Communication method and device

Abstract

The present application relates to a communication method and a communication device. The method comprises: a first communication device sends first information, wherein the first information is used for indicating a prediction capability related to mobility management supported by the first communication device. In embodiments of the present application, by reporting a prediction capability related to mobility management supported by a communication device, an algorithm related to the mobility management of the communication device side can be reasonably operated.

Description

Communication method and device Technical Field

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

[0002] In the fifth-generation (5G) new radio (NR) of the 3rd Generation Partnership Project (3GPP), after the user equipment (UE) performs initial access, the network can obtain the UE capabilities by directly obtaining the UE capabilities through the radio interface or by downloading the stored UE capabilities through the core network.

[0003] Summary of the Invention

[0004] This embodiment of the present application provides a communication method, including:

[0005] The first communication device sends first information, where the first information is used to indicate a mobility management-related prediction capability supported by the first communication device.

[0006] This embodiment of the present application provides a communication method, including:

[0007] The second communication device receives and sends first information, where the first information is used to indicate a mobility management-related prediction capability supported by the first communication device.

[0008] An embodiment of the present application provides a first communication device, including:

[0009] The sending unit is configured to send first information, where the first information is used to indicate a mobility management-related prediction capability supported by the first communication device.

[0010] An embodiment of the present application provides a second communication device, including:

[0011] The receiving unit is configured to receive and send first information, where the first information is used to indicate a mobility management-related prediction capability supported by the first communication device.

[0012] An embodiment of the present application provides a communication device, comprising: a transceiver, a processor, and a memory. The memory is used to store a computer program, the transceiver is used to communicate with other devices, and the processor is used to call and execute the computer program stored in the memory so that the communication device performs the above-mentioned communication method.

[0013] An embodiment of the present application provides a chip for implementing the above-mentioned communication method.

[0014] Specifically, the chip includes: a processor, which is used to call and run a computer program from a memory, so that a device equipped with the chip executes the above-mentioned communication method.

[0015] An embodiment of the present application provides a computer-readable storage medium for storing a computer program, which, when executed by a device, enables the device to execute the above-mentioned communication method.

[0016] An embodiment of the present application provides a computer program product, including computer program instructions, which enable a computer to execute the above-mentioned communication method.

[0017] An embodiment of the present application provides a computer program, which, when executed on a computer, enables the computer to execute the above-mentioned communication method.

[0018] In the embodiment of the present application, by reporting the prediction capabilities related to mobility management supported by the communication device, the mobility management-related algorithms on the communication device side can be reasonably operated. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] FIG1 is a schematic diagram of an application scenario according to an embodiment of the present application.

[0020] Figure 2 is a schematic diagram of the measurement model.

[0021] FIG3 is a schematic flowchart of a communication method according to an embodiment of the present application.

[0022] FIG4 is a schematic flowchart of a communication method according to another embodiment of the present application.

[0023] FIG5 is a schematic flowchart of a communication method according to another embodiment of the present application.

[0024] FIG6 is a schematic flowchart of a communication method according to an embodiment of the present application.

[0025] FIG7 is a schematic flowchart of a communication method according to another embodiment of the present application.

[0026] FIG8 is a schematic flowchart of a communication method according to another embodiment of the present application.

[0027] FIG9 is a schematic block diagram of a first communication device according to an embodiment of the present application.

[0028] FIG10 is a schematic block diagram of a second communication device according to an embodiment of the present application.

[0029] FIG11 is a schematic block diagram of a communication device according to an embodiment of the present application.

[0030] FIG12 is a schematic block diagram of a chip according to an embodiment of the present application.

[0031] FIG13 is a schematic block diagram of a communication system according to an embodiment of the present application. DETAILED DESCRIPTION

[0032] The technical solutions in the embodiments of the present application will be described below in conjunction with the drawings in the embodiments of the present application.

[0033] The technical solutions of the embodiments of the present application can be applied to various communication systems, such as: Long Term Evolution (LTE) system, Advanced Long Term Evolution (LTE-A) 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, NR-U) system, Non-Terrestrial Networks (NTN) system, Universal Mobile Telecommunication System (UMTS), Wireless Local Area Networks (WLAN), Wireless Fidelity (WiFi), Fifth Generation (5G) system or other communication systems.

[0034] Generally speaking, traditional communication systems support a limited number of connections and are easy to implement. However, with the development of communication technology, mobile communication systems will not only support traditional communications, but will also support, for example, device-to-device (D2D) communication, machine-to-machine (M2M) communication, machine-type communication (MTC), vehicle-to-vehicle (V2V) communication, or vehicle-to-everything (V2X) communication, etc. The embodiments of the present application can also be applied to these communication systems.

[0035] In one embodiment, the communication system in the embodiment of the present application can be applied to a carrier aggregation (CA) scenario, a dual connectivity (DC) scenario, and a standalone (SA) networking scenario.

[0036] In one embodiment, the communication system in the embodiment of the present application can be applied to an unlicensed spectrum, wherein the unlicensed spectrum can also be considered as a shared spectrum; or, the communication system in the embodiment of the present application can also be applied to an authorized spectrum, wherein the authorized spectrum can also be considered as an unshared spectrum.

[0037] The embodiments of the present application describe various embodiments in conjunction with network devices and terminal devices, wherein the terminal device may also be referred to as 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 or user device, etc.

[0038] The terminal device can be a station (STAION, ST) in a WLAN, a cellular phone, a cordless phone, a Session Initiation Protocol (SIP) phone, a Wireless Local Loop (WLL) station, a Personal Digital Assistant (PDA) device, a handheld device with wireless communication capabilities, a computing device or other processing device connected to a wireless modem, a vehicle-mounted device, a wearable device, a terminal device in a next-generation communication system such as an NR network, or a terminal device in a future evolved Public Land Mobile Network (PLMN) network, etc.

[0039] In an embodiment of the present application, the terminal device can be deployed on land, including indoors or outdoors, handheld, wearable or vehicle-mounted; it can also be deployed on the water surface (such as ships, etc.); it can also be deployed in the air (such as airplanes, balloons and satellites, etc.).

[0040] In an embodiment of the present application, the terminal device may be a mobile phone, a tablet computer, a computer with wireless transceiver function, a virtual reality (VR) terminal device, an augmented reality (AR) terminal device, a wireless terminal device in industrial control, a wireless terminal device in self-driving, a wireless terminal device in remote medical, a wireless terminal device in a smart grid, a wireless terminal device in transportation safety, a wireless terminal device in a smart city, or a wireless terminal device in a smart home, etc.

[0041] As an example and not a limitation, in the embodiment of the present application, the terminal device may also be a wearable device. Wearable devices may also be called wearable smart devices, which are a general term for wearable devices that are intelligently designed and developed using wearable technology for daily wear, such as glasses, gloves, watches, clothing, and shoes. A wearable device is a portable device that is worn directly on the body or integrated into the user's clothes or accessories. Wearable devices are not only hardware devices, but also achieve powerful functions through software support, data interaction, and cloud interaction. Broadly speaking, wearable smart devices include those that are fully functional, large in size, and can achieve complete or partial functions without relying on smartphones, such as smart watches or smart glasses, as well as those that only focus on a certain type of application function and need to be used in conjunction with other devices such as smartphones, such as various smart bracelets and smart jewelry for vital sign monitoring.

[0042] In an embodiment of the present application, the network device may be a device for communicating with a mobile device. The network device may be an access point (AP) in a WLAN, an evolved base station (eNB or eNodeB) in LTE, or a relay station or access point, or a vehicle-mounted device, a wearable device, and a network device (gNB) in an NR network, or a network device in a future evolved PLMN network or a network device in an NTN network, etc.

[0043] As an example and not a limitation, in an embodiment of the present application, the network device may have a mobile feature, for example, the network device may be a mobile device. Alternatively, the network device may be a satellite or a balloon station. For example, the satellite may be a low earth orbit (LEO) satellite, a medium earth orbit (MEO) satellite, a geostationary earth orbit (GEO) satellite, a high elliptical orbit (HEO) satellite, etc. Optionally, the network device may also be a base station set up in a location such as land or water.

[0044] In an embodiment of the present application, the network device can provide services for a cell, and the terminal device communicates with the network device through the transmission resources used by the cell (for example, frequency domain resources, or spectrum resources). The cell can be a cell corresponding to the network device (for example, a base station). The cell can belong to a macro base station or a base station corresponding to a small cell. The small cells here may include: metro cells, micro cells, pico cells, femto cells, etc. These small cells have the characteristics of small coverage and low transmission power, and are suitable for providing high-speed data transmission services.

[0045] FIG1 exemplarily illustrates a communication system 100. The communication system includes a network device 110 and two terminal devices 120. In one embodiment, the communication system 100 may include multiple network devices 110, and each network device 110 may include a different number of terminal devices 120 within its coverage area, which is not limited in this embodiment of the present application.

[0046] In one embodiment, the communication system 100 may further include other network entities such as a Mobility Management Entity (MME) and an Access and Mobility Management Function (AMF), which is not limited in this embodiment of the present application.

[0047] Among them, the network equipment may include access network equipment and core network equipment. That is, the wireless communication system also includes multiple core networks for communicating with the access network equipment. The access network equipment can be an evolutionary base station (evolutional node B, abbreviated as eNB or e-NodeB) macro base station, micro base station (also called "small base station"), pico base station, access point (AP), transmission point (TP) or new generation base station (new generation Node B, gNodeB), etc. in a long-term evolution (LTE) system, a next-generation (mobile communication system) (next radio, NR) system or an authorized auxiliary access long-term evolution (LAA-LTE) system.

