Method and device for reporting channel information in wireless communication node

Abstract

The invention discloses a method and a device for reporting channel information in a node for wireless communication. The first node receives the RS in the first resource set; and sending the first channel information report. The first resource set comprises at least one RS resource used for at least one of channel measurement or interference measurement for reporting the first channel information; the first channel information report occupies M processing resources in a first time domain resource, and M is a positive integer; the M depends on the size of the first time domain resource. According to the method, the total number of the processing resources occupied by channel information reporting is flexibly adjusted in consideration of the size of the time domain resources occupied by the processing resources, the processing resources can be utilized more efficiently, the number of necessary processing resources is reduced as much as possible, and energy consumption is reduced.

Description

[0001] Technical Field This application relates to transmission methods and apparatus in wireless communication systems, and more particularly to schemes and apparatus for channel information reporting in wireless communication systems. Background Technology

[0002] In traditional wireless communication, the UE (User Equipment) calculates CSI (channel state information) by measuring downlink reference signals. The CSI includes, but is not limited to, one or more of CRI (Channel state information-reference signal resource indicator), RI (Rank indicator), PMI (Precoding Matrix indicator), or CQI (Channel quality indicator).

[0003] With the adoption of new technologies, the increase in the number of antennas, the diversification of application scenarios, and the increasing demands on system performance, traditional measurement and reporting methods incur significant redundancy overhead. Therefore, in NR R (release) 18, research on AI (Artificial Intelligence) / ML (Machine Learning) technologies was initiated to explore their impact on system performance and design. Compared to traditional processing methods, AI / ML offers advantages such as training-based and deployment-required features. Furthermore, AI / ML is a key candidate technology for future 6G communications. Once AI / ML functionality is introduced, existing channel information-related measurement mechanisms, generation and / or reporting mechanisms, and related configuration signaling may become inadequate to meet the demands of AI / ML. Summary of the Invention

[0004] The applicant discovered through research that generating a channel information report requires a certain amount of processing resources from the generator. Typically, the transmitting and receiving ends need to have a consistent understanding of the time these processing resources are occupied. Therefore, determining the time these processing resources are occupied is a key issue that needs to be addressed. To address this issue, this application discloses a solution. It should be noted that although many embodiments of this application are geared towards AI / ML, this application is also applicable to other solutions, such as traditional channel information reporting schemes. Furthermore, adopting a unified solution for different scenarios (including but not limited to AI / ML-based schemes and traditional information reporting schemes) helps reduce hardware complexity and cost. Where there is no conflict, the embodiments and features in the embodiments of the first node of this application can be applied to the second node, and vice versa. Where there is no conflict, the embodiments and features in the embodiments of this application can be arbitrarily combined with each other.

[0005] As an example, the interpretation of terms in this application is based on the definitions in the 3GPP specification protocol TS38 series.

[0006] As an example, the interpretation of the terms in this application is based on the definitions in the 3GPP specification protocol TS28 series.

[0007] This application discloses a method used in a first node of wireless communication, characterized by comprising:

[0008] Receive RS in the first resource set;

[0009] Send the first channel information report;

[0010] The first resource set includes at least one RS resource used for at least one of the channel measurement or interference measurement in the first channel information reporting; the first channel information reporting occupies M processing resources in the first time domain resources, where M is a positive integer; and M depends on the size of the first time domain resources.

[0011] As an example, the problem this application aims to solve includes: how to determine the total number of processing resources occupied by channel information reporting.

[0012] As an example, the essence of the above method is that the total number of processing resources occupied by channel information reporting is related to the size of the time-domain resources occupied by the processing resources.

[0013] As an example, the advantages of the above method include: taking into account the size of the time-domain resources occupied by processing resources, flexibly adjusting the total number of processing resources occupied by channel information reporting can make more efficient use of processing resources, minimize the number of necessary processing resources, and reduce energy consumption.

