Communication method, terminal, network device, communication system, and storage medium

Abstract

The present disclosure relates to a communication method, a terminal, a network device, a communication system, and a storage medium. The method comprises: a terminal sends first information to a network device, the first information being used for indicating a first parameter set supported by the terminal, and the first parameter set being used for artificial intelligence (AI)-based beam prediction. By means of embodiments of the present disclosure, the communication efficiency can be improved.

Description

Communication methods, terminals, network equipment, communication systems and storage media Technical Field

[0001] This disclosure relates to the field of communication technology, and in particular to communication methods, terminals, network devices, communication systems and storage media. Background Technology

[0002] In New Radio (NR), especially in frequency band 2, beam-based transmission and reception are required to ensure coverage. During beam management, network devices configure a set of reference signal resources for beam measurement. The terminal measures the reference signal resources in this set and reports the measurement results to the network device.

[0003] With the development of technology, terminals can perform beam prediction through artificial intelligence (AI) technology.

[0004] Summary of the Invention

[0005] How the terminal can report the set of parameters it supports for AI beam prediction to the network device is a technical problem that needs to be solved.

[0006] This disclosure provides embodiments of a communication method, a terminal, a network device, a communication system, and a storage medium.

[0007] According to a first aspect of the present disclosure, a communication method is proposed, the method comprising: a terminal sending first information to a network device, the first information being used to indicate a first set of parameters supported by the terminal, the first set of parameters being used for beam prediction based on artificial intelligence (AI).

[0008] According to a second aspect of the present disclosure, a communication method is proposed, the method comprising: a network device receiving first information sent by a terminal, the first information being used to indicate a first set of parameters supported by the terminal, the first set of parameters being used for beam prediction based on artificial intelligence (AI).

[0009] According to a third aspect of the present disclosure, a terminal is provided, comprising: a transceiver module for sending first information to a network device, the first information being used to indicate a first set of parameters supported by the terminal, the first set of parameters being used for beam prediction based on artificial intelligence (AI).

[0010] According to a fourth aspect of the present disclosure, a network device is provided, comprising: a transceiver module for receiving first information sent by a terminal, the first information being used to indicate a first set of parameters supported by the terminal, the first set of parameters being used for beam prediction based on artificial intelligence (AI).

[0011] According to a fifth aspect of the present disclosure, a terminal is provided, comprising: one or more processors; wherein the processors are configured to execute the communication method of the first aspect.

[0012] According to a sixth aspect of the present disclosure, a network device is provided, comprising: one or more processors; wherein the processors are configured to perform the communication method of the second aspect.

[0013] According to a seventh aspect of the present disclosure, a communication system is provided, including a terminal and a network device, wherein the terminal is configured to implement the communication method of the first aspect, and the network device is configured to implement the communication method of the second aspect.

[0014] According to an eighth aspect of the present disclosure, a storage medium is provided that stores instructions which, when executed on a communication device, cause the communication device to perform the communication method of the first or second aspect.

[0015] In this embodiment of the present disclosure, the terminal sends first information to the network device. The first information is used to indicate a first set of parameters supported by the terminal. The first set of parameters is used for AI-based beam prediction, enabling the network device to be configured based on the first set of parameters supported by the terminal, thereby improving communication efficiency. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of this disclosure, the accompanying drawings required for the description of the embodiments are introduced below. The following drawings are only some embodiments of this disclosure and do not impose specific limitations on the protection scope of this disclosure.

[0017] Figure 1 is a schematic diagram of the architecture of a communication system according to an embodiment of the present disclosure.

[0018] Figure 2 is an interactive schematic diagram of a communication method according to an embodiment of the present disclosure.

[0019] Figure 3 is a flowchart illustrating a communication method according to an embodiment of the present disclosure.

[0020] Figure 4 is a flowchart illustrating a communication method according to an embodiment of the present disclosure.

[0021] Figure 5 is an interactive schematic diagram of a communication method according to an embodiment of the present disclosure.

[0022] Figure 6A is a schematic diagram of the structure of the terminal proposed in an embodiment of this disclosure.

[0023] Figure 6B is a schematic diagram of the structure of the network device proposed in an embodiment of this disclosure.

[0024] Figure 7A is a schematic diagram of the structure of the communication device proposed in an embodiment of this disclosure.

[0025] Figure 7B is a schematic diagram of the chip structure proposed in an embodiment of this disclosure. Detailed Implementation

[0026] This disclosure provides embodiments of a communication method, a terminal, a network device, a communication system, and a storage medium.

[0027] In a first aspect, embodiments of this disclosure propose a communication method, the method comprising: a terminal sending first information to a network device, the first information being used to indicate a first set of parameters supported by the terminal, the first set of parameters being used for beam prediction based on artificial intelligence (AI).

[0028] In the above embodiments, the terminal sends first information to the network device. The first information is used to indicate a first set of parameters supported by the terminal. The first set of parameters is used for AI-based beam prediction, enabling the network device to be configured based on the first set of parameters supported by the terminal, thereby improving communication efficiency.

[0029] In conjunction with some embodiments of the first aspect, in some embodiments, the first parameter set includes at least one of the following: the beam prediction type supported by the terminal, the beam prediction type including spatial beam prediction and / or temporal beam prediction; the relationship between the first set and the second set supported by the terminal, the first set being the set corresponding to model input data, and the second set being the set corresponding to model output data; the number of beams included in the first set; the number of beams included in the second set; the beam reporting content supported by the terminal; the performance monitoring type supported by the terminal, the performance monitoring type including one of terminal-side performance monitoring, network-side performance monitoring, and hybrid performance monitoring; and the performance metrics supported by the terminal.

[0030] In conjunction with some embodiments of the first aspect, in some embodiments, the beam prediction type supported by the terminal includes time-domain beam prediction, and the first parameter set further includes at least one of the following: a range of the number of first time instances; a minimum number of first time instances; a period of the first time instances; a range of the number of second time instances; a maximum number of second time instances; a range of time intervals between the second time instances and a reference time; a maximum time interval between the second time instances and the reference time; wherein the first time instance is a historical measurement time instance supported by the terminal, and the second time instance is a future prediction time instance supported by the terminal.

[0031] In conjunction with some embodiments of the first aspect, in some embodiments, the performance indicators include at least one of the following: accuracy of beam prediction; accuracy of beam quality prediction; overhead of reference signal resources; overhead of uplink control information; prediction delay; distribution of model input data; and distribution of model output data.

[0032] In conjunction with some embodiments of the first aspect, in some embodiments, the accuracy of the beam quality prediction includes at least one of the following: a first difference, the first difference being the difference between the actual measured value of the first predicted beam and the actual measured value of the first actual beam; a first ratio, the first ratio being the ratio between the number of predictions in which the first difference falls within a preset range and the total number of predictions; a second difference, the second difference being the difference between the actual measured value of the first predicted beam and the predicted measured value of the first predicted beam; and a third difference, the third difference being the difference between a first capacity and a second capacity, wherein the first capacity is determined based on the signal-to-interference-plus-noise ratio (SINR) of the first predicted beam, and the second capacity is determined based on the SINR of the first actual beam.

[0033] In some embodiments, in conjunction with the first aspect, the method further includes: the terminal receiving second information sent by the network device, the second information being used to indicate a second parameter set, the second parameter set being at least one of the first parameter set.

[0034] In some embodiments, in conjunction with the first aspect, the method further includes: the terminal sending third information to the network device, the third information indicating that the second parameter set is unavailable.

[0035] In conjunction with some embodiments of the first aspect, in some embodiments, the method further includes: the terminal sending fourth information to the network device, the fourth information being used to indicate a third parameter set or a fourth parameter set, the third parameter set being a parameter set available to the terminal, and the fourth parameter set being a parameter set available to the terminal after a preset time period.

[0036] In conjunction with some embodiments of the first aspect, in some embodiments, the method further includes: the terminal sending fifth information to the network device, the fifth information including at least one of the following: information indicating that the terminal supports a fifth parameter set, the fifth parameter set being at least one of a second parameter set; indication information of the fifth parameter set; sixth information corresponding to the fifth parameter set, the sixth information being used to indicate parameter information not included in the fifth parameter set; and attribute information of the beam supported by the terminal.

[0037] In some embodiments, in conjunction with the first aspect, the method further includes: the terminal receiving configuration information sent by the network device; the terminal obtaining a beam report based on the configuration information and AI function; and the terminal sending the beam report to the network device.

[0038] Secondly, embodiments of this disclosure propose a communication method, the method comprising: a network device receiving first information sent by a terminal, the first information being used to indicate a first set of parameters supported by the terminal, the first set of parameters being used for beam prediction based on artificial intelligence (AI).

[0039] In conjunction with some embodiments of the second aspect, in some embodiments, the first parameter set includes at least one of the following: the beam prediction type supported by the terminal, the beam prediction type including spatial beam prediction and / or temporal beam prediction; the relationship between the first set and the second set supported by the terminal, the first set being the set corresponding to model input data, and the second set being the set corresponding to model output data; the number of beams included in the first set; the number of beams included in the second set; the beam reporting content supported by the terminal; the performance monitoring type supported by the terminal, the performance monitoring type including one of terminal-side performance monitoring, network-side performance monitoring, and hybrid performance monitoring; and the performance metrics supported by the terminal.

[0040] In conjunction with some embodiments of the second aspect, in some embodiments, the beam prediction type supported by the terminal includes time-domain beam prediction, and the first parameter set further includes at least one of the following: a range of the number of first time instances; a minimum number of first time instances; a period of the first time instances; a range of the number of second time instances; a maximum number of second time instances; a range of time intervals between the second time instances and a reference time; a maximum time interval between the second time instances and the reference time; wherein the first time instance is a historical measurement time instance supported by the terminal, and the second time instance is a future prediction time instance supported by the terminal.

[0041] In conjunction with some embodiments of the second aspect, in some embodiments, the performance indicators include at least one of the following: accuracy of beam prediction; accuracy of beam quality prediction; overhead of reference signal resources; overhead of uplink control information; prediction delay; distribution of model input data; distribution of model output data.

[0042] In conjunction with some embodiments of the second aspect, in some embodiments, the accuracy of the beam quality prediction includes at least one of the following: a first difference, the first difference being the difference between the actual measured value of the first predicted beam and the actual measured value of the first actual beam; a first ratio, the first ratio being the ratio between the number of predictions where the first difference falls within a preset range and the total number of predictions; a second difference, the second difference being the difference between the actual measured value of the first predicted beam and the predicted measured value of the first predicted beam; and a third difference, the third difference being the difference between a first capacity and a second capacity, wherein the first capacity is determined based on the signal-to-interference-plus-noise ratio (SINR) of the first predicted beam, and the second capacity is determined based on the SINR of the first actual beam.

