Channel estimation methods, devices, terminals and network-side equipment

Abstract

This application discloses a channel estimation method, apparatus, terminal, and network-side device, belonging to the field of communication technology. The channel estimation method of this application includes: a terminal receiving first information sent by a network-side device, the first information being used to indicate a target association relationship, the target association relationship being an association relationship between a first signal and multiple sets of second signals, the multiple sets of second signals corresponding one-to-one with multiple resource ranges; the terminal performing channel estimation based on the first information.

Description

Technical Field

[0001] This application belongs to the field of communication technology, specifically relating to a channel estimation method, apparatus, terminal, and network-side equipment. Background Technology

[0002] In related technologies, a terminal can use the estimation result corresponding to the first signal to predict the channel estimation result corresponding to the second signal. For example, the channel parameters (such as delay spread, average delay, etc.) obtained from channel estimation of two signals in quasi-co-location (QCL) are considered to be consistent. When the first signal and the second signal are in QCL, the channel estimation result corresponding to the second signal is predicted based on the estimation result corresponding to the first signal. However, in some scenarios (such as when the channel changes frequently), the probability of inconsistencies in the channel parameters corresponding to the two signals considered to be in QCL is relatively high, which will lead to poor accuracy of channel estimation. Summary of the Invention

[0003] This application provides a channel estimation method, apparatus, terminal, and network-side device that can solve the problem of poor accuracy in channel estimation.

[0004] Firstly, a channel estimation method is provided, executed by a terminal, the method comprising:

[0005] The terminal receives first information sent by the network-side device. The first information is used to indicate a target association relationship. The target association relationship is the association relationship between a first signal and multiple sets of second signals. The multiple sets of second signals correspond one-to-one with multiple resource ranges.

[0006] The terminal performs channel estimation based on the first information.

[0007] Secondly, a channel estimation method is provided, executed by a network-side device, the method comprising:

[0008] The network-side device sends first information to the terminal. The first information is used to indicate the target association relationship. The target association relationship is the association relationship between the first signal and multiple sets of second signals. The multiple sets of second signals correspond one-to-one with multiple resource ranges.

[0009] Thirdly, a channel estimation apparatus is provided, comprising:

[0010] The receiving module is used to receive first information sent by the network-side device. The first information is used to indicate a target association relationship. The target association relationship is the association relationship between a first signal and multiple sets of second signals. The multiple sets of second signals correspond one-to-one with multiple resource ranges.

[0011] The processing module is used to perform channel estimation based on the first information.

[0012] Fourthly, a channel estimation apparatus is provided, comprising:

[0013] The sending module is used to send first information to the terminal. The first information is used to indicate a target association relationship. The target association relationship is the association relationship between a first signal and multiple sets of second signals. The multiple sets of second signals correspond one-to-one with multiple resource ranges.

[0014] Fifthly, a channel estimation 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.

[0015] 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.

[0016] Seventhly, a terminal is provided, including a processor and a communication interface, wherein,

[0017] A communication interface is used to receive first information sent by a network-side device. The first information is used to indicate a target association relationship. The target association relationship is the association relationship between a first signal and multiple sets of second signals. The multiple sets of second signals correspond one-to-one with multiple resource ranges.

[0018] A processor for performing channel estimation based on the first information.

[0019] 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.

[0020] Ninthly, a network-side device is provided, including a processor and a communication interface, wherein,

[0021] A communication interface is used to send first information to a terminal. The first information is used to indicate a target association relationship. The target association relationship is the association relationship between a first signal and multiple sets of second signals. The multiple sets of second signals correspond one-to-one with multiple resource ranges.

[0022] 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.

[0023] 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.

[0024] 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 programs or instructions to implement the method as described in the first aspect, or to implement the method as described in the second aspect.

[0025] 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 method as described in the first aspect, or to implement the method as described in the second aspect.

[0026] In this embodiment, the terminal receives first information sent by a network-side device. This first information indicates a target association relationship, which is the association between a first signal and multiple sets of second signals, each set of second signals corresponding one-to-one with multiple resource ranges. The terminal performs channel estimation based on the first information. In this way, the terminal performs channel estimation based on the association relationship between the first signal and the multiple sets of second signals. Using this association relationship reduces the probability of inconsistencies in the channel parameters corresponding to the first and second signals, thereby improving the accuracy of channel estimation. Attached Figure Description

[0027] Figure 1 This is a block diagram of a wireless communication system applicable to embodiments of this application;

[0028] Figure 2 This is an example of a signal QCL in related technologies;

[0029] Figure 3 This is one of the flowcharts of a channel estimation method provided in the embodiments of this application;

[0030] Figure 4 This is one example of a channel estimation method provided in the embodiments of this application;

[0031] Figure 5 This is one example of a signal correlation relationship provided in the embodiments of this application;

[0032] Figure 6 This is a second example of a channel estimation method provided in the embodiments of this application;

[0033] Figure 7 This is a second example of a signal correlation relationship provided in the embodiments of this application;

[0034] Figure 8 This is a second flowchart of a channel estimation method provided in the embodiments of this application;

[0035] Figure 9 This is the third flowchart of a channel estimation method provided in the embodiments of this application;

[0036] Figure 10 This is one of the structural schematic diagrams of a channel estimation device provided in the embodiments of this application;

[0037] Figure 11 This is a second schematic diagram of the structure of a channel estimation device provided in an embodiment of this application;

[0038] Figure 12 This is a schematic diagram of the structure of a communication device provided in an embodiment of this application;

[0039] Figure 13 This is a schematic diagram of the structure of a terminal provided in an embodiment of this application;

[0040] Figure 14 This is one of the structural schematic diagrams of a network-side device provided in the embodiments of this application;

[0041] Figure 15 This is a second schematic diagram of the structure of a network-side device provided in an embodiment of this application. Detailed Implementation

[0042] 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.

[0043] 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.

[0044] 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.

[0045] 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 in the systems and radio technologies mentioned above, as well as in 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) communication systems.

[0046] Figure 1This diagram illustrates a block diagram of a wireless communication system applicable to embodiments 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 devices (home appliances with wireless communication capabilities, such as refrigerators, televisions, washing machines, or furniture), game consoles, personal computers (PCs), ATMs, or self-service machines, 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 this application embodiment. Network-side equipment 12 may include access network equipment or core network equipment, wherein 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, Transmission and Reception 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 specific technical terms. 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.

[0047] 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 (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.

[0048] 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).

[0049] For ease of understanding, the following explains some aspects of the embodiments of this application:

[0050] 1. Quasi-Colocation (QCL)

[0051] Quasi-co-location can also be described as quasi-co-location. Two signals transmitted from the same antenna port should experience the same radio channel, while signals transmitted from two different antenna ports should experience different radio conditions. However, in some cases, signals transmitted from two different antenna ports may encounter radio channels with common characteristics. In this case, the antenna ports are called quasi-co-location or quasi-co-location. If the channel characteristics of a symbol on one antenna port can be inferred from the channel of a symbol on another antenna port, then the two antenna ports are called quasi-co-location.

[0052] There are four types of QCL: QCL Type A, QCL Type B, QCL Type C, and QCL Type D. These four types indicate the granularity of combinations of large-scale parameters that can be used in QCL. These large-scale channel parameters include: delay spread, average delay, Doppler spread, Doppler offset, average gain, and spatial reception parameters, etc.

[0053] QCL-TypeA:{Doppler shift,Doppler spread,average delay,delay spread};

[0054] QCL-TypeB:{Doppler shift,Doppler spread};

[0055] QCL-TypeC:{Doppler shift, average delay};

[0056] QCL-TypeD:{Spatial Rx parameter}.

[0057] Taking the tracking reference signal (TRS) and demodulation reference signal (DMRS) QCL as an example (e.g.) Figure 2 As shown in the figure (where N represents the TRS period), the large-scale channel parameters estimated by TRS within one TRS period can be considered consistent with the large-scale channel parameters experienced by DMRS. Therefore, when performing DMRS channel estimation, it is not necessary to repeatedly estimate these large-scale parameters; the large-scale information estimated by TRS can be directly copied and used for DMRS channel estimation, interpolation filtering, etc.

[0058] 2. AI

[0059] Artificial intelligence has been widely applied in various fields. AI units can be implemented in various ways, such as neural networks, decision trees, support vector machines, and Bayesian classifiers. This application uses neural networks as an example, but does not limit the specific type of AI unit.

