Interference prediction methods and apparatuses, and device and storage medium

Abstract

The present application belongs to the technical field of wireless communications. Disclosed are interference prediction methods and apparatuses, and a device and a storage medium. An interference prediction method in the embodiments of the present application comprises: a terminal receiving first auxiliary information from a network-side device; and performing interference prediction on the basis of the first auxiliary information, thereby improving the accuracy of interference prediction.

Description

Interference prediction methods, apparatus, equipment and storage media

[0001] Cross-reference of related applications

[0002] This application claims priority to Chinese Patent Application No. 202411917253.5, filed on December 24, 2024, entitled "Interference Prediction Method, Apparatus, Device and Storage Medium", the entire contents of which are incorporated herein by reference. Technical Field

[0003] This application belongs to the field of communication technology, and specifically relates to an interference prediction method, apparatus, device, and storage medium. Background Technology

[0004] In existing communication systems, terminals are susceptible to interference from various sources, such as neighboring base stations and other terminals. The interference experienced by the terminal includes interference power or interference-plus-noise (IpN). Interference can lead to poor signal transmission quality, ultimately causing reception errors or failures. Currently, interference prediction and reporting are possible on the terminal side, but the accuracy of interference prediction results is low. Summary of the Invention

[0005] This application provides an interference prediction method, apparatus, device, and storage medium that can improve the accuracy of interference prediction.

[0006] In a first aspect, an interference prediction method is provided, executed by a terminal, the method comprising: receiving first auxiliary information from a network-side device; and performing interference prediction based on the first auxiliary information.

[0007] In some exemplary embodiments, the terminal performs interference prediction based on the first auxiliary information, including: the terminal determines an AI interference prediction model to be used for interference prediction based on the first auxiliary information; and the terminal uses the AI ​​interference prediction model to perform interference prediction.

[0008] In some exemplary embodiments, the method further includes:

[0009] The terminal receives at least one of the following information from the network-side device: interference measurement configuration information or interference reporting configuration information;

[0010] The terminal performs interference measurement using the corresponding interference measurement resources according to the interference measurement configuration information to obtain interference measurement information;

[0011] The terminal uses the AI ​​interference prediction model to predict interference, including:

[0012] The terminal obtains interference prediction information based on the interference measurement information and the AI ​​interference prediction model;

[0013] The terminal sends the interference prediction information to the network-side device according to the interference reporting configuration information.

[0014] Secondly, an interference prediction method is provided, which is executed by a network-side device. The method includes: sending first auxiliary information to a terminal, wherein the first auxiliary information is used by the terminal to perform interference prediction.

[0015] In some exemplary embodiments, the method further includes:

[0016] The network-side device determines interference measurement resources for the terminal based on the reference signal type supported by the terminal when performing interference prediction or the first indication information. The first indication information is used to indicate whether the terminal supports the demodulation reference signal (DMRS) type when performing interference measurement or interference prediction.

[0017] The network-side device sends the interference measurement resources to the terminal.

[0018] In some exemplary embodiments, the network-side device determines interference measurement resources for the terminal based on the reference signal type supported by the terminal when performing interference prediction or the first indication information, including:

[0019] When the terminal supports DMRS type among the reference signal types when performing interference measurement or prediction, or when the first indication information indicates that the terminal supports DMRS type when performing measurement or interference prediction, then DMRS resources are configured for the terminal as interference measurement resources.

[0020] In some exemplary embodiments, the method further includes:

[0021] The network-side device sends at least one of the following information to the terminal: interference measurement configuration information or interference reporting configuration information;

[0022] The network-side device receives interference prediction information from the terminal. The interference prediction information is sent by the terminal according to the interference reporting configuration information. The interference prediction information is predicted by the terminal based on the interference measurement information. The interference measurement information is measured by the terminal based on the interference measurement configuration information.

[0023] In some exemplary embodiments, the method further includes:

[0024] The network-side device determines scheduling information for the terminal based on the interference prediction information;

[0025] The network-side device sends the scheduling information to the terminal.

[0026] Thirdly, an interference prediction device is provided, comprising: a receiving module for receiving first auxiliary information from a network-side device; and a processing module for performing interference prediction based on the first auxiliary information.

[0027] Fourthly, an interference prediction device is provided, comprising: a transmitting module for transmitting first auxiliary information to a terminal, the first auxiliary information being used by the terminal to perform interference prediction.

[0028] Fifthly, an interference prediction apparatus is provided, the apparatus being configured to perform the steps of the method described in the first aspect, or to implement the steps of the method described in the second aspect.

[0029] In a sixth aspect, a terminal is provided, the terminal including a processor and a memory, the memory storing a program or instructions executable on the processor, the program or instructions, when executed by the processor, implementing the steps of the method as described in the first aspect.

[0030] In a seventh aspect, a terminal is provided, including a processor and a communication interface, wherein the communication interface is used to receive first auxiliary information from a network-side device, and the processor is used to perform interference prediction based on the first auxiliary information.

[0031] Eighthly, a network-side device is provided, the network-side device including a processor and a memory, the memory storing a program or instructions executable on the processor, the program or instructions, when executed by the processor, implementing the steps of the method as described in the second aspect.

[0032] In a ninth aspect, a network-side device is provided, including a processor and a communication interface, wherein the processor is used to generate first auxiliary information, and the communication interface is used to send the first auxiliary information to a terminal, the first auxiliary information being used by the terminal to perform interference prediction.

[0033] In a tenth aspect, a readable storage medium is provided, on which a program or instructions are stored, which, when executed by a processor, implement the steps of the method described in the first aspect, or implement the steps of the method described in the second aspect.

[0034] Eleventhly, a wireless communication system is provided, comprising: a terminal and a network-side device, wherein the terminal can be used to perform the steps of the method as described in the first aspect, and the network-side device can be used to perform the steps of the method as described in the second aspect.

[0035] In a twelfth aspect, a chip is provided, the chip including a processor and a communication interface coupled to the processor, the processor being configured to run a program or instructions to implement the steps of the method described in the first aspect, or to implement the steps of the method described in the second aspect.

[0036] In a thirteenth aspect, a computer program / program product is provided, which is stored in a storage medium and is executed by at least one processor to implement the steps of the interference prediction method as described in the first aspect, or to implement the steps of the interference prediction method as described in the second aspect.

[0037] In this embodiment, the terminal receives first auxiliary information from the network-side device; based on the first auxiliary information, interference prediction is performed. The terminal can select an interference prediction algorithm adapted to the cell based on the first auxiliary information to perform interference prediction, thereby improving the accuracy of interference prediction. Attached Figure Description

[0038] Figure 1 shows a block diagram of a wireless communication system that can be applied to an embodiment of this application;

[0039] Figure 2 is a schematic diagram illustrating the principle of interference prediction;

[0040] Figure 3 is a flowchart of interference prediction performed on the terminal side;

[0041] Figure 4 is a flowchart of a network-side device performing interference prediction.

[0042] Figure 5 is a flowchart of an interference prediction method provided in an embodiment of this application;

[0043] Figure 6 is a flowchart of an interference prediction method provided in an embodiment of this application;

[0044] Figure 7 is a signaling flowchart of an interference prediction method provided in an embodiment of this application;

[0045] Figure 8 is a signaling flowchart of an interference prediction method provided in an embodiment of this application;

[0046] Figure 9 is a schematic block diagram of an interference prediction device provided in an embodiment of this application;

[0047] Figure 10 is another schematic block diagram of the interference prediction device provided in the embodiment of this application;

[0048] Figure 11 is a schematic diagram of the structure of the communication device provided in an embodiment of this application;

[0049] Figure 12 is a schematic diagram of the hardware structure of a terminal implementing an embodiment of this application;

[0050] Figure 13 is a schematic diagram of the hardware structure of a network-side device that implements an embodiment of this application. Detailed Implementation

[0051] The technical solutions of the embodiments of this application will be clearly described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application are within the scope of protection of this application.

[0052] The terms "first," "second," etc., used in this application are used to distinguish similar objects and not to describe a specific order or sequence. It should be understood that such terms can be used interchangeably where appropriate so that embodiments of this application can be implemented in orders other than those illustrated or described herein, and the objects distinguished by "first" and "second" are generally of the same class, not limited in number; for example, the first object can be one or more. Furthermore, "or" in this application indicates at least one of the connected objects. For example, the scope of protection for "A or B" covers at least three scenarios: Scenario 1: including A but not B; Scenario 2: including B but not A; Scenario 3: including both A and B. In addition, the terms "A and / or B," "at least one of A and B," and "at least one of A or B" also cover at least the above three scenarios. The character " / " generally indicates that the preceding and following objects are in an "or" relationship.

[0053] The term "instruction" in this application can be either a direct instruction (or explicit instruction) or an indirect instruction (or implicit instruction). A direct instruction can be understood as the sender explicitly informing the receiver of specific information, the required operation, or the requested result in the instruction sent. An indirect instruction can be understood as the receiver determining the corresponding information based on the instruction sent by the sender, or making a judgment and determining the required operation or requested result based on the judgment result.

[0054] It is worth noting that the technologies described in this application are 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 this application are often used interchangeably, and the described technologies can be used with the systems and radio technologies mentioned above, as well as with other systems and radio technologies. The following description describes New Radio (NR) systems for illustrative purposes, and the term NR is used in most of the following description; however, these technologies can also be applied to systems other than NR systems, such as 6th generation (6G) radio systems. th Generation 6G communication system.

[0055] Figure 1 shows a block diagram of a wireless communication system applicable to an embodiment of this application. The wireless communication system includes a terminal 11 and a network-side device 12. The terminal 11 can also be referred to as User Equipment (UE), and can be a mobile phone, tablet computer, laptop computer, notebook computer, personal digital assistant (PDA), handheld computer, netbook, ultra-mobile personal computer (UMPC), mobile internet device (MID), augmented reality (AR), virtual reality (VR) device, robot, wearable device, flight vehicle, vehicle user equipment (VUE), shipboard equipment, pedestrian user equipment (PUE), smart home (home devices with wireless communication capabilities, such as refrigerators, televisions, washing machines, or furniture), game console, personal computer (PC), ATM, or self-service machine, etc. Wearable devices include: smartwatches, smart bracelets, smart earphones, smart glasses, smart jewelry (smart bracelets, smart chains, smart rings, smart necklaces, smart anklets, smart anklets, etc.), smart wristbands, smart clothing, etc. Among these, in-vehicle devices can also be referred to as in-vehicle terminals, in-vehicle controllers, in-vehicle modules, in-vehicle components, in-vehicle chips, or in-vehicle units, etc. It should be noted that the specific type of terminal 11 is not limited in the embodiments of this application.

[0056] Network-side equipment 12 may include access network equipment or core network equipment. Access network equipment may also be referred to as Radio Access Network (RAN) equipment, radio access network function, or radio access network unit. Access network equipment may include base stations, wireless local area network (WLAN) access points (APs), or wireless Fidelity (WiFi) nodes, etc. Among them, base stations can be referred to as Node B (NB), Evolved Node B (eNB), Next Generation Node B (gNB), New Radio Node B (NR Node B), Access Point, Relay Base Station (RBS), Serving Base Station (SBS), Base Transceiver Station (BTS), Radio Base Station, Radio Transceiver, Basic Service Set (BSS), Extended Service Set (ESS), Home Node B (HNB), Home Evolved Node B, Transmit / Receive Point (TRP), Non-Terrestrial Network (NTN) equipment (such as satellite or high altitude platform stations). The term "base station" can be any suitable term in the field, such as "station" or any other appropriate term in the relevant field, as long as the same technical effect is achieved. The term "base station" is not limited to any specific technical term. It should be noted that the embodiments of this application only use the base station in the NR system as an example for introduction, and do not limit the specific type of base station.