[0048] It should be understood that in the embodiments of the present application, a device having a communication function in a network / system may be referred to as a communication device. Taking the communication system shown in Figure 1 as an example, the communication device may include a network device and a terminal device having a communication function. The network device and the terminal device may be specific devices in the embodiments of the present application and will not be described in detail here. The communication device may also include other devices in the communication system, such as a network controller, a mobility management entity, and other network entities, which are not limited in the embodiments of the present application.

[0049] It should be understood that the terms "system" and "network" are often used interchangeably herein. The term "and / or" is simply a description of an association between related objects, indicating that three possible relationships exist. For example, "A and / or B" can represent: A exists alone, A and B exist simultaneously, or B exists alone. Furthermore, the character " / " generally indicates that the related objects are in an "or" relationship.

[0050] It should be understood that the "indication" mentioned in the embodiments of this application can be a direct indication, an indirect indication, or an indication of an association. For example, "A indicates B" can mean that A directly indicates B, for example, B can be obtained through A; it can also mean that A indirectly indicates B, for example, A indicates C, and B can be obtained through C; it can also mean that there is an association between A and B.

[0051] In the description of the embodiments of the present application, the term "corresponding" may indicate a direct or indirect correspondence between the two, or an association relationship between the two, or a relationship between indication and being indicated, configuration and being configured, etc.

[0052] To facilitate understanding of the technical solutions of the embodiments of the present application, the relevant technologies of the embodiments of the present application are described below. The following relevant technologies can be arbitrarily combined with the technical solutions of the embodiments of the present application as optional solutions, and they all fall within the protection scope of the embodiments of the present application.

[0053] 1. UE capability

[0054] In the 3GPP 5G NR control plane core standard protocol, the network can require the UE to report the technical features supported by the UE through Radio Resource Control (RRC) signaling. After the UE makes initial access, the network can obtain the UE capabilities in the following ways:

[0055] Method 1: Directly obtain through the wireless interface

[0056] 1. After the base station to which the UE is connected establishes a connection with the core network, if the core network finds that the UE capabilities of the UE are not stored, it will request the base station to obtain the UE capabilities of the UE through the NG interface.

[0057] 2. The base station then sends a Capability Request message to the UE on the Uu interface. This message primarily requests the UE to send UE capability signaling. The message may contain auxiliary information elements, such as filters used to reduce the uplink signaling load (the UE filters out content based on the filter and then reports the remaining content).

[0058] 3. After receiving the request message, the UE reports content related to its wireless capabilities. A clear distinction between the reported technical features is their granularity, as well as the differences between frequency division duplex (FDD) and / or time division duplex (TDD) communication modes. The granularity of technical features is primarily described from a frequency domain perspective. From coarse to fine, it can include: per UE (e.g., all bandwidths supported by the UE, and their bandwidth combinations, support the feature); per band (set according to the granularity of the bandwidths supported by the UE); per band combination (set according to the granularity of the bandwidth combinations supported by the UE, where one or more bandwidths may be included in a bandwidth combination for configuring dual link or carrier aggregation); per feature set (set according to the granularity of different bandwidths within a bandwidth combination); and per feature set per carrier aggregation (per feature set per CC) (set according to the granularity of different bandwidths within a bandwidth combination, provided carrier aggregation is supported).

[0059] 4. The base station records the received UE capabilities (included in the UE Capability Information message) locally for use in the current communication process. Furthermore, the base station sends the UE capabilities to the core network via the Next Generation (NG) interface. The core network stores these UE capabilities.

[0060] Method 2: Downloading stored UE capabilities through the core network. In the first step above, if the core network finds that the UE capabilities of the UE have been stored, the core network directly sends these UE capabilities related to radio access to the base station through the NG interface for use in this communication process.

[0061] UE capabilities include measurement and / or mobility-related UE capabilities. These UE capabilities are per-UE capabilities. Table 1 shows examples of UE capabilities related to mobility. "M" indicates whether the technical feature is mandatory. If mandatory, the signaling bit of the UE capability is used to indicate whether the technical feature has been tested jointly between the network and the terminal.

[0062] 2. Artificial Intelligence (AI) / Machine Learning (ML)

[0063] 3GPP has studied whether AI / ML algorithms can help improve the performance of the physical layer, and has documented the core evaluation methods and results in a technical report (TR). In addition, the TR also records the steps and content for managing AI / ML on the network side or the UE side, or both sides. These contents become life cycle management (LCM) content in the TR. LCM can include data collection, model training, function / model identification, model transmission, model reasoning, function / model selection, activation, deactivation, replacement and fallback, function / model monitoring, model update, UE capability reporting, etc.

[0064] From the perspective of UE capabilities, no further description is given except that the UE reporting, storage and downloading mechanisms can be simply reused.

[0065] 3. Radio Resource Management (RRM) Measurement

[0066] In 3GPP cellular communication systems, the UE needs to measure the strength or quality of the wireless signals in the current serving cell and neighboring cells, and then report this information to the network using an RRC message called a measurement report. The network can generally make relevant handover decisions based on this information.

[0067] Refer to Model Figure 2, which includes how the UE performs intra-frequency or inter-frequency measurements, how it performs beam-based measurement sampling at Layer 1 (L1), and how it determines measurement events based on network-configured parameters.

[0068] Several reference points shown in Figure 2 are as follows:

[0069] A: The UE performs physical layer measurement sampling at the beam granularity (e.g., gNB beam1, gNB beam1, ..., gNB beamK).

[0070] A1: The UE performs Layer 1 filtering on the beam measurement results. Generally, the protocol specifies the length of the measurement period under specific RRC configurations. This measurement period mandates that the UE perform at least one sampling, and that the beam measurement results after L1 filtering meet the performance requirements specified in the 3GPP specification. At reference point A, the UE performs a specific number of samplings within a measurement period. In test cases, an oversampling of 4 to 5 is typically used.

[0071] B: A1 performs a consolidation operation on the beam measurement results obtained in a certain cell to synthesize the L1 cell-level measurement results.

[0072] C: L1 cell-level measurement results of a certain cell, which are filtered through Layer 3 (Layer 3, L3) (Layer 3 Beam filtering) to obtain L3 cell-level measurement results in sequence.

[0073] D: The measurement results of the serving cell and / or neighboring cells are used to determine whether a specific measurement event is established according to certain judgment conditions (configured by the network). For example, whether the measurement result of the neighboring cell is higher than the measurement result of the primary cell (PCell) of the cell by an offset value (A3 event), etc.

[0074] When the network configures a measurement task for a UE, a specific measurement task may include:

[0075] 1. The measurement object, including the measured frequency and reference signal description. If the measured frequency is the same as the center frequency of the current serving cell and the subcarrier spacing is the same, it is an intra-frequency measurement; otherwise, it is an inter-frequency measurement.

[0076] 2. Measurement configuration, including the type of measurement reporting (including event triggering, periodic reporting, and periodic reporting after event triggering, etc.), as well as various configuration parameters corresponding to each reporting type.

[0077] 3. What links the above two parts is a measurement task, which is identified by an identification number (measID).

[0078] The measurement tasks configured for the UE are in a dual connectivity architecture (with two cell groups, namely the master cell group (MCG) and the secondary cell group (SCG). Each cell group can be configured with its own measurement tasks. The same measurement objects can even be configured in each measurement task. When there is only one cell group (i.e., a stand alone architecture with only MCG), the measurement tasks are configured by the MCG.

[0079] In addition, 3GPP has studied what factors affect mobility performance when deploying multi-layer networks (hetnets). In these studies, some key indicators were defined, including:

[0080] 1. Handover failure: When the network sends a handover command message to the UE, if the timer T310 used to determine the radio link failure is running or has timed out, this situation is determined as a handover failure. The determination of radio link failure is made according to the LTE protocol. After receiving N310 consecutive indications of link deterioration (Qout), the UE will start the T310 timer. If the T310 timer times out, the UE will assume that a radio link failure has occurred. When T310 is running, if N311 indications of link improvement (Qin) are received, the timer T310 will be stopped. The length of the T310 timer, counters N310 and N311 are all configured by the network.

[0081] 2. Ping-pong handover: When a UE switches from cell A to cell B and then switches back to cell A within a specified time threshold (e.g., 1 second), such a handover is considered a ping-pong handover.

[0082] 3. Too short handover: When a UE switches from cell A to cell B and then switches back to cell C within a specified time threshold (e.g., 1 second), and cell C is not cell A, such handover is considered too short.

[0083] These models and switching metric definitions can be reused in the research of the AI ​​mobility project.

[0084] Research projects focused on improving mobility management (handover) support AI / ML models for mobility management. Specifically, there is no specific solution for the UE-side model. This solution allows for UE capability reporting and the network to perform appropriate configuration based on the reported UE capabilities, enabling the UE-side AI / ML model to operate efficiently.

[0085] FIG3 is a schematic flow chart of a communication method 300 according to an embodiment of the present application. The method can optionally be applied to the system shown in FIG1 , but is not limited thereto. The method includes at least part of the following contents.

[0086] S310. A first communication device sends first information, where the first information is used to indicate a mobility management-related prediction capability supported by the first communication device.

[0087] In an embodiment of the present application, a first communication device may report to a second communication device prediction capabilities related to mobility management supported by the first communication device, such as reporting one or more prediction capabilities supported by an AI / ML model that supports mobility management. Prediction capabilities may also be referred to as prediction functions.

[0088] In the embodiment of the present application, by reporting the prediction capabilities related to mobility management supported by the communication device, the mobility management-related algorithms on the communication device side can be reasonably operated.

[0089] In one embodiment, the mobility management-related prediction capability includes at least one of the following: measurement result prediction; measurement event prediction; and abnormal event prediction.