[0060] Generally, the AI ​​algorithms and AI units selected vary depending on the type of problem. Among related technologies, the main method for improving 5G network performance using AI is to enhance or replace existing algorithms or processing modules with neural network-based algorithms and AI units. In specific scenarios, neural network-based algorithms and AI units can achieve better performance than deterministic algorithms. Commonly used neural networks include deep neural networks, convolutional neural networks, and recurrent neural networks. Existing AI tools can be used to build, train, and validate neural networks.

[0061] In related technologies, AI has demonstrated superior performance compared to traditional methods in complex communication tasks such as wireless environment modeling, signal detection, channel estimation, beamforming, positioning, mobility management, radio resource allocation, traffic prediction, network state tracking, and intelligent scheduling. 3GPP has already conducted wireless AI standardization research in several projects, including AI / ML for Operation Administration and Maintenance (OAM), AI / ML for Next Generation Radio Access Network (NG-RAN), Enablers for Network Automation for 5G-Phase 3, 5G Systems Support for AI / ML-based Services, and AI / ML for Air Interface. Specific research directions include:

[0062] AI / ML for OAM primarily focuses on management data analytics service (MDAS).

[0063] Enablers for Network Automation for 5G-Phase 3 and 5G Systems Support for AI / ML-based Services are projects that introduce AI into the core network. In Release 18, the main research focuses on AI model sharing, support for federated learning, enhancement of NWDAF, and 5G systems assisting AI / ML models to achieve intelligent transmission and provide transmission assurance.

[0064] AI / ML for NG-RAN investigated three use cases and a basic functional framework in Release 17: network power saving, load balancing, and mobility optimization. Release 18 primarily focused on data acquisition and signaling enhancement.

[0065] AI / ML for Air Interface is a project established in Release 18 for air interface enhancement. Its research focuses on the general architecture of air interface AI, such as cooperation level and lifecycle management, as well as three use cases: AI-based channel state information (CSI) enhancement, beam enhancement, and positioning enhancement.

[0066] With the popularization of AI technology and resources, more high-value use cases will emerge, continuously improving the performance of mobile communication systems.

[0067] The channel estimation method, apparatus, and related equipment provided in this application will be described in detail below with reference to the accompanying drawings and through some embodiments and application scenarios.

[0068] See Figure 3 , Figure 3 This is a flowchart of a channel estimation method provided in an embodiment of this application, such as... Figure 3 As shown, the channel estimation method includes the following steps:

[0069] Step 101: The terminal receives first information sent by the network-side device. The first information is used to indicate the target association relationship. The target association relationship is the association relationship between the first signal and multiple sets of second signals. The multiple sets of second signals correspond one-to-one with multiple resource ranges.

[0070] Step 102: The terminal performs channel estimation based on the first information.

[0071] The association between the first signal and multiple sets of second signals can be understood or replaced as the grouping association between the first signal and multiple sets of second signals, or the association between the first signal and the second signals of multiple resource ranges, or the association between the first signal and the second signals of different resource ranges in multiple resource ranges.

[0072] In one implementation, the target association relationship may refer to different association relationships between the first signal and multiple sets of second signals. The target association relationship can be understood or replaced as a grouping association relationship.

[0073] It should be noted that one of the multiple sets of second signals can refer to the second signal in one of the multiple resource ranges. Taking the resource range as a time-domain resource range as an example, the first set of second signals can be the second signal in the range from the 1st to the 10th time slot, the second set of second signals can be the second signal in the range from the 11th to the 20th time slot, the third set of second signals can be the second signal in the range from the 21st to the 30th time slot; and so on.

[0074] In one embodiment, the plurality of resource ranges are different resource ranges. Each set of second signals corresponds to a different resource range.

[0075] Wherein, the first signal can be a reference signal, and the second signal can be a reference signal.

[0076] In one embodiment, the first signal may include at least one of the following: TRS, CSI Reference Signal (CSI-RS), and Synchronization Signal Block (SSB); the second signal may include at least one of the following: DMRS, TRS, and CSI-RS.

[0077] For example, the first signal and the second signal can be any combination of the following:

[0078] {The first signal is SSB, the second signal is DMRS};

[0079] {The first signal is SSB, the second signal is TRS};

[0080] {The first signal is SSB, and the second signal is CSI-RS};

[0081] {The first signal is TRS, the second signal is DMRS};

[0082] {The first signal is TRS, and the second signal is CSI-RS};

[0083] {The first signal is CSI-RS, and the second signal is DMRS}.

[0084] The CSI-RS can be either a CSI-RS for beam management or a CSI-RS for CSI acquisition.

[0085] The DMRS can be a DMRS on the Physical downlink shared channel (PDSCH) or a DMRS on the Physical downlink control channel (PDCCH).

[0086] It should be noted that, when the first signal and the second signal satisfy the target correlation relationship, the first signal and the second signal in different resource ranges have the same or similar channel parameters, and the channel parameters include at least one of the following: delay spread, average delay, Doppler spread, Doppler offset, average gain, spatial receiving parameter (spatial RX parameter), spatial transmitting parameter (spatial TX parameter), etc.

[0087] The resource range may include a time-domain resource range, a frequency-domain resource range, and / or a spatial-domain resource range. Each of the plurality of resource ranges may include a time-domain resource range, a frequency-domain resource range, and / or a spatial-domain resource range.

[0088] In one embodiment, the plurality of second signals can correspond one-to-one with a plurality of time-domain resource ranges. For example, each of the plurality of second signals corresponds to a different time-domain resource range.

[0089] In one embodiment, the plurality of second signals may correspond one-to-one with a plurality of frequency domain resource ranges. For example, each of the plurality of second signals corresponds to a different frequency domain resource range.

[0090] In one embodiment, the multiple sets of second signals can correspond one-to-one with multiple airspace resource ranges. For example, each set of second signals corresponds to a different airspace resource range.

[0091] For example, the time domain resource range corresponding to a certain group of second signals in the plurality of groups of second signals can be the range from the kth time slot to the mth time slot, where k and m are both integers and k is less than m.

[0092] For example, the frequency domain resource range corresponding to one of the multiple sets of second signals can be the range of the k-th subcarrier, resource block (RB), or sub-band to the m-th subcarrier, RB, or sub-band. For instance, a certain frequency domain resource range can be the range from the k-th subcarrier to the m-th subcarrier; or, a certain frequency domain resource range can be the range from the k-th RB to the m-th RB; or, a certain frequency domain resource range can be the range from the k-th sub-band to the m-th sub-band, where k and m are both integers, and k is less than m.

[0093] For example, the spatial resource range corresponding to one of the multiple sets of second signals can be the range from the k-th sub-antenna, port, or TRP to the m-th sub-antenna, port, or TRP. For instance, a spatial resource range can be the range from the k-th sub-antenna to the m-th sub-antenna; or, a spatial resource range can be the range from the k-th port to the m-th port; or, a spatial resource range can be the range from the k-th TRP to the m-th TRP, where k and m are both integers, and k is less than m.

[0094] In one implementation, the effective resource scope corresponding to the target association relationship includes the plurality of resource scopes. For example, the resource scope obtained by merging the plurality of resource scopes may be less than or equal to the effective resource scope corresponding to the target association relationship. The effective resource scope corresponding to the target association relationship may refer to the resource scope in which the target association relationship is effective.

[0095] In one implementation, the target association is associated with a first AI unit. The first AI unit is used to output multiple sets of estimation results or multiple sets of prediction results of the first signal with respect to the first channel parameters based on the first signal.

[0096] The multiple sets of estimation results can be multiple sets of channel estimation results, which may include channel coefficients, vectors, or matrices; or, the multiple sets of estimation results can be multiple sets of channel parameter estimation results, which may include values ​​of channel parameters (such as large-scale channel parameters).

[0097] The multiple prediction results can be multiple channel prediction results, which may include predicted channel coefficients, vectors, or matrices; or, the multiple prediction results can be multiple channel parameter prediction results, which may include predicted channel parameter values ​​(such as large-scale channel parameters).

[0098] In one embodiment, the terminal performing channel estimation based on the first information may include: the terminal performing channel estimation based on the first information and the first signal; or, the terminal performing channel estimation based on the channel estimation result or channel prediction result corresponding to the first signal and the first information; or, the terminal performing channel estimation based on the channel parameter estimation result or channel parameter prediction result corresponding to the first signal and the first information.

