in the measurement model. The position of the first model in the algorithmic structure is associated with the function of the first model.

[0084] The following describes the algorithm structure associated with the first model, using the measurement model in Figure 2 as an example. In some embodiments, the output of the first model can serve as input to the beam combining / selection module and the layer 3 beam filter. In other words, the first model can be used to generate predicted values ​​for beam measurement sampling results. The algorithm structure associated with the first model can be shown in Figure 4.

[0085] In this structure, the input to the first model can be the L1 beam measurement results of the terminal device at certain time points and / or other auxiliary parameters. Auxiliary parameters can include, for example, the terminal device's determination of its own movement trajectory. Furthermore, the output of the first model can be a predicted L1 beam measurement result for a particular beam at a certain time point. This predicted L1 beam measurement result and the terminal device's actual L1 beam measurement result can be used in the calculation process of subsequent modules.

[0086] In other embodiments, the input of the first model may serve as the input of a reporting criteria evaluation module. In this case, the output of the first model may be a predicted value of a layer 3 cell measurement result. In other words, the first model may be used to generate a predicted value of a cell measurement result. The algorithm structure associated with the first model may be as shown in FIG5 .

[0087] As described above, the first information may include configuration information for the terminal device to determine the RRM measurement result based on the first model, or in other words, the first information is used to configure the terminal device to determine the RRM measurement result based on the first model. The following describes the configuration information in the embodiments of the present application.

[0088] In some implementations, the configuration information is used to configure the number of predicted values ​​that the terminal device is allowed to generate based on the first model within the measurement period. In other words, the configuration information is used to indicate the number of predicted values ​​generated based on the first model within the measurement period. Taking the predicted value including the predicted L1 beam measurement result information as an example, in some implementations, the configuration information is used to configure the number of predicted L1 beam measurement results allowed within a measurement period. In other implementations, the configuration information is used to configure the number of predicted L1 beam measurement results allowed within a measurement period, and the proportion of the total number of measurement results within the measurement period. Taking the predicted value including the predicted L3 beam measurement result information as an example, in some implementations, the configuration information is used to configure the number of predicted L1 beam measurement results allowed within a measurement period. In other implementations, if the predicted value includes the predicted L1 beam measurement result information, accordingly, the configuration information is used to configure the number of predicted L1 beam measurement results allowed within a measurement period, and the proportion of the total number of measurement results within the measurement period.

[0089] It should be noted that, assuming that the number of measurement values ​​of the measurement results within the measurement period configured by the network device is N, then the number of predicted values ​​of the measurement results configured above is the number M added on the basis of N. Accordingly, the total number of measurement results within the measurement period is the sum of N and M, where N and M are positive integers greater than or equal to 1.

[0090] Furthermore, if the embodiments of the present application are used to calculate beam measurement results, they can be combined with a sliding window mechanism. N or N+M can be two mechanisms for the sliding window size. Regardless of the sliding window size, the frequency of obtaining L3 cell measurement results increases. When the sliding window is N+M, the performance of the L1 beam measurement results obtained after L1 filtering in each measurement cycle is better. This is because, compared to the N measurement values ​​specified in the original specification, M more predicted values ​​are obtained within the same time period.

[0091] In some implementations, the configuration information is used to configure the position of the predicted value generated based on the first model, and the position of the predicted value is used to indicate the relative positional relationship between the predicted value and the measured value in the time domain. Alternatively, the configuration information is used to indicate the insertion method of the predicted value into the measured value in the time domain. Alternatively, the configuration information is used to indicate the insertion time domain position of the predicted value into the measured value in the time domain. Alternatively, the configuration information is used to indicate the time domain position of the predicted value.

[0092] In the embodiment of the present application, the implementation method of the above-mentioned information for configuring the position is not specifically limited. For example, the configuration information may be a bitmap, and accordingly, each bit in the bitmap corresponds to the index of the time domain position. If the value of the bit corresponding to the index of the time domain position is a first value, it indicates that the time domain position is the time domain position of the predicted value of the measurement result. On the contrary, if the value of the bit corresponding to the index of the time domain position is a second value, it indicates that the time domain position is not the time domain position of the predicted value of the measurement result. The first value and the second value are different values, for example, the first value may be 0, and the second value may be 1. For another example, the first value may be 1, and the second value may be 0.

[0093] In an embodiment of the present application, the information used to configure the number of predicted values ​​can be the same as the information used to configure the positions of the predicted values, which helps reduce the transmission overhead required to transmit the information. Taking the configuration information as a bitmap as an example, the number of first values ​​in the bitmap is the number of predicted values ​​within the measurement period. Of course, in an embodiment of the present application, the information used to configure the number of predicted values ​​can be independent of the information used to configure the positions of the predicted values.

[0094] In some implementations, the first model is used to generate predicted values ​​of beam measurement results, and the configuration information is used to configure a prediction scheme for the beam measurement results, wherein the prediction scheme indicates how the predicted values ​​of the beam measurement results and the measured values ​​of the beam measurement results are arranged in the time domain. In other words, the configuration information is used to configure how the predicted values ​​of the beam measurement results and the measured values ​​of the beam measurement results are arranged in the time domain. This is described below in conjunction with Methods 1 to 3.