[0014] As an example, the advantages of the above method include ensuring that the sending and receiving ends have a consistent understanding of the processing resource usage.

[0015] As an example, the advantages of the above method include: better adaptability to various application scenarios or terminals.

[0016] As an example, the advantages of the above method include: good flexibility and adaptability.

[0017] As an example, the advantages of the above method include: better adaptability to various processing capabilities.

[0018] As an example, the advantages of the above method include: better adaptability to various different terminal capabilities.

[0019] As an example, the advantages of the above method include: improved accuracy of channel information reporting.

[0020] As one example, the first node is a user equipment.

[0021] As an example, the first node is a relay node.

[0022] According to one aspect of this application, M depends on the size of the first time-domain resource only when a first condition is met; the first condition includes at least one of the first channel information reporting being generated based on inference or the first channel information reporting generating a corresponding first identifier.

[0023] As an example, the advantages of the above method include: better adaptability to various types of channel information reporting, and good flexibility and adaptability.

[0024] As an example, the advantages of the above method include: better adaptability to various processing capabilities, better adaptability to various application scenarios or terminals, and good flexibility and adaptability.

[0025] As an example, the advantages of the above method include improved accuracy of channel information reporting.

[0026] According to one aspect of this application, the generation of the first channel information report corresponds to a first identifier, and the M further depends on the first identifier.

[0027] According to one aspect of this application, when the size of the first time-domain resource is less than a first threshold, M is a first positive integer; when the size of the first time-domain resource is greater than the first threshold, M is a second positive integer; the second positive integer is less than the first positive integer.

[0028] As an example, in the above method, the processing time is longer, but the total number of processing resources required can be less. The advantages include: flexibly adjusting the total number of processing resources used based on the duration of processing time allows for more efficient use of processing resources, minimizing the amount of necessary processing resources and reducing energy consumption.

[0029] According to one aspect of this application, the generation of the first channel information report corresponds to a first identifier, and the first threshold depends on the first identifier.

[0030] As an example, the advantages of the above method include: better adaptability to various application scenarios or terminals.

[0031] As an example, the advantages of the above method include: good flexibility and adaptability.

[0032] As an example, the advantages of the above method include: better adaptability to various processing capabilities.

[0033] As an example, the advantages of the above method include: better adaptability to various different terminal capabilities.

[0034] According to one aspect of this application, the N1 positive integers correspond to N1 size ranges, where N1 is a positive integer greater than 1; the size of the first time-domain resource belongs to a first size range, which is one of the N1 size ranges; and M is a positive integer among the N1 positive integers that corresponds to the first size range.

[0035] According to one aspect of this application, the N integer sets correspond to N identifiers, where N is a positive integer greater than 1; the generation of the first channel information report corresponds to a first identifier, which is one of the N identifiers; and one integer set in the N integer sets corresponding to the first identifier includes the N1 positive integers.

[0036] As an example, the advantages of the above method include: better adaptability to various application scenarios or terminals.

[0037] As an example, the advantages of the above method include: good flexibility and adaptability.

[0038] As an example, the advantages of the above method include: better adaptability to various processing capabilities.

[0039] As an example, the advantages of the above method include: better adaptability to various different terminal capabilities.

[0040] According to one aspect of this application, it is characterized by comprising:

[0041] Receive the first signaling;

[0042] The first channel information reporting is triggered by the first signaling; the first time domain resource starts after the physical layer channel carrying the first signaling, or the first time domain resource starts after the first symbol of the physical layer channel carrying the first signaling.

[0043] According to one aspect of this application, the first time-domain resource begins with the first symbol of the earliest RS time in a first time-set set; the first time-set set includes at least one RS time in the first resource set.

[0044] According to one aspect of this application, the first time-domain resource terminates at the last symbol of the physical layer channel carrying the first channel information report.

[0045] According to one aspect of this application, it is characterized by comprising:

[0046] Receive the first information block;

[0047] The first information block is used to configure the first channel information reporting.