[0099] In one implementation, the target association is associated with a first AI unit, which is used to input a first signal or a first channel estimation result obtained based on the first signal, and output multiple sets of channel parameter estimation results. Each set of channel parameter estimation results is associated with a second signal in a different resource range. The terminal can obtain a second channel estimation result based on the second signal and its associated channel parameter estimation results.

[0100] Taking the first signal as TRS and the second signal as DMRS as an example, Figure 4 The description refers to the estimation results of multiple sets of channel parameters obtained based on TRS. Figure 5 It describes the specific relationships.

[0101] In one implementation, the first information may be carried by at least one of the following:

[0102] Radio Resource Control (RRC) messages; Medium Access Control (MAC) Control Element (CE) messages; Non-Access Stratum (NAS) messages; Management and orchestration messages; User plane data (such as logical channels, Data Radio Bearer (DRB) or Protocol Data Unit (PDU) sessions); Downlink Control Information (DCI) messages; System Information Block (SIB); Layer 1 signaling for the Physical Downlink Control Channel (PDCCH); Information for the Physical Downlink Shared Channel (PDSCH); MSG 2 information for the Physical Random Access Channel (PRACH); MSG 4 information for the Physical Random Access Channel (PRACH); MSG B information for the Physical Random Access Channel (PRACH).

[0103] The AI ​​unit described in this application embodiment may also be referred to as an AI model, machine learning (ML) model, ML unit, AI structure, AI function, AI characteristic, machine learning model, neural network, neural network function, neural network functionality, etc. Alternatively, the AI ​​unit may refer to a processing unit capable of implementing specific algorithms, formulas, processing flows, capabilities, etc., related to AI. Or, the AI ​​unit may be a processing method, algorithm, function, module, or unit for a specific dataset. Alternatively, the AI ​​unit 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), or application-specific integrated circuit (ASIC). This application embodiment does not specifically limit this. Optionally, the specific dataset includes the input or output of the AI ​​unit.

[0104] Optionally, the identifier of the AI ​​unit may be an AI model identifier, AI structure identifier, AI algorithm identifier, function ID, physical identifier, logical identifier, global identifier, local identifier, or the identifier of a specific dataset associated with the AI ​​unit, or the identifier of a specific scenario, environment, channel characteristics, or device related to the AI, or the identifier of a function, characteristic, capability, or module related to the AI. This application embodiment does not specifically limit this.

[0105] Within a specific resource range, the terminal can predict channel parameters based on AI, thereby enabling grouped correlation between different signals. Specifically, multiple sets of channel parameters are obtained by predicting the channel parameters based on the first signal, and each set of parameters is associated with a set of second signals. Compared to the global correlation method of the traditional QCL scheme, the embodiments of this application can improve the correlation between channel parameters and second signals, thereby improving the estimation accuracy of the second signals and increasing throughput.

[0106] In existing QCL schemes, the QCL relationship between one signal and another is global, meaning that the specified large-scale information of the first and second signals is completely consistent. However, when the channel changes frequently, it is difficult to satisfy this completely consistent relationship. For example, in high-speed scenarios, due to the rapid changes in the channel, it is difficult to guarantee that the estimated TRS (such as the large-scale information mentioned above) is QCL for all DMRS within its period.

[0107] If the existing QCL scheme is still used, the large-scale information of the two QCL signals is actually mismatched, which leads to a decrease in channel estimation accuracy and consequently a decrease in throughput. Reducing the resource range in which QCL is effective increases resource overhead, which in turn also reduces throughput. This application's embodiment predicts channel parameters based on AI estimation results without changing the resource range in which QCL is effective. The predicted channel parameters avoid mismatch between the two QCL signals, further preventing a decrease in channel estimation. At this point, the two signals that were originally intended for QCL will have different correlation relationships.

[0108] In this embodiment, the terminal receives first information sent by a network-side device. This first information indicates a target association relationship, which is the association between a first signal and multiple sets of second signals, each set of second signals corresponding one-to-one with multiple resource ranges. The terminal performs channel estimation based on the first information. In this way, the terminal performs channel estimation based on the association relationship between the first signal and the multiple sets of second signals. Using this association relationship reduces the probability of inconsistencies in the channel parameters corresponding to the first and second signals, thereby improving the accuracy of channel estimation.

[0109] Optionally, the target association is associated with channel parameters, and / or the target association is set with an effective resource range.

[0110] It should be noted that the target association may be different or the same for different channel parameters.

[0111] The target association is defined with an effective resource scope, meaning the target association is established within a specific resource scope. For example:

[0112] The effective resource scope includes the target time domain resource scope, such as the interval between two consecutive transmissions of the first signal, or one period of the periodically transmitted first signal; and / or,

[0113] The effective resource scope includes the target frequency domain resource range; and / or,

[0114] The effective resource range includes the target airspace resource range, such as a specific set of antennas or ports.

[0115] Optionally, the target correlation relationship is the correlation relationship between multiple sets of estimation results of the first signal with respect to the first channel parameters and the multiple sets of second signals, wherein the multiple sets of estimation results correspond one-to-one with the multiple sets of second signals; or,

[0116] The target correlation relationship is the correlation between multiple sets of prediction results of the first signal with respect to the first channel parameters and the multiple sets of second signals, wherein the multiple sets of prediction results correspond one-to-one with the multiple sets of second signals.

[0117] Optionally, the first information includes at least one of the following:

[0118] First indication information, the first indication information is used to indicate that the first signal and the second signal have the target correlation relationship with respect to the first channel parameter;

[0119] The second indication information is used to indicate the correlation between multiple sets of estimation results or multiple sets of prediction results of the first signal with respect to the first channel parameters and the multiple sets of second signals, respectively.

[0120] The scope of resources for which the target association is effective;

[0121] The identifier of the first artificial intelligence (AI) unit, which is used to output multiple sets of estimation results or multiple sets of prediction results of the first signal with respect to the first channel parameters based on the first signal.

[0122] The first channel parameter may include at least one of the following: delay spread, average delay, Doppler spread, Doppler offset, average gain, spatial reception parameters, spatial transmission parameters, etc.

[0123] In one implementation, the first indication information may be an association level. When the association level is a preset level, it indicates that the first signal is associated with multiple sets of second signals.

[0124] like Figure 6 As shown, a set of estimation results for multiple channel parameters is obtained based on the first signal, and different channel parameters have different correlation levels.

[0125] For example, if the first indication information indicates level 1, it means that, with respect to the first channel parameters, the first signal is associated with all second signals across multiple resource ranges (or expressed as a global association); or,

[0126] If the first indication information indicates level 2, it indicates that, regarding the first channel parameters, the first signal and multiple sets of second signals have a grouped correlation relationship.

[0127] The first AI unit can be used to obtain a set of estimation results for multiple channel parameters based on the first signal, and different channel parameters can have different correlation levels.

[0128] For example, for a terminal, one possible configuration is that the association level for channel parameter 1 is level 1 and the association level for channel parameter 2 is level 2. For channel parameters with an association level of level 2, a target association relationship can be configured.

[0129] The effective resource range may include at least one of a time domain range, a frequency domain range, and a spatial domain range. For example, the effective resource range may be one of the multiple resource ranges.

[0130] Optionally, the second indication information includes at least one of the following:

[0131] The resource intervals of the multiple resource ranges;

[0132] The starting resource identifier for each of the plurality of resource ranges;

[0133] The end resource identifier of each of the plurality of resource ranges;

[0134] The number of resources included in the multiple resource ranges.

[0135] In one implementation, the second indication information may include resource intervals for the plurality of resource ranges. The correlation between the first signal and multiple sets of second signals can be described by the resource intervals of the second signals for each resource range, which is particularly suitable for scenarios where the resource intervals of the second signals for each resource range are the same (e.g., ...). Figure 5(As shown). For example, resource interval {10} indicates that the first group of first channel parameters obtained based on the first signal is associated with the second signal in the range of the first resource to the 10th resource; the second group of first channel parameters obtained based on the first signal is associated with the second signal in the range of the 11th resource to the 20th resource; the third group of first channel parameters obtained based on the first signal is associated with the second signal in the range of the 21st resource to the 30th resource, and so on.