[0090] In an embodiment of the present application, the measurement result may include one or more of Reference Signal Receiving Power (RSRP), Reference Signal Receiving Quality (RSRQ), Signal to Interference plus Noise Ratio (SINR), etc. The measurement result prediction may include obtaining a predicted measurement result based on historical measurement results. The historical measurement result may be an actual measurement result or a historically predicted result. The predicted measurement result may include at least one of the following: a measurement result for a period of time in the future, a measurement result at a future time point, and a measurement result at a time point in the past when no measurement was performed.

[0091] In the embodiment of the present application, the measurement event may include one or more of an A1 event (a serving cell exceeds a threshold value), an A2 event (a serving cell falls below a threshold value), an A3 event (a neighboring cell exceeds a primary serving cell by an offset value), and the like. The measurement event prediction may include a measurement event predicted based on historical measurement results or predicted measurement results. For example, if within a time period, the predicted value of the measurement result of the neighboring cell is higher than the predicted value of the measurement result of the primary cell (PCell) of the current cell by an offset value, it can be predicted that an A3 event will occur within the time period.

[0092] In the embodiment of the present application, the abnormal event may include one or more of handover failure, radio link failure, too short a handover time, ping-pong handover, etc. Whether an abnormal event occurs can be predicted based on the measurement results and / or measurement events.

[0093] In one embodiment, the measurement result prediction includes at least one of the following:

[0094] L1 (physical layer) beam measurement result prediction;

[0095] L3 (network layer) cell measurement result prediction.

[0096] For example, L1 beam measurement result prediction may include predicting an L1 beam measurement result based on historical L1 beam measurement results of a cell. The predicted L1 beam measurement result, after merging and L3 filtering, is called a predicted L3 cell measurement result. The predicted L1 beam measurement result may be a time domain prediction result, a frequency domain prediction result, or a spatial domain prediction result. The time domain prediction result may include measurement results for a future period predicted using actual measurement results from a past period, or measurement results for unmeasured time points in a past period predicted using actual measurement results from a past period. The frequency domain prediction result may include unmeasured frequency band measurement results predicted based on actually measured frequency bands. The spatial domain prediction result may include unmeasured beam / cell measurement results predicted based on actually measured beam / cell measurement results.

[0097] In one embodiment, the L3 cell measurement result prediction includes: predicting subsequent L3 cell measurement results based on historical L1 beam measurement results, and / or predicting subsequent L3 cell measurement results based on historical L3 cell measurement results.

[0098] For example, the L3 cell measurement result prediction capability may include L3 cell measurement result prediction capability 1 and L3 cell measurement result prediction capability 2. L3 cell measurement result prediction capability 1 may include directly predicting the L3 cell measurement result of a cell based on a historical L1 beam measurement result of the cell. L3 cell measurement result prediction capability 2 may include predicting the L3 cell measurement result of the cell based on a historical L3 cell measurement result of the cell.

[0099] In one embodiment, the measurement event prediction includes: predicting the measurement event based on historical L1 beam measurement results, and / or predicting the measurement event based on historical L3 cell measurement results.

[0100] For example, the measurement event prediction function may include measurement event prediction capability 1 and measurement event prediction capability 2. Measurement event prediction capability 1 includes predicting a measurement event for a cell based on historical L1 beam measurement results of the cell. Measurement event prediction capability 2 includes predicting a measurement event for the cell based on historical L3 cell measurement results of the cell.

[0101] In one embodiment, the abnormal event prediction includes at least one of the following:

[0102] Wireless link failure prediction;

[0103] Handover failure prediction;

[0104] Too short a switching event prediction time;

[0105] Ping-pong switching event prediction.

[0106] For example, radio link failure prediction includes: predicting whether the radio link of the serving cell has failed based on the L1 beam measurement results. For another example, handover failure prediction includes combining the measurement event and the prediction results of the radio link failure, as well as some internal auxiliary information such as the UE's location or moving speed, to predict whether a handover failure will occur. For another example, it is predicted whether the UE will switch to cell C quickly after switching from cell A to cell B, and whether the time spent in cell B is less than a threshold, thereby predicting whether the UE will experience a too-short handover event. For another example, it is predicted whether the UE will switch back to cell A quickly after switching from cell A to cell B, and whether the time spent in cell B is less than a threshold, thereby predicting whether the UE will experience a ping-pong handover event.

[0107] FIG4 is a schematic flow chart of a communication method 400 according to another embodiment of the present application. The method may include one or more features of the above method 300. In one embodiment, the method further includes:

[0108] S410. The first communication device receives second information, which is used to request the first communication device to report prediction capabilities related to mobility management. For example, this step may be before S310. After receiving the second information from the second communication device, the first communication device sends the first information to the second communication device. An AI / ML model in the first communication device can support one or more prediction capabilities related to mobility management, and a prediction capability can be called a technical feature. There may be more than one model supporting the same or similar technical features inside the first communication device. The AI / ML models can be numbered for accurate identification in signaling. For example, model 1 supports technical feature 1 and technical feature 2, and model 2 supports technical feature 2 and technical feature 3. Among them, technical feature 1 represents L1 beam measurement result prediction capability, technical feature 2 represents L3 cell measurement result prediction capability 1, and technical feature 3 represents measurement event prediction capability 2.

[0109] In one embodiment, the second information includes a filtering condition for the mobility management-related prediction capabilities required to be reported by the first communication device. The first communication device may determine which mobility management-related prediction capabilities to report to the second communication device based on the filtering condition.

[0110] In one embodiment, the filtering condition includes at least one of the following:

[0111] Requesting the first communication device to report a model supporting one or more technical features;

[0112] Require the first communication device to report a model that satisfies one or more handover scenarios;

[0113] Requesting the first communication device to report one or more supported technical features;

[0114] The one technical feature corresponds to a prediction capability related to mobility management, and a model supports the one or more technical features.

[0115] In an embodiment of the present application, if the filtering condition includes requiring the first communication device to report models that support certain technical features, then in addition to reporting the filtered models, the first communication device may also describe the switching scenarios to which these models are applicable. For example, the switching scenarios to which these models are applicable include at least one of the following: switching between macro cells, between micro cells, between multi-layer cells, switching of low-speed UEs, switching of medium- and high-speed UEs, etc. For example, if the filtering condition includes requiring the first communication device to report models that support technical feature 1, then the first communication device may report the number of model 1 and the switching scenario of model 1. If the filtering condition includes requiring the first communication device to report models that support technical feature 2, then the first communication device may report the numbers of model 1 and model 2, as well as the switching scenarios of model 1 and model 2.

[0116] In an embodiment of the present application, if the filtering condition includes requiring the first communication device to report a model that supports certain switching scenarios, then in addition to reporting the filtered models, the first communication device may also describe the technical features supported by each model. For example, if the filtering condition includes requiring the first communication device to report a model that supports switching scenario S1. If switching scenario S1 includes ping-pong switching, the number of the model that supports ping-pong switching event prediction may be reported, and all technical features supported by the model, such as technical features 1, 2, and 3, may also be reported. If switching scenario S1 includes too short a time switching, the number of the model that supports too short a time switching event prediction may be reported, and all technical features supported by the model, such as technical features 2, 3, and 4, may also be reported.

[0117] In the embodiment of the present application, if the filtering condition includes requiring the first communication device to report supported specific technical features, the model may not be described. For example, if the filtering condition includes requiring the first communication device to report supported technical feature 1, the first communication device may report technical feature 1.

[0118] In one embodiment, the reporting granularity of the mobility management-related prediction capability includes terminal, frequency band, or frequency band combination.

[0119] In one embodiment, the reporting granularity is that the terminal indicates reporting the models and / or technical features corresponding to all frequency bands and frequency band combinations supported by the terminal; or

[0120] The reporting granularity is frequency band, indicating reporting of the model and / or technical features corresponding to a frequency band; or

[0121] The reporting granularity is a frequency band combination, which means reporting a model and / or technical features corresponding to a frequency band combination.

[0122] For example, the frequency bands supported by UE1 include bandA, bandB, and bandC, where bandA corresponds to technical feature A1 and technical feature A2, bandB corresponds to technical feature B1 and technical feature B2, and bandC corresponds to technical feature C1 and technical feature C2. If the reporting granularity is UE, all corresponding technical feature serial numbers and other information can be reported. If the reporting granularity is frequency band, the serial numbers of technical feature A1 and technical feature A2 corresponding to a certain frequency band, such as bandA, and other information can be reported. If the reporting granularity is the frequency band combination bandA and bandB, the technical features of the two frequency bands can be matched one-to-one according to the serial numbers, and these one-to-one corresponding technical feature combinations {A1, B1}, {A2, B2} become the technical feature combinations in the frequency band combination. These technical feature combinations can be reported subsequently.

[0123] In one embodiment, the relationship between the predictive capabilities includes at least one of the following:

[0124] Supports the prediction of terminals, frequency bands or frequency band combinations for measurement events, as well as the prediction of measurement results;

[0125] Supports prediction of short-term handover events or ping-pong handover events for terminals, frequency bands, or frequency band combinations, as well as prediction of measurement events and / or measurement results;

[0126] Supports handover failure prediction for terminals, frequency bands, or frequency band combinations, as well as measurement event prediction and radio link failure prediction;

[0127] Supports prediction of wireless link failure terminals, frequency bands, or frequency band combinations, and also supports prediction of measurement results.

[0128] In the embodiments of the present application, the above-mentioned various prediction capabilities may be differentiated by level. For example, the prediction of a too short or ping-pong handover event is higher than the prediction of a measurement event, the prediction of a measurement event is higher than the prediction of a measurement result, the prediction of a handover failure event is higher than the prediction of a measurement event, and the prediction of a radio link failure is higher than the prediction of a measurement result.