[0057] Core network equipment, also known as core network nodes, core network functions, or core network elements, includes, but is not limited to, at least one of the following: Mobility Management Entity (MME), Access and Mobility Management Function (AMF), Session Management Function (SMF), User Plane Function (UPF), Policy Control Function (PCF), Policy and Charging Rules Function (PCRF), Edge Application Server Discovery Function (EASDF), Unified Data Management (UDM), Unified Data Repository (UDR), Home Subscriber Server (HSS), Centralized network configuration (CNC), Network Repository Function (NRF), Network Exposure Function (NEF), Local NEF (or L-NEF), and Binding Support. Functions include BSF, Application Function (AF), Location Management Function (LMF), Gateway Mobile Location Centre (GMLC), Network Data Analytics Function (NWDAF), and Non-Terrestrial Network (NTN) equipment (such as satellite or high altitude platform station).It should be noted that the embodiments of this application only use the core network equipment in the NR system as an example for introduction, and do not limit the specific type of core network equipment. If the name of the core network equipment mentioned in the embodiments of this application changes in subsequent protocol versions (e.g., 6G), it is also within the scope of protection of this application.

[0058] Optionally, the core network equipment can be implemented by one or more functional modules in a single device, or by multiple devices working together; this application does not specifically limit this. It is understood that the aforementioned functional modules can be network elements in hardware devices, software functional modules running on dedicated hardware, or virtualized functional modules instantiated on a platform (e.g., a cloud platform).

[0059] Terminals are susceptible to interference from various sources, such as neighboring base stations, uplink and downlink communications from other terminals, and sidelink communications from other terminals. The interference experienced by a terminal can be referred to as interference power or interference-plus-noise (IpN), where IpN is the sum of the interference power and noise power measured by the terminal.

[0060] When a base station is unaware of the interference a terminal experiences on target communication resources, it may configure or schedule communication resources with relatively high interference intensity for the terminal. This may reduce the signal-to-interference-plus-noise ratio (SINR) and consequently impair communication performance, such as increasing the data transmission error rate and latency.

[0061] Interference at a terminal may change rapidly in the time, frequency, and spatial domains. Interference at a terminal is correlated in the time, frequency, and spatial domains. For example, changes in interference in the time domain may be related to interference in the frequency or spatial domains, and future interference may be related to past interference.

[0062] Based on these characteristics of interference, interference prediction can be performed, and the predicted interference information can be used for terminal scheduling. Figure 2 is a schematic diagram of the principle of interference prediction. As shown in Figure 2, the interference prediction module predicts interference based on historically measured interference information to obtain future interference information.

[0063] Knowing future interference information allows the network to make better scheduling decisions and coordinate interference between cells, thereby reducing future interference to terminals and improving link quality. For example, network equipment can avoid scheduling users who will experience strong interference in future communication resources. Furthermore, based on predicted interference information, the network can more accurately determine the modulation and coding scheme (MCS) to reduce the initial block error rate and transmission latency.

[0064] The terminal side knows the interference information on the scheduled future communication resources. By utilizing the correlation of interference in the time domain, frequency domain, or spatial domain, it can better eliminate interference during data demodulation and improve decoding accuracy.

[0065] In this embodiment, interference prediction can be performed on the terminal side or the network side. Figure 3 is a flowchart of interference prediction performed on the terminal side. As shown in Figure 3, the interference prediction process includes the following steps:

[0066] S101. The terminal sends interference prediction-related capability information to the network-side equipment.

[0067] The network-side device can be an access network device or a core network device. The interference prediction-related capability information sent by the terminal to the network-side device may include at least one of the following: the type of interference that the terminal can predict, the time information of the predicted interference, the time information of the historical interference required for prediction, or the prediction time interval.

[0068] The type of interference that the terminal can predict is, for example, interference power or IpN. The timing information of the predicted interference indicates how far in the future the terminal can predict interference. The timing information of the historical interference required for prediction indicates how long past interference information should be used for interference prediction. Interference prediction is usually not continuous; the prediction time interval indicates how often the terminal performs interference prediction.

[0069] S102. The network-side equipment sends interference measurement configuration information and interference reporting configuration information to the terminal.

[0070] After receiving the interference prediction capability information from the terminal, the network-side device determines the interference prediction configuration information based on the interference prediction capability information. The interference prediction configuration information includes interference measurement configuration information and interference reporting configuration information.

[0071] Interference measurement configuration information is used to configure interference measurement resources for the terminal. Interference measurement resources refer to the communication resources configured by the network-side equipment for the terminal to measure interference. The terminal measures interference through the interference measurement resources.

[0072] For example, interference measurement resources may include channel state information reference signal (CSI-RS), channel state information for interference measurement (CSI-IM), interference measurement resource (IMR), or DMRS.

[0073] A CSI-RS refers to a reference signal transmitted by the base station, which the terminal can use to estimate the channel and feed back channel state information to the base station. A CSI-IM refers to a set of resource elements (REs) reserved for interference measurement. An IMR is a time-frequency resource allocated by the network to the terminal for interference measurement.

[0074] Interference reporting configuration information is used to configure interference reporting related information for the terminal. Interference reporting related information may include the content of the reported interference information, the time of interference reporting, and the interference measurement resources on which the reported interference information is obtained.

[0075] S103. The terminal performs interference measurement based on the interference measurement configuration information to obtain interference measurement information.

[0076] The terminal measures interference based on the interference measurement resources configured by the network-side equipment, and obtains interference measurement information (i.e., interference measurement results). This interference measurement information may include a set of measured interference values, or a set of measured interference values ​​and evaluation indicators for those measured interference values.

[0077] A set of measurement interference values ​​includes one or more measurement interference values. When a set of measurement interference values ​​includes multiple measurement interference values, these multiple measurement interference values ​​can be measurement interference values ​​at different time points of the same interference measurement resource. Optionally, the same time point can also include multiple measurement interference values.

[0078] Optionally, the measured interference values ​​include, but are not limited to: interference power, SINR, interference level, carrier-to-interference ratio (C / I), etc., measured in a certain time domain, frequency domain, or spatial domain.

[0079] Interference level is an indicator describing the intensity of interference. In one example, the interference level can be divided into three levels: high, medium, and low, which can be indicated by 2 bits. In another example, the interference level can be divided into ten levels from 1 to 10, with higher values ​​indicating stronger interference. Each level can be associated with a range of interference power or SINR, depending on the device implementation or protocol.

[0080] Optionally, the evaluation metrics for measuring interference values ​​include at least one of the following: probability of measuring interference values, confidence level, accuracy, uncertainty, and uncertainty range.

[0081] The probability of measuring interference values ​​represents the probability that a terminal will measure a specific interference value on interference measurement resources. A higher value for the evaluation index of measuring interference values ​​indicates a higher probability of occurrence, greater confidence or credibility, higher accuracy, lower uncertainty, or a smaller range of uncertainty.

[0082] Optionally, the interference measurement information may be obtained based on a set of interference measurement resources, which may include: one or more CSI-RS, one or more CSI-IM, or one or more IMR.

[0083] S104. The terminal performs interference prediction based on interference measurement information.

[0084] The terminal uses an interference prediction algorithm to predict interference based on the interference measurement information, and obtains interference prediction information. The interference measurement information is historical interference information, and the interference prediction information is the predicted future interference information.

[0085] The interference prediction information may include a set of predicted interference values, or a set of predicted interference values ​​and an evaluation index for those predicted interference values.

[0086] Optionally, a set of predicted interference values ​​may include one or more predicted interference values. When a set of predicted interference values ​​includes multiple predicted interference values, these multiple predicted interference values ​​may be predicted interference values ​​at different time points of the same communication resource. Optionally, the same time point may also include multiple predicted interference values.

[0087] Optionally, the predicted interference values ​​include, but are not limited to: interference power, SINR, interference level, carrier-to-interference ratio (C / I), etc., predicted in a certain time domain, frequency domain, or spatial domain.

[0088] Optionally, the evaluation metrics for predicting interference values ​​include at least one of the following: probability of predicting interference values, confidence level, accuracy, uncertainty, and uncertainty range.

[0089] The probability of predicting interference values ​​represents the probability that a terminal will predict a specific interference value on communication resources. A higher value for the evaluation index of predicted interference values ​​indicates a higher probability of occurrence, greater confidence or credibility, higher accuracy, lower uncertainty, or a smaller range of uncertainty.

[0090] S105. The terminal sends interference prediction information to the network-side equipment.

[0091] The terminal reports interference prediction information based on the interference reporting configuration information configured by the network-side equipment. Optionally, the terminal carries this interference prediction information through a Channel State Feedback (CSF) report. This CSF report may include interference prediction information for specific time, frequency, or spatial resources.

[0092] Optionally, the terminal performs interference measurement on the first communication resource (i.e., interference measurement resource), and predicts the interference information of the terminal on the second communication resource based on the interference measurement information on the first communication resource. The first communication resource and the second communication resource may be the same, partially the same or different, and this application embodiment does not limit this.

[0093] The first and second communication resources here can be regarded as a collection of one or more time-domain resources, frequency-domain resources and spatial-domain resources, and may also be associated with at least one reference signal resource, at least one set of reference signal resources or at least one reference signal configuration.

[0094] S106. The network-side device sends scheduling information to the terminal.

[0095] After receiving interference prediction information obtained from the terminal, network-side equipment (such as the serving base station or neighboring base stations of the terminal) determines the terminal's scheduling information based on the interference prediction information. For example, the base station can avoid scheduling terminals that are predicted to experience strong interference on future communication resources. Furthermore, based on the interference prediction information, the base station can more accurately determine the MCS (Multi-Segment Control), thereby reducing the initial block error rate and transmission latency.

[0096] Figure 4 is a flowchart of interference prediction performed by network-side devices. As shown in Figure 4, the interference prediction process includes the following steps:

[0097] S201. The terminal sends interference prediction capability information to the network-side equipment.

[0098] S202. The network-side equipment sends interference measurement configuration information and interference reporting configuration information to the terminal.

[0099] S203. The terminal performs interference measurement based on the interference measurement configuration information to obtain interference measurement information.

[0100] The specific implementation of steps S201-S203 is the same as that of steps S101-S103 mentioned above, and will not be repeated here.

[0101] S204. The terminal sends interference measurement information to the network-side equipment.

[0102] The terminal reports interference measurement information according to the interference reporting configuration information configured on the network-side equipment. Optionally, the terminal carries this interference measurement information through a CSF report. This CSF report may include interference measurement information on specific time, frequency, or airspace resources.

[0103] S205. Network-side equipment performs interference prediction based on interference measurement information.

[0104] Based on the interference measurement information reported by the terminal, the network-side equipment uses an interference prediction algorithm to predict interference and obtain interference prediction information. This interference prediction information may include a set of predicted interference values, or a set of predicted interference values ​​and an evaluation index for those predicted interference values.

[0105] S206. The network-side device sends scheduling information to the terminal.

[0106] Network-side devices determine terminal scheduling information based on interference prediction information they obtain, in order to make better scheduling decisions.

[0107] In the interference prediction process shown in Figures 3 and 4, in order for network-side devices to consider the temporal, frequency, and spatial characteristics of interference experienced by the terminal during resource scheduling, the terminal needs to report interference-related information to the network side. This interference-related information includes the aforementioned interference measurement information or interference prediction information.

[0108] In this embodiment, the interference-related information reported by the terminal may be in the form of a distribution-based representation or a non-distribution-based representation. Specifically, for a distribution-based representation, the interference distribution reported by the terminal may be a probability density function or a probability mass function related to the time domain, frequency domain, or spatial domain.

[0109] A probability density function describes the probability of a continuous random variable within a certain range. A probability mass function describes the probability of a discrete random variable equaling certain values. For example, X is a discrete random variable, and its possible range of values ​​is: R X ={x1,x2,x3,x4,…}, the probability mass function of X is: P X (x k ) = P(X = x k ), k = 1, 2, 3, 4, ...

[0110] In some implementations, the interference distribution reported by the terminal takes the form of a probability quality function, which describes the interference value measured or predicted on a certain time domain, frequency domain, or spatial domain resource and its probability, i.e.: P X (IpN=x) k|t=t m f = f n ,s=s q )

[0111] Where k = 1, 2, 3, 4, ..., m = 1, 2, 3, 4, ..., n = 1, 2, 3, 4, ..., q = 1, 2, 3, 4, ...

[0112] x k This represents the k-th interference value, such as x1 = -30dBm, x2 = -31dBm, x3 = -32dBm, etc.

[0113] t m This represents the m-th time-domain resource, such as t1 = slot1, t2 = slot2, t3 = slot3, etc.