[0095] In mode 1, the predicted value of the beam measurement result corresponds to the first moment, and the beam measurement result prediction scheme is used to indicate that the first moment is between the moments corresponding to two adjacent beam measurement results. In other words, the configuration information is used to indicate that the predicted value of the beam measurement result is between the measured values ​​of two adjacent beam measurement results in the time domain.

[0096] For ease of understanding, the following describes a beam measurement result prediction scheme according to an embodiment of the present application in conjunction with FIG6 . As shown in FIG6 , the current measurement cycle includes a measured value of the measurement result and a predicted value of the measurement result, wherein the predicted value of the measurement result is located between the measured values ​​of two adjacent beam measurement results in the time domain.

[0097] In an embodiment of the present application, a terminal device can obtain more measurement results (including measurement values ​​and predicted values) in the same time, which helps to obtain more layer 3 cell measurement results. For example, as shown in Figure 2, at reference point C, the terminal device can obtain more L3 cell measurement results in the same time. The specific percentage of additional L3 cell measurement results depends on the specific method. For example, as shown in Figure 3, by inserting a predicted value between every two adjacent measurement values, 100% more L3 cell measurement results can be obtained. Accordingly, in the structure of Figure 2, the predicted results obtained at reference point A1 will obtain an L3 cell measurement result after merging and L3 filtering.

[0098] In mode 2, the predicted values ​​of multiple beam measurement results correspond to multiple time instants. The beam measurement result prediction scheme indicates that the multiple time instants are located between the time periods corresponding to two adjacent beam measurement result sets. In other words, the configuration information indicates that the predicted values ​​of the beam measurement results are located between two adjacent beam measurement result sets in the time domain. A beam measurement result set includes the measured values ​​of one or more beam measurement results.

[0099] For ease of understanding, the following describes a beam measurement result prediction scheme according to an embodiment of the present application in conjunction with FIG7 . As shown in FIG7 , the current measurement cycle includes a measured value of the measurement result and a predicted value of the measurement result, wherein the predicted value of the measurement result is located between two adjacent beam measurement result sets in the time domain.

[0100] In mode 3, the prediction scheme for the beam measurement result is used to indicate that multiple moments are located in the first half of the measurement period, or multiple moments are located in the second half of the measurement period. In other words, the configuration information is used to indicate that the predicted value of the beam measurement result is located in the first half or the second half of the measurement period.

[0101] For ease of understanding, the following describes a beam measurement result prediction scheme according to an embodiment of the present application in conjunction with FIG8 . As shown in FIG8 , the current measurement cycle includes a measured value of the measurement result and a predicted value of the measurement result, wherein the predicted value of the measurement result is located in the second half of the measurement cycle in the time domain.

[0102] It should be noted that the beam measurement result prediction scheme described above in conjunction with Figures 6 to 8 is also applicable to the prediction scheme of cell measurement results (e.g., layer 3 cell measurement results). In this case, it is only necessary to replace the beam measurement results described above with the cell measurement results. For the sake of brevity, this is not further described below.

[0103] In some implementations, the beam measurement result includes a beam measurement sampling result (or a measurement value of the beam measurement result), and the configuration information is used to configure a filtering method for the beam measurement sampling result and / or the predicted value of the beam measurement result.

[0104] In some implementations, the filtering method includes a sliding window method and / or a variant sliding window method.

[0105] In some implementations, the size of the sliding window is the number of beam measurement results in a measurement period, or the size of the sliding window is the sum of the number of beam measurement results in a measurement period and the number of predicted values ​​of the beam measurement results.

[0106] For ease of understanding, the following describes a schematic diagram of the filtering method of an embodiment of the present application in conjunction with Figures 9 and 10.

[0107] FIG9 uses the measurement results shown in FIG6 as an example to illustrate the filtering method of an embodiment of the present application. As shown in FIG9 , a predicted value of the measurement result is inserted between the measured values ​​of every two adjacent measurement results within a measurement cycle. Then, within the measurement cycle, the corresponding L1 beam measurement results are obtained based on the measured values ​​and the predicted values ​​in chronological order. L1 filtering employs a sliding window approach, ensuring that the frequency of the L1 beam measurement results remains essentially consistent with the frequency of the measured values.

[0108] Furthermore, the measurements in Figure 9 are based on historical measurements (and predictions). The measurements and predictions are then filtered using L1 filtering to produce an L1 beam measurement result. This result is a mixture of actual measurements and predictions. This approach allows for a greater number of L1 beam measurement results to be obtained within a single measurement cycle.

[0109] Figure 10 illustrates a filtering method according to another embodiment of the present application. As shown in Figure 10 , the predicted value of the measurement result can be obtained in the second half of measurement cycle 2. Correspondingly, the actual value of the measurement result can be obtained in the second half of measurement cycle 1 and the second half of measurement cycle 2. Subsequently, a sliding window mechanism is used to obtain the L1 beam measurement result.

[0110] In the embodiment of the present application, the L3 cell measurement result can be predicted according to the historical L3 cell measurement results (and the predicted value of the L3 cell measurement results) within a measurement cycle without changing the existing L1 measurement result.

