Communication method, communication apparatus, terminal, and storage medium

Abstract

The present application relates to a communication method, a communication apparatus, a terminal, and a storage medium. The communication method comprises: determining a measurement period on the basis of a first capability of a terminal, the first capability being a time domain prediction capability of the terminal. By means of the embodiments of the present application, the measurement period can be shortened or the transmission of measurement resources can be reduced.

Description

Communication method, communication apparatus, terminal, and storage medium TECHNICAL FIELD

[0001] The present disclosure relates to the technical field of communication, and particularly relates to a communication method, a communication apparatus, a terminal and a storage medium. BACKGROUND

[0002] Radio Resource Management (RRM) measurement procedures are essential to maintain the performance and reliability of mobile networks. To facilitate RRM measurements by terminals, network equipment transmits various types of reference signals, representing a significant system overhead that simultaneously consumes radio resources and network energy. In non-artificial intelligence (AI) based RRM measurements, a terminal first measures a plurality of layer 1 (L1) samples based on the reference signals. These L1 samples are then filtered by layer 1. Then, the terminal reports the filtered L1 results to a higher layer (L3). The higher layer further applies layer 3 filtering for cell quality measurements.

[0003] SUMMARY

[0004] How to determine a measurement period in the case that a terminal has a time domain prediction capability is a problem to be solved.

[0005] Embodiments of the present disclosure provide a communication method, a communication apparatus, a terminal and a storage medium.

[0006] According to a first aspect of embodiments of the present disclosure, a communication method is provided, comprising: determining a measurement period based on a first capability of a terminal, wherein the measurement period comprises a layer 1 measurement period and / or a layer 3 measurement period, the first capability is a prediction capability of the terminal in a time domain, and the measurement period is a period for the terminal to perform measurement.

[0007] According to a second aspect of embodiments of the present disclosure, a communication apparatus is provided, comprising: a processing module configured to determine a measurement period based on a first capability of a terminal, wherein the measurement period comprises a layer 1 measurement period and / or a layer 3 measurement period, the first capability is a prediction capability of the terminal in a time domain, and the measurement period is a period for the terminal to perform measurement.

[0008] According to a third aspect of embodiments of the present disclosure, a terminal is provided, comprising: one or more processors; and wherein the terminal is configured to perform the communication method of the first aspect.

[0009] According to a fourth aspect of the embodiments of the present disclosure, a storage medium is provided, which stores instructions, when the instructions are executed on a communication device, causing the communication device to perform the method of the first aspect.

[0010] According to a fifth aspect of the embodiments of the present disclosure, a computer program is provided, which, when executed by a communication device, causes the communication device to perform the method of the first aspect.

[0011] By the embodiments of the present disclosure, the measurement period is determined based on the time domain prediction capability of the terminal. Since the terminal has the time domain prediction capability, the terminal can omit the measurement on part of the samples and use the AI model for prediction. Therefore, the measurement period is determined based on the time domain prediction capability of the terminal, which can shorten the measurement time, thereby saving communication resources and improving communication efficiency. BRIEF DESCRIPTION OF DRAWINGS

[0012] In order to more clearly illustrate the technical solutions in the embodiments of the present disclosure, the following describes the drawings required for the embodiments, and the following drawings are only some embodiments of the present disclosure, which do not specifically limit the protection scope of the present disclosure.

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

[0014] FIG. 2 is a flow schematic diagram of a communication method according to an embodiment of the present disclosure.

[0015] FIG. 3 is a flow schematic diagram of a communication method according to an embodiment of the present disclosure.

[0016] FIG. 4 is a structural schematic diagram of a communication device according to an embodiment of the present disclosure.

[0017] FIG. 5A is a structural schematic diagram of a communication device according to an embodiment of the present disclosure.

[0018] FIG. 5B is a structural schematic diagram of a chip according to an embodiment of the present disclosure. DETAILED DESCRIPTION

[0019] The embodiments of the present disclosure provide a communication method, a communication device, a terminal and a storage medium.

[0020] In a first aspect, the embodiments of the present disclosure provide a communication method, comprising: determining a measurement period based on a first capability of a terminal, wherein the measurement period comprises a layer 1 measurement period and / or a layer 3 measurement period, the first capability is a prediction capability of the terminal in a time domain, the measurement period is a period for the terminal to perform measurement, and the prediction capability is a capability of predicting based on measurement.

[0021] In the above embodiments, the measurement period is determined based on the time domain prediction capability of the terminal; since the terminal has the time domain prediction capability, the terminal can omit the measurement on part of the samples, and use the AI model to make a prediction, thereby, the measurement period is determined based on the time domain prediction capability of the terminal, the measurement time can be shortened, thereby saving communication resources and improving communication efficiency.

[0022] In some embodiments of the first aspect, in some embodiments, the first capability comprises a capability of predicting Q layer 1 measurement samples based on P layer 1 measurement samples, P and Q are both positive integers; and the measurement period comprises a layer 1 measurement period corresponding to a first frequency range, and the measurement period is determined based on a first ratio, the first ratio being a ratio of P to (P+Q).

[0023] In some embodiments of the first aspect, in some embodiments, the first capability comprises a capability of predicting 1 filtered layer 1 measurement result based on P layer 1 measurement samples, P being a positive integer; and the measurement period comprises a layer 1 measurement period corresponding to a first frequency range, and the measurement period is determined based on the P.

[0024] In some embodiments of the first aspect, in some embodiments, the first capability comprises a capability of predicting 1 filtered layer 1 measurement result based on K filtered layer 1 measurement results, K being a positive integer; and the measurement period comprises a layer 3 measurement period corresponding to a second frequency range, and the measurement period is determined based on the K.

[0025] In some embodiments of the first aspect, in some embodiments, the first capability comprises a capability of predicting Q layer 1 measurement samples based on P layer 1 measurement samples, P and Q being both positive integers; and the measurement period comprises a layer 1 measurement period corresponding to full receive beam sweeping in a second frequency range, and the measurement period is determined based on a first ratio, the first ratio being a ratio of P to (P+Q).

[0026] In some embodiments of the first aspect, in some embodiments, the first capability comprises a capability of predicting 1 filtered layer 1 measurement result based on P layer 1 measurement samples, P being a positive integer; and the measurement period comprises a layer 1 measurement period corresponding to full receive beam sweeping in a second frequency range, and the measurement period is determined based on the P.

[0027] In some embodiments of the first aspect, in some embodiments, the first capability comprises a capability of predicting 1 filtered layer 1 measurement result based on K filtered layer 1 measurement results, K being a positive integer; and the measurement period comprises a layer 3 measurement period corresponding to full receive beam sweeping in a second frequency range, and the measurement period is determined based on the K.

[0028] In some embodiments of the first aspect, in some embodiments, the first capability comprises a capability of predicting Q layer 1 measurement samples based on P layer 1 measurement samples, P and Q are both positive integers; the measurement period comprises a layer 1 measurement period corresponding to a specific receive beam sweeping in the second frequency range, the measurement period is determined based on a first ratio and a second ratio, the first ratio is a ratio of P and (P+Q), the second ratio is a ratio of F and G, F is a number of specific receive beams, G is a number of all receive beams, F and G are both positive integers.

[0029] In some embodiments of the first aspect, in some embodiments, the first capability comprises a capability of predicting 1 filtered layer 1 measurement result based on P layer 1 measurement samples, P is a positive integer; the measurement period comprises a layer 1 measurement period corresponding to a specific receive beam sweeping in the second frequency range, the measurement period is determined based on the P and a second ratio, the second ratio is a ratio of F and G, F is a number of specific receive beams, G is a number of all receive beams, F and G are both positive integers.

[0030] In some embodiments of the first aspect, in some embodiments, the first capability comprises a capability of predicting 1 filtered layer 1 measurement result based on K filtered layer 1 measurement results, K is a positive integer; the measurement period comprises a layer 3 measurement period corresponding to a specific receive beam sweeping in the second frequency range, the measurement period is determined based on the K and a second ratio, the second ratio is a ratio of F and G, F is a number of specific receive beams, G is a number of all receive beams, F and G are both positive integers.

[0031] In the second aspect, the embodiments of the present disclosure provide a communication apparatus, comprising: a processing module configured to determine a measurement period based on a first capability of a terminal, wherein the measurement period comprises a layer 1 measurement period and / or a layer 3 measurement period, the first capability is a prediction capability of the terminal in a time domain, and the measurement period is a period for the terminal to perform measurement.

[0032] In some embodiments of the second aspect, in some embodiments, the first capability comprises a capability of predicting Q layer 1 measurement samples based on P layer 1 measurement samples, P and Q are both positive integers; the measurement period comprises a layer 1 measurement period corresponding to a first frequency range, the measurement period is determined based on a first ratio, and the first ratio is a ratio of P and (P+Q).

[0033] In some embodiments of the second aspect, in some embodiments, the first capability comprises a capability of predicting one filtered layer 1 measurement result based on P layer 1 measurement samples, P being a positive integer; and the measurement period comprises a layer 1 measurement period corresponding to the first frequency range, the measurement period being determined based on the P.

[0034] In some embodiments of the second aspect, in some embodiments, the first capability comprises a capability of predicting one filtered layer 1 measurement result based on K filtered layer 1 measurement results, K being a positive integer; and the measurement period comprises a layer 3 measurement period corresponding to the first frequency range, the measurement period being determined based on the K.

[0035] In some embodiments of the second aspect, in some embodiments, the first capability comprises a capability of predicting Q layer 1 measurement samples based on P layer 1 measurement samples, P and Q both being positive integers; and the measurement period comprises a layer 1 measurement period corresponding to full receive beam sweeping in the second frequency range, the measurement period being determined based on a first ratio, the first ratio being a ratio of the P to (P+Q).

[0036] In some embodiments of the second aspect, in some embodiments, the first capability comprises a capability of predicting one filtered layer 1 measurement result based on P layer 1 measurement samples, P being a positive integer; and the measurement period comprises a layer 1 measurement period corresponding to full receive beam sweeping in the second frequency range, the measurement period being determined based on the P.

[0037] In some embodiments of the second aspect, in some embodiments, the first capability comprises a capability of predicting one filtered layer 1 measurement result based on K filtered layer 1 measurement results, K being a positive integer; and the measurement period comprises a layer 3 measurement period corresponding to full receive beam sweeping in the second frequency range, the measurement period being determined based on the K.

[0038] In some embodiments of the second aspect, in some embodiments, the first capability comprises a capability of predicting Q layer 1 measurement samples based on P layer 1 measurement samples, P and Q both being positive integers; and the measurement period comprises a layer 1 measurement period corresponding to specific receive beam sweeping in the second frequency range, the measurement period being determined based on a first ratio and a second ratio, the first ratio being a ratio of the P to (P+Q), the second ratio being a ratio of F to G, F and G both being positive integers, the F being a number of specific receive beams, the G being a number of total receive beams.