[0114] f n This represents the nth frequency domain resource, such as f1 = subband1, f2 = subband2, f3 = subband3, etc.

[0115] s q This represents the q-th spatial resource, such as s1 = beamindex1, s2 = beamindex2, s3 = beamindex3, etc.

[0116] P X (IpN=x) k |t=t m f = f n ,s=s q ) indicates that the terminal has time-domain resources t m Frequency domain resources f n and airspace resources q The measured or predicted interference value is x k The probability of.

[0117] It is understandable that the granularity of time-domain resources, frequency-domain resources, and spatial-domain resources is not limited to the slots, subbands, or beams mentioned above. They can also be other things. For example, time-domain resources can also be Orthogonal Frequency Division Multiplexing (OFDM) symbols, subframes, frames, etc., frequency-domain resources can also be physical resource blocks (PRBs) or resource blocks (RBs), and spatial-domain resources can also be physical cells, reference signal resources, ports, etc.

[0118] Optionally, in some implementations, the network-side device may be configured with the granularity of interference measurement or interference prediction: frequency domain granularity, time domain granularity, or spatial domain granularity.

[0119] Frequency domain granularity: Interference measurement or interference prediction is based on the full bandwidth or sub-band (or multiple sub-bands), etc. If an interference value can be associated with the full bandwidth or (one or more) sub-bands, then this interference value describes the interference intensity of the full bandwidth or (one or more) sub-bands.

[0120] Temporal granularity: Interference measurement or interference prediction is symbol-level interference, slot-level interference, or multiple slot-level interference, etc. For example, if an interference value is slot-level interference, then this interference value describes the interference intensity on one slot.

[0121] Spatial granularity: Network-side devices may configure multiple reference signal resources or beams for interference measurement or interference prediction. If an interference value is associated with a specific beam or reference signal resource, then the interference value describes the interference intensity on that beam or reference signal resource.

[0122] Optionally, in some implementations, network-side devices or terminals use artificial intelligence (AI) models to predict interference. The AI ​​model used for interference prediction is also called an AI interference prediction model.

[0123] AI models can be implemented in various ways, including but not limited to: neural networks, decision trees, support vector machines, Bayesian classifiers, etc. AI models can also be represented as machine learning (ML) models.

[0124] In the embodiments of this application, the AI ​​model may also be referred to as an AI unit, AI structure, etc., or the AI ​​model may refer to a processing unit that can implement specific algorithms, formulas, processing flows, capabilities, etc. related to AI, or the AI ​​model may be a processing method, algorithm, function, module or unit for a specific dataset, or the AI ​​model may be a processing method, algorithm, function, module or unit running on AI-related hardware such as a Graphics Processing Unit (GPU), Neural Network Processing Unit (NPU), Tensor Processing Unit (TPU), Application Specific Integrated Circuit (ASIC), etc. This application does not make specific limitations in this regard.

[0125] The identifier (ID) of the AI ​​model in the embodiments of this application may be a model identifier, an AI structure identifier, an AI algorithm identifier, or an identifier of a specific dataset associated with the AI ​​model, or an identifier of a specific scenario, environment, channel characteristics, or device related to AI, or an identifier of a function, characteristic, capability, or module related to AI. This application does not make any specific limitations on this.

[0126] In this embodiment, the AI ​​model's ID (or index) can be represented in various ways, such as the model's functional ID or model ID, physical ID, logical ID, global ID, or local ID. It is understood that an AI model may have multiple functions, and correspondingly, it can have multiple functional IDs. The global ID can be a unique, global ID defined by the AI ​​model across all networks or models provided by all model providers, uniquely identifying a model. The local ID is used to identify a model within a specific network or model provided by a specific model provider.

[0127] The interference prediction method provided in this application will be described in detail below with reference to the accompanying drawings, through some embodiments and application scenarios.

[0128] Figure 5 is a flowchart of an interference prediction method provided in an embodiment of this application. The method in this embodiment is executed by a terminal. As shown in Figure 5, the method provided in this embodiment includes the following steps.

[0129] S301, The terminal receives the first auxiliary information from the network-side device.

[0130] The terminal receives first auxiliary information sent by the network-side device. The first auxiliary information is used to assist the terminal in interference prediction. The first auxiliary information includes information about at least one cell, network environment information, or communication environment information.

[0131] For example, the first auxiliary information includes at least one of the following:

[0132] (1) At least one cell’s first scheduling algorithm information or scheduling algorithm update information.

[0133] Cell scheduling algorithms are used to allocate cell communication resources among different terminals. Commonly used scheduling algorithms include proportional fair scheduling and round-robin scheduling.

[0134] (2) At least one cell’s first beam information or updated beam information.

[0135] The beam information of a cell can include the number of beams, beamwidth, beam center angle, etc.

[0136] (3) At least one cell’s first frequency domain scheduling granularity information or frequency domain scheduling granularity information update information.

[0137] The frequency domain scheduling granularity of a cell can include broadband scheduling, subband scheduling, etc.

[0138] (4) At least one cell’s first scheduling type or scheduling type update information.

[0139] The scheduling type of a cell can include semi-persistent scheduling, dynamic scheduling, or static scheduling.

[0140] (5) At least one cell’s first network load information or network load information update information.

[0141] The network load information of a community is used to describe the network's operating status. Network load is closely related to network performance; for example, network load is divided into three levels: high, medium, and low. Typically, when the network load is high, the utilization rate of time-frequency resources may be higher.

[0142] (6) At least one cell’s first slot format information or slot format information update information.

[0143] The slot format refers to the configuration method of slots in the network. It defines the transmission direction of each slot within a subframe, including which slots are uplink slots, which slots are downlink slots, and which slots are flexible slots. Uplink slots are used for uplink transmission, downlink slots are used for downlink transmission, and flexible slots can be used for both uplink and downlink transmission.

[0144] (7) At least one cell’s first transmit power information or transmit power information update information.

[0145] The cell's transmit power, also known as the cell's maximum transmit power, refers to the maximum sum of the downlink transmit power of all channels that can be transmitted simultaneously within the cell. Configuring the cell's transmit power is crucial for ensuring communication quality, improving spectrum utilization, and optimizing network performance. In NR systems, the cell's transmit power can be flexibly configured.

[0146] (8) At least one cell’s first service type information or service type information update information.

[0147] The service types in a cell can include periodic services and non-periodic services. Periodic services refer to service data packets arriving at a certain period, such as one data packet arriving every 10 milliseconds. The size of the data packets can be fixed or variable.

[0148] (9) At least one cell’s first ID or ID update information.

[0149] At least one cell (i.e., one or more) in the first auxiliary information may include the terminal's serving cell and / or neighboring cells (one or more neighboring cells).

[0150] The first auxiliary information is information configured by the network-side device for the terminal to assist in interference prediction in the current or future period. This first auxiliary information may be the same as or different from the first auxiliary information used by the terminal in the previous period. If the first auxiliary information is different from the first auxiliary information used by the terminal in the previous period, that is, at least one piece of information in the first auxiliary information has changed.

[0151] When the first auxiliary information differs from the first auxiliary information used by the terminal in a previous period, the network-side device can indicate the changed first auxiliary information to the terminal in the following two ways:

[0152] Method 1: The first auxiliary information includes the values ​​of each piece of information after the changes.

[0153] Method 2: The first auxiliary information includes update information for each piece of information. This update information is used to indicate whether the information should be updated. This update information can also be a change indication information, which is used to indicate whether the information has changed. The information that has changed is the information that needs to be updated.

[0154] Of the nine types of information mentioned above, some or all may have changed. For Method 1, the first auxiliary information may include the values ​​of all information, or it may only include the values ​​of the changed information. Similarly, for Method 2, the first auxiliary information may include updated information for all information, or it may only include updated information for the changed information.

[0155] In Method 1, after receiving the first auxiliary information, the terminal compares the previous values ​​of each piece of information with the values ​​included in the first auxiliary information. For a given piece of information, if the previous value of that information is the same as the value included in the first auxiliary information, the terminal determines that the information has not changed; if the previous value of that information is different from the value included in the first auxiliary information, the terminal determines that the information has changed. Taking frequency domain scheduling granularity information as an example, if the previous value of the frequency domain scheduling granularity information is broadband scheduling, and the value included in the first auxiliary information is sub-band scheduling, then the terminal determines that the frequency domain scheduling granularity information has changed.

[0156] In Method 2, the terminal determines whether the information has changed based on the update information of each piece of information. For example, the update information is indicated by a bit. When the value of the update information is 1, it means that the information has changed, and when the value of the update information is 0, it means that the information has not changed.

[0157] In one implementation, the update information may only be used to indicate whether information should be updated. When the update information indicates that information should be updated, it means that the information has changed; when the update information indicates that information should not be updated, it means that the information has not changed. In another implementation, the update information may include update indication information and the updated value. The update indication information is used to indicate whether information should be updated. If information needs to be updated, the update information may also include the updated value of that information.

[0158] Optionally, in this embodiment, the terminal uses an AI interference prediction model to predict interference. Accordingly, the first auxiliary information is associated with at least one AI interference prediction model. The first auxiliary information is information configured by the network-side device for the terminal for the current or future period. The first auxiliary information associated with the AI ​​interference prediction model, or the first auxiliary information used during model training or model data collection, may be the same or different.

[0159] The first auxiliary information is different from the first auxiliary information associated with the AI ​​interference prediction model or used during model training or model data collection. That is, at least one of the first auxiliary information has changed. The network-side device can indicate the changed first auxiliary information to the terminal in the above two ways, which will not be repeated here.

[0160] In some implementations, before receiving the first auxiliary information from the network-side device, the terminal sends a first request message to the network-side device, which is used to request the first auxiliary information from the network-side device.

[0161] In one example, the first request message includes the types of various first auxiliary information requested from the network-side device, that is, the terminal tells the network-side device which first auxiliary information is needed, and the network-side device returns the values ​​of various first auxiliary information to the terminal.

[0162] In another example, the first request message includes first configuration information, which is used to indicate the interference prediction function supported by the terminal, that is, the terminal tells the network-side device the values ​​of various first auxiliary information it already has.

[0163] In some implementations, the terminal sends the first configuration information to the network-side device before receiving the first auxiliary information from the network-side device.

[0164] In some implementations, the network-side device decides to send the first auxiliary information to the terminal based on its own implementation. For example, the network-side device sends the first auxiliary information to the terminal periodically, or the network-side device sends the first auxiliary information to the terminal when it determines that the first auxiliary information has changed.

[0165] For example, the first configuration information includes at least one of the following:

[0166] (1) At least one timestamp information is provided to indicate the time when the AI ​​interference prediction model was acquired or the time when the dataset was acquired.

[0167] (2) At least one time period information, used to indicate the acquisition time of the AI ​​interference prediction model or the acquisition time of the dataset.

[0168] Optionally, the first configuration information is associated with at least one AI interference prediction model of the terminal, which is used to predict interference. When the first configuration information is associated with at least one AI interference prediction model of the terminal, the terminal indicates the acquisition time of the AI ​​interference prediction model or the acquisition time of the dataset by carrying the timestamp information or time period information.

[0169] The acquisition time of the AI ​​interference prediction model can be either the training time or the update time of the AI ​​interference prediction model. The dataset refers to the dataset used during the training or update of the AI ​​interference prediction model, and the acquisition time of the dataset refers to the actual time when the data in the dataset was generated. Based on the acquisition time of the AI ​​interference prediction model or the acquisition time of the dataset, the network-side device can obtain the first auxiliary information associated with the AI ​​interference prediction model, or the first auxiliary information expected by the terminal. For example, if the network-side device stores network configuration log information at that time, the first auxiliary information at that time can be obtained by consulting the log information at that time.

[0170] The first auxiliary information used by the AI ​​interference prediction model during training and inference may be the same or different. Inconsistency in the first auxiliary information used by the AI ​​interference prediction model during training and inference may affect the inference performance of the AI ​​interference prediction model. In this embodiment, the network-side device configures the first auxiliary information for the terminal as consistent as possible with the first auxiliary information used during training based on the first configuration information reported by the terminal, so as to improve the accuracy of the prediction results of the AI ​​interference prediction model.