[0111] In addition, in the embodiment of the present application, the algorithm structure associated with the first model described in FIG5 may be used for calculation.

[0112] In some implementations, if the first model is used to generate predicted values ​​of beam measurement results, the input of the first model is historical beam measurement results (also called "measurement values ​​of historical measurement results"), or the input of the first model is historical beam measurement results and historical predicted values ​​of beam measurement results.

[0113] In some implementations, if the first model is used to generate predicted values ​​of layer 3 cell measurement results, the input of the first model is historical layer 3 cell measurement results (also referred to as "measured values ​​of historical layer 3 cell measurement results"), or the input of the first model is historical layer 3 cell measurement results and historical predicted values ​​of layer 3 cell measurement results.

[0114] In some implementations, if the first model is used to generate a predicted value of a layer 1 cell measurement result, the input of the first model is a historical layer 1 cell measurement result (also referred to as a "measurement value of a historical layer 1 cell measurement result"). Alternatively, the input of the first model is a historical layer 1 cell measurement result and a historical predicted value of a layer 1 cell measurement result.

[0115] In some implementations, the input of the first model includes historical location information of the terminal device and / or predicted values ​​of future location information of the terminal device.

[0116] The above describes an embodiment of the present application in which the measurement results are predicted by the first model to increase the number of measurement results in the time domain and improve the accuracy of the measurement results. In an embodiment of the present application, the accuracy of the measurement results can also be improved by increasing the predicted measurement sampling (for example, the predicted measurement sampling before L1 filtering, or the predicted value of the measurement quantity before L1 filtering) without increasing the frequency of measurement reports. In other words, one L1 beam measurement result is still reported in one measurement cycle, and the actual measurement sampling and the predicted measurement sampling are L1 filtered together. The L1 beam measurement result obtained in this way may have higher accuracy because more measurement samples are equivalently performed in the time domain. The method of increasing the predicted measurement value of layer 1 can refer to Figures 9 and 10.

[0117] In addition, in an embodiment of the present application, the actual number of measurements can be reduced at different stages (for example, measurement sampling before L1 filtering. For example, L1 beam measurement results. For example, L1 cell measurement results. For example, L3 measurement results), and the measured value of the measurement result and the predicted value of the measurement result are used together to participate in the subsequent calculation process (for example, L1 filtering, merging, L3 filtering, etc.), while ensuring the measurement performance, so as to reduce the measurement behavior of the terminal device and thereby reduce the power consumption of the terminal device.

[0118] The method embodiments of the present application are described in detail above, and the device embodiments of the present application are described in detail below. It should be understood that the description of the method embodiments corresponds to the description of the device embodiments, so for parts not described in detail, reference can be made to the above method embodiments.

[0119] FIG11 is a schematic diagram of a terminal device provided in an embodiment of the present application. The terminal device 1100 includes: a receiving unit 1110 .

[0120] The receiving unit 1110 is used to receive first information sent by a network device, where the first information is used by the terminal device to determine a radio resource management RRM measurement result based on a first model.

[0121] In some embodiments, the first information includes one or more of the following: indication information of whether the terminal device is capable of determining the RRM measurement result based on the first model; and configuration information for the terminal device to determine the RRM measurement result based on the first model.

[0122] In some embodiments, the configuration information is used to configure an algorithm structure associated with the first model, and the algorithm structure is used to determine the function of the first model.

[0123] In some embodiments, the function of the first model includes the first model being used to generate one or more of: a predicted value of a beam measurement result; a predicted value of a layer 1 cell measurement result; and a predicted value of a layer 3 cell measurement result; wherein the beam measurement result includes a beam measurement sampling result and / or a layer 1 beam measurement result.

[0124] In some embodiments, the configuration information is used to configure the number of predicted values ​​that the terminal device is allowed to generate based on the first model within a measurement period.

[0125] In some embodiments, the configuration information is used to configure the position of the predicted value generated based on the first model, and the position of the predicted value is used to indicate the relative position relationship between the predicted value and the measured value in the time domain.

[0126] In some embodiments, the first model is used to generate a predicted value of the beam measurement result, and the configuration information is used to configure a prediction scheme for the beam measurement result.

[0127] In some embodiments, the predicted value of the beam measurement result corresponds to a first moment, and the prediction scheme of the beam measurement result is used to indicate that the first moment is located between two adjacent moments corresponding to the beam measurement results.

[0128] In some embodiments, the predicted values ​​of the plurality of beam measurement results correspond to a plurality of moments, and the prediction scheme of the beam measurement results is used to indicate that the plurality of moments are located between time periods corresponding to two adjacent sets of beam measurement results.

[0129] In some embodiments, the prediction scheme of the beam measurement results is used to indicate that: the multiple moments are located in the first half of the measurement period, or the multiple moments are located in the second half of the measurement period.

[0130] In some embodiments, the beam measurement result includes a beam measurement sampling result, and the configuration information is used to configure a filtering method for the beam measurement result and / or a predicted value of the beam measurement result.

[0131] In some embodiments, the filtering method includes a sliding window method and / or a variant sliding window method.