[0039] In some embodiments of the second aspect, in some embodiments, the first capability comprises a capability of predicting one filtered layer 1 measurement result based on P layer 1 measurement samples, P being a positive integer; and the measurement period comprises a layer 1 measurement period corresponding to performing specific receive beam sweeping in the second frequency range, the measurement period being determined based on the P and a second ratio, the second ratio being a ratio of F and G, F being a number of specific receive beams, and G being a number of all receive beams, F and G being positive integers.

[0040] In some embodiments of the second aspect, in some embodiments, the first capability comprises a capability of predicting one filtered layer 1 measurement result based on P layer 1 measurement samples, P being a positive integer; and the measurement period comprises a layer 1 measurement period corresponding to performing specific receive beam sweeping in the second frequency range, the measurement period being determined based on the P and a second ratio, the second ratio being a ratio of F and G, F being a number of specific receive beams, and G being a number of all receive beams, F and G being positive integers.

[0041] In a third aspect, an embodiment of the present disclosure provides a terminal, comprising: one or more processors; wherein the terminal is configured to perform the communication method of the first aspect.

[0042] In a fourth aspect, an embodiment of the present disclosure provides a storage medium, the storage medium storing instructions, when the instructions are executed on a communication device, causing the communication device to perform any of the above communication methods.

[0043] In a fifth aspect, an embodiment of the present disclosure provides a program product, when the program product is executed on a communication device, causing the communication device to perform any of the above communication methods.

[0044] In a sixth aspect, an embodiment of the present disclosure provides a computer program, when the computer program is executed on a communication device, causing the communication device to perform any of the above communication methods.

[0045] In a seventh aspect, an embodiment of the present disclosure provides a chip or chip system. The chip or chip system comprises processing circuitry configured to perform any of the above communication methods.

[0046] It can be understood that the above communication device, storage medium, program product, computer program, chip or chip system are all used to perform the method proposed in the embodiments of the present disclosure. Therefore, the beneficial effects they can achieve can refer to the beneficial effects in the corresponding method, which will not be repeated here.

[0047] The embodiments of the present disclosure propose a communication method, a communication apparatus, a terminal and a storage medium. In some embodiments, the communication method and the information processing method, the information sending method, the information receiving method and the like can be replaced with each other.

[0048] The embodiments of the present disclosure are not exhaustive, but only illustrate some embodiments, and are not specific limitations on the protection scope of the present disclosure. In the case of no contradiction, each step in an embodiment can be implemented as an independent embodiment, and the steps can be combined arbitrarily, for example, the scheme after removing part of the steps in an embodiment can also be implemented as an independent embodiment, and the order of the steps in an embodiment can be exchanged arbitrarily, in addition, the optional implementation in an embodiment can be combined arbitrarily; in addition, the embodiments can be combined arbitrarily, for example, part or all of the steps of different embodiments can be combined arbitrarily, an embodiment can be combined with the optional implementation of other embodiments arbitrarily.

[0049] In each embodiment of the present disclosure, the terms and / or descriptions between the embodiments are consistent if there is no special description and logical conflict, and can be referred to each other, and the technical features in different embodiments can be combined to form a new embodiment according to their inherent logical relationship.

[0050] The terms used in the embodiments of the present disclosure are only for the purpose of describing the specific embodiments, and not as a limitation on the present disclosure.

[0051] In the embodiments of the present disclosure, unless otherwise specified, the elements expressed in singular form, such as "one", "a", "the", "above", "said", "preceding", "this" and the like, can represent "one and only one", and can also represent "one or more", "at least one" and the like. For example, in the case of using articles such as "a", "an", "the" and the like in English, the noun after the article can be understood as singular expression, and can also be understood as plural expression.

[0052] In the embodiments of the present disclosure, "plurality" means two or more.

[0053] In some embodiments, the terms "at least one of", "one or more", "a plurality of", "multiple" and the like can be replaced with each other.

[0054] In some embodiments, "at least one of A, B", "A and / or B", "in one case A, in another case B", "responsive to case A, responsive to case B" and the like, can be interpreted to include both cases, A and B, in some embodiments, A (A is performed regardless of B), in some embodiments, B (B is performed regardless of A), in some embodiments, selected from the group consisting of A and B (the selection between A and B is an option), in some embodiments, A and B (both A and B are performed).

[0055] In some embodiments, "A or B" and the like, can be interpreted to include both cases, A and B, in some embodiments, A (A is performed regardless of B), in some embodiments, B (B is performed regardless of A), in some embodiments, selected from the group consisting of A and B (the selection between A and B is an option).

[0056] In some embodiments, the prefix words "first", "second" and the like in the disclosure do not limit the position, order, priority, number or content of the described objects, and the description of the described objects should be referred to the context of the claims or embodiments, and should not be construed as redundant limitations. For example, the described objects are "fields", and the ordinal words before "fields" in "first field" and "second field" do not limit the position or order between "fields", and "first" and "second" do not limit whether the "fields" modified by them are in the same message or not, nor limit the order of "first field" and "second field". For another example, the described objects are "levels", and the ordinal words before "levels" in "first level" and "second level" do not limit the priority between "levels". For another example, the number of the described objects is not limited by the ordinal words, and can be one or more. For example, "first device", where the number of "devices" can be one or more. In addition, the objects modified by different prefix words can be the same or different, for example, the described objects are "devices", and "first device" and "second device" can be the same device or different devices, and their types can be the same or different; for another example, the described objects are "information", and "first information" and "second information" can be the same information or different information, and their contents can be the same or different.

[0057] In some embodiments, "including A", "containing A", "for indicating A", "carrying A" can be interpreted as directly carrying A, or indirectly indicating A.

[0058] In some embodiments, the terms "in response to", "in response to determining", "in the case of", "when", "when", "if", "if" and the like can be replaced with each other.

[0059] In some embodiments, the terms "greater than", "greater than or equal to", "not less than", "more than", "more than or equal to", "not less than", "higher than", "higher than or equal to", "not lower than", "above", and the like can be replaced with each other, and the terms "less than", "less than or equal to", "not greater than", "fewer than", "fewer than or equal to", "not more than", "lower than", "lower than or equal to", "not higher than", "below", and the like can be replaced with each other.

[0060] In some embodiments, an apparatus and the like can be interpreted as an entity, and can also be interpreted as virtual, and the name thereof is not limited to the name recited in the embodiments, and the terms "apparatus", "equipment", "device", "circuit", "network element", "node", "function", "unit", "section", "system", "network", "chip", "chip system", "entity", "subject", and the like can be replaced with each other.

[0061] In some embodiments, "network" can be interpreted as an apparatus (for example, an access network device, a core network device, and the like) included in the network.

[0062] In some embodiments, the terms “access network device (AN device),” “radio access network device (RAN device),” “base station (BS),” “radio base station,” “fixed station,” “node,” “access point,” “transmission point (TP),” “reception point (RP),” “transmission / reception point (TRP),” “panel,” “antenna panel,” “antenna array,” “cell,” “macro cell,” “small cell,” “femto cell,” “pico cell,” “sector,” “cell group,” “serving cell,” “carrier,” “component carrier,” “bandwidth part (BWP),” and the like can be used interchangeably.

[0063] In some embodiments, the terms "terminal," "terminal device," "user equipment (UE)," "user terminal," "mobile station (MS)," "mobile terminal (MT)," "subscriber station," "mobile unit," "subscriber unit," "wireless unit," "remote unit," "mobile device," "wireless device," "wireless communication device," "remote device," "mobile subscriber station," "access terminal," "mobile terminal," "wireless terminal," "remote terminal," "handset," "user agent," "mobile client," "client," and so on can be replaced with each other.

[0064] In some embodiments, the access network device, the core network device, or the network device can be replaced with a terminal. For example, the embodiments of the present disclosure can also be applied to a structure in which communication between the access network device, the core network device, or the network device and the terminal is replaced with communication between a plurality of terminals (e.g., device-to-device (D2D), vehicle-to-everything (V2X), etc.). In this case, the terminal can also be configured to have all or part of the functions of the access network device. In addition, the terms "uplink," "downlink," and the like can also be replaced with terms corresponding to the inter-terminal communication (e.g., "side"). For example, the uplink channel, the downlink channel, and the like can be replaced with the side channel, and the uplink, the downlink, and the like can be replaced with the sidelink.

[0065] In some embodiments, the terminal can be replaced with the access network device, the core network device, or the network device. In this case, the access network device, the core network device, or the network device can also be configured to have all or part of the functions of the terminal.

[0066] In some embodiments, the data, information, etc. can be obtained in compliance with the laws and regulations of the country where the location is located.

[0067] In some embodiments, the data, information, etc. can be obtained after obtaining the consent of the user.

[0068] In addition, each element, each row, or each column in the table of the embodiments of the present disclosure can be implemented as an independent embodiment, and any combination of any element, any row, or any column can also be implemented as an independent embodiment.

[0069] FIG. 1 is a schematic diagram of an architecture of a communication system according to an embodiment of the present disclosure.

[0070] As shown in FIG. 1, the communication system 100 includes a terminal 101 and a network device 102.

[0071] In some embodiments, the network device 102 sends various types of reference signals to the terminal 101, the terminal 101 measures the reference information to obtain layer 1 measurement samples, performs layer 1 filtering on the layer 1 measurement samples, obtains filtered measurement results, and reports the measurement results to the network device, and the network device performs subsequent communication based on the measurement results.

[0072] Among them, the terminal 101 can have a time domain prediction capability, for example, can input part of the measurement samples to an AI model to predict other part of the measurement samples, or to predict the measurement results.

[0073] In some embodiments, the terminal 101 can be a user equipment (UE), and the terminal includes at least one of a mobile phone, a wearable device, an Internet of Things device, a car with communication function, a smart car, a tablet computer (Pad), a computer with wireless transceiver function, a virtual reality (VR) terminal device, an augmented reality (AR) terminal device, a wireless terminal device in industrial control, a wireless terminal device in self-driving, a wireless terminal device in remote medical surgery, a wireless terminal device in smart grid, a wireless terminal device in transportation safety, a wireless terminal device in smart city, a wireless terminal device in smart home, and the like, but is not limited thereto.

[0074] In some embodiments, the network device 102 can include at least one of an access network device and a core network device.

[0075] In some embodiments, the access network device is at least one of a node or a device that accesses a terminal to a wireless network, for example, an evolved NodeB (eNB) in a 5G communication system, a next generation eNB (ng-eNB), a next generation NodeB (gNB), a node B (NB), a home node B (HNB), a home evolved node B (HeNB), a wireless backhaul device, a radio network controller (RNC), a base station controller (BSC), a base transceiver station (BTS), a base band unit (BBU), a mobile switching center, a base station in a 6G communication system, an Open RAN, a Cloud RAN, a base station in other communication systems, an access node in a Wi-Fi system, but is not limited thereto.