[0171] In one scenario, the network-side device can configure the first auxiliary information adapted to the AI ​​interference prediction model for the terminal based on the acquisition time of the AI ​​interference prediction model or the acquisition time of the dataset reported by the terminal.

[0172] In another scenario, the network-side device determines whether the terminal's AI interference prediction model is available or whether it is activated based on the acquisition time of the AI ​​interference prediction model or the acquisition time of the dataset reported by the terminal.

[0173] (3) At least one cell’s second scheduling algorithm information.

[0174] (4) Second beam information of at least one cell.

[0175] (5) Second frequency domain scheduling granularity information of at least one cell.

[0176] (6) At least one cell’s second scheduling type.

[0177] (7) Second network load information of at least one cell.

[0178] (8) Second time slot format information of at least one cell.

[0179] (9) Second transmission power information of at least one cell.

[0180] (10) At least one second service type in a cell.

[0181] (11) At least one second identifier of a cell.

[0182] After receiving the first configuration information, the network-side device determines the first auxiliary information based on the first configuration information. When the first configuration information is associated with at least one AI interference prediction model of the terminal, the first auxiliary information determined by the network-side device is also associated with that at least one AI interference prediction model.

[0183] For any piece of information in the first auxiliary information, the second information in the first configuration information may be the same as or different from the first information in the first auxiliary information. The second information is the information used by the terminal for interference prediction before the current moment, while the first information is the information newly determined by the network-side device for the terminal for future interference prediction. Taking scheduling algorithm information as an example, the first scheduling algorithm information and the second scheduling algorithm information may be the same or different. Other information is the same, and so on, without further listing.

[0184] Optionally, the first configuration information may also include the reference signal type or first indication information supported by the terminal when performing interference measurement or interference prediction. The first indication information is used to indicate whether the terminal supports the demodulation reference signal (DMRS) type when performing interference measurement or interference prediction.

[0185] The network-side device determines the target reference signal type used by the terminal to perform interference measurement or interference prediction based on the reference signal type or first indication information supported by the terminal when performing interference measurement or interference prediction. The terminal can measure interference information based on the target reference signal type and predict future interference information based on the measured interference information.

[0186] Optionally, the reference signal types supported by the terminal when performing interference measurement or interference prediction include at least one of the following: CSI-RS for channel measurement, CS-RS for interference measurement, CSI-IM and DMRS; or DMRS and non-DMRS; or CSI-RS and DMRS.

[0187] S302, The terminal performs interference prediction based on the first auxiliary information.

[0188] Optionally, the terminal uses an AI interference prediction model for interference prediction. Of course, the terminal can also use other interference prediction algorithms. The terminal determines the interference prediction algorithm to use based on the first auxiliary information. It is understood that different first auxiliary information corresponds to different network environments in the cell, and the interference prediction algorithm used should be adapted to the cell's network environment. Therefore, the interference prediction algorithm can be determined based on the first auxiliary information. Different first auxiliary information may correspond to different interference prediction algorithms, and using an adapted interference prediction algorithm will yield more accurate interference prediction information.

[0189] When a terminal uses an AI interference prediction model for interference prediction, in some implementations, the terminal determines the AI ​​interference prediction model to be used based on first auxiliary information, and then uses the determined AI interference prediction model for interference prediction. When the first auxiliary information is associated with multiple AI interference prediction models, the terminal can select a target AI interference prediction model from the multiple AI interference prediction models based on the first auxiliary information for interference prediction.

[0190] For example, the terminal compares the first auxiliary information sent by the network-side device with its own local first configuration information. When some information in the first auxiliary information is updated or changed, the terminal determines that the AI ​​interference prediction model used previously or currently is no longer applicable to the future network environment. The terminal can then reselect an appropriate AI interference prediction model for interference prediction based on the first auxiliary information sent by the network-side device.

[0191] In some implementations, before the terminal performs interference prediction based on the first auxiliary information, the method further includes: the terminal receiving second indication information from a network-side device regarding the first auxiliary information. This second indication information is used to indicate information related to the first auxiliary information, and includes at least one of the following:

[0192] Time indication information is used to indicate the effective time of the first auxiliary information;

[0193] Frequency indication information, used to indicate the carrier frequency associated with the first auxiliary information;

[0194] Bandwidth indication information, used to indicate the bandwidth associated with the first auxiliary information;

[0195] At least one Bandwidth Part (BWP) ID, wherein the frequency range of the BWP corresponding to the at least one BWP identifier is the effective frequency range of the first auxiliary information.

[0196] Interference often changes rapidly, and network-side devices often dynamically adjust scheduling strategies based on network conditions. Therefore, network-side devices need to indicate the validity period of the first auxiliary information. Within the validity period (or validity time range) of the first auxiliary information indicated by the network-side device, the terminal can assume that the first auxiliary information is valid or that the first auxiliary information remains unchanged.

[0197] Optionally, the effective time range of the first auxiliary information can be indicated in the following ways:

[0198] Method 1: The network-side device indicates the start and end times of the valid time range.

[0199] Method 2: The network-side device indicates the start time of the valid time range and a time range (i.e., a period of time). The terminal can obtain the end time of the valid time range based on the start time and the time range.

[0200] Method 3: The network-side device indicates the end time of the valid time range, and the method for determining the start time of the valid time range is agreed upon by the protocol, such as agreeing that the start time is the time when the terminal receives the first auxiliary information.

[0201] Method four: The network-side device specifies a time range. The start time of the valid time range is determined by a protocol, such as specifying the start time as the time the terminal receives the first auxiliary information. The terminal can then determine the end time of the valid time range based on the specified start time and the time range itself.

[0202] The frequency indication information is used to indicate on which carrier frequencies the first auxiliary information is valid. The frequency indication information may include the frequency information of each carrier associated with the first auxiliary information. The frequency information may be the frequency point of the carrier or the frequency range of the carrier.

[0203] The bandwidth indication information is used to indicate the bandwidth on which the first auxiliary information is valid. The bandwidth indication information may include the frequency range of the bandwidth associated with the first auxiliary information, for example, the bandwidth associated with the first auxiliary information is 15 MHz, 30 MHz, or 60 MHz.

[0204] The at least one BWP ID is used to indicate the valid frequency range of the first auxiliary information, which can also be understood as indicating that the first auxiliary information is valid on the specific BWP corresponding to the BPW identifier. Each BWP ID corresponds to one BWP, and each BWP corresponds to one frequency range.

[0205] In some implementations, the terminal receives a third or fourth indication from the network-side device. The third indication is used to indicate whether the AI ​​interference prediction model is activated or deactivated, and the fourth indication is used to indicate whether the AI ​​interference prediction model is available.

[0206] In some implementations, the network-side device can determine whether to activate the AI ​​interference prediction model or whether the AI ​​interference prediction model is available based on the first configuration information, and send a third or fourth indication information to the terminal. The first configuration information is used to indicate the interference prediction function supported by the terminal.

[0207] In some implementations, the third indication information is indicated by 1 bit, where bit 1 indicates activation of the AI ​​interference prediction model and bit 0 indicates deactivation of the AI ​​interference prediction model; or, bit 1 indicates switching the state of the AI ​​interference prediction model, switching to deactivation if the original state of the AI ​​interference prediction model was activation, and switching to activation if the original state of the AI ​​interference prediction model was deactivation, and bit 0 indicates not switching the state of the AI ​​interference prediction model.

[0208] In some implementations, the fourth indication information is indicated by 1 bit, where bit 1 indicates that the AI ​​interference prediction model is available and bit 0 indicates that the AI ​​interference prediction model is unavailable; or, bit 1 indicates switching the state of the AI ​​interference prediction model, switching to the unavailable state if the original state of the AI ​​interference prediction model was available, and switching to the available state if the original state of the AI ​​interference prediction model was unavailable, and bit 0 indicates not switching the state of the AI ​​interference prediction model.

[0209] In some implementations, the terminal receives a fifth indication information from the network-side device, which is used to indicate the effective time of the AI ​​interference prediction model.

[0210] Within the effective time (or effective time range) of the AI ​​interference prediction model indicated by the network-side device, the terminal can assume that the AI ​​interference prediction model is effective, activatable, or available.

[0211] In some implementations, the network-side device indicates the effective time range of an AI interference prediction model. The indication method for the effective time range of the AI ​​interference prediction model can be any of the indication methods for the effective time range of the first auxiliary information mentioned above, which will not be repeated here.

[0212] In some implementations, the network-side device instructs the terminal to use a fifth instruction message to set a timer, which then deactivates the AI ​​interference prediction model after the timer expires.

[0213] In some implementations, the terminal receives at least one of the following information from the network-side device: interference measurement configuration information or interference reporting configuration information. Based on the interference measurement configuration information, the terminal performs interference measurement using the corresponding interference measurement resources to obtain interference measurement information. Based on this interference measurement information and the AI ​​interference prediction model, it obtains interference prediction information and sends the interference prediction information to the network-side device according to the interference reporting configuration information. In this implementation, the terminal performs interference prediction. The AI ​​interference prediction model is determined based on the first auxiliary information. The interference measurement configuration information, interference reporting configuration information, interference measurement process, and interference reporting content refer to the relevant content of the interference prediction process shown in Figures 2 and 3 above, and will not be repeated here.

[0214] The network-side device determines the terminal's scheduling information based on the interference prediction information reported by the terminal. The terminal receives the scheduling information sent by the network-side device. The scheduling information includes at least one of the following: time-domain resources of the Physical Downlink Shared Channel (PDSCH), frequency-domain resources of the PDSCH, or modulation and coding scheme (MCS).

[0215] Modulation Coding Scheme (MCS) is a key parameter in wireless communication, defining the modulation and coding scheme for data transmission. The choice of MCS directly affects data transmission rate, reliability, and spectral efficiency. Network-side equipment selects a matching MCS based on interference prediction information from the terminal. For example, when the terminal's interference prediction information indicates severe future interference, the network-side equipment can choose a low-order modulation scheme and higher coding redundancy (i.e., a lower MCS) to ensure data transmission reliability. Conversely, when the terminal's interference prediction information indicates less severe future interference (i.e., favorable future channel conditions), the network-side equipment can choose a high-order modulation scheme and lower coding redundancy (i.e., a higher MCS) to improve data transmission rate.

[0216] In some implementations, the terminal receives at least one of the following information from the network-side device: interference measurement configuration information or interference reporting configuration information. Based on the interference measurement configuration information, the terminal performs interference measurement using the corresponding interference measurement resources to obtain interference measurement information, and then sends this interference measurement information to the network-side device according to the interference reporting configuration information. In this implementation, the network-side device performs interference prediction based on the interference measurement information reported by the terminal and determines scheduling information based on the interference prediction information.

[0217] In this embodiment, the terminal receives first auxiliary information from the network-side device and performs interference prediction based on the first auxiliary information. The accuracy of interference prediction is improved by the terminal performing interference prediction based on the first auxiliary information, and the network-side device can make better scheduling decisions based on the accurate interference prediction information.

[0218] Figure 6 is a flowchart of an interference prediction method provided in an embodiment of this application. The method in this embodiment is executed by a network-side device. As shown in Figure 6, the method provided in this embodiment includes the following steps.

[0219] S401. The network-side device sends first auxiliary information to the terminal. The first auxiliary information is used by the terminal to predict interference.

[0220] The first auxiliary information is used to assist the terminal in interference prediction. The first auxiliary information includes information about at least one cell, network environment information, or communication environment information. The at least one cell includes the terminal's serving cell and / or neighboring cells.

[0221] For example, the first auxiliary information includes at least one of the following:

[0222] (1) At least one cell's first scheduling algorithm information or scheduling algorithm update information;

[0223] (2) First beam information or updated beam information of at least one cell;

[0224] (3) At least one cell's first frequency domain scheduling granularity information or frequency domain scheduling granularity information update information;

[0225] (4) At least one cell’s first scheduling type or scheduling type update information;

[0226] (5) At least one cell's first network load information or updated network load information;

[0227] (6) At least one cell's first time slot format information or time slot format information update information;

[0228] (7) At least one cell’s first transmit power information or transmit power information update information;

[0229] (8) At least one cell's first service type information or updated service type information;

[0230] (9) At least one cell’s first identifier or identifier update information.