[0136] In one embodiment, the second indication information may include a starting resource identifier (or expressed as a starting resource flag) for each of the plurality of resource ranges; and an ending resource identifier (or expressed as an ending resource flag) for each of the plurality of resource ranges. The association between the first signal and multiple sets of second signals can be described using multiple {starting resource identifiers, ending resource identifiers}, which is particularly suitable for situations where resource intervals are not fixed (e.g., ...). Figure 7 (As shown). Taking time-domain resources as an example, for instance, {time slot 1, time slot 20}, {time slot 21, time slot 30}, and {time slot 31, time slot 40} describe three sets of first signals. This indicates that the first set of first channel parameters obtained based on the first signals are associated with the second signals from time slot 1 to time slot 20, the second set of first channel parameters obtained based on the first signals are associated with the second signals from time slot 21 to time slot 30, and the third set of first channel parameters obtained based on the first signals are associated with the second signals from time slot 31 to time slot 40.

[0137] In one embodiment, the second indication information may include the number of resources contained in the plurality of resource ranges. The association between the first signal and multiple sets of second signals can be described by the number of resources contained in the second signal of each resource range. For example, the resource number {20, 10, 10} describes 3 sets of first signals, indicating that the first set of first channel parameters obtained based on the first signal is associated with the second signals in the range of resources 1 to 20, the second set of first channel parameters obtained based on the first signal is associated with the second signals in the range of resources 21 to 30, and the third set of first channel parameters obtained based on the first signal is associated with the second signals in the range of resources 31 to 40.

[0138] Optionally, the method further includes:

[0139] The terminal sends first capability information to the network-side device;

[0140] The first capability information is used to indicate at least one of the following:

[0141] Does the terminal support being configured with the target association relationship?

[0142] The terminal supports the type of the first signal corresponding to the target association relationship;

[0143] The type of the second signal corresponding to the target association relationship supported by the terminal;

[0144] The terminal supports the channel parameters corresponding to the target association relationship;

[0145] The terminal supports parameter information of the target association relationship;

[0146] The terminal supports the first AI unit corresponding to the target association relationship.

[0147] Whether the terminal supports being configured with the target association can also be expressed as whether the terminal supports the target association.

[0148] In one embodiment, the parameter information of the target association supported by the terminal may include: the number of the at least one resource range, that is, the number of divided resource ranges.

[0149] It should be noted that the reporting of the first capability information can be triggered by the terminal receiving capability query information, or it can be reported proactively by the terminal.

[0150] In this embodiment, the terminal sends first capability information to the network-side device, thereby enabling the network-side device to know the terminal's capabilities in supporting the target association, which facilitates the network-side device in configuring the terminal to match its capabilities in terms of channel estimation.

[0151] Optionally, before the terminal sends the first capability information to the network-side device, the method further includes:

[0152] The terminal receives capability query information sent by the network-side device, and the capability query information is used to query the capabilities corresponding to the target association.

[0153] It should be noted that the capability query information can be used to query whether the terminal supports target association, what type of first signal and what type of second signal support the target association with respect to what type of channel parameters, the specific parameters of the target association supported by the terminal, and the identifier of the first AI unit related to the target association, etc.

[0154] In this embodiment, the terminal receives capability query information sent by the network-side device and sends first capability information to the network-side device, thereby enabling the terminal to report the target association capability supported by the terminal based on the query request of the network-side device.

[0155] Optionally, the method further includes:

[0156] The terminal sends first auxiliary information to the network-side device;

[0157] The first auxiliary information includes at least one of the following:

[0158] The terminal's mobility information; the terminal's status information.

[0159] The mobility information of the terminal can be used to describe the mobility status of the terminal. For example, the mobility information of the terminal may include the terminal's speed or activity range level, etc.

[0160] The terminal's status information can be used to describe the terminal's status. For example, the terminal's status information may include remaining battery power, available computing power, level of busy or idle status, main business mode, etc.

[0161] In this embodiment, the terminal sends first auxiliary information to the network-side device, so that the network-side device can determine a target association relationship that matches the mobility information and / or the state information of the terminal based on the first auxiliary information, configure the target association relationship for the terminal, and enable the terminal to perform channel estimation based on the target association relationship.

[0162] Optionally, the terminal performs channel estimation based on the first information, including:

[0163] The terminal obtains multiple sets of estimation results or multiple sets of prediction results of the first signal with respect to the first channel parameters based on the first AI unit;

[0164] Based on the first information and the multiple sets of estimation results or multiple sets of prediction results, the terminal determines a set of estimation results or a set of prediction results corresponding to the second signal of each of the multiple resource ranges;

[0165] The terminal performs channel estimation based on the second signal of each resource range and a corresponding set of estimation results or a set of prediction results.

[0166] Optionally, in one embodiment, the terminal performs channel estimation based on the second signal of each resource range and a corresponding set of estimation results or a set of prediction results, which may include: the terminal inputting the second signal of each resource range and a corresponding set of estimation results into a second AI unit, and the second AI unit outputting the channel estimation result or prediction result corresponding to the second signal; or, the terminal inputting the second signal of each resource range and a corresponding set of prediction results into a second AI unit, and the second AI unit outputting the channel estimation result or prediction result corresponding to the second signal.

[0167] In this implementation, channel estimation can be performed using the target correlation, which can improve the accuracy of channel estimation.

[0168] The following examples will provide further explanation:

[0169] Example 1:

[0170] like Figure 8 As shown, the channel estimation method includes the following process:

[0171] (1) The network-side device sends capability query information to the terminal. The capability query information is used to query whether the terminal supports packet association between the first signal and the second signal, which first signals and which second signals support packet association with respect to which channel parameters, the specific parameters of the packet association supported by the terminal, and the identifiers of the first AI units related to the packet association.

[0172] (2) The terminal reports the first capability information to the network-side device. The reporting of the first capability information can be triggered by the terminal receiving capability query information or it can be actively reported by the terminal.

[0173] The first capability information includes at least one of the following:

[0174] Does the terminal support group association between the first and second signals?

[0175] Which first signals and which second signals the terminal supports for packet association with respect to which channel parameters;

[0176] The specific parameters of the group association supported by the terminal, such as how many groups of group association are supported, that is, the second signal can be divided into several groups to be associated with the first signal in different ways;

[0177] The first AI unit identifier related to the group association supported by the terminal.

[0178] (3) The terminal reports first auxiliary information to the network-side device. The first auxiliary information is used by the network-side device to obtain the association relationship that best matches the current scenario. The first auxiliary information includes:

[0179] Terminal mobility information, such as speed and activity range level;

[0180] Terminal status information, such as remaining battery power, available computing power, level of busy or idle status, and main business mode.

[0181] (4) The network-side device sends first information to the terminal, the first information being used to describe the grouping relationship between the first signal and multiple groups of second signals.

[0182] The grouping correlation between the first signal and the multiple groups of second signals refers to the different correlation relationships between the first signal and the multiple groups of second signals.

[0183] The grouping association is established within a specific resource scope, for example:

[0184] Within a specific time domain resource range, such as the interval between two consecutive transmissions of the first signal, or within one period of a periodically transmitted first signal;

[0185] Within a specific frequency domain resource range;

[0186] Within a specific airspace resource range, such as within a specific set of antennas or ports.

[0187] The first signal may include at least one of the following: TRS, CSI-RS, SSB, and the second signal may include at least one of the following: DMRS, TRS, CSI-RS.

[0188] For example, the first signal and the second signal can be any combination of the following:

[0189] {The first signal is SSB, the second signal is DMRS};

[0190] {The first signal is SSB, the second signal is TRS};

[0191] {The first signal is SSB, and the second signal is CSI-RS};

[0192] {The first signal is TRS, the second signal is DMRS};

[0193] {The first signal is TRS, and the second signal is CSI-RS};

[0194] {The first signal is CSI-RS, and the second signal is DMRS}.

[0195] The CSI-RS can be: a CSI-RS for beam management, or a CSI-RS for CSI acquisition; the DMRS can be a DMRS on the PDSCH, or a DMRS on the PDCCH.

[0196] In the grouping correlation relationship between the first signal and multiple groups of second signals, the correlation refers to having the same or similar channel parameters. The channel parameters include at least one of the following: delay spread, average delay, Doppler spread, Doppler offset, average gain, spatial RX parameter, spatial TX parameter, etc.

[0197] The grouping correlation between the first signal and multiple sets of second signals is associated with a first AI unit. The first AI unit is used to input the first signal or a first channel estimation result obtained based on the first signal, and output multiple sets of channel parameter estimation results. Each set of channel parameter estimation results is associated with a set of second signals. The terminal can obtain a second channel estimation result based on the second signal and its associated channel parameter estimation result.