[0132] In some embodiments, the size of the sliding window is the number of the beam measurement results in a measurement period, or the size of the sliding window is the sum of the number of the beam measurement results in a measurement period and the number of predicted values ​​of the beam measurement results.

[0133] In some embodiments, if the first model is used to generate the predicted value of the beam measurement result, the input of the first model is the historical beam measurement result, or the input of the first model is the historical beam measurement result and the historical predicted value of the beam measurement result; if the first model is used to generate the predicted value of the layer 3 cell measurement result, the input of the first model is the historical layer 3 cell measurement result, or the input of the first model is the historical layer 3 cell measurement result and the historical predicted value of the layer 3 cell measurement result; if the first model is used to generate the predicted value of the layer 1 cell measurement result, the input of the first model is the historical layer 1 cell measurement result, or the input of the first model is the historical layer 1 cell measurement result and the historical predicted value of the layer 1 cell measurement result.

[0134] In some embodiments, the input of the first model includes historical location information of the terminal device and / or predicted values ​​of future location information of the terminal device.

[0135] In some embodiments, the RRM measurement result is used for primary cell handover and / or primary-secondary cell handover.

[0136] FIG12 is a schematic diagram of a network device according to an embodiment of the present application. The network device 1200 includes a sending unit 1210 .

[0137] The sending unit 1210 is used to send first information to the terminal device, where the first information is used by the terminal device to determine a radio resource management RRM measurement result based on a first model.

[0138] In some embodiments, the first information includes one or more of the following: indication information of whether the terminal device is capable of determining the RRM measurement result based on the first model; and configuration information for the terminal device to determine the RRM measurement result based on the first model.

[0139] In some embodiments, the configuration information is used to configure an algorithm structure associated with the first model, and the algorithm structure is used to determine the function of the first model.

[0140] In some embodiments, the function of the first model includes the first model being used to generate one or more of: a predicted value of a beam measurement result; a predicted value of a layer 1 cell measurement result; and a predicted value of a layer 3 cell measurement result; wherein the beam measurement result includes a beam measurement sampling result and / or a layer 1 beam measurement result.

[0141] In some embodiments, the configuration information is used to configure the number of predicted values ​​that the terminal device is allowed to generate based on the first model within a measurement period.

[0142] In some embodiments, the configuration information is used to configure the position of the predicted value generated based on the first model, and the position of the predicted value is used to indicate the relative position relationship between the predicted value and the measured value in the time domain.

[0143] In some embodiments, the first model is used to generate a predicted value of a beam measurement result, and the configuration information is used to configure a prediction scheme for the beam measurement result.

[0144] In some embodiments, the predicted value of the beam measurement result corresponds to a first moment, and the prediction scheme of the beam measurement result is used to indicate that the first moment is located between two adjacent moments corresponding to the beam measurement results.

[0145] In some embodiments, the predicted values ​​of the plurality of beam measurement results correspond to a plurality of moments, and the prediction scheme of the beam measurement results is used to indicate that the plurality of moments are located between time periods corresponding to two adjacent sets of beam measurement results.

[0146] In some embodiments, the prediction scheme of the beam measurement results is used to indicate that: the multiple moments are located in the first half of the measurement period, or the multiple moments are located in the second half of the measurement period.

[0147] In some embodiments, the beam measurement result includes a beam measurement sampling result, and the configuration information is used to configure a filtering method for the beam measurement result and / or a predicted value of the beam measurement result.

[0148] In some embodiments, the filtering method includes a sliding window method and / or a variant sliding window method.

[0149] In some embodiments, the size of the sliding window is the number of the beam measurement results in a measurement period, or the size of the sliding window is the sum of the number of the beam measurement results in a measurement period and the number of predicted values ​​of the beam measurement results.

[0150] In some embodiments, if the first model is used to generate the predicted value of the beam measurement result, the input of the first model is the historical beam measurement result, or the input of the first model is the historical beam measurement result and the historical predicted value of the beam measurement result; if the first model is used to generate the predicted value of the layer 3 cell measurement result, the input of the first model is the historical layer 3 cell measurement result, or the input of the first model is the historical layer 3 cell measurement result and the historical predicted value of the layer 3 cell measurement result; if the first model is used to generate the predicted value of the layer 1 cell measurement result, the input of the first model is the historical layer 1 cell measurement result, or the input of the first model is the historical layer 1 cell measurement result and the historical predicted value of the layer 1 cell measurement result.

[0151] In some embodiments, the input of the first model includes historical location information of the terminal device and / or predicted values ​​of future location information of the terminal device.

[0152] In some embodiments, the RRM measurement result is used for primary cell handover and / or primary-secondary cell handover.

[0153] In an optional embodiment, the above-mentioned receiving unit 1110 may be a transceiver 1330, and the communication device 1300 may further include a processor 1310 and a memory 1320, as specifically shown in FIG13 .

[0154] In an optional embodiment, the sending unit 1210 may be a transceiver 1230 , and the communication device 1300 may further include a processor 1310 and a memory 1320 , as specifically shown in FIG13 .