[0231] The first auxiliary information is the auxiliary information configured by the network-side device for the terminal to assist the terminal in interference prediction in the current or future period of time. The first auxiliary information may be the same as or different from the first auxiliary information used by the terminal in the previous period of time.

[0232] When the first auxiliary information differs from the first auxiliary information used by the terminal in a previous period, the network-side device can indicate the changed first auxiliary information to the terminal in the following two ways:

[0233] Method 1: The first auxiliary information includes the values ​​of each piece of information after the changes.

[0234] Method 2: The first auxiliary information includes update information for each piece of information, which is used to indicate whether the information should be updated.

[0235] Optionally, in this embodiment, the terminal uses an AI interference prediction model to predict interference. Accordingly, the first auxiliary information is associated with at least one AI interference prediction model. The first auxiliary information is auxiliary information configured by the network-side device for the terminal to use for interference prediction in the current or future period. The first auxiliary information associated with the AI ​​interference prediction model, or the first auxiliary information used during model training or model data collection, may be the same or different.

[0236] The first auxiliary information is different from the first auxiliary information associated with the AI ​​interference prediction model or used during model training or model data collection. That is, at least one of the first auxiliary information has changed. The network-side device can indicate the changed first auxiliary information to the terminal in the above two ways, which will not be repeated here.

[0237] In some implementations, before the network-side device sends the first auxiliary information to the terminal, the network-side device receives a first request message sent by the terminal, which is used to request the first auxiliary information.

[0238] In one example, the first request message includes the type of first auxiliary information requested from the network-side device, that is, the terminal tells the network-side device what first auxiliary information is needed, and the network-side device returns the values ​​of various first auxiliary information to the terminal.

[0239] In another example, the first request message includes first configuration information, which is used to indicate the interference prediction function supported by the terminal, that is, the terminal tells the network-side device the values ​​of various first auxiliary information it already has.

[0240] In some implementations, before the network-side device sends the first auxiliary information to the terminal, the network-side device receives the first configuration information sent by the terminal. The first configuration information is used to indicate the interference prediction function supported by the terminal, and the network-side device determines the first auxiliary information based on the first configuration information.

[0241] In some implementations, the network-side device decides to send the first auxiliary information to the terminal based on its own implementation. For example, the network-side device sends the first auxiliary information to the terminal periodically, or the network-side device sends the first auxiliary information to the terminal when it determines that the first auxiliary information has changed.

[0242] For example, the first configuration information includes at least one of the following:

[0243] (1) At least one timestamp information is provided to indicate the time when the AI ​​interference prediction model was acquired or the time when the dataset was acquired.

[0244] (2) At least one time period information, used to indicate the acquisition time of the AI ​​interference prediction model or the acquisition time of the dataset.

[0245] (3) At least one cell’s second scheduling algorithm information.

[0246] (4) Second beam information of at least one cell.

[0247] (5) Second frequency domain scheduling granularity information of at least one cell.

[0248] (6) At least one cell’s second scheduling type.

[0249] (7) Second network load information of at least one cell.

[0250] (8) Second time slot format information of at least one cell.

[0251] (9) Second transmission power information of at least one cell.

[0252] (10) At least one second service type in a cell.

[0253] (11) At least one second identifier of a cell.

[0254] The first auxiliary information used by the AI ​​interference prediction model during training and inference may be the same or different. Inconsistency in the first auxiliary information used during training and inference may affect the inference performance of the AI ​​interference prediction model. In this embodiment, the network-side device can obtain the first auxiliary information associated with the AI ​​interference prediction model, or the first auxiliary information expected by the terminal, based on the acquisition time of the AI ​​interference prediction model or the acquisition time of the dataset reported by the terminal. Based on the acquisition time of the AI ​​interference prediction model or the acquisition time of the dataset, the network-side device can configure the first auxiliary information adapted to the AI ​​interference prediction model for the terminal, thereby improving the accuracy of the prediction results of the AI ​​interference prediction model.

[0255] In some implementations, the first configuration information is associated with at least one AI interference prediction model supported by the terminal device. The AI ​​interference prediction model is used to perform interference prediction. Correspondingly, the first auxiliary information is associated with at least one AI interference prediction model supported by the terminal device.

[0256] In some implementations, the first configuration information also includes the reference signal type or first indication information supported by the terminal when performing interference measurement or interference prediction. The first indication information is used to indicate whether the terminal supports the DMRS type when performing interference measurement or interference prediction.

[0257] Optionally, the reference signal types supported by the terminal when performing interference measurement or interference prediction include at least one of the following: CSI-RS for channel measurement, CS-RS for interference measurement, CSI-IM and DMRS; or DMRS and non-DMRS; or CSI-RS and DMRS.

[0258] In some implementations, the network-side device determines the interference measurement resources for the terminal based on the reference signal type or first indication information supported by the terminal when performing interference prediction. That is, it determines the target reference signal type used by the interference measurement resources. The network-side device sends the interference measurement resources to the terminal, and the terminal can measure the interference information based on the interference measurement resources corresponding to the target reference signal type.

[0259] Optionally, in some implementations, when the reference signal types supported by the terminal during interference measurement or interference prediction include the DMRS type, or when the first indication information indicates that the terminal supports the DMRS type during measurement or interference prediction, the network-side device prioritizes configuring DMRS resources for the terminal as interference measurement resources. Interference measurement based on the CSI-RI type incurs higher overhead, while interference measurement based on the DMRS type incurs lower overhead. The network-side device determines whether it is necessary to configure CSI-RS for the terminal's interference prediction based on the reference signal types supported by the terminal during interference measurement or interference prediction, or the first indication information. If configuring CSI-RS is not necessary, DMRS can be prioritized for the terminal's interference prediction to save interference measurement overhead.

[0260] In some implementations, the network-side device further sends second indication information of the first auxiliary information to the terminal. This second indication information is used to indicate information related to the first auxiliary information, and includes at least one of the following:

[0261] Time indication information is used to indicate the effective time of the first auxiliary information;

[0262] Frequency indication information, used to indicate the carrier frequency associated with the first auxiliary information;

[0263] Bandwidth indication information, used to indicate the bandwidth associated with the first auxiliary information;

[0264] At least one BWP ID, wherein the frequency range of the BWP corresponding to the at least one BWP ID is the effective frequency range of the first auxiliary information.

[0265] In some implementations, the network-side device sends a third or fourth indication to the terminal. The third indication indicates whether the AI ​​interference prediction model is activated or deactivated, and the fourth indication indicates whether the AI ​​interference prediction model is available. The terminal activates or deactivates the AI ​​interference prediction model based on the third indication. After activation, the terminal can use the AI ​​interference prediction model to predict interference. Alternatively, the terminal determines whether the AI ​​interference prediction model is available or unavailable based on the fourth indication. If the AI ​​interference prediction model is available, the terminal can use it to predict interference.

[0266] In some implementations, the network-side device receives first configuration information sent by the terminal, and determines whether to activate or deactivate the AI ​​interference prediction model, or whether the AI ​​interference prediction model is available or unavailable, based on the first configuration information. The first configuration information is used to indicate the interference prediction functions supported by the terminal.

[0267] For example, if the first auxiliary information used by the AI ​​interference prediction model at the time of acquisition of the AI ​​interference prediction model or the time of acquisition of the dataset is different from the first auxiliary information at the current time or a future period, it indicates that the network environment has changed and the AI ​​interference prediction model may no longer be applicable. In this case, the network-side device can choose to deactivate the AI ​​interference prediction model or determine that the AI ​​interference prediction model is unavailable.

[0268] For example, if the network load information carried in the first configuration information is different from the network load information at the current time or in the future, then the AI ​​interference prediction model may no longer be applicable. The network-side device can choose to deactivate the AI ​​interference prediction model or determine that the AI ​​interference prediction model is unavailable.

[0269] In some implementations, the network-side device sends a fifth indication message to the terminal, which indicates the effective time of the AI ​​interference prediction model, which is used to perform interference prediction.

[0270] The description and instruction method of the first to fifth instruction information mentioned above refer to the relevant description of the aforementioned Embodiment 1, and the same content will not be repeated.

[0271] In some implementations, the network-side device sends at least one of the following information to the terminal: interference measurement configuration information or interference reporting configuration information; the network-side device receives interference prediction information from the terminal, which is sent by the terminal based on the interference reporting configuration information, predicted by the terminal based on the interference measurement information, or measured by the terminal based on the interference measurement configuration information. The network-side device determines scheduling information for the terminal based on the interference prediction information and sends the scheduling information to the terminal. In this implementation, the terminal performs the interference prediction.

[0272] In some implementations, the network-side device sends at least one of the following information to the terminal: interference measurement configuration information or interference reporting configuration information; the network-side device receives interference measurement information from the terminal, which is measured by the terminal according to the interference measurement configuration information; the network-side device performs interference prediction based on the interference measurement information, determines scheduling information for the terminal based on the interference prediction information, and sends the scheduling information to the terminal. In this implementation, the network-side device performs interference prediction.

[0273] Whether interference prediction is performed by the terminal or the network-side equipment, the network-side equipment determines the scheduling information for the terminal based on the interference prediction information. This scheduling information includes at least one of the following: time-domain resources of PDSCH, frequency-domain resources of PDSCH, or MCS.

[0274] In this embodiment, the network-side device sends first auxiliary information to the terminal. This first auxiliary information is used by the terminal to perform interference prediction. The terminal performs interference prediction based on the first auxiliary information, which improves the accuracy of interference prediction. The network-side device can make better scheduling decisions based on the accurate interference prediction information obtained by the terminal.

[0275] It should be noted that the embodiments of the network-side device correspond to the embodiments of the terminal-side device. The information sent by the terminal is received by the network-side device, and the information sent by the network side is received by the terminal. Therefore, the limitations of its information are consistent with those of the terminal side. For features that are repeated on the terminal side, they will not be described again on the network device side.

[0276] Based on the above embodiments, this application also provides an interference prediction method. This embodiment describes the signaling interaction between a terminal and a network-side device during communication. In this embodiment, the terminal performs interference measurement and interference prediction. Figure 7 is a signaling flowchart of an interference prediction method provided by this application. As shown in Figure 7, the method provided by this embodiment includes the following steps.

[0277] S501: The terminal sends interference prediction-related capability information to the network-side equipment.

[0278] S502, The terminal sends a first request message to the network-side device.

[0279] The first request message is used to request first auxiliary information from the network-side device. In one example, the first request message includes the types of various first auxiliary information that need to be returned; in another example, the first request message includes first configuration information, which is used to indicate the interference prediction function supported by the terminal.

[0280] S503, The network-side device sends the first auxiliary information to the terminal.

[0281] The network-side device determines the first auxiliary information based on the first request message. When the first request message includes the first configuration information, the network-side device generates the first auxiliary information based on whether the information in the first configuration information has changed.

[0282] S504. The network-side equipment sends interference measurement configuration information and interference reporting configuration information to the terminal.

[0283] S505: The terminal performs interference measurement based on the interference measurement configuration information to obtain interference measurement information.

[0284] It should be noted that steps S502 and S503 are not executed in any particular order with steps S504 and S505. Steps S502 and S503 can be executed before steps S504 and S505, after steps S504 and S505, or in parallel.

[0285] In some implementations, before steps S504 and S505, the network-side device can determine the interference measurement configuration information and / or interference reporting configuration information of the terminal based on the first configuration information of the interference prediction function supported by the terminal. For example, when the first configuration information also includes the reference signal type or first indication information supported by the terminal when performing interference measurement or interference prediction, the network-side device can determine the interference measurement resources based on the reference signal type or first indication information supported by the terminal when performing interference measurement or interference prediction.

[0286] S506. The terminal performs interference prediction based on the interference measurement information and the first auxiliary information to obtain interference prediction information.

[0287] The terminal determines the appropriate interference prediction algorithm based on the first auxiliary information, and performs interference prediction using the interference prediction algorithm and interference measurement information. Optionally, the terminal can use an AI interference prediction model to perform interference prediction. Accordingly, the terminal can determine the appropriate AI interference prediction model based on the first auxiliary information, and perform interference prediction based on the determined AI interference prediction model and interference measurement information. The interference measurement information is the input of the AI ​​interference prediction model, and the output of the AI ​​interference prediction model is the interference prediction information.