[0043] In conjunction with some embodiments of the second aspect, in some embodiments, the method further includes: the network device sending second information to the terminal, the second information being used to indicate a second parameter set, the second parameter set being at least one of the first parameter set.

[0044] In some embodiments, in conjunction with the second aspect, the method further includes: the network device receiving third information sent by the terminal, the third information being used to indicate that the second parameter set is unavailable.

[0045] In conjunction with some embodiments of the second aspect, in some embodiments, the method further includes: the network device receiving fourth information sent by the terminal, the fourth information being used to indicate a third parameter set or a fourth parameter set, the third parameter set being a parameter set available to the terminal, and the fourth parameter set being a parameter set available to the terminal after a preset time period.

[0046] In conjunction with some embodiments of the second aspect, in some embodiments, the method further includes: the network device receiving fifth information sent by the terminal, the fifth information including at least one of the following: information indicating that the terminal supports a fifth parameter set, the fifth parameter set being at least one of a second parameter set; indication information of the fifth parameter set; sixth information corresponding to the fifth parameter set, the sixth information being used to indicate parameter information not included in the fifth parameter set; and attribute information of the beam supported by the terminal.

[0047] In conjunction with some embodiments of the second aspect, in some embodiments, the method further includes: the network device sending configuration information to the terminal; the network device receiving a beam report sent by the terminal, the beam report being obtained based on the configuration information and AI functions.

[0048] Thirdly, this disclosure provides a terminal, including: a transceiver module, configured to send first information to a network device, the first information being configured to indicate a first set of parameters supported by the terminal, the first set of parameters being configured for beam prediction based on artificial intelligence (AI).

[0049] Fourthly, embodiments of this disclosure propose a network device, including: a transceiver module, configured to receive first information sent by a terminal, the first information being configured to indicate a first set of parameters supported by the terminal, the first set of parameters being configured for beam prediction based on artificial intelligence (AI).

[0050] Fifthly, embodiments of this disclosure provide a terminal comprising: one or more processors; wherein the processors are configured to execute the communication method of the first aspect.

[0051] In a sixth aspect, embodiments of this disclosure provide a network device comprising: one or more processors; wherein the processors are configured to perform the communication method of the second aspect.

[0052] In a seventh aspect, embodiments of this disclosure provide a communication system including a terminal and a network device, wherein the terminal is configured to implement the communication method of the first aspect, and the network device is configured to implement the communication method of the second aspect.

[0053] Eighthly, embodiments of this disclosure provide a storage medium storing instructions that, when executed on a communication device, cause the communication device to perform the communication method of the first or second aspect.

[0054] Ninthly, embodiments of this disclosure provide a program product that, when executed by a communication device, causes the communication device to perform the method as described in the optional implementation of the first or second aspect.

[0055] In a tenth aspect, embodiments of this disclosure provide a computer program that, when run on a computer, causes the computer to perform the methods described in an optional implementation of the first or second aspect.

[0056] Eleventhly, embodiments of this disclosure provide a chip or chip system. The chip or chip system includes processing circuitry configured to perform the methods described in optional implementations of the first or second aspect.

[0057] It is understood that the aforementioned network devices, terminals, communication systems, storage media, program products, computer programs, chips, or chip systems are all used to execute the methods proposed in the embodiments of this disclosure. Therefore, the beneficial effects they can achieve can be referred to the beneficial effects in the corresponding methods, and will not be repeated here.

[0058] This disclosure provides embodiments of a communication method, a terminal, a network device, a communication system, and a storage medium. In some embodiments, the terms "communication method" and "information reporting method," "information receiving method," etc., can be used interchangeably.

[0059] This disclosure is not exhaustive, but merely illustrative of some embodiments, and is not intended to limit the scope of protection of this disclosure. Unless otherwise specified, each step in a particular embodiment can be implemented as an independent embodiment, and the steps can be arbitrarily combined. For example, a solution after removing some steps in a particular embodiment can also be implemented as an independent embodiment, and the order of the steps in a particular embodiment can be arbitrarily interchanged. Furthermore, the optional implementation methods in a particular embodiment can be arbitrarily combined; moreover, the embodiments can be arbitrarily combined, for example, some or all steps of different embodiments can be arbitrarily combined, and a particular embodiment can be arbitrarily combined with the optional implementation methods of other embodiments.

[0060] In each of the disclosed embodiments, unless otherwise specified or in case of logical conflict, the terminology and / or descriptions of the embodiments are consistent and can be referenced by each other. Technical features in different embodiments can be combined to form new embodiments based on their inherent logical relationships.

[0061] The terminology used in the embodiments of this disclosure is for the purpose of describing particular embodiments only and is not intended to limit the scope of this disclosure.

[0062] In this embodiment of the disclosure, unless otherwise stated, elements expressed in the singular form, such as "a," "an," "the," "the," "the," "the," "the," "the," "this," etc., can mean "one and only one," or "one or more," "at least one," etc. For example, when using articles such as "a," "an," "the," etc. in translation, the noun following the article can be understood as either a singular expression or a plural expression.

[0063] In the embodiments disclosed herein, "multiple" refers to two or more.

[0064] In some embodiments, the terms “at least one of”, “one or more”, “a plurality of”, “multiple”, etc., may be used interchangeably.

[0065] In some embodiments, the notation "at least one of A and B", "A and / or B", "A in one case, B in another", "in response to one case A, in response to another case B", etc., may include the following technical solutions depending on the situation: in some embodiments, A (execute A regardless of B); in some embodiments, B (execute B regardless of A); in some embodiments, execution is selected from A and B (A and B are selectively executed); in some embodiments, A and B (both A and B are executed). The same applies when there are more branches such as A, B, C, etc.

[0066] In some embodiments, the notation "A or B" may include the following technical solutions, depending on the situation: in some embodiments, A (execution of A regardless of B); in some embodiments, B (execution of B regardless of A); in some embodiments, execution is selected from A and B (A and B are selectively executed). The same applies when there are more branches such as A, B, C, etc.

[0067] The prefixes "first," "second," etc., used in the embodiments of this disclosure are merely for distinguishing different descriptive objects and do not impose restrictions on the position, order, priority, quantity, or content of the descriptive objects. The description of the descriptive objects is found in the claims or the context of the embodiments, and the use of prefixes should not constitute unnecessary restrictions. For example, if the descriptive object is a "field," the ordinal numbers preceding "field" in "first field" and "second field" do not restrict the position or order of the "fields." "First" and "second" do not restrict whether the "fields" they modify are in the same message, nor do they restrict the order of "first field" and "second field." Similarly, if the descriptive object is a "level," the ordinal numbers preceding "level" in "first level" and "second level" do not restrict the priority between "levels." Furthermore, the number of descriptive objects is not limited by ordinal numbers and can be one or more. For example, in "first device," the number of "devices" can be one or more. Furthermore, the objects modified by different prefixes can be the same or different. For example, if the object being described is "device", then "first device" and "second device" can be the same device or different devices, and their types can be the same or different. Similarly, if the object being described is "information", then "first information" and "second information" can be the same information or different information, and their content can be the same or different.

[0068] In some embodiments, “including A,” “containing A,” “for indicating A,” and “carrying A” can be interpreted as directly carrying A or indirectly indicating A.

[0069] In some embodiments, the terms “in response to…”, “in response to determining…”, “in the case of…”, “when…”, “if…”, “if…”, etc., can be used interchangeably.

[0070] 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,” and “above” can be used interchangeably, as can the terms “less than,” “less than or equal to,” “not greater than,” “less than,” “less than or equal to,” “not more than,” “lower than,” “lower than or equal to,” “not higher than,” and “below”.

[0071] In some embodiments, devices, etc., can be interpreted as physical or virtual, and their names are not limited to the names recorded in the embodiments. Terms such as “device”, “equipment”, “circuit”, “network element”, “node”, “function”, “unit”, “section”, “system”, “network”, “chip”, “chip system”, “entity”, and “subject” can be used interchangeably.

[0072] In some embodiments, "network" can be interpreted as devices included in a network (e.g., access network devices, core network devices, etc.).

[0073] 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," and "bandwidth part (BWP)" can be used interchangeably.

[0074] 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", and "client" can be used interchangeably.

[0075] In some embodiments, access network devices, core network devices, or network devices can be replaced by terminals. For example, embodiments of this disclosure can also be applied to structures where communication between access network devices, core network devices, or network devices and terminals is replaced by communication between multiple terminals (e.g., device-to-device (D2D), vehicle-to-everything (V2X), etc.). In this case, the structure can also be configured such that the terminal has all or part of the functions of the access network device. Furthermore, terms such as "uplink" and "downlink" can be replaced with terms corresponding to communication between terminals (e.g., "sidelink"). For example, uplink channel, downlink channel, etc., can be replaced with sidelink channel, and uplink link, downlink, etc., can be replaced with sidelink link.

[0076] In some embodiments, the terminal may be replaced by an access network device, a core network device, or a network device. In this case, the access network device, core network device, or network device may also be configured to have all or some of the functions of the terminal.

[0077] In some embodiments, the acquisition of data, information, etc., may comply with the laws and regulations of the country where the location is situated.

[0078] In some embodiments, data, information, etc., may be obtained with the user's consent.

[0079] Furthermore, each element, each row, or each column in the table of this 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.

[0080] Figure 1 is a schematic diagram of the architecture of a communication system according to an embodiment of the present disclosure.

[0081] As shown in Figure 1, the communication system 100 includes a terminal 101 and a network device 102.

[0082] In some embodiments, terminal 101 may be user equipment (UE), and terminal 101 includes, for example, at least one of the following: mobile phone, wearable device, Internet of Things device, car with communication function, smart car, tablet computer, computer with wireless transceiver function, virtual reality (VR) terminal device, augmented reality (AR) terminal device, wireless terminal device in industrial control, wireless terminal device in self-driving, wireless terminal device in remote medical surgery, wireless terminal device in smart grid, wireless terminal device in transportation safety, wireless terminal device in smart city, and wireless terminal device in smart home, but is not limited thereto.

[0083] In some embodiments, network device 102 may be a functional network element in a core network device. The core network device may be a single device, including a first network element, a second network element, etc., or it may be multiple devices or a group of devices, each including all or part of the first network element, the second network element, etc. Network elements may be virtual or physical. The core network may include, for example, at least one of an Evolved Packet Core (EPC), a 5G Core Network (5GCN), and a Next Generation Core (NGC).

[0084] In some embodiments, network device 102 may include at least one of access network device and core network device.

[0085] In some embodiments, the access network device is, for example, a node or device that connects a terminal to a wireless network. The access network device may include, but is not limited to, at least one of the following in a 5G communication system: evolved Node B (eNB), next-generation eNB (ng-eNB), next-generation Node B (gNB), node B (NB), home node B (HNB), home evolved node B (HeNB), radio backhaul device, radio network controller (RNC), base station controller (BSC), base transceiver station (BTS), base band unit (BBU), mobile switching center, base station in a 6G communication system, open RAN, cloud RAN, base station in other communication systems, and access node in a Wi-Fi system.

