Method for determining association scope of associated id, apparatus, communication device, and medium

Abstract

The present application relates to the technical field of wireless communications, and discloses a method for determining an association scope of an Associated ID, an apparatus, a communication device, and a medium. The method comprises: determining an Associated ID associated with a first object and a second object; and when the Associated ID associated with the first object and the second object is the same, according to a first rule, determining whether an association scope indicated by the Associated ID is the same, wherein the first rule includes one of the following: when the Associated ID associated with the first object and the second object is the same, the association scope indicated by the Associated ID is different; when the Associated ID associated with the first object and the second object is the same, the association scope indicated by the Associated ID is the same; when the Associated ID associated with the first object and the second object is the same, and the first object and the second object belong to a first set, the association scope indicated by the Associated ID is different; and when the Associated ID associated with the first object and the second object is the same, and the first object and the second object belong to a second set, the association scope indicated by the Associated ID is the same.

Description

Method and apparatus for determining association range of association identifier, communication device and medium

[0001] The present application claims priority to the Chinese patent application No. 202411086913.X, filed on August 8, 2024, and entitled "Method and apparatus for determining association range of association identifier, communication device and medium", the content of which is incorporated herein by reference in its entirety. TECHNICAL FIELD

[0002] The present application belongs to the technical field of wireless communication, and specifically relates to a method and apparatus for determining association range of association identifier, a communication device and a medium. BACKGROUND

[0003] Currently, in some wireless communication scenarios, such as training or inference scenarios of an artificial intelligence (AI) model for a wireless communication network, there is a concept of an associated identifier (Associated ID), which is used to indicate network side conditions or terminal side conditions explicitly or implicitly. However, the association range of the specific Associated ID has not been specifically defined. In some cases, one end of the wireless communication believes that the same Associated ID associated with different objects indicates different network side conditions or terminal side conditions, while the other end believes that the same Associated ID associated with different objects indicates the same network side conditions or terminal side conditions, resulting in a conflict in understanding between the two ends, thereby reducing the performance of the wireless communication system. SUMMARY

[0004] Embodiments of the present application provide a method and apparatus for determining the association range of an associated identifier, a communication device and a medium, which can solve the problem of inconsistent understanding of the association range of the Associated ID by the communication device, thereby reducing the performance of the wireless communication system.

[0005] In a first aspect, a method for determining the association range of an associated identifier is provided, comprising:

[0006] A first communication device determines an associated identifier (Associated ID) associated with a first object and a second object;

[0007] The first communication device determines whether the association range indicated by the Associated ID associated with the first object and the second object is the same according to a first rule in the case that the Associated ID associated with the first object and the second object is the same;

[0008] The first rule includes one of the following:

[0009] the Associated ID associated with the first object and the second object is different in the case that the Associated ID associated with the first object and the second object is the same;

[0010] the Associated ID associated with the first object and the second object is the same in the case that the Associated ID associated with the first object and the second object is the same;

[0011] the Associated ID associated with the first object and the second object is different in the case that the Associated ID associated with the first object and the second object is the same, and the first object and the second object belong to a first set;

[0012] the Associated ID associated with the first object and the second object is the same in the case that the Associated ID associated with the first object and the second object is the same, and the first object and the second object belong to a second set; the second set is different from the first set.

[0013] In a second aspect, a device for determining an association range of an association identifier is provided, and the device comprises:

[0014] a processing module configured to determine an association identifier Associated ID associated with a first object and a second object; and determine whether the association range indicated by the Associated ID associated with the first object and the second object is the same or different in the case that the Associated ID associated with the first object and the second object is the same, according to a first rule.

[0015] The first rule comprises one of the following:

[0016] the Associated ID associated with the first object and the second object is different in the case that the Associated ID associated with the first object and the second object is the same;

[0017] the Associated ID associated with the first object and the second object is the same in the case that the Associated ID associated with the first object and the second object is the same;

[0018] the Associated ID associated with the first object and the second object is different in the case that the Associated ID associated with the first object and the second object is the same and the first object and the second object belong to a first set;

[0019] the Associated ID associated with the first object and the second object is the same in the case that the Associated ID associated with the first object and the second object is the same and the first object and the second object belong to a second set; the second set is different from the first set.

[0020] In a third aspect, a determination apparatus of an association range of an association identifier is provided, and the apparatus is configured to perform the steps of the method according to the first aspect.

[0021] In a fourth aspect, a communication device is provided, and the terminal includes a processor and a memory, the memory stores programs or instructions executable on the processor, and the programs or instructions are executed by the processor to implement the steps of the method according to the first aspect.

[0022] In a fifth aspect, a communication device is provided, and the device includes a processor and a communication interface, and the processor is configured to determine an association identifier Associated ID associated with a first object and a second object; in the case that the Associated ID associated with the first object and the second object is the same, determine whether the association range indicated by the Associated ID associated with the first object and the second object is the same according to a first rule.

[0023] The first rule includes one of the following:

[0024] the Associated ID associated with the first object and the second object is different in the case that the Associated ID associated with the first object and the second object is the same and the first object and the second object belong to a first set;

[0025] the Associated ID associated with the first object and the second object is the same in the case that the Associated ID associated with the first object and the second object is the same and the first object and the second object belong to a second set; the second set is different from the first set.

[0026] the Associated ID associated with the first object and the second object is different in the case that the Associated ID associated with the first object and the second object is the same and the first object and the second object belong to a first set;

[0027] In a case where the first object and the second object are associated with the same Associated ID and belong to a second set, the Associated ID associated with the first object and the second object indicates the same association range; the second set is different from the first set. In a sixth aspect, a readable storage medium is provided, and the readable storage medium stores a program or instructions, which are executed by a processor to implement the steps of the method in the first aspect.

[0028] In a seventh aspect, a chip is provided, and the chip includes a processor and a communication interface. The communication interface is coupled to the processor. The processor is configured to execute a program or instructions to implement the method in the first aspect.

[0029] In an eighth aspect, a computer program / program product is provided, and the computer program / program product is stored in a storage medium. The computer program / program product is executed by at least one processor to implement the steps of the method in the first aspect.

[0030] In the embodiments of the present application, in a case where the first object and the second object are associated with the same Associated ID, whether the Associated ID associated with the first object and the second object indicates the same association range is determined according to the first rule, so that each communication device can have a consistent understanding of the association range of the Associated ID, thereby improving the performance of the wireless communication system. BRIEF DESCRIPTION OF DRAWINGS

[0031] FIG. 1 is a block diagram of a wireless communication system to which embodiments of the present application can be applied;

[0032] FIG. 2 is a schematic diagram of a neural network;

[0033] FIG. 3 is a schematic diagram of a neuron;

[0034] FIG. 4 is a flowchart of a method for determining an association range of an association identifier according to an embodiment of the present application;

[0035] FIG. 5 is a structural diagram of a device for determining an association range of an association identifier according to an embodiment of the present application;

[0036] FIG. 6 is a structural diagram of a communication device according to an embodiment of the present application;

[0037] FIG. 7 is a hardware structural diagram of a terminal according to an embodiment of the present application;

[0038] FIG. 8 is a hardware structural diagram of a network-side device according to an embodiment of the present application;

[0039] FIG. 9 is a second schematic diagram of a hardware structure of a network-side device according to an embodiment of the present application. DETAILED DESCRIPTION

[0040] With reference to the accompanying drawings, the technical solutions in the embodiments of the present application will be described clearly. Obviously, the described embodiments are only some of the embodiments of the present application, but not all the embodiments of the present application. Based on the embodiments in the present application, all the other embodiments obtained by those skilled in the art belong to the scope of protection of the present application.