[0048] This application discloses a method used in a second node for wireless communication, characterized by comprising:

[0049] Send RS in the first resource set;

[0050] Receive the first channel information report;

[0051] The first resource set includes at least one RS resource used for at least one of the channel measurement or interference measurement in the first channel information reporting; the first channel information reporting occupies M processing resources in the first time domain resources, where M is a positive integer; and M depends on the size of the first time domain resources.

[0052] In one embodiment, the second node is a base station.

[0053] As one embodiment, the second node includes a base station.

[0054] As one embodiment, the second node includes the core network.

[0055] As one embodiment, the second node includes a base station and a core network.

[0056] In one embodiment, the second node is a user equipment.

[0057] As one example, the second node is a relay node.

[0058] According to one aspect of this application, M depends on the size of the first time-domain resource only when a first condition is met; the first condition includes at least one of the first channel information reporting being generated based on inference or the first channel information reporting generating a corresponding first identifier.

[0059] According to one aspect of this application, the generation of the first channel information report corresponds to a first identifier, and the M further depends on the first identifier.

[0060] According to one aspect of this application, when the size of the first time-domain resource is less than a first threshold, M is a first positive integer; when the size of the first time-domain resource is greater than the first threshold, M is a second positive integer; the second positive integer is less than the first positive integer.

[0061] According to one aspect of this application, the generation of the first channel information report corresponds to a first identifier, and the first threshold depends on the first identifier.

[0062] According to one aspect of this application, the N1 positive integers correspond to N1 size ranges, where N1 is a positive integer greater than 1; the size of the first time-domain resource belongs to a first size range, which is one of the N1 size ranges; and M is a positive integer among the N1 positive integers that corresponds to the first size range.

[0063] According to one aspect of this application, the N integer sets correspond to N identifiers, where N is a positive integer greater than 1; the generation of the first channel information report corresponds to a first identifier, which is one of the N identifiers; and one integer set in the N integer sets corresponding to the first identifier includes the N1 positive integers.

[0064] According to one aspect of this application, it is characterized by comprising:

[0065] Send the first signaling;

[0066] The first channel information reporting is triggered by the first signaling; the first time domain resource starts after the physical layer channel carrying the first signaling, or the first time domain resource starts after the first symbol of the physical layer channel carrying the first signaling.

[0067] According to one aspect of this application, the first time-domain resource begins with the first symbol of the earliest RS time in a first time-set set; the first time-set set includes at least one RS time in the first resource set.

[0068] According to one aspect of this application, the first time-domain resource terminates at the last symbol of the physical layer channel carrying the first channel information report.

[0069] According to one aspect of this application, it is characterized by comprising:

[0070] Send the first information block;

[0071] The first information block is used to configure the first channel information reporting.

[0072] This application discloses a first node used for wireless communication, characterized in that it comprises:

[0073] The first processor receives RS from the first resource set and sends the first channel information report.

[0074] The first resource set includes at least one RS resource used for at least one of the channel measurement or interference measurement in the first channel information reporting; the first channel information reporting occupies M processing resources in the first time domain resources, where M is a positive integer; and M depends on the size of the first time domain resources.

[0075] This application discloses a second node used for wireless communication, characterized in that it comprises:

[0076] The second processor sends RS in the first resource set and receives the first channel information report.

[0077] The first resource set includes at least one RS resource used for at least one of the channel measurement or interference measurement in the first channel information reporting; the first channel information reporting occupies M processing resources in the first time domain resources, where M is a positive integer; and M depends on the size of the first time domain resources.