[0086] In some embodiments, the technical solutions of this disclosure can be applied to the Open RAN architecture. In this case, the interfaces between or within access network devices involved in the embodiments of this disclosure can be transformed into internal interfaces of Open RAN. The processes and information interactions between these internal interfaces can be implemented by software or programs.

[0087] In some embodiments, the access network device may be composed of a central unit (CU) and a distributed unit (DU). The CU may also be called a control unit. The CU-DU structure can separate the protocol layer of the access network device. Some of the protocol layer functions are centrally controlled by the CU, while the remaining part or all of the protocol layer functions are distributed in the DU and centrally controlled by the CU. However, this is not the only possibility.

[0088] In some embodiments, a core network device may be a single device comprising one or more network elements, or it may be multiple devices or a group of devices, each comprising all or part of the aforementioned one or more network elements. Network elements may be virtual or physical. The core network may include, for example, at least one of an Evolved Packet Core (EPC), a 5G Core Network (5GCN), or a Next Generation Core (NGC).

[0089] It is understood that the communication system described in this disclosure is for the purpose of more clearly illustrating the technical solutions of this disclosure, and does not constitute a limitation on the technical solutions proposed in this disclosure. As those skilled in the art will know, with the evolution of system architecture and the emergence of new business scenarios, the technical solutions proposed in this disclosure are also applicable to similar technical problems.

[0090] The following embodiments of this disclosure can be applied to the communication system 100 shown in FIG1, or to some of the main bodies, but are not limited thereto. The main bodies shown in FIG1 are illustrative. The communication system may include all or some of the main bodies in FIG1, or may include other main bodies outside of FIG1. ​​The number and form of each main body are arbitrary. Each main body may be physical or virtual. The connection relationship between the main bodies is illustrative. The main bodies may not be connected or may be connected. The connection can be in any way, it can be a direct connection or an indirect connection, it can be a wired connection or a wireless connection.

[0091] The embodiments disclosed herein can be applied to Long Term Evolution (LTE), LTE-Advanced (LTE-A), LTE-Beyond (LTE-B), SUPER 3G, IMT-Advanced, 4th generation mobile communication system (4G), 5th generation mobile communication system (5G), 5G new radio (NR), Future Radio Access (FRA), New-Radio Access Technology (RAT), New Radio (NR), New radio access (NX), Future generation radio access (FX), Global System for Mobile communications (GSM), CDMA2000, Ultra Mobile Broadband (UMB), IEEE 802.11 (Wi-Fi), IEEE 802.16 (WiMAX), and IEEE 802.20, Ultra-Wideband (UWB), Bluetooth (a registered trademark), Public Land Mobile Network (PLMN) networks, Device-to-Device (D2D) systems, Machine-to-Machine (M2M) systems, Internet of Things (IoT) systems, Vehicle-to-Everything (V2X) systems, systems utilizing other communication methods, and next-generation systems built upon them, etc. Furthermore, multiple systems can be combined (e.g., a combination of LTE or LTE-A with 5G).

[0092] In NR, especially when the communication frequency band is in frequency range 2, high-frequency channels attenuate quickly, so beam-based transmission and reception are required to ensure coverage.

[0093] During beam management, the network device configures a set of reference signal resources for beam measurement. The terminal measures the reference signal resources in this set. The terminal reports the identifiers (IDs) of the X strongest reference signal resources, along with their corresponding Layer 1 reference signal received power (L1-RSRP) and / or Layer 1 signal-to-interference-plus-noise ratio (L1-SINR), to the network device, where X is a positive integer.

[0094] In related technologies, it is assumed that the network device's set of reference signal resources includes X reference signal resources, each corresponding to a different transmit beam of the network device. For each reference signal resource, the terminal needs to use all receive beams to measure the reference signal, obtain the beam measurement quality corresponding to each receive beam, and determine one or more of the best beam measurement qualities. Therefore, the number of beam pairs that the terminal needs to measure is M*N. Here, M represents the number of transmit beams of the network device, N is the number of receive beams of the terminal, and * represents multiplication.

[0095] In some embodiments, an implementation process for beam prediction based on AI (Artificial Intelligence) models and / or AI functions is provided. Here, AI functions can be considered as one or more AI models that achieve a similar function or purpose.

[0096] In some embodiments, the AI ​​model used for beam prediction may be referred to as a beam prediction model. Of course, it may also be called a beam prediction AI model, a prediction AI model, a prediction beam model, etc. This disclosure does not limit the name of such AI model.

[0097] In some implementations, when the AI ​​model is for spatial prediction, the L1-RSRP of the terminal measurement set (set) B (which may also include beam or beam pair ID) is input into the AI ​​model to predict the L1-RSRP of the best beam and / or beam pair in set A, and / or the identifier of the best beam and / or beam pair in set A.

[0098] The relationship between set B and set A includes the following two types:

[0099] The first type of relationship is that set B is a subset of set A. For example, if set A contains 32 reference signal resources (each reference signal resource corresponds to a beam direction), then set B contains N partial reference signal resources. For instance, set B contains 8 of the 32 reference signal resources, i.e., N = 8.

[0100] The second relationship is as follows: set B is a wide beam, and set A is a narrow beam. For example, set A contains 32 reference signal resources (each reference signal resource corresponds to a beam direction, and the 32 reference signal resources cover a 120-degree direction). Set B contains another Y reference signal resources, for example, Y=8. These Y reference signal resources also cover a 120-degree direction, meaning that the beam direction of each reference signal resource in set B covers the beam directions of multiple reference signal resources in set A. This can be understood as a QCL (quasi-co-location) type (Type) D relationship between the 32 / Y reference signal resources in set A and one reference signal resource in set B.

[0101] Understandably, the examples of the first and second relationships described above only depict the case of the transmitted beam. When considering beam pairs that include both transmitted and received beams, the terminal's received beam must also be considered. For example, with 32 transmitted beams and 4 received beams, set A would be 32*4 beam pairs, and set B could be 32 beam pairs, 16 beam pairs, and so on.

[0102] In some embodiments, when the AI ​​model is a time-domain prediction, the terminal measures the L1-RSRP of historical time set B, inputs it into the AI ​​model, and predicts the L1-RSRP of future time set A. Besides the two relationships mentioned above, there is another relationship between set B and set A: set B and set A are the same.

[0103] If beam prediction is based on an AI model, then the reference signal for future moments does not need to be sent; that is, beam information can be obtained based on the output of the AI ​​model and reported to the network equipment.

[0104] If beam prediction is performed using methods from related technologies, reference signals for future moments also need to be transmitted. The terminal measures the reference signals for future moments and obtains beam information, which is then reported to the base station. Therefore, during model performance monitoring, for spatial beam prediction, network devices need to periodically transmit the transmitted beams in set B and set A, and the terminal needs to measure all beams or beam pairs in set B and set A.

[0105] In related technologies, lifecycle management can be performed based on functionality. That is, the terminal only informs the network device that it supports a certain function, without needing to specify whether it can support one or multiple models under that function. When the network device instructs the terminal to activate the function, the terminal can independently determine which model to activate. Furthermore, the terminal can switch between different models under that function without informing the network.

[0106] In some embodiments, the terminal can send a set of supported feature groups / parameters (FG) based on capability signaling (e.g., Radio Resource Control (RRC) signaling) to inform the network device of the functions the terminal supports. When the network device needs to activate AI / ML functions and / or models, it can send a set of parameter groups, which mainly describe the configuration parameters preferred by the network side. The terminal then provides feedback on which parameter groups it can support, i.e., which parameter groups the available functions and / or models on the terminal side can support. The specific definition of the parameter groups, how the terminal provides feedback on the supported parameter groups, and how the terminal reports information when it cannot support any parameter groups are technical issues that need to be addressed.

[0107] This disclosure provides a communication method in which a terminal sends first information to a network device. The first information is used to indicate a first set of parameters supported by the terminal. The first set of parameters is used for AI-based beam prediction, enabling the network device to be configured based on the first set of parameters supported by the terminal, thereby improving communication efficiency.

[0108] Figure 2 is an interactive schematic diagram of a communication method according to an embodiment of the present disclosure. As shown in Figure 2, the embodiments of the present disclosure relate to a communication method, which includes:

[0109] Step S2101: The terminal sends the first information to the network device.

[0110] In some embodiments, the network device receives first information sent by the terminal.

[0111] In some embodiments, the first information is used to indicate a first set of parameters supported by the terminal, the first set of parameters being used for beam prediction based on AI / Machine Learning (ML).

[0112] In some embodiments, the first parameter set includes at least one of the following: the beam prediction type supported by the terminal, including spatial beam prediction and / or temporal beam prediction; the relationship between the first set and the second set supported by the terminal, wherein the first set is the set corresponding to the model input data and the second set is the set corresponding to the model output data; the number of beams included in the first set; the number of beams included in the second set; the beam reporting content supported by the terminal; the performance monitoring type supported by the terminal, including one of terminal-side performance monitoring, network-side performance monitoring, and hybrid performance monitoring; and the performance metric supported by the terminal.

[0113] In some embodiments, there may be one or more first parameter sets, and each first parameter set may include one or more parameters, and each first parameter set may include at least one of the above-mentioned items.

[0114] In some embodiments, the beam prediction type supported by the terminal may be spatial beam prediction, temporal beam prediction, or both.

[0115] In some embodiments, the first set is the set corresponding to the model input data, which can be referred to as set B. The first set is obtained by the actual measurements performed by the terminal. The second set is the set corresponding to the model output data, which can be referred to as set A. The terminal can input the measurement data of the first set into the AI / ML model to obtain the prediction data corresponding to the second set. The relationship between the first set and the second set can be one of the following: the first set is a subset of the second set; the first set is different from the second set, for example, the first set includes wide beams while the second set includes narrow beams; the first set is the same as the second set (for cases where the terminal supports temporal beam prediction).

[0116] In some embodiments, the number of beams included in the first set can be represented by the maximum and / or minimum number of beams included in the first set.

[0117] In some embodiments, the number of beams included in the second set can be represented by the maximum and / or minimum number of beams included in the second set.

[0118] In some embodiments, the beam report content supported by the terminal may include at least one of the following: L1-RSRP; beam ID or reference signal (RS) ID; the probability that the beam corresponding to each beam ID or RS ID is the best beam.

[0119] In some embodiments, the performance monitoring types supported by the terminal include one of terminal-side performance monitoring, network-side performance monitoring, and hybrid performance monitoring.

[0120] Terminal-side performance monitoring refers to the process where the terminal measures and obtains measurement information from a first set and a second set. The measurement information from the first set is input into an AI model to obtain prediction information from the second set. The measurement information from the second set and the prediction information are compared to obtain performance indicators. When the performance indicators meet preset conditions, the terminal determines to activate / deactivate a function or model. The terminal can inform the network device of its decision to activate / deactivate the function or model. Alternatively, the terminal can wait for a response from the network device before activating / deactivating the function or model. The response from the network device can include agreement, disagreement, or instructions for the terminal to activate or deactivate.