[0076] In some embodiments, the technical solutions of the present disclosure can be applied to an Open RAN architecture, at this time, the interfaces between or within the access network devices involved in the embodiments of the present disclosure can become internal interfaces of the Open RAN, and the processes and information interactions between these internal interfaces can be realized through software or programs.

[0077] In some embodiments, the access network device can be composed of a central unit (CU) and a distributed unit (DU), wherein the CU can also be referred to as a control unit. The CU-DU structure can split the protocol layers of the access network device, and the functions of part of the protocol layers are controlled by the CU, and the functions of the remaining part or all of the protocol layers are distributed in the DU and controlled by the CU, but are not limited thereto.

[0078] In some embodiments, the core network device can be one device including one or more network elements, or can be multiple devices or device groups including all or part of the one or more network elements respectively. The network element can be virtual or physical. The core network includes at least one of an evolved packet core (EPC), a 5G core network (5GCN), a next generation core (NGC), for example.

[0079] It can be understood that the communication system described in the embodiments of the present disclosure is for more clearly illustrating the technical solutions of the embodiments of the present disclosure, and does not constitute a limitation on the technical solutions proposed in the embodiments of the present disclosure. Those skilled in the art can know that, with the evolution of system architecture and the appearance of new business scenarios, the technical solutions proposed in the embodiments of the present disclosure are also applicable to similar technical problems.

[0080] The following embodiments of the present disclosure can be applied to the communication system 100 shown in FIG. 1 or part of the subject, but are not limited thereto. The subjects shown in FIG. 1 are exemplary, and the communication system can include all or part of the subjects in FIG. 1, or other subjects other than FIG. 1. The number and form of each subject is arbitrary, each subject can be physical or virtual, the connection relationship between each subject is exemplary, each subject can not be connected or can be connected, the connection can be in any way, can be direct connection or indirect connection, can be wired connection or wireless connection.

[0081] Embodiments of the present disclosure can be applied to Long Term Evolution (LTE), LTE-Advanced (LTE-A), LTE-Beyond (LTE-B), SUPER 3G, IMT-Advanced, 4th generation mobile communication system (4G), 5th generation mobile communication system (5G), 5G new radio (NR), 6th generation mobile communication system (6G), Future Radio Access (FRA), New-Radio Access Technology (RAT), New Radio (NR), New radio access (NX), Future generation radio access (FX), Global System for Mobile communications (GSM (registered trademark)), CDMA2000, Ultra Mobile Broadband (UMB), IEEE 802.11 (Wi-Fi (registered trademark)), IEEE 802.16 (WiMAX (registered trademark)), IEEE 802.20, Ultra-WideBand (UWB), Bluetooth (Bluetooth (registered trademark)), Public Land Mobile Network (PLMN) network, Device-to-Device (D2D) system, Machine to Machine (M2M) system, Internet of Things (IoT) system, Vehicle-to-Everything (V2X), system using other communication methods, next-generation system expanded based on them, and the like. Further, a plurality of systems can be applied in combination (for example, combination of LTE or LTE-A and 5G, and the like).

[0082] Radio Resource Management (RRM) measurement procedures are essential to maintain the performance and reliability of mobile networks. With the development of cellular technology and the introduction of higher frequency bands such as FR2, the number of measurement reports can further increase due to dynamic channel conditions, beamforming, dense deployment, and smaller cell sizes. To facilitate UE RRM measurements, the network transmits various types of reference signals, representing a significant system overhead that simultaneously consumes radio resources and network energy. In traditional non-AI-based RRM measurements, a UE first measures multiple L1 samples based on reference signals. These L1 samples are then subjected to L1 filtering. Then, the UE reports the filtered L1 results to higher layers (layer 3, L3). The higher layers further apply layer 3 filtering for cell quality measurements. Layer 1 filtering introduces a certain degree of measurement averaging. Layer 3 filtering for cell quality and related parameters is specified in the protocol version TS 38.331.

[0083] For beam management, the evaluation results show that AI / machine learning (ML) can provide good beam prediction accuracy with less measurement or reference signal (RS) overhead in the time and spatial domains. For mobility, under certain spatial consistency, AI / ML can be extended to cross-cell RRM measurement prediction.

[0084] There are two main goals for AI RRM measurement prediction: reducing reference signal overhead, and improving handoff (HO) performance.

[0085] When AI is applied, the UE can further reduce the L1 measurement delay and cell detection delay through reference signal received power (RSRP) prediction. In addition, depending on the terminal capability, the measurement delay will also be different.

[0086] The measurement period (TSSB_measurement_period_intra) for the non-gap intra-frequency measurement is shown in Table 1 and Table 2. Table 1 gives the measurement period for the non-gap intra-frequency measurement corresponding to FR1, and Table 2 gives the measurement period for the non-gap intra-frequency measurement corresponding to FR2.

[0087] Table 1 and Table 2 show the calculation method of the measurement period when there is no discontinuous reception (DRX), the DRX cycle is ≤320 ms, and the DRX cycle is >320 ms. Where K pis a relaxation factor (also referred to as adjustment factor) to compensate for SSB-based Measurement Timing Configuration (SMTC) and Measuring Gap (MG) collision, ceil() is a rounding function, CSSF intra is a carrier specific scaling factor (CSSF) for intra-frequency measurement corresponding to different DRX cycles.

[0088] It should be noted that if different SMTC cycles are used for different cells, the SMTC cycle in the table refers to the SMTC cycle used when identifying the cell.

[0089] Table 1 Measurement cycle for gapless intra-frequency measurement (FR1)

[0090] Table 2 Measurement cycle for gapless intra-frequency measurement (FR2)

[0091] When RSRP prediction is applied, the measurement delay can be reduced. When RSRP prediction is applied, the UE can have different receive (RX) beam capabilities. In addition, due to the change in measurement delay, the reporting delay also needs to be modified.

[0092] Therefore, the embodiments of the present disclosure provide a communication method, determining a measurement cycle based on a time domain prediction capability of a terminal; since the terminal has the time domain prediction capability, the terminal can omit the measurement of part of the samples and use an AI model for prediction, thereby determining the measurement cycle based on the time domain prediction capability of the terminal, which can shorten the measurement time, thereby saving communication resources and improving communication efficiency.

[0093] FIG. 2 is a flow diagram of a communication method according to an embodiment of the present disclosure.

[0094] In the embodiments of the present disclosure, the communication method can be performed by a terminal, but the present disclosure does not limit this.

[0095] As shown in FIG. 2, the embodiments of the present disclosure relate to a communication method, and the above method comprises:

[0096] In step S2101, a measurement cycle is determined based on a first capability of a terminal.

[0097] In some embodiments, the first capability is a time domain prediction capability of the terminal, i.e., the first capability is the prediction capability of the terminal in the time domain.

[0098] In some embodiments, the time domain prediction capability can be a prediction capability of the terminal in the time domain, for example, a prediction capability of the terminal in the time domain based on the AI model.

[0099] In some embodiments, the measurement period includes a layer 1 measurement period and / or a layer 3 measurement period. That is, the measurement period can be a layer 1 measurement period, the measurement period can also be a layer 3 measurement period, and the measurement period can also include a layer 1 measurement period and a layer 3 measurement period.

[0100] In some embodiments, the measurement period is a period in which the terminal performs measurement, and the prediction capability is a capability of making prediction based on the measurement.

[0101] For example, the terminal performs measurement in the measurement period to obtain measurement samples, and the terminal makes prediction based on the measurement samples to obtain predicted other measurement samples or measurement results.

[0102] In some embodiments, the first capability can include at least one of the following:

[0103] A capability of predicting Q layer 1 measurement samples based on P layer 1 measurement samples, P and Q being positive integers;

[0104] A capability of predicting 1 filtered layer 1 measurement result based on P layer 1 measurement samples;

[0105] A capability of predicting 1 filtered layer 1 measurement result based on K filtered layer 1 measurement results, K being a positive integer.

[0106] It can be understood that the above letters P, Q, and K are only illustrative, and other letters can also be used by those skilled in the art to represent the above meanings, and the present disclosure does not limit this.

[0107] In an exemplary embodiment, the first capability includes a capability of predicting Q layer 1 measurement samples based on P layer 1 measurement samples, P and Q being positive integers; the measurement period includes a layer 1 measurement period corresponding to a first frequency range, and a first ratio is determined, the first ratio being a ratio of P to (P+Q).

[0108] The layer 1 measurement sample can include, but is not limited to, a layer 1 RSRP measurement sample.

[0109] In an example, the first capability can be that the terminal can predict Q layer 1 measurement samples based on P layer 1 measurement samples, that is, the terminal does not need to measure (P+Q) layer 1 measurement samples, but only needs to measure P layer 1 measurement samples, and the remaining Q layer 1 measurement samples can be predicted by the AI model.

[0110] In the case where the terminal has the first capability, the measurement period can be a layer 1 measurement period corresponding to a first frequency range, where the first frequency range can be FR1 (450MHz to 6GHz). The layer 1 measurement period corresponding to FR1 can be determined based on a first ratio, where the first ratio is a ratio of P and (P+Q). That is, in the case where the terminal has the first capability, the measurement period can be determined based on P / (P+Q).

[0111] In this example, the L1 measurement period for FR1 intra-frequency measurement is defined as follows:

[0112] For the case where DRX is not present, the L1 measurement period is max(200ms, ceil(5 / (P+Q) x P x Kp) x SMTC period) x CSSF p x SMTC period) x CSSF intra ;

[0113] For the case where DRX cycle ≤ 320ms, the L1 measurement period is max(200ms, ceil(1.5 x 5 / (P+Q) x P x Kp) x max(SMTC period, DRX cycle)) x CSSF intra ;

[0114] For the case where DRX cycle > 320ms, the L1 measurement period is ceil(5 / (P+Q) x P x K p x DRX cycle) x CSSF intra .

[0115] In some embodiments, the first capability can be represented by a field. For example, the first capability is represented by a first field and a second field, where the first field is a value of P and the second field is a value of Q. For another example, the first capability is represented by a first field, where the first field is a value of P / (P+Q).

[0116] In the embodiments of the present disclosure, in the case where the terminal has the first capability, the terminal does not need to measure all samples, and thus the measurement period can be determined based on the first ratio, thereby shortening the time length required for terminal measurement, saving communication resources, and improving communication efficiency. On the other hand, in the case where the terminal has the first capability, in the time slots in which the terminal can use the AI model for prediction, the network device can not need to send reference signals, thereby reducing the number of network device sending resources, thereby saving communication resources.

[0117] In the example embodiments, the first capability includes a capability of predicting 1 filtered layer 1 measurement result based on P layer 1 measurement samples, where P is a positive integer; the measurement period includes a layer 1 measurement period corresponding to a first frequency range, and the measurement period is determined based on P.

[0118] In an example, the first capability can be that the terminal is capable of predicting one filtered layer 1 measurement result based on P layer 1 measurement samples, i.e., the terminal can directly predict one filtered layer 1 measurement result based on P layer 1 measurement samples. The terminal can input the P layer 1 measurement samples into an AI model, and the AI model can directly predict to obtain one filtered layer 1 measurement result. That is, the AI model can have the function of predicting multiple measurement samples and filtering.