[0041] The terms "first", "second", and the like in the present application are used to distinguish similar objects, and are not used to describe a specific order or sequence. It should be understood that the terms used in this way can be interchanged under appropriate circumstances, so that the embodiments of the present application can be implemented in an order other than those illustrated or described herein, and the objects distinguished by "first", "second" are generally a category, and are not limited to the number of objects, for example, the first object can be one or more. In addition, "or" in the present application means at least one of the connected objects. For example, the protection scope of "A or B" at least covers three schemes, namely, scheme one: including A and not including B; scheme two: including B and not including A; scheme three: including A and B. In addition, the terms "A and / or B", "at least one of A and B", "at least one of A or B" also at least cover the above three schemes, respectively. The character " / " generally represents that the objects before and after are in an "or" relationship.

[0042] The term "indication" in the present application can be a direct indication (or explicit indication) or an indirect indication (or implicit indication). The direct indication can be understood as the sender explicitly informing the receiver of the specific information, the operation to be performed or the request result, etc. in the indication sent by the sender. The indirect indication can be understood as the receiver determining the corresponding information according to the indication sent by the sender, or judging and determining the operation to be performed or the request result, etc. according to the judgment result.

[0043] It is worth noting that the technology described in the embodiments of the present application is not limited to Long Term Evolution (LTE) / LTE-Advanced (LTE-A) systems, but can also be used in other wireless communication systems, such as Code Division Multiple Access (CDMA), Time Division Multiple Access (TDMA), Frequency Division Multiple Access (FDMA), Orthogonal Frequency Division Multiple Access (OFDMA), Single-carrier Frequency-Division Multiple Access (SC-FDMA) or other systems. The terms "system" and "network" in the embodiments of the present application are often used interchangeably, and the described technology can be used in the above-mentioned systems and radio technologies, as well as in other systems and radio technologies. The following description describes a New Radio (NR) system for example purposes, and NR terminology is used in most of the following description, but these technologies can also be applied to systems other than NR systems, such as 6th Generation (6G) communication systems. th

[0044] ​FIG. 1 shows a block diagram of a wireless communication system to which embodiments of the present application can be applied. The wireless communication system includes a terminal 11 and a network-side device 12. The terminal 11 can be a terminal-side device such as a mobile phone, a Tablet Personal Computer, a Laptop Computer, a notebook computer, a Personal Digital Assistant (PDA), a palmtop computer, a netbook, an Ultra-mobile Personal Computer (UMPC), a Mobile Internet Device (MID), an Augmented Reality (AR) device, a Virtual Reality (VR) device, a robot, a wearable device, a flight vehicle, a Vehicle User Equipment (VUE), a shipboard device, a Pedestrian User Equipment (PUE), a smart home (a home device with a wireless communication function such as a refrigerator, a television, a washing machine, or furniture), a game console, a Personal Computer (PC), a kiosk, or a self-service machine. The wearable device includes a smart watch, a smart bracelet, a smart earphone, smart glasses, smart jewelry (a smart bracelet, a smart necklace, a smart ring, a smart necklace, a smart anklet, a smart necklace, etc.), a smart wristband, smart clothes, etc. The vehicle-mounted device can also be referred to as a vehicle-mounted terminal, a vehicle-mounted controller, a vehicle-mounted module, a vehicle-mounted component, a vehicle-mounted chip, or a vehicle-mounted unit, etc. It should be noted that the specific type of the terminal 11 is not limited in the embodiments of the present application. The network-side device 12 can include an access network device or a core network device. The access network device can also be referred to as a Radio Access Network (RAN) device, a radio access network function, or a radio access network unit. The access network device can include a base station, a Wireless Local Area Network (WLAN) Access Point (AP), or a Wireless Fidelity (WiFi) node, etc.The base station can be referred to as a Node B (NB), an evolved Node B (eNB), a next generation Node B (gNB), a New Radio Node B (NR Node B), an access point, a relay station (RBS), a serving base station (SBS), a base transceiver station (BTS), a radio base station, a radio transceiver, a basic service set (BSS), an extended service set (ESS), a home Node B (HNB), a home evolved Node B, a transmit / receive point (TRP), or some other suitable terminology in the art, and is not limited to a particular technical terminology, provided that the same technical effect is achieved. It should be noted that in the embodiments of the present application, only the base station in the NR system is taken as an example for introduction, and the specific type of the base station is not limited.

[0045] The core network device can also be referred to as a core network node, a core network function, or a core network network element, etc., which includes but is not limited to at least one of the following: a mobility management entity (MME), an access and mobility management function (AMF), a session management function (SMF), a user plane function (UPF), a policy control function (PCF), a policy and charging rules function (PCRF), an edge application server discovery function (EASDF), a unified data management (UDM), a unified data repository (UDR), a home subscriber server (HSS), a centralized network configuration (CNC), a network repository function (NRF), a network exposure function (NEF), a local NEF (or L-NEF), a binding support function (BSF), an application function (AF), a location management function (LMF), a gateway mobile location center (GMLC), a network data analytics function (NWDAF), etc. It should be noted that only the core network device in the NR system is taken as an example for introduction in the embodiments of the present application, and the specific type of the core network device is not limited. If the name of the core network device mentioned in the embodiments of the present application changes in the subsequent protocol version (for example, 6G), it is also within the protection scope of the present application.

[0046] Optionally, the core network device can be implemented by one or more function modules in one device, or can be implemented by multiple devices together, and the embodiments of the present application do not make specific limitations. It can be understood that the above function modules can be network elements in a hardware device, software function modules running on a special hardware, or virtualized function modules instantiated on a platform (for example, a cloud platform).

[0047] First, the technical terms involved in the present application will be described below.

[0048] I. Artificial Intelligence (AI)

[0049] Artificial intelligence has been widely applied in various fields. Integrating artificial intelligence into wireless communication networks can significantly improve technical indicators such as throughput, latency, and user capacity, and is an important task for future wireless communication networks.

[0050] The algorithms used by the AI module have various types, such as neural networks, decision trees, support vector machines, and Bayesian classifiers. The present application takes the neural network as an example to illustrate the algorithm used by the AI module, but does not limit the specific type of algorithm used by the AI module.

[0051] A schematic diagram of a neural network is shown in FIG. 2. The neural network is composed of neurons, and a schematic diagram of a neuron is shown in FIG. 3. α1, α2…α K are inputs, w1, w2…w K are weights (multiplicative coefficients), b is a bias (additive coefficient), and σ(.) is an activation function. Common activation functions include Sigmoid, tanh, ReLU, etc.