[0078] As an example, compared with conventional solutions, this application has the following advantages:

[0079] It can utilize processing resources more efficiently;

[0080] Minimize the amount of necessary processing resources, thereby reducing energy consumption;

[0081] This ensures that the transmitting and receiving ends have a consistent understanding of the processing resources occupied by channel information reporting;

[0082] Better adaptable to various application scenarios;

[0083] Better adaptable to various processing capabilities;

[0084] Better adaptable to various different terminals;

[0085] Better adaptable to reporting various types of channel information;

[0086] It has good flexibility;

[0087] It has good adaptability;

[0088] Higher accuracy and real-time performance of channel information;

[0089] Enhanced reliability and robustness;

[0090] Enhanced overall system performance. Attached Figure Description

[0091] Other features, objects, and advantages of this application will become more apparent from the following detailed description of non-limiting embodiments with reference to the accompanying drawings:

[0092] Figure 1 A flowchart of a first channel information reporting according to an embodiment of this application is shown;

[0093] Figure 2 A schematic diagram of a network architecture according to an embodiment of this application is shown;

[0094] Figure 3 A schematic diagram of an embodiment of a wireless protocol architecture for the user plane and control plane according to an embodiment of this application is shown;

[0095] Figure 4 A schematic diagram of a first communication device and a second communication device according to an embodiment of this application is shown;

[0096] Figure 5 The transmission between a first node and a second node according to one embodiment of this application is illustrated;

[0097] Figures 6A-6B Schematic diagrams of a first condition according to an embodiment of this application are shown respectively;

[0098] Figures 7A-7C Schematic diagrams of a first time-domain resource according to an embodiment of this application are shown respectively;

[0099] Figures 8A-8B The diagrams show the total number of processing resources occupied in the first time domain resources for the first channel information reporting according to one embodiment of the present application;

[0100] Figures 9A-9B Schematic diagrams are shown, respectively, illustrating the size of M dependent on the first temporal resource according to one embodiment of this application;

[0101] Figure 10 A schematic diagram illustrating the relationship between a first threshold and a first identifier according to an embodiment of this application is shown;

[0102] Figure 11 A schematic diagram illustrating the relationship between N1 positive integers and a first identifier according to an embodiment of this application is shown;

[0103] Figures 12A-12C The diagrams illustrating the generation of a corresponding first identifier in the first channel information reporting according to one embodiment of this application are shown respectively;

[0104] Figures 13A-13B Schematic diagrams illustrating the deployment of the first operation of the first node according to one embodiment of this application are shown respectively;

[0105] Figure 14 A schematic diagram of the deployment of AI / ML functions in a RAN (Radio Access Network) domain according to an embodiment of this application is shown;

[0106] Figure 15 A schematic diagram illustrating the deployment of AI / ML functions in a UE according to an embodiment of this application is shown;

[0107] Figure 16 A schematic diagram of an artificial intelligence or machine learning-based processing system according to an embodiment of this application is shown;

[0108] Figure 17 A structural block diagram of a processing apparatus for a first node according to an embodiment of this application is shown;

[0109] Figure 18 A structural block diagram of a processing apparatus for a second node according to an embodiment of this application is shown. Detailed Implementation

[0110] The technical solutions of this application will be further described in detail below with reference to the accompanying drawings. It should be noted that, unless otherwise specified, the embodiments and features in the embodiments of this application can be arbitrarily combined with each other. Considering performance, flexibility, complexity, overhead, and compatibility, those skilled in the art are motivated to flexibly combine the embodiments in different drawings without conflict, such as, but not limited to, those in the accompanying drawings. Figure 1 Examples and appendices Figure 5 -Appendix Figure 18 The embodiments in the appendix Figure 5 Examples and appendices Figure 6A -Appendix Figure 18 Examples, etc.

[0111] Example 1

[0112] Example 1 illustrates a flowchart of a first channel information reporting according to an embodiment of this application, as shown in the attached diagram. Figure 1 As shown. In the appendix Figure 1 In the 100 shown, each box represents a step. In particular, the order of the steps in the boxes does not represent a specific temporal relationship between the steps.

[0113] In Embodiment 1, the first node receives RS in the first resource set in step 101; and sends a first channel information report in step 102; wherein, the first resource set includes at least one RS resource used for at least one of channel measurement or interference measurement for the first channel information report; the first channel information report occupies M processing resources in the first time domain resources, where M is a positive integer; and M depends on the size of the first time domain resources.