[0288] S507: The terminal sends interference prediction information to the network-side equipment.

[0289] S508: The network-side equipment determines the terminal's scheduling information based on the interference prediction information.

[0290] S509, the network-side equipment sends scheduling information to the terminal.

[0291] Based on the above embodiments, this application also provides an interference prediction method. This embodiment describes the signaling interaction between a terminal and a network-side device during communication. In this embodiment, the terminal performs interference measurement, and the network-side device performs interference prediction. Figure 8 is a signaling flowchart of an interference prediction method provided by this application. As shown in Figure 8, the method provided by this embodiment includes the following steps.

[0292] S601. The terminal sends interference prediction-related capability information to the network-side equipment.

[0293] S602, The terminal sends a first request message to the network-side device.

[0294] The first request message is used to request first auxiliary information from the network-side device. In one example, the first request message includes the types of various first auxiliary information that need to be returned; in another example, the first request message includes first configuration information, which is used to indicate the interference prediction function supported by the terminal.

[0295] S603, The network-side device determines the first auxiliary information.

[0296] The network-side device determines the first auxiliary information based on the first request message. When the first request message includes the first configuration information of the interference prediction function supported by the terminal, the network-side device generates the first auxiliary information based on whether the information in the first configuration information has changed.

[0297] S604. The network-side equipment sends interference measurement configuration information and interference reporting configuration information to the terminal.

[0298] S605. The terminal performs interference measurement based on the interference measurement configuration information to obtain interference measurement information.

[0299] S606, The terminal sends interference measurement information to the network-side equipment.

[0300] It should be noted that steps S602 and S603 are not executed in any order with step S604. Steps S602 and S603 can be executed before step S604, after step S604, or in parallel.

[0301] In some implementations, before step S604, in steps S602 and S603, the network-side device can determine the terminal's interference measurement configuration information and / or interference reporting configuration information based on the first configuration information of the interference prediction function supported by the terminal. For example, when the first configuration information also includes the reference signal type or first indication information supported by the terminal when performing interference measurement or interference prediction, the network-side device can determine the interference measurement resources based on the reference signal type or first indication information supported by the terminal when performing interference measurement or interference prediction.

[0302] S607. The network-side equipment performs interference prediction based on interference measurement information and first auxiliary information to obtain interference prediction information.

[0303] The terminal determines the appropriate interference prediction algorithm based on the first auxiliary information and performs interference prediction using the interference prediction algorithm and interference measurement information. Optionally, the network-side device can use an AI interference prediction model for interference prediction. The network-side device can determine the AI ​​interference prediction model to use based on the first auxiliary information and perform interference prediction based on the determined AI interference prediction model and interference measurement information. The interference measurement information is the input of the AI ​​interference prediction model, and the output of the AI ​​interference prediction model is the interference prediction information.

[0304] S608: The network-side equipment determines the terminal's scheduling information based on the interference prediction information.

[0305] S609, The network-side device sends scheduling information to the terminal.

[0306] The interference prediction method provided in this application can be executed by an interference prediction device. This application uses an interference prediction device executing the interference prediction method as an example to illustrate the interference prediction device provided in this application.

[0307] This application provides an interference prediction device. As an example, the interference prediction device may be a terminal or a component in a terminal, such as a chip. Exemplarily, the terminal may include, but is not limited to, the types of terminals 11 listed above, and this application does not impose specific limitations.

[0308] The interference prediction device includes a receiving module, a transmitting module, and a processing module. These modules can be implemented in software or hardware. When implemented in hardware, the processing module can be implemented by a processor. For example, the processor can include a general-purpose processor, a special-purpose processor, such as a Central Processing Unit (CPU), a microprocessor, a Digital Signal Processor (DSP), an Artificial Intelligence (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, gate circuits, transistors, discrete hardware components, etc. The receiving and transmitting modules can be implemented by a communication interface, which can include one or more of the following: transceiver, pins, circuits, buses, radio frequency units, etc.

[0309] Specifically, referring to Figure 9, which is a schematic block diagram of an interference prediction device provided in an embodiment of this application, when the interference prediction device 700 is a terminal or a component in a terminal, the interference prediction device 700 includes:

[0310] Receiver module 701 is used to receive first auxiliary information from network-side devices;

[0311] The processing module 702 is used to perform interference prediction based on the first auxiliary information.

[0312] In some implementations, the first auxiliary information includes at least one of the following:

[0313] The first scheduling algorithm information or the update information of the scheduling algorithm for the cell;

[0314] The first beam information or updated beam information of the cell;

[0315] The cell's first frequency domain scheduling granularity information or the update information of frequency domain scheduling granularity information;

[0316] The cell's first scheduling type or updated scheduling type information;

[0317] The initial network load information of the community or the updated network load information;

[0318] The first time slot format information or the update information of the time slot format information of the cell;

[0319] The cell's initial transmit power information or updated transmit power information;

[0320] The community's primary service type information or updated service type information;

[0321] The primary signage of the community or information on updated signage.

[0322] In some implementations, the apparatus further includes a sending module, configured to send a first request message to the network-side device, the first request message being used to request the first auxiliary information from the network-side device.

[0323] In some implementations, the apparatus further includes a sending module for sending first configuration information to the network-side device, the first configuration information being used to indicate the interference prediction function supported by the terminal.

[0324] In some implementations, the first configuration information includes at least one of the following:

[0325] Timestamp information is used to indicate the time when the AI ​​interference prediction model was acquired or the time when the dataset was acquired.

[0326] Time period information is used to indicate the time when the AI ​​interference prediction model was acquired or the time when the dataset was acquired;

[0327] Information on the second scheduling algorithm of the cell;

[0328] Second beam information for the cell;

[0329] Second frequency domain scheduling granularity information for the cell;

[0330] The second dispatch type for the community;

[0331] Second network load information for the community;

[0332] The second time slot format information of the cell;

[0333] Second transmission power information of the cell

[0334] The community's second type of business;

[0335] The second sign of the community.

[0336] In some implementations, the first configuration information is associated with at least one AI interference prediction model of the terminal, which is used to perform interference prediction.

[0337] In some implementations, the first configuration information may also include the reference signal type or first indication information supported by the terminal when performing interference measurement or interference prediction; the first indication information is used to indicate whether the terminal supports the demodulation reference signal (DMRS) type when performing interference measurement or interference prediction.

[0338] In some implementations, the receiving module 701 is further configured to: receive second indication information of the first auxiliary information from the network-side device, wherein the second indication information is used to indicate information related to the first auxiliary information;

[0339] The second instruction information includes at least one of the following:

[0340] Time indication information is used to indicate the effective time of the first auxiliary information;

[0341] Frequency indication information, used to indicate the carrier frequency associated with the first auxiliary information;

[0342] Bandwidth indication information, used to indicate the bandwidth associated with the first auxiliary information;

[0343] A partial bandwidth (BWP) identifier is used to indicate the effective frequency range of the first auxiliary information.

[0344] In some implementations, the processing module 702 uses an AI interference prediction model to predict interference.

[0345] In some implementations, the receiving module 701 is further configured to: receive third indication information or fourth indication information from the network-side device;

[0346] The third indication information is used to indicate whether the AI ​​interference prediction model is activated or deactivated, and the fourth indication information is used to indicate whether the AI ​​interference prediction model is available.

[0347] In some implementations, the receiving module 701 is further configured to: receive fifth indication information from the network-side device, the fifth indication information being used to indicate the effective time of the AI ​​interference prediction model.

[0348] In some implementations, the processing module 702 is specifically used to: determine the AI ​​interference prediction model to be used for interference prediction based on the first auxiliary information; and use the AI ​​interference prediction model to perform interference prediction.

[0349] In some implementations, the receiving module 701 is further configured to: receive at least one of the following information from the network-side device: interference measurement configuration information or interference reporting configuration information; the processing module 702 is further configured to: perform interference measurement using corresponding interference measurement resources according to the interference measurement configuration information to obtain interference measurement information, and obtain interference prediction information according to the interference measurement information and the AI ​​interference prediction model; the device 700 further includes a sending module, configured to send the interference prediction information to the network-side device according to the interference reporting configuration information.

[0350] In some implementations, the interference prediction information includes a set of interference prediction values, or a set of interference prediction values ​​and an evaluation index of the interference prediction values.

[0351] The evaluation metrics for the interference prediction values ​​include at least one of the following: the probability, confidence level, uncertainty, or uncertainty range of the interference prediction values.

[0352] The interference prediction device 700 provided in this application embodiment can realize the various processes executed by the terminal in the method described in the embodiments shown in Figures 3-8, and achieve the same technical effect. To avoid repetition, it will not be described again here.

[0353] The interference prediction method provided in this application can be executed by an interference prediction device. This application uses an interference prediction device executing the interference prediction method as an example to illustrate the interference prediction device provided in this application.

[0354] This application provides an interference prediction device. As an example, the interference prediction device may be a network-side device or a component within a network-side device, such as a chip. Exemplarily, the network-side device may include, but is not limited to, the types of network-side devices 12 listed above; this application does not impose specific limitations on these types.

[0355] The interference prediction device includes a receiving module, a transmitting module, and a processing module. These modules can be implemented in software or hardware. When implemented in hardware, the processing module can be implemented by a processor. For example, the processor can include general-purpose processors, special-purpose processors, such as CPUs, microprocessors, DSPs, AI processors, GPUs, ASICs, NPs, FPGAs, or other programmable logic devices, gate circuits, transistors, discrete hardware components, etc. The receiving and transmitting modules can be implemented by a communication interface, which can include one or more of the following: transceivers, pins, circuits, buses, radio frequency units, etc.

[0356] Specifically, referring to Figure 10, which is a schematic block diagram of an interference prediction device provided in an embodiment of this application, when the interference prediction device 800 is a network-side device or a component in a network-side device, the interference prediction device 800 includes:

[0357] The sending module 801 is used to send first auxiliary information to the terminal, the first auxiliary information being used by the terminal to perform interference prediction.

[0358] In some implementations, the first auxiliary information includes at least one of the following:

[0359] The first scheduling algorithm information or the update information of the scheduling algorithm for the cell;

[0360] The first beam information or updated beam information of the cell;

[0361] The cell's first frequency domain scheduling granularity information or the update information of frequency domain scheduling granularity information;

[0362] The cell's first scheduling type or updated scheduling type information;

[0363] The initial network load information of the community or the updated network load information;

[0364] The first time slot format information or the update information of the time slot format information of the cell;

[0365] The cell's initial transmit power information or updated transmit power information;

[0366] The community's primary service type information or updated service type information;

[0367] The primary signage of the community or information on updated signage.

[0368] In some implementations, the device 800 further includes: a receiving module, configured to receive a first request message sent by the terminal, the first request message being used to request the first auxiliary information; and a processing module, configured to determine the first auxiliary information based on the first request message.

[0369] In some implementations, the device 800 further includes: a receiving module for receiving first configuration information of the interference prediction function supported by the terminal sent by the terminal; and a processing module for determining the first auxiliary information based on the first configuration information.

[0370] In some implementations, the first configuration information includes at least one of the following:

[0371] Timestamp information is used to indicate the time when the AI ​​interference prediction model was acquired or the time when the dataset was acquired.

[0372] Time period information is used to indicate the time when the AI ​​interference prediction model was acquired or the time when the dataset was acquired;

[0373] Information on the second scheduling algorithm of the cell;

[0374] Second beam information for the cell;

[0375] Second frequency domain scheduling granularity information for the cell;

[0376] The second dispatch type for the community;

[0377] Second network load information for the community;

[0378] The second time slot format information of the cell;

[0379] Second transmission power information of the cell

[0380] The community's second type of business;

[0381] The second sign of the community.

[0382] In some implementations, the first configuration information is associated with at least one AI interference prediction model supported by the terminal device, the AI ​​interference prediction model being used to perform interference prediction.

[0383] In some implementations, the first configuration information may also include the reference signal type or first indication information supported by the terminal when performing interference measurement or interference prediction;

[0384] The first indication information is used to indicate whether the terminal supports the demodulation reference signal (DMRS) type when performing interference measurement or interference prediction.