[0052] The parameters of the neural network are optimized by a gradient optimization algorithm. Gradient optimization algorithms are a class of algorithms that minimize or maximize an objective function (sometimes also called a loss function), and the objective function is often a mathematical combination of model parameters and data. For example, given data X and its corresponding label Y, a neural network model f(.) is constructed. With the model, the predicted output f(X) can be obtained according to the input X, and the difference between the predicted value and the true value (f(X)-Y) can be calculated, which is the loss function. Our goal is to find appropriate W, b, so that the value of the above loss function reaches the minimum, and the smaller the loss value, the closer the model is to the true situation.

[0053] The common optimization algorithm at present is basically based on error back propagation (BP) algorithm. The basic idea of BP algorithm is that the learning process consists of two processes of forward propagation of signals and backward propagation of errors. When forward propagating, the input sample is transmitted from the input layer to the output layer through the processing of each hidden layer. If the actual output of the output layer does not match the expected output, the backward propagation of errors is entered. The error back propagation is to transmit the output error to the input layer through the hidden layer in a certain form, and allocate the error to all units of each layer to obtain the error signal of each unit, which is used as the basis for correcting the weights of each unit. The weight adjustment process of each layer is repeated. The process of continuously adjusting the weights is the learning and training process of the network. This process continues until the output error of the network is reduced to an acceptable level or the preset learning times are reached.

[0054] The common optimization algorithm includes gradient descent, stochastic gradient descent (SGD), mini-batch gradient descent, momentum method, Nesterov (the name of the inventor, specifically stochastic gradient descent with momentum), adaptive gradient descent (Adagrad), Adadelta, root mean square prop (RMSprop), adaptive moment estimation (Adam), etc.

[0055] These optimization algorithms, when error back propagation, are based on the error / loss obtained from the loss function, and the derivative / partial derivative of the current neuron is added to the learning rate, the previous gradient / derivative / partial derivative, etc. to obtain the gradient, and the gradient is transmitted to the previous layer.

[0056] II. AI unit / AI model

[0057] The AI unit / AI model described in the present application can also be referred to as an AI unit, an AI model, a machine learning (ML) model, an ML unit, an AI structure, an AI function, an AI feature, a machine learning model, a neural network, a neural network function, a neural network function, etc., or the AI unit / AI model can also refer to a processing unit capable of implementing specific algorithms, formulas, features, processing flows, capabilities, etc. related to AI, or the AI unit / AI model can be a processing method, algorithm, function, feature, module or unit for a specific data set, or the AI unit / AI model can be a processing method, algorithm, function, feature, module or unit running on AI / ML related hardware such as a Graphics Processing Unit (GPU), a Neural Processing Unit (NPU), a Tensor Processing Unit (TPU), or an Application-Specific Integrated Circuit (ASIC). The present application does not make specific limitations. Optionally, the specific data set includes the input and / or output of the AI unit / AI model.

[0058] Optionally, the identification of the AI unit / AI model can be an AI model identification, an AI parameter identification, an AI structure identification, an AI algorithm identification, or an identification of a specific data set associated with the AI unit / AI model, or an identification of a specific scene, environment, area, cell, channel feature, device related to AI / ML, or an identification of a function, feature, capability or module related to AI / ML. The present application does not make specific limitations.

[0059] The determination method, device, communication device and medium of the associated range of the associated identification provided by the embodiments of the present application will be described in detail below in combination with the drawings and some embodiments and their application scenarios.

[0060] Please refer to FIG. 4, the present application embodiment provides a kind of determination method of the associated range of the associated identification, comprising:

[0061] Step 41: the first communication device determines the Associated ID associated with the first object and the second object;

[0062] Step 42: the first communication device determines whether the associated range indicated by the Associated ID associated with the first object and the second object is the same according to the first rule in the case where the Associated ID associated with the first object and the second object is the same;

[0063] The first rule comprises one of the following:

[0064] In a case where the Associated IDs associated with the first object and the second object are the same, the Associated IDs associated with the first object and the second object indicate different association ranges.

[0065] In a case where the Associated IDs associated with the first object and the second object are the same, the Associated IDs associated with the first object and the second object indicate the same association range.

[0066] In a case where the Associated IDs associated with the first object and the second object are the same and the first object and the second object belong to a first set, the Associated IDs associated with the first object and the second object indicate different association ranges.

[0067] In a case where the Associated IDs associated with the first object and the second object are the same and the first object and the second object belong to a second set, the Associated IDs associated with the first object and the second object indicate the same association range. The second set is different from the first set.

[0068] In an embodiment of the present application, the first communication device can be a terminal or a network side device, and the network side device can be an access network device or a core network device.

[0069] In an embodiment of the present application, in a case where the Associated IDs associated with the first object and the second object are the same, whether the Associated IDs associated with the first object and the second object indicate the same association range is determined according to a first rule, so that each communication device can have a consistent understanding of the association range of the Associated ID, thereby improving the performance of the wireless communication system. In some embodiments, the first rule can be configured by the network side, reported or configured by the terminal, agreed by the protocol or offline agreement. The first rule can be determined in various ways, which increases flexibility.

[0070] In some embodiments, the first object and the second object are different reference signals (Reference Signal, RS) or artificial intelligence functions (AI functionality). The AI function can also be referred to as the function of an AI model. Of course, the object in the embodiments of the present application is not limited to this, and can also be other types of objects.

[0071] For example, RS1 is associated with Associated ID 1, RS2 is also associated with Associated ID 1, but the Associated ID associated by RS1 and RS2 actually associates different association ranges.

[0072] For another example, AI functionality 1 is associated with Associated ID 3, AI functionality 2 is also associated with Associated ID 3, but the Associated ID associated by AI functionality 1 and AI functionality 2 actually associates different association ranges.

[0073] In some embodiments, optionally, the Associated ID is used to show or implicitly indicate network side conditions or terminal side conditions, such as network side or terminal side antenna hardware type, antenna configuration, beam configuration, etc.

[0074] In some embodiments, optionally, the Associated ID can be configured or indicated in AI functionality, AI feature, AI feature group, AI component, etc. configuration, or in reference signal related resource configuration, resource set configuration, measurement configuration, reporting configuration, etc. configuration.

[0075] In some embodiments, optionally, the different reference signals include at least one of the following:

[0076] 1) Different types of reference signals;

[0077] Such as Channel State Information Reference Signal (CSI-RS) and tracking reference signal (TRS);

[0078] 2) Reference signals for different purposes;

[0079] Such as RS for beam measurement and RS for precoding matrix indication (PMI) / channel information compression.

[0080] 3) Reference signals of the same type but for different purposes;

[0081] Such as CSI-RS for beam measurement and CSI-RS for PMI / channel information compression.

[0082] 4) the same purpose but different types of reference signals;

[0083] 5) reference signals of different cells or base stations or cell groups or physical ranges;

[0084] 6) reference signals of the same type but different resource sets.

[0085] For example, RS of resource set 1 and RS of resource set 2.

[0086] In the embodiments of the present application, different reference signals can include multiple types, which can be set according to specific needs, so as to adapt to various scenarios.

[0087] In some embodiments, the first set and the second set can be defined at the same time, and it can be determined whether the first object and the second object belong to the first set or the second set.

[0088] In some embodiments, only the first set can be defined, and other objects outside the first set belong to the second set.

[0089] In some embodiments, only the second set can be defined, and other objects outside the second set belong to the first set.