[0119] In the case where the terminal has such a first capability, the measurement period can be a layer 1 measurement period corresponding to the first frequency range. The layer 1 measurement period corresponding to FR1 can be determined based on P.

[0120] In this example, the L1 measurement period for FR1 intra-frequency measurement is defined as follows:

[0121] For the case where there is no DRX, the L1 measurement period is max(200ms, ceil(P x K p )x SMTC period) x CSSF intra ;

[0122] For the case where the DRX cycle is ≤ 320ms, the L1 measurement period is max(200ms, ceil(1.5 x P x K p )x max(SMTC period, DRX cycle)) x CSSF intra ;

[0123] For the case where the DRX cycle is > 320ms, the L1 measurement period is ceil(P x K p )x DRX cycle x CSSF intra .

[0124] In this example, it can also be understood that the measurement period is determined based on the quotient of P and the first parameter (for example, 5), so that the 5 in the ceil function shown in Table 1 is offset, and thus the first parameter (for example, 5) does not exist in the formula of the measurement period in this example.

[0125] For the case where there is no DRX, the L1 measurement period is max(200ms, ceil(5 x P / 5 x K p )x SMTC period) x CSSF intra , where the 5 in 5 x P / 5 is offset.

[0126] It can be understood that the terminal needs to measure P measurement samples without time domain prediction capability, and the terminal only needs to measure P measurement samples with the above time domain prediction capability, so the measurement period can be determined based on P (or based on the quotient of P and the first parameter), thereby shortening the time length required by the terminal for measurement, saving communication resources, and improving communication efficiency. On the other hand, in the case that the terminal has time domain prediction capability, the network device can not need to send reference signals in the time slots in which the terminal can use the AI model for prediction, thereby reducing the number of network device transmission resources, thereby saving communication resources.

[0127] In some embodiments, the first capability can be represented by a field. For example, the first capability is represented by a first field, and the first field is the value of P.

[0128] In an exemplary embodiment, the first capability includes the capability of predicting 1 filtered layer 1 measurement result based on K filtered layer 1 measurement results, K is a positive integer; the measurement period includes a layer 3 measurement period corresponding to the first frequency range, and the measurement period is determined based on K.

[0129] In an example, the first capability can be that the terminal can predict 1 filtered layer 1 measurement result based on K filtered layer 1 measurement results. For example, the terminal can predict 1 filtered layer 1 measurement sample corresponding to the next time window based on K filtered layer 1 measurement results corresponding to the previous K time windows, respectively. For example, the terminal can input K filtered layer 1 measurement results into an AI model to predict 1 filtered layer 1 measurement result.

[0130] In the case that the terminal has such a first capability, the measurement period can be a layer 3 measurement period corresponding to the first frequency range. The layer 3 measurement period corresponding to FR1 can be determined based on K.

[0131] In this example, the L3 measurement period of FR1 intra-frequency measurement is defined as follows:

[0132] For the case that there is no DRX, the L1 measurement period is max(200ms, ceil(5x K x K p ) x SMTC period) x CSSF intra ;

[0133] For the case that the DRX period is ≤320ms, the L3 measurement period is max(200ms, ceil(1.5x 5x K x K intra ;

[0134] For the case that the DRX period is >320ms, the L3 measurement period is ceil(5x K x K px DRX cycle x CSSF intra .

[0135] In the embodiments of the present disclosure, when the terminal has the first capability described above, the terminal predicts one filtered layer 1 measurement result from K filtered layer 1 measurement results, which can shorten the time required for terminal measurement, save communication resources, and improve communication efficiency. On the other hand, when the terminal has the time domain prediction capability, in the time slots in which the terminal can use the AI model for prediction, the network device can not need to send reference signals, thereby reducing the number of network device transmission resources, thereby saving communication resources.

[0136] In some embodiments, the first capability can be represented by a field. For example, the first capability is represented by a first field, and the first field is a value of K.

[0137] In an exemplary embodiment, the first capability includes the capability of predicting Q layer 1 measurement samples based on P layer 1 measurement samples, and P and Q are both positive integers; the measurement period includes a layer 1 measurement period corresponding to full receive beam sweeping in a second frequency range, and the measurement period is determined based on a first ratio, and the first ratio is the ratio of P to (P+Q).

[0138] In an example, the first capability can be that the terminal can predict Q layer 1 measurement samples based on P layer 1 measurement samples, that is, the terminal does not need to measure all (P+Q) layer 1 measurement samples, but only needs to measure P layer 1 measurement samples, and the remaining Q layer 1 measurement samples can be predicted by an AI model.

[0139] In the case where the terminal has such a first capability, the measurement period can be a layer 1 measurement period corresponding to full receive beam sweeping in a second frequency range, and the second frequency range can be FR2 (24.25GHz to 52.6GHz), and full receive beam sweeping means that the terminal applies complete receive beam sweeping in space through multiple receive beams. The layer 1 measurement period corresponding to FR2 can be determined based on a first ratio, and the first ratio is the ratio of P to (P+Q).

[0140] That is, in the case where the terminal has such a first capability, the measurement period can be determined based on 5x P / (P+Q).

[0141] In this example, the L1 measurement period for FR2 intra-frequency measurement is defined as follows:

[0142] For the case where there is no DRX, the L1 measurement period is max(400ms, ceil(M meas_period_w / o_gaps / 5x P / (P+Q)x K p xK layer1_measurement )x SMTC period)x CSSF intra ;

[0143] For DRX cycle ≤ 320ms, L1 measurement period is max(400ms, ceil(1.5x M meas_period_w / o_gaps / 5x P / (P+Q)xK p x K layer1_measurement )x max(SMTC period, DRX cycle))x CSSF intra ;

[0144] For DRX cycle > 320ms, L1 measurement period is ceil(M meas_period_w / o_gaps / 5xK p x P / Q x K layer1_measurement )x DRX cycle x CSSF intra .

[0145] where M meas_period_w / o_gaps denotes the number of SMTC occasions in which the UE is expected to successfully measure SSBs, K layer1_measurement denotes a scaling factor related to layer 1 measurement.

[0146] In the embodiments of the present disclosure, in the case that the terminal has the first capability described above, the terminal does not need to measure all samples, and thus the measurement period can be determined based on the first ratio, so as to shorten the time length required for terminal measurement, save communication resources, and improve communication efficiency. On the other hand, in the case that the terminal has the time domain prediction capability, in the time slots in which the terminal can use the AI model for prediction, the network device can not need to send reference signals, so as to reduce the number of network device sending resources, thereby saving communication resources.

[0147] In an example embodiment, the first capability includes a capability of predicting one filtered layer 1 measurement result based on P layer 1 measurement samples, P being a positive integer; and the measurement period includes a layer 1 measurement period corresponding to full receive beam sweeping in a second frequency range, and the measurement period is determined based on P.

[0148] In an example, the first capability can be that the terminal can predict one filtered layer 1 measurement result based on P layer 1 measurement samples, i.e., the terminal can directly predict one filtered layer 1 measurement result based on P layer 1 measurement samples. The terminal can input the P layer 1 measurement samples into the AI model, and the AI model can directly predict one filtered layer 1 measurement result. That is, the AI model can have the function of predicting and filtering multiple measurement samples.

[0149] In the case that the terminal has the first capability, the measurement period can be a layer 1 measurement period corresponding to full receive beam sweeping in the second frequency range. The second frequency range can be FR2, and the layer 1 measurement period corresponding to FR2 can be determined based on a ratio of P and the second parameter (e.g., P / 5).

[0150] In this example, the L1 measurement period for FR2 intra-frequency measurement is defined as follows:

[0151] For No DRX case, the L1 measurement period is max(400ms, ceil(M meas_period_w / o_gaps / 5x P x K p x K layer1_measurement )x SMTC period)x CSSF intra ;

[0152] For DRX cycle <= 320ms, the L1 measurement period is max(400ms, ceil(1.5x M meas_period_w / o_gaps / 5x P x K p x K layer1_measurement )x max(SMTC period, DRX cycle))x CSSF intra ;

[0153] For DRX cycle > 320ms, the L1 measurement period is ceil(M meas_period_w / o_gaps / 5x K p x P x K layer1_measurement )x DRX cycle x CSSF intra .

[0154] In the embodiments of the present disclosure, the terminal needs to measure M measurement samples in the case that the terminal does not have the time domain prediction capability, and the terminal only needs to measure P measurement samples in the case that the terminal has the time domain prediction capability, so the measurement period can be determined based on P (or based on the quotient of P and the second parameter), thereby shortening the time length required for terminal measurement, saving communication resources, and improving communication efficiency. On the other hand, in the case that the terminal has the first capability, the network device can not need to send reference signals in the time slots in which the terminal can use the AI model for prediction, thereby reducing the number of network device sending resources, thereby saving communication resources.

[0155] In the exemplary embodiments, the first capability includes a capability of predicting 1 filtered layer 1 measurement result based on K filtered layer 1 measurement results, K being a positive integer; and the measurement period includes a layer 3 measurement period corresponding to full receive beam sweeping in the second frequency range, and the measurement period is determined based on K.

[0156] In an example, the first capability can be that the terminal can predict 1 filtered layer 1 measurement result based on K filtered layer 1 measurement results. For example, the terminal can predict 1 filtered layer 1 measurement sample corresponding to a next time window based on K filtered layer 1 measurement results respectively corresponding to previous K time windows. For example, the terminal can input the K filtered layer 1 measurement results into an AI model to predict 1 filtered layer 1 measurement result.

[0157] In a case where the terminal has the first capability, the measurement period can be a layer 3 measurement period corresponding to full receive beam sweeping in a second frequency range. The second frequency range can be FR2, and the layer 3 measurement period corresponding to FR2 can be determined based on K.

[0158] In this example, the L3 measurement period of the FR2 intra-frequency measurement is defined as follows:

[0159] For a case where DRX does not exist, max(400ms, ceil(M meas_period_w / o_gaps x K x K p x K layer1_measurement )x SMTC period)x CSSF intra ;

[0160] For a case where the DRX period is less than or equal to 320ms, max(400ms, ceil(1.5x M meas_period_w / o_gaps x K x K p x K layer1_measurement )x max(SMTC period, DRX period))x CSSF intra ;

[0161] For a case where the DRX period is greater than 320ms, ceil(M meas_period_w / o_gaps x K x K p x K layer1_measurement )x DRX period)x CSSF intra .

[0162] In the embodiments of the present disclosure, in a case where the terminal has the first capability, the terminal predicts 1 filtered layer 1 measurement result based on K filtered layer 1 measurement results, which can shorten the time length required for terminal measurement, save communication resources, and improve communication efficiency. On the other hand, in a case where the terminal has the time domain prediction capability, the network device can not need to send a reference signal in a time slot in which the terminal can use an AI model for prediction, thereby reducing the number of network device sending resources, thereby saving communication resources.