[0385] In some implementations, the device 800 further includes: a processing module, configured to determine interference measurement resources for the terminal based on the reference signal type supported by the terminal when performing interference measurement or interference prediction, or the first indication information; the sending module 801 is further configured to send the interference measurement resources to the terminal.

[0386] In some implementations, the processing module is specifically configured to: when the terminal supports DMRS type among the reference signal types when performing interference measurement or interference prediction, or when the first indication information indicates that the terminal supports DMRS type when performing interference measurement or interference prediction, then configure DMRS resources for the terminal as interference measurement resources.

[0387] In some implementations, the sending module 801 is further configured to: send second indication information of the first auxiliary information to the terminal, wherein the second indication information is used to indicate information related to the first auxiliary information;

[0388] The second instruction information includes at least one of the following:

[0389] Time indication information is used to indicate the effective time of the first auxiliary information;

[0390] Frequency indication information, used to indicate the carrier frequency associated with the first auxiliary information;

[0391] Bandwidth indication information, used to indicate the bandwidth associated with the first auxiliary information;

[0392] At least one partial bandwidth BWP identifier, wherein the frequency range of the BWP corresponding to the at least one BWP identifier is the effective frequency range of the first auxiliary information.

[0393] In some implementations, the sending module 801 is further configured to: send third indication information or fourth indication information to the terminal;

[0394] The third indication information is used to indicate whether the AI ​​interference prediction model is activated or deactivated, and the fourth indication information is used to indicate whether the AI ​​interference prediction model is available.

[0395] In some implementations, the device 800 further includes: a receiving module, configured to receive first configuration information of the interference prediction function supported by the terminal sent by the terminal; and a processing module, configured to determine, based on the first configuration information, whether to activate or deactivate the AI ​​interference prediction model, or to determine whether the AI ​​interference prediction model is available or unavailable.

[0396] In some implementations, the sending module 801 is further configured to: send a fifth indication message to the terminal, the fifth indication message being used to indicate the effective time of the AI ​​interference prediction model, the AI ​​interference prediction model being used to perform interference prediction.

[0397] In some implementations, the sending module 801 is further configured to: send at least one of the following information to the terminal: interference measurement configuration information or interference reporting configuration information; the device 800 further includes: a receiving module, configured to receive interference prediction information from the terminal, wherein the interference prediction information is sent by the terminal according to the interference reporting configuration information, the interference prediction information is predicted by the terminal according to the interference measurement information, and the interference measurement information is measured by the terminal according to the interference measurement configuration information.

[0398] In some implementations, the device 800 further includes: a processing module, configured to determine scheduling information for the terminal based on the interference prediction information; the sending module 801 is further configured to send the scheduling information to the terminal.

[0399] The interference prediction device 800 provided in this application embodiment can realize the various processes executed by the network-side device in the method described in the embodiments shown in Figures 3-8, and achieve the same technical effect. To avoid repetition, it will not be described again here.

[0400] As shown in Figure 11, this application embodiment also provides a communication device 900, including a processor 901 and a memory 902. The memory 902 stores programs or instructions that can run on the processor 901. For example, when the communication device 900 is a terminal, the program or instructions executed by the processor 901 implement the various steps executed by the terminal in the above method embodiment, and achieve the same technical effect. When the communication device 900 is a network-side device, the program or instructions executed by the processor 901 implement the various steps executed by the network-side device in the above method embodiment, and achieve the same technical effect. To avoid repetition, this will not be described again here.

[0401] This application also provides a terminal, including a processor and a communication interface, wherein the communication interface is coupled to the processor, and the processor is used to run programs or instructions to implement the steps in the method embodiments shown in Figures 3-8. This terminal embodiment corresponds to the above-described terminal-side method embodiments, and all implementation processes and methods of the above-described method embodiments can be applied to this terminal embodiment and achieve the same technical effect. The terminal may be the interference prediction device shown in Figure 9. Specifically, Figure 12 is a schematic diagram of the hardware structure of a terminal implementing an embodiment of this application.

[0402] The terminal 1000 includes, but is not limited to, at least some of the following components: radio frequency unit 1001, network module 1002, audio output unit 1003, input unit 1004, sensor 1005, display unit 1006, user input unit 1007, interface unit 1008, memory 1009, and processor 1010.

[0403] Those skilled in the art will understand that the terminal 1000 may also include a power supply (such as a battery) for powering various components. The power supply can be logically connected to the processor 1010 through a power management system, thereby enabling functions such as charging, discharging, and power consumption management through the power management system. The terminal structure shown in Figure 12 does not constitute a limitation on the terminal. The terminal may include more or fewer components than shown, or combine certain components, or have different component arrangements, which will not be elaborated here.

[0404] It should be understood that, in this embodiment, the input unit 1004 may include a graphics processor 10041 and a microphone 10042. The graphics processor 10041 processes image data of still images or videos obtained by an image capture device (such as a camera) in video capture mode or image capture mode. The display unit 1006 may include a display panel 10061, which may be configured in the form of a liquid crystal display, an organic light-emitting diode, or the like. The user input unit 1007 includes a touch panel 10071 and at least one of other input devices 10072. The touch panel 10071 is also called a touch screen. The touch panel 10071 may include a touch detection device and a touch controller. Other input devices 10072 may include, but are not limited to, physical keyboards, function keys (such as volume control buttons, power buttons, etc.), trackballs, mice, and joysticks, which will not be described in detail here.

[0405] In this embodiment, after receiving downlink data from the network-side device, the radio frequency unit 1001 can transmit it to the processor 1010 for processing; in addition, the radio frequency unit 1001 can send uplink data to the network-side device. Typically, the radio frequency unit 1001 includes, but is not limited to, antennas, amplifiers, transceivers, couplers, low-noise amplifiers, duplexers, etc.

[0406] The memory 1009 can be used to store software programs or instructions, as well as various data. The memory 1009 may primarily include a first storage area for storing programs or instructions and a second storage area for storing data. The first storage area may store the operating system, application programs or instructions required for at least one function (such as sound playback, image playback, etc.). Furthermore, the memory 1009 may include volatile memory or non-volatile memory. The non-volatile memory may be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. Volatile memory can be random access memory (RAM), static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDRSDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link dynamic random access memory (SLDRAM), and direct memory bus RAM (DRRAM). The memory 1009 in this embodiment includes, but is not limited to, these and any other suitable types of memory.

[0407] The processor 1010 may include one or more processing units; optionally, the processor 1010 integrates an application processor and a modem processor, wherein the application processor mainly handles operations involving the operating system, user interface, and applications, and the modem processor mainly handles wireless communication signals, such as a baseband processor. It is understood that the aforementioned modem processor may also not be integrated into the processor 1010.

[0408] The processor 1010 is configured to receive first auxiliary information from a network-side device and perform interference prediction based on the first auxiliary information.

[0409] It is understood that the implementation process of each implementation method mentioned in this embodiment can refer to the relevant descriptions of the method embodiments shown in Figures 3-8, and achieve the same or corresponding technical effects. To avoid repetition, it will not be described again here.

[0410] This application also provides a network-side device, including a processor and a communication interface. The communication interface is coupled to the processor, and the processor is used to run programs or instructions to implement the steps of the method embodiments shown in Figures 3-8. This network-side device embodiment corresponds to the above-described network-side device method embodiments. All implementation processes and methods of the above-described method embodiments can be applied to this network-side device embodiment and achieve the same technical effects.

[0411] Specifically, this application embodiment also provides a network-side device, which may be the interference prediction device shown in FIG10. As shown in FIG13, the network-side device 1100 includes: an antenna 1101, a radio frequency device 1102, a baseband device 1103, a processor 1104, and a memory 1105. The antenna 1101 is connected to the radio frequency device 1102. In the uplink direction, the radio frequency device 1102 receives information through the antenna 1101 and sends the received information to the baseband device 1103 for processing. In the downlink direction, the baseband device 1103 processes the information to be transmitted and sends it to the radio frequency device 1102. The radio frequency device 1102 processes the received information and transmits it through the antenna 1101.

[0412] The method executed by the network-side device in the above embodiments can be implemented in the baseband device 1103, which includes a baseband processor.

[0413] The baseband device 1103 may include at least one baseband board, on which multiple chips are disposed, as shown in FIG13. One of the chips is, for example, a baseband processor, which is connected to the memory 1105 via a bus interface to call the program or instructions in the memory 1105 to execute the network-side device operation shown in the above method embodiment.

[0414] The network-side device may also include a network interface 1106, such as a Common Public Radio Interface (CPRI).

[0415] Specifically, the network-side device 1100 in this application embodiment further includes: instructions or programs stored in memory 1105 and executable on processor 1104. Processor 1104 calls the instructions or programs in memory 1105 to execute the methods executed by each module shown in FIG10 and achieve the same technical effect. To avoid repetition, it will not be described in detail here.

[0416] This application also provides a readable storage medium storing a program or instructions. When the program or instructions are executed by a processor, they implement the various processes of the method embodiments shown in Figures 3-8 above and achieve the same technical effect. To avoid repetition, they will not be described again here.

[0417] The processor mentioned above is the processor in the terminal or network-side device described in the above embodiments. The readable storage medium includes computer-readable storage media, such as computer read-only memory (ROM), random access memory (RAM), magnetic disk, or optical disk. In some examples, the readable storage medium may be a non-transient readable storage medium.

[0418] This application embodiment also provides a chip, which includes a processor and a communication interface. The communication interface is coupled to the processor. The processor is used to run programs or instructions to implement the various processes of the method embodiments shown in Figures 3-8 above, and can achieve the same technical effect. To avoid repetition, it will not be described again here.

[0419] It should be understood that the chip mentioned in the embodiments of this application may also be referred to as a system-on-a-chip, system chip, chip system, or system-on-a-chip, etc.

[0420] This application also provides a computer program / program product, which is stored in a storage medium and executed by at least one processor to implement the various processes of the method embodiments shown in Figures 3-8 above, and can achieve the same technical effect. To avoid repetition, it will not be described again here.

[0421] This application also provides a communication system, including a terminal and a network-side device. The terminal can be used to perform the steps of the interference prediction method described above, and the network-side device can be used to perform the steps of the interference prediction method described above.

[0422] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element. Furthermore, it should be noted that the scope of the methods and apparatuses in the embodiments of this application is not limited to performing functions in the order shown or discussed, but may also include performing functions substantially simultaneously or in the reverse order, depending on the functions involved. For example, the described methods may be performed in a different order than described, and various steps may be added, omitted, or combined. Additionally, features described with reference to certain examples may be combined in other examples.

[0423] From the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of computer software products plus necessary general-purpose hardware platforms, and of course, they can also be implemented by hardware. The computer software product is stored in a storage medium (such as ROM, RAM, magnetic disk, optical disk, etc.) and includes several instructions to cause the terminal or network-side device to execute the methods described in the various embodiments of this application.

[0424] The embodiments of this application have been described above with reference to the accompanying drawings. However, this application is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other implementations under the guidance of this application without departing from the spirit and scope of the claims. All of these implementations are within the protection scope of this application.

Claims

1. An interference prediction method, wherein, include: The terminal receives the first auxiliary information from the network-side device; The terminal performs interference prediction based on the first auxiliary information.

2. The method according to claim 1, wherein, The first auxiliary information includes at least one of the following: The first scheduling algorithm information or the update information of the scheduling algorithm for the cell; The first beam information or updated beam information of the cell; The cell's first frequency domain scheduling granularity information or the update information of frequency domain scheduling granularity information; The cell's first scheduling type or updated scheduling type information; The initial network load information of the community or the updated network load information; The first time slot format information or the update information of the time slot format information of the cell; The cell's initial transmit power information or updated transmit power information; The community's primary service type information or updated service type information; The primary signage of the community or information on updated signage.

3. The method according to claim 1 or 2, wherein, Before the terminal receives the first auxiliary information from the network-side device, it also includes: The terminal sends a first request message to the network-side device, the first request message being used to request the first auxiliary information from the network-side device.

4. The method according to claim 1 or 2, wherein, Before the terminal receives the first auxiliary information from the network-side device, it also includes: The terminal sends first configuration information to the network-side device, the first configuration information being used to indicate the interference prediction function supported by the terminal.

