Processing method and apparatus, device, and storage medium used for measurement

Abstract

Disclosed are a processing method and apparatus, a device, and a storage medium used for measurement, and belonging to the technical field of mobile communication. The method is executed by a terminal device, and comprises: receiving measurement indication information, the measurement indication information being used to indicate that measurement be performed on a spatial filter in one or more measurement sets to obtain a measurement result, the measurement result being used to predict link quality of the spatial filter in one or more prediction sets, to obtain a prediction result. The present solution provides a measurement indication solution for predicting a measurement result of a spatial filter, ensures measurement flexibility for the measurement result of the spatial filter, and improves prediction efficacy for the spatial filter.

Description

Processing method, device, equipment and storage medium for measurement Technical Field

[0001] The present application relates to the field of mobile communication technology, and in particular to a processing method, apparatus, device and storage medium for measurement. Background Art

[0002] In the 5G NR system, in order to support beam management of terminal devices, the terminal needs to perform beam measurement on candidate cells adjacent to the serving cell.

[0003] In related technologies, in order to reduce the overhead of beam measurement performed by terminal devices, a solution is proposed to predict the measurement results of other beams through a machine learning model based on the measurement results of some beams by the terminal devices.

[0004] Summary of the Invention

[0005] The embodiments of the present application provide a processing method, apparatus, device, and storage medium for measurement. The technical solution is as follows:

[0006] In one aspect, an embodiment of the present application provides a processing method for measurement, the method being performed by a terminal device, the method comprising:

[0007] receiving measurement indication information, where the measurement indication information is used to instruct to measure one or more spatial filters in a measurement set to obtain a measurement result;

[0008] The measurement results are used to predict the link quality of one or more spatial filters in the prediction set to obtain a prediction result.

[0009] In one aspect, an embodiment of the present application provides a processing method for measurement, the method being performed by a network device, the method comprising:

[0010] Sending measurement indication information to a terminal device, where the measurement indication information is used to instruct the terminal device to measure one or more spatial filters in a measurement set to obtain a measurement result;

[0011] The measurement results are used to predict the link quality of one or more spatial filters in the prediction set to obtain a prediction result.

[0012] On the other hand, an embodiment of the present application provides a processing device for measurement, the device comprising:

[0013] a receiving module, configured to receive measurement indication information, where the measurement indication information is used to indicate that measurement results are obtained by measuring one or more spatial filters in a measurement set;

[0014] The measurement results are used to predict the link quality of one or more spatial filters in the prediction set to obtain a prediction result.

[0015] On the other hand, an embodiment of the present application provides a processing device for measurement, the device comprising:

[0016] a sending module, configured to send measurement instruction information to a terminal device, wherein the measurement instruction information is used to instruct the terminal device to measure one or more spatial filters in a measurement set to obtain a measurement result;

[0017] The measurement results are used to predict the link quality of one or more spatial filters in the prediction set to obtain a prediction result.

[0018] On the other hand, an embodiment of the present application provides a terminal device, the terminal device including a processor, a memory, and a transceiver;

[0019] The memory stores a computer program, and the processor executes the computer program so that the terminal device implements the above-mentioned processing method for measurement.

[0020] On the other hand, an embodiment of the present application provides a network device, the network device including a processor, a memory, and a transceiver;

[0021] The memory stores a computer program, and the processor executes the computer program to enable the network device to implement the above-mentioned processing method for measurement.

[0022] On the other hand, an embodiment of the present application further provides a computer-readable storage medium, wherein the storage medium stores a computer program, and the computer program is loaded and executed by a processor to implement the above-mentioned processing method for measurement.

[0023] On the other hand, the present application further provides a chip, which is used to run in a communication device so that the communication device executes the above-mentioned processing method for measurement.

[0024] In another aspect, the present application provides a computer program product, comprising computer instructions stored in a computer-readable storage medium. A processor of a communication device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, causing the communication device to perform the above-described processing method for measurement.

[0025] In yet another aspect, the present application provides a computer program, which is executed by a processor of a communication device to implement the above-mentioned processing method for measurement.

[0026] An embodiment of the present application provides a resource configuration solution, in which a network device instructs a terminal device to measure the spatial filters in one or more measurement sets through measurement indication information, so as to subsequently predict the prediction results of the spatial filters corresponding to one or more prediction sets, thereby providing a measurement indication solution for predicting the measurement results of the spatial filters, ensuring the flexibility of the measurement when predicting the measurement results of the spatial filters, and thereby improving the prediction effect of the spatial filters. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] FIG1 is a schematic diagram of the architecture of a communication system provided by an embodiment of the present application;

[0028] FIG2 is a diagram of a neuron structure involved in this application;

[0029] FIG3 is a diagram of a neural network structure involved in this application;

[0030] FIG4 is a diagram showing the relationship between the input and output of a beam (pair) model;

[0031] FIG5 is a diagram showing the relationship between input and output of an optimal beam (pair) quality model;

[0032] Figure 6 is a diagram showing another implementation of the model;

[0033] FIG7 is a flowchart of a processing method for measurement provided by one embodiment of the present application;

[0034] FIG8 is a flowchart of a processing method for measurement provided by one embodiment of the present application;

[0035] FIG9 is a flow chart of the UE-side model spatial domain mobility prediction;

[0036] FIG10 is a schematic diagram of spatial domain mobility measurement and prediction;

[0037] FIG11 is an input-output relationship diagram of the spatial domain mobility prediction model 1;

[0038] FIG12 is an input-output relationship diagram of the spatial domain mobility prediction model 2;

[0039] FIG13 is an input-output relationship diagram of the spatial domain mobility prediction model 3;

[0040] FIG14 is a flowchart of a processing method for measurement provided by one embodiment of the present application;

[0041] FIG15 is a flow chart of the spatial domain mobility prediction of the NW side model;

[0042] FIG16 is a block diagram of a processing device for measurement provided by one embodiment of the present application;

[0043] FIG17 is a block diagram of a processing device for measurement provided by one embodiment of the present application;

[0044] FIG18 is a schematic structural diagram of a communication device provided in one embodiment of the present application. DETAILED DESCRIPTION

[0045] In order to make the objectives, technical solutions and advantages of this application clearer, the implementation methods of this application are further described in detail below with reference to the accompanying drawings.

[0046] The network architecture and business scenarios described in the embodiments of the present application are intended to more clearly illustrate the technical solutions of the embodiments of the present application, and do not constitute a limitation on the technical solutions provided by the embodiments of the present application. A person skilled in the art will appreciate that, with the evolution of the network architecture and the emergence of new business scenarios, the technical solutions provided by the embodiments of the present application are equally applicable to similar technical problems.

[0047] 1 shows a schematic diagram of a communication system according to an exemplary embodiment of the present application, which includes a network device 110 and a terminal device 120, and / or a terminal device 120 and a terminal device 130, which are not limited in the present application.

[0048] The network device 110 in the present application provides wireless communication functions, and the network device 110 includes but is not limited to: Evolved Node B (eNB), Radio Network Controller (RNC), Node B (NB), Base Station Controller (BSC), Base Transceiver Station (BTS), Home Base Station (e.g., Home Evolved Node B, or Home Node B, HNB), Baseband Unit (BBU), Access Point (AP) in Wireless Fidelity (Wi-Fi) system, Wireless Relay Node, Wireless Backhaul Node, Transmission Point (TP) or Transmission and Reception Point (TRP), etc., and can also be the Next Generation Node B (NGNB) in the 5th Generation (5G) mobile communication system. The term "gNB" refers to a base station (B, gNB) or a transmission point (TRP or TP), or one or a group of antenna panels (including multiple antenna panels) of a base station in a 5G system, or a network node constituting a gNB or a transmission point, such as a baseband unit (BBU) or a distributed unit (DU), or a base station in a Beyond Fifth Generation (B5G) or a 6th Generation (6G) mobile communication system, or a core network (CN), fronthaul, backhaul, radio access network (RAN), network slicing, or a serving cell, primary cell (PCell), primary secondary cell (PSCell), special cell (SpCell), secondary cell (SCell), or neighboring cell of a terminal device.

[0049] The terminal device 120 and / or terminal device 130 in this application are also called user equipment (UE), access terminal, user unit, user station, mobile station, mobile station, remote station, remote terminal, mobile device, user terminal, terminal, wireless communication device, user agent, and user device. The terminals include, but are not limited to, handheld devices, wearable devices, vehicle-mounted devices, and Internet of Things devices, such as mobile phones, tablet computers, e-book readers, laptop computers, desktop computers, televisions, game consoles, mobile Internet devices (MIDs), augmented reality (AR) terminals, virtual reality (VR) terminals, and mixed reality (MR) terminals, wearable devices, handles, electronic tags, controllers, wireless terminals in industrial control, wireless terminals in self-driving, wireless terminals in remote medical care, wireless terminals in smart grids, wireless terminals in transportation safety, wireless terminals in smart cities, wireless terminals in smart homes, wireless terminals in remote medical surgery, cellular phones, cordless phones, session initiation protocol (SIP) phones, wireless local loops (WLANs), and wireless terminals in industrial control. Loop (WLL) stations, personal digital assistants (PDA), TV set-top boxes (STB), customer premises equipment (CPE), etc.

[0050] The network device 110 and the terminal device 120 communicate with each other via some air interface technology, such as a Uu interface.

[0051] Exemplarily, there are two communication scenarios between the network device 110 and the terminal device 120: an uplink communication scenario and a downlink communication scenario. Uplink communication refers to sending signals to the network device 110; downlink communication refers to sending signals to the terminal device 120.

[0052] The terminal device 120 and the terminal device 130 communicate with each other via some air interface technology, such as a PC5 interface.

[0053] In some embodiments, there are two communication scenarios between the terminal device 120 and the terminal device 130: a first sideline communication scenario and a second sideline communication scenario. The first sideline communication refers to sending signals to the terminal device 130; the second sideline communication refers to sending signals to the terminal device 120.

[0054] Terminal device 120 and terminal device 130 are both within the network coverage and located in the same cell, or terminal device 120 and terminal device 130 are both within the network coverage but located in different cells, or terminal device 120 is within the network coverage but terminal device 130 is outside the network coverage.

[0055] The technical solutions provided in the embodiments of the present application can be applied to various communication systems, such as: Global System of Mobile communication (GSM) system, Code Division Multiple Access (CDMA) system, Wideband Code Division Multiple Access (WCDMA) system, General Packet Radio Service (GPRS), Long Term Evolution (LTE) system, LTE Frequency Division Duplex (FDD) system, LTE Time Division Duplex (TDD) system, Advanced Long Term Evolution (LTE-A) system, Universal Mobile Telecommunication System (UMTS), Worldwide Interoperability for Microwave Access (WiMAX) communication system, 5G mobile communication system, New Radio (NR) system, NR system evolution system, LTE on unlicensed spectrum (LTE-U) system, NR on unlicensed spectrum (NR-based access to unlicensed spectrum) system. Unlicensed spectrum, NR-U) system, terrestrial communication network (Terrestrial Networks, TN) system, non-terrestrial communication network (Non-Terrestrial Networks, NTN) system, wireless local area network (Wireless Local Area Networks, WLAN), wireless fidelity (Wireless Fidelity, Wi-Fi), cellular Internet of Things system, cellular passive Internet of Things system, can also be applied to the subsequent evolution system of the 5G NR system, and can also be applied to B5G, 6G and subsequent evolution systems. In some embodiments of the present application, "NR" may also be referred to as a 5G NR system or a 5G system. Among them, the 5G mobile communication system may include non-standalone networking (NSA) and / or standalone networking (SA).

[0056] The technical solutions provided in the embodiments of the present application can also be applied to machine type communication (MTC), long term evolution technology for machine-to-machine communication (LTE-M), device-to-device (D2D) network, machine-to-machine (M2M) network, Internet of Things (IoT) network or other networks. Among them, the IoT network can include, for example, the Internet of Vehicles. Among them, the communication mode in the Internet of Vehicles system is collectively referred to as vehicle to other devices (Vehicle to X, V2X, X can represent anything), for example, the V2X can include: vehicle to vehicle (V2V) communication, vehicle to infrastructure (V2I) communication, vehicle to pedestrian communication (V2P) or vehicle to network (V2N) communication, etc.

[0057] 1) NR inter-cell beam management

[0058] In R17 beam management, based on the UE's capability report, the network (NetWork, NW) will configure and / or activate the beam management function for non-serving cells for the UE, including beam measurement, beam reporting and beam indication.

[0059] The UE can measure non-serving cells in addition to the serving cell. The UE's capabilities support measuring 1, 2, 3, or 7 non-serving cells. Non-serving cells have different physical cell identifiers (PCIs) from the serving cell. The UE measures the Synchronization Signal / Physical Broadcast Channel Block (SSB) of non-serving cells to select a downlink beam (pair) with better beam quality and report it to the network network (NW).

[0060] In one beam reporting, the UE can only report up to four downlink transmit beams from a non-serving cell, which includes the resource index corresponding to the beam (Channel State Information Reference Signal Resource Indicator (CRI) or SSB Resource Indicator (SSBRI)) and link quality, such as Level 1-Reference Signal Receiving Power (L1-RSRP).

[0061] The NW uses a unified Transmission Configuration Indication (TCI) state to indicate beams from non-serving cells. Specifically, the NW pre-configures the reference signal from the non-serving cell (using an additional PCI index) in the indicated unified TCI state. Once this downlink (DL) / joint TCI state is indicated to the UE, it indicates that the UE will use it to receive the downlink beam from the non-serving cell.