[0198] Taking the first signal as TRS and the second signal as DMRS as an example, Figure 4 The description refers to the estimation results of multiple sets of channel parameters obtained based on TRS. Figure 5 It describes the specific relationships.

[0199] It should be noted that the first signal and the second signal have different correlation relationships under different channel parameters. Different correlation levels can be assigned to different channel parameters, for example:

[0200]

[0201] like Figure 6 As shown, the first AI unit can be used to obtain a set of estimation results for multiple channel parameters based on the first signal, and different channel parameters have different correlation levels.

[0202] For example, one possible configuration is that the association level for channel parameter 1 is level 1, and the association level for channel parameter 2 is level 2. For channel parameters with an association level of level 2, it is necessary to further determine how they are grouped and associated. Assuming that the association level of the first signal and the second signal with respect to the first channel parameter is level 2, the grouping association relationship between the first signal and multiple groups of second signals can be described by any of the following:

[0203] A. The grouping relationship between the first signal and multiple groups of second signals can be described by the resource interval of each group of second signals. For example, this can be applied to scenarios where the resource interval of each group of second signals is the same (e.g., Figure 5 (As shown). For example, resource interval {10} indicates that the first group of first channel parameters obtained based on the first signal is associated with the second signal in the range of the first resource to the 10th resource; the second group of first channel parameters obtained based on the first signal is associated with the second signal in the range of the 11th resource to the 20th resource; the third group of first channel parameters obtained based on the first signal is associated with the second signal in the range of the 21st resource to the 30th resource, and so on.

[0204] B. The grouping relationship between the first signal and multiple sets of second signals can be described using multiple {start resource flags, end resource flags}. For example, this can be applied to situations where the resource interval is not fixed (e.g., ...). Figure 7(As shown). Taking time-domain resources as an example, for instance, {time slot 1, time slot 20}, {time slot 21, time slot 30}, and {time slot 31, time slot 40} describe three sets of first signals. This indicates that the first set of first channel parameters obtained based on the first signals are associated with the second signals from time slot 1 to time slot 20, the second set of first channel parameters obtained based on the first signals are associated with the second signals from time slot 21 to time slot 30, and the third set of first channel parameters obtained based on the first signals are associated with the second signals from time slot 31 to time slot 40.

[0205] C. The grouping relationship between the first signal and multiple groups of second signals can be described by the number of resources contained in each group of second signals. For example, the number of resources {20, 10, 10} describes 3 groups of first signals, indicating that the first group of first channel parameters obtained based on the first signal is associated with the second signals in the range of resources 1 to 20, the second group of first channel parameters obtained based on the first signal is associated with the second signals in the range of resources 21 to 30, and the third group of first channel parameters obtained based on the first signal is associated with the second signals in the range of resources 31 to 40.

[0206] In one implementation, the first information includes at least one of the following:

[0207] The first indication information is used to indicate the association level between the first signal and the second signal, that is, which channel parameters the first signal and the second signal are globally associated with, and which channel parameters are group-associated with.

[0208] The second indication information is descriptive information used to indicate the grouping relationship between the first signal and the second signal with respect to the first channel parameters;

[0209] The effective resource range of the grouping correlation between the first signal and multiple groups of second signals (i.e., the effective resource range of the target correlation) includes at least one of the following: time domain range, frequency domain range, and spatial domain range.

[0210] The identifier of the first AI unit, which is used to output multiple sets of channel parameters based on the first signal, and each set of channel parameters is associated with a set of second AI units.

[0211] This application implements a novel method for configuring the correlation between signals. It proposes predicting channel parameters based on AI estimation results without changing the resource range where the QCL (Quick Channel Registry) is effective. The predicted channel parameters can avoid signal mismatch between two QCLs, prevent channel estimation degradation, and thus improve throughput. Especially in high-speed, high-latency, and high-port scenarios, this application can achieve even higher gains.

[0212] See Figure 9 , Figure 9This is a flowchart of a channel estimation method provided in an embodiment of this application, such as... Figure 9 As shown, the channel estimation method includes the following steps:

[0213] Step 201: The network-side device sends first information to the terminal. The first information is used to indicate the target association relationship. The target association relationship is the association relationship between the first signal and multiple sets of second signals. The multiple sets of second signals correspond one-to-one with multiple resource ranges.

[0214] Optionally, the target association is associated with channel parameters, and / or the target association is set with an effective resource range.

[0215] Optionally, the target correlation relationship is the correlation relationship between multiple sets of estimation results of the first signal with respect to the first channel parameters and the multiple sets of second signals, wherein the multiple sets of estimation results correspond one-to-one with the multiple sets of second signals; or,

[0216] The target correlation relationship is the correlation between multiple sets of prediction results of the first signal with respect to the first channel parameters and the multiple sets of second signals, wherein the multiple sets of prediction results correspond one-to-one with the multiple sets of second signals.

[0217] Optionally, the first information includes at least one of the following:

[0218] First indication information, the first indication information is used to indicate that the first signal and the second signal have the target correlation relationship with respect to the first channel parameter;

[0219] The second indication information is used to indicate the correlation between multiple sets of estimation results or multiple sets of prediction results of the first signal with respect to the first channel parameters and the multiple sets of second signals, respectively.

[0220] The scope of resources for which the target association is effective;

[0221] The identifier of the first artificial intelligence (AI) unit, which is used to output multiple sets of estimation results or multiple sets of prediction results of the first signal with respect to the first channel parameters based on the first signal.

[0222] Optionally, the second indication information includes at least one of the following:

[0223] The resource intervals of the multiple resource ranges;

[0224] The starting resource identifier for each of the plurality of resource ranges;

[0225] The end resource identifier of each of the plurality of resource ranges;

[0226] The number of resources included in the multiple resource ranges.

[0227] Optionally, the method further includes:

[0228] The network-side device receives the first capability information sent by the terminal;

[0229] The first capability information is used to indicate at least one of the following:

[0230] Does the terminal support being configured with the target association relationship?

[0231] The terminal supports the type of the first signal corresponding to the target association relationship;

[0232] The type of the second signal corresponding to the target association relationship supported by the terminal;

[0233] The terminal supports the channel parameters corresponding to the target association relationship;

[0234] The terminal supports parameter information of the target association relationship;

[0235] The terminal supports the first AI unit corresponding to the target association relationship.

[0236] Optionally, before the network-side device receives the first capability information sent by the terminal, the method further includes:

[0237] The network-side device sends capability query information to the terminal, and the capability query information is used to query the capabilities corresponding to the association with the target.

[0238] Optionally, the method further includes:

[0239] The network-side device receives the first auxiliary information sent by the terminal;

[0240] The network-side device determines the first information based on the first auxiliary information;

[0241] The first auxiliary information includes at least one of the following:

[0242] The terminal's mobility information; the terminal's status information.

[0243] It should be noted that this embodiment is used as a reference for... Figure 3 The implementation methods of the network-side devices shown in the embodiments can be found in the following examples. Figure 3 The related descriptions of the embodiments shown are not repeated here to avoid repetition.

[0244] The channel estimation method provided in this application can be executed by a channel estimation device. This application uses the example of a channel estimation device executing the channel estimation method to illustrate the channel estimation device provided in this application.

[0245] This application provides a channel estimation device. As an example, the channel estimation device can be a communication device or a component within a communication device, such as a chip. The communication device can be a terminal, a network-side device, or a server, etc. Exemplarily, the terminal can be, but is not limited to, the type of terminal 11 listed above, and the network-side device can be, but is not limited to, the type of network-side device 12 listed above. This application does not impose specific limitations.

[0246] The channel estimation 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, etc., such as central processing units (CPUs), microprocessors, digital signal processors (DSPs), artificial intelligence (AI) processors, graphics processing units (GPUs), application-specific integrated circuits (ASICs), network processors (NPs), field-programmable gate arrays (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.

[0247] For details, see Figure 10 When the channel estimation device is a terminal or a component within a terminal, the channel estimation device 300 includes:

[0248] The receiving module 301 is used to receive first information sent by the network-side device. The first information is used to indicate a target association relationship. The target association relationship is the association relationship between a first signal and multiple sets of second signals. The multiple sets of second signals correspond one-to-one with multiple resource ranges.