[0163] In an example embodiment, the first capability comprises a capability of predicting Q number of layer 1 measurement samples based on P number of layer 1 measurement samples, P and Q are both positive integers; the measurement period comprises a layer 1 measurement period corresponding to a specific receive beam sweeping in a second frequency range, the measurement period is determined based on a first ratio and a second ratio, the first ratio is a ratio of P and (P+Q), the second ratio is a ratio of F and G, F is a number of the specific receive beams, G is a number of all receive beams, F and G are both positive integers.

[0164] In an example, the first capability can be that the terminal is capable of predicting Q number of layer 1 measurement samples based on P number of layer 1 measurement samples, i.e., the terminal does not need to measure all (P+Q) number of layer 1 measurement samples, but only needs to measure P number of layer 1 measurement samples, and the remaining Q number of layer 1 measurement samples can be predicted by an AI model.

[0165] In the case where the terminal has such a first capability, the measurement period can be a layer 1 measurement period corresponding to a specific receive beam sweeping in a second frequency range, where the second frequency range can be FR2 (24.25GHz to 52.6GHz).

[0166] Wherein, the specific receive beam refers to part of the total receive beam, for example, there are G total receive beams, and F receive beams are specific receive beams. The specific receive beam sweeping refers to the terminal applying a specific receive beam or a subset of all receive beams for prediction.

[0167] Wherein, the layer 1 measurement period corresponding to FR2 can be determined based on a first ratio and a second ratio, for example, can be determined based on a product of the first ratio and the second ratio. The first ratio is a ratio of P and (P+Q), and the second ratio is a ratio of F and G.

[0168] That is, in the case where the terminal has such a first capability, the measurement period can be determined based on P / (P+Q) x F / G.

[0169] In this example, the L1 measurement period for FR2 intra-frequency measurement is defined as follows:

[0170] For the case where DRX does not exist, the L1 measurement period is max(400ms, ceil(M meas_period_w / o_gaps / 5 / G x F x P / (P+Q)x K p x K layer1_measurement )x SMTC period)x CSSF intra ;

[0171] For the case where the DRX period is ≤320ms, the L1 measurement period is max(400ms, ceil(1.5x M meas_period_w / o_gaps / 5 / G x F x P / (P+Q)x Kp x K layer1_measurement )x max(SMTC period, DRX period)) x CSSF intra ;

[0172] For DRX cycle > 320ms, L1 measurement period is ceil(M meas_period_w / o_gaps / 5 / 8 x F x K p x P / Q x K layer1_measurement )x DRX period x CSSF intra .

[0173] In an example, the number of all receiving beams G can be 8, and the L1 measurement period of FR2 intra-frequency measurement is defined as follows:

[0174] For the case of no DRX, L1 measurement period is max(400ms, ceil(M meas_period_w / o_gaps / 5 / 8 x F x P / (P+Q) x K p x K layer1_measurement )x SMTC period) x CSSF intra ;

[0175] For DRX cycle ≤ 320ms, L1 measurement period is max(400ms, ceil(1.5x M meas_period_w / o_gaps / 5 / 8 x F x P / (P+Q) x K p x K layer1_measurement )x max(SMTC period, DRX period)) x CSSF intra ;

[0176] For DRX cycle > 320ms, L1 measurement period is ceil(M meas_period_w / o_gaps / 5 / 8 x F x K p x P / Q x K layer1_measurement )x DRX period x CSSF intra .

[0177] In the embodiments of the present disclosure, in the case that the terminal has the first capability described above, the terminal does not need to measure all samples, and thus the measurement period can be determined based on the first ratio, so as to shorten the time length required for terminal measurement, save communication resources, and improve communication efficiency. On the other hand, in the case that the terminal has the time domain prediction capability, in the time slots in which the terminal can use the AI model for prediction, the network device can not need to send the reference signal, so as to reduce the number of network device sending resources, thereby saving communication resources.

[0178] In an example embodiment, the first capability comprises a capability of predicting one filtered layer 1 measurement result based on P layer 1 measurement samples, P being a positive integer; and the measurement period comprises a layer 1 measurement period corresponding to a specific receive beam sweeping in a second frequency range, the measurement period being determined based on P and a second ratio, the second ratio being a ratio of F and G, F being a number of the specific receive beams, G being a number of all receive beams, F and G being positive integers.

[0179] In an example, the first capability can be that the terminal is capable of predicting one filtered layer 1 measurement result based on P layer 1 measurement samples, i.e., the terminal can directly predict one filtered layer 1 measurement result based on P layer 1 measurement samples. The terminal can input the P layer 1 measurement samples into an AI model, and the AI model can directly predict one filtered layer 1 measurement result. That is, the AI model can have a function of predicting and filtering a plurality of measurement samples.

[0180] In a case where the terminal has such a first capability, the measurement period can be a layer 1 measurement period corresponding to a specific receive beam sweeping in a second frequency range. The second frequency range can be FR2, and the layer 1 measurement period corresponding to FR2 can be determined based on P and a second ratio. For example, it can be determined based on a product of P and the second ratio (i.e., P x the second ratio). The second ratio is a ratio of F and G.

[0181] That is, in a case where the terminal has such a first capability, the measurement period can be determined based on P x F / G / 5.

[0182] In this example, the L1 measurement period for FR2 intra-frequency measurement is defined as follows:

[0183] For the case where DRX is not present, the L1 measurement period is max(400ms, ceil(M meas_period_w / o_gaps / 5 / G x F x P x K p x K layer1_measurement )x SMTC period)x CSSF intra ;

[0184] For the case where DRX cycle ≤ 320ms, the L1 measurement period is max(400ms, ceil(1.5x M meas_period_w / o_gaps / 5 / G x F x P x K p x K layer1_measurement )x max(SMTC period, DRX cycle))x CSSF intra ;

[0185] For the case where DRX cycle > 320ms, the L1 measurement period is ceil(M meas_period_w / o_gaps / 5 / G x F x K px P x K layer1_measurement )x DRX cycle)x CSSF intra .

[0186] In an example, the number of all receive beams G can be 8, and the L1 measurement period for FR2 intra-frequency measurement is defined as follows:

[0187] For the case of no DRX, the L1 measurement period is max(400ms, ceil(M meas_period_w / o_gaps / 5 / 8x F x P x K p xK layer1_measurement )x SMTC period)x CSSF intra ;

[0188] For the case of DRX cycle ≤ 320ms, the L1 measurement period is max(400ms, ceil(1.5x M meas_period_w / o_gaps / 5 / 8x F x P x K p x K layer1_measurement )x max(SMTC period, DRX cycle))x CSSF intra ;

[0189] For the case of DRX cycle > 320ms, the L1 measurement period is ceil(M meas_period_w / o_gaps / 5 / 8x F x K p x P x K layer1_measurement )x DRX cycle)x CSSF intra .

[0190] In the embodiments of the present disclosure, the terminal needs to measure second parameter measurement samples in the case of not having time domain prediction capability, and the terminal only needs to measure P measurement samples in the case of having the above time domain prediction capability, so the measurement period can be determined based on P (or based on the quotient of P and the second parameter), thereby shortening the time length required by the terminal for measurement, saving communication resources, and improving communication efficiency.

[0191] In the example embodiments, the first capability includes an ability of predicting one filtered layer 1 measurement result based on K filtered layer 1 measurement results, K being a positive integer; the measurement period includes a layer 3 measurement period corresponding to specific receive beam scanning in a second frequency range, and the measurement period is determined based on K and a second ratio, the second ratio being a ratio of F and G, F being a number of specific receive beams, and G being a number of all receive beams, both F and G being positive integers.

[0192] In an example, the first capability can be that the terminal is capable of predicting 1 filtered layer 1 measurement result based on K filtered layer 1 measurement results. For example, the terminal can predict 1 filtered layer 1 measurement sample corresponding to a next time window based on K filtered layer 1 measurement results respectively corresponding to previous K time windows. For example, the terminal can input the K filtered layer 1 measurement results into an AI model to predict 1 filtered layer 1 measurement result.

[0193] In a case that the terminal has the first capability, the measurement period can be a layer 3 measurement period corresponding to a specific receive beam sweeping in a second frequency range. The second frequency range can be FR2, and the layer 3 measurement period corresponding to FR2 can be determined based on K and a second ratio. For example, determined based on a product of K and the second ratio (K x the second ratio).

[0194] In this example, the L3 measurement period for FR2 intra-frequency measurement is defined as follows:

[0195] For no DRX case, the L3 measurement period is max(400ms, ceil(M meas_period_w / o_gaps x K / G x F x K p xK layer1_measurement )x SMTC period)x CSSF intra ;

[0196] For DRX cycle ≤ 320ms, the L3 measurement period is max(400ms, ceil(1.5x M meas_period_w / o_gaps x K / G x F x K p xK layer1_measurement )x max(SMTC period, DRX cycle))x CSSF intra ;

[0197] For DRX cycle > 320ms, the L3 measurement period is ceil(M meas_period_w / o_gaps xK p x K / G x F x K layer1_measurement )x DRX cycle)x CSSF intra .

[0198] In an example, the number of all receive beams G can be 8, and the L1 measurement period for FR2 intra-frequency measurement is defined as follows:

[0199] For no DRX case, the L3 measurement period is max(400ms, ceil(M meas_period_w / o_gaps x K / 8x F x K p xK layer1_measurement )x SMTC period)x CSSF intra ;

[0200] For DRX cycle ≤ 320ms, L3 measurement period is max(400ms, ceil(1.5 x M meas_period_w / o_gaps x K / 8x F x K p xK layer1_measurement )x max(SMTC period, DRX cycle) x CSSF intra ;

[0201] For DRX cycle > 320ms, L3 measurement period is ceil(M meas_period_w / o_gaps xK p x K / 8x F x K layer1_measurement )x DRX cycle x CSSF intra .

[0202] In the embodiments of the present disclosure, when the terminal has the first capability described above, the terminal predicts one filtered layer 1 measurement result from K filtered layer 1 measurement results, which can shorten the time required for terminal measurement, save communication resources, and improve communication efficiency. On the other hand, when the terminal has the time domain prediction capability, the network device can not need to send reference signals in the time slots in which the terminal can use the AI model for prediction, thereby reducing the number of network device sending resources, thereby saving communication resources

[0203] In step S2102, measurement is performed based on a measurement period to obtain a measurement sample.

[0204] In some embodiments, the terminal can determine the measurement period based on the first capability of the terminal itself, and perform measurement of the corresponding reference signal in the measurement period to obtain a measurement sample.

[0205] In step S2103, a measurement result is obtained based on the measurement sample, and the measurement result is reported to the network device.

[0206] In some embodiments, the terminal can use an AI model to predict a measurement result based on the measurement sample, and report the measurement result to the network device. The network device can perform subsequent communication based on the measurement result.