[0062] 2) NR Layer 1 / Layer 2 Triggered Mobility

[0063] In Release 18's L1 / L2-triggered mobility management, compared to the inter-cell beam management in Release 17, standardization has enhanced measurement and reporting to a certain extent. The UE can now measure both the serving cell and the target cell configured by the network (NW), and report up to M x L ​​measurement results (depending on UE capabilities) in a single report. Obviously, measuring a large number of candidate cells requires significant reference signal overhead, as well as the latency required for the UE to measure these reference signals. After all, the UE often cannot simultaneously measure multiple beams from multiple candidate cells.

[0064] 3) Neural Networks (NN)

[0065] A neural network is a computational model consisting of multiple interconnected neuron nodes. The connections between the nodes represent weighted values ​​from input signals to output signals, called weights. Each node performs a weighted summation of different input signals and outputs them through a specific activation function. A diagram of a neuron structure involved in this application is shown in Figure 2.

[0066] Deep Neural Network: This application involves a neural network structure diagram as shown in Figure 3, which includes an input layer, a hidden layer, and an output layer. Through different connection methods, weights, and activation functions of multiple neurons, different outputs can be generated, thereby fitting the mapping relationship from input to output. Each upper-level node is connected to all of its lower-level nodes. This fully connected model can also be called a deep neural network (DNN) in this case. The NN model can perform beam prediction in the spatial domain.

[0067] Acquisition of the model: A NN model can be trained and obtained through the processes of data set construction, training, verification and testing. The NN model involved in this application may have been trained in advance through offline training or online training. It should be noted that offline training and online training are not mutually exclusive. First, the NW can obtain a static training result through offline training of the data set, which can be referred to as offline training here. During the use of the NN by the NW or UE, as the UE further measures and / or reports, the NN model can continue to collect more data and perform real-time online training to optimize the parameters of the NN model to achieve better inference and prediction results.

[0068] 4) Beam management use cases based on artificial intelligence (AI) / machine learning (ML)

[0069] As one of the main use cases in the Release 18 AI project, AI / ML-based beam management has garnered widespread attention from various companies, leading to multiple rounds of use case selection and simulation hypothesis discussions. A preliminary implementation framework has also been agreed upon for AI / ML-based spatial and temporal beam prediction. Currently, two use cases have been defined: downlink beam prediction in the spatial and temporal domains. The definition of spatial-domain beam (pair) prediction is as follows:

[0070] For AI / ML-based beam management, support BM-Case1 and BM-Case2 for characterization and baseline performance evaluations:

[0071] BM-Case 1: Spatial-domain DL beam prediction for Set A of beams based on measurement results of Set B of beams;

[0072] BM-Case 2: Temporal DL beam prediction for Set A of beams based on the historic measurement results of Set B of beams;

[0073] Details of BM-Use Case 1 and BM-Use Case 2 are to be determined; other sub-use cases are to be determined;

[0074] Note: For BM-Case1 and BM-Case2, Beams in Set A and Set B can be in the same Frequency Range.

[0075] The beam prediction in the spatial domain (BM-Case1) is as follows:

[0076] The optimal downlink beam (pair) in Set A is predicted by measuring the beams (pairs) in Set B. Set B can be a subset of Set A, containing a subset of beams (pairs). Set A can be considered the full set of beams (pairs). Set B and Set A can be two different beam sets, meaning that Set B is a small set of wide beams that roughly spatially overlaps the large number of narrow beams in Set A.

[0077] Model Implementation: Using the input and output diagrams of the beam (pair) model shown in Figure 4 and the input and output diagram of the optimal beam (pair) quality model shown in Figure 5 as examples, it can be understood that two different models use the same input (Set B) and have two different outputs: one is the predicted top-K beam (pair) index, and the other is the link quality of the top-K beam (pair), namely L1-RSRP. Another model implementation diagram can be shown in Figure 6.

[0078] Figure 4 shows the input and output relationship of a beam (pair) index prediction model. This model can be considered to solve a multi-classification problem. The model maps the L1-RSRP of a subset (Set B as input) to the optimal K beam (pair) indices. The output is the optimal K beam (pair) indices selected from the entire set, that is, the K beam (pair) indices with the highest L1-RSRP. The label used by this model is the optimal (i.e., the highest L1-RSRP) beam (pair) index measured in the entire set.

[0079] Figure 5 shows a schematic diagram of the optimal beam (pair) quality prediction model, which can be understood as a linear regression problem. Its input and output relationship is the relationship between the input L1-RSRP of a subset of the beams (pairs) and the optimal L1-RSRP of the K beams (pairs). The input is the same as the beam (pair) prediction model in Figure 4, but the output is the K (K >= 1) optimal L1-RSRPs. The labels are the optimal K L1-RSRPs measured in the entire set and / or the corresponding K beam (pair) indices.

[0080] In Figure 6, the model outputs all L1-RSRPs for the beams (pairs) in Set A. By sorting all predicted L1-RSRPs from high to low, the top K predicted L1-RSRPs are selected. The corresponding optimal K beam (pair) indices are then found based on the output positions of these top K L1-RSRPs. In summary, this model can implement the functions of both Figures 4 and 5. However, its training requires a larger dataset.

[0081] It should be noted that the word "beam (pair)" means "beam" or "beam pair". Specifically, whether uplink or downlink, a beam in this application can refer to a transmit beam or a receive beam, and a beam pair refers to a pair of a transmit beam and a receive beam.

[0082] In subsequent solutions of this application, "beam" can be described as a "spatial filter". Optionally, the meanings of "beam" and "spatial filter" below are the same, or the descriptions of "beam" and "spatial filter" can be interchangeable.

[0083] For the model involved in this application, its output can be understood as inference or prediction. In this application, inference and prediction have the same meaning and can be interchangeable.

[0084] Optionally, the above-mentioned Set B and Set A respectively represent the measurement set and prediction set (such as the full set) of the downlink beam (pair) prediction.

[0085] At present, the R18NR standard already supports multi-cell beam management and layer 1 / layer 2 triggered mobility management. The scanning of a large number of spatial beams (pairs) in the downlink will bring a lot of reference signal overhead and measurement delay. For example, each candidate cell deploys 64 different downlink transmission directions in the frequency range (FR) 2 (carried by up to 64 SSBs), and the UE uses multiple beams for reception (assuming that each antenna panel has 4 different receiving beams). Then the UE needs to measure at least 64*4=256 beam pairs, which corresponds to a downlink resource overhead of 256 resources. Considering that the total number of serving cells and candidate cells is at least 8, how to reduce the UE's measurement overhead and the corresponding delay is a question worth considering.

[0086] This application uses an AI / ML-based method, through training with a large amount of data, so that the model can infer the optimal candidate cell (including the current serving cell) and / or the optimal candidate beam (pair) of the cell, and / or the predicted link quality of the beam (pair), such as L1-RSRP, with only a small amount of measurement. To this end, this application proposes a solution for instructing a terminal device to measure a measurement set through a network device to obtain a prediction result of a prediction set based on an AI / ML model.

[0087] This application can be applied to scenarios where a trained AI / ML model is used for mobility-related predictions. Limited spatial beam (pair) measurements can be used to select the most suitable cell and the serving beam (pair) within the cell from a global perspective (multiple candidate cells and all corresponding beams (pairs)). In the solution shown in this application, the model responsible for mobility prediction can be deployed on the UE side or the NW side.

[0088] Please refer to FIG7 , which shows a flowchart of a measurement processing method provided by an embodiment of the present application. The method can be interactively executed by a terminal device and a network device, wherein the terminal device can be the terminal device 120 or the terminal device 130 in the network architecture shown in FIG1 , and the network device can be the network device 110 in the network architecture shown in FIG1 . The method can include the following steps:

[0089] In step 701, the network device sends measurement indication information to the terminal device, and the terminal device receives the measurement indication information; the measurement indication information is used to instruct the terminal device to measure one or more spatial filters in the measurement set to obtain measurement results; the measurement results are used to predict the link quality of the spatial filters in one or more prediction sets to obtain prediction results.

[0090] For example, the above measurement results may be input into a prediction model to obtain the prediction results of the prediction model outputting the link quality of one or more spatial filters in the prediction set.

[0091] To sum up, in the scheme shown in the embodiment of the present application, the network device instructs the terminal device to measure the spatial filters in one or more measurement sets through measurement indication information, so as to subsequently obtain the prediction results of the spatial filters corresponding to one or more prediction sets through prediction, thereby providing a measurement indication scheme for predicting the measurement results of the spatial filter, ensuring the flexibility of the measurement when predicting the measurement results of the spatial filter, and thereby improving the prediction effect of the spatial filter.

[0092] The solution shown in the above embodiment of the present application can be implemented as a mobility prediction technology based on a spatial domain AI / ML model, with the measurement results of multiple cells as the input of the model, and the model on the UE side or NW side predicts (outputs) the optimal cell and / or the optimal beam (pair) under the cell, and / or the link quality corresponding to the beam (pair). Based on this, the solution involved in the present application may also include signaling that supports the input and output of the model, such as UE capability reporting, NW configuration and activation, UE reporting of periodic / semi-continuous / non-periodic / L1 or L2 mobility events, etc., thereby reducing the overhead and delay of downlink multi-cell beam (pair) measurement.

[0093] In some embodiments, if the model is deployed on the UE side, that is, the process of predicting the link quality of one or more spatial filters in the prediction set is performed by the UE, the UE reports to the NW whether the measurement and prediction of the spatial domain mobility on the UE side is supported.

[0094] In some embodiments, the NW configures and / or activates a multi-cell measurement set and prediction set, i.e., Set B, based on the UE's capability for mobility measurement and prediction. n (1≤n≤N) and Set A p (1≤p≤P), where each measurement set and prediction set can correspond to a candidate cell respectively.

[0095] In some embodiments, AI / ML performs mobility prediction for multiple cells, including the current serving cell and multiple candidate cells.

[0096] In some embodiments, the UE may measure SSB resources and / or CSI-RS resources (including CSI-RS for mobility resources) of multiple cells.

[0097] In some embodiments, the output of the UE-side model is the optimal L candidate cells, the optimal beam (pair) index in each optimal cell and / or the link quality corresponding to each optimal beam (pair) index.

[0098] In some embodiments, the UE may perform conventional periodic / semi-persistent / aperiodic reporting, and may also perform reporting based on L1 / L2 mobility events.

[0099] In some embodiments, for reporting of mobility, this case provides a specific reporting format, which includes a PCI index or a Set A index, a corresponding resource index CRI or SSBRI, and RSRP.

[0100] In some embodiments, the UE sends a cell handover request to the NW, which includes a candidate cell ID, a beam (pair) index corresponding to the candidate cell, and / or a link quality corresponding to the beam (pair) index. The NW then sends a confirmation of the cell request information to the UE.

[0101] In some embodiments, the mobility prediction model can be deployed on the NW side, that is, the above process of predicting the link quality of the spatial filters in one or more prediction sets is performed by the NW, and the UE completes the measurement of multiple cell measurement sets and reports the measurement results to the NW.

[0102] Regarding the above-mentioned embodiments, the subsequent embodiments of this application will be introduced in detail by taking the model deployed on the terminal device side or on the network device side as an example.

[0103] Based on the solution shown in FIG7 above, please refer to FIG8 , which shows a flowchart of a processing method for measurement provided by an embodiment of the present application, which can be interactively executed by a terminal device and a network device; wherein the terminal device and the network device can be the terminal device 120 and the network device 110 in the network architecture shown in FIG1 ; or, the terminal device and the network device can be the terminal device 130 and the network device 110 in the network architecture shown in FIG1 . When the process of predicting the link quality of one or more spatial filters in the prediction set is performed by the terminal device, for example, when the prediction model is set in the terminal device, as shown in FIG8 , the following steps can be included:

[0104] Step 801: The network device sends measurement instruction information to the terminal device, and the terminal device receives the measurement instruction information.

[0105] The measurement indication information is used to instruct the terminal device to measure one or more spatial filters in the measurement set to obtain measurement results; the measurement results are used to predict the link quality of the spatial filters in one or more prediction sets to obtain prediction results.

[0106] In some embodiments, the measurement indication information may be carried via Radio Resource Control (RRC) signaling.

[0107] In other embodiments, the above-mentioned measurement indication information can also be carried through other signaling other than RRC, for example, through a Media Access Control (MAC) control element (CE), or through a random access message sent by a network device to a terminal device.

[0108] In some embodiments, the measurement indication information is used to configure one or more measurement sets and / or to activate one or more measurement sets.

[0109] For example, the above-mentioned measurement indication information can configure one or more measurement sets to the terminal device. Subsequently, the network device instructs the terminal device to measure the one or more measurement sets previously configured through additional signaling, or the terminal device determines whether to measure the one or more measurement sets.

[0110] For another example, if the terminal device is pre-configured with several measurement sets, the measurement indication information may instruct the terminal to enable (activate) one or more of the measurement sets, and the terminal device may perform measurements on the one or more measurement sets. Optionally, the measurement sets may be pre-defined by a protocol or pre-configured to the terminal device by the network device through other signaling.

[0111] For another example, the measurement indication information may configure one or more measurement sets for the terminal device, and at the same time instruct the network device to start measuring the one or more measurement sets (ie, activate one or more measurement sets).