[0249] Processing module 302 is used to perform channel estimation based on the first information.

[0250] Optionally, the target association is associated with channel parameters, and / or the target association is set with an effective resource range.

[0251] Optionally, the target correlation relationship is the correlation relationship between multiple sets of estimation results of the first signal with respect to the first channel parameters and the multiple sets of second signals, wherein the multiple sets of estimation results correspond one-to-one with the multiple sets of second signals; or,

[0252] The target correlation relationship is the correlation between multiple sets of prediction results of the first signal with respect to the first channel parameters and the multiple sets of second signals, wherein the multiple sets of prediction results correspond one-to-one with the multiple sets of second signals.

[0253] Optionally, the first information includes at least one of the following:

[0254] First indication information, the first indication information is used to indicate that the first signal and the second signal have the target correlation relationship with respect to the first channel parameter;

[0255] The second indication information is used to indicate the correlation between multiple sets of estimation results or multiple sets of prediction results of the first signal with respect to the first channel parameters and the multiple sets of second signals, respectively.

[0256] The scope of resources for which the target association is effective;

[0257] The identifier of the first artificial intelligence (AI) unit, which is used to output multiple sets of estimation results or multiple sets of prediction results of the first signal with respect to the first channel parameters based on the first signal.

[0258] Optionally, the second indication information includes at least one of the following:

[0259] The resource intervals of the multiple resource ranges;

[0260] The starting resource identifier for each of the plurality of resource ranges;

[0261] The end resource identifier of each of the plurality of resource ranges;

[0262] The number of resources included in the multiple resource ranges.

[0263] Optionally, the device further includes:

[0264] The sending module is used to send first capability information to the network-side device;

[0265] The first capability information is used to indicate at least one of the following:

[0266] Does the terminal support being configured with the target association relationship?

[0267] The terminal supports the type of the first signal corresponding to the target association relationship;

[0268] The type of the second signal corresponding to the target association relationship supported by the terminal;

[0269] The terminal supports the channel parameters corresponding to the target association relationship;

[0270] The terminal supports parameter information of the target association relationship;

[0271] The terminal supports the first AI unit corresponding to the target association relationship.

[0272] Optionally, the receiving module is further configured to:

[0273] The system receives capability query information sent by the network-side device, which is used to query the capabilities associated with the target.

[0274] Optionally, the device further includes:

[0275] The sending module is used to send first auxiliary information to the network-side device;

[0276] The first auxiliary information includes at least one of the following:

[0277] The terminal's mobility information; the terminal's status information.

[0278] Optionally, the processing module is specifically used for:

[0279] Based on the first AI unit, multiple sets of estimation results or multiple sets of prediction results of the first signal with respect to the first channel parameters are obtained;

[0280] Based on the first information and the multiple sets of estimation results or multiple sets of prediction results, determine a set of estimation results or a set of prediction results corresponding to the second signal of each of the multiple resource ranges;

[0281] Channel estimation is performed based on the second signal for each resource range and a corresponding set of estimation results or a set of prediction results.

[0282] See Figure 11 When the channel estimation device is a network-side device or a component within a network-side device, the channel estimation device 400 includes:

[0283] The sending module 401 is used to send first information to the terminal. The first information is used to indicate a target association relationship. The target association relationship is the association relationship between a first signal and multiple sets of second signals. The multiple sets of second signals correspond one-to-one with multiple resource ranges.

[0284] Optionally, the target association is associated with channel parameters, and / or the target association is set with an effective resource range.

[0285] Optionally, the target correlation relationship is the correlation relationship between multiple sets of estimation results of the first signal with respect to the first channel parameters and the multiple sets of second signals, wherein the multiple sets of estimation results correspond one-to-one with the multiple sets of second signals; or,

[0286] The target correlation relationship is the correlation between multiple sets of prediction results of the first signal with respect to the first channel parameters and the multiple sets of second signals, wherein the multiple sets of prediction results correspond one-to-one with the multiple sets of second signals.

[0287] Optionally, the first information includes at least one of the following:

[0288] First indication information, the first indication information is used to indicate that the first signal and the second signal have the target correlation relationship with respect to the first channel parameter;

[0289] The second indication information is used to indicate the correlation between multiple sets of estimation results or multiple sets of prediction results of the first signal with respect to the first channel parameters and the multiple sets of second signals, respectively.

[0290] The scope of resources for which the target association is effective;

[0291] The identifier of the first artificial intelligence (AI) unit, which is used to output multiple sets of estimation results or multiple sets of prediction results of the first signal with respect to the first channel parameters based on the first signal.

[0292] Optionally, the second indication information includes at least one of the following:

[0293] The resource intervals of the multiple resource ranges;

[0294] The starting resource identifier for each of the plurality of resource ranges;

[0295] The end resource identifier of each of the plurality of resource ranges;

[0296] The number of resources included in the multiple resource ranges.

[0297] Optionally, the device further includes:

[0298] The receiving module is used to receive the first capability information sent by the terminal;

[0299] The first capability information is used to indicate at least one of the following:

[0300] Does the terminal support being configured with the target association relationship?

[0301] The terminal supports the type of the first signal corresponding to the target association relationship;

[0302] The type of the second signal corresponding to the target association relationship supported by the terminal;

[0303] The terminal supports the channel parameters corresponding to the target association relationship;

[0304] The terminal supports parameter information of the target association relationship;

[0305] The terminal supports the first AI unit corresponding to the target association relationship.

[0306] Optionally, the sending module is further configured to:

[0307] Send capability query information to the terminal, the capability query information being used to query the capabilities corresponding to the association with the target.

[0308] Optionally, the receiving module in the device is further configured to receive first auxiliary information sent by the terminal;

[0309] The network-side device determines the first information based on the first auxiliary information;

[0310] The first auxiliary information includes at least one of the following:

[0311] The terminal's mobility information; the terminal's status information.

[0312] The channel estimation apparatus provided in this application can improve the accuracy of channel estimation.

[0313] The channel estimation device provided in this application embodiment can achieve... Figure 3 and Figure 9 The various processes implemented in the method embodiments achieve the same technical effect, and will not be described again here to avoid repetition.

[0314] like Figure 12 As shown in the illustration, this application also provides a communication device 500, including a processor 501 and a memory 502. The memory 502 stores programs or instructions that can run on the processor 501. For example, when the communication device 500 is a terminal, the program or instructions executed by the processor 501 implement the various steps of the channel estimation method embodiment described above, and achieve the same technical effect. When the communication device 500 is a network-side device, the program or instructions executed by the processor 501 implement the various steps of the channel estimation method embodiment described above, and achieve the same technical effect. To avoid repetition, further details are omitted here.

[0315] This application embodiment 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, for example... Figure 3 The steps in the method embodiment shown are illustrated. This terminal embodiment corresponds to the above-described terminal-side method embodiment. 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 can be... Figure 10 The channel estimation device shown. Specifically, Figure 13 A schematic diagram of the hardware structure of a terminal to implement an embodiment of this application.

[0316] The terminal 600 includes, but is not limited to, at least some of the following components: radio frequency unit 601, network module 602, audio output unit 603, input unit 604, sensor 605, display unit 606, user input unit 607, interface unit 608, memory 609, and processor 610.

[0317] Those skilled in the art will understand that the terminal 600 may also include a power supply (such as a battery) for supplying power to various components. The power supply may be logically connected to the processor 610 through a power management system, thereby enabling functions such as managing charging, discharging, and power consumption through the power management system. Figure 13 The terminal structure shown 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.

[0318] It should be understood that, in this embodiment, the input unit 604 may include a graphics processor 6041 and a microphone 6042. The graphics processor 6041 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 606 may include a display panel 6061, which may be configured in the form of a liquid crystal display, an organic light-emitting diode, or the like. The user input unit 607 includes at least one of a touch panel 6071 and other input devices 6072. The touch panel 6071 is also called a touch screen. The touch panel 6071 may include two parts: a touch detection device and a touch controller. Other input devices 6072 may include, but are not limited to, a physical keyboard, function keys (such as volume control buttons, power buttons, etc.), a trackball, a mouse, and a joystick, which will not be described in detail here.

[0319] In this embodiment, after receiving downlink data from the network-side device, the radio frequency unit 601 can transmit it to the processor 610 for processing; in addition, the radio frequency unit 601 can send uplink data to the network-side device. Typically, the radio frequency unit 601 includes, but is not limited to, antennas, amplifiers, transceivers, couplers, low-noise amplifiers, duplexers, etc.