[0207] The communication method related to the embodiments of the present disclosure can include at least one of steps S2101 to S2103. For example, step S2101 can be implemented as an independent embodiment, but is not limited thereto.

[0208] In some embodiments, step S2102 is optional, and one or more of these steps can be omitted or replaced in different embodiments.

[0209] In some embodiments, step S2103 is optional, and one or more of these steps can be omitted or replaced in different embodiments.

[0210] In some embodiments, other optional implementations described before or after the description corresponding to FIG. 2 can be referred to.

[0211] In some embodiments, the names of information and the like are not limited to the names described in the embodiments, and the terms of “information”, “message”, “signal”, “signaling”, “report”, “configuration”, “indication”, “instruction”, “command”, “channel”, “parameter”, “domain”, “field”, “symbol”, “symbol”, “codebook”, “codeword”, “codepoint”, “bit”, “data”, “program”, “chip”, and the like can be replaced with each other.

[0212] In some embodiments, the terms of “time”, “time point”, “time position”, and the like can be replaced with each other, and the terms of “time length”, “time period”, “time window”, “window”, “time”, and the like can be replaced with each other.

[0213] In some embodiments, “acquire”, “obtain”, “get”, “receive”, “transmit”, “bidirectional transmission”, “send and / or receive”, and the like can be replaced with each other, and can be interpreted as receiving from other subjects, acquiring from protocols, acquiring from higher layers, obtaining by self-processing, and the like.

[0214] In some embodiments, the terms of “send”, “transmit”, “report”, “issue”, “transmit”, “bidirectional transmission”, “send and / or receive”, and the like can be replaced with each other.

[0215] In some embodiments, the terms "certain", "preset", "pre-set", "set", "indicated", "any", "first", and the like can be replaced with each other, and "certain A", "preset A", "pre-set A", "set A", "indicated A", "any A", "first A" can be interpreted as A predetermined in a protocol or the like, or A obtained by setting, configuration, or indication, or a specific A, any A, or first A, but are not limited thereto.

[0216] In some embodiments, the determination or judgment can be made by a value represented by 1 bit (0 or 1), or by a true or false value (Boolean value) represented by true or false, or by comparison of numerical values (for example, comparison with a predetermined value), but is not limited thereto.

[0217] In some embodiments, "not expected to receive" can be interpreted as not receiving on the time domain resource and / or the frequency domain resource, or as not performing subsequent processing on the data or the like after receiving the data or the like; "not expected to send" can be interpreted as not sending, or as sending but not expecting the receiving party to respond to the content of the sending.

[0218] FIG. 3 is a flow diagram of a communication method according to an embodiment of the present disclosure.

[0219] As shown in FIG. 3, the embodiment of the present disclosure relates to a communication method, and the above method comprises:

[0220] In step S3101, a measurement period is determined based on a first capability of the terminal.

[0221] In some embodiments, the terminal has a time domain prediction capability, and in a time slot in which the terminal can use an AI model for prediction, the network device can not need to send a reference signal, thereby reducing the number of resources sent by the network device, thereby saving communication resources.

[0222] The optional implementation of step S3101 can refer to the optional implementation of step S2101 of FIG. 2 and other associated parts in the embodiments involved in FIG. 2, which will not be repeated here.

[0223] The embodiment of the present disclosure defines a UE capability for RRM measurement prediction in the time domain and a UE capability for RRM measurement prediction in the RX beam domain.

[0224] Case 1: Define the UE time domain prediction capability and measurement period for RSRP prediction of FR1.

[0225] Option 1: UE capability is defined as P number of L1 RSRP samples for measurement and Q number of L1 RSRP samples for measurement prediction of one L3 report, the capability is [P, Q].

[0226] The L1 measurement period for FR1 intra-frequency measurement is defined as follows:

[0227] For the case where DRX is not present, the L1 measurement period is max(200ms, ceil(5 / (P+Q) x P x Kp) x SMTC period) x CSSF p . intra ;

[0228] For the case where DRX cycle ≤ 320ms, the L1 measurement period is max(200ms, ceil(1.5 x 5 / (P+Q) x P x Kp) x max(SMTC period, DRX cycle)) x CSSF intra .

[0229] For the case where DRX cycle > 320ms, the L1 measurement period is ceil(5 / (P+Q) x P x Kp) x DRX cycle x CSSF p . intra .

[0230] Where SMTC is the synchronization signal block (PSS / SSS PBCH Block, SSB) based mobility measurement window.

[0231] K p is the scaling factor (also referred to as scaling coefficient) for SSB frequency layers measured without measurement gap (GAP, also referred to as measurement gap). K p = N total / N available , where N available and N total are calculated as follows:

[0232] For a window W of duration max(SMTC period, xRP_max) where xRP_max is the maximum xRP of all configured per-UE GAP, periodic multiple subscriber identity module (MUSIM) interval, and / or, per FR GAP within the same FR as the SSB frequency layer, and starting from any SMTC occasion:

[0233] N total is the total number of SMTC occasions within the window, including occasions overlapping with GAP and MUSIM interval occasions within the window, and

[0234] Navailable is the number of SMTC occasions that do not overlap with any non-dropped GAP or non-dropped MUSIM gap occasion within the window W after considering the measurement GAP and MUSIM gap in collision rules in the respective communication standards.

[0235] When N available = 0, K p = 1.

[0236] When the configured GAP is before the MG (measurement gap) or the MG is activated, xRP = MGRP (Measuring Gap Repeat Period), and when the configured GAP is NCSG (Network controlled small gap), xRP = VIRP, for periodic MUSIM gap as well xRP = MGRP.

[0237] CSSF intra : This is a scaling factor for a specific carrier and is determined as: CSSF outside_gap,i , i.e., no-gap-with-interruption is indicated when the intra-frequency SMTC is fully or partially overlapped with the GAP, or no-gap-no-interruption is indicated when the intra-frequency SMTC is fully overlapped with the GAP of the UE, or no-gap-no-interruption is indicated when the intra-frequency SMTC is fully or partially overlapped with the GAP of the UE.

[0238] Option 2: UE capability is defined as predicting one L3 report based on P L1 RSRP samples with 1 filtered L1 RSRP, the capability is [P].

[0239] The L1 measurement period for intra-frequency measurement in FR1 will be defined as follows:

[0240] For the case where DRX does not exist, the L1 measurement period is max(200ms, ceil(P x K p ) x SMTC period) Note 1 x CSSF intra ;

[0241] For the case where DRX cycle ≤ 320ms, the L1 measurement period is max(200ms, ceil(1.5 x P x Kp) x max(SMTC period, DRX cycle)) x CSSF intra ;

[0242] For DRX cycle > 320ms, L1 measurement period is ceil(P x Kp) x DRX cycle x CSSF intra .

[0243] Option 3: UE capability is defined as predicting one L1 filtered RSRP based on K L1 filtered RSRPs. L3 measurement period for FR1 intra-frequency measurement will be defined as follows:

[0244] For no DRX case, L3 measurement period is max(200ms, ceil(K x 5 x K p x SMTC period) x CSSF Note 1 x CSSF intra ;

[0245] For DRX cycle < 320ms, L3 measurement period is max(200ms, ceil(1.5 x 5 x K x K p x max(SMTC period, DRX cycle)) x CSSF intra ;

[0246] For DRX cycle > 320ms, L3 measurement period is ceil(5 x K x K p x DRX cycle x CSSF intra .

[0247] Case 2: Define UE RX beam capability and measurement period for RSRP prediction for FR2.

[0248] Option 1: Define full RX beam sweeping capability, i.e. UE will apply full RX beam sweeping in space through multiple RX beams.

[0249] Option 1-1: UE time capability is defined as predicting Q L1 RSRP samples for one L3 report based on P L1 RSRP samples measurement, the capability is [P, Q]. L1 measurement period for FR2 intra-frequency measurement will be defined as follows:

[0250] For no DRX case, L1 measurement period is max(400ms, ceil(M meas_period_w / o_gaps / 5 x P / (P+Q) x K p xK layer1_measurement )x SMTC period) x CSSF intra ;

[0251] For DRX cycle < 320ms, L1 measurement period is max(400ms, ceil(1.5 x Mmeas_period_w / o_gaps / 5 x P / (P+Q) x K p x K layer1_measurement )x max(SMTC period, DRX period) x CSSF intra ;

[0252] For DRX cycle > 320ms, L1 measurement period is ceil(M meas_period_w / o_gaps / 5 x K p x P / Q x K layer1_measurement )x DRX cycle x CSSF intra .

[0253] Option 1-2: UE time capability is defined as predicting one L3 report from one filtered L1 RSRP based on P L1 RSRP samples, the capability is [P]. L1 measurement period for FR2 intra-frequency measurement is defined as follows:

[0254] For No DRX case, L1 measurement period is max(400ms, ceil(M meas_period_w / o_gaps / 5 x P x K p x K layer1_measurement )x SMTC period) x CSSF intra ;

[0255] For DRX cycle <= 320ms, L1 measurement period is max(400ms, ceil(1.5 x M meas_period_w / o_gaps / 5 x P x K p x K layer1_measurement )x max(SMTC period, DRX period) x CSSF intra ;

[0256] For DRX cycle > 320ms, L1 measurement period is ceil(M meas_period_w / o_gaps / 5 x K p x P x K layer1_measurement )x DRX cycle x CSSF intra .

[0257] Option 1-3: UE time capability is defined as predicting one L1 filtered RSRP from K L1 filtered RSRPs. L3 measurement period for FR2 intra-frequency measurement is defined as follows:

[0258] For No DRX case, L3 measurement period is max(400ms, ceil(M meas_period_w / o_gaps x K x K p x K layer1_measurement )x SMTC period) x CSSFintra ;

[0259] For DRX cycle ≤ 320ms, L3 measurement period is max(400ms, ceil(1.5 x M meas_period_w / o_gaps x K x K p x K layer1_measurement )x max(SMTC period, DRX cycle)) x CSSF intra ;

[0260] For DRX cycle > 320ms, L3 measurement period is ceil(M meas_period_w / o_gaps x K x K p x K layer1_measurement )x DRX cycle x CSSF intra .

[0261] Option 2: Define specific RX beam sweeping capability. UE will apply one specific RX beam or a subset of full RX beams for prediction, e.g. RX beam number is F. Assume full RX beam sweeping number is 8.

[0262] Option 2-1: UE time capability is defined based on measurement of P number of L1 RSRP samples to predict Q number of L1 RSRP samples for one L3 report, the capability is [P, Q]. Define L1 measurement period for FR2 intra-frequency measurement as follows:

[0263] For no DRX case, L1 measurement period is max(400ms, ceil(M meas_period_w / o_gaps / 5 / 8 x F x P / (P+Q) x K p x K layer1_measurement )x SMTC period) x CSSF intra ;

[0264] For DRX cycle ≤ 320ms, L1 measurement period is max(400ms, ceil(1.5 x M meas_period_w / o_gaps / 5 / 8 x F x P / (P+Q) x K p x K layer1_measurement )x max(SMTC period, DRX cycle)) x CSSF intra ;

[0265] For DRX cycle > 320ms, L1 measurement period is ceil(M meas_period_w / o_gaps / 5 / 8 x F x K p x P / Q x K layer1_measurement )x DRX cycle x CSSF intra .