[0121] Network-side performance monitoring refers to the process where the terminal sends measurement and prediction information from a second set to the network device, which then calculates performance metrics, determines whether to activate or deactivate the function or model, and instructs the terminal on the decision.

[0122] Hybrid performance monitoring refers to the terminal comparing the measurement information and prediction information of a second set to obtain performance indicators, and then reporting the performance indicators to the network device. The network device determines whether to activate or deactivate the function or model and instructs the terminal accordingly.

[0123] In some embodiments, the performance metrics include at least one of the following: accuracy of beam prediction; accuracy of beam quality prediction; overhead of reference signal resources; overhead of uplink control information; prediction delay; distribution of model input data; and distribution of model output data.

[0124] In some embodiments, the terminal can predict the K strongest beams or K beam pairs in a second set (e.g., set A) based on AI functions or AI models, where K is a positive integer. The accuracy of beam prediction is a parameter indicating whether the strongest beam predicted by the terminal is consistent with the actual strongest beam. The consistency between the predicted strongest beam and the actual strongest beam can be that the predicted strongest beam is included in the actual N strongest beams or that the actual strongest beam is included in the predicted K strongest beams. The strongest beam can be the strongest beam in L1-RSRP or L1-SINR. The accuracy of beam prediction can be a ratio, such as the ratio of the number of correct predictions to the total number of predictions. A correct prediction means that the predicted strongest beam is consistent with the actual strongest beam.

[0125] In some embodiments, the terminal can predict beam quality based on AI functions or AI models. The accuracy of beam quality prediction includes at least one of the following: a first difference, which is the difference between the actual measured value of the first predicted beam and the actual measured value of the first actual beam; a first ratio, which is the ratio between the number of predictions where the first difference falls within a preset range and the total number of predictions; a second difference, which is the difference between the actual measured value of the first predicted beam and the predicted measured value of the first predicted beam; and a third difference, which is the difference between a first capacity and a second capacity, wherein the first capacity is determined based on the signal-to-interference-plus-noise ratio (SINR) of the first predicted beam, and the second capacity is determined based on the SINR of the first actual beam.

[0126] The first predicted beam can be the strongest predicted beam, and the first actual beam can be the strongest actual beam. Measurements can include, but are not limited to, L1-RSRP and L1-SINR measurements.

[0127] The first difference is the difference between the actual measured value of the first predicted beam and the actual measured value of the first actual beam. For example, the terminal can obtain the predicted strongest beam based on AI functions or AI models, and obtain the actual L1-RSRP value of the predicted strongest beam, and the actual L1-RSRP value of the actual strongest beam. The first difference is obtained based on the actual L1-RSRP value of the predicted strongest beam and the actual L1-RSRP value of the actual strongest beam. This first difference characterizes the accuracy of the beam quality prediction. Characterizing the accuracy of the beam quality prediction through this first difference can be done by calculating the proportion of the first difference that is lower than a threshold value, or the proportion that is higher than a threshold value.

[0128] The first ratio is determined based on the first difference and a preset range. The first ratio is the ratio of the number of predictions where the first difference falls within the preset range to the total number of predictions. The preset range can be set according to actual conditions, for example, it could be 1 dB. The first ratio can be calculated based on multiple predictions by the model. For example, if multiple first differences are obtained from multiple predictions by the model, the ratio of the number of times these first differences are within 1 dB to the total number of predictions is the first ratio.

[0129] The second difference is the difference between the actual measured value of the first predicted beam and the predicted measured value of the first predicted beam. For example, the terminal can obtain the predicted strongest beam based on AI functions or AI models, obtain the actual L1-RSRP value of the predicted strongest beam, and obtain the predicted L1-RSRP value of the predicted strongest beam based on AI functions or AI models. The second difference is obtained based on the actual L1-RSRP value and the predicted L1-RSRP value of the predicted strongest beam, and this second difference characterizes the accuracy of the beam quality prediction. Characterizing the accuracy of the beam quality prediction through this second difference can be achieved by calculating the proportion of the second difference that is below a threshold value, or the proportion that is above a threshold value.

[0130] The third difference is the difference between the first capacity and the second capacity. The terminal can obtain the predicted strongest beam based on AI functions or AI models and obtain the SINR of the predicted strongest beam. The first capacity is calculated based on Shannon's formula. The terminal can obtain the SINR of the actual strongest beam and calculate the second capacity based on Shannon's formula. The difference between the first capacity and the second capacity is the third difference, which characterizes the accuracy of beam quality prediction.

[0131] In some embodiments, the overhead of reference signal resources refers to how much reference signal resources the model requires. Factors affecting the overhead of reference signal resources include the size of the first set corresponding to the model input and the number of historical measurement time instances during time-domain prediction.

[0132] In some embodiments, the overhead of uplink control information refers to the signaling overhead of the terminal reporting to the network device. For example, when the model is deployed on the network side, the terminal sends the measurement results of the first set to the network device. In this case, the overhead of uplink control information refers to the signaling overhead of the terminal reporting the measurement results of the first set.

[0133] In some embodiments, the distribution of model input data and the distribution of model output data can be, for example, the L1-RSRP distribution.

[0134] In some embodiments, where the beam prediction type supported by the terminal includes time-domain beam prediction, the first parameter set further includes at least one of the following: a range of the number of first time instances; a minimum number of first time instances; a period of the first time instances; a range of the number of second time instances; a maximum number of second time instances; a range of time intervals between the second time instances and a reference time; and a maximum time interval between the second time instances and the reference time; wherein the first time instance is a historical measurement time instance supported by the terminal, and the second time instance is a future prediction time instance supported by the terminal.

[0135] In this embodiment, the first time instance is a historical measurement time instance supported by the terminal, meaning the terminal performs actual measurements within the first time instance; the second time instance is a future prediction time instance supported by the terminal, meaning the terminal makes predictions based on the measurement results obtained within the first time instance to obtain the predicted value corresponding to the second time instance. The first time instance can be a time period or a moment. The second time instance can be a time period or a moment.

[0136] In this embodiment of the disclosure, the range of the number of first time instances refers to the range of the number of first time instances supported by the terminal, for example, the range is [T1, T2], where T1 and T2 are both positive integers, T1 < T2, that is, the minimum number of first time instances that the terminal can support is T1, and the maximum number is T2. That is, the terminal can perform beam prediction based on the measurement results corresponding to at least T1 first time instances, and the terminal can perform beam prediction based on the measurement results corresponding to at most T2 first time instances.

[0137] In this embodiment of the disclosure, the minimum number of first time instances refers to the minimum number of first time instances supported by the terminal. For example, the minimum value is T1, that is, the minimum number of first time instances that the terminal can support is T1, that is, the terminal can perform beam prediction based on the measurement results corresponding to at least T1 first time instances.

[0138] In this embodiment of the disclosure, the period of the first time instance refers to the time interval between two adjacent first time instances.

[0139] In this embodiment of the disclosure, the range of the number of second time instances refers to the range of the number of second time instances supported by the terminal, for example, the range is [T3, T4], where T3 and T4 are both positive integers, T3 < T4, that is, the minimum number of second time instances that the terminal can support is T3, and the maximum number is T4. That is, the terminal can predict the measurement results corresponding to at least T3 second time instances, and the terminal can predict the measurement results corresponding to at most T4 second time instances.

[0140] In this embodiment of the disclosure, the maximum number of second time instances refers to the maximum number of second time instances supported by the terminal. For example, the maximum number is T4, which means that the terminal can support a maximum of T4 second time instances, and the terminal can predict the measurement results corresponding to a maximum of T4 second time instances.

[0141] In this embodiment of the disclosure, the first parameter set may include a range of the number of first time instances supported by the terminal, or a minimum number of first time instances, or a period of the first time instances. The first parameter set may include a range of the number of second time instances supported by the terminal, or a maximum number of second time instances. The first parameter set may include a range of time intervals between the second time instances supported by the terminal and a reference time, or a maximum time interval between the second time instances and the reference time, wherein the reference time may be the last first time instance, i.e., the last historical measurement time instance.

[0142] Optionally, the reference time may be the transmission time of one of the reference signal resources corresponding to the last time instance in the first time instance; the reference time may also be the time of transmitting the beam report; this disclosure does not limit this.

[0143] In step S2102, the network device sends the second information to the terminal.

[0144] In some embodiments, the terminal receives second information sent by the network device.

[0145] In some embodiments, the second information is used to indicate a second parameter set, which is at least one of the parameters in the first parameter set.

[0146] In some embodiments, there may be one or more second parameter sets, each of which may include one or more parameters. Each second parameter set is one of the first parameter sets. That is, one or more second parameter sets may be determined from one or more first parameter sets, and each second parameter set may include at least one of the contents of the first parameter set.

[0147] In some embodiments, the second parameter set may be a parameter set recommended by the network device, or the second parameter set may be a parameter set corresponding to the current configuration of the network device.

[0148] In some embodiments, the terminal may determine the information to be reported to the network device based on the second parameter set. If the second parameter set includes a parameter set available to the terminal, then step S2105 is executed; if the second parameter set does not include a parameter set available to the terminal, then steps S2103 and S2104 are executed.

[0149] In step S2103, the terminal sends third information to the network device.

[0150] In some embodiments, the network device receives third information sent by the terminal.

[0151] In some embodiments, the third information is used to indicate that the second parameter set is unavailable.

[0152] In some embodiments, the terminal determines whether the second parameter set is applicable. If the second parameter set is not applicable, the terminal sends third information to the network device to inform the network device that the second parameter set is not applicable.

[0153] In some embodiments, the unavailability of the second parameter set may be due to the terminal-side function or model corresponding to the second parameter set not being ready, or the terminal currently having insufficient power to meet the requirements for the operation of the function or model.

[0154] In some embodiments, the third information may include information indicating that the second parameter set is unavailable (e.g., information indicating "none"). The third information may also include, for each bit in the second parameter set, a bit value of either "0" or "1" for each bit when all second parameter sets are unavailable.

[0155] Step S2104: The terminal sends the fourth information to the network device.

[0156] In some embodiments, the network device receives fourth information sent by the terminal.

[0157] In some embodiments, the fourth information and the third information are contained in one information, or the fourth information is contained in the third information.

[0158] In other embodiments, the fourth and third information are sent separately.

[0159] In some embodiments, the fourth information is used to indicate either a third parameter set or a fourth parameter set. The third parameter set is a parameter set available to the terminal, and the fourth parameter set is a parameter set available to the terminal after a preset time period. Wherein, a parameter set available to the terminal indicates that the function or model corresponding to the third parameter set is ready on the terminal side and can be activated at any time. A parameter set available to the terminal after a preset time period indicates that after the preset time period, the terminal side can prepare the function or model corresponding to the fourth parameter set, and the fourth parameter set becomes an available parameter set.