[0129] For example, if the granularity of supported measurement event prediction is UE, the entire UE also supports prediction capabilities lower than measurement event prediction, such as measurement result prediction.

[0130] For another example, if the UE reports that it supports measurement event prediction on the frequency band bandA, the network may interpret it as the UE also supports measurement result prediction on the frequency band bandA.

[0131] For another example, if the UE reports that it supports handover failure event prediction on the frequency band combination bandA and bandB, the network may interpret it as the UE also supporting measurement event prediction and radio link failure prediction on the frequency bands bandA and bandB.

[0132] FIG5 is a schematic flow chart of a communication method 500 according to another embodiment of the present application. The method may include one or more features of the above methods 300 and 400. In one embodiment, the method further includes:

[0133] S510: The first communication device receives third information, where the third information is used to configure the mobility management-related prediction capability reported by the first communication device. For example, this step may occur after S310. After the first communication device sends the first information to the second communication device, the second communication device may send corresponding configuration information to the first communication device based on the mobility management-related prediction capability supported by the first communication device in the first information, such as one or more of the measurement amount, measurement period, number of sampling times, measurement reporting type, measurement object, and measurement task.

[0134] In one embodiment, the first communication device may be a terminal, and the second communication device may be a network device. The interaction between the network device and the terminal may be understood as a two-way selection process, so that the technical features executed by the terminal are technical features supported by both parties.

[0135] In one embodiment, the configuration granularity of the mobility management-related prediction capability includes a terminal, a measurement object, or a measurement task.

[0136] In one embodiment, the configuration granularity is that the terminal represents configuring all measurement tasks of a terminal; or

[0137] The configuration granularity is that the measurement object represents configuration of measurement tasks corresponding to all measurement task identifiers associated with one measurement object; or

[0138] The configuration granularity is that the measurement task represents the configuration of a measurement object associated with a measurement task identifier.

[0139] For example, if the configuration granularity of certain configuration information (third information) is a terminal (UE), the configuration information may be used for all measurement tasks of the UE.

[0140] For another example, if the configuration granularity of certain configuration information is measurement task, and the configuration information includes information of a specific measurement object O1, the configuration information can be used for measurement tasks corresponding to all measurement task identifiers T1, T2, and T3 associated with the measurement object O1.

[0141] For another example, if the configuration granularity of certain configuration information is a measurement object, and the configuration information includes a specific measurement task identifier T1, the configuration information can be used for measurement objects O1 and O2 associated with T1.

[0142] In one embodiment, the configuration granularity of the measurement result prediction, the measurement event prediction, the too-short-time handover event prediction, or the ping-pong handover event prediction is a terminal, a measurement object, or a measurement task.

[0143] In an embodiment of the present application, for a specific prediction capability, it can be configured according to the granularity of the terminal, measurement object or measurement task. For example, if the configuration granularity of the measurement result prediction is UE, the measurement result prediction on all measurement tasks in the UE can use the configuration information of the measurement result prediction. For another example, if the configuration granularity of the measurement event prediction is measurement object, the measurement event prediction on all measurement tasks associated with the measurement object in the UE can use the configuration information of the measurement event prediction. For another example, if the configuration granularity of the too short time switching event prediction or the ping-pong switching event prediction is measurement task, the measurement object associated with the measurement task can use the configuration information of the too short time switching event prediction or the ping-pong switching event prediction.

[0144] In one implementation, the configuration granularity of the radio link failure prediction is a measurement task in which the frequency point where the primary cell or the primary and secondary cells are located is the measurement object.

[0145] In one embodiment, the configuration granularity of handover failure prediction includes a combination of radio link failure configuration granularity and measurement event granularity. For example, if the radio link failure configuration granularity is UE and the measurement event granularity is frequency band, the configuration granularity of handover failure prediction can be UE and frequency band. The UE in the embodiments of the present application can also be replaced by a mobile device.

[0146] In one embodiment, the third information is used to configure one or more measurement event predictions, too-short-time handover event predictions, ping-pong handover event predictions, radio link failure predictions, or handover failure predictions on a measurement task.

[0147] FIG6 is a schematic flow chart of a communication method 600 according to an embodiment of the present application. The method can optionally be applied to the system shown in FIG1 , but is not limited thereto. The method includes at least part of the following contents.

[0148] S610: The second communication device receives and sends first information, where the first information is used to indicate a mobility management-related prediction capability supported by the first communication device.

[0149] In one embodiment, the mobility management-related prediction capability includes at least one of the following: measurement result prediction; measurement event prediction; and abnormal event prediction.

[0150] In one embodiment, the measurement result prediction includes at least one of the following:

[0151] L1 beam measurement result prediction;

[0152] L3 cell measurement result prediction.

[0153] In one embodiment, the L3 cell measurement result prediction includes: predicting subsequent L3 cell measurement results based on historical L1 beam measurement results, and / or predicting subsequent L3 cell measurement results based on historical L3 cell measurement results.

[0154] In one embodiment, the measurement event prediction includes: predicting the measurement event based on historical L1 beam measurement results, and / or predicting the measurement event based on historical L3 cell measurement results.

[0155] In one embodiment, the abnormal event prediction includes at least one of the following:

[0156] Wireless link failure prediction;

[0157] Handover failure prediction;

[0158] Too short a switching event prediction time;

[0159] Ping-pong switching event prediction.

[0160] FIG7 is a schematic flow chart of a communication method 700 according to another embodiment of the present application. The method may include one or more features of the above method 600. In one embodiment, the method further includes:

[0161] S710: The second communication device sends second information, where the second information is used to request the first communication device to report prediction capabilities related to mobility management.

[0162] In one embodiment, the second information includes a filtering condition requiring the first communication device to report a mobility management-related prediction capability.

[0163] In one embodiment, the filtering condition includes at least one of the following:

[0164] Requesting the first communication device to report a model supporting one or more technical features;

[0165] Require the first communication device to report a model that satisfies one or more handover scenarios;

[0166] Requesting the first communication device to report one or more supported technical features;

[0167] The one technical feature corresponds to a prediction capability related to mobility management, and a model supports the one or more technical features.

[0168] In one embodiment, the reporting granularity of the mobility management-related prediction capability includes terminal, frequency band, or frequency band combination.

[0169] In one embodiment, the reporting granularity is that the terminal indicates reporting the models and / or technical features corresponding to all frequency bands and frequency band combinations supported by the terminal; or

[0170] The reporting granularity is frequency band, indicating reporting of the model and / or technical features corresponding to a frequency band; or

[0171] The reporting granularity is a frequency band combination, which means reporting a model and / or technical features corresponding to a frequency band combination.

[0172] In one embodiment, the relationship between the predictive capabilities includes at least one of the following:

[0173] Supports the prediction of terminals, frequency bands or frequency band combinations for measurement events, as well as the prediction of measurement results;

[0174] Supports prediction of short-term handover events or ping-pong handover events for terminals, frequency bands, or frequency band combinations, as well as prediction of measurement events and / or measurement results;

[0175] Supports handover failure prediction for terminals, frequency bands, or frequency band combinations, as well as measurement event prediction and radio link failure prediction;

[0176] Supports prediction of wireless link failure terminals, frequency bands, or frequency band combinations, and also supports prediction of measurement results.

[0177] FIG8 is a schematic flow chart of a communication method 800 according to another embodiment of the present application. The method may include one or more features of the above methods 600 and 700. In one embodiment, the method further includes:

[0178] S810: The second communication device sends third information, where the third information is used to configure a prediction capability related to mobility management reported by the first communication device.

[0179] In one embodiment, the configuration granularity of the mobility management-related prediction capability includes a terminal, a measurement object, or a measurement task.

[0180] In one embodiment, the configuration granularity is that the terminal represents configuring all measurement tasks of a terminal; or

[0181] The configuration granularity is that the measurement object represents configuration of measurement tasks corresponding to all measurement task identifiers associated with one measurement object; or

[0182] The configuration granularity is that the measurement task represents the configuration of a measurement object associated with a measurement task identifier.

[0183] In one embodiment, the configuration granularity of the measurement result prediction, the measurement event prediction, the too-short-time handover event prediction, or the ping-pong handover event prediction is a terminal, a measurement object, or a measurement task.

[0184] In one implementation, the configuration granularity of the radio link failure prediction is a measurement task in which the frequency point where the primary cell or the primary and secondary cells are located is the measurement object.

[0185] In one embodiment, the configuration granularity of handover failure prediction includes a combination of radio link failure configuration granularity and measurement event granularity.

[0186] In one embodiment, the third information is used to configure one or more measurement event predictions, too-short-time handover event predictions, ping-pong handover event predictions, radio link failure predictions, or handover failure predictions on a measurement task.

[0187] For specific examples of the second communication device executing methods 600, 700, and 800 of this embodiment, reference can be made to the relevant descriptions about the second communication device in the above methods 300, 400, and 500, which will not be repeated here for the sake of brevity.

[0188] In an embodiment of the present application, the UE may report the AI / ML model capabilities for improving the mobility management (handover) function and / or performance of the cellular communication system through UE capability signaling, and the network may configure how the UE runs the AI / ML model based on the capabilities reported by the UE.

[0189] 1. Capability reporting

[0190] The AI / ML model supporting mobility management can support multiple functions (capabilities), including but not limited to at least one of the following technical features:

[0191] 1. L1 (physical layer) beam measurement result prediction function. The L1 beam measurement result is predicted based on the historical L1 beam measurement results of the cell. The predicted L1 beam measurement result is called the predicted L3 cell measurement result after merging and L3 filtering. The historical measurement result can be an actual measurement result or a historical predicted result. This applies to all relevant function descriptions below. Furthermore, the predicted L1 beam measurement result can be a time domain prediction result (for example, the actual measurement result of the past period of time is used to predict the measurement result of the future period of time, or the actual measurement result of the past period of time is used to predict the measurement result of an unmeasured time point in the past period of time), a frequency domain prediction result (for example, the unmeasured frequency band measurement result is predicted based on the actually measured frequency band), or a spatial domain prediction result (for example, the unmeasured beam / cell measurement result is predicted based on the actually measured beam / cell measurement result); the L3 cell measurement result prediction functions 1 and 2 can also make the above distinction, which will not be repeated below.