[0266] Option 2-2: UE time capability is defined based on the measurement of P L1 RSRP samples to predict 1 filtered L1 RSRP for one L3 report, the capability is [P]. The L1 measurement period for intra-frequency measurement for FR2 is defined as follows:

[0267] For no DRX case, the L1 measurement period is max(400ms, ceil(M meas_period_w / o_gaps / 5 / 8 x F x P x K p x K layer1_measurement )x SMTC period)x CSSF intra ;

[0268] For DRX cycle <= 320ms, the L1 measurement period is max(400ms, ceil(1.5 x M meas_period_w / o_gaps / 5 / 8 x F x P x K p x K layer1_measurement )x max(SMTC period, DRX cycle))x CSSF intra ;

[0269] For DRX cycle > 320ms, the L1 measurement period is ceil(M meas_period_w / o_gaps / 5 / 8 x F x K p x P x K layer1_measurement )x DRX cycle x CSSF intra .

[0270] Option 2-3: UE capability is defined based on K L1 filtered RSRP to predict 1 L1 filtered RSRP. The L3 measurement period for intra-frequency measurement for FR2 is defined as follows:

[0271] For no DRX case, the L3 measurement period is max(400ms, ceil(M meas_period_w / o_gaps x K / 8 x F x K p x K layer1_measurement )x SMTC period)x CSSF intra ;

[0272] For DRX cycle <= 320ms, the L3 measurement period is max(400ms, ceil(1.5 x M meas_period_w / o_gaps x K / 8 x F x K p x K layer1_measurement )x max(SMTC period, DRX cycle))x CSSF intra ;

[0273] For DRX cycle > 320ms, the L3 measurement period is ceil(Mmeas_period_w / o_gaps xK p x K / 8x F x K layer1_measurement )x DRX cycle x CSSF intra .

[0274] The embodiments of the present disclosure further provide a device for implementing any of the above methods, for example, a device comprising units or modules for implementing the steps performed by the terminal in any of the above methods. For another example, another device is provided, comprising units or modules for implementing the steps performed by the network equipment (such as access network equipment, core network function node, core network equipment, etc.) in any of the above methods.

[0275] It should be understood that the division of each unit or module in the above device is only a logical function division, and all or part of them can be integrated into one physical entity or physically separated in actual implementation. In addition, the units or modules in the device can be implemented in the form of processor calling software: for example, the device includes a processor connected with a memory, the memory stores instructions, and the processor calls the instructions stored in the memory to implement any of the above methods or to implement the functions of each unit or module of the device, wherein the processor is a general processor such as a central processing unit (CPU) or a microprocessor, and the memory is a memory in the device or a memory outside the device. Alternatively, the units or modules in the device can be implemented in the form of hardware circuit, and the functions of part or all of the units or modules can be implemented by designing the hardware circuit, and the hardware circuit can be understood as one or more processors; for example, in one implementation, the hardware circuit is an application-specific integrated circuit (ASIC), and the functions of part or all of the units or modules are implemented by designing the logical relationship of elements in the circuit; for another example, in another implementation, the hardware circuit is a programmable logic device (PLD), and taking a field programmable gate array (FPGA) as an example, it can include a large number of logic gate circuits, and the connection relationship between the logic gate circuits is configured by a configuration file, so as to implement the functions of part or all of the units or modules. All units or modules of the above device can be implemented in the form of processor calling software, or all units or modules can be implemented in the form of hardware circuit, or part of the units or modules are implemented in the form of processor calling software, and the remaining part is implemented in the form of hardware circuit.

[0276] In the embodiments of the present disclosure, the processor is a circuit with signal processing capability. In one implementation, the processor can be a circuit with instruction reading and running capability, such as a central processing unit (CPU), a microprocessor, a graphics processing unit (GPU) (which can be understood as a microprocessor), a digital signal processor (DSP), or the like. In another implementation, the processor can implement certain functions through a logical relationship of a hardware circuit, and the logical relationship of the hardware circuit is fixed or can be reconfigured. For example, the processor is a hardware circuit implemented by an application-specific integrated circuit (ASIC) or a programmable logic device (PLD), such as an FPGA. In the reconfigurable hardware circuit, the processor loads a configuration document to implement the configuration of the hardware circuit. It can be understood that the processor loads instructions to implement the functions of the above part or all units or modules. In addition, the hardware circuit can also be designed for artificial intelligence, which can be understood as an ASIC, such as a neural network processing unit (NPU), a tensor processing unit (TPU), a deep learning processing unit (DPU), or the like.

[0277] FIG. 4 is a structural schematic diagram of a communication apparatus according to an embodiment of the present disclosure. The communication apparatus can be applied to a terminal. As shown in FIG. 4, the communication apparatus 4100 can include a processing module 4101. In some embodiments, the processing module 4101 is configured to determine a measurement period based on a first capability of a terminal, wherein the measurement period includes a layer 1 measurement period and / or a layer 3 measurement period, the first capability is a prediction capability of the terminal in a time domain, the measurement period is a period for the terminal to perform measurement, and the prediction capability is a capability of prediction based on measurement.

[0278] In some embodiments, the apparatus described above can further include a transceiving module.

[0279] In some embodiments, the first capability includes a capability of predicting Q layer 1 measurement samples based on P layer 1 measurement samples, P and Q are positive integers; and the measurement period includes a layer 1 measurement period corresponding to a first frequency range, and the measurement period is determined based on a first ratio, the first ratio being a ratio of P to (P+Q).

[0280] In some embodiments, the first capability comprises a capability of predicting one filtered layer 1 measurement result based on P layer 1 measurement samples, P being a positive integer; and the measurement period comprises a layer 1 measurement period corresponding to the first frequency range, the measurement period being determined based on the P.

[0281] In some embodiments, the first capability comprises a capability of predicting one filtered layer 1 measurement result based on K filtered layer 1 measurement results, K being a positive integer; and the measurement period comprises a layer 3 measurement period corresponding to the first frequency range, the measurement period being determined based on the K.

[0282] In some embodiments, the first capability comprises a capability of predicting Q layer 1 measurement samples based on P layer 1 measurement samples, P and Q each being a positive integer; and the measurement period comprises a layer 1 measurement period corresponding to full receive beam sweeping in the second frequency range, the measurement period being determined based on a first ratio, the first ratio being a ratio of the P to (P+Q).

[0283] In some embodiments, the first capability comprises a capability of predicting one filtered layer 1 measurement result based on P layer 1 measurement samples, P being a positive integer; and the measurement period comprises a layer 1 measurement period corresponding to full receive beam sweeping in the second frequency range, the measurement period being determined based on the P.

[0284] In some embodiments, the first capability comprises a capability of predicting one filtered layer 1 measurement result based on K filtered layer 1 measurement results, K being a positive integer; and the measurement period comprises a layer 3 measurement period corresponding to full receive beam sweeping in the second frequency range, the measurement period being determined based on the K.

[0285] In some embodiments, the first capability comprises a capability of predicting Q layer 1 measurement samples based on P layer 1 measurement samples, P and Q each being a positive integer; and the measurement period comprises a layer 1 measurement period corresponding to specific receive beam sweeping in the second frequency range, the measurement period being determined based on a first ratio and a second ratio, the first ratio being a ratio of the P to (P+Q), the second ratio being a ratio of F to G, F being a number of specific receive beams, G being a number of total receive beams, F and G each being a positive integer.

[0286] In some embodiments, the first capability comprises a capability of predicting one filtered layer 1 measurement result based on P layer 1 measurement samples, P being a positive integer; and the measurement period comprises a layer 1 measurement period corresponding to specific receive beam sweeping in the second frequency range, the measurement period being determined based on the P and a second ratio, the second ratio being a ratio of F to G, F being a number of specific receive beams, G being a number of total receive beams, F and G each being a positive integer.

[0287] In some embodiments, the first capability comprises a capability of predicting K filtered layer 1 measurement results based on 1 filtered layer 1 measurement result, K being a positive integer; the measurement period comprises a layer 3 measurement period corresponding to a specific receive beam sweeping in a second frequency range, the measurement period being determined based on the K and a second ratio, the second ratio being a ratio of F and G, F being a number of specific receive beams, G being a number of all receive beams, F and G being positive integers.

[0288] FIG. 5A is a structural schematic diagram of a communication device 5100 according to an embodiment of the present disclosure. The communication device 5100 can be a network device (for example, an access network device, a core network device, etc.), a terminal (for example, a user equipment, etc.), a chip, a chip system, or a processor supporting the network device to implement any of the above methods, or a chip, a chip system, or a processor supporting the terminal to implement any of the above methods. The communication device 5100 can be used to implement the methods described in the above method embodiments, and details can be referred to the descriptions in the above method embodiments.

[0289] As shown in FIG. 5A, the communication device 5100 includes one or more processors 5101. The processor 5101 can be a general purpose processor or a special purpose processor, for example, a baseband processor or a central processing unit. The baseband processor can be used to process communication protocols and communication data, and the central processing unit can be used to control the communication device (for example, a base station, a baseband chip, a terminal device, a terminal device chip, a DU or a CU, etc.), execute programs, and process data of the programs. Optionally, the communication device 5100 is configured to perform any of the above methods. Optionally, the one or more processors 5101 are configured to invoke instructions to cause the communication device 5100 to perform any of the above methods.

[0290] In some embodiments, the communication device 5100 further includes one or more transceivers 5102. When the communication device 5100 includes the one or more transceivers 5102, the transceiver 5102 performs at least one of the communication steps such as transmitting and / or receiving in the above methods, and the processor 5101 performs at least one of the other steps. In an optional embodiment, the transceiver can include a receiver and / or a transmitter, which can be separate or integrated together. Optionally, the terms of transceiver, transceiving unit, transceiver, transceiving circuit, interface circuit, interface, etc. can be replaced with each other, and the terms of transmitter, transmitting unit, transmitter, transmitting circuit, etc. can be replaced with each other, and the terms of receiver, receiving unit, receiver, receiving circuit, etc. can be replaced with each other.

[0291] In some embodiments, the communication device 5100 further comprises one or more memories 5103 for storing data. Alternatively, all or part of the memories 5103 can also be outside the communication device 5100. In optional embodiments, the communication device 5100 can comprise one or more interface circuits 5104. Optionally, the interface circuit 5104 is connected with the memory 5103, and the interface circuit 5104 can be used to receive data from the memory 5103 or other devices, and can be used to send data to the memory 5103 or other devices. For example, the interface circuit 5104 can read the data stored in the memory 5103 and send the data to the processor 5101.