[0160] In some embodiments, if the second parameter set is unavailable, the terminal sends a parameter set available to the network device or a parameter set available after a preset time period to facilitate the network device in subsequently determining the configuration information.

[0161] Step S2105: The terminal sends the fifth information to the network device.

[0162] In some embodiments, the network device receives the fifth information sent by the terminal.

[0163] In some embodiments, the terminal determines whether the second parameter set is available. If an available parameter set exists, the terminal sends a fifth message to the network device to inform the network device that the second parameter set is available. Here, "second parameter set available" means that for at least one parameter set in the second parameter set, the terminal has a prepared function or model ready to be activated and used at any time.

[0164] In some embodiments, the fifth information includes at least one of the following: information indicating that the terminal supports a fifth parameter set, wherein the fifth parameter set is at least one of the second parameter set; indication information of the fifth parameter set; sixth information corresponding to the fifth parameter set, wherein the sixth information is used to indicate parameter information not included in the fifth parameter set; and attribute information of the beam supported by the terminal.

[0165] In some embodiments, there may be one or more fifth parameter sets, each fifth parameter set including one or more parameters, and the fifth parameter set is one or more parameter sets available to the terminal in the second parameter set.

[0166] The terminal is instructed to support at least one fifth parameter set, such as information indicating "yes".

[0167] The indication information of the fifth parameter set may include, but is not limited to, the identifier of the fifth parameter set.

[0168] In some embodiments, the second parameter set contains N parameter sets, and the fifth information may also contain N bits, each bit corresponding to one parameter set in the second parameter set. A bit displaying "0" indicates that the parameter set corresponding to that bit is unavailable, and a bit displaying "1" indicates that the parameter set corresponding to that bit is available. Conversely, a bit displaying "0" indicates that the parameter set corresponding to that bit is available, and a bit displaying "1" indicates that the parameter set corresponding to that bit is unavailable. This disclosure does not impose any limitations on this.

[0169] The sixth information is used to indicate parameter information not included in the fifth parameter set, such as the number of beams in the first set, the number of beams in the second set, the number of historical measurement time instances, the number of future prediction time instances, and the duration of future prediction time instances.

[0170] The attribute information of the beams supported by the terminal may include beam direction, beamwidth, etc.

[0171] Step S2106: The network device sends configuration information to the terminal.

[0172] In some embodiments, the terminal receives configuration information sent by the network device.

[0173] In some embodiments, the network device may determine configuration information based on at least one of the third, fourth, and fifth information reported by the terminal.

[0174] In step S2107, the terminal obtains a beam report based on configuration information and AI function.

[0175] In some embodiments, the terminal may determine a first set based on configuration information, measure the beams in the first set to obtain measurement results, process the measurement results based on AI functions or AI models to obtain prediction data corresponding to a second set, and obtain a beam report based on the prediction data.

[0176] Step S2108: The terminal sends a beam report to the network device.

[0177] In some embodiments, the network device receives a beam report sent by the terminal.

[0178] The communication method involved in the embodiments of this disclosure may include at least one of steps S2101 to S2108. For example, step S2101 may be implemented as a standalone embodiment, step S2101+S2102 may be implemented as a standalone embodiment, step S2101+S2102+S2103 may be implemented as a standalone embodiment, step S2101+S2102+S2103+S2104 may be implemented as a standalone embodiment, and step S2101+S2102+S2105 may be implemented as a standalone embodiment, but is not limited thereto.

[0179] In some embodiments, steps S2103 and S2104 are optional, and one or more of these steps may be omitted or substituted in different embodiments.

[0180] In some embodiments, step S2105 is optional, and one or more of these steps may be omitted or substituted in different embodiments.

[0181] In some embodiments, steps S2106, S2107, and S2108 are optional, and one or more of these steps may be omitted or substituted in different embodiments.

[0182] In some embodiments, other optional implementations described before or after the specification corresponding to FIG2 may be referred to.

[0183] In some embodiments, the names of information, etc., are not limited to the names described in the embodiments. Terms such as "information", "message", "signal", "signaling", "report", "configuration", "indication", "instruction", "command", "channel", "parameter", "domain", "field", "symbol", "symbol", "codebook", "codeword", "codepoint", "bit", "data", "program", and "chip" can be used interchangeably.

[0184] In some embodiments, terms such as “moment,” “point in time,” “time,” and “time location” can be used interchangeably, as can terms such as “duration,” “segment,” “time window,” “window,” and “time.”

[0185] In some embodiments, “get,” “obtain,” “receive,” “transmit,” “bidirectional transmission,” and “send and / or receive” can be used interchangeably and can be interpreted as receiving from other entities, obtaining from protocols, obtaining from higher layers, obtaining through self-processing, or autonomous implementation, among other meanings.

[0186] In some embodiments, terms such as “send,” “transmit,” “report,” “distribute,” “transmit,” “bidirectional transmission,” “send and / or receive” can be used interchangeably.

[0187] In some embodiments, terms such as "certain," "preset," "default," "set," "indicated," "a certain," "any," and "first" can be used interchangeably. "Certain A," "preset A," "default A," "set A," "indicated A," "a certain A," "any A," and "first A" can be interpreted as A pre-defined in a protocol or the like, or as A obtained through setting, configuration, or instruction, or as specific A, a certain A, any A, or first A, but are not limited thereto.

[0188] 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), or by a comparison of numerical values ​​(e.g., a comparison with a predetermined value), but is not limited thereto.

[0189] In some embodiments, "not expecting to receive" can be interpreted as not receiving on time domain resources and / or frequency domain resources, or as not performing subsequent processing on the data after receiving it; "not expecting to send" can be interpreted as not sending, or as sending but not expecting the receiver to respond to the sent content.

[0190] Figure 3 is a flowchart illustrating a communication method according to an embodiment of the present disclosure. As shown in Figure 3, the present disclosure relates to a communication method, which includes:

[0191] Step S3101: Send the first message.

[0192] The optional implementation of step S3101 can be found in the optional implementation of step S2101 in Figure 2 and other related parts in the embodiments involved in Figure 2, which will not be repeated here.

[0193] In some embodiments, the terminal sends first information to the network device.

[0194] Step S3102: Obtain the second information.

[0195] The optional implementation of step S3102 can be found in the optional implementation of step S2102 in Figure 2 and other related parts in the embodiments involved in Figure 2, which will not be repeated here.

[0196] In some embodiments, the terminal receives second information sent to the network device.

[0197] Step S3103: Send the third message.

[0198] The optional implementation of step S3103 can be found in the optional implementation of step S2103 in Figure 2 and other related parts in the embodiments involved in Figure 2, which will not be repeated here.

[0199] In some embodiments, the terminal sends third information to the network device.

[0200] Step S3104: Send the fourth message.

[0201] The optional implementation of step S3104 can be found in the optional implementation of step S2104 in Figure 2 and other related parts in the embodiments involved in Figure 2, which will not be repeated here.

[0202] In some embodiments, the terminal sends fourth information to the network device.

[0203] Step S3105: Send the fifth message.

[0204] The optional implementation of step S3105 can be found in the optional implementation of step S2105 in Figure 2 and other related parts in the embodiments involved in Figure 2, which will not be repeated here.

[0205] In some embodiments, the terminal sends fifth information to the network device.

[0206] In some embodiments, the terminal may receive configuration information sent by the network device, obtain a beam report based on the configuration information and AI function, and send the beam report to the network device.

[0207] The communication method involved in the embodiments of this disclosure may include at least one of steps S3101 to S3105. For example, step S3101 may be implemented as a standalone embodiment, step S3101+S3102 may be implemented as a standalone embodiment, step S3101+S3102+S3103+S3104 may be implemented as a standalone embodiment, and step S3101+S3102+S3105 may be implemented as a standalone embodiment, but is not limited thereto.

[0208] In some embodiments, steps S3103 and S3104 are optional, and one or more of these steps may be omitted or substituted in different embodiments.

[0209] In some embodiments, step S3105 is optional, and one or more of these steps may be omitted or substituted in different embodiments.

[0210] Figure 4 is a flowchart illustrating a communication method according to an embodiment of the present disclosure. As shown in Figure 4, the present disclosure relates to a communication method, which includes:

[0211] Step S4101: Obtain the first information.

[0212] The optional implementation of step S4101 can be found in the optional implementation of step S2101 in Figure 2 and other related parts in the embodiments involved in Figure 2, which will not be repeated here.

[0213] In some embodiments, the network device receives first information sent by the terminal.

[0214] Step S4102: Send the second message.

[0215] The optional implementation of step S4102 can be found in the optional implementation of step S2102 in Figure 2 and other related parts in the embodiments involved in Figure 2, which will not be repeated here.

[0216] In some embodiments, the network device sends second information to the terminal.

[0217] Step S4103: Obtain third information.

[0218] The optional implementation of step S4103 can be found in the optional implementation of step S2103 in Figure 2 and other related parts in the embodiments involved in Figure 2, which will not be repeated here.

[0219] In some embodiments, the network device receives third information sent by the terminal.

[0220] Step S4104: Obtain the fourth piece of information.

[0221] The optional implementation of step S4104 can be found in the optional implementation of step S2104 in Figure 2 and other related parts in the embodiments involved in Figure 2, which will not be repeated here.

[0222] In some embodiments, the network device receives fourth information sent by the terminal.

[0223] Step S4105: Obtain the fifth piece of information.

[0224] The optional implementation of step S4105 can be found in the optional implementation of step S2105 in Figure 2 and other related parts in the embodiments involved in Figure 2, which will not be repeated here.

[0225] In some embodiments, the network device receives the fifth information sent by the terminal.

[0226] In some embodiments, the network device may send configuration information to the terminal, and the network device may receive beam reports sent by the terminal.

[0227] The communication method involved in the embodiments of this disclosure may include at least one of steps S4101 to S4105. For example, step S4101 may be implemented as a standalone embodiment, step S4101+S4102 may be implemented as a standalone embodiment, step S4101+S4102+S4103+S4104 may be implemented as a standalone embodiment, and step S4101+S4102+S4105 may be implemented as a standalone embodiment, but is not limited thereto.

[0228] In some embodiments, steps S4103 and S4104 are optional, and one or more of these steps may be omitted or substituted in different embodiments.

[0229] In some embodiments, step S4105 is optional, and one or more of these steps may be omitted or substituted in different embodiments.

[0230] Figure 5 is an interactive schematic diagram of a communication method according to an embodiment of the present disclosure. As shown in Figure 5, the embodiments of the present disclosure relate to a communication method, which includes:

[0231] Step S5101: The terminal sends the first information to the network device.