[0192] 2. L3 cell measurement result prediction function 1: directly predict the L3 cell measurement result of the cell based on the historical L1 beam measurement results of the cell.

[0193] 3. L3 cell measurement result prediction function 2: predict the L3 cell measurement result of the cell based on the historical L3 cell measurement results of the cell.

[0194] 4. Measurement event prediction function 1: predict the measurement event of the cell based on the historical L1 beam measurement results of the cell.

[0195] 5. Measurement event prediction function 2: predicts the measurement event of the cell based on the historical L3 cell measurement results of the cell.

[0196] 6. The L1 beam quality measurement results predict the failure of the serving cell radio link.

[0197] 7. Handover failure prediction: Combines measurement events and predictions of radio link failures, as well as possible other internal auxiliary information (such as UE location or movement speed) to predict whether a handover failure will occur.

[0198] 8. Too-short-time handover event prediction: predicting that after handover from source cell (A) to cell B, the time spent in cell B is less than a predefined threshold, and then the cell is quickly switched to cell C (A!=C).

[0199] 9. Ping-pong handover event prediction: predicts that after switching from source cell (A) to cell B, the time spent in cell B is less than a pre-defined threshold, and then the event of switching to cell A is quickly predicted.

[0200] An AI / ML model can support one or more of the above functions.

[0201] For example, due to hardware (computing power) or software factors (such as format, etc.), when such AI / ML models are first applied, there may be more than one model supporting the same or similar functions within the UE, which can be called AI / ML models of the same family. In order to properly manage these AI / ML models of the same family, these models can be numbered for accurate identification in signaling.

[0202] For example, these AI / ML models and the capabilities they support can be described using a table with two dimensions:

[0203] Table 2

[0204] When the UE reports UE capabilities in response to a request from the network, the UE may report the capabilities it supports according to the dimensions of the model or the dimensions of the technical features.

[0205] The network can set filtering conditions in the filter of the UE Capability Enquiry message. The following are examples:

[0206] 1. For example, the network can require the UE to report models that support certain technical features. When the UE reports the filtered models, it can also provide a brief additional description of these models, such as the handover scenarios in which these models are applicable (such as handover between macro cells, micro cells, or multi-layer cells; handover between low-speed UEs and medium-speed UEs, etc.).

[0207] 2. Alternatively, the network may require the UE to report models that meet certain handover scenarios. When the UE reports the models that meet the requirements, it may describe each model, such as which specific technical features it supports among the above technical features.

[0208] 3. Or the network simply requires the UE to report support for certain technical features, but does not provide a specific description of the model itself.

[0209] The granularity of these UE capabilities reported by the UE may be per UE, per band, or per band combination.

[0210] 2. Network Configuration

[0211] After the network obtains the aforementioned information related to the mobility AI / ML capabilities from the UE's capabilities during the initial access process, it configures how the UE uses the mobility AI / ML model based on the current network and the actual situation of the UE. An example is shown below:

[0212] 1. For RRM measurement prediction capabilities, such as L1 or L3, beam-level or cell-level prediction capabilities, the configuration granularity is per UE (e.g., all measurement objects associated with all measIDs of a UE), per MO (e.g., a measurement object (MO), and the measurement tasks corresponding to all measIDs associated with that MO), or per measurement task (i.e., measurement objects associated with a measID). These three granularities are arranged from coarse to fine.

[0213] 2. The ability to predict measurement events. The granularity range can be the same as the granularity of the RRM measurement prediction capability configuration. Since RRM measurement prediction is the basis of measurement events, or conversely, measurement event prediction is often the purpose of RRM measurement prediction, when the measurement event prediction capability is configured according to a certain granularity, the requirement for RRM measurement prediction can be implicit, so there is no need to repeatedly configure the RRM measurement prediction capability at this granularity. However, the RRM measurement prediction capability can be configured separately on the MO and / or measurement task that is not configured with the measurement event prediction capability, for different purposes such as saving UE energy consumption (replacing part of the original measurement samples or measurement results with predicted measurement results).

[0214] 3. The prediction of Radio Link Failure (RLF) or handover failure can be configured on at least one intra-frequency measurement task or measurement object of the frequency point where the primary secondary cell (PSCell) is located. PSCell is the primary cell in a cell cluster. This is because there are two bases for RLF or handover failure judgment: one is whether a radio link failure occurs in the PSCell, and the other is whether the network requires a handover command to be sent when the RLF has occurred (or the corresponding timer T310 is running). The current RLM measurement is for the PSCell. As an extension, the subsequent prediction of RLF or handover failure can also be for the Scell ​​or non-serving cell.

[0215] 4. The configuration granularity for short-duration handover event prediction or ping-pong handover event prediction can be the same as that for measurement event prediction. Given that these two prediction capabilities are based on measurement task prediction, their configuration granularity can be the same as or even finer. For example, if measurement events are configured at the MO granularity, these two events can be configured based on the measurement tasks associated with that MO.

[0216] The switching in the embodiment of the present application can also be replaced by SCG change, that is, adding or replacing the SCG without changing the MCG. The SCG change can also occur at the same time as the MCG change.

[0217] The UE of the embodiment of the present application can support reporting of AI / ML-related capabilities related to mobility, and the network can perform relevant configurations based on the received capabilities so that the AI / ML algorithm supporting mobility on the UE side can operate reasonably.

[0218] FIG9 is a schematic block diagram of a first communication device 900 according to an embodiment of the present application. The first communication device 900 may include:

[0219] The sending unit 901 is configured to send first information, where the first information is used to indicate a mobility management-related prediction capability supported by the first communication device.

[0220] In one embodiment, the mobility management-related prediction capability includes at least one of the following: measurement result prediction; measurement event prediction; and abnormal event prediction.

[0221] In one embodiment, the measurement result prediction includes at least one of the following:

[0222] L1 beam measurement result prediction;

[0223] L3 cell measurement result prediction.

[0224] In one embodiment, the L3 cell measurement result prediction includes: predicting subsequent L3 cell measurement results based on historical L1 beam measurement results, and / or predicting subsequent L3 cell measurement results based on historical L3 cell measurement results.

[0225] In one embodiment, the measurement event prediction includes: predicting the measurement event based on historical L1 beam measurement results, and / or predicting the measurement event based on historical L3 cell measurement results.

[0226] In one embodiment, the abnormal event prediction includes at least one of the following:

[0227] Wireless link failure prediction;

[0228] Handover failure prediction;

[0229] Too short a switching event prediction time;

[0230] Ping-pong switching event prediction.

[0231] In one implementation, the first communication device further includes: a receiving unit 902 .

[0232] In one implementation, the receiving unit 902 is configured to receive second information, where the second information is used to request the first communication device to report the mobility management-related prediction capability.

[0233] In one embodiment, the second information includes a filtering condition requiring the first communication device to report a mobility management-related prediction capability.

[0234] In one embodiment, the filtering condition includes at least one of the following:

[0235] Requesting the first communication device to report a model supporting one or more technical features;

[0236] Require the first communication device to report a model that satisfies one or more handover scenarios;

[0237] Requesting the first communication device to report one or more supported technical features;

[0238] The one technical feature corresponds to a prediction capability related to mobility management, and a model supports the one or more technical features.

[0239] In one embodiment, the reporting granularity of the mobility management-related prediction capability includes terminal, frequency band, or frequency band combination.

[0240] In one embodiment, the reporting granularity is that the terminal indicates reporting the models and / or technical features corresponding to all frequency bands and frequency band combinations supported by the terminal; or

[0241] The reporting granularity is frequency band, indicating reporting of the model and / or technical features corresponding to a frequency band; or

[0242] The reporting granularity is a frequency band combination, which means reporting a model and / or technical features corresponding to a frequency band combination.

[0243] In one embodiment, the relationship between the predictive capabilities includes at least one of the following:

[0244] Supports the prediction of terminals, frequency bands or frequency band combinations for measurement events, as well as the prediction of measurement results;

[0245] Supports prediction of short-term handover events or ping-pong handover events for terminals, frequency bands, or frequency band combinations, as well as prediction of measurement events and / or measurement results;

[0246] Supports handover failure prediction for terminals, frequency bands, or frequency band combinations, as well as measurement event prediction and radio link failure prediction;

[0247] Supports prediction of wireless link failure terminals, frequency bands, or frequency band combinations, and also supports prediction of measurement results.

[0248] In one implementation, the receiving unit 902 is configured to receive third information, where the third information is used to configure the mobility management-related prediction capability reported by the first communication device.

[0249] In one embodiment, the configuration granularity of the mobility management-related prediction capability includes a terminal, a measurement object, or a measurement task.

[0250] In one embodiment, the configuration granularity is that the terminal represents configuring all measurement tasks of a terminal; or

[0251] The configuration granularity is that the measurement object represents configuration of measurement tasks corresponding to all measurement task identifiers associated with one measurement object; or

[0252] The configuration granularity is that the measurement task represents the configuration of a measurement object associated with a measurement task identifier.

[0253] In one embodiment, the configuration granularity of the measurement result prediction, the measurement event prediction, the too-short-time handover event prediction, or the ping-pong handover event prediction is a terminal, a measurement object, or a measurement task.