[0292] The communication device 5100 in the above embodiments can be a network device or a terminal, but the scope of the communication device 5100 described in the present disclosure is not limited thereto, and the structure of the communication device 5100 can not be limited by Figure 5A. The communication device can be a standalone device or can be part of a larger device. For example, the communication device can be: 1) a standalone integrated circuit (IC), or a chip, or a chip system or subsystem; (2) a set of one or more ICs, which can optionally include a storage component for storing data, programs; (3) an ASIC, such as a modem; (4) a module that can be embedded in other devices; (5) a receiver, a terminal device, a smart terminal device, a cellular phone, a wireless device, a handset, a mobile unit, a vehicle-mounted device, a network device, a cloud device, an artificial intelligence device, etc.; (6) other devices, etc.

[0293] Figure 5B is a structural schematic diagram of a chip 5200 according to an embodiment of the present disclosure. For the case where the communication device 5100 is a chip or a chip system, the structural schematic diagram of the chip 5200 shown in Figure 5B can be referred to, but is not limited thereto.

[0294] The chip 5200 comprises one or more processors 5201. The chip 5200 is configured to execute any of the above methods.

[0295] In some embodiments, the chip 5200 further comprises one or more interface circuits 5202. Optionally, the terms interface circuit, interface, transceiver pin, etc. can be replaced with each other. In some embodiments, the chip 5200 further comprises one or more memories 5203 for storing data. Optionally, all or part of the memories 5203 can be outside the chip 5200. Optionally, the interface circuit 5202 is connected with the memory 5203, and the interface circuit 5202 can be used to receive data from the memory 5203 or other devices, and the interface circuit 5202 can be used to send data to the memory 5203 or other devices. For example, the interface circuit 5202 can read the data stored in the memory 5203 and send the data to the processor 5201.

[0296] In some embodiments, the interface circuit 5202 performs at least one of the communication steps (for example, step S2101, but not limited thereto) of transmitting and / or receiving and the like in the above method. The interface circuit 5202 performing the communication steps of transmitting and / or receiving and the like in the above method refers to, for example, the interface circuit 5202 performing data interaction between the processor 5201, the chip 5200, the memory 5203, or the transceiver device. In some embodiments, the processor 5201 performs at least one of the other steps.

[0297] The modules and / or devices described in each of the embodiments of the virtual device, the physical device, the chip, and the like can be combined or separated as the case may be. Alternatively, part or all of the steps can also be executed by a plurality of modules and / or devices in cooperation, which is not limited here.

[0298] The disclosure also proposes a storage medium, and the above storage medium stores instructions, which, when executed on the communication device 5100, causes the communication device 5100 to perform any one of the above methods. Alternatively, the above storage medium is an electronic storage medium. Alternatively, the above storage medium is a computer readable storage medium, but is not limited thereto, and it can also be a storage medium readable by other devices. Alternatively, the above storage medium can be a non-transitory storage medium, but is not limited thereto, and it can also be a transitory storage medium.

[0299] The disclosure also proposes a program product, and the above program product is executed by the communication device 5100, so that the communication device 5100 performs any one of the above methods. Alternatively, the above program product is a computer program product.

[0300] The disclosure also proposes a computer program, which, when executed on a computer, causes the computer to perform any one of the above methods.

Claims

1. A communication method characterized by comprising: The method comprises: determining a measurement period based on a first capability of a terminal; wherein the measurement period comprises a layer 1 measurement period and / or a layer 3 measurement period, the first capability is a prediction capability of the terminal in a time domain, and the measurement period is a period for the terminal to perform measurement, and the prediction capability is a capability of prediction based on measurement.

2. The method of claim 1, wherein, The first capability comprises a capability of predicting Q layer 1 measurement samples based on P layer 1 measurement samples, wherein P and Q are positive integers. The measurement period comprises a layer 1 measurement period corresponding to a first frequency range, and the measurement period is determined based on a first ratio, wherein the first ratio is a ratio of P to (P+Q).

3. The method of claim 1, wherein, The first capability comprises a capability of predicting one filtered layer 1 measurement result based on P layer 1 measurement samples, wherein P is a positive integer. The measurement period comprises a layer 1 measurement period corresponding to a first frequency range, and the measurement period is determined based on P.

4. The method of claim 1, wherein, The first capability comprises a capability of predicting one filtered layer 1 measurement result based on K filtered layer 1 measurement results, wherein K is a positive integer. The measurement period comprises a layer 3 measurement period corresponding to a first frequency range, and the measurement period is determined based on K.

5. The method of claim 1, wherein, The first capability comprises a capability of predicting Q layer 1 measurement samples based on P layer 1 measurement samples, wherein P and Q are positive integers. The measurement period comprises a layer 1 measurement period corresponding to full receive beam sweeping in a second frequency range, and the measurement period is determined based on a first ratio, wherein the first ratio is a ratio of P to (P+Q).

6. The method of claim 1, wherein, The first capability comprises a capability of predicting one filtered layer 1 measurement result based on P layer 1 measurement samples, wherein P is a positive integer. The measurement period comprises a layer 1 measurement period corresponding to full receive beam sweeping in a second frequency range, and the measurement period is determined based on P.

7. The method of claim 1, wherein, The first capability comprises a capability of predicting one filtered layer 1 measurement result based on K filtered layer 1 measurement results, wherein K is a positive integer. The measurement period comprises a layer 3 measurement period corresponding to full receive beam sweeping in a second frequency range, and the measurement period is determined based on K.

8. The method of claim 1, wherein, The first capability comprises a capability of predicting Q layer 1 measurement samples based on P layer 1 measurement samples, wherein P and Q are positive integers. The measurement period comprises a layer 1 measurement period corresponding to specific receive beam sweeping in a second frequency range, and the measurement period is determined based on a first ratio and a second ratio, wherein the first ratio is a ratio of P to (P+Q), and the second ratio is a ratio of F to G, wherein F is a number of specific receive beams, G is a number of all receive beams, and F and G are positive integers.

9. The method of claim 1, wherein, The first capability comprises a capability of predicting one filtered layer 1 measurement result based on P layer 1 measurement samples, wherein P is a positive integer. The measurement period comprises a layer 1 measurement period corresponding to specific receive beam sweeping in a second frequency range, and the measurement period is determined based on P and a second ratio, wherein the second ratio is a ratio of F to G, F is a number of specific receive beams, G is a number of all receive beams, and F and G are positive integers.

10. The method of claim 1, wherein, The first capability comprises a capability of predicting one filtered layer 1 measurement result based on K filtered layer 1 measurement results, K being a positive integer; The measurement period comprises a layer 3 measurement period corresponding to specific receive beam sweeping in a second frequency range, the measurement period being determined based on the K and a second ratio, the second ratio being a ratio of F and G, F being a number of specific receive beams, and G being a number of all receive beams, F and G being positive integers.

11. A communications device, characterized by The apparatus comprises: The processing module is configured to determine a measurement period based on a first capability of a terminal, wherein the measurement period comprises a layer 1 measurement period and / or a layer 3 measurement period, the first capability is a prediction capability of the terminal in a time domain, and the measurement period is a period for the terminal to perform measurement.

12. The apparatus of claim 11, wherein, The first capability comprises a capability of predicting Q layer 1 measurement samples based on P layer 1 measurement samples, P and Q being positive integers; The measurement period comprises a layer 1 measurement period corresponding to a first frequency range, the measurement period being determined based on a first ratio, the first ratio being a ratio of P and (P+Q).

13. The apparatus of claim 11, wherein, The first capability comprises a capability of predicting one filtered layer 1 measurement result based on P layer 1 measurement samples, P being a positive integer; The measurement period comprises a layer 1 measurement period corresponding to a first frequency range, the measurement period being determined based on the P.

14. The apparatus of claim 11, wherein, The first capability comprises a capability of predicting one filtered layer 1 measurement result based on K filtered layer 1 measurement results, K being a positive integer; The measurement period comprises a layer 3 measurement period corresponding to a first frequency range, the measurement period being determined based on the K.

15. The apparatus of claim 11, wherein, The first capability comprises a capability of predicting Q layer 1 measurement samples based on P layer 1 measurement samples, P and Q being positive integers; The measurement period comprises a layer 1 measurement period corresponding to full receive beam sweeping in a second frequency range, the measurement period being determined based on a first ratio, the first ratio being a ratio of P and (P+Q).

16. The apparatus of claim 11, wherein, The first capability comprises a capability of predicting one filtered layer 1 measurement result based on P layer 1 measurement samples, P being a positive integer; The measurement period comprises a layer 1 measurement period corresponding to full receive beam sweeping in a second frequency range, the measurement period being determined based on the P.

17. The apparatus of claim 11, wherein, The first capability comprises a capability of predicting one filtered layer 1 measurement result based on K filtered layer 1 measurement results, K being a positive integer; The measurement period comprises a layer 3 measurement period corresponding to full receive beam sweeping in a second frequency range, the measurement period being determined based on the K.

18. The apparatus of claim 11, wherein, The first capability comprises a capability of predicting Q layer 1 measurement samples based on P layer 1 measurement samples, P and Q being positive integers; The measurement period comprises a layer 1 measurement period corresponding to specific receive beam sweeping in a second frequency range, the measurement period being determined based on a first ratio and a second ratio, the first ratio being a ratio of P and (P+Q), and the second ratio being a ratio of F and G, F being a number of specific receive beams, and G being a number of all receive beams, F and G being positive integers.

19. The apparatus of claim 11, wherein, The first capability comprises a capability of predicting one filtered layer 1 measurement result based on P layer 1 measurement samples, P being a positive integer; The measurement period comprises a layer 1 measurement period corresponding to performing specific receive beam sweeping in the second frequency range, and the measurement period is determined based on the P and a second ratio, the second ratio being a ratio of F and G, F being a number of specific receive beams, and G being a number of all receive beams, F and G being positive integers.

20. The apparatus of claim 11, wherein, The first capability comprises a capability of predicting one filtered layer 1 measurement result based on K filtered layer 1 measurement results, K being a positive integer; The measurement period comprises a layer 3 measurement period corresponding to performing specific receive beam sweeping in the second frequency range, and the measurement period is determined based on the K and a second ratio, the second ratio being a ratio of F and G, F being a number of specific receive beams, and G being a number of all receive beams, F and G being positive integers.

21. A terminal, characterized by Comprising: A processing module configured to determine a measurement period based on a first capability of a terminal, the first capability being a time-domain prediction capability of the terminal.

22. A terminal, characterized by Comprising: One or more processors; The terminal is configured to perform the method in any one of claims 1 to 10.

23. A storage medium, the storage medium storing instructions, wherein, The instructions, when executed on the communication device, cause the communication device to perform the method in any one of claims 1 to 10.

24. A program product, characterized by Comprising: A computer program which, when executed by a communication device, causes the communication device to perform the method in any one of claims 1 to 10.

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