[0232] The optional implementation of step S5101 can be found in step S2101 of Figure 2, step S3101 of Figure 3, step S4101 of Figure 4, and other related parts in the embodiments involved in Figures 2, 3, and 4, which will not be repeated here.

[0233] In some embodiments, the above methods may include the methods of the embodiments described above on the communication system side, terminal side, network device side, etc., which will not be repeated here.

[0234] The communication method provided in this disclosure may specifically include: a terminal reporting a support parameter set (feature group), wherein the parameter set includes beam prediction based on AI / ML.

[0235] The parameter set includes at least one of the following:

[0236] The terminal supports the following beam management (BM) cases: the optional values ​​are BM case 1 (spatial beam prediction) and / or BM case 2 (temporal beam prediction);

[0237] The terminal supports the mapping relationship between set B and set A, with possible values ​​as follows: set B is a subset of set A; set B is different from set A (e.g., set B contains wide beams, while set A contains narrow beams); set B is the same as set A (only exists in BM case2).

[0238] The maximum or minimum number of beams included in set B supported by the terminal;

[0239] The maximum or minimum number of beams included in set A supported by the terminal;

[0240] The range or minimum number of historical measurement time instances supported by the terminal (only exists in BM case 2);

[0241] The period of historical measurement time instances supported by the terminal (exists only in BM case 2);

[0242] The range or maximum number of future prediction time instances supported by the terminal (exists only in BM case 2);

[0243] The range or maximum value of the time length of future predicted time instances supported by the terminal (i.e., the time interval between the last historical measurement time instance) (exists only in BM case 2);

[0244] The terminal supports beam reporting content, with optional values ​​including at least one of the following: L1-RSRP; beam ID, or RS ID; probability that each beam ID is the best beam;

[0245] The terminal supports the following performance monitoring types: terminal-side performance monitoring, network-side performance monitoring, or hybrid performance monitoring.

[0246] Among them, terminal-side performance monitoring refers to the terminal measuring and obtaining the measured beam information of set A, and simultaneously inputting the measured beam information of set B into the model to obtain the predicted beam information of set A. The measured beam information and predicted beam information of set A are compared to obtain the performance metric. When the performance metric meets the event, the terminal determines to activate / deactivate the function or model. For example, when the metric is higher than a threshold, lower than a threshold, or the beam prediction accuracy is lower than a threshold, the terminal determines to activate the function or model.

[0247] In some embodiments, the terminal informs the network device of its decision to activate / deactivate the feature or model. The activation / deactivation process begins only after the network device provides a response. The network device's response may include agreement, disagreement, or instructions to the terminal to activate or deactivate.

[0248] Among them, network-side performance monitoring refers to the terminal sending the measured beam information and predicted beam information of set A to the network device, which then calculates the performance indicators, determines whether to activate or deactivate the function or model, and instructs the terminal accordingly.

[0249] Hybrid performance monitoring refers to the terminal comparing the measured beam information and predicted beam information of set A to obtain performance indicators, and then reporting these indicators to the network device. The network device determines whether to activate or deactivate the function or model and instructs the terminal accordingly.

[0250] In some embodiments, the terminal reports the performance metrics to the network device only after the performance metrics have been met.

[0251] In some embodiments, the terminal supports at least one of the following performance metrics:

[0252] The accuracy of beam prediction of the strongest beam pair among K beam pairs; correct prediction means that the predicted strongest beam pair ID includes the actual strongest beam pair ID, or the predicted strongest beam pair ID is included among the actual strongest N beam pairs IDs; the downlink transmit beam ID can be equivalent to the reference signal resource ID, such as SSB ID, CSI-RS ID, or SRS ID; the downlink receive beam ID is the terminal's receive beam (Rx beam ID); the beam pair ID is the ID corresponding to the combination of the downlink transmit beam and the downlink receive beam; strongest refers to the strongest L1-RSRP or L1-SINR; this indicator can be based on the accuracy of the output beam information obtained through multiple derivations of the model, and can be a ratio.

[0253] L1-RSRP within 1dB: The accuracy when the difference between the actual L1-RSRP of the predicted best beam and the actual L1-RSRP of the actual best beam is within 1dB; this metric can be based on the accuracy of the output beam information after multiple derivations of the model, for example, it can be a ratio.

[0254] L1-RSRP difference: The difference between the actual L1-RSRP of the predicted best beam (pair) and the actual L1-RSRP of the actual best beam. For example, the average value is X dB, or the value at the 5% point of the cumulative distribution function is Y dB; it can also be the proportion of L1-RSRP difference that is lower than the threshold value, or the proportion that is higher than the threshold value.

[0255] Predicted L1-RSRP difference: The difference between the actual L1-RSRP of the predicted best beam (pair) and the predicted L1-RSRP of the best beam (pair). For example, the average value is X dB, or the value at the 5% point of the cumulative distribution function is Y dB; it can also be the proportion of the predicted L1-RSRP difference that is below the threshold or above the threshold.

[0256] Average UE throughput (the average throughput of a UE based on beam prediction results obtained from multiple beam predictions), or UE throughput at 5% of the cumulative distribution function: Based on the predicted strongest beam (pair) and the actual strongest beam (pair), obtain the SINR corresponding to the two beams (pairs), calculate the capacity based on Shannon capacity, and the difference in capacity is the index.

[0257] Reference signal overhead, i.e. how much reference signal resources the model requires, is mainly affected by factors including the size of the set B corresponding to the model input and the number of historical measurement times during time-domain prediction.

[0258] Uplink control information overhead: If it is a network-side model, then the measurement results of set B need to be reported to the network, which is the signaling overhead of this reporting.

[0259] Predicted latency, e.g., t ms;

[0260] The distribution of model input data, for example, if the input data is L1-RSRP, its distribution characteristics refer to the size range, etc.

[0261] Model output data distribution.

[0262] In some embodiments, the terminal receives at least one set of parameters sent by the network device and determines the parameter sets supported by the terminal. Each parameter set includes one or more of the contents of the aforementioned parameter sets.

[0263] In some embodiments, if it is determined that the terminal does not support a set of parameters, the terminal reports at least one of the following:

[0264] Indicates none: that is, there is no supported parameter set;

[0265] For each parameter set, 1 bit of information is fed back, where '1' indicates that the parameter set is supported and '0' indicates that the parameter set is not supported. That is, in this case, the 1 bit corresponding to each parameter set is '0'.

[0266] Furthermore, in some embodiments, the terminal provides suggested parameter sets, each parameter set including one or more items from the aforementioned parameter sets. Furthermore, the terminal can indicate more detailed parameter information for the suggested parameter sets, i.e., parameter information not included in the aforementioned parameter sets, such as the specific number of beams in set B, the specific number of beams in set A, the number of historical measurement time instances, the number of future prediction time instances, and the duration of the future prediction time instances.

[0267] After the terminal provides the suggested parameter set, the network device sends another parameter set, which is the same as the parameter set suggested by the terminal. The terminal can also subsequently indicate more detailed parameter information for the suggested parameter set.

[0268] Furthermore, in some other embodiments, the terminal informs the network device that it can support a certain parameter set after a period of time. For example, after a period of time, the terminal can obtain the model corresponding to the parameter set.

[0269] In this case, the terminal can also provide more detailed parameter information corresponding to the parameter set. Alternatively, after receiving the instruction from the terminal, the network device can send the parameter set again after a period of time, and the terminal can then provide more detailed parameter information corresponding to the parameter set. Or, after a period of time, the terminal can proactively report that the parameter set is now supported (in this case, the terminal can also include content two in this report, directly updating the supported parameter sets after a period of time).

[0270] In some embodiments, if it is determined that the terminal supports at least one parameter set, the terminal reports the supported at least one parameter set. The reported content includes at least one of the following:

[0271] The indication is "yes": A supported parameter set is available.

[0272] Supported parameter set IDs;

[0273] For each parameter set, 1 bit of information is fed back, where '1' indicates that the parameter set is supported and '0' indicates that the parameter set is not supported. That is, in this case, at least one parameter set will have a '1' bit of information.

[0274] Furthermore, the terminal can indicate more detailed parameter information for the supported parameter sets, i.e., parameter information not included in the second part, such as the specific number of beams in set B, the specific number of beams in set A, the number of historical measurement time instances, the number of future prediction time instances, and the duration of the future prediction time instances.

[0275] The associated ID is used to indicate the attributes of the downlink receive beam or beam set / list supported by the terminal, such as beam direction and beamwidth.

[0276] In some embodiments, the terminal reports based on RRC.

[0277] In some embodiments, the terminal receives Channel State Information (CSI) report configuration information sent by the network device, uses the measurement data obtained based on set B in the configuration information as model input, and obtains the prediction data corresponding to set A in the configuration information based on the determined model. Based on the prediction data, it obtains a beamform report and sends it to the network side.

[0278] This disclosure proposes a method for reporting the parameter set supported by a terminal, so that network devices can determine the configuration parameters supported by the terminal according to requirements, thereby improving the performance of AI-based beam prediction.

[0279] In the embodiments disclosed herein, some or all of the steps and their optional implementations may be arbitrarily combined with some or all of the steps in other embodiments, or may be arbitrarily combined with the optional implementations in other embodiments.

[0280] This disclosure also provides an apparatus for implementing any of the above methods. For example, an apparatus is provided that includes units or modules for implementing the steps performed by the terminal in any of the above methods. Alternatively, another apparatus is provided that includes units or modules for implementing the steps performed by a network device (e.g., an access network device, a core network functional node, a core network device, etc.) in any of the above methods.

[0281] It should be understood that the division of units or modules in the above device is only a logical functional division. In actual implementation, they can be fully or partially integrated into a single physical entity, or they can be physically separated. Furthermore, the units or modules in the device can be implemented by a processor calling software: for example, the device includes a processor connected to a memory containing instructions. The processor calls the instructions stored in the memory to implement any of the above methods or to implement the functions of the units or modules in the above device. The processor can be, for example, a general-purpose processor, such as a Central Processing Unit (CPU) or a microprocessor, and the memory can be internal or external to the device. Alternatively, the units or modules in the device can be implemented in the form of hardware circuits. The functionality of some or all of the units or modules can be achieved through the design of these hardware circuits, which can be understood as one or more processors. For example, in one implementation, the hardware circuit is an application-specific integrated circuit (ASIC). The functionality of some or all of the units or modules is achieved through the design of the logical relationships between the components within the circuit. In another implementation, the hardware circuit can be implemented using a programmable logic device (PLD). Taking a field-programmable gate array (FPGA) as an example, it can include a large number of logic gates. The connection relationships between the logic gates are configured through configuration files, thereby achieving the functionality of some or all of the units or modules. All units or modules of the above device can be implemented entirely through processor-called software, entirely through hardware circuits, or partially through processor-called software with the remaining parts implemented through hardware circuits.