[0254] In one implementation, the configuration granularity of the radio link failure prediction is a measurement task in which the frequency point where the primary cell or the primary and secondary cells are located is the measurement object.

[0255] In one embodiment, the configuration granularity of handover failure prediction includes a combination of radio link failure configuration granularity and measurement event granularity.

[0256] In one embodiment, the third information is used to configure one or more measurement event predictions, too-short-time handover event predictions, ping-pong handover event predictions, radio link failure predictions, or handover failure predictions on a measurement task.

[0257] The first communication device 900 of the embodiment of the present application can implement the corresponding functions of the first communication device in the aforementioned method embodiment. The processes, functions, implementation methods and beneficial effects corresponding to the various modules (sub-modules, units or components, etc.) in the first communication device 900 can be found in the corresponding descriptions in the above-mentioned method embodiments, and will not be repeated here. It should be noted that the functions described in the various modules (sub-modules, units or components, etc.) in the first communication device 900 of the embodiment of the application can be implemented by different modules (sub-modules, units or components, etc.) or by the same module (sub-module, unit or component, etc.).

[0258] FIG10 is a schematic block diagram of a second communication device 1000 according to an embodiment of the present application. The second communication device 1000 may include:

[0259] The receiving unit 1001 is configured to receive and send first information, where the first information is used to indicate a mobility management-related prediction capability supported by a first communication device.

[0260] In one embodiment, the mobility management-related prediction capability includes at least one of the following: measurement result prediction; measurement event prediction; and abnormal event prediction.

[0261] In one embodiment, the measurement result prediction includes at least one of the following:

[0262] L1 beam measurement result prediction;

[0263] L3 cell measurement result prediction.

[0264] In one embodiment, the L3 cell measurement result prediction includes: predicting subsequent L3 cell measurement results based on historical L1 beam measurement results, and / or predicting subsequent L3 cell measurement results based on historical L3 cell measurement results.

[0265] In one embodiment, the measurement event prediction includes: predicting the measurement event based on historical L1 beam measurement results, and / or predicting the measurement event based on historical L3 cell measurement results.

[0266] In one embodiment, the abnormal event prediction includes at least one of the following:

[0267] Wireless link failure prediction;

[0268] Handover failure prediction;

[0269] Too short a switching event prediction time;

[0270] Ping-pong switching event prediction.

[0271] In one implementation, the second communication device further includes: a sending unit 1002 .

[0272] In one implementation, the sending unit 1002 is configured to send second information, where the second information is used to request the first communication device to report the mobility management-related prediction capability.

[0273] In one embodiment, the second information includes a filtering condition requiring the first communication device to report a mobility management-related prediction capability.

[0274] In one embodiment, the filtering condition includes at least one of the following:

[0275] Requesting the first communication device to report a model supporting one or more technical features;

[0276] Require the first communication device to report a model that satisfies one or more handover scenarios;

[0277] Requesting the first communication device to report one or more supported technical features;

[0278] The one technical feature corresponds to a prediction capability related to mobility management, and a model supports the one or more technical features.

[0279] In one embodiment, the reporting granularity of the mobility management-related prediction capability includes terminal, frequency band, or frequency band combination.

[0280] In one embodiment, the reporting granularity is that the terminal indicates reporting the models and / or technical features corresponding to all frequency bands and frequency band combinations supported by the terminal; or

[0281] The reporting granularity is frequency band, indicating reporting of the model and / or technical features corresponding to a frequency band; or

[0282] The reporting granularity is a frequency band combination, which means reporting a model and / or technical features corresponding to a frequency band combination.

[0283] In one embodiment, the relationship between the predictive capabilities includes at least one of the following:

[0284] Supports the prediction of terminals, frequency bands or frequency band combinations for measurement events, as well as the prediction of measurement results;

[0285] Supports prediction of short-term handover events or ping-pong handover events for terminals, frequency bands, or frequency band combinations, as well as prediction of measurement events and / or measurement results;

[0286] Supports handover failure prediction for terminals, frequency bands, or frequency band combinations, as well as measurement event prediction and radio link failure prediction;

[0287] Supports prediction of wireless link failure terminals, frequency bands, or frequency band combinations, and also supports prediction of measurement results.

[0288] In one implementation, the sending unit 1002 is configured to send third information, where the third information is used to configure a mobility management-related prediction capability reported by the first communication device.

[0289] In one embodiment, the configuration granularity of the mobility management-related prediction capability includes a terminal, a measurement object, or a measurement task.

[0290] In one embodiment, the configuration granularity is that the terminal represents configuring all measurement tasks of a terminal; or

[0291] The configuration granularity is that the measurement object represents configuration of measurement tasks corresponding to all measurement task identifiers associated with one measurement object; or

[0292] The configuration granularity is that the measurement task represents the configuration of a measurement object associated with a measurement task identifier.

[0293] In one embodiment, the configuration granularity of the measurement result prediction, the measurement event prediction, the too-short-time handover event prediction, or the ping-pong handover event prediction is a terminal, a measurement object, or a measurement task.

[0294] In one implementation, the configuration granularity of the radio link failure prediction is a measurement task in which the frequency point where the primary cell or the primary and secondary cells are located is the measurement object.

[0295] In one embodiment, the configuration granularity of handover failure prediction includes a combination of radio link failure configuration granularity and measurement event granularity.

[0296] In one embodiment, the third information is used to configure one or more measurement event predictions, too-short-time handover event predictions, ping-pong handover event predictions, radio link failure predictions, or handover failure predictions on a measurement task.

[0297] The second communication device 1000 of the embodiment of the present application can implement the corresponding functions of the second communication device in the aforementioned method embodiment. The processes, functions, implementation methods and beneficial effects corresponding to the various modules (sub-modules, units or components, etc.) in the second communication device 1000 can be found in the corresponding descriptions in the above-mentioned method embodiments, and will not be repeated here. It should be noted that the functions described in the various modules (sub-modules, units or components, etc.) in the second communication device 1000 of the embodiment of the application can be implemented by different modules (sub-modules, units or components, etc.) or by the same module (sub-module, unit or component, etc.).

[0298] Figure 11 is a schematic structural diagram of a communication device 1100 according to an embodiment of the present application. The communication device 1100 includes a processor 1110, which can call and execute a computer program from a memory to enable the communication device 1100 to implement the method in the embodiment of the present application.

[0299] In one embodiment, the communication device 1100 may further include a memory 1120. The processor 1110 may call and execute a computer program from the memory 1120 to enable the communication device 1100 to implement the method in the embodiment of the present application.

[0300] The memory 1120 may be a separate device independent of the processor 1110 , or may be integrated into the processor 1110 .

[0301] In one embodiment, the communication device 1100 may further include a transceiver 1130 , and the processor 1110 may control the transceiver 1130 to communicate with other devices. Specifically, the transceiver 1130 may send information or data to other devices, or receive information or data sent by other devices.

[0302] The transceiver 1130 may include a transmitter and a receiver. The transceiver 1130 may further include an antenna, and the number of antennas may be one or more.

[0303] In one embodiment, the communication device 1100 may be the first communication device of the embodiment of the present application, and the communication device 1100 may implement the corresponding processes implemented by the first communication device in each method of the embodiment of the present application. For the sake of brevity, they will not be repeated here.

[0304] In one embodiment, the communication device 1100 may be the second communication device of the embodiment of the present application, and the communication device 1100 may implement the corresponding processes implemented by the second communication device in each method of the embodiment of the present application. For the sake of brevity, they will not be repeated here.

[0305] 7 is a schematic structural diagram of a chip 700 according to an embodiment of the present application. The chip 700 includes a processor 710, which can call and execute a computer program from a memory to implement the method according to the embodiment of the present application.

[0306] In one embodiment, the chip 700 may further include a memory 720. The processor 710 may call and execute a computer program from the memory 720 to implement the method executed by the terminal device or the network device in the embodiment of the present application.

[0307] The memory 720 may be a separate device independent of the processor 710 , or may be integrated into the processor 710 .

[0308] In one embodiment, the chip 700 may further include an input interface 730. The processor 710 may control the input interface 730 to communicate with other devices or chips, and specifically, may obtain information or data sent by other devices or chips.

[0309] In one embodiment, the chip 700 may further include an output interface 740. The processor 710 may control the output interface 740 to communicate with other devices or chips, and specifically, may output information or data to other devices or chips.

[0310] In one embodiment, the chip can be applied to the first communication device in the embodiment of the present application, and the chip can implement the corresponding processes implemented by the first communication device in each method of the embodiment of the present application. For the sake of brevity, it will not be repeated here.

[0311] In one embodiment, the chip can be applied to the second communication device in the embodiment of the present application, and the chip can implement the corresponding processes implemented by the second communication device in each method of the embodiment of the present application. For the sake of brevity, it will not be repeated here.

[0312] The chips used in the first communication device and the second communication device may be the same chip or different chips.

[0313] It should be understood that the chip mentioned in the embodiments of the present application can also be called a system-level chip, a system chip, a chip system or a system-on-chip chip, etc.

[0314] The processor mentioned above may be a general-purpose processor, a digital signal processor (DSP), a field programmable gate array (FPGA), an application specific integrated circuit (ASIC), or other programmable logic devices, transistor logic devices, discrete hardware components, etc. The general-purpose processor mentioned above may be a microprocessor or any conventional processor, etc.

[0315] The memory mentioned above may be a volatile memory or a non-volatile memory, or may include both volatile and non-volatile memories. The non-volatile memory may be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or a flash memory. The volatile memory may be a random access memory (RAM).