[0114] As one embodiment, the first resource set includes at least one RS (Reference Signal) resource used for channel measurements in the first channel information reporting.

[0115] As one embodiment, the first resource set includes at least one RS resource used for channel measurements in the first channel information reporting and at least one RS resource used for interference measurements in the first channel information reporting.

[0116] As an example, at least one RS resource used for channel measurement in the first channel information reporting includes one or more of CSI-RS (Channel State Information Reference Signal) resources and synchronization signal resources.

[0117] As an example, any RS resource used for channel measurement in the first channel information reporting is a CSI-RS (Channel State Information Reference Signal) resource or a synchronization signal resource.

[0118] As one embodiment, the synchronization signal resources include at least the resources occupied by the synchronization signal.

[0119] As an example, the synchronization signal resource is an SSB (Synchronization Signal Block).

[0120] As an example, the synchronization signal resource is an SS / PBCH (Synchronization Signal / Physical Broadcast Channel) block resource.

[0121] As an example, at least one RS resource used for interference measurement in the first channel information reporting includes one or more of NZP (non-zero power) CSI-RS resources and CSI-IM (Channel State Information-Interference Measurement) resources for interference measurement.

[0122] As an example, any RS resource used for interference measurement in the first channel information reporting is an NZP CSI-RS resource or a CSI-IM resource for interference measurement.

[0123] As an example, the first channel information reporting simultaneously occupies M processing resources in the first time domain resources.

[0124] As an example, the time that the first channel information is reported to occupy M processing resources in the first time domain resources overlaps.

[0125] As an example, the first channel information report occupies M processing resources in the generator of the first channel information report in the first time domain resources.

[0126] As one embodiment, the first channel information reporting occupies M processing resources in the first time domain resources of the sender of the first channel information reporting.

[0127] As an example, the first channel information reporting occupies M processing resources in the first node in the first time domain resources.

[0128] As an example, the processing resources are different from air interface resources, which include at least one of time domain resources, frequency domain resources, or code domain resources.

[0129] As one embodiment, the M processing resources are among the generators of the first channel information report.

[0130] As an example, the M processing resources are among the senders of the first channel information report.

[0131] As an example, the M processing resources are located in the first node.

[0132] As an example, the first node reports the total number of processing resources in the first node in its capability information.

[0133] As one embodiment, the M processing resources are used to calculate or generate the first channel information report.

[0134] As an example, the M processing resources are used to infer the first channel information reporting.

[0135] As an example, the M processing resources are used to obtain and report the first channel information based on inference.

[0136] As one embodiment, the M processing resources are used for at least one of the processing, calculation, or inference of the first channel information reporting.

[0137] As an example, the M processing resources are used for at least one of processing, computation, or inference.

[0138] As an example, the M processing resources are used for computation.

[0139] As an example, the M processing resources are used for inference.

[0140] As an example, the M processing resources are used for at least addition and multiplication operations.

[0141] As an example, the M processing resources are used for at least convolution operations.

[0142] As one example, the M processing resources belong to one or more processing units.

[0143] As an example, the M processing resources belong to one processing unit.

[0144] As one embodiment, the M processing resources are M processing units.

[0145] As one example, a processing unit includes one or more processing resources.

[0146] Regarding the processing unit described in the above embodiments, some typical but non-limiting implementations are described below:

[0147] As one embodiment, the processing unit is used for at least one of processing, calculation, or reasoning.

[0148] As an example, the processing unit is a CSI processing unit.

[0149] As one embodiment, the processing unit is an AI processing unit (APU).

[0150] As one embodiment, the processing unit is a central processing unit (CPU).

[0151] As an example, the processing unit is a GPU (graphics processing unit).

[0152] As one embodiment, the processing unit is a general-purpose processing unit.

[0153] As one embodiment, the processing unit is a general-purpose graphics processing unit (GPGPU).