[0282] In this embodiment, the processor is a circuit with signal processing capabilities. In one implementation, the processor can be a circuit with instruction read and execute capabilities, such as a Central Processing Unit (CPU), a microprocessor, a graphics processing unit (GPU) (which can be understood as a microprocessor), or a digital signal processor (DSP). In another implementation, the processor can implement certain functions through the logical relationships of hardware circuits. The logical relationships of the aforementioned hardware circuits are fixed or reconfigurable. For example, the processor is a hardware circuit implemented using an application-specific integrated circuit (ASIC) or a programmable logic device (PLD), such as an FPGA. In a reconfigurable hardware circuit, the process of the processor loading a configuration document and configuring the hardware circuit can be understood as the process of the processor loading instructions to implement the functions of some or all of the above units or modules. Furthermore, it can also be a hardware circuit designed for artificial intelligence, which can be understood as an ASIC, such as a Neural Network Processing Unit (NPU), a Tensor Processing Unit (TPU), or a Deep Learning Processing Unit (DPU).

[0283] Figure 6A is a schematic diagram of the structure of a terminal according to an embodiment of this disclosure. As shown in Figure 6A, the terminal 6100 may include a transceiver module 6101. In some embodiments, the transceiver module 6101 is used to send first information to a network device. Optionally, the transceiver module is used to perform at least one of the steps performed by the terminal in any of the above methods (e.g., step S2101, step S2103, but not limited thereto), which will not be described in detail here.

[0284] In some embodiments, the terminal may further include a processing module.

[0285] In some embodiments, the first parameter set includes at least one of the following: the beam prediction type supported by the terminal, wherein the beam prediction type includes spatial beam prediction and / or temporal beam prediction; the relationship between the first set and the second set supported by the terminal, wherein the first set is the set corresponding to model input data and the second set is the set corresponding to model output data; the number of beams included in the first set; the number of beams included in the second set; the beam reporting content supported by the terminal; the performance monitoring type supported by the terminal, wherein the performance monitoring type includes one of terminal-side performance monitoring, network-side performance monitoring, and hybrid performance monitoring; and the performance metrics supported by the terminal.

[0286] In some embodiments, the beam prediction type supported by the terminal includes time-domain beam prediction, and the first parameter set further includes at least one of the following: a range of the number of first time instances; a minimum number of first time instances; a period of the first time instances; a range of the number of second time instances; a maximum number of second time instances; a range of time intervals between the second time instances and a reference time; and a maximum time interval between the second time instances and the reference time; wherein the first time instance is a historical measurement time instance supported by the terminal, and the second time instance is a future prediction time instance supported by the terminal.

[0287] In some embodiments, the performance metrics include at least one of the following: accuracy of beam prediction; accuracy of beam quality prediction; overhead of reference signal resources; overhead of uplink control information; prediction delay; distribution of model input data; and distribution of model output data.

[0288] In some embodiments, the accuracy of the beam quality prediction includes at least one of the following: a first difference, which is the difference between the actual measured value of the first predicted beam and the actual measured value of the first actual beam; a first ratio, which is the ratio between the number of predictions in which the first difference falls within a preset range and the total number of predictions; a second difference, which is the difference between the actual measured value of the first predicted beam and the predicted measured value of the first predicted beam; and a third difference, which is the difference between a first capacity and a second capacity, wherein the first capacity is determined based on the signal-to-interference-plus-noise ratio (SINR) of the first predicted beam and the second capacity is determined based on the SINR of the first actual beam.

[0289] In some embodiments, the transceiver module is further configured to receive second information sent by the network device, the second information being used to indicate a second parameter set, the second parameter set being at least one of the first parameter set.

[0290] In some embodiments, the transceiver module is further configured to send third information to the network device, the third information being used to indicate that the second parameter set is unavailable.

[0291] In some embodiments, the transceiver module is further configured to send fourth information to the network device, the fourth information being used to indicate a third parameter set or a fourth parameter set, the third parameter set being a parameter set available to the terminal, and the fourth parameter set being a parameter set available to the terminal after a preset time period.

[0292] In some embodiments, the transceiver module is further configured to send fifth information to the network device, the fifth information including at least one of the following: information indicating that the terminal supports a fifth parameter set, the fifth parameter set being at least one of a second parameter set; indication information of the fifth parameter set; sixth information corresponding to the fifth parameter set, the sixth information being used to indicate parameter information not included in the fifth parameter set; and attribute information of the beam supported by the terminal.

[0293] In some embodiments, the transceiver module is further configured to receive configuration information sent by the network device; the terminal obtains a beam report based on the configuration information and AI function; and the terminal sends the beam report to the network device.

[0294] Figure 6B is a schematic diagram of the structure of a network device according to an embodiment of this disclosure. As shown in Figure 6B, the network device 6200 may include a transceiver module 6201. In some embodiments, the transceiver module 6201 is used to receive first information sent by a terminal. Optionally, the transceiver module is used to perform at least one of the steps performed by the network device in any of the above methods (e.g., step S2101, but not limited thereto), which will not be described in detail here.

[0295] In some embodiments, the network device may further include a processing module.

[0296] In some embodiments, the first parameter set includes at least one of the following: the beam prediction type supported by the terminal, wherein the beam prediction type includes spatial beam prediction and / or temporal beam prediction; the relationship between the first set and the second set supported by the terminal, wherein the first set is the set corresponding to model input data and the second set is the set corresponding to model output data; the number of beams included in the first set; the number of beams included in the second set; the beam reporting content supported by the terminal; the performance monitoring type supported by the terminal, wherein the performance monitoring type includes one of terminal-side performance monitoring, network-side performance monitoring, and hybrid performance monitoring; and the performance metrics supported by the terminal.

[0297] In some embodiments, the beam prediction type supported by the terminal includes time-domain beam prediction, and the first parameter set further includes at least one of the following: a range of the number of first time instances; a minimum number of first time instances; a period of the first time instances; a range of the number of second time instances; a maximum number of second time instances; a range of time intervals between the second time instances and a reference time; and a maximum time interval between the second time instances and the reference time; wherein the first time instance is a historical measurement time instance supported by the terminal, and the second time instance is a future prediction time instance supported by the terminal.

[0298] In some embodiments, the performance metrics include at least one of the following: accuracy of beam prediction; accuracy of beam quality prediction; overhead of reference signal resources; overhead of uplink control information; prediction delay; distribution of model input data; and distribution of model output data.

[0299] In some embodiments, the accuracy of the beam quality prediction includes at least one of the following: a first difference, the first difference being the difference between the actual measured value of the first predicted beam and the actual measured value of the first actual beam; a first ratio, the first ratio being the ratio between the number of predictions in which the first difference falls within a preset range and the total number of predictions; a second difference, the second difference being the difference between the actual measured value of the first predicted beam and the predicted measured value of the first predicted beam; and a third difference, the third difference being the difference between a first capacity and a second capacity, wherein the first capacity is determined based on the signal-to-interference-plus-noise ratio (SINR) of the first predicted beam, and the second capacity is determined based on the SINR of the first actual beam.

[0300] In some embodiments, the method further includes: the network device sending second information to the terminal, the second information indicating a second parameter set, the second parameter set being at least one of the first parameter set.

[0301] In some embodiments, the method further includes: the network device receiving third information sent by the terminal, the third information being used to indicate that the second parameter set is unavailable.

[0302] In some embodiments, the method further includes: the network device receiving fourth information sent by the terminal, the fourth information being used to indicate a third parameter set or a fourth parameter set, the third parameter set being a parameter set available to the terminal, and the fourth parameter set being a parameter set available to the terminal after a preset time period.

[0303] In some embodiments, the method further includes: the network device receiving fifth information sent by the terminal, the fifth information including at least one of the following: information indicating that the terminal supports a fifth parameter set, the fifth parameter set being at least one of a second parameter set; indication information of the fifth parameter set; sixth information corresponding to the fifth parameter set, the sixth information being used to indicate parameter information not included in the fifth parameter set; and attribute information of the beam supported by the terminal.

[0304] In some embodiments, the method further includes: the network device sending configuration information to the terminal; the network device receiving a beam report sent by the terminal, the beam report being obtained based on the configuration information and AI functionality.

[0305] In some embodiments, the processing module may be a single module or may include multiple sub-modules. Optionally, the multiple sub-modules may each perform all or part of the steps required by the processing module. Optionally, the processing module may be interchangeable with a processor.

[0306] Figure 7A is a schematic diagram of the structure of the communication device 7100 proposed in an embodiment of this disclosure. The communication device 7100 can be a network device (e.g., access network device, core network device, etc.), a terminal (e.g., user equipment, etc.), a chip, chip system, or processor that supports the network device in implementing any of the above methods, or a chip, chip system, or processor that supports the terminal in implementing any of the above methods. The communication device 7100 can be used to implement the methods described in the above method embodiments; for details, please refer to the descriptions in the above method embodiments.

[0307] As shown in Figure 7A, the communication device 7100 includes one or more processors 7101. The processor 7101 can be a general-purpose processor or a dedicated processor, such as a baseband processor or a central processing unit (CPU). The baseband processor can be used to process communication protocols and communication data, while the CPU can be used to control communication devices (e.g., base stations, baseband chips, terminal devices, terminal device chips, DUs or CUs, etc.), execute programs, and process program data. Optionally, the communication device 7100 can be used to execute any of the above methods. Optionally, one or more processors 7101 can be used to invoke instructions to cause the communication device 7100 to execute any of the above methods.

[0308] In some embodiments, the communication device 7100 further includes one or more transceivers 7102. When the communication device 7100 includes one or more transceivers 7102, the transceiver 7102 performs at least one of the communication steps (e.g., steps S2101, S2103, but not limited thereto) in the above method, such as sending and / or receiving, while the processor 7101 performs at least one of the other steps. In optional embodiments, the transceiver may include a receiver and / or a transmitter, which may be separate or integrated. Optionally, the terms transceiver, transceiver unit, transceiver, transceiver circuit, interface circuit, interface, etc., can be used interchangeably; the terms transmitter, sending unit, transmitter, sending circuit, etc., can be used interchangeably; and the terms receiver, receiving unit, receiver, receiving circuit, etc., can be used interchangeably.

[0309] In some embodiments, the communication device 7100 further includes one or more memories 7103 for storing data. Optionally, all or part of the memories 7103 may be located outside the communication device 7100. In optional embodiments, the communication device 7100 may include one or more interface circuits 7104. Optionally, the interface circuits 7104 are connected to the memories 7103 and can be used to receive data from the memories 7103 or other devices, and to send data to the memories 7103 or other devices. For example, the interface circuits 7104 can read data stored in the memories 7103 and send the data to the processor 7101.