[0112] In some embodiments, the one or more prediction sets correspond to a current serving cell of the terminal device and one or more candidate cells of the terminal device, respectively.

[0113] In the above embodiment, the prediction set can cover the current service cell of the terminal device, as well as one or more candidate cells of the terminal device, so that the terminal device and / or network device can obtain complete measurement / prediction results of the current service cell of the terminal device, as well as one or more candidate cells of the terminal device, to ensure that management processes such as cell switching are subsequently performed based on the measurement or prediction results.

[0114] For example, the one or more prediction sets mentioned above can be the current serving cell of the terminal device, and a set consisting of all beams (spatial filters) corresponding to one or more candidate cells of the terminal device (compared to one or more measurement sets, the one or more prediction sets can be a full set).

[0115] Optionally, each of the one or more prediction sets may correspond to a cell, for example, the prediction set includes all beams corresponding to the cell. Alternatively, each of the one or more prediction sets may correspond to some beams in a cell; or each of the one or more prediction sets may correspond to all beams in multiple cells.

[0116] In some embodiments, the one or more measurement sets correspond to a current serving cell of the terminal device and one or more candidate cells of the terminal device, respectively.

[0117] In the above embodiment, the measurement set can cover the current service cell of the terminal device and one or more candidate cells of the terminal device, so that the prediction model makes predictions through the measurement results of the current service cell of the terminal device and part of the beam of each cell in the one or more candidate cells of the terminal device, thereby ensuring the accuracy of the prediction.

[0118] For example, the one or more measurement sets mentioned above may be the current serving cell of the terminal device, and a set consisting of partial beams (spatial filters) corresponding to one or more candidate cells of the terminal device (compared to one or more prediction sets, the one or more measurement sets may be a subset thereof).

[0119] Optionally, each of the one or more measurement sets may correspond to a cell, for example, the measurement set may include a beam / multiple partial beams corresponding to the cell. Alternatively, each of the one or more measurement sets may correspond to a beam among the partial beams in a cell.

[0120] In some embodiments, the prediction result is used to indicate one or more of the following:

[0121] The best cell among the cells corresponding to one or more prediction sets;

[0122] The optimal spatial filter or the optimal spatial filter pair under the optimal cell;

[0123] and, the link quality of the optimal spatial filter or optimal spatial filter pair.

[0124] Among them, the optimal cell among the cells corresponding to the above-mentioned one or more prediction sets may refer to one or more cells with the highest prediction results (such as link quality) among the cells corresponding to one or more prediction sets; wherein the prediction result of a cell may be the highest value among the prediction results of the beam / beam pair corresponding to the cell; or, the prediction result of a cell may be the average value of the prediction results of the beam / beam pair corresponding to the cell.

[0125] In some embodiments, the prediction results include one or more of the following:

[0126] Identifiers of L best cells among the cells corresponding to one or more prediction sets; L is an integer greater than or equal to 1;

[0127] The index of the best spatial filter or the index of the best spatial filter pair in the L best cells;

[0128] and the link quality corresponding to the index of the optimal spatial filter, or the link quality corresponding to the index of the optimal spatial filter pair.

[0129] In the above embodiment, the optimal cell among the cells corresponding to one or more prediction sets can be indicated by the identifiers of L optimal cells among the cells corresponding to one or more prediction sets; wherein L can be a predefined value or a value indicated by the network device to the terminal device (for example, through RRC signaling).

[0130] The optimal spatial filter / optimal spatial filter pair in the above-mentioned optimal cell can be indicated by the index of the optimal spatial filter / optimal spatial filter pair.

[0131] In some embodiments, the identification of the best cell includes one or more of the following:

[0132] The physical cell identifier (PCI) of the optimal cell; each cell may correspond to one PCI, and the prediction model may output the PCI corresponding to each of the L optimal cells;

[0133] The PCI index of the best cell; wherein the PCIs of one or more cells may form a PCI set, which may be represented by an index (i.e., a PCI index). The prediction model may output the PCI index of the set consisting of the PCIs corresponding to the L best cells, thereby reducing the number of bits of information contained in the identifier of the best cell when the number of best cells is greater than or equal to 2;

[0134] Configuration index of the optimal cell;

[0135] The index of the prediction set to which the best cell belongs.

[0136] In some embodiments, the index of the optimal spatial filter or the index of the optimal spatial filter pair comprises:

[0137] Channel State Information Reference Signal CSI-RS Resource Indicator CRI of the optimal spatial filter or the optimal spatial filter pair;

[0138] and / or, the synchronization signal block SSB resource indication SSB RI of the optimal spatial filter or the optimal spatial filter pair.

[0139] In some embodiments, link quality includes one or more of the following:

[0140] Layer 1 reference signal received power L1-RSRP, layer 1 signal to interference plus noise ratio L1-SINR, layer 1 received signal strength indicator L1-RSSI, layer 1 reference signal received quality L1-RSRQ, and channel quality indicator CQI.

[0141] Step 802: The network device sends prediction indication information to the terminal device, and the terminal device receives the prediction indication information.

[0142] The prediction indication information is used to configure one or more prediction sets and / or to activate one or more prediction sets.

[0143] For example, the above-mentioned prediction indication information can configure one or more prediction sets to the terminal device. Subsequently, the network device instructs the terminal device through additional signaling to predict the one or more prediction sets previously configured, or the terminal device determines whether to predict the one or more prediction sets.

[0144] For another example, the terminal device is pre-configured with several prediction sets / groups. The prediction indication information may instruct the terminal to enable (activate) one or more prediction sets from the several prediction sets / groups, and the terminal device performs measurements on the one or more prediction sets. Optionally, the several prediction sets / groups may be pre-defined by a protocol, or pre-configured to the terminal device by the network device through other signaling.

[0145] For another example, the prediction indication information may configure one or more prediction sets for the terminal device, and at the same time instruct the network device to start measuring the one or more prediction sets (ie, activate one or more prediction sets).

[0146] In some embodiments, the above-mentioned prediction indication information can be carried through RRC signaling.

[0147] In other embodiments, the above-mentioned prediction indication information may also be carried through other signaling other than RRC, for example, carried through MAC CE, or carried through a random access message sent by a network device to a terminal device.

[0148] In some embodiments, the measurement indication information and the prediction indication information may be carried by the same signaling, or the measurement indication information and the prediction indication information may be carried by different signaling.

[0149] In some embodiments, the method further comprises:

[0150] The terminal device reports the capability information of the terminal device to the network device; the network device receives the capability information of the terminal device reported by the terminal device; wherein the capability information is used to indicate the capability of the terminal device to measure and / or predict spatial domain mobility; the capability information of the terminal device is used by the network device to determine one or more measurement sets, and / or one or more prediction sets.

[0151] In the above embodiment, one or more measurement sets, and / or one or more prediction sets, may be determined by the capability information of the terminal device, and the network device may determine which measurement sets and prediction sets to configure or activate for the terminal based on the capability information reported by the terminal.

[0152] In some embodiments, the capability information includes at least one of the following information:

[0153] Whether the terminal device supports measurement and / or prediction of spatial domain mobility;

[0154] When the terminal device supports measurement of spatial domain mobility, the terminal device supports a maximum number of candidate cells for measurement on all downlink component carriers (CCs) / bandwidth parts (BWPs);

[0155] When the terminal device supports prediction of spatial domain mobility, the terminal device supports a maximum number of predicted candidate cells on all downlink CCs / BWPs;

[0156] When the terminal device supports measurement of spatial domain mobility, the terminal device supports a maximum number of measurement sets on a downlink CC / BWP; each measurement set corresponds to one cell;

[0157] In the case where the terminal device supports prediction of spatial domain mobility, the terminal device supports a maximum number of prediction sets on all downlink CCs / BWPs; each prediction set corresponds to one cell.

[0158] Step 803: The terminal device measures the spatial filters in one or more measurement sets to obtain measurement results.

[0159] In the process of accessing the service cell and communicating, the terminal device may regularly / irregularly measure the spatial filters in the above one or more measurement sets.

[0160] In some embodiments, each of the one or more measurement sets corresponds to a cell, and the measurement results of the spatial filters in the one or more measurement sets include:

[0161] Measurement results of downlink reference signal resources of cells corresponding to one or more measurement sets on spatial filters in one or more measurement sets.

[0162] In some embodiments, the downlink reference signal resources include SSB resources and / or CSI-RS resources.

[0163] Step 804: The terminal device reports prediction information to the network device according to the prediction result, and the network device receives the prediction information reported by the terminal device according to the prediction result.

[0164] In the scheme shown in the embodiment of the present application, after the terminal device obtains the measurement results of the spatial filters in one or more measurement sets, it can input part or all of the measurement results of the spatial filters in the one or more measurement sets into the prediction model to obtain the prediction results of the one or more prediction sets as the output of the prediction model.

[0165] After the terminal device obtains the prediction results of one or more prediction sets, it can report prediction information to the network device based on the prediction results; wherein the above prediction information may include all the information in the prediction results, or the above prediction information may also include part of the information in the prediction results.

[0166] For example, the terminal device can determine the reported prediction information based on the relationship between the prediction result corresponding to the service cell and the prediction results of other cells in the prediction results; or, the above prediction information can be determined by the relationship between the prediction result corresponding to the service cell and the prediction results of the candidate cell.

[0167] For example, if the prediction result corresponding to the service cell is the best among the prediction results of the above one or more prediction sets, the prediction information reported by the terminal device may include the prediction result of the current service cell; if the prediction result corresponding to the service cell is the best or not the best among the prediction results of the above one or more prediction sets, the prediction information reported by the terminal device may include the prediction result of the current service cell, as well as the prediction results of one or more candidate cells that are better than the service cell.

[0168] In some embodiments, the terminal device reports prediction information to the network device based on the prediction result, including:

[0169] Reporting prediction information to network devices in a periodic manner;

[0170] Report forecast information to network devices in a semi-continuous manner;

[0171] Report prediction information to network devices in a non-periodic manner.

[0172] Accordingly, the network device receives prediction information reported by the terminal device based on the prediction result, including:

[0173] Receive prediction information reported periodically by terminal devices;

[0174] Receive prediction information reported by terminal devices in a semi-continuous manner;

[0175] Receive prediction information reported by terminal devices in a non-periodic manner.

[0176] In an embodiment of the present application, the terminal device can report prediction information to the network device according to a pre-configured periodic / semi-continuous / non-periodic reporting timing / reporting strategy.

[0177] In some embodiments, the terminal device reports prediction information to the network device based on the prediction result, including:

[0178] Report prediction information to network devices based on L1 / L2 mobility events.

[0179] Accordingly, the network device receives prediction information reported by the terminal device based on the prediction result, including:

[0180] Receive prediction information reported by the terminal device based on L1 / L2 mobility events.

[0181] In an embodiment of the present application, the above prediction information can also be reported by the terminal device when triggered by an L1 / L2 mobility event. For example, when the L1 / L2 mobility event indicates that the terminal device may have a need for cell switching, the prediction information is reported.

[0182] In some embodiments, the L1 / L2 mobility event includes at least one of the following events:

[0183] The predicted link performance of the current serving cell is better than / weaker than the first threshold;

[0184] The predicted link performance of the current serving cell is better / weaker than the predicted link performance of the candidate cell plus the first offset;

[0185] The predicted link performance of the candidate cell is better or weaker than the second threshold;

[0186] The predicted link performance of the current serving cell is weaker than the point threshold, and the predicted link performance of the candidate cell is better than the fourth threshold.

[0187] In an embodiment of the present application, when the link performance / link quality of the serving cell is low, and / or the link performance / link quality of the candidate cell is high, it can be determined that the terminal device may have a need for cell switching. At this time, the terminal device can report prediction information.

[0188] After the terminal device reports the above prediction information, the network device can determine whether to send a cell switching instruction to the terminal device based on the prediction information.

[0189] Step 805: The terminal device sends a cell switching request to the network device according to the prediction result; the network device receives the cell switching request sent by the terminal device according to the prediction result.

[0190] In this step, the terminal device may also proactively initiate a cell switching request based on the prediction result.

[0191] In some embodiments, the cell switching request includes a prediction result.

[0192] Optionally, the cell switching request may include all information of the prediction result, or may include part of the information of the prediction result.

[0193] When the cell switching request includes part of the information in the prediction result, the method for determining the part of the information in the prediction result may refer to the method for determining the prediction information described above.

[0194] Among them, the above steps 804 and 805 can be used either one or the other; or, the above steps 804 and 805 can be used at the same time.

[0195] Example 1: Mobility Inference (UE-side Model)

[0196] This embodiment deploys an AI / ML model on the UE side, so that the UE uses the measurement results of the downlink reference signal as input to the model for inference.

[0197] Please refer to Figure 9, which shows a flowchart of the UE-side model spatial domain mobility prediction. As shown in Figure 9, the UE-side AI / ML model infers the overall process of the optimal candidate cell and / or the optimal beam (pair) under that cell and / or the performance of that beam (pair). The solid ellipse represents the beam (pair) in Set Bn that the UE actually measured; the dotted ellipse represents the beam (pair) that the UE did not measure but is included in the prediction set. The optimal step in the process, namely CSC, is represented by a dotted line because the optimal cell predicted by the model may be the current serving cell, so cell switching is not required.