[0090] In some embodiments, optionally, the first rule is that, in the case that the Associated IDs associated with the first object and the second object are the same, the Associated IDs associated with the first object and the second object indicate the same association range, or the first rule is that, in the case that the Associated IDs associated with the first object and the second object are the same and the first object and the second object belong to the second set, the Associated IDs associated with the first object and the second object indicate the same association range.

[0091] The different reference signals include at least one of the following:

[0092] 1) synchronization signal block (SSB) and channel state information reference signal (CSI-RS);

[0093] That is, in the case that the Associated IDs associated with the SSB and the CSI-RS are the same, the Associated IDs associated with the SSB and the CSI-RS indicate the same association range.

[0094] 3) different reference signals of the same purpose or the same AI functionality;

[0095] 3) different reference signals with the same quasi co-location (QCL) relationship;

[0096] If RS2 is configured or associated in the QCL relationship of RS1, and RS1 and RS2 are associated with the same Associated ID, the Associated ID associated with RS1 and RS2 indicates the same association range.

[0097] If RS2 is configured in the QCL-D (Type D) configuration of RS1, and a Transmission Configuration Indicator (TCI) is configured in the QCL-D configuration of RS1, and RS2 is configured in the TCI, and RS1 and RS2 are associated with the same Associated ID, the Associated ID associated with RS1 and RS2 indicates the same association range.

[0098] 4) Different reference signals with transmission association;

[0099] If SRS transmission is based on CSI-RS (in uplink non-codebook transmission, the precoding of SRS is obtained by measuring CSI-RS), and the SRS and the CSI-RS are associated with the same Associated ID, the Associated ID associated with the SRS and the CSI-RS indicates the same association range.

[0100] If DMRS transmission is based on PTRS (detecting phase noise, used to reduce the phase error of DMRS), CSI-RS (detecting downlink channel state information, used for beamforming of DMRS) or SRS (detecting uplink channel state information, using channel reciprocity to obtain downlink channel state information, used for beamforming of DMRS), and the DMRS and the PTRS, CSI-RS or SRS are associated with the same Associated ID, the Associated ID associated with the SRS and the PTRS, CSI-RS or SRS indicates the same association range.

[0101] 5) Different reference signals indicated by the network side.

[0102] If the network side indicates RS1 and RS2, and RS1 and RS2 are associated with the same Associated ID, the Associated ID associated with RS1 and RS2 indicates the same association range.

[0103] In some embodiments, optionally, the different reference signals with the same use or the same AI functionality include at least one of the following:

[0104] 2a) Different reference signals for beam report, beam measurement, cell report or cell measurement;

[0105] The beam report, for example, includes at least one of the following: L1 reference signal received power (L1-RSRP), L1 reference signal received quality (L1-RSRQ), L1 signal to interference plus noise ratio (L1-SINR), L3-RSRP, L3-RSRQ, L3-SINR, etc.

[0106] For example, in the case that the SSB and CSI-RS associated with the same Associated ID for beam measurement, the associated range indicated by the Associated ID of the SSB and CSI-RS associated is the same.

[0107] 2b) Different reference signals for AI model based beam management functionality;

[0108] 2c) Reference signals for the same purpose but located in different cells;

[0109] For example, SSBs for beam report, beam measurement, cell report or cell measurement, and different cells.

[0110] 2d) High-level AI functionality same but detailed-level AI functionality different reference signals.

[0111] For example, both for AI model based beam management functionality, but one RS for spatial beam prediction, one RS for time domain beam prediction.

[0112] For example, both for AI model based positioning, but one RS for direct positioning, one RS for indirect positioning.

[0113] For example, both for AI model based positioning, but one RS for supervised positioning, one RS for semi-supervised positioning.

[0114] In some embodiments, optionally, the different AIfunctionality includes at least one of:

[0115] different features;

[0116] different feature groups;

[0117] different components.

[0118] In some embodiments, optionally, the first rule is that, when the Associated IDs associated with the first object and the second object are the same, the associated ranges indicated by the Associated IDs associated with the first object and the second object are the same; or, when the Associated IDs associated with the first object and the second object are the same and the first object and the second object belong to a second set, the associated ranges indicated by the Associated IDs associated with the first object and the second object are the same.

[0119] The different AIfunctionality includes at least one of:

[0120] different AIfunctionality of the same high-level but different detailed-level;

[0121] different AIfunctionality indicated by the network side.

[0122] In some embodiments, optionally, the first object and the second object are different reference signals, and the first communication device determining the Associated IDs associated with the first object and the second object includes: the first communication device obtaining the Associated IDs associated with the first object and the second object from at least one of resource configuration, resource set configuration, associated measurement configuration, and associated reporting configuration of the first object and the second object. In the embodiments of the present application, the Associated IDs associated with the first object and the second object can be configured in multiple ways to increase flexibility.

[0123] In some embodiments, the first object and the second object are different AI functionalities, and the first communication device determining the Associated ID associated with the first object and the second object comprises: the first communication device obtaining the Associated ID associated with the first object and the second object from at least one of a feature configuration associated with the AI functionality, a feature group configuration associated with the AI functionality, and a component configuration associated with the AI functionality. In the embodiments of the present application, the Associated ID associated with the first object and the second object can be configured in various ways to increase flexibility.

[0124] In some embodiments, the Associated ID indicates at least one of the following:

[0125] a network side condition;

[0126] a terminal side condition;

[0127] data set information;

[0128] data feature information;

[0129] a network side condition used for training of a target AI model;

[0130] a network side condition used for inference of the target AI model;

[0131] a terminal side condition used for training of the target AI model;

[0132] a terminal side condition used for inference of the target AI model.

[0133] In the embodiments of the present application, the association range types are various to adapt to different application scenarios.

[0134] In some embodiments, the network side condition comprises at least one of the following:

[0135] network side hardware information;

[0136] network side signaling configuration;

[0137] physical cell information;

[0138] serving cell information;

[0139] area information;

[0140] cell group information;

[0141] cell list information;

[0142] network side surrounding wireless environment or wireless signal feature.

[0143] In some embodiments, optionally, the terminal-side condition comprises at least one of:

[0144] terminal-side hardware information;

[0145] terminal-side signaling configuration;

[0146] terminal-side surrounding wireless environment or wireless signal feature.

[0147] In some embodiments, optionally, the dataset information comprises at least one of: dataset information used for training of the target AI model, dataset information used for inference of the target AI model.

[0148] In some embodiments, optionally, the data feature information comprises at least one of: data feature information used for training of the target AI model, data feature information used for inference of the target AI model.

[0149] In some embodiments, optionally, the target AI model is used for one of:

[0150] 1) reference signal processing;

[0151] The reference signal processing comprises at least one of: signal detection, filtering, equalization, etc., and the reference signal comprises at least one of: Demodulation Reference Signal (DMRS), Sounding Reference Signal (SRS), Synchronization Signal and PBCH block (SSB), Channel State Information Reference Signal (CSI-RS), Tracking Reference Signal (TRS), Positioning Reference Signals (PRS), Phase-tracking reference signal (PTRS), etc.

[0152] 2) channel signal transmission, reception, demodulation and / or sending;

[0153] The channel includes at least one of a physical downlink control channel (PDCCH), a physical downlink shared channel (PDSCH), a physical uplink control channel (PUCCH), a physical uplink shared channel (PUSCH), a physical random access channel (PRACH), a physical broadcast channel (PBCH), and the like.