[0310] The communication device 7100 described in the above embodiments may be a network device or a terminal, but the scope of the communication device 7100 described in this disclosure is not limited thereto, and the structure of the communication device 7100 may not be limited by FIG. 7A. The communication device may be a standalone device or a part of a larger device. For example, the communication device may be: (1) a standalone integrated circuit IC, or chip, or chip system or subsystem; (2) a collection of one or more ICs, optionally, the IC collection may also include storage components for storing data and programs; (3) an ASIC, such as a modem; (4) a module that can be embedded in other devices; (5) a receiver, terminal device, smart terminal device, cellular phone, wireless device, handheld device, mobile unit, vehicle device, network device, cloud device, artificial intelligence device, etc.; (6) others, etc.

[0311] Figure 7B is a schematic diagram of the chip structure proposed in an embodiment of this disclosure. For cases where the communication device 7100 can be a chip or a chip system, please refer to the schematic diagram of the chip 7200 shown in Figure 7B, but it is not limited thereto.

[0312] Chip 7200 includes one or more processors 7201. Chip 7200 is used to perform any of the above methods.

[0313] In some embodiments, chip 7200 further includes one or more interface circuits 7202. Optionally, terms such as interface circuit, interface, and transceiver pin can be used interchangeably. In some embodiments, chip 7200 further includes one or more memories 7203 for storing data. Optionally, all or part of the memories 7203 may be located outside chip 7200. Optionally, interface circuit 7202 is connected to memory 7203, and interface circuit 7202 can be used to receive data from memory 7203 or other devices, and interface circuit 7202 can be used to send data to memory 7203 or other devices. For example, interface circuit 7202 can read data stored in memory 7203 and send the data to processor 7201.

[0314] In some embodiments, the interface circuit 7202 performs at least one of the communication steps such as sending and / or receiving in the above method (e.g., steps S2101, S2103, but not limited thereto). For example, the interface circuit 7202 performing the communication steps such as sending and / or receiving in the above method means that the interface circuit 7202 performs data interaction between the processor 7201, the chip 7200, the memory 7203, or the transceiver device. In some embodiments, the processor 7201 performs at least one of the other steps.

[0315] The modules and / or devices described in the various embodiments, such as virtual devices, physical devices, and chips, can be combined or separated arbitrarily as needed. Optionally, some or all steps can also be performed collaboratively by multiple modules and / or devices, which is not limited here.

[0316] This disclosure also proposes a storage medium storing instructions that, when executed on the communication device 7100, cause the communication device 7100 to perform any of the above methods. Optionally, the storage medium is an electronic storage medium. Optionally, the storage medium is a computer-readable storage medium, but not limited thereto; it may also be a storage medium readable by other devices. Optionally, the storage medium may be a non-transitory storage medium, but not limited thereto; it may also be a temporary storage medium.

[0317] This disclosure also provides a program product that, when executed by the communication device 7100, causes the communication device 7100 to perform any of the above methods. Optionally, the program product is a computer program product.

[0318] This disclosure also proposes a computer program that, when run on a computer, causes the computer to perform any of the above methods.

Claims

1. A communication method, characterized in that, The method includes: The terminal sends first information to the network device, the first information being used to indicate a first set of parameters supported by the terminal, the first set of parameters being used for beam prediction based on artificial intelligence (AI).

2. The method according to claim 1, characterized in that, The first parameter set includes at least one of the following: The terminal supports beam prediction types, which include spatial beam prediction and / or temporal beam prediction. The relationship between the first set and the second set supported by the terminal is as follows: the first set is the set corresponding to the model input data, and the second set is the set corresponding to the model output data. The number of beams included in the first set; The number of beams included in the second set; The beam reporting content supported by the terminal; The terminal supports performance monitoring types, which include one of terminal-side performance monitoring, network-side performance monitoring, and hybrid performance monitoring. The terminal supports the following performance metrics.

3. The method according to claim 2, characterized in that, The beam prediction types supported by the terminal include time-domain beam prediction, and the first parameter set further includes at least one of the following: The range of the number of instances at the first moment; Minimum number of instances in the first instance; The lifecycle of the first instance; The range of the number of instances in the second time period; The maximum number of instances in the second time period; The range of time intervals between the second time instance and the reference time; The maximum time interval between the second time instance and the reference time; Wherein, the first time instance is a historical measurement time instance supported by the terminal, and the second time instance is a future prediction time instance supported by the terminal.

4. The method according to claim 2, characterized in that, The performance metrics include at least one of the following: The accuracy of beam prediction; The accuracy of beam quality prediction; The overhead of reference signal resources; The overhead of uplink control information; Predicted latency; Distribution of model input data; Distribution of model output data.

5. The method according to claim 4, characterized in that, The accuracy of the beam quality prediction includes at least one of the following: The first difference is the difference between the actual measured value of the first predicted beam and the actual measured value of the first actual beam. The first ratio is the ratio between the number of predictions where the first difference falls within a preset range and the total number of predictions. The second difference is the difference between the actual measured value of the first predicted beam and the predicted measured value of the first predicted beam. The third difference is the difference between the first capacity and the second capacity, wherein the first capacity is determined based on the signal-to-interference-plus-noise ratio (SINR) of the first predicted beam and the second capacity is determined based on the SINR of the first actual beam.

6. The method according to any one of claims 1 to 5, characterized in that, The method further includes: The terminal receives second information sent by the network device, the second information being used to indicate a second parameter set, the second parameter set being at least one of the first parameter sets.

7. The method according to claim 6, characterized in that, The method further includes: The terminal sends a third message to the network device, the third message indicating that the second parameter set is unavailable.

8. The method according to claim 7, characterized in that, The method further includes: The terminal sends a fourth message to the network device. The fourth message is used to indicate a third parameter set or a fourth parameter set. The third parameter set is a parameter set available to the terminal, and the fourth parameter set is a parameter set available to the terminal after a preset time period.

9. The method according to claim 6, characterized in that, The method further includes: The terminal sends a fifth piece of information to the network device, the fifth piece of information including at least one of the following: The terminal is instructed to support a fifth parameter set, which is at least one parameter set in the second parameter set. The indication information of the fifth parameter set; The sixth information corresponding to the fifth parameter set is used to indicate parameter information not included in the fifth parameter set; The terminal supports beam attribute information.

10. The method according to any one of claims 1 to 9, characterized in that, The method further includes: The terminal receives configuration information sent by the network device; The terminal obtains beam reports based on configuration information and AI functions; The terminal sends the beam report to the network device.

11. A communication method, characterized in that, The method includes: The network device receives first information sent by the terminal, the first information being used to indicate a first set of parameters supported by the terminal, the first set of parameters being used for beam prediction based on artificial intelligence (AI).

12. The method according to claim 11, characterized in that, The first parameter set includes at least one of the following: The terminal supports beam prediction types, which include spatial beam prediction and / or temporal beam prediction. The relationship between the first set and the second set supported by the terminal is as follows: the first set is the set corresponding to the model input data, and the second set is the set corresponding to the model output data. The number of beams included in the first set; The number of beams included in the second set; The beam reporting content supported by the terminal; The terminal supports performance monitoring types, which include one of terminal-side performance monitoring, network-side performance monitoring, and hybrid performance monitoring. The terminal supports the following performance metrics.

13. The method according to claim 12, characterized in that, The beam prediction types supported by the terminal include time-domain beam prediction, and the first parameter set further includes at least one of the following: The range of the number of instances at the first moment; Minimum number of instances in the first instance; The lifecycle of the first instance; The range of the number of instances in the second time period; The maximum number of instances in the second time period; The range of time intervals between the second time instance and the reference time; The maximum time interval between the second time instance and the reference time; Wherein, the first time instance is a historical measurement time instance supported by the terminal, and the second time instance is a future prediction time instance supported by the terminal.

14. The method according to claim 12, characterized in that, The performance metrics include at least one of the following: The accuracy of beam prediction; The accuracy of beam quality prediction; The overhead of reference signal resources; The overhead of uplink control information; Predicted latency; Distribution of model input data; Distribution of model output data.

15. The method according to claim 14, characterized in that, The accuracy of the beam quality prediction includes at least one of the following: The first difference is the difference between the actual measured value of the first predicted beam and the actual measured value of the first actual beam. The first ratio is the ratio between the number of predictions where the first difference falls within a preset range and the total number of predictions. The second difference is the difference between the actual measured value of the first predicted beam and the predicted measured value of the first predicted beam. The third difference is the difference between the first capacity and the second capacity, wherein the first capacity is determined based on the signal-to-interference-plus-noise ratio (SINR) of the first predicted beam and the second capacity is determined based on the SINR of the first actual beam.

16. The method according to any one of claims 11 to 15, characterized in that, The method further includes: The network device sends second information to the terminal, the second information being used to indicate a second parameter set, the second parameter set being... It is at least one of the parameters in the first parameter set.

17. The method according to claim 16, characterized in that, The method further includes: The network device receives third information sent by the terminal, the third information being used to indicate that the second parameter set is unavailable.

18. The method according to claim 17, characterized in that, The method further includes: The network device receives fourth information sent by the terminal. The fourth information is used to indicate a third parameter set or a fourth parameter set. The third parameter set is a parameter set available to the terminal, and the fourth parameter set is a parameter set available to the terminal after a preset time period.

19. The method according to claim 16, characterized in that, The method further includes: The network device receives a fifth message sent by the terminal, the fifth message including at least one of the following: The terminal is instructed to support a fifth parameter set, which is at least one parameter set in the second parameter set. The indication information of the fifth parameter set; The sixth information corresponding to the fifth parameter set is used to indicate parameter information not included in the fifth parameter set; The terminal supports beam attribute information.

20. The method according to any one of claims 11 to 19, characterized in that, The method further includes: The network device sends configuration information to the terminal; The network device receives a beam report sent by the terminal, the beam report being obtained based on the configuration information and AI function.

21. A terminal, characterized in that, include: The transceiver module is used to send first information to the network device. The first information is used to indicate a first set of parameters supported by the terminal. The first set of parameters is used for beam prediction based on artificial intelligence (AI).

22. A network device, characterized in that, include: The transceiver module is used to receive first information sent by the terminal, the first information being used to indicate a first set of parameters supported by the terminal, the first set of parameters being used for beam prediction based on artificial intelligence (AI).

23. A terminal, characterized in that, include: One or more processors; The terminal is used to execute the method according to any one of claims 1 to 10.

24. A network device, characterized in that, include: One or more processors; The network device is used to perform the method according to any one of claims 11 to 20.

25. A communication system, characterized in that, The device includes a terminal and a network device, wherein the terminal is configured to implement the method of any one of claims 1 to 10, and the network device is configured to implement the method of any one of claims 11 to 20.

26. A storage medium storing instructions, characterized in that, When the instructions are executed on a communication device, the communication device performs the method as described in any one of claims 1 to 10 or the method as described in any one of claims 11 to 20.

27. A program product, characterized in that, include: A computer program, when executed by a communication device, causes the communication device to perform the method as described in any one of claims 1 to 10 or the method as described in any one of claims 11 to 20.

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