[0154] As one embodiment, the first time-domain resource includes one or more symbols.

[0155] As one embodiment, the first time-domain resource includes a plurality of consecutive symbols.

[0156] As one embodiment, the first time-domain resource includes one or more time slots.

[0157] As one example, the first time-domain resource includes one or more time periods.

[0158] As an example, the first time-domain resource includes a time period.

[0159] As an example, the size of the first time-domain resource is the total number of symbols included in the first time-domain resource.

[0160] As an example, the size of the first time domain resource is the time length of the first time domain resource.

[0161] As an example, the size of the first time-domain resource is the total number of time slots in which the first time-domain resource is located.

[0162] As one embodiment, the first time-domain resource includes one or more symbols, and the size of the first time-domain resource is the total number of symbols included in the first time-domain resource.

[0163] As one embodiment, the first time-domain resource includes a plurality of consecutive symbols, and the size of the first time-domain resource is the total number of symbols included in the first time-domain resource.

[0164] As an example, the termination time of the first time-domain resource depends on the time-domain resources occupied by the physical layer channel carrying the first channel information report.

[0165] As an example, the first time-domain resource terminates at the last symbol of the physical layer channel carrying the first channel information report.

[0166] As an example, the first time-domain resource terminates after the last symbol of the physical layer channel carrying the first channel information report.

[0167] As an example, the first time-domain resource terminates at the last symbol of the physical layer channel carrying the first channel information report.

[0168] As an example, the first time-domain resource terminates before the last symbol of the physical layer channel carrying the first channel information report.

[0169] Typically, "after" means "later than".

[0170] Typically, "before" means "earlier than".

[0171] As an example, the size of the first time-domain resource is predefined.

[0172] As an example, the size of the first time-domain resource is configurable.

[0173] As an example, the symbol is a single-carrier symbol.

[0174] As an example, the symbol is a multi-carrier symbol.

[0175] As one example, the time slot includes multiple symbols.

[0176] As one example, the time slot includes 14 symbols.

[0177] As an example, the symbols are obtained by passing the output of the transform precoding through OFDM symbol generation.

[0178] As an example, the multicarrier symbol is an OFDM (Orthogonal Frequency Division Multiplexing) symbol.

[0179] As an example, the multi-carrier symbol is an SC-FDMA (Single Carrier-Frequency Division Multiple Access) symbol.

[0180] As an example, the multicarrier symbol is a DFT-S-OFDM (Discrete Fourier Transform Spread OFDM) symbol.

[0181] As an example, the multi-carrier symbol is an FBMC (Filter Bank Multi Carrier) symbol.

[0182] As one embodiment, the multicarrier symbol includes CP (Cyclic Prefix).

[0183] As an example, the value of M depends on the size of the first time-domain resource.

[0184] As an example, the range of candidate values ​​for M depends on the size of the first time-domain resource.

[0185] As an example, the size of M and the size of the first time-domain resource are mapped.

[0186] As an example, the size of M and the size of the first time-domain resource are in a corresponding relationship.

[0187] As an example, the size of M and the size of the first time-domain resource are functionally related.

[0188] As an example, M depends on a second parameter, the value of which depends on the size of the first time-domain resource.

[0189] Example 2

[0190] Example 2 illustrates a schematic diagram of a network architecture according to an embodiment of this application, as shown in the attached diagram. Figure 2 As shown.