[0154] 3) Channel state information acquisition;

[0155] The channel state information acquisition includes at least one of:

[0156] 3a) Channel state information feedback, the channel state information including at least one of channel-related information, channel matrix-related information, channel feature information, channel matrix feature information, a precoding matrix indicator (PMI), a rank indication (RI), a CSI-RS resource indicator (CRI), a channel quality indicator (CQI), a layer indicator (LI), and the like.

[0157] 3b) Frequency division duplex (FDD) uplink-downlink partial reciprocity. For an FDD system, according to the partial reciprocity, the base station can inform the terminal of angle information and time delay information through a CSI-RS precoding or direct indication method according to the uplink channel acquisition angle and time delay information, and the terminal reports according to the indication of the base station or selects and reports within the indication range of the base station, thereby reducing the calculation amount of the terminal and the overhead of channel state information (CSI) reporting.

[0158] 4) Beam management;

[0159] The beam management includes at least one of beam measurement, beam reporting, beam prediction (spatial domain prediction or frequency domain prediction), beam failure detection, beam failure recovery, and new beam indication in beam failure recovery.

[0160] 5) Channel prediction;

[0161] The channel prediction comprises at least one of the following: prediction of channel state information, beam prediction.

[0162] 6) Channel and / or source coding;

[0163] The channel and / or source coding comprises at least one of the following: channel coding, channel decoding, source coding, source decoding, joint source channel coding, joint source channel decoding.

[0164] 7) Interference suppression;

[0165] The interference suppression comprises at least one of the following: intra-cell interference, inter-cell interference, out-of-band interference, intermodulation interference, etc.

[0166] 8) Positioning;

[0167] The positioning can be a specific position (including horizontal position and / or vertical position) or a future possible trajectory of the terminal estimated by a reference signal (such as SRS), or information assisting position estimation or trajectory estimation, such as Timing of Arrival (TOA), line of sight or non-line of sight, or Reference Signal Time Difference (RSTD).

[0168] 9) Prediction and / or management of higher layer service and / or parameter;

[0169] The parameter may, for example, comprise at least one of the following: throughput, required data packet size, service demand, moving speed, noise information, etc.

[0170] 10) Encoding and / or parsing of control signaling.

[0171] The control signaling may, for example, comprise at least one of the following: power control related signaling, beam management related signaling.

[0172] The method for determining the association range of the association identifier provided in the embodiments of the present application can be executed by the device for determining the association range of the association identifier. In the embodiments of the present application, the device for determining the association range of the association identifier is taken as an example to illustrate the device for determining the association range of the association identifier provided in the embodiments of the present application.

[0173] The embodiment of the present application provides a determination device of an association range of an association identifier. As an example, the determination device of the association range of the association identifier can be a communication device or a component in the communication device, such as a chip. The communication device can be a terminal, a network side device, a server or the like. For example, the terminal can include but is not limited to the types of the terminal 11 listed above, the network side device can include but is not limited to the types of the network side device 12 listed above, and the embodiment of the present application is not limited specifically.

[0174] The determination device of the association range of the association identifier includes a receiving module, a sending module and a processing module. The receiving module, the sending module and the processing module can be implemented by software or by hardware. When implemented by hardware, the processing module can be implemented by a processor. For example, the processor can include a general processor, a special processor or the like, such as a central processing unit (CPU), a microprocessor, a digital signal processor (DSP), an artificial intelligent (AI) processor, a graphics processing unit (GPU), an application specific integrated circuit (ASIC), a network processor (NP), a field programmable gate array (FPGA) or other programmable logic devices, a gate circuit, a transistor, a discrete hardware component or the like. The receiving module and the sending module can be implemented by a communication interface. The communication interface can include one or more of a transceiver, a pin, a circuit, a bus, a radio frequency unit or the like.

[0175] Specifically, referring to FIG. 5, the determination device 50 of the association range of the association identifier includes:

[0176] The processing module 51 is configured to determine an association identifier Associated ID associated with a first object and a second object, and determine whether an association range indicated by the Associated ID associated with the first object and the second object is the same according to a first rule in a case where the Associated ID associated with the first object and the second object is the same.

[0177] The first rule includes one of the following:

[0178] In a case where the first object and the second object are associated with the same Associated ID, the first object and the second object are associated with the Associated ID indicating different association ranges.

[0179] In a case where the first object and the second object are associated with the same Associated ID, the first object and the second object are associated with the Associated ID indicating the same association range.

[0180] In a case where the first object and the second object are associated with the same Associated ID and belong to a first set, the first object and the second object are associated with the Associated ID indicating different association ranges.

[0181] In a case where the first object and the second object are associated with the same Associated ID and belong to a second set, the first object and the second object are associated with the Associated ID indicating the same association range; the second set is different from the first set.

[0182] In the embodiments of the present application, in a case where the first object and the second object are associated with the same Associated ID, whether the first object and the second object are associated with the Associated ID indicating the same association range is determined according to a first rule, so that each communication device can have a consistent understanding of the association range of the Associated ID, thereby improving the performance of the wireless communication system.

[0183] In some embodiments, optionally, the first rule is configured by a network side, reported or configured by a terminal, agreed by a protocol or offline.

[0184] In some embodiments, optionally, the first object and the second object are different reference signals or AI functionalities.

[0185] In some embodiments, optionally, the different reference signals include at least one of the following:

[0186] Different types of reference signals;

[0187] Reference signals for different purposes;

[0188] Reference signals of the same type but for different purposes;

[0189] Reference signals of the same purpose but of different types;

[0190] Reference signals of different cells or base stations or cell groups or physical ranges;

[0191] Reference signals of the same type but different resource sets.

[0192] In some embodiments, optionally, the first rule is that, in the case that the Associated IDs associated with the first object and the second object are the same, the associated ranges indicated by the Associated IDs associated with the first object and the second object are the same, or, in the case that the Associated IDs associated with the first object and the second object are the same and the first object and the second object belong to the second set, the associated ranges indicated by the Associated IDs associated with the first object and the second object are the same;

[0193] The different reference signals include at least one of the following:

[0194] Synchronization signal blocks (SSBs) and channel state information reference signals (CSI-RSs);

[0195] Different reference signals of the same use or the same AI functionality;

[0196] Different reference signals having the same quasi-co-location (QCL) relationship;

[0197] Different reference signals having transmission association;

[0198] Different reference signals indicated by the network side.

[0199] In some embodiments, optionally, the different reference signals of the same use or the same AI functionality include at least one of the following:

[0200] Different reference signals for beam reporting, beam measurement, cell reporting, or cell measurement;

[0201] Different reference signals for a beam management function based on a target AI model;

[0202] Reference signals of the same use and located in different cells;

[0203] Reference signals of the same High-level AI functionality but different detailed-level AI functionality.

[0204] In some embodiments, optionally, the different AI functionality includes at least one of the following:

[0205] Different features;

[0206] different feature groups;

[0207] different components.