[0316] It should be understood that the above-mentioned memories are exemplary but not restrictive. For example, the memories in the embodiments of the present application may also be static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link dynamic random access memory (SLDRAM), and direct RAM RAM (DR RAM), etc. In other words, the memories in the embodiments of the present application are intended to include, but are not limited to, these and any other suitable types of memories.

[0317] FIG13 is a schematic block diagram of a communication system 1300 according to an embodiment of the present application. The communication system 1300 includes a first communication device 1310 and a second communication device 1320 .

[0318] The first communication device 1310 is configured to send first information, where the first information is used to indicate a prediction capability related to mobility management supported by the first communication device.

[0319] The second communication device 1320 is configured to receive and send first information.

[0320] The first communication device 1310 can be used to implement the corresponding functions implemented by the first communication device in the above method, and the second communication device 1320 can be used to implement the corresponding functions implemented by the second communication device in the above method. For the sake of brevity, they are not described here in detail.

[0321] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When software is used for implementation, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function in accordance with the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from a website, computer, server or data center by wired (such as coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (such as infrared, wireless, microwave, etc.) mode to another website, computer, server or data center. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more available media integrations. The available medium may be a magnetic medium (eg, a floppy disk, a hard disk, a magnetic tape), an optical medium (eg, a DVD), or a semiconductor medium (eg, a solid state disk (SSD)).

[0322] It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0323] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0324] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any modifications or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in the present application should be included within the scope of protection of the present application. Therefore, the scope of protection of the present application should be based on the scope of protection of the claims.

Claims

1. A communication method, comprising: A first communication device sends first information, where the first information is used to indicate a mobility management-related prediction capability supported by the first communication device.

2. The method according to claim 1, wherein The prediction capability related to mobility management includes at least one of the following: measurement result prediction; measurement event prediction; abnormal event prediction.

3. The method according to claim 2, wherein: The measurement result prediction includes at least one of the following: Layer 1 L1 beam measurement result prediction; Layer 3 L3 cell measurement result prediction.

4. The method according to claim 3, wherein: The L3 cell measurement result prediction includes: predicting subsequent L3 cell measurement results based on historical L1 beam measurement results, and / or predicting subsequent L3 cell measurement results based on historical L3 cell measurement results.

5. The method according to claim 2, wherein: The measurement event prediction includes: predicting the measurement event according to historical L1 beam measurement results, and / or predicting the measurement event according to historical L3 cell measurement results.

6. The method according to claim 2, wherein: The abnormal event prediction includes at least one of the following: Wireless link failure prediction; Handover failure prediction; Too short a switching event prediction time; Ping-pong switching event prediction.

7. The method according to any one of claims 1 to 6, wherein The method further comprises: The first communication device receives second information, where the second information is used to request the first communication device to report the mobility management-related prediction capability.

8. The method according to claim 7, wherein: The second information includes a filtering condition requiring the first communication device to report a mobility management-related prediction capability.

9. The method according to claim 8, wherein The filtering condition includes at least one of the following: Require the first communication device to report a model that supports one or more technical features; Require the first communication device to report a model that satisfies one or more handover scenarios; Requesting the first communication device to report one or more supported technical features; Among them, one technical feature corresponds to a prediction capability related to mobility management, and one model supports one or more technical features.

10. The method according to any one of claims 1 to 9, wherein The reporting granularity of the mobility management-related prediction capability includes terminal, frequency band or frequency band combination.

11. The method according to claim 10, wherein: The reporting granularity is that the terminal indicates reporting of models and / or technical features corresponding to all frequency bands and frequency band combinations supported by the terminal; or The reporting granularity is frequency band, indicating reporting of the model and / or technical features corresponding to a frequency band; or The reporting granularity is a frequency band combination, which means reporting a model and / or technical features corresponding to a frequency band combination.

12. The method according to claim 10 or 11, wherein: The relationship between predictive abilities includes at least one of the following: Supports the prediction of terminals, frequency bands or frequency band combinations for measurement events, as well as the prediction of measurement results; Supports prediction of short-term handover events or ping-pong handover events for terminals, frequency bands, or frequency band combinations, as well as prediction of measurement events and / or measurement results; Supports handover failure prediction for terminals, frequency bands, or frequency band combinations, as well as measurement event prediction and radio link failure prediction; Supports prediction of wireless link failure terminals, frequency bands, or frequency band combinations, and also supports prediction of measurement results.

13. The method according to any one of claims 1 to 12, wherein The method further comprises: The first communication device receives third information, where the third information is used to configure a prediction capability related to mobility management reported by the first communication device.

14. The method according to claim 13, wherein The configuration granularity of the mobility management-related prediction capability includes a terminal, a measurement object, or a measurement task.

15. The method according to claim 14, wherein The configuration granularity is terminal, which means configuring all measurement tasks of a terminal; or The configuration granularity is that the measurement object represents configuration of measurement tasks corresponding to all measurement task identifiers associated with one measurement object; or The configuration granularity is that the measurement task represents configuring a measurement object associated with a measurement task identifier.

16. The method according to claim 14 or 15, wherein: The configuration granularity of the measurement result prediction, measurement event prediction, too-short-time handover event prediction, or ping-pong handover event prediction is terminal, measurement object, or measurement task.

17. The method according to claim 14 or 15, wherein: The configuration granularity of the radio link failure prediction is a measurement task in which the frequency point where the primary cell or the primary and secondary cells are located is the measurement object.

18. The method according to claim 14 or 15, wherein The configuration granularity of handover failure prediction includes a combination of radio link failure configuration granularity and measurement event granularity.

19. The method according to any one of claims 16 to 18, wherein The third information is used to configure one or more measurement event predictions, too-short-time handover event predictions, ping-pong handover event predictions, radio link failure predictions, or handover failure predictions on a measurement task.

20. A communication method, comprising: The second communication device receives and sends first information, where the first information is used to indicate a prediction capability related to mobility management supported by the first communication device.

21. The method according to claim 20, wherein The prediction capability related to mobility management includes at least one of the following: measurement result prediction; measurement event prediction; abnormal event prediction.

22. The method according to claim 21, wherein The measurement result prediction includes at least one of the following: L1 beam measurement result prediction; L3 cell measurement result prediction.

23. The method according to claim 22, wherein The L3 cell measurement result prediction includes: predicting subsequent L3 cell measurement results based on historical L1 beam measurement results, and / or predicting subsequent L3 cell measurement results based on historical L3 cell measurement results.

24. The method according to claim 20, wherein The measurement event prediction includes: predicting the measurement event according to historical L1 beam measurement results, and / or predicting the measurement event according to historical L3 cell measurement results.

25. The method according to claim 20, wherein The abnormal event prediction includes at least one of the following: Wireless link failure prediction; Handover failure prediction; Too short a switching event prediction time; Ping-pong switching event prediction.

26. The method according to any one of claims 20 to 25, wherein The method further comprises: The second communication device sends second information, where the second information is used to request the first communication device to report the mobility management-related prediction capability.

27. The method according to claim 26, wherein The second information includes a filtering condition requiring the first communication device to report a mobility management-related prediction capability.

28. The method according to claim 27, wherein The filtering condition includes at least one of the following: Require the first communication device to report a model that supports one or more technical features; Require the first communication device to report a model that satisfies one or more handover scenarios; Requesting the first communication device to report one or more supported technical features; Among them, one technical feature corresponds to a prediction capability related to mobility management, and one model supports one or more technical features.

29. The method according to any one of claims 20 to 28, wherein The reporting granularity of the mobility management-related prediction capability includes terminal, frequency band or frequency band combination.

30. The method according to claim 29, wherein The reporting granularity is that the terminal indicates reporting of models and / or technical features corresponding to all frequency bands and frequency band combinations supported by the terminal; or The reporting granularity is frequency band, indicating reporting of the model and / or technical features corresponding to a frequency band; or The reporting granularity is a frequency band combination, which means reporting a model and / or technical features corresponding to a frequency band combination.

31. The method according to claim 29 or 30, wherein The relationship between predictive abilities includes at least one of the following: Supports the prediction of terminals, frequency bands or frequency band combinations for measurement events, as well as the prediction of measurement results; Supports prediction of short-term handover events or ping-pong handover events for terminals, frequency bands, or frequency band combinations, as well as prediction of measurement events and / or measurement results; Supports handover failure prediction for terminals, frequency bands, or frequency band combinations, as well as measurement event prediction and radio link failure prediction; Supports prediction of wireless link failure terminals, frequency bands, or frequency band combinations, and also supports prediction of measurement results.

32. The method according to any one of claims 20 to 31, wherein The method further comprises: The second communication device sends third information, where the third information is used to configure a prediction capability related to mobility management reported by the first communication device.

33. The method according to claim 32, wherein The configuration granularity of the mobility management-related prediction capability includes a terminal, a measurement object, or a measurement task.

34. The method according to claim 33, wherein The configuration granularity is terminal, which means configuring all measurement tasks of a terminal; or The configuration granularity is that the measurement object represents configuration of measurement tasks corresponding to all measurement task identifiers associated with one measurement object; or The configuration granularity is that the measurement task represents configuring a measurement object associated with a measurement task identifier.

35. The method according to claim 33 or 34, wherein The configuration granularity of the measurement result prediction, measurement event prediction, too-short-time handover event prediction, or ping-pong handover event prediction is terminal, measurement object, or measurement task.

36. The method according to claim 33 or 34, wherein The configuration granularity of the radio link failure prediction is a measurement task in which the frequency point where the primary cell or the primary and secondary cells are located is the measurement object.

37. The method according to claim 33 or 34, wherein The configuration granularity of handover failure prediction includes a combination of radio link failure configuration granularity and measurement event granularity.

38. The method according to any one of claims 35 to 36, wherein The third information is used to configure one or more measurement event predictions, too-short-time handover event predictions, ping-pong handover event predictions, radio link failure predictions, or handover failure predictions on a measurement task.