[0198] It should be noted that for Set B input to the model, Set B itself can be a measurement set of a candidate cell. Set B can also be generated from a measurement set of a candidate cell, Set C. That is, Set B is the top-M beams (pairs) measured in Set C and their L1-RSRP.

[0199] 1) UE capability reporting

[0200] Before the NW configures the measurement resources and prediction sets required by the model for the UE, the UE needs to inform the NW through capability reporting whether it supports the measurement and prediction of the spatial domain mobility of the UE-side model. If this feature is supported, the capabilities reported by the UE include but are not limited to:

[0201] The maximum number of candidate cells supported for measurement across all downlink CCs / BWPs; for example, the maximum number of measurement sets that can be configured (generally, each measurement set corresponds to one candidate cell); and the maximum number of measurement sets that a UE can measure simultaneously.

[0202] The maximum number of candidate cell predictions supported across all downlink CCs / BWPs; for example, the maximum number of prediction sets that can be configured (generally, each prediction set corresponds to one candidate cell);

[0203] How many candidate cell measurement sets are supported at most on a downlink CC / BWP? For example, in each measurement set Set B n (1≤n≤N), the maximum number of downlink SSB resources and / or CSI-RS resources that can be measured, including CSI-RS for mobility resources;

[0204] The maximum number of candidate cell prediction sets supported on a downlink CC / BWP is, for example, in each prediction set Set A p (1≤p≤P), the maximum number of downlink beams (pairs), that is, the number of SSBRIs and / or CRIs, can be predicted.

[0205] 2) Network Configuration

[0206] NW configures and / or activates the candidate cell measurement set Set B required for model input for UE n (≤n≤N):

[0207] The NW uses RRC signaling to configure one or more Set B groups for the UE n (1≤n≤N). For example, multiple sets of Set B n (1≤n≤N) can be expressed as {Set B 1X , Set B 2X ,…,Set B NX},…,{Set B 1Z , Set B 2Z ,…,Set B NZ}; For example, Set B n The downlink beam (pair) measurement set may include CSI-RS resources (including CSI-RS for mobility) resources and / or SSB resources.

[0208] If the NW configures multiple Set B groups for the UE n (1≤n≤N), then NW also needs to use MAC CE signaling to activate one of the multiple configurations, Set B, according to the actual deployment and antenna configuration. n (1≤n≤N). Otherwise, the UE only uses a configured set of Set Bn (1≤n≤N), for example {Set B 1X , Set B 2X ,…,Set B NX}. It should be noted that each set B n The number of N in (1≤n≤N) may be different, such as N=4 or 8.

[0209] NW configures and / or activates the downlink beam (pair) prediction set Set A output by the model for the UE p (1≤p≤P):

[0210] The NW uses RRC signaling to configure one or more beam (pair) prediction sets Set A for the UE. p (1≤p≤P); For example, multiple sets of Set Ap(1≤p≤P) can be represented as {Set A 1X , Set A 2X ,…,Set A PX},…,{Set A 1Z , Set A 2Z ,…,Set A PZ}; For another example, Set Ap as a beam (pair) prediction set may include CSI-RS resources (including CSI-RS for mobility) and / or SSB resources.

[0211] If the NW is configured with multiple Set A p (1≤p≤P), then the NW also needs to use MAC CE signaling to activate one of the multiple configurations, Set A, based on the actual deployment and antenna configuration. p (1≤p≤P). Otherwise, only the configured set Set A is used p (1≤p≤P), such as {Set A 1X , Set A 2X ,…,Set A PX Similarly, the maximum P value of different groups can be different, such as P = 2 or 4.

[0212] 3) UE measurement of mobility measurement set

[0213] In order to find the best serving cell and / or the best downlink beam (pair) under the cell from multiple cells, the UE measures the SSB and / or CSI-RS resources of N cells through layer 1, which corresponds to a set of Set B n (1≤n≤N). The N cells include one current serving cell (such as SpCell) and (N-1) candidate cells.

[0214] It should be noted that the number of all cells (assuming it is M) is not necessarily equal to the number of measurement sets N. For example, when M = 16 and N = 8, the UE only measures 8 of the cells, but can infer the most suitable cell and / or the optimal beam (pair) corresponding to the cell from the 16 cells (including 1 SpCell serving cell and 15 candidate cells).

[0215] In addition, it should be noted that for beam-level mobility, the evaluation of model prediction is performed according to the index of the output optimal beam (pair). However, this case focuses on cell mobility, namely (cell-level mobility). For example, a single optimal beam in a cell (other beams are of poor quality) does not guarantee that the cell is the optimal cell for the UE. A common method to confirm the optimal cell is to average the link quality (such as L1-RSRP) of multiple beams in the cell to obtain the optimal cell (ranked from high to low by the mean L1-RSRP). In this case, the model used to predict the optimal cell also refers to the optimal cell selection mechanism, namely cell-level mobility.

[0216] Consider the beam (pair) prediction in the spatial domain (BM-Case1), for example, Set B n The beams (pairs) included in the prediction set are only a subset of the corresponding cell's downlink beams (pairs). For example, in the spatial-domain mobility measurement and prediction diagram shown in Figure 10, the UE measures downlink reference signals in Set B1 in serving cell #1 and in Sets B2 and B3 in candidate cells #2 and #3. Reference signals actually measured by the UE are represented by solid ellipses, while reference signals not measured but included in the prediction set are represented by dashed ellipses.

[0217] 4) Model input and output

[0218] There are two main ways to input the UE-side model:

[0219] The first way is to just enter Set B in a fixed order n (1≤n≤N) reference signal link quality. UE will set all Set B n The measurement results in a fixed order are used as the input of the model, as shown in Case 1 in the input-output relationship diagram of the spatial domain mobility prediction model 1 shown in FIG11 .

[0220] The second way is that the input of the model includes Set B n The advantage is that different Set B can be flexibly selected. n The combination serves as the input of the model, as shown in Case 2 in Figure 11.

[0221] Link quality is generally L1-RSRP, and can also be L1-SINR, L1-RSSI, L1-RSRQ, and CQI.

[0222] There are also two main ways to output the UE-side model:

[0223] The first approach uses two independent models for prediction. The first model (as shown in Figure 11) predicts the index of the optimal candidate cell and / or the index of the optimal beam (pair) within the selected cell. The second model (as shown in the input-output relationship diagram of spatial-domain mobility prediction model 2 in Figure 12) predicts the link quality of the optimal beam (pair) corresponding to the optimal cell, such as L1-RSRP.

[0224] The second approach is to use one model to complete all prediction tasks, as shown in the input-output relationship diagram of the spatial domain mobility prediction model 3 in Figure 13. This model predicts Set A pThe total L1-RSRPs for each set in (1≤p≤P) are then sorted from highest to lowest by L1-RSRP to select the top-L candidate cells (including the original serving cell), along with the top-K beams (pairs) within each candidate cell, and finally the corresponding predicted L1-RSRP values. Note: The value of K can be different for each candidate cell.

[0225] Regardless of the implementation method of the model, the final output is Set A p (1≤p≤P):

[0226] The best L candidate cells (which may include the current serving cell); and / or,

[0227] The best beam(pair) index in each best cell and / or (only for FR2, higher frequency bands); and / or,

[0228] The link quality corresponding to each optimal beam (pair) index, such as L1-RSRP.

[0229] 5) Reporting of the best candidate cell and / or best beam (pair) and / or link quality

[0230] The time domain characteristics of mobility prediction reporting can be divided into the following two mechanisms:

[0231] ① Periodic / semi-continuous / aperiodic reporting: The UE periodically or semi-continuously reports the predicted results of the mobility model based on the reporting period and offset configured by the network network (NW). Semi-continuous reporting requires the NW to activate the measurement and reporting after configuration. For aperiodic reporting, the NW sends a DCI to trigger the UE's corresponding measurement and reporting.

[0232] ② Based on the reporting of mobility events, define the predicted layer 1 / layer 2 mobility events as follows:

[0233] A) The predicted link performance of the current serving cell is better / weaker than a specific threshold;

[0234] B) The predicted link performance of the current serving cell is better / weaker than that of the candidate cell + an offset;

[0235] C) The predicted link performance of the candidate cell is better / weaker than a specific threshold;

[0236] D) The predicted link performance of the current serving cell is weaker than a specific threshold, and the predicted link performance of the candidate cell is better than a specific threshold.

[0237] The UE compares the mobility events defined above with the prediction results of the model to determine whether a layer 1 / layer 2 mobility event has occurred, and autonomously chooses whether to make mobility-related reports. For example, when the optimal cell output by the model is still the UE's current serving cell, the UE does not need to report, nor does it need to trigger subsequent mobility operations. When the optimal cell output by the model is a candidate cell, and its performance is better than the current serving cell by an offset (such as 6dB), the UE can determine that Event B has occurred and trigger a non-periodic report based on the UE request (for example, it can be carried by uplink control information (UCI)). The process is as follows:

[0238] S1, the output of the UE-side model triggers a mobility event (e.g., the link quality of the candidate cell is sufficiently better than that of the current serving cell, for example, greater than a certain offset, such as 6dB L1-RSRP);

[0239] S2, resources for UE to request mobility reporting;

[0240] S3, NW agrees to the UE's reporting request and sends uplink scheduling DCI;

[0241] S4: The UE uses the PUSCH scheduled by the NW to carry the mobility-related report.

[0242] The content of mobility prediction reporting can be divided into the following two mechanisms:

[0243] For the model prediction result, i.e., the optimal candidate cell index selected from Set Ap, 1≤p≤P, and / or the optimal beam (pair) index of the optimal cell, and / or the link quality (e.g., L1-RSRP) corresponding to the optimal beam (pair) index, the UE reports the model prediction result to the NW in a beam reporting instance;

[0244] For the optimal candidate cell, the UE may need to report the index of the cell. For example, the index can be PCI, PCI index, configuration index of candidate cell, or the index of Set Ap corresponding to the cell, that is, p value; for the beam (pair) index within the candidate cell, the existing resource index in the NR system, such as SSBRI or CRI, can be used; for link quality, this case takes L1-RSRP as an example, and does not exclude other link quality indicators, such as L1-SINR or CQI.

[0245] It should be noted that there is currently no PCI reporting in NR technology. Because the NW is configured through RRC, the optimal beam reported by the UE comes from the same cell, that is, the same PCI. In addition, since the PCI parameter has the potential risk of exposing the base station configuration on the NW side, this application also considers the PCI index, that is, a simple encoding of multiple PCIs, such as 8 10-bit real PCIs can be encoded into a 3-bit PCI index. In addition, in mobility enhancement, multiple candidate cells need to be configured in advance through RRC parameters, so the configuration index of the candidate cell can also be used as the identifier or index of a cell.

[0246] To report predictions related to mobility, the existing beam reporting format needs to be revised, as shown in Table 1. For the predicted optimal candidate cell index, its PCI, PCI index, candidate cell configuration index, or corresponding Set A index (if available) can be reported. For the predicted beam (pair), if the prediction is for a downlink transmit beam, the conventional CRI or SSBRI can be used to represent it. If it is a downlink transmit / receive beam pair, the beam (pair) can be used to refer to it.

[0247] Table 1

[0248] 6) Channel Switch Command (CSC) or Channel Switch Request (CSQ)

[0249] In the Rel-18NR standard, the NW is supported to use a cell handover command based on the unified TCI state (carried by the MAC CE). The unified TCI state is the DL / joint TCI state, which includes a PCI index or candidate cell configuration index, which can indicate the candidate cell index to which the UE switches.

[0250] In addition to the CSC from the NW, the UE may not report all the output results of the model, but instead send a cell handover suggestion to the NW. This is also carried by the MAC CE, which should at least include:

[0251] Candidate cell ID, such as PCI, PCI index, candidate cell configuration index or index p of Set A; and / or,

[0252] The beam (pair) index corresponding to the candidate cell, such as CRI / SSBRI or beam (pair) index; and / or,

[0253] Link quality corresponding to the beam (pair) index, such as L1-RSRP.

[0254] After receiving the handover request sent by the UE, the NW sends a confirmation command to the UE, and the UE can complete subsequent mobility operations.

[0255] Based on the solution shown in FIG7 above, please refer to FIG14, which shows a flowchart of a processing method for measurement provided by an embodiment of the present application, which can be interactively executed by a terminal device and a network device; wherein the terminal device and the network device can be the terminal device 120 and the network device 110 in the network architecture shown in FIG1; or, the terminal device and the network device can be the terminal device 130 and the network device 110 in the network architecture shown in FIG1. ​​When the process of predicting the link quality of one or more spatial filters in the prediction set is performed by the network device, for example, when the prediction model is set in the network device, as shown in FIG14, the following steps can be included:

[0256] Step 1401: The network device sends measurement instruction information to the terminal device, and the terminal device receives the measurement instruction information.

[0257] The measurement indication information is used to instruct the terminal device to measure the spatial filters in one or more measurement sets to obtain measurement results; the measurement results are used to predict the link quality of the spatial filters in one or more prediction sets to obtain prediction results.

[0258] In some embodiments, the measurement indication information is used to configure one or more measurement sets and / or to activate one or more measurement sets.

[0259] In some embodiments, the one or more prediction sets correspond to a current serving cell of the terminal device and one or more candidate cells of the terminal device, respectively.

[0260] In some embodiments, the one or more measurement sets correspond to a current serving cell of the terminal device and one or more candidate cells of the terminal device, respectively.