[0155] FIG13 is a schematic block diagram of an apparatus according to an embodiment of the present application. The dashed lines in FIG13 indicate that the unit or module is optional. Apparatus 1300 may be used to implement the method described in the above method embodiment. Apparatus 1300 may be a chip, a terminal device, or a network device.

[0156] The device 1300 may include one or more processors 1310. The processor 1310 may support the device 1300 to implement the method described in the above method embodiment. The processor 1310 may be a general-purpose processor or a special-purpose processor. For example, the processor may be a central processing unit (CPU). Alternatively, the processor may be another general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic device, discrete hardware component, etc. The general-purpose processor may be a microprocessor or the processor may be any conventional processor, etc.

[0157] The apparatus 1300 may further include one or more memories 1320. The memories 1320 store programs that can be executed by the processor 1310, causing the processor 1310 to perform the methods described in the above method embodiments. The memories 1320 may be independent of the processor 1310 or integrated into the processor 1310.

[0158] The apparatus 1300 may further include a transceiver 1330. The processor 1310 may communicate with other devices or chips via the transceiver 1330. For example, the processor 1310 may transmit and receive data with other devices or chips via the transceiver 1330.

[0159] The present application also provides a computer-readable storage medium for storing a program. The computer-readable storage medium can be applied to a terminal or network device provided in the present application, and the program enables a computer to execute the method performed by the terminal or network device in each embodiment of the present application.

[0160] The present application also provides a computer program product. The computer program product includes a program. The computer program product can be applied to a terminal or network device provided in the present application, and the program causes a computer to execute the method performed by the terminal or network device in each embodiment of the present application.

[0161] The embodiments of the present application also provide a computer program. The computer program can be applied to the terminal or network device provided in the embodiments of the present application, and the computer program enables a computer to execute the method performed by the terminal or network device in each embodiment of the present application.

[0162] It should be understood that the terms "system" and "network" in this application can be used interchangeably. In addition, the terms used in this application are only used to explain the specific embodiments of this application and are not intended to limit this application. The terms "first", "second", "third", and "fourth" in the specification and claims of this application and the accompanying drawings are used to distinguish different objects rather than to describe a specific order. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions.

[0163] In the embodiments of this application, the term "indication" may refer to a direct indication, an indirect indication, or an indication of an association. For example, "A indicates B" may refer to a direct indication of B, e.g., B can obtain information through A; it may refer to an indirect indication of B, e.g., A indicates C, e.g., B can obtain information through C; or it may refer to an association between A and B.

[0164] In the embodiment of the present application, "B corresponding to A" means that B is associated with A and B can be determined based on A. However, it should be understood that determining B based on A does not mean determining B based solely on A, but B can also be determined based on A and / or other information.

[0165] In the embodiments of the present application, the term "corresponding" may indicate a direct or indirect correspondence between the two, or an association relationship between the two, or a relationship between indication and indication, configuration and configuration, etc.

[0166] In the embodiments of the present application, "pre-definition" or "pre-configuration" may be implemented by pre-storing corresponding codes, tables, or other methods that can be used to indicate relevant information in a device (e.g., a terminal device and a network device). The present application does not limit the specific implementation method. For example, pre-definition may refer to information defined in a protocol.

[0167] In the embodiments of the present application, the “protocol” may refer to a standard protocol in the communications field, for example, it may include an LTE protocol, an NR protocol, and related protocols used in future communication systems, and the present application does not limit this.

[0168] In the embodiments of this application, the term "and / or" is simply a description of the association relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this document generally indicates that the related objects are in an "or" relationship.

[0169] In the embodiments of this application, the term "include" can refer to direct inclusion or indirect inclusion. Alternatively, the term "include" in the embodiments of this application can be replaced with "indicates" or "is used to determine." For example, "A includes B" can be replaced with "A indicates B" or "A is used to determine B."

[0170] In various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0171] In the several embodiments provided in this application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are merely schematic. For example, the division of the units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0172] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0173] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0174] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website, computer, server or data center to another website, computer, server or data center via a wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) method. The computer-readable storage medium can be any available medium that can be read by a computer or a data storage device such as a server or data center that includes one or more available media integrated therein. The available medium may be a magnetic medium (eg, a floppy disk, a hard disk, a magnetic tape), an optical medium (eg, a digital versatile disc (DVD)), or a semiconductor medium (eg, a solid state disk (SSD)).

[0175] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of this application. Therefore, the scope of protection of this application should be based on the scope of protection of the claims.

Claims

1. A wireless communication method, characterized in that: include: The terminal device receives first information sent by the network device, where the first information is used by the terminal device to determine a radio resource management RRM measurement result based on a first model.

2. The method according to claim 1, characterized in that The first information includes one or more of the following: Indication information of whether the terminal device is capable of determining the RRM measurement result based on the first model; and The terminal device determines configuration information of the RRM measurement result based on the first model.

3. The method according to claim 2, characterized in that The configuration information is used to configure an algorithm structure associated with the first model, and the algorithm structure is used to determine a function of the first model.