[0320] The memory 609 can be used to store software programs or instructions, as well as various data. The memory 609 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 609 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 609 in this embodiment includes, but is not limited to, these and any other suitable types of memory.

[0321] Processor 610 may include one or more processing units; optionally, processor 610 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 processor 610.

[0322] The radio frequency unit 601 is used to: receive first information sent by the network side device, the first information being used to indicate a target association relationship, the target association relationship being the association relationship between a first signal and multiple sets of second signals, the multiple sets of second signals corresponding one-to-one with multiple resource ranges;

[0323] Processor 610 is used to perform channel estimation based on the first information.

[0324] Optionally, the target association is associated with channel parameters, and / or the target association is set with an effective resource range.

[0325] Optionally, the target correlation relationship is the correlation relationship between multiple sets of estimation results of the first signal with respect to the first channel parameters and the multiple sets of second signals, wherein the multiple sets of estimation results correspond one-to-one with the multiple sets of second signals; or,

[0326] The target correlation relationship is the correlation between multiple sets of prediction results of the first signal with respect to the first channel parameters and the multiple sets of second signals, wherein the multiple sets of prediction results correspond one-to-one with the multiple sets of second signals.

[0327] Optionally, the first information includes at least one of the following:

[0328] First indication information, the first indication information is used to indicate that the first signal and the second signal have the target correlation relationship with respect to the first channel parameter;

[0329] The second indication information is used to indicate the correlation between multiple sets of estimation results or multiple sets of prediction results of the first signal with respect to the first channel parameters and the multiple sets of second signals, respectively.

[0330] The scope of resources for which the target association is effective;

[0331] The identifier of the first artificial intelligence (AI) unit, which is used to output multiple sets of estimation results or multiple sets of prediction results of the first signal with respect to the first channel parameters based on the first signal.

[0332] Optionally, the second indication information includes at least one of the following:

[0333] The resource intervals of the multiple resource ranges;

[0334] The starting resource identifier for each of the plurality of resource ranges;

[0335] The end resource identifier of each of the plurality of resource ranges;

[0336] The number of resources included in the multiple resource ranges.

[0337] Optionally, the radio frequency unit 601 is further configured to: send first capability information to the network-side device;

[0338] The first capability information is used to indicate at least one of the following:

[0339] Does the terminal support being configured with the target association relationship?

[0340] The terminal supports the type of the first signal corresponding to the target association relationship;

[0341] The type of the second signal corresponding to the target association relationship supported by the terminal;

[0342] The terminal supports the channel parameters corresponding to the target association relationship;

[0343] The terminal supports parameter information of the target association relationship;

[0344] The terminal supports the first AI unit corresponding to the target association relationship.

[0345] Optionally, the radio frequency unit 601 is further configured to:

[0346] The system receives capability query information sent by the network-side device, which is used to query the capabilities associated with the target.

[0347] Optionally, the radio frequency unit 601 is further configured to: send first auxiliary information to the network-side device;

[0348] The first auxiliary information includes at least one of the following:

[0349] The terminal's mobility information; the terminal's status information.

[0350] Optionally, the processor 610 is specifically used for:

[0351] Based on the first AI unit, multiple sets of estimation results or multiple sets of prediction results of the first signal with respect to the first channel parameters are obtained;

[0352] Based on the first information and the multiple sets of estimation results or multiple sets of prediction results, determine a set of estimation results or a set of prediction results corresponding to the second signal of each of the multiple resource ranges;

[0353] Channel estimation is performed based on the second signal for each resource range and a corresponding set of estimation results or a set of prediction results.

[0354] It is understood that the implementation process of each implementation method mentioned in this embodiment can be referred to the method embodiment. Figure 3The relevant descriptions and the achievement of the same or corresponding technical effects will not be repeated here to avoid duplication.

[0355] This application embodiment also provides a network-side device, 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, for example... Figure 9 The steps of the method embodiment shown are illustrated. This network-side device embodiment corresponds to the above-described network-side device method embodiment. All implementation processes and methods of the above-described method embodiments can be applied to this network-side device embodiment and can achieve the same technical effect.

[0356] Specifically, embodiments of this application also provide a network-side device, which can be... Figure 11 The channel estimation device shown. (As shown in the image) Figure 14 As shown, the network-side device 700 includes: an antenna 701, a radio frequency (RF) device 702, a baseband device 703, a processor 704, and a memory 705. The antenna 701 is connected to the RF device 702. In the uplink direction, the RF device 702 receives information through the antenna 701 and transmits the received information to the baseband device 703 for processing. In the downlink direction, the baseband device 703 processes the information to be transmitted and sends it to the RF device 702. The RF device 702 processes the received information and transmits it through the antenna 701.

[0357] The method executed by the network-side device in the above embodiments can be implemented in the baseband device 703, which includes a baseband processor.

[0358] The baseband device 703 may, for example, include at least one baseband board on which multiple chips are disposed, such as... Figure 14 As shown, one of the chips is, for example, a baseband processor, which is connected to the memory 705 via a bus interface to call the program or instructions in the memory 705 to execute the network-side device operations shown in the above method embodiments.

[0359] The network-side device may also include a network interface 706, such as a Common Public Radio Interface (CPRI).

[0360] The radio frequency device 702 is used to: send first information to the terminal, the first information being used to indicate a target association relationship, the target association relationship being the association relationship between a first signal and multiple sets of second signals, the multiple sets of second signals corresponding one-to-one with multiple resource ranges.

[0361] Furthermore, the network-side device 700 in this application embodiment also includes: a program or instructions stored in a memory 705 and executable on a processor 704, wherein the processor 704 calls the program or instructions in the memory 705 to execute. Figure 7 The methods executed by each module shown achieve the same technical effect, and to avoid repetition, they will not be described in detail here.

[0362] Specifically, embodiments of this application also provide a network-side device. For example... Figure 15 As shown, the network-side device 800 includes: a processor 801, a network interface 802, and a memory 803. This network-side device can be... Figure 11 The channel estimation device shown is illustrated. The network interface 802 is, for example, a common public radio interface (CPRI).

[0363] The network interface 802 is used to send first information to the terminal, the first information being used to indicate a target association relationship, the target association relationship being the association relationship between a first signal and multiple sets of second signals, the multiple sets of second signals corresponding one-to-one with multiple resource ranges.

[0364] Furthermore, the network-side device 800 in this embodiment of the application also includes: a program or instructions stored in a memory 803 and executable on a processor 801, wherein the processor 801 calls the program or instructions in the memory 803 to execute. Figure 11 The methods executed by each module shown achieve the same technical effect, and to avoid repetition, they will not be described in detail here.

[0365] 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 above-described channel estimation method embodiments and achieve the same technical effect. To avoid repetition, they will not be described again here.

[0366] The processor mentioned above is either the processor in the terminal described in the above embodiments or the processor in the network-side device. 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.

[0367] 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 above-described channel estimation method embodiments and can achieve the same technical effect. To avoid repetition, it will not be described again here.

[0368] 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.

[0369] 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 above-described channel estimation method embodiments, and can achieve the same technical effect. To avoid repetition, it will not be described again here.

[0370] This application also provides a wireless communication system, including: a terminal and a network-side device, wherein the terminal can be used to perform the steps of the channel estimation method applied to the terminal as described above, and the network-side device can be used to perform the steps of the channel estimation method applied to the network-side device as described above.

[0371] 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.

[0372] 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 the computer software product includes several instructions to cause the terminal or network-side device to execute the methods described in the various embodiments of this application.

[0373] 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. A channel estimation method, characterized in that, include: The terminal receives first information sent by the network-side device. The first information is used to indicate a target association relationship. The target association relationship is the association relationship between a first signal and multiple sets of second signals. The multiple sets of second signals correspond one-to-one with multiple resource ranges. The terminal performs channel estimation based on the first information.

2. The method according to claim 1, characterized in that, The target association is associated with channel parameters, and / or the target association is set with an effective resource range.

3. The method according to claim 1 or 2, characterized in that, The target correlation relationship is the correlation between multiple sets of estimation results of the first signal with respect to the first channel parameters and the multiple sets of second signals, wherein the multiple sets of estimation results correspond one-to-one with the multiple sets of second signals; or, The target correlation relationship is the correlation between multiple sets of prediction results of the first signal with respect to the first channel parameters and the multiple sets of second signals, wherein the multiple sets of prediction results correspond one-to-one with the multiple sets of second signals.