[0261] In some embodiments, the prediction result is used to indicate one or more of the following:

[0262] The best cell among the cells corresponding to one or more prediction sets;

[0263] The optimal spatial filter or the optimal spatial filter pair under the optimal cell;

[0264] and, the link quality of the optimal spatial filter or optimal spatial filter pair.

[0265] In some embodiments, the prediction results include one or more of the following:

[0266] Identifiers of L best cells among the cells corresponding to one or more prediction sets; L is an integer greater than or equal to 1;

[0267] The index of the best spatial filter or the index of the best spatial filter pair in the L best cells;

[0268] and the link quality corresponding to the index of the optimal spatial filter, or the link quality corresponding to the index of the optimal spatial filter pair.

[0269] In some embodiments, the identification of the best cell includes one or more of the following:

[0270] The physical cell identifier (PCI) of the optimal cell; each cell may correspond to one PCI, and the prediction model may output the PCI corresponding to each of the L optimal cells;

[0271] The PCI index of the best cell; wherein the PCIs of one or more cells may form a PCI set, which may be represented by an index (i.e., a PCI index). The prediction model may output the PCI index of the set consisting of the PCIs corresponding to the L best cells, thereby reducing the number of bits of information contained in the identifier of the best cell when the number of best cells is greater than or equal to 2;

[0272] Configuration index of the optimal cell;

[0273] The index of the prediction set to which the best cell belongs.

[0274] In some embodiments, the index of the optimal spatial filter or the index of the optimal spatial filter pair comprises:

[0275] Channel State Information Reference Signal CSI-RS Resource Indicator CRI of the optimal spatial filter or the optimal spatial filter pair;

[0276] and / or, the synchronization signal block SSB resource indication SSB RI of the optimal spatial filter or the optimal spatial filter pair.

[0277] In some embodiments, link quality includes one or more of the following:

[0278] Layer 1 reference signal received power L1-RSRP, layer 1 signal to interference plus noise ratio L1-SINR, layer 1 received signal strength indicator L1-RSSI, layer 1 reference signal received quality L1-RSRQ, and channel quality indicator CQI.

[0279] Step 1402: The network device sends prediction indication information to the terminal device, and the terminal device receives the prediction indication information.

[0280] The prediction indication information is used to configure one or more prediction sets and / or to activate one or more prediction sets.

[0281] In some embodiments, the method further comprises:

[0282] The terminal device reports the capability information of the terminal device to the network device; the network device receives the capability information of the terminal device reported by the terminal device; wherein the capability information is used to indicate the capability of the terminal device to measure and / or predict spatial domain mobility; the capability information of the terminal device is used by the network device to determine one or more measurement sets, and / or one or more prediction sets.

[0283] In some embodiments, the capability information includes at least one of the following information:

[0284] Whether the terminal device supports measurement and / or prediction of spatial domain mobility;

[0285] When the terminal device supports measurement of spatial domain mobility, the terminal device supports a maximum number of candidate cells for measurement on all downlink component carriers CC / bandwidth parts BWP;

[0286] When the terminal device supports prediction of spatial domain mobility, the terminal device supports a maximum number of predicted candidate cells on all downlink CCs / BWPs;

[0287] When the terminal device supports measurement of spatial domain mobility, the terminal device supports a maximum number of measurement sets on a downlink CC / BWP; each measurement set corresponds to one cell;

[0288] In the case where the terminal device supports prediction of spatial domain mobility, the terminal device supports a maximum number of prediction sets on all downlink CCs / BWPs; each prediction set corresponds to one cell.

[0289] Step 1403: The terminal device measures the spatial filters in one or more measurement sets to obtain measurement results.

[0290] In some embodiments, each of the one or more measurement sets corresponds to a cell, and the measurement results of the spatial filters in the one or more measurement sets include:

[0291] Measurement results of downlink reference signal resources of cells corresponding to one or more measurement sets on spatial filters in one or more measurement sets.

[0292] In some embodiments, the downlink reference signal resources include SSB resources and / or CSI-RS resources.

[0293] The above steps 1401 to 1403 may refer to steps 801 to 803 in the embodiment shown in FIG. 8 .

[0294] Step 1404: The terminal device reports a measurement report to the network device based on the measurement result; correspondingly, the network device receives the measurement report reported by the terminal device based on the measurement result.

[0295] In some embodiments, the measurement report includes: link quality of resource indexes corresponding to one or more measurement sets;

[0296] The link qualities of the resource indexes corresponding to one or more measurement sets are arranged according to the arrangement order of the one or more measurement sets and the arrangement order of the resource indexes corresponding to each measurement set.

[0297] In the embodiment of the present application, a reporting format is designed: UE sets Set B n The measurement results of (1≤n≤N) are reported in a pre-set order. For example, according to Set B n The index n is reported from small to large, so Set B can be omitted n The index of each measurement set Set B n Within, the resource index (ie, SSBRI or CRI) can be reported from small to large, so Set B can be omitted. n Finally, in this reporting format, only the measured link quality, such as L1-RSRP, needs to be reported. A specific format can be found in Table 2, where the absolute value of RSRP is reported, and no differential RSRP is reported.

[0298] Table 2

[0299] In some embodiments, the measurement report includes:

[0300] The difference between the link quality of the resource index corresponding to one or more measurement sets and the reference link quality;

[0301] The differences between the link qualities of the resource indexes corresponding to one or more measurement sets and the reference link qualities are arranged according to the arrangement order of the one or more measurement sets and the arrangement order of the resource indexes corresponding to each measurement set.

[0302] In an embodiment of the present application, the network device may also report the difference between the link quality of the resource index corresponding to one or more measurement sets and the reference link quality in a difference manner. At the same time, the difference between the resource index corresponding to one or more measurement sets is also arranged in a certain order.

[0303] The reference link quality may be one or more of the link qualities of the resource indexes corresponding to one or more measurement sets, or may be an additionally set reference value.

[0304] In some embodiments, the measurement report includes:

[0305] a first reference link quality; the first reference link quality is a link quality of a first resource index corresponding to a first measurement set; the first measurement set is one of one or more measurement sets, and the first resource index is one of the resource indexes corresponding to the first measurement set;

[0306] and, differences between the first reference link quality and other link qualities except the first reference link quality among the link qualities of the resource indexes respectively corresponding to the one or more measurement sets.

[0307] In some embodiments, the first reference link quality is the highest link quality among the link qualities of the resource indexes respectively corresponding to one or more measurement sets;

[0308] Alternatively, the first reference link quality is the lowest link quality among link qualities of resource indexes corresponding to one or more measurement sets.

[0309] In some embodiments, the measurement report further includes first flag information, where the first flag information is used to indicate that the link quality of the first resource index is the first reference link quality.

[0310] In other embodiments, the first reference link quality may also be notified to the network device through additional signaling or fields.

[0311] In order to further save the reporting overhead, Table 3 shows a format for differential reporting with L1-RSRP. As shown in Table 3, all Set B n A highest L1-RSRP is selected as a reference (for differential reporting), so it is only necessary to mark the resource set and resource index to which the L1-RSRP belongs.

[0312] Table 3

[0313] In some embodiments, the measurement report includes:

[0314] second reference link quality; the second reference link quality is the link quality of the second resource index corresponding to the second measurement set; the second measurement set is any one of one or more measurement sets, and the second resource index is one of the resource indexes corresponding to the second measurement set;

[0315] and, the difference between the second reference link quality and the other link qualities except the second reference link quality in the link qualities of the resource indexes corresponding to the second measurement set.

[0316] In some embodiments, the second reference link quality is the highest link quality among the link qualities of the resource indexes corresponding to the second measurement set;

[0317] Alternatively, the second reference link quality is the lowest link quality among the link qualities of the resource indexes corresponding to the second measurement set.

[0318] In some embodiments, the measurement report further includes second flag information, where the second flag information is used to indicate that the link quality of the second resource index is the second reference link quality.

[0319] In other embodiments, the second reference link quality may also be notified to the network device through additional signaling or fields.

[0320] For example, as shown in Table 4, the differential reporting with L1-RSRP. n In the example, the resource index with the highest L1-RSRP is marked, and the other resource indexes are arranged in a fixed order (such as from small to large).

[0321] Table 4

[0322] In some embodiments, the measurement report includes:

[0323] Link quality of resource indexes corresponding to all or part of one or more measurement sets;

[0324] and, an identifier of a measurement set corresponding to the link quality included in the measurement report, and / or an identifier of a resource index corresponding to the link quality included in the measurement report.

[0325] UE can flexibly report part or all of Set B n (1≤n≤N) measurement results. Specifically, the UE can report Set B n The index of the measurement set or the PCI corresponding to the measurement set, PCI index, or candidate cell index, followed by the link quality corresponding to each measurement resource in the measurement set, such as L1-RSRP, etc. A reporting format can be shown in Table 5, where Set B n The number of measurement resources in Xn express.

[0326] Table 5

[0327] In some embodiments, the terminal device reports a measurement report to the network device based on the measurement result, including:

[0328] Report one or more sub-measurement reports corresponding to the measurement set to the network device based on the measurement results;

[0329] The sub-measurement report includes the link quality of the resource index in the corresponding measurement set.

[0330] Accordingly, the network device receives a measurement report reported by the terminal device based on the measurement result, including:

[0331] Receiving sub-measurement reports corresponding to one or more measurement sets reported by the terminal device according to the measurement results;

[0332] The sub-measurement report includes the link quality of the resource index in the corresponding measurement set.

[0333] In some embodiments, the sub-measurement report further includes an identifier of the corresponding measurement set;

[0334] Alternatively, the sub-measurement report further includes an identifier of a corresponding measurement set and an identifier of a resource index corresponding to the link quality included in the sub-measurement report.

[0335] For example, the UE may report only one measurement set, Set B, in each report. n The measurement results are shown in Table 6. NW needs to collect multiple reports from UE as input to the model. Of course, considering the flexibility of the NW side model, NW side does not necessarily need to wait until all measurement sets Set B are collected. n The measurement results of (1≤n≤N) are then predicted.

[0336] Table 6

[0337] Example 2: Mobility Inference (Model Deployed on the NW Side)

[0338] In the embodiment of the present application, an AI / ML model is deployed on the NW side. Please refer to FIG15 , which shows a flow chart of the NW side model spatial domain mobility prediction. As shown in FIG15 , the UE performs mobility measurement, i.e., measurement Set B n (1≤n≤N) and reports the measurement results to the NW. The AI / ML model deployed on the NW side can then predict spatial mobility.

[0339] 1) UE capability reporting

[0340] Before the NW configures the measurement resources required by the model for the UE, the UE needs to inform the NW through capability reporting whether it supports the measurement and reporting of spatial domain mobility of the UE-side model. If this feature is supported, the capabilities reported by the UE include but are not limited to:

[0341] The maximum number of candidate cells supported for measurement across all downlink CCs / BWPs: for example, the maximum number of measurement sets that can be configured (generally, each measurement set corresponds to one candidate cell); another example, the maximum number of measurement sets that a UE can measure simultaneously;

[0342] How many candidate cell measurement sets are supported on a downlink CC / BWP at most? For example, in each measurement set Set B n (1≤n≤N), the maximum number of downlink SSB resources and / or CSI-RS resources (including CSI-RS for mobility resources) that can be measured.

[0343] 2) Network Configuration

[0344] NW configures and / or activates the candidate cell measurement set Set B required for model input for UE n (1≤n≤N):

[0345] ①NW uses RRC signaling to configure one or more Set B groups for UE n (1≤n≤N); for example, multiple sets of Set B n (1≤n≤N) can be expressed as {Set B 1X , Set B 2X ,…,Set B NX},…,{Set B 1Z , Set B 2Z ,…,Set B NZ}; For example, Set B n The downlink beam (pair) measurement set may include CSI-RS resources (including CSI-RS for mobility resources) and / or SSB resources.

[0346] ② If the NW configures multiple Set B groups for the UE n (1≤n≤N), then NW also needs to use MAC CE signaling to activate one of the multiple configurations, Set B, according to the actual deployment and antenna configuration. n (1≤n≤N). Otherwise, the UE only uses the configured set of Set B n (1≤n≤N), for example {Set B 1X , Set B 2X ,…,Set BNX}. It should be noted that each set B n The number of N in (1≤n≤N) may be different, such as N=4 or 8.

[0347] After the measurement is completed, the Set B used for NW side model input can be reported according to the periodic or semi-continuous CSI report configured by the NW, or through the aperiodic CSI report dynamically triggered by the NW. n (1≤n≤N) is reported to the NW. In this embodiment, the model is deployed only on the NW side, so the UE cannot predict whether a mobility event has occurred and cannot complete autonomous measurement result reporting. Among them, the UE's measurement and reporting process of the mobility measurement set in Example 2 can refer to the solutions shown in Tables 2 to 6.

[0348] For the input-output relationship of the NW-side model and the cell switching command involved in this embodiment, reference may be made to the description of the above-mentioned embodiment 1.

[0349] Please refer to Figure 16, which shows a block diagram of a processing device for measurement provided by an embodiment of the present application. The processing device for measurement has the function of implementing the method shown in Figure 7, Figure 8 or Figure 15 above, which is performed by the terminal device. As shown in Figure 16, the device may include:

[0350] The receiving module 1601 is configured to receive measurement instruction information, where the measurement instruction information is used to instruct to measure one or more spatial filters in a measurement set to obtain a measurement result;

[0351] The measurement results are used to predict the link quality of one or more spatial filters in the prediction set to obtain a prediction result.