4. The method according to claim 3, characterized in that The functionality of the first model includes the first model being used to generate one or more of the following: Predicted values ​​of beam measurements; The predicted value of the layer 1 cell measurement result; as well as The predicted value of the layer 3 cell measurement result; The beam measurement result includes a beam measurement sampling result and / or a layer 1 beam measurement result.

5. The method according to any one of claims 2 to 4, characterized in that The configuration information is used to configure the number of predicted values ​​that the terminal device is allowed to generate based on the first model within a measurement period.

6. The method according to any one of claims 2 to 5, characterized in that The configuration information is used to configure the position of the predicted value generated based on the first model, and the position of the predicted value is used to indicate the relative position relationship between the predicted value and the measured value in the time domain.

7. The method according to any one of claims 2 to 6, characterized in that The first model is used to generate a predicted value of the beam measurement result, and the configuration information is used to configure a prediction scheme for the beam measurement result.

8. The method according to claim 7, characterized in that The predicted value of the beam measurement result corresponds to a first moment, and the prediction scheme of the beam measurement result is used to indicate that the first moment is located between two adjacent moments corresponding to the beam measurement results.

9. The method according to claim 7, characterized in that The predicted values ​​of the multiple beam measurement results correspond to multiple moments, and the prediction scheme of the beam measurement results is used to indicate that the multiple moments are located between time periods corresponding to two adjacent beam measurement result sets.

10. The method according to claim 9, characterized in that The prediction scheme of the beam measurement result is used to indicate that the multiple moments are located in the first half of the measurement period, or the multiple moments are located in the second half of the measurement period.

11. The method according to any one of claims 7 to 10, characterized in that The beam measurement result includes a beam measurement sampling result, and the configuration information is used to configure a filtering method for the beam measurement sampling result and / or a predicted value of the beam measurement result.

12. The method according to claim 11, characterized in that The filtering method includes a sliding window method and / or a variant sliding window method.

13. The method according to claim 12, characterized in that The size of the sliding window used in the filtering method is the number of the beam measurement results in the measurement period, or the size of the sliding window is the sum of the number of the beam measurement results in the measurement period and the number of predicted values ​​of the beam measurement results.

14. The method according to any one of claims 1 to 13, characterized in that If the first model is used to generate the predicted value of the beam measurement result, the input of the first model is the historical beam measurement result, or the input of the first model is the historical beam measurement result and the historical predicted value of the beam measurement result; If the first model is used to generate a predicted value of a layer 3 cell measurement result, the input of the first model is a historical layer 3 cell measurement result, or the input of the first model is a historical layer 3 cell measurement result and a historical predicted value of the layer 3 cell measurement result; If the first model is used to generate a predicted value of a layer 1 cell measurement result, the input of the first model is a historical layer 1 cell measurement result, or the input of the first model is a historical layer 1 cell measurement result and a historical predicted value of the layer 1 cell measurement result.

15. The method according to any one of claims 1 to 14, characterized in that The input of the first model includes historical location information of the terminal device and / or predicted value of future location information of the terminal device.

16. The method according to any one of claims 1 to 15, characterized in that The RRM measurement result is used for primary cell handover and / or primary and secondary cell handover.

17. A wireless communication method, characterized in that: include: The network device sends first information to the terminal device, where the first information is used by the terminal device to determine a radio resource management RRM measurement result based on a first model.

18. The method according to claim 17, characterized in that The first information includes one or more of the following: Indication information of whether the terminal device is capable of determining the RRM measurement result based on the first model; and The terminal device determines configuration information of the RRM measurement result based on the first model.

19. The method according to claim 18, characterized in that The configuration information is used to configure an algorithm structure associated with the first model, and the algorithm structure is used to determine a function of the first model.

20. The method according to claim 19, wherein The functionality of the first model includes the first model being used to generate one or more of the following: Predicted values ​​of beam measurements; The predicted value of the layer 1 cell measurement result; as well as The predicted value of the layer 3 cell measurement result; The beam measurement result includes a beam measurement sampling result and / or a layer 1 beam measurement result.

21. The method according to any one of claims 18 to 20, characterized in that The configuration information is used to configure the number of predicted values ​​that the terminal device is allowed to generate based on the first model within a measurement period.

22. The method according to any one of claims 18 to 21, characterized in that The configuration information is used to configure the position of the predicted value generated based on the first model, and the position of the predicted value is used to indicate the relative position relationship between the predicted value and the measured value in the time domain.

23. The method according to any one of claims 18 to 22, characterized in that The first model is used to generate a predicted value of a beam measurement result, and the configuration information is used to configure a prediction scheme for the beam measurement result.

24. The method according to claim 23, wherein The predicted value of the beam measurement result corresponds to a first moment, and the prediction scheme of the beam measurement result is used to indicate that: the first moment is located between two adjacent moments corresponding to the beam measurement results.

25. The method according to claim 23, characterized in that The predicted values ​​of the multiple beam measurement results correspond to multiple moments, and the prediction scheme of the beam measurement results is used to indicate that: the multiple moments are located between time periods corresponding to two adjacent sets of beam measurement results.

26. The method according to claim 25, characterized in that The prediction scheme of the beam measurement result is used to indicate that: the multiple moments are located in the first half of the measurement period, or the multiple moments are located in the second half of the measurement period.