4. The method according to any one of claims 1-3, characterized in that, The first information includes at least one of the following: First indication information, the first indication information is used to indicate that the first signal and the second signal have the target correlation relationship with respect to the first channel parameter; The second indication information is used to indicate the correlation between multiple sets of estimation results or multiple sets of prediction results of the first signal with respect to the first channel parameters and the multiple sets of second signals, respectively. The scope of resources for which the target association is effective; The identifier of the first artificial intelligence (AI) unit, which is used to output multiple sets of estimation results or multiple sets of prediction results of the first signal with respect to the first channel parameters based on the first signal.

5. The method according to claim 4, characterized in that, The second instruction information includes at least one of the following: The resource intervals of the multiple resource ranges; The starting resource identifier for each of the plurality of resource ranges; The end resource identifier of each of the plurality of resource ranges; The number of resources included in the multiple resource ranges.

6. The method according to any one of claims 1-5, characterized in that, The method further includes: The terminal sends first capability information to the network-side device; The first capability information is used to indicate at least one of the following: Does the terminal support being configured with the target association relationship? The terminal supports the type of the first signal corresponding to the target association relationship; The type of the second signal corresponding to the target association relationship supported by the terminal; The terminal supports the channel parameters corresponding to the target association relationship; The terminal supports parameter information of the target association relationship; The terminal supports the first AI unit corresponding to the target association relationship.

7. The method according to claim 6, characterized in that, Before the terminal sends the first capability information to the network-side device, the method further includes: The terminal receives capability query information sent by the network-side device, and the capability query information is used to query the capabilities corresponding to the target association.

8. The method according to any one of claims 1-7, characterized in that, The method further includes: The terminal sends first auxiliary information to the network-side device; The first auxiliary information includes at least one of the following: The terminal's mobility information; the terminal's status information.

9. The method according to any one of claims 1-8, characterized in that, The terminal performs channel estimation based on the first information, including: The terminal obtains multiple sets of estimation results or multiple sets of prediction results of the first signal with respect to the first channel parameters based on the first AI unit; Based on the first information and the multiple sets of estimation results or multiple sets of prediction results, the terminal determines a set of estimation results or a set of prediction results corresponding to the second signal of each of the multiple resource ranges; The terminal performs channel estimation based on the second signal of each resource range and a corresponding set of estimation results or a set of prediction results.

10. A channel estimation method, characterized in that, include: The network-side device sends first information to the terminal. The first information is used to indicate the target association relationship. The target association relationship is the association relationship between the first signal and multiple sets of second signals. The multiple sets of second signals correspond one-to-one with multiple resource ranges.

11. The method according to claim 10, characterized in that, The target association is associated with channel parameters, and / or the target association is set with an effective resource range.

12. The method according to claim 10 or 11, characterized in that, The target correlation relationship is the correlation between multiple sets of estimation results of the first signal with respect to the first channel parameters and the multiple sets of second signals, wherein the multiple sets of estimation results correspond one-to-one with the multiple sets of second signals; or, The target correlation relationship is the correlation between multiple sets of prediction results of the first signal with respect to the first channel parameters and the multiple sets of second signals, wherein the multiple sets of prediction results correspond one-to-one with the multiple sets of second signals.

13. The method according to any one of claims 10-12, characterized in that, The first information includes at least one of the following: First indication information, the first indication information is used to indicate that the first signal and the second signal have the target correlation relationship with respect to the first channel parameter; The second indication information is used to indicate the correlation between multiple sets of estimation results or multiple sets of prediction results of the first signal with respect to the first channel parameters and the multiple sets of second signals, respectively. The scope of resources for which the target association is effective; The identifier of the first artificial intelligence (AI) unit, which is used to output multiple sets of estimation results or multiple sets of prediction results of the first signal with respect to the first channel parameters based on the first signal.

14. The method according to claim 13, characterized in that, The second instruction information includes at least one of the following: The resource intervals of the multiple resource ranges; The starting resource identifier for each of the plurality of resource ranges; The end resource identifier of each of the plurality of resource ranges; The number of resources included in the multiple resource ranges.

15. The method according to any one of claims 10-14, characterized in that, The method further includes: The network-side device receives the first capability information sent by the terminal; The first capability information is used to indicate at least one of the following: Does the terminal support being configured with the target association relationship? The terminal supports the type of the first signal corresponding to the target association relationship; The type of the second signal corresponding to the target association relationship supported by the terminal; The terminal supports the channel parameters corresponding to the target association relationship; The terminal supports parameter information of the target association relationship; The terminal supports the first AI unit corresponding to the target association relationship.

16. The method according to claim 15, characterized in that, Before the network-side device receives the first capability information sent by the terminal, the method further includes: The network-side device sends capability query information to the terminal, and the capability query information is used to query the capabilities corresponding to the association with the target.

17. The method according to any one of claims 10-16, characterized in that, The method further includes: The network-side device receives the first auxiliary information sent by the terminal; The network-side device determines the first information based on the first auxiliary information; The first auxiliary information includes at least one of the following: The terminal's mobility information; the terminal's status information.

18. A channel estimation device, characterized in that, include: The receiving module is used to receive first information sent by the network-side device. The first information is used to indicate a target association relationship. The target association relationship is the association relationship between a first signal and multiple sets of second signals. The multiple sets of second signals correspond one-to-one with multiple resource ranges. The processing module is used to perform channel estimation based on the first information.

19. The apparatus according to claim 18, characterized in that, The first information includes at least one of the following: First indication information, the first indication information is used to indicate that the first signal and the second signal have the target correlation relationship with respect to the first channel parameter; The second indication information is used to indicate the correlation between multiple sets of estimation results or multiple sets of prediction results of the first signal with respect to the first channel parameters and the multiple sets of second signals, respectively. The scope of resources for which the target association is effective; The identifier of the first artificial intelligence (AI) unit, which is used to output multiple sets of estimation results or multiple sets of prediction results of the first signal with respect to the first channel parameters based on the first signal.

20. The apparatus according to claim 18 or 19, characterized in that, The device further includes: The sending module is used to send first capability information to the network-side device; The first capability information is used to indicate at least one of the following: Does the terminal support being configured with the target association relationship? The terminal supports the type of the first signal corresponding to the target association relationship; The type of the second signal corresponding to the target association relationship supported by the terminal; The terminal supports the channel parameters corresponding to the target association relationship; The terminal supports parameter information of the target association relationship; The terminal supports the first AI unit corresponding to the target association relationship.

21. A channel estimation device, characterized in that, include: The sending module is used to send first information to the terminal. The first information is used to indicate a target association relationship. The target association relationship is the association relationship between a first signal and multiple sets of second signals. The multiple sets of second signals correspond one-to-one with multiple resource ranges.

22. The apparatus according to claim 21, characterized in that, The first information includes at least one of the following: First indication information, the first indication information is used to indicate that the first signal and the second signal have the target correlation relationship with respect to the first channel parameter; The second indication information is used to indicate the correlation between multiple sets of estimation results or multiple sets of prediction results of the first signal with respect to the first channel parameters and the multiple sets of second signals, respectively. The scope of resources for which the target association is effective; The identifier of the first artificial intelligence (AI) unit, which is used to output multiple sets of estimation results or multiple sets of prediction results of the first signal with respect to the first channel parameters based on the first signal.

23. The apparatus according to claim 21 or 22, characterized in that, The device further includes: The receiving module is used to receive the first capability information sent by the terminal; The first capability information is used to indicate at least one of the following: Does the terminal support being configured with the target association relationship? The terminal supports the type of the first signal corresponding to the target association relationship; The type of the second signal corresponding to the target association relationship supported by the terminal; The terminal supports the channel parameters corresponding to the target association relationship; The terminal supports parameter information of the target association relationship; The terminal supports the first AI unit corresponding to the target association relationship.

24. A terminal, characterized in that, 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 channel estimation method as described in any one of claims 1 to 9.

25. A network-side device, characterized in that, 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 channel estimation method as described in any one of claims 10 to 17.

26. A readable storage medium, characterized in that, The readable storage medium stores a program or instructions that, when executed by a processor, implement the channel estimation method as described in any one of claims 1 to 9, or implement the steps of the channel estimation method as described in any one of claims 10 to 17.

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