[0352] In some embodiments, the prediction result is used to indicate one or more of the following:

[0353] An optimal cell among the cells corresponding to the one or more prediction sets;

[0354] An optimal spatial filter or an optimal spatial filter pair under the optimal cell;

[0355] and, the link quality of the optimal spatial filter or the optimal spatial filter pair.

[0356] In some embodiments, the prediction result includes one or more of the following:

[0357] Identifiers of L optimal cells among the cells corresponding to the one or more prediction sets; L is an integer greater than or equal to 1;

[0358] The index of the optimal spatial filter or the index of the optimal spatial filter pair in the L optimal cells;

[0359] and, the link quality corresponding to the index of the optimal spatial filter, or the link quality corresponding to the index of the optimal spatial filter pair.

[0360] In some embodiments, the identifier of the optimal cell includes one or more of the following: a physical cell identifier PCI of the optimal cell; a PCI index of the optimal cell; a configuration index of the optimal cell; and an index of a prediction set to which the optimal cell belongs.

[0361] In some embodiments, the index of the optimal spatial filter or the index of the optimal spatial filter pair comprises:

[0362] a channel state information reference signal CSI-RS resource indicator CRI of the optimal spatial filter or the optimal spatial filter pair;

[0363] And / or, the synchronization signal block SSB resource indication SSB RI of the optimal spatial filter or the optimal spatial filter pair.

[0364] In some embodiments, the link quality includes one or more of the following:

[0365] Layer 1 reference signal received power L1-RSRP, layer 1 signal to interference plus noise ratio L1-SINR, layer 1 received signal strength indicator L1-RSSI, layer 1 reference signal received quality L1-RSRQ, and channel quality indicator CQI.

[0366] In some embodiments, the measurement indication information is used to configure the one or more measurement sets and / or to activate the one or more measurement sets.

[0367] In some embodiments, the receiving module 1601 is further configured to receive prediction indication information, where the prediction indication information is used to configure the one or more prediction sets and / or to activate the one or more prediction sets.

[0368] In some embodiments, the apparatus further comprises:

[0369] A sending module, configured to report capability information of the terminal device to the network device;

[0370] The capability information is used to indicate the terminal device's ability to measure and / or predict spatial domain mobility; the capability information of the terminal device is used by the network device to determine the one or more measurement sets and / or the one or more prediction sets.

[0371] In some embodiments, the capability information includes at least one of the following information:

[0372] Whether the terminal device supports measurement and / or prediction of spatial domain mobility;

[0373] In the case where the terminal device supports measurement of spatial domain mobility, the terminal device supports a maximum number of candidate cells for measurement on all downlink component carriers CC / bandwidth parts BWP;

[0374] In the case where the terminal device supports prediction of spatial domain mobility, the terminal device supports a maximum number of predicted candidate cells on all downlink CCs / BWPs;

[0375] In the case where the terminal device supports measurement of spatial domain mobility, the terminal device supports a maximum number of measurement sets for measurement on one downlink CC / BWP; each measurement set corresponds to one cell;

[0376] In the case where the terminal device supports prediction of spatial domain mobility, the terminal device supports a maximum number of prediction sets on all downlink CCs / BWPs; each prediction set corresponds to one cell.

[0377] In some embodiments, the one or more prediction sets correspond to a current serving cell of the terminal device and one or more candidate cells of the terminal device, respectively.

[0378] In some embodiments, each of the one or more measurement sets corresponds to a cell,

[0379] The measurement results of the spatial filters in the one or more measurement sets include:

[0380] Measurement results of downlink reference signal resources of cells corresponding to the one or more measurement sets on the spatial filters in the one or more measurement sets.

[0381] In some embodiments, the downlink reference signal resources include SSB resources and / or CSI-RS resources.

[0382] In some embodiments, when the process of predicting the link quality of one or more spatial filters in the prediction set is performed by the terminal device, the sending module is further used to report prediction information to the network device according to the prediction result.

[0383] In some embodiments, the sending module is used to:

[0384] reporting the prediction information to the network device in a periodic manner;

[0385] reporting the prediction information to the network device in a semi-continuous manner;

[0386] The prediction information is reported to the network device in an aperiodic manner.

[0387] In some embodiments, the sending module is configured to report the prediction information to the network device according to an L1 / L2 mobility event.

[0388] In some embodiments, the L1 / L2 mobility event includes at least one of the following events:

[0389] The predicted link performance of the current serving cell is better than / weaker than the first threshold;

[0390] The predicted link performance of the current serving cell is better / weaker than the predicted link performance of the candidate cell plus the first offset;

[0391] The predicted link performance of the candidate cell is better or weaker than the second threshold;

[0392] The predicted link performance of the current serving cell is weaker than the point threshold, and the predicted link performance of the candidate cell is better than the fourth threshold.

[0393] In some embodiments, when the above-mentioned process of predicting the link quality of the spatial filters in one or more prediction sets is performed by the terminal device, the sending module is further used to send a cell switching request to the network device based on the prediction result.

[0394] In some embodiments, the cell switching request includes the prediction result.

[0395] In some embodiments, when the process of predicting the link quality of one or more spatial filters in the prediction set is performed by a network device, the sending module is further used to report a measurement report to the network device based on the measurement result.

[0396] In some embodiments, the measurement report includes:

[0397] link qualities of resource indexes respectively corresponding to the one or more measurement sets;

[0398] The link qualities of the resource indexes respectively corresponding to the one or more measurement sets are arranged according to the arrangement order of the one or more measurement sets and the arrangement order of the resource indexes corresponding to each of the measurement sets.

[0399] In some embodiments, the measurement report includes:

[0400] A difference between the link quality of the resource indexes respectively corresponding to the one or more measurement sets and the reference link quality;

[0401] The differences between the link qualities of the resource indexes corresponding to the one or more measurement sets and the reference link qualities are arranged according to the arrangement order of the one or more measurement sets and the arrangement order of the resource indexes corresponding to each of the measurement sets.

[0402] In some embodiments, the measurement report includes:

[0403] a first reference link quality; the first reference link quality is a link quality of a first resource index corresponding to a first measurement set; the first measurement set is one of the one or more measurement sets, and the first resource index is one of the resource indexes corresponding to the first measurement set;

[0404] and, a difference between the first reference link quality and other link qualities other than the first reference link quality among the link qualities of the resource indexes respectively corresponding to the one or more measurement sets.

[0405] In some embodiments, the first reference link quality is the highest link quality among the link qualities of the resource indexes respectively corresponding to one or more measurement sets;

[0406] Alternatively, the first reference link quality is the lowest link quality among link qualities of resource indexes corresponding to one or more measurement sets.

[0407] In some embodiments, the measurement report further includes first flag information, where the first flag information is used to indicate that the link quality of the first resource index is the first reference link quality.

[0408] In some embodiments, the measurement report includes:

[0409] second reference link quality; the second reference link quality is the link quality of the second resource index corresponding to the second measurement set; the second measurement set is any one of the one or more measurement sets, and the second resource index is one of the resource indexes corresponding to the second measurement set;

[0410] and, a difference between the second reference link quality and other link qualities of the resource index corresponding to the second measurement set except the second reference link quality.

[0411] In some embodiments, the second reference link quality is the highest link quality among the link qualities of the resource indexes corresponding to the second measurement set;

[0412] Alternatively, the second reference link quality is the lowest link quality among the link qualities of the resource indexes corresponding to the second measurement set.

[0413] In some embodiments, the measurement report further includes second flag information, where the second flag information is used to indicate that the link quality of the second resource index is the second reference link quality.

[0414] In some embodiments, the measurement report includes:

[0415] link qualities of resource indexes corresponding to all or part of the one or more measurement sets;

[0416] and, an identifier of a measurement set corresponding to the link quality included in the measurement report, and / or an identifier of a resource index corresponding to the link quality included in the measurement report.

[0417] In some embodiments, the sending module is configured to report, to the network device, sub-measurement reports corresponding to the one or more measurement sets respectively according to the measurement result; the sub-measurement reports include link quality of resource indexes in the corresponding measurement set.

[0418] In some embodiments, the sub-measurement report further includes an identifier of a corresponding measurement set;

[0419] Alternatively, the sub-measurement report further includes an identifier of a corresponding measurement set and an identifier of a resource index corresponding to the link quality included in the sub-measurement report.

[0420] Please refer to Figure 17, which shows a block diagram of a processing device for measurement provided by an embodiment of the present application. The processing device for measurement has the function of implementing the method shown in Figure 7, Figure 8 or Figure 15 above, which is performed by the network device. As shown in Figure 17, the device may include:

[0421] A sending module 1701 is configured to send measurement instruction information to a terminal device, where the measurement instruction information is used to instruct the terminal device to measure one or more spatial filters in a measurement set to obtain a measurement result;

[0422] The measurement results are used to predict the link quality of one or more spatial filters in the prediction set to obtain a prediction result.

[0423] In some embodiments, the prediction result is used to indicate one or more of the following:

[0424] An optimal cell among the cells corresponding to the one or more prediction sets;

[0425] An optimal spatial filter or an optimal spatial filter pair under the optimal cell;

[0426] and, the link quality of the optimal spatial filter or the optimal spatial filter pair.

[0427] In some embodiments, the prediction result includes one or more of the following:

[0428] Identifiers of L optimal cells among the cells corresponding to the one or more prediction sets; L is an integer greater than or equal to 1;

[0429] The index of the optimal spatial filter or the index of the optimal spatial filter pair in the L optimal cells;

[0430] and the link quality corresponding to the index of the optimal spatial filter, or the link quality corresponding to the index of the optimal spatial filter pair.

[0431] In some embodiments, the identifier of the optimal cell includes one or more of the following: a physical cell identifier PCI of the optimal cell; a PCI index of the optimal cell; a configuration index of the optimal cell; and an index of a prediction set to which the optimal cell belongs.

[0432] In some embodiments, the index of the optimal spatial filter or the index of the optimal spatial filter pair comprises:

[0433] A CSI-RS resource indicator CRI of the optimal spatial filter or the optimal spatial filter pair;

[0434] And / or, the SSB resource indication SSB RI of the optimal spatial filter or the optimal spatial filter pair.

[0435] In some embodiments, the link quality includes one or more of: L1-RSRP, L1-SINR, L1-RSSI, L1-RSRQ, and CQI.

[0436] In some embodiments, the measurement indication information is used to configure the one or more measurement sets and / or to activate the one or more measurement sets.

[0437] In some embodiments, the sending module 1701 is further used to send prediction indication information to the terminal device, where the prediction indication information is used to configure the one or more prediction sets and / or to activate the one or more prediction sets.

[0438] In some embodiments, the apparatus further comprises:

[0439] A receiving module, configured to receive capability information of the terminal device reported by the terminal device; the capability information is used to indicate the capability of the terminal device to measure and / or predict spatial domain mobility;

[0440] A determination module is configured to determine the one or more measurement sets and / or the one or more prediction sets according to the capability information of the terminal device.

[0441] In some embodiments, the capability information includes at least one of the following information:

[0442] Whether the terminal device supports measurement and / or prediction of spatial domain mobility;

[0443] In the case where the terminal device supports measurement of spatial domain mobility, the maximum number of candidate cells supported by the terminal device for measurement on all downlink CCs / BWPs;

[0444] In the case where the terminal device supports prediction of spatial domain mobility, the terminal device supports a maximum number of predicted candidate cells on all downlink CCs / BWPs;

[0445] In the case where the terminal device supports measurement of spatial domain mobility, the terminal device supports a maximum number of measurement sets for measurement on one downlink CC / BWP; each measurement set corresponds to one cell;

[0446] In the case where the terminal device supports prediction of spatial domain mobility, the terminal device supports a maximum number of prediction sets on all downlink CCs / BWPs; each prediction set corresponds to one cell.

[0447] In some embodiments, the one or more prediction sets correspond to a current serving cell of the terminal device and one or more candidate cells of the terminal device, respectively.

[0448] In some embodiments, each of the one or more measurement sets corresponds to a cell,

[0449] The measurement results of the spatial filters in the one or more measurement sets include:

[0450] Measurement results of downlink reference signal resources of cells corresponding to the one or more measurement sets on the spatial filters in the one or more measurement sets.

[0451] In some embodiments, the downlink reference signal resources include SSB resources and / or CSI-RS resources.

[0452] In some embodiments, when the above-mentioned process of predicting the link quality of the spatial filters in one or more prediction sets is performed by a terminal device, the receiving module is further used to receive prediction information reported by the terminal device based on the prediction result.

[0453] In some embodiments, the receiving prediction information reported by the terminal device according to the prediction result includes:

[0454] Receiving the prediction information reported by the terminal device in a periodic manner;

[0455] receiving the prediction information reported by the terminal device in a semi-continuous manner;

[0456] Receive the prediction information reported by the terminal device in a non-periodic manner.

[0457] In some embodiments, the receiving module is configured to receive the prediction information reported by the terminal device according to an L1 / L2 mobility event.

[0458] In some embodiments, the L1 / L2 mobility event includes at least one of the following events:

[0459] The predicted link performance of the current serving cell is better than / weaker than the first threshold;

[0460] The predicted link performance of the current serving cell is better / weaker than the predicted link performance of the candidate cell plus the first offset;

[0461] The predicted link performance of the candidate cell is better or weaker than the second threshold;

[0462] The predicted link performance of the current serving cell is weaker than the point threshold, and the predicted link performance of the candidate cell is better than the fourth threshold.