27. The method according to any one of claims 23 to 26, characterized in that The beam measurement result includes a beam measurement sampling result, and the configuration information is used to configure a filtering method for the beam measurement sampling result and / or a predicted value of the beam measurement result.

28. The method according to claim 27, characterized in that The filtering method includes a sliding window method and / or a variant sliding window method.

29. The method according to claim 28, characterized in that The size of the sliding window used in the filtering method is the number of the beam measurement results in the measurement period, or the size of the sliding window is the sum of the number of the beam measurement results in the measurement period and the number of predicted values ​​of the beam measurement results.

30. The method according to any one of claims 17 to 29, wherein If the first model is used to generate the predicted value of the beam measurement result, the input of the first model is the historical beam measurement result, or the input of the first model is the historical beam measurement result and the historical predicted value of the beam measurement result; If the first model is used to generate a predicted value of a layer 3 cell measurement result, the input of the first model is a historical layer 3 cell measurement result, or the input of the first model is a historical layer 3 cell measurement result and a historical predicted value of the layer 3 cell measurement result; If the first model is used to generate a predicted value of a layer 1 cell measurement result, the input of the first model is a historical layer 1 cell measurement result, or the input of the first model is a historical layer 1 cell measurement result and a historical predicted value of the layer 1 cell measurement result.

31. The method according to any one of claims 17 to 30, characterized in that The input of the first model includes historical location information of the terminal device and / or predicted value of future location information of the terminal device.

32. The method according to any one of claims 17 to 31, characterized in that The RRM measurement result is used for primary cell handover and / or primary and secondary cell handover.

33. A terminal device, characterized in that: include: A receiving unit is used to receive first information sent by a network device, where the first information is used by the terminal device to determine a radio resource management RRM measurement result based on a first model.

34. The device according to claim 33, characterized in that The first information includes one or more of the following: Indication information of whether the terminal device is capable of determining the RRM measurement result based on the first model; and The terminal device determines configuration information of the RRM measurement result based on the first model.

35. The device according to claim 34, characterized in that The configuration information is used to configure an algorithm structure associated with the first model, and the algorithm structure is used to determine a function of the first model.

36. The apparatus according to claim 35, wherein The functionality of the first model includes the first model being used to generate one or more of the following: Predicted values ​​of beam measurements; The predicted value of the layer 1 cell measurement result; as well as The predicted value of the layer 3 cell measurement result; The beam measurement result includes a beam measurement sampling result and / or a layer 1 beam measurement result.

37. The apparatus according to any one of claims 34 to 36, characterized in that The configuration information is used to configure the number of predicted values ​​that the terminal device is allowed to generate based on the first model within a measurement period.

38. The apparatus according to any one of claims 34 to 37, characterized in that The configuration information is used to configure the position of the predicted value generated based on the first model, and the position of the predicted value is used to indicate the relative position relationship between the predicted value and the measured value in the time domain.

39. The apparatus according to any one of claims 34 to 38, characterized in that The first model is used to generate a predicted value of the beam measurement result, and the configuration information is used to configure a prediction scheme for the beam measurement result.

40. The apparatus according to claim 39, wherein The predicted value of the beam measurement result corresponds to a first moment, and the prediction scheme of the beam measurement result is used to indicate that: the first moment is located between two adjacent moments corresponding to the beam measurement results.

41. The apparatus according to claim 39, wherein The predicted values ​​of the multiple beam measurement results correspond to multiple moments, and the prediction scheme of the beam measurement results is used to indicate that: the multiple moments are located between time periods corresponding to two adjacent sets of beam measurement results.

42. The device according to claim 41, characterized in that The prediction scheme of the beam measurement result is used to indicate that: the multiple moments are located in the first half of the measurement period, or the multiple moments are located in the second half of the measurement period.

43. The apparatus according to any one of claims 39 to 42, characterized in that The beam measurement result includes a beam measurement sampling result, and the configuration information is used to configure a filtering method for the beam measurement sampling result and / or a predicted value of the beam measurement result.

44. The device according to claim 43, characterized in that The filtering method includes a sliding window method and / or a variant sliding window method.

45. The apparatus according to claim 44, wherein The size of the sliding window used in the filtering method is the number of the beam measurement results in the measurement period, or the size of the sliding window is the sum of the number of the beam measurement results in the measurement period and the number of predicted values ​​of the beam measurement results.

46. ​​The apparatus according to any one of claims 33 to 45, characterized in that If the first model is used to generate the predicted value of the beam measurement result, the input of the first model is the historical beam measurement result, or the input of the first model is the historical beam measurement result and the historical predicted value of the beam measurement result; If the first model is used to generate a predicted value of a layer 3 cell measurement result, the input of the first model is a historical layer 3 cell measurement result, or the input of the first model is a historical layer 3 cell measurement result and a historical predicted value of the layer 3 cell measurement result; If the first model is used to generate a predicted value of a layer 1 cell measurement result, the input of the first model is a historical layer 1 cell measurement result, or the input of the first model is a historical layer 1 cell measurement result and a historical predicted value of the layer 1 cell measurement result.