39. A first communication device, comprising: A sending unit is used to send first information, where the first information is used to indicate a mobility management-related prediction capability supported by the first communication device.

40. The first communication device according to claim 39, wherein The prediction capability related to mobility management includes at least one of the following: measurement result prediction; measurement event prediction; abnormal event prediction.

41. The first communication device according to claim 40, wherein: The measurement result prediction includes at least one of the following: L1 beam measurement result prediction; L3 cell measurement result prediction.

42. The first communication device according to claim 41, wherein The L3 cell measurement result prediction includes: predicting subsequent L3 cell measurement results based on historical L1 beam measurement results, and / or predicting subsequent L3 cell measurement results based on historical L3 cell measurement results.

43. The first communication device according to claim 40, wherein: The measurement event prediction includes: predicting the measurement event according to historical L1 beam measurement results, and / or predicting the measurement event according to historical L3 cell measurement results.

44. The first communication device according to claim 40, wherein The abnormal event prediction includes at least one of the following: Wireless link failure prediction; Handover failure prediction; Too short a switching event prediction time; Ping-pong switching event prediction.

45. The first communication device according to any one of claims 39 to 44, wherein: The first communication device further includes: The receiving unit is configured to receive second information, where the second information is used to request the first communication device to report the mobility management-related prediction capability.

46. ​​The first communication device according to claim 45, wherein The second information includes a filtering condition requiring the first communication device to report a mobility management-related prediction capability.

47. The first communication device according to claim 46, wherein The filtering condition includes at least one of the following: Require the first communication device to report a model that supports one or more technical features; Require the first communication device to report a model that satisfies one or more handover scenarios; Requesting the first communication device to report one or more supported technical features; Among them, one technical feature corresponds to a prediction capability related to mobility management, and one model supports one or more technical features.

48. The first communication device according to any one of claims 39 to 47, wherein: The reporting granularity of the mobility management-related prediction capability includes terminal, frequency band or frequency band combination.

49. The first communication device according to claim 48, wherein The reporting granularity is that the terminal indicates reporting of models and / or technical features corresponding to all frequency bands and frequency band combinations supported by the terminal; or The reporting granularity is frequency band, indicating reporting of the model and / or technical features corresponding to a frequency band; or The reporting granularity is a frequency band combination, which means reporting a model and / or technical features corresponding to a frequency band combination.

50. The first communication device according to claim 48 or 49, wherein: The relationship between predictive abilities includes at least one of the following: Supports the prediction of terminals, frequency bands or frequency band combinations for measurement events, as well as the prediction of measurement results; Supports short-time handover event prediction or ping-pong handover event prediction terminal, frequency band or frequency band combination, and also supports measurement event prediction and and / or prediction of measurement results; Supports handover failure prediction for terminals, frequency bands, or frequency band combinations, as well as measurement event prediction and radio link failure prediction; Supports prediction of wireless link failure terminals, frequency bands, or frequency band combinations, and also supports prediction of measurement results.

51. The first communication device according to any one of claims 39 to 50, wherein: The first communication device further includes: The receiving unit is configured to receive third information, where the third information is used to configure the prediction capability related to mobility management reported by the first communication device.

52. The first communication device according to claim 51, wherein The configuration granularity of the mobility management-related prediction capability includes a terminal, a measurement object, or a measurement task.

53. The first communication device according to claim 52, wherein: The configuration granularity is terminal, which means configuring all measurement tasks of a terminal; or The configuration granularity is that the measurement object represents configuration of measurement tasks corresponding to all measurement task identifiers associated with one measurement object; or The configuration granularity is that the measurement task represents configuring a measurement object associated with a measurement task identifier.

54. The first communication device according to claim 52 or 53, wherein: The configuration granularity of the measurement result prediction, measurement event prediction, too-short-time handover event prediction, or ping-pong handover event prediction is terminal, measurement object, or measurement task.

55. The first communication device according to claim 52 or 53, wherein: The configuration granularity of the radio link failure prediction is a measurement task in which the frequency point where the primary cell or the primary and secondary cells are located is the measurement object.

56. The first communication device according to claim 52 or 53, wherein: The configuration granularity of handover failure prediction includes a combination of radio link failure configuration granularity and measurement event granularity.

57. The first communication device according to any one of claims 54 to 56, wherein: The third information is used to configure one or more measurement event predictions, too-short-time handover event predictions, ping-pong handover event predictions, radio link failure predictions, or handover failure predictions on a measurement task.

58. A second communication device, comprising: The receiving unit is configured to receive and send first information, where the first information is used to indicate a mobility management-related prediction capability supported by the first communication device.

59. The second communication device according to claim 58, wherein The prediction capability related to mobility management includes at least one of the following: measurement result prediction; measurement event prediction; abnormal event prediction.

60. The second communication device according to claim 59, wherein The measurement result prediction includes at least one of the following: L1 beam measurement result prediction; L3 cell measurement result prediction.

61. The second communication device according to claim 60, wherein The L3 cell measurement result prediction includes: predicting subsequent L3 cell measurement results based on historical L1 beam measurement results, and / or predicting subsequent L3 cell measurement results based on historical L3 cell measurement results.

62. The second communication device according to claim 58, wherein The measurement event prediction includes: predicting the measurement event according to historical L1 beam measurement results, and / or predicting the measurement event according to historical L3 cell measurement results.

63. The second communication device according to claim 58, wherein The abnormal event prediction includes at least one of the following: Wireless link failure prediction; Handover failure prediction; Too short a switching event prediction time; Ping-pong switching event prediction.

64. The second communication device according to any one of claims 58 to 64, wherein: The second communication device further includes: The sending unit is configured to send second information, where the second information is used to request the first communication device to report the mobility management-related prediction capability.

65. The second communication device according to claim 64, wherein The second information includes a filtering condition requiring the first communication device to report a mobility management-related prediction capability.

66. The second communication device according to claim 65, wherein The filtering condition includes at least one of the following: Require the first communication device to report a model that supports one or more technical features; Require the first communication device to report a model that satisfies one or more handover scenarios; Requesting the first communication device to report one or more supported technical features; Among them, one technical feature corresponds to a prediction capability related to mobility management, and one model supports one or more technical features.

67. The second communication device according to any one of claims 58 to 66, wherein: The reporting granularity of the mobility management-related prediction capability includes terminal, frequency band or frequency band combination.

68. The second communication device according to claim 67, wherein The reporting granularity is that the terminal indicates reporting of models and / or technical features corresponding to all frequency bands and frequency band combinations supported by the terminal; or The reporting granularity is frequency band, indicating reporting of the model and / or technical features corresponding to a frequency band; or The reporting granularity is a frequency band combination, which means reporting a model and / or technical features corresponding to a frequency band combination.

69. The method according to claim 67 or 68, wherein The relationship between predictive abilities includes at least one of the following: Supports the prediction of terminals, frequency bands or frequency band combinations for measurement events, as well as the prediction of measurement results; Supports prediction of short-term handover events or ping-pong handover events for terminals, frequency bands, or frequency band combinations, as well as prediction of measurement events and / or measurement results; Supports handover failure prediction for terminals, frequency bands, or frequency band combinations, as well as measurement event prediction and radio link failure prediction; Supports prediction of wireless link failure terminals, frequency bands, or frequency band combinations, and also supports prediction of measurement results.

70. The second communication device according to any one of claims 58 to 69, wherein: The second communication device further includes: The sending unit is configured to send third information, where the third information is used to configure the prediction capability related to mobility management reported by the first communication device.

71. The second communication device according to claim 70, wherein: The configuration granularity of the mobility management-related prediction capability includes a terminal, a measurement object, or a measurement task.

72. The second communication device according to claim 71, wherein The configuration granularity is terminal, which means configuring all measurement tasks of a terminal; or The configuration granularity is that the measurement object represents configuration of measurement tasks corresponding to all measurement task identifiers associated with one measurement object; or The configuration granularity is that the measurement task represents configuring a measurement object associated with a measurement task identifier.

73. The second communication device according to claim 71 or 72, wherein: The configuration granularity of the measurement result prediction, measurement event prediction, too-short-time handover event prediction, or ping-pong handover event prediction is terminal, measurement object, or measurement task.

74. The second communication device according to claim 71 or 72, wherein: The configuration granularity of the radio link failure prediction is a measurement task in which the frequency point where the primary cell or the primary and secondary cells are located is the measurement object.

75. The second communication device according to claim 71 or 72, wherein: The configuration granularity of handover failure prediction includes a combination of radio link failure configuration granularity and measurement event granularity.

76. The second communication device according to any one of claims 73 to 74, wherein: The third information is used to configure one or more measurement event predictions, too-short-time handover event predictions, ping-pong handover event predictions, radio link failure predictions, or handover failure predictions on a measurement task.

77. A communication device comprising: A transceiver, a processor, and a memory, wherein the memory is used to store a computer program, the transceiver is used to communicate with other devices, and the processor is used to call and run the computer program stored in the memory to enable the communication device to perform the method according to any one of claims 1 to 19 or any one of claims 20 to 38.

78. A chip comprising: A processor, configured to call and run a computer program from a memory, so that a device equipped with the chip executes a method as claimed in any one of claims 1 to 19 or any one of claims 20 to 38.

79. A computer-readable storage medium for storing a computer program, which, when executed by a device, causes the device to perform the method according to any one of claims 1 to 19 or any one of claims 20 to 38.

80. A computer program product comprising computer program instructions for causing a computer to perform the method of any one of claims 1 to 19 or any one of 20 to 38.

81. A computer program causing a computer to perform the method of any one of claims 1 to 19 or any one of 20 to 38.

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