[0463] In some embodiments, when the above-mentioned process of predicting the link quality of the spatial filters in one or more prediction sets is performed by a terminal device, the receiving module is further used to receive a cell switching request sent by the terminal device according to the prediction result.

[0464] In some embodiments, the cell switching request includes the prediction result.

[0465] In some embodiments, when the process of predicting the link quality of one or more spatial filters in the prediction set is performed by a network device, the receiving module is further used to receive a measurement report reported by the terminal device based on the measurement result.

[0466] In some embodiments, the measurement report includes:

[0467] link qualities of resource indexes respectively corresponding to the one or more measurement sets;

[0468] The link qualities of the resource indexes respectively corresponding to the one or more measurement sets are arranged according to the arrangement order of the one or more measurement sets and the arrangement order of the resource indexes corresponding to each of the measurement sets.

[0469] In some embodiments, the measurement report includes:

[0470] A difference between the link quality of the resource indexes respectively corresponding to the one or more measurement sets and the reference link quality;

[0471] The differences between the link qualities of the resource indexes corresponding to the one or more measurement sets and the reference link qualities are arranged according to the arrangement order of the one or more measurement sets and the arrangement order of the resource indexes corresponding to each of the measurement sets.

[0472] In some embodiments, the measurement report includes:

[0473] a first reference link quality; the first reference link quality is a link quality of a first resource index corresponding to a first measurement set; the first measurement set is one of one or more measurement sets, and the first resource index is one of the resource indexes corresponding to the first measurement set;

[0474] and, a difference between the first reference link quality and other link qualities other than the first reference link quality among the link qualities of the resource indexes respectively corresponding to the one or more measurement sets.

[0475] In some embodiments, the first reference link quality is the highest link quality among the link qualities of the resource indexes respectively corresponding to one or more measurement sets;

[0476] Alternatively, the first reference link quality is the lowest link quality among link qualities of resource indexes corresponding to one or more measurement sets.

[0477] In some embodiments, the measurement report further includes first flag information, where the first flag information is used to indicate that the link quality of the first resource index is the first reference link quality.

[0478] In some embodiments, the measurement report includes:

[0479] second reference link quality; the second reference link quality is the link quality of the second resource index corresponding to the second measurement set; the second measurement set is any one of one or more measurement sets, and the second resource index is one of the resource indexes corresponding to the second measurement set;

[0480] and, a difference between the second reference link quality and other link qualities of the resource index corresponding to the second measurement set except the second reference link quality.

[0481] In some embodiments, the second reference link quality is the highest link quality among the link qualities of the resource indexes corresponding to the second measurement set;

[0482] Alternatively, the second reference link quality is the lowest link quality among the link qualities of the resource indexes corresponding to the second measurement set.

[0483] In some embodiments, the measurement report further includes second flag information, where the second flag information is used to indicate that the link quality of the second resource index is the second reference link quality.

[0484] In some embodiments, the measurement report includes:

[0485] link qualities of resource indexes corresponding to all or part of the one or more measurement sets;

[0486] and, an identifier of a measurement set corresponding to the link quality included in the measurement report, and / or an identifier of a resource index corresponding to the link quality included in the measurement report.

[0487] In some embodiments, the receiving module is configured to receive sub-measurement reports corresponding to the one or more measurement sets reported by the terminal device according to the measurement results; the sub-measurement reports include link quality of resource indexes in the corresponding measurement sets.

[0488] In some embodiments, the sub-measurement report further includes an identifier of a corresponding measurement set;

[0489] Alternatively, the sub-measurement report further includes an identifier of a corresponding measurement set and an identifier of a resource index corresponding to the link quality included in the sub-measurement report.

[0490] It should be noted that the device provided in the above embodiment only uses the division of the above-mentioned functional modules as an example to implement its functions. In actual applications, the above-mentioned functions can be assigned to different functional modules according to actual needs, that is, the content structure of the device can be divided into different functional modules to complete all or part of the functions described above.

[0491] Regarding the apparatus in the above embodiment, the specific manner in which each module performs operations has been described in detail in the embodiment of the method, and will not be elaborated here.

[0492] Please refer to FIG18 , which shows a schematic diagram of the structure of a communication device 1800 provided in one embodiment of the present application. The communication device 1800 may include: a processor 1801 , a receiver 1802 , a transmitter 1803 , a memory 1804 , and a bus 1805 .

[0493] The processor 1801 includes one or more processing cores. The processor 1801 executes various functional applications and information processing by running software programs and modules.

[0494] Receiver 1802 and transmitter 1803 can be implemented as a communication component, which can be a communication chip. This communication chip can also be called a transceiver. Memory 1804 is connected to processor 1801 via bus 1805. Memory 1804 can be used to store computer programs, and processor 1801 is used to execute the computer programs to implement the various steps in the above method embodiments.

[0495] In addition, the memory 1804 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, including but not limited to: magnetic disk or optical disk, electrically erasable programmable read-only memory, erasable programmable read-only memory, static random access memory, read-only memory, magnetic memory, flash memory, and programmable read-only memory.

[0496] In an exemplary embodiment, when the communication device 1800 is implemented as the terminal device described above, the receiver 1802 and the processor 1801 execute the computer program to cause the communication device to implement the steps performed by the terminal device in any of the methods shown in Figures 7, 8, or 15. In this case, the receiver 1802 may correspondingly implement the method and steps implemented by the receiving module 1601 in Figure 16, and the transmitter 1803 may correspondingly implement the method and steps implemented by the transmitting module in Figure 16.

[0497] In an exemplary embodiment, when the communication device 1800 is implemented as the aforementioned network device, the transmitter 1803 and the processor 1801 execute the computer program to cause the communication device to implement the steps performed by the network device in any of the methods shown in FIG7 , FIG8 , or FIG15 . In this case, the transmitter 1803 may correspondingly implement the method and steps implemented by the transmitting module 1701 in FIG17 , and the receiver 1802 may correspondingly implement the method and steps implemented by the receiving module in FIG17 .

[0498] An embodiment of the present application also provides a computer-readable storage medium, which stores a computer program. The computer program is loaded and executed by a processor to implement all or part of the steps performed by the terminal device or network device in the method shown in Figures 7, 8 or 15 above.

[0499] The present application also provides a chip, which is used to run in a communication device so that the communication device executes all or part of the steps performed by the terminal device or network device in the method shown in Figure 7, Figure 8 or Figure 15 above.

[0500] The present application also provides a computer program product, which includes computer instructions stored in a computer-readable storage medium. A processor of a communication device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the communication device to perform all or part of the steps performed by the terminal device or network device in the method shown in Figures 7, 8, or 15 above.

[0501] The present application also provides a computer program, which is executed by a processor of a communication device to implement all or part of the steps performed by a terminal device or a network device in the method shown in Figure 7, Figure 8 or Figure 15 above.

[0502] Those skilled in the art will appreciate that in one or more of the above examples, the functions described in the embodiments of the present application can be implemented using hardware, software, firmware, or any combination thereof. When implemented using software, these functions can be stored in a computer-readable medium or transmitted as one or more instructions or codes on a computer-readable medium. Computer-readable media include computer storage media and communication media, wherein communication media include any media that facilitates the transmission of computer programs from one place to another. The storage medium can be any available medium that can be accessed by a general-purpose or special-purpose computer.

[0503] The above description is merely an exemplary embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present application shall be included in the scope of protection of the present application.

Claims

1. A processing method for measuring, characterized in that The method is performed by a terminal device, and the method includes: Receiving measurement indication information, where the measurement indication information is used to indicate that a measurement result is obtained by measuring one or more spatial filters in a measurement set; The measurement results are used to predict the link quality of the spatial filters in one or more prediction sets to obtain prediction results.

2. The method according to claim 1, characterized in that The prediction result is used to indicate one or more of the following: An optimal cell among the cells corresponding to the one or more prediction sets; An optimal spatial filter or an optimal spatial filter pair under the optimal cell; and, the link quality of the optimal spatial filter or the optimal spatial filter pair.

3. The method according to claim 2, characterized in that The prediction results include one or more of the following: Identifications of L optimal cells among the cells corresponding to the one or more prediction sets; L is an integer greater than or equal to 1; The index of the optimal spatial filter or the index of the optimal spatial filter pair in the L optimal cells; The link quality corresponding to the index of the optimal spatial filter, or the link quality corresponding to the index of the optimal spatial filter pair.

4. The method according to claim 3, characterized in that The identifier of the best cell includes one or more of the following: A physical cell identifier PCI of the optimal cell; The PCI index of the best cell; The configuration index of the optimal cell; The index of the prediction set to which the optimal cell belongs.

5. The method according to claim 3 or 4, characterized in that: The index of the optimal spatial filter or the index of the optimal spatial filter pair includes: A channel state information reference signal CSI-RS resource indication CRI of the optimal spatial filter or the optimal spatial filter pair; And / or, the synchronization signal block SSB resource indication SSB RI of the optimal spatial filter or the optimal spatial filter pair.

6. The method according to any one of claims 3 to 5, characterized in that: The link quality includes one or more of the following: Layer 1 reference signal received power L1-RSRP, layer 1 signal to interference plus noise ratio L1-SINR, layer 1 received signal strength indicator L1-RSSI, layer 1 reference signal received quality L1-RSRQ, and channel quality indicator CQI.

7. The method according to any one of claims 1 to 6, characterized in that: The measurement indication information is used to configure the one or more measurement sets and / or to activate the one or more measurement sets.

8. The method according to any one of claims 1 to 7, characterized in that: The method further comprises: Prediction indication information is received, where the prediction indication information is used to configure the one or more prediction sets and / or to activate the one or more prediction sets.

9. The method according to any one of claims 1 to 8, characterized in that: The method further comprises: Reporting capability information of the terminal device to the network device; The capability information is used to indicate the ability of the terminal device to measure and / or predict spatial domain mobility; the capability information of the terminal device is used by the network device to determine the one or more measurement sets and / or the one or more prediction sets.

10. The method according to claim 9, characterized in that The capability information includes at least one of the following information: Whether the terminal device supports measurement and / or prediction of spatial domain mobility; In the case where the terminal device supports measurement of spatial domain mobility, the terminal device supports a maximum number of candidate cells for measurement on all downlink component carriers CC / bandwidth parts BWP; In the case where the terminal device supports prediction of spatial domain mobility, the terminal device supports a maximum number of predicted candidate cells on all downlink CCs / BWPs; In the case where the terminal device supports measurement of spatial domain mobility, the terminal device supports a maximum number of measurement sets for measurement on one downlink CC / BWP; each measurement set corresponds to one cell; In the case where the terminal device supports prediction of spatial domain mobility, the terminal device supports a maximum number of prediction sets on all downlink CCs / BWPs; each prediction set corresponds to a cell.

11. The method according to any one of claims 1 to 10, characterized in that: The one or more prediction sets respectively correspond to the current serving cell of the terminal device and one or more candidate cells of the terminal device.

12. The method according to any one of claims 1 to 11, characterized in that: Each measurement set in the one or more measurement sets corresponds to a cell, and the measurement result of the spatial filter in the one or more measurement sets includes: The measurement result of the downlink reference signal resource of the cell corresponding to the one or more measurement sets is obtained on the spatial filter in the one or more measurement sets.

13. The method according to claim 12, characterized in that The downlink reference signal resources include SSB resources and / or CSI-RS resources.

14. The method according to any one of claims 1 to 13, characterized in that: In the case where the process of predicting the link quality of the spatial filters in one or more prediction sets is performed by the terminal device, the method further includes: Report prediction information to the network device according to the prediction result.

15. The method according to claim 14, characterized in that The reporting prediction information to the network device according to the prediction result includes: Reporting the prediction information to the network device in a periodic manner; reporting the prediction information to the network device in a semi-continuous manner; The prediction information is reported to the network device in a non-periodic manner.

16. The method according to claim 14, characterized in that The reporting prediction information to the network device according to the prediction result includes: The prediction information is reported to the network device according to the L1 / L2 mobility event.

17. The method according to claim 16, characterized in that The L1 / L2 mobility event includes at least one of the following events: The predicted link performance of the current serving cell is better / weaker than the first threshold; The predicted link performance of the current serving cell is better / weaker than the predicted link performance of the candidate cell plus the first offset; The predicted link performance of the candidate cell is better / weaker than the second threshold; The predicted link performance of the current serving cell is weaker than the point threshold, and the predicted link performance of the candidate cell is better than the fourth threshold.

18. The method according to any one of claims 1 to 13, characterized in that: In the case where the process of predicting the link quality of the spatial filters in one or more prediction sets is performed by the terminal device, the method further includes: According to the prediction result, a cell switching request is sent to the network device.

19. The method according to claim 18, characterized in that The cell switching request includes the prediction result.

20. The method according to any one of claims 1 to 13, characterized in that: In the case where the process of predicting the link quality of the spatial filters in the one or more prediction sets is performed by the network device, the method further includes: According to the measurement result, a measurement report is reported to the network device.

21. The method according to claim 20, characterized in that The measurement report includes: link qualities of resource indexes respectively corresponding to the one or more measurement sets; The link qualities of the resource indexes respectively corresponding to the one or more measurement sets are arranged according to the arrangement order of the one or more measurement sets and the arrangement order of the resource indexes corresponding to each of the measurement sets.