47. The apparatus according to any one of claims 33 to 46, characterized in that The input of the first model includes historical location information of the terminal device and / or predicted value of future location information of the terminal device.

48. The apparatus according to any one of claims 33 to 47, characterized in that The RRM measurement result is used for primary cell handover and / or primary and secondary cell handover.

49. A network device, characterized in that include: A sending unit is used to send first information to a terminal device, where the first information is used by the terminal device to determine a radio resource management RRM measurement result based on a first model.

50. The apparatus according to claim 49, wherein The first information includes one or more of the following: Indication information of whether the terminal device is capable of determining the RRM measurement result based on the first model; and The terminal device determines configuration information of the RRM measurement result based on the first model.

51. The apparatus according to claim 50, wherein The configuration information is used to configure an algorithm structure associated with the first model, and the algorithm structure is used to determine a function of the first model.

52. The apparatus according to claim 51, wherein The functionality of the first model includes the first model being used to generate one or more of the following: Predicted values ​​of beam measurements; The predicted value of the layer 1 cell measurement result; as well as The predicted value of the layer 3 cell measurement result; The beam measurement result includes a beam measurement sampling result and / or a layer 1 beam measurement result.

53. The apparatus according to any one of claims 50 to 52, characterized in that The configuration information is used to configure the number of predicted values ​​that the terminal device is allowed to generate based on the first model within a measurement period.

54. The apparatus according to any one of claims 50 to 53, characterized in that The configuration information is used to configure the position of the predicted value generated based on the first model, and the position of the predicted value is used to indicate the relative position relationship between the predicted value and the measured value in the time domain.

55. The apparatus according to any one of claims 50 to 54, characterized in that The first model is used to generate a predicted value of a beam measurement result, and the configuration information is used to configure a prediction scheme for the beam measurement result.

56. The apparatus according to claim 55, wherein The predicted value of the beam measurement result corresponds to a first moment, and the prediction scheme of the beam measurement result is used to indicate that: the first moment is located between two adjacent moments corresponding to the beam measurement results.

57. The apparatus according to claim 55, wherein The predicted values ​​of the multiple beam measurement results correspond to multiple moments, and the prediction scheme of the beam measurement results is used to indicate that: the multiple moments are located between time periods corresponding to two adjacent sets of beam measurement results.

58. The apparatus according to claim 57, wherein The prediction scheme of the beam measurement result is used to indicate that: the multiple moments are located in the first half of the measurement period, or the multiple moments are located in the second half of the measurement period.

59. The apparatus according to any one of claims 55 to 58, characterized in that The beam measurement result includes a beam measurement sampling result, and the configuration information is used to configure a filtering method for the beam measurement sampling result and / or a predicted value of the beam measurement result.

60. The apparatus according to claim 59, wherein The filtering method includes a sliding window method and / or a variant sliding window method.

61. The apparatus according to claim 60, wherein The size of the sliding window used in the filtering method is the number of the beam measurement results in the measurement period, or the size of the sliding window is the sum of the number of the beam measurement results in the measurement period and the number of predicted values ​​of the beam measurement results.

62. The apparatus according to any one of claims 49 to 61, characterized in that If the first model is used to generate the predicted value of the beam measurement result, the input of the first model is the historical beam measurement result, or the input of the first model is the historical beam measurement result and the historical predicted value of the beam measurement result; If the first model is used to generate a predicted value of a layer 3 cell measurement result, the input of the first model is a historical layer 3 cell measurement result, or the input of the first model is a historical layer 3 cell measurement result and a historical predicted value of the layer 3 cell measurement result; If the first model is used to generate a predicted value of a layer 1 cell measurement result, the input of the first model is a historical layer 1 cell measurement result, or the input of the first model is a historical layer 1 cell measurement result and a historical predicted value of the layer 1 cell measurement result.

63. The apparatus according to any one of claims 49 to 62, characterized in that The input of the first model includes historical location information of the terminal device and / or predicted value of future location information of the terminal device.

64. The apparatus according to any one of claims 49 to 63, characterized in that The RRM measurement result is used for primary cell handover and / or primary and secondary cell handover.

65. A terminal device, characterized in that: The system comprises a transceiver, a memory and a processor, wherein the memory is used to store a program, and the processor is used to call the program in the memory and control the transceiver to receive or send a signal, so as to execute the method according to any one of claims 1 to 16.

66. A network device, characterized in that The system comprises a transceiver, a memory and a processor, wherein the memory is used to store a program, and the processor is used to call the program in the memory and control the transceiver to receive or send a signal to execute the method according to any one of claims 17 to 32.

67. A chip, characterized in that: The device comprises a processor configured to call a program from a memory so that a device equipped with the chip executes the method according to any one of claims 1 to 16 or 17 to 32.

68. A computer-readable storage medium, characterized in that A program is stored thereon, the program causing a computer to execute the method according to any one of claims 1-16 or 17-32.

69. A computer program product, characterized in that The method comprises a program for causing a computer to execute the method according to any one of claims 1 to 16 or 17 to 32.

70. A computer program, characterized in that The computer program causes a computer to execute the method according to any one of claims 1 to 16 or 17 to 32.

Images