[0208] In some embodiments, optionally, the first rule is that the Associated IDs associated with the first object and the second object are the same, and the Associated IDs associated with the first object and the second object indicate the same association range; or the first rule is that the Associated IDs associated with the first object and the second object are the same, and the first object and the second object belong to a second set, and the Associated IDs associated with the first object and the second object indicate the same association range.

[0209] The different AIfunctionality includes at least one of the following:

[0210] AIfunctionality of a high level and AIfunctionality of a detailed level;

[0211] Different AIfunctionality indicated by the network side.

[0212] In some embodiments, optionally, the first object and the second object are different reference signals, and the processing module 51 is configured to obtain the Associated IDs associated with the first object and the second object from at least one of resource configuration, resource set configuration, associated measurement configuration, and associated reporting configuration of the first object and the second object.

[0213] In some embodiments, optionally, the first object and the second object are different AIfunctionality, and the processing module 51 is configured to obtain the Associated IDs associated with the first object and the second object from at least one of feature configuration, feature group configuration, and component configuration associated with the AIfunctionality.

[0214] In some embodiments, optionally, the association range indicated by the Associated ID includes at least one of the following:

[0215] Network side conditions;

[0216] Terminal side conditions;

[0217] dataset information;

[0218] data feature information;

[0219] network side condition used for training of the target AI model;

[0220] network side condition used for inference of the target AI model;

[0221] terminal side condition used for training of the target AI model;

[0222] terminal side condition used for inference of the target AI model.

[0223] In some embodiments, the network side condition comprises at least one of:

[0224] network side hardware information;

[0225] network side signaling configuration;

[0226] physical cell information;

[0227] serving cell information;

[0228] area information;

[0229] cell group information;

[0230] cell list information;

[0231] network side surrounding wireless environment or wireless signal feature.

[0232] In some embodiments, the terminal side condition comprises at least one of:

[0233] terminal side hardware information;

[0234] terminal side signaling configuration;

[0235] terminal side surrounding wireless environment or wireless signal feature.

[0236] In some embodiments, the target AI model is used for one of:

[0237] reference signal processing;

[0238] channel signal transmission, reception, demodulation and / or sending;

[0239] channel state information acquisition;

[0240] beam management;

[0241] channel prediction;

[0242] channel and / or source coding;

[0243] Interference suppression

[0244] Positioning

[0245] Prediction and / or management of higher layer services and / or parameters

[0246] Encoding and / or parsing of control signaling.

[0247] The determination apparatus for the association range of the association identifier provided by the embodiments of the present application can realize each process of the method embodiment of Figure 4 and achieve the same technical effects. To avoid repetition, details are not described here.

[0248] As shown in Figure 6, the embodiments of the present application also provide a communication device 60, which includes a processor 61 and a memory 62, and the memory 62 stores programs or instructions executable on the processor 61. When the programs or instructions are executed by the processor 61, each step of the above-mentioned determination method for the association range of the association identifier embodiment is realized, and the same technical effects can be achieved. To avoid repetition, details are not described here.

[0249] The embodiments of the present application also provide a terminal, which includes a processor and a communication interface, the communication interface and the processor are coupled, and the processor is used to run programs or instructions to realize the steps in the method embodiment shown in Figure 4. The terminal embodiment corresponds to the above-mentioned first communication device side method embodiment, and each implementation process and implementation manner of the above-mentioned method embodiment can be applied to the terminal embodiment, and the same technical effects can be achieved. The terminal can be the determination apparatus for the association range of the association identifier shown in Figure 5. Specifically, Figure 7 is a hardware structure schematic diagram of a terminal for realizing the embodiments of the present application.

[0250] The terminal 70 includes, but is not limited to, at least part of components such as a radio frequency unit 71, a network module 72, an audio output unit 73, an input unit 74, a sensor 75, a display unit 76, a user input unit 77, an interface unit 78, a memory 79, and a processor 710.

[0251] Those skilled in the art can understand that the terminal 70 can also include a power supply (such as a battery) for supplying power to each component, and the power supply can be logically connected with the processor 710 through a power management system, so as to realize functions such as management of charging, discharging, and power consumption management through the power management system. The terminal structure shown in Figure 7 does not constitute a limitation on the terminal, and the terminal can include more or fewer components than the illustrated, or combine certain components, or different component arrangements, which are not described here.

[0252] It should be understood that in the embodiments of the present application, the input unit 74 can include a graphics processor 741 and a microphone 742, and the graphics processor 741 processes image data of a still picture or a video obtained by an image capture device (such as a camera) in a video capture mode or an image capture mode. The display unit 76 can include a display panel 761, which can be configured in the form of a liquid crystal display, an organic light-emitting diode, etc. The user input unit 77 includes at least one of a touch panel 771 and other input devices 772. The touch panel 771 is also called a touch screen. The touch panel 771 can include two parts of a touch detection device and a touch controller. The other input devices 772 can include, but are not limited to, a physical keyboard, function keys (such as volume control keys, on-off keys, etc.), a trackball, a mouse, a joystick, and the like, which will not be described here.

[0253] In the embodiments of the present application, after the radio frequency unit 71 receives the downlink data from the network side device, it can be transmitted to the processor 710 for processing. In addition, the radio frequency unit 71 can send uplink data to the network side device. Generally, the radio frequency unit 71 includes, but is not limited to, an antenna, an amplifier, a transceiver, a coupler, a low noise amplifier, a duplexer, etc.

[0254] The memory 79 can be used to store software programs or instructions and various data. The memory 79 can mainly include a first storage area storing programs or instructions and a second storage area storing data, wherein the first storage area can store an operating system, application programs or instructions required by at least one function (such as a sound playing function, an image playing function, etc.), and the like. In addition, the memory 79 can include a volatile memory or a non-volatile memory. The non-volatile memory can be a Read-Only Memory (ROM), a Programmable ROM (PROM), an Erasable Programmable ROM (EPROM), an Electrically EPROM (EEPROM), or a flash memory. The volatile memory can be a Random Access Memory (RAM), a Static RAM (SRAM), a Dynamic RAM (DRAM), a Synchronous DRAM (SDRAM), a Double Data Rate SDRAM (DDR SDRAM), an Enhanced SDRAM (ESDRAM), a Synchlink DRAM (SLDRAM), and a Direct Rambus RAM (DRRAM). The memory 79 in the embodiments of the present application includes but is not limited to these and any other suitable types of memory.

[0255] The processor 710 can include one or more processing units; optionally, the processor 710 integrates an application processor and a modem processor, wherein the application processor mainly processes operations related to an operating system, a user interface, and an application program, and the modem processor mainly processes wireless communication signals, such as a baseband processor. It can be understood that the above-mentioned modem processor can also not be integrated into the processor 710.

[0256] The processor 710 is configured to determine an associated identification Associated ID associated with the first object and the second object.

[0257] The first communication device determines, according to a first rule, whether the association range indicated by the Associated ID associated with the first object and the second object is the same in the case that the Associated ID associated with the first object and the second object is the same.

[0258] The first rule comprises one of the following:

[0259] In a case where the Associated IDs associated with the first object and the second object are the same, the Associated IDs associated with the first object and the second object indicate different association ranges.

[0260] In a case where the Associated IDs associated with the first object and the second object are the same, the Associated IDs associated with the first object and the second object indicate the same association range.