22. The method according to claim 20, characterized in that The measurement report includes: A difference between the link quality of the resource indexes respectively corresponding to the one or more measurement sets and the reference link quality; The differences between the link qualities of the resource indexes respectively corresponding to the one or more measurement sets and the reference link qualities are arranged according to the arrangement order of the one or more measurement sets and the arrangement order of the resource indexes corresponding to each of the measurement sets.

23. The method according to claim 22, characterized in that The measurement report includes: a first reference link quality; the first reference link quality is a link quality of a first resource index corresponding to a first measurement set; the first measurement set is one of the one or more measurement sets, and the first resource index is one of the resource indexes corresponding to the first measurement set; and, a difference between the first reference link quality and other link qualities other than the first reference link quality among the link qualities of the resource indexes respectively corresponding to the one or more measurement sets.

24. The method according to claim 23, characterized in that The first reference link quality is the highest link quality among the link qualities of the resource indexes respectively corresponding to one or more measurement sets; or, The first reference link quality is the lowest link quality among link qualities of resource indexes respectively corresponding to one or more measurement sets.

25. The method according to claim 23 or 24, characterized in that The measurement report also includes first marking information, where the first marking information is used to indicate that the link quality of the first resource index is the first reference link quality.

26. The method according to claim 22, characterized in that The measurement report includes: second reference link quality; the second reference link quality is the link quality of the second resource index corresponding to the second measurement set; the second measurement set is any one of the one or more measurement sets, and the second resource index is one of the resource indexes corresponding to the second measurement set; And, the difference between the second reference link quality and other link qualities of the link qualities of the resource indexes corresponding to the second measurement set except the second reference link quality.

27. The method according to claim 26, characterized in that The second reference link quality is the highest link quality among the link qualities of the resource indexes corresponding to the second measurement set; Alternatively, the second reference link quality is the lowest link quality among the link qualities of the resource indexes corresponding to the second measurement set.

28. The method according to claim 26 or 27, characterized in that The measurement report also includes second marking information, where the second marking information is used to indicate that the link quality of the second resource index is the second reference link quality.

29. The method according to claim 20, characterized in that The measurement report includes: Link qualities of resource indexes corresponding to all or part of the one or more measurement sets; and, an identifier of a measurement set corresponding to the link quality included in the measurement report, and / or an identifier of a resource index corresponding to the link quality included in the measurement report.

30. The method according to claim 20, characterized in that Reporting a measurement report to the network device according to the measurement result includes: Reporting, according to the measurement result, to the network device, sub-measurement reports respectively corresponding to the one or more measurement sets; The sub-measurement report includes the link quality of the resource index in the corresponding measurement set.

31. The method according to claim 30, characterized in that The sub-measurement report also includes an identifier of a corresponding measurement set; Alternatively, the sub-measurement report further includes an identifier of a corresponding measurement set and an identifier of a resource index corresponding to the link quality included in the sub-measurement report.

32. A processing method for measuring, characterized in that The method is performed by a network device, and the method includes: Sending measurement indication information to a terminal device, where the measurement indication information is used to instruct the terminal device to measure one or more spatial filters in a measurement set to obtain a measurement result; The measurement results are used to predict the link quality of the spatial filters in one or more prediction sets to obtain prediction results.

33. The method according to claim 32, characterized in that The prediction result is used to indicate one or more of the following: An optimal cell among the cells corresponding to the one or more prediction sets; An optimal spatial filter or an optimal spatial filter pair under the optimal cell; and, the link quality of the optimal spatial filter or the optimal spatial filter pair.

34. The method according to claim 33, characterized in that The prediction results include one or more of the following: Identifications of L optimal cells among the cells corresponding to the one or more prediction sets; L is an integer greater than or equal to 1; The index of the optimal spatial filter or the index of the optimal spatial filter pair in the L optimal cells; The link quality corresponding to the index of the optimal spatial filter, or the link quality corresponding to the index of the optimal spatial filter pair.

35. The method according to claim 34, characterized in that The identifier of the best cell includes one or more of the following: A physical cell identifier PCI of the optimal cell; The PCI index of the best cell; The configuration index of the optimal cell; The index of the prediction set to which the optimal cell belongs.

36. The method according to claim 34 or 35, characterized in that The index of the optimal spatial filter or the index of the optimal spatial filter pair includes: A CSI-RS resource indication CRI of the optimal spatial filter or the optimal spatial filter pair; And / or, the SSB resource indication SSB RI of the optimal spatial filter or the optimal spatial filter pair.

37. The method according to any one of claims 34 to 36, characterized in that: The link quality includes one or more of the following: L1-RSRP, L1-SINR, L1-RSSI, L1-RSRQ, and CQI.

38. The method according to any one of claims 32 to 37, characterized in that: The measurement indication information is used to configure the one or more measurement sets and / or to activate the one or more measurement sets.

39. The method according to any one of claims 32 to 38, characterized in that The method further comprises: Sending prediction indication information to the terminal device, where the prediction indication information is used to configure the one or more prediction sets and / or to activate the one or more prediction sets.

40. The method according to any one of claims 32 to 39, characterized in that: The method further comprises: Receiving capability information of the terminal device reported by the terminal device; the capability information is used to indicate the capability of the terminal device to measure and / or predict spatial domain mobility; The one or more measurement sets and / or the one or more prediction sets are determined according to the capability information of the terminal device.

41. The method according to claim 40, characterized in that The capability information includes at least one of the following information: Whether the terminal device supports measurement and / or prediction of spatial domain mobility; In the case where the terminal device supports measurement of spatial domain mobility, the maximum number of candidate cells supported by the terminal device for measurement on all downlink CCs / BWPs; In the case where the terminal device supports prediction of spatial domain mobility, the terminal device supports at most The number of candidate cells supported for prediction; In the case where the terminal device supports measurement of spatial domain mobility, the terminal device supports a maximum number of measurement sets for measurement on one downlink CC / BWP; each measurement set corresponds to one cell; In the case where the terminal device supports prediction of spatial domain mobility, the terminal device supports a maximum number of prediction sets on all downlink CCs / BWPs; each prediction set corresponds to a cell.

42. The method according to any one of claims 32 to 41, characterized in that The one or more prediction sets respectively correspond to the current serving cell of the terminal device and one or more candidate cells of the terminal device.

43. The method according to any one of claims 32 to 42, characterized in that: Each measurement set in the one or more measurement sets corresponds to a cell, and the measurement result of the spatial filter in the one or more measurement sets includes: The measurement result of the downlink reference signal resource of the cell corresponding to the one or more measurement sets is obtained on the spatial filter in the one or more measurement sets.

44. The method according to claim 43, characterized in that The downlink reference signal resources include SSB resources and / or CSI-RS resources.

45. The method according to any one of claims 32 to 44, characterized in that In the case where the process of predicting the link quality of the spatial filters in one or more prediction sets is performed by the terminal device, the method further includes: Receive prediction information reported by the terminal device based on the prediction result.

46. ​​The method according to claim 45, characterized in that The receiving prediction information reported by the terminal device according to the prediction result includes: Receiving the prediction information reported by the terminal device in a periodic manner; Receiving the prediction information reported by the terminal device in a semi-continuous manner; Receive the prediction information reported by the terminal device in a non-periodic manner.

47. The method according to claim 45, characterized in that The receiving prediction information reported by the terminal device according to the prediction result includes: Receive the prediction information reported by the terminal device according to the L1 / L2 mobility event.

48. The method according to claim 47, characterized in that The L1 / L2 mobility event includes at least one of the following events: The predicted link performance of the current serving cell is better / weaker than the first threshold; The predicted link performance of the current serving cell is better / weaker than the predicted link performance of the candidate cell plus the first offset; The predicted link performance of the candidate cell is better / weaker than the second threshold; The predicted link performance of the current serving cell is weaker than the point threshold, and the predicted link performance of the candidate cell is better than the fourth threshold.

49. The method according to any one of claims 32 to 44, characterized in that In the case where the process of predicting the link quality of the spatial filters in one or more prediction sets is performed by the terminal device, the method further includes: Receive a cell switching request sent by the terminal device according to the prediction result.

50. The method according to claim 49, characterized in that The cell switching request includes the prediction result.

51. The method according to any one of claims 32 to 44, characterized in that In the case where the process of predicting the link quality of the spatial filters in the one or more prediction sets is performed by the network device, the method further includes: Receive a measurement report reported by the terminal device based on the measurement result.

52. The method according to claim 51, characterized in that The measurement report includes: link qualities of resource indexes respectively corresponding to the one or more measurement sets; The link qualities of the resource indexes respectively corresponding to the one or more measurement sets are arranged according to the arrangement order of the one or more measurement sets and the arrangement order of the resource indexes corresponding to each of the measurement sets.

53. The method according to claim 51, characterized in that The measurement report includes: A difference between the link quality of the resource indexes respectively corresponding to the one or more measurement sets and the reference link quality; The differences between the link qualities of the resource indexes respectively corresponding to the one or more measurement sets and the reference link qualities are arranged according to the arrangement order of the one or more measurement sets and the arrangement order of the resource indexes corresponding to each of the measurement sets.

54. The method according to claim 53, characterized in that The measurement report includes: a first reference link quality; the first reference link quality is a link quality of a first resource index corresponding to a first measurement set; the first measurement set is one of the one or more measurement sets, and the first resource index is one of the resource indexes corresponding to the first measurement set; and, a difference between the first reference link quality and other link qualities other than the first reference link quality among the link qualities of the resource indexes respectively corresponding to the one or more measurement sets.

55. The method according to claim 54, characterized in that The first reference link quality is the highest link quality among the link qualities of the resource indexes respectively corresponding to one or more measurement sets; or, The first reference link quality is the lowest link quality among link qualities of resource indexes respectively corresponding to one or more measurement sets.

56. The method according to claim 54 or 55, characterized in that The measurement report also includes first marking information, where the first marking information is used to indicate that the link quality of the first resource index is the first reference link quality.

57. The method according to claim 53, characterized in that The measurement report includes: second reference link quality; the second reference link quality is the link quality of the second resource index corresponding to the second measurement set; the second measurement set is any one of the one or more measurement sets, and the second resource index is one of the resource indexes corresponding to the second measurement set; And, the difference between the second reference link quality and other link qualities of the link qualities of the resource indexes corresponding to the second measurement set except the second reference link quality.

58. The method according to claim 57, characterized in that The second reference link quality is the highest link quality among the link qualities of the resource indexes corresponding to the second measurement set; Alternatively, the second reference link quality is the lowest link quality among the link qualities of the resource indexes corresponding to the second measurement set.

59. The method according to claim 57 or 58, characterized in that The measurement report also includes second marking information, where the second marking information is used to indicate that the link quality of the second resource index is the second reference link quality.

60. The method according to claim 51, characterized in that The measurement report includes: Link qualities of resource indexes corresponding to all or part of the one or more measurement sets; and, an identifier of a measurement set corresponding to the link quality included in the measurement report, and / or an identifier of a resource index corresponding to the link quality included in the measurement report.

61. The method according to claim 51, characterized in that The receiving a measurement report reported by the terminal device according to the measurement result includes: Receiving sub-measurement reports respectively corresponding to the one or more measurement sets reported by the terminal device according to the measurement result; The sub-measurement report includes the link quality of the resource index in the corresponding measurement set.

62. The method according to claim 61, characterized in that The sub-measurement report also includes an identifier of a corresponding measurement set; Alternatively, the sub-measurement report further includes an identifier of a corresponding measurement set and an identifier of a resource index corresponding to the link quality included in the sub-measurement report.

63. A processing device for measuring, characterized in that The device comprises: A receiving module, used to receive measurement indication information, where the measurement indication information is used to indicate that a measurement result is obtained by measuring one or more spatial filters in a measurement set; The measurement results are used to predict the link quality of the spatial filters in one or more prediction sets to obtain prediction results.

64. A processing device for measuring, characterized in that The device comprises: A sending module, used to send measurement indication information to a terminal device, where the measurement indication information is used to instruct the terminal device to measure one or more spatial filters in a measurement set to obtain a measurement result; The measurement results are used to predict the link quality of the spatial filters in one or more prediction sets to obtain prediction results.

65. A terminal device, characterized in that: The terminal device includes a processor, a memory and a transceiver; The memory stores a computer program, and the processor executes the computer program so that the terminal device implements the processing method for measurement as described in any one of claims 1 to 31 above.

66. A network device, characterized in that: The terminal device includes a processor, a memory and a transceiver; The memory stores a computer program, and the processor executes the computer program so that the network device implements the processing method for measurement as described in any one of claims 32 to 62.

67. A computer-readable storage medium, characterized in that The storage medium stores a computer program, and the computer program is used to be executed by a processor of a communication device, so that the communication device implements the processing method for measurement as described in any one of claims 1 to 62.

68. A chip, characterized in that: The chip is used to run in a communication device so that the communication device executes the processing method for measurement as claimed in any one of claims 1 to 62.

69. A computer program product, characterized in that The computer program product includes computer instructions, which are stored in a computer-readable storage medium; the processor of the communication device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, so that the communication device performs the processing method for measurement as described in any one of claims 1 to 62.

70. A computer program, characterized in that The computer program is executed by a processor of a communication device so that the communication device implements the processing method for measurement according to any one of claims 1 to 62.

Images