5. The method according to claim 4, wherein, The first configuration information includes at least one of the following: Timestamp information is used to indicate the time when the AI ​​interference prediction model was acquired or the time when the dataset was acquired. Time period information is used to indicate the time when the AI ​​interference prediction model was acquired or the time when the dataset was acquired; Information on the second scheduling algorithm of the cell; Second beam information for the cell; Second frequency domain scheduling granularity information for the cell; The second dispatch type for the community; Second network load information for the community; The second time slot format information of the cell; Second transmission power information of the cell The community's second type of business; The second sign of the community.

6. The method according to claim 4 or 5, wherein, The first configuration information is associated with at least one AI interference prediction model of the terminal, which is used to perform interference prediction.

7. The method according to any one of claims 4-6, wherein, The first configuration information also includes the reference signal type or first indication information supported by the terminal when performing interference measurement or interference prediction; The first indication information is used to indicate whether the terminal supports the demodulation reference signal (DMRS) type when performing interference measurement or interference prediction.

8. The method according to any one of claims 1-7, wherein, Before the terminal performs interference prediction based on the first auxiliary information, it further includes: The terminal receives second indication information from the network-side device, the second indication information being used to indicate information related to the first auxiliary information; The second instruction information includes at least one of the following: Time indication information is used to indicate the effective time of the first auxiliary information; Frequency indication information, used to indicate the carrier frequency associated with the first auxiliary information; Bandwidth indication information, used to indicate the bandwidth associated with the first auxiliary information; At least one partial bandwidth BWP identifier, wherein the frequency range of the BWP corresponding to the at least one BWP identifier is the effective frequency range of the first auxiliary information.

9. The method according to any one of claims 1-8, wherein, The terminal uses an AI interference prediction model to predict interference.

10. The method according to claim 9, wherein, Also includes: The terminal receives at least one of the following information from the network-side device: The third instruction information is used to indicate whether to activate or deactivate the AI ​​interference prediction model; The fourth indication is used to indicate whether the AI ​​interference prediction model is available; The fifth indicator is used to indicate the effective time of the AI ​​interference prediction model.

11. An interference prediction method, wherein, include: The network-side device sends first auxiliary information to the terminal, which is used by the terminal to predict interference.

12. The method according to claim 11, wherein, The first auxiliary information includes at least one of the following: The first scheduling algorithm information or the update information of the scheduling algorithm for the cell; The first beam information or updated beam information of the cell; The cell's first frequency domain scheduling granularity information or the update information of frequency domain scheduling granularity information; The cell's first scheduling type or updated scheduling type information; The initial network load information of the community or the updated network load information; The first time slot format information or the update information of the time slot format information of the cell; The cell's initial transmit power information or updated transmit power information; The community's primary service type information or updated service type information; The primary signage of the community or information on updated signage.

13. The method according to claim 11 or 12, wherein, Before the network-side device sends the first auxiliary information to the terminal, it also includes: The network-side device receives a first request message sent by the terminal, the first request message being used to request the first auxiliary information; The network-side device determines the first auxiliary information based on the first request message.

14. The method according to claim 11 or 12, wherein, Before the network-side device sends the first auxiliary information to the terminal, it also includes: The network-side device receives first configuration information sent by the terminal, the first configuration information being used to indicate the interference prediction function supported by the terminal; The network-side device determines the first auxiliary information based on the first configuration information.

15. The method according to claim 14, wherein, The first configuration information includes at least one of the following: Timestamp information is used to indicate the time when the AI ​​interference prediction model was acquired or the time when the dataset was acquired. Time period information is used to indicate the time when the AI ​​interference prediction model was acquired or the time when the dataset was acquired; Information on the second scheduling algorithm of the cell; Second beam information for the cell; Second frequency domain scheduling granularity information for the cell; The second dispatch type for the community; Second network load information for the community; The second time slot format information of the cell; Second transmission power information of the cell The community's second type of business; The second sign of the community.

16. The method according to claim 14 or 15, wherein, The first configuration information is associated with at least one AI interference prediction model supported by the terminal device, and the AI ​​interference prediction model is used to perform interference prediction.

17. The method according to any one of claims 14-16, wherein, The first configuration information also includes the reference signal type or first indication information supported by the terminal when performing interference measurement or interference prediction; The first indication information is used to indicate whether the terminal supports the demodulation reference signal (DMRS) type when performing interference measurement or interference prediction.

18. The method according to any one of claims 11-17, wherein, Also includes: The network-side device sends a second indication information to the terminal, wherein the second indication information is used to indicate information related to the first auxiliary information; The second instruction information includes at least one of the following: Time indication information is used to indicate the effective time of the first auxiliary information; Frequency indication information, used to indicate the carrier frequency associated with the first auxiliary information; Bandwidth indication information, used to indicate the bandwidth associated with the first auxiliary information; At least one partial bandwidth BWP identifier, wherein the frequency range of the BWP corresponding to the at least one BWP identifier is the effective frequency range of the first auxiliary information.

19. The method according to any one of claims 11-18, wherein, Also includes: The network-side device sends at least one of the following pieces of information to the terminal: The third instruction information is used to indicate whether to activate or deactivate the AI ​​interference prediction model; The fourth indication is used to indicate whether the AI ​​interference prediction model is available; The fifth indication is used to indicate the effective time of the AI ​​interference prediction model; The AI ​​interference prediction model is used for interference prediction.

20. The method according to claim 19, wherein, Also includes: The network-side device receives first configuration information sent by the terminal, the first configuration information being used to indicate the interference prediction function supported by the terminal; The network-side device determines whether to activate or deactivate the AI ​​interference prediction model, or whether the AI ​​interference prediction model is available or unavailable, based on the first configuration information.

21. An interference prediction device, wherein, include: The receiving module is used to receive first auxiliary information from the network-side device; The processing module is used to predict interference based on the first auxiliary information.

22. The apparatus according to claim 21, wherein, The first auxiliary information includes at least one of the following: The first scheduling algorithm information or the update information of the scheduling algorithm for the cell; The first beam information or updated beam information of the cell; The cell's first frequency domain scheduling granularity information or the update information of frequency domain scheduling granularity information; The cell's first scheduling type or updated scheduling type information; The initial network load information of the community or the updated network load information; The first time slot format information or the update information of the time slot format information of the cell; The cell's initial transmit power information or updated transmit power information; The community's primary service type information or updated service type information; The primary signage of the community or information on updated signage.

23. The apparatus according to claim 21 or 22, wherein, Also includes: The sending module is used to send a first request message to the network-side device, the first request message being used to request the first auxiliary information from the network-side device.

24. The apparatus according to claim 21 or 22, wherein, Also includes: The sending module is used to send first configuration information to the network-side device, wherein the first configuration information is used to indicate the interference prediction function supported by the terminal.

25. The apparatus according to claim 24, wherein, The first configuration information includes at least one of the following: Timestamp information is used to indicate the time when the AI ​​interference prediction model was acquired or the time when the dataset was acquired. Time period information is used to indicate the time when the AI ​​interference prediction model was acquired or the time when the dataset was acquired; Information on the second scheduling algorithm of the cell; Second beam information for the cell; Second frequency domain scheduling granularity information for the cell; The second dispatch type for the community; Second network load information for the community; The second time slot format information of the cell; Second transmission power information of the cell The community's second type of business; The second sign of the community.

26. The apparatus according to claim 24 or 25, wherein, The first configuration information also includes the reference signal type or first indication information supported by the terminal when performing interference measurement or interference prediction; The first indication information is used to indicate whether the terminal supports the demodulation reference signal (DMRS) type when performing interference measurement or interference prediction.

27. The apparatus according to any one of claims 21-26, wherein, The receiving module is further configured to: receive second indication information of the first auxiliary information from the network-side device, wherein the second indication information is used to indicate information related to the first auxiliary information; The second instruction information includes at least one of the following: Time indication information is used to indicate the effective time of the first auxiliary information; Frequency indication information, used to indicate the carrier frequency associated with the first auxiliary information; Bandwidth indication information, used to indicate the bandwidth associated with the first auxiliary information; At least one partial bandwidth BWP identifier, wherein the frequency range of the BWP corresponding to the at least one BWP identifier is the effective frequency range of the first auxiliary information.

28. The apparatus according to any one of claims 21-27, wherein, The processing module uses an AI interference prediction model to predict interference.

29. The apparatus according to claim 28, wherein, The receiving module is also used for: Receive at least one of the following information from the network-side device: The third instruction information is used to indicate whether to activate or deactivate the AI ​​interference prediction model; The fourth indication information is used to indicate whether the AI ​​interference prediction model is available; The fifth indication information is used to indicate the effective time of the AI ​​interference prediction model.

30. An interference prediction device, wherein, include: The sending module is used to send first auxiliary information to the terminal, the first auxiliary information being used by the terminal to predict interference.

31. The apparatus according to claim 30, wherein, The first auxiliary information includes at least one of the following: The first scheduling algorithm information or the update information of the scheduling algorithm for the cell; The first beam information or updated beam information of the cell; The cell's first frequency domain scheduling granularity information or the update information of frequency domain scheduling granularity information; The cell's first scheduling type or updated scheduling type information; The initial network load information of the community or the updated network load information; The first time slot format information or the update information of the time slot format information of the cell; The cell's initial transmit power information or updated transmit power information; The community's primary service type information or updated service type information; The primary signage of the community or information on updated signage.

32. The apparatus according to claim 30 or 31, wherein, Also includes: The receiving module is configured to receive a first request message sent by the terminal, wherein the first request message is used to request the first auxiliary information; The processing module is used to determine the first auxiliary information based on the first request message.

33. The apparatus according to claim 30 or 31, wherein, Also includes: A receiving module is configured to receive first configuration information of the interference prediction function supported by the terminal, sent by the terminal. The processing module is used to determine the first auxiliary information based on the first configuration information.

34. The apparatus according to claim 33, wherein, The first configuration information includes at least one of the following: Timestamp information is used to indicate the time when the AI ​​interference prediction model was acquired or the time when the dataset was acquired. Time period information is used to indicate the time when the AI ​​interference prediction model was acquired or the time when the dataset was acquired; Information on the second scheduling algorithm of the cell; Second beam information for the cell; Second frequency domain scheduling granularity information for the cell; The second dispatch type for the community; Second network load information for the community; The second time slot format information of the cell; Second transmission power information of the cell The community's second type of business; The second sign of the community.

35. The apparatus according to claim 33 or 34, wherein, The first configuration information also includes the reference signal type or first indication information supported by the terminal when performing interference measurement or interference prediction; The first indication information is used to indicate whether the terminal supports the demodulation reference signal (DMRS) type when performing interference measurement or interference prediction.

36. The apparatus according to any one of claims 30-35, wherein, The sending module is further configured to: send second indication information of the first auxiliary information to the terminal, wherein the second indication information is used to indicate information related to the first auxiliary information; The second instruction information includes at least one of the following: Time indication information is used to indicate the effective time of the first auxiliary information; Frequency indication information, used to indicate the carrier frequency associated with the first auxiliary information; Bandwidth indication information, used to indicate the bandwidth associated with the first auxiliary information; At least one partial bandwidth BWP identifier, wherein the frequency range of the BWP corresponding to the at least one BWP identifier is the effective frequency range of the first auxiliary information.

37. The apparatus according to any one of claims 30-36, wherein, The sending module is further configured to: send at least one of the following information to the terminal: The third instruction information is used to indicate whether to activate or deactivate the AI ​​interference prediction model; The fourth indication is used to indicate whether the AI ​​interference prediction model is available; The fifth instruction is used to indicate the effective time of the AI ​​interference prediction model; The AI ​​interference prediction model is used for interference prediction.

38. A terminal device, wherein, It includes a processor and a memory, the memory storing a program or instructions that can run on the processor, the program or instructions being executed by the processor to implement the steps of the interference prediction method as described in any one of claims 1 to 10.

39. A network-side device, wherein, It includes a processor and a memory, the memory storing a program or instructions that can run on the processor, the program or instructions being executed by the processor to implement the steps of the interference prediction method as described in any one of claims 11 to 20.

40. A readable storage medium, wherein, The readable storage medium stores a program or instructions that, when executed by a processor, implement the interference prediction method as described in any one of claims 1-10, or implement the steps of the interference prediction method as described in any one of claims 11-20.

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