[0261] In a case where the Associated IDs associated with the first object and the second object are the same and the first object and the second object belong to a first set, the Associated IDs associated with the first object and the second object indicate different association ranges.

[0262] In a case where the Associated IDs associated with the first object and the second object are the same and the first object and the second object belong to a second set, the Associated IDs associated with the first object and the second object indicate the same association range. The second set is different from the first set.

[0263] In the embodiments of the present application, in a case where the Associated IDs associated with the first object and the second object are the same, it is determined according to the first rule whether the Associated IDs associated with the first object and the second object indicate the same association range, so that each communication device can have a consistent understanding of the association range of the Associated ID, thereby improving the performance of the wireless communication system.

[0264] It can be understood that the implementation processes of each implementation mode mentioned in the embodiments can refer to the related descriptions of the method embodiments shown in FIG. 4, and achieve the same or corresponding technical effects. To avoid repetition, they will not be described here again.

[0265] The embodiments of the present application also provide a network side device, comprising a processor and a communication interface, the communication interface and the processor are coupled, the processor is used to run programs or instructions to realize the steps of the method embodiments shown in FIG. 4. The network side device embodiments correspond to the method embodiments of the first communication device side described above, and each implementation process and implementation mode of the above method embodiments can be applied to the network side device embodiments, and the same technical effects can be achieved.

[0266] Specifically, the embodiment of the present application further provides a network side device, which can be the determination apparatus of the association range of the association identifier as shown in FIG. 5. As shown in FIG. 8, the network side device 80 comprises an antenna 81, a radio frequency device 82, a baseband device 83, a processor 84 and a memory 85. The antenna 81 is connected with the radio frequency device 82. In the uplink direction, the radio frequency device 82 receives information through the antenna 81, and sends the received information to the baseband device 83 for processing. In the downlink direction, the baseband device 83 processes the information to be sent, and sends the processed information to the radio frequency device 82, which processes the received information and sends the processed information out through the antenna 81.

[0267] The method performed by the network side device in the above embodiment can be implemented in the baseband device 83, which comprises a baseband processor.

[0268] The baseband device 83 can comprise at least one baseband board, for example, on which a plurality of chips are arranged, as shown in FIG. 8. One of the chips is a baseband processor, for example, which is connected with the memory 85 through a bus interface to call the program in the memory 85 and perform the operations of the network device shown in the above method embodiment.

[0269] The network side device can further comprise a network interface 86, which is a common public radio interface (CPRI), for example.

[0270] Specifically, the network side device 80 of the embodiment of the present application further comprises instructions or programs stored in the memory 85 and executable on the processor 84, and the processor 84 calls the instructions or programs in the memory 85 to perform the method performed by each module shown in FIG. 5 and achieve the same technical effects. To avoid repetition, details are not described herein.

[0271] Specifically, the embodiment of the present application further provides a network side device. As shown in FIG. 9, the network side device 90 comprises a processor 91, a network interface 92 and a memory 93. The network side device can be the determination apparatus of the association range of the association identifier as shown in FIG. 5. The network interface 92 is a common public radio interface (CPRI), for example.

[0272] Specifically, the network side device 90 of the embodiment of the present application further comprises instructions or programs stored in the memory 93 and executable on the processor 91, and the processor 91 calls the instructions or programs in the memory 93 to perform the method performed by each module shown in FIG. 5 and achieve the same technical effects. To avoid repetition, details are not described herein.

[0273] The embodiment of the present application further provides a readable storage medium, wherein a program or instructions are stored on the readable storage medium, the program or instructions are executed by a processor to implement each process of the method for determining the association range of the association identifier, and the same technical effects can be achieved. To avoid repetition, details are not described herein.

[0274] The processor is the processor in the terminal in the above-described embodiments. The readable storage medium includes a computer readable storage medium, such as a computer readable only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and the like. In some examples, the readable storage medium can be a non-transitory readable storage medium.

[0275] The embodiment of the present application further provides a chip, which includes a processor and a communication interface, the communication interface is coupled with the processor, and the processor is used to run a program or instructions to implement each process of the method for determining the association range of the association identifier, and the same technical effects can be achieved. To avoid repetition, details are not described herein.

[0276] It should be understood that the chip mentioned in the embodiment of the present application can also be referred to as a system chip, a system chip, a chip system or a system on chip, and the like.

[0277] The embodiment of the present application further provides a computer program / program product, which is stored in a storage medium, and is executed by at least one processor to implement each process of the method for determining the association range of the association identifier, and the same technical effects can be achieved. To avoid repetition, details are not described herein.

[0278] It should be understood that, in this document, the term "comprising" or "including" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements not only includes those elements, but also includes other elements not explicitly listed or inherent to such a process, method, article or device. Without more limitations, the element defined by the statement "including a" does not exclude the presence of additional identical elements in the process, method, article or device including the element. In addition, it should be noted that the scope of the method and device in the embodiments of the present application is not limited to the order of performing the functions as shown or discussed, but can also include performing the functions in a substantially simultaneous manner or in a reverse order, for example, the described method can be performed in an order different from the described order, and various steps can be added, omitted or combined. In addition, the features described with reference to some examples can be combined in other examples.

[0279] Through the description of the above embodiments, those skilled in the art can clearly understand that the above-mentioned example methods can be realized by means of a computer software product and a general hardware platform as necessary, and of course can also be realized by hardware. The computer software product is stored in a storage medium (such as a ROM, a RAM, a magnetic disc, an optical disc, etc.), and includes a plurality of instructions for enabling a terminal or a network side device to execute the method described in each embodiment of the present application.

[0280] The embodiments of the present application are described above in combination with the drawings, but the present application is not limited to the specific embodiments described above, and the specific embodiments described above are merely illustrative rather than limiting. Those skilled in the art can make many forms of embodiments under the inspiration of the present application without departing from the scope of the present application and the scope protected by the claims, and these embodiments all belong to the protection of the present application.

Claims

1. A method of determining a range of association for an association identifier, wherein, The method comprises: A first communication device determines an associated ID of a first object and a second object; The first communication device determines whether the associated range indicated by the associated ID of the first object and the second object is the same according to a first rule in the case that the associated ID of the first object and the second object is the same; The first rule comprises one of the following: In the case that the associated ID of the first object and the second object is the same, the associated range indicated by the associated ID of the first object and the second object is different; In the case that the associated ID of the first object and the second object is the same, the associated range indicated by the associated ID of the first object and the second object is the same; In the case that the associated ID of the first object and the second object is the same and the first object and the second object belong to a first set, the associated range indicated by the associated ID of the first object and the second object is different; In the case that the associated ID of the first object and the second object is the same and the first object and the second object belong to a second set, the associated range indicated by the associated ID of the first object and the second object is the same; the second set is different from the first set.

2. The method of claim 1, wherein, The first rule is configured by a network side, reported or configured by a terminal, agreed by a protocol or offline agreement.

3. The method of claim 1 or 2, wherein, The first object and the second object are different reference signals or AIfunctionality.

4. The method of claim 3, wherein, The different reference signals comprise at least one of the following: Different types of reference signals; Different purpose reference signals; Reference signals of the same type but different purposes; Reference signals of the same purpose but different types; Reference signals of different cells or base stations or cell groups or physical ranges; Reference signals of the same type but different resource sets.

5. The method of claim 3, wherein, The first rule is that the associated range indicated by the associated ID of the first object and the second object is the same in the case that the associated ID of the first object and the second object is the same, or the first rule is that the associated range indicated by the associated ID of the first object and the second object is the same in the case that the associated ID of the first object and the second object is the same and the first object and the second object belong to a second set; The different reference signals comprise at least one of the following: Synchronization signal block (SSB) and channel state information reference signal (CSI-RS); Different reference signals of the same purpose or the same AIfunctionality; Different reference signals with the same quasi co-location (QCL) relationship; Different reference signals with transmission association; Different reference signals indicated by a network side.

6. The method of claim 5, wherein, The same use or different reference signals of the same AIfunctionality include at least one of the following: Different reference signals for beam reporting, beam measurement, cell reporting, or cell measurement; Different reference signals for AI model-based beam management functions; Reference signals of the same use and located in different cells; Reference signals of the same High-level AIfunctionality but different detailed-level AIfunctionality.

7. The method of claim 3, wherein, The different AIfunctionality includes at least one of the following: Different features; Different feature groups; Different components.

8. The method of claim 3, wherein, The first rule is that the Associated ID of the first object and the second object is the same, and the associated range indicated by the Associated ID of the first object and the second object is the same; or the first rule is that the Associated ID of the first object and the second object is the same, and the first object and the second object belong to the second set, and the associated range indicated by the Associated ID of the first object and the second object is the same. The different AIfunctionality includes at least one of the following: The same High-level AIfunctionality but different detailed-level AIfunctionality; Different AIfunctionality indicated by the network side.

9. The method of claim 3, wherein, The first object and the second object are different reference signals, and the first communication device determines the Associated ID associated with the first object and the second object, including: The first communication device obtains the Associated ID associated with the first object and the second object from at least one of the resource configuration, resource set configuration, associated measurement configuration, and associated reporting configuration of the first object and the second object.

10. The method of claim 3, wherein, The first object and the second object are different AIfunctionality, and the first communication device determines the Associated ID associated with the first object and the second object, including: The first communication device obtains the Associated ID associated with the first object and the second object from at least one of the feature configuration, associated feature group configuration, and associated component configuration of the AIfunctionality.

11. The method of any one of claims 1-10, wherein, The associated range indicated by the Associated ID includes at least one of the following: Network side conditions; Terminal side conditions; Data set information; Data feature information; Network side conditions used for training of the target AI model; Network side conditions used for inference of the target AI model; Terminal-side conditions used by the target AI model for training; Terminal-side conditions used by the target AI model for inference.

12. The method of claim 11, wherein, The network-side conditions include at least one of: Network-side hardware information; Network-side signaling configuration; Physical cell information; Serving cell information; Area information; Cell group information; Cell list information; Network-side surrounding wireless environment or wireless signal characteristics.

13. The method of claim 11, wherein, The terminal-side conditions include at least one of: Terminal-side hardware information; Terminal-side signaling configuration; Terminal-side surrounding wireless environment or wireless signal characteristics.

14. The method of claim 6 or 11, wherein, The target AI model is used for one of: Reference signal processing; Channel signal transmission, reception, demodulation, and / or sending; Channel state information acquisition; Beam management; Channel prediction; Channel and / or source coding and decoding; Interference suppression; Positioning; Prediction and / or management of higher-layer services and / or parameters; Encoding and / or parsing of control signaling.

15. An apparatus for determining a range of association for an association identifier, wherein, Comprise: A processing module configured to determine an associated ID (Associated ID) associated with a first object and a second object; In a case where the Associated ID associated with the first object and the second object is the same, determine whether the associated range indicated by the Associated ID associated with the first object and the second object is the same according to a first rule; The first rule includes one of: In a case where the Associated ID associated with the first object and the second object is the same, the associated range indicated by the Associated ID associated with the first object and the second object is different; In a case where the Associated ID associated with the first object and the second object is the same, the associated range indicated by the Associated ID associated with the first object and the second object is the same; In a case where the Associated ID associated with the first object and the second object is the same, and the first object and the second object belong to a first set, the associated range indicated by the Associated ID associated with the first object and the second object is different; In a case where the Associated ID associated with the first object and the second object is the same, and the first object and the second object belong to a second set, the associated range indicated by the Associated ID associated with the first object and the second object is the same; the second set is different from the first set.

16. The apparatus of claim 15, wherein, The first object and the second object are different reference signals or AI functionalities.

17. The apparatus of claim 16, wherein, The different reference signals include at least one of: Different types of reference signals; Reference signals for different purposes; Reference signals of the same type but for different purposes; Reference signals of the same purpose but of different types; Reference signals of different cells or base stations or cell groups or physical ranges; Reference signals of the same type but different resource sets.

18. The apparatus of claim 16, wherein, The first rule is that the Associated IDs of the first object and the second object are the same, and the associated ranges indicated by the Associated IDs of the first object and the second object are the same, or the first rule is that the Associated IDs of the first object and the second object are the same, and the first object and the second object belong to a second set, and the associated ranges indicated by the Associated IDs of the first object and the second object are the same. The different reference signals include at least one of the following: Synchronization signal block (SSB) and channel state information reference signal (CSI-RS); Different reference signals with the same use or the same AI functionality; Different reference signals with the same quasi co-location (QCL) relationship; Different reference signals with transmission association; Different reference signals indicated by the network side.

19. The apparatus of claim 16, wherein, The different AI functionalities include at least one of the following: Different features; Different feature groups; Different components.

20. The apparatus of claim 16, wherein, The first rule is that the Associated IDs of the first object and the second object are the same, and the associated ranges indicated by the Associated IDs of the first object and the second object are the same, or the first rule is that the Associated IDs of the first object and the second object are the same, and the first object and the second object belong to a second set, and the associated ranges indicated by the Associated IDs of the first object and the second object are the same. The different AI functionalities include at least one of the following: High-level AI functionalities that are the same but have different detailed levels; Different AI functionalities indicated by the network side.

21. The apparatus of claim 16, wherein, The first object and the second object are different reference signals, and the processing module is configured to obtain the Associated ID associated with the first object and the second object from at least one of resource configuration, resource set configuration, associated measurement configuration, and associated reporting configuration of the first object and the second object.

22. The apparatus of claim 16, wherein, The first object and the second object are different AI functionalities, and the processing module is configured to obtain the Associated ID associated with the first object and the second object from at least one of feature configuration, feature group configuration, and component configuration associated with the AI functionality.

23. The apparatus of any of claims 15-22, wherein, The associated range indicated by the Associated ID includes at least one of the following: Network side conditions; Terminal side conditions; Dataset information; Data feature information; Network side condition used for training of the target AI model; Network side condition used for inference of the target AI model; Terminal side condition used for training of the target AI model; Terminal side condition used for inference of the target AI model.

24. A communications device, comprising: A processor and a memory, the memory storing a program or instructions executable on the processor, the program or instructions being executed by the processor to implement the steps of the method for determining the association range of the association identifier according to any one of claims 1 to 14.

25. A readable storage medium, wherein, A readable storage medium storing a program or instructions executable by a processor to implement the method for determining the association range of the association identifier according to any one of claims 1 to 14.

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