[0191] Appendix Figure 2The network architecture 200 is described. The network architecture 200 is a 5G NR (New Radio) / LTE (Long-Term Evolution) / LTE-A (Long-Term Evolution Advanced) system, or a 5G+ network architecture, or a 6G network architecture, or a network architecture adopted in future evolutions by 3GPP; the network architecture 200 may be referred to as 5GS (5G System) / EPS (Evolved Packet System), or 6GS (6G System); the network architecture 200 includes at least one of UE (User Equipment) 201, RAN (Radio Access Network) 202, core network 210, HSS (Home Subscriber Server) / UDM (Unified Data Management) 220, and Internet service 230. The network architecture 200 can interconnect with other access networks, but these entities / interfaces are not shown for simplicity. As shown, the network architecture 200 provides packet-switched services; however, those skilled in the art will readily understand that the various concepts presented throughout this application can be extended to networks providing circuit-switched services or other cellular networks. The RAN includes node 203. The RAN may also include other nodes 204. Node 203 provides user and control plane protocol termination toward UE 201. Node 203 may be connected to other nodes 204 via an Xn interface (e.g., backhaul) / X2 interface. Node 203 may also be referred to as a base station, base transceiver station, radio base station, radio transceiver, transceiver function, basic service set (BSS), extended service set (ESS), TRP (transmitter-receiver node), or some other suitable term. The core network 210 is a 5GC (5G Core Network) / EPC (Evolved Packet Core), or the core network 210 is a 6GC; node 203 provides UE 201 with an access point to the core network 210.Examples of UE201 include cellular phones, smartphones, Session Initiation Protocol (SIP) phones, laptops, personal digital assistants (PDAs), satellite radios, non-terrestrial base station communications, satellite mobile communications, global positioning systems, multimedia devices, video devices, digital audio players (e.g., MP3 players), cameras, game consoles, drones, aircraft, narrowband IoT devices, machine-type communication devices, land vehicles, automobiles, wearable devices, or any other similar functional devices. Those skilled in the art may also refer to UE201 as a mobile station, subscriber station, mobile unit, subscriber unit, radio unit, remote unit, mobile device, radio device, wireless communication device, remote device, mobile subscriber station, access terminal, mobile terminal, wireless terminal, remote terminal, handheld device, user agent, mobile client, client, or any other suitable term. Node 203 is connected to the core network 210 via an S1 / NG interface. The core network 210 includes an MME (Mobility Management Entity) / AMF (Authentication Management Field) / SMF (Session Management Function) 211, other MMEs / AMFs / SMFs 214, an S-GW (Service Gateway) / UPF (User Plane Function) 212, and a P-GW (Packet Data Network Gateway) / UPF 213. The MME / AMF / SMF 211 is the control node that handles signaling between the UE 201 and the core network 210. Generally, the MME / AMF / SMF 211 provides bearer and connection management. All user IP (Internet Protocol) packets are transmitted through the S-GW / UPF 212, which is itself connected to the P-GW / UPF 213. The P-GW provides UE IP address allocation and other functions. The P-GW / UPF 213 is connected to the Internet service 230. Internet services 230 include operator-compliant Internet protocol services, which may specifically include Internet, intranet, IMS (IP Multimedia Subsystem), and packet switching services.

[0192] As an example, the first node includes the UE201.

[0193] As one embodiment, the second node includes the node 203.

[0194] As one embodiment, the second node includes the core network 210.

[0195] As one embodiment, the second node includes the node 203 and the core network 210.

[0196] As an example, the wireless link between the UE201 and the node203 includes a cellular link.

[0197] As an example, the processing resources described in this application are in the UE201.

[0198] As an example, the second information block is generated in the UE201.

[0199] As an example, the first channel information is generated in the UE201.

[0200] As an example, the sender of the first channel information report includes the UE201.

[0201] As an example, the target receiver for the first channel information reporting includes the node 203.

[0202] As an example, the first information block is generated in node 203.

[0203] As an example, the sender of the first information block includes the node 203.

[0204] As an example, the target recipient of the first information block includes the UE201.

[0205] As an example, the first signaling is generated in node 203.

[0206] As an example, the sender of the first signaling includes the node 203.

[0207] As an example, the target recipient of the first signaling includes the UE201.

[0208] As an example, the RS in the first resource set is generated in node 203.

[0209] As an example, the sender of the RS in the first resource set includes the node 203.

[0210] As an example, the target recipient of the RS in the first resource set includes the UE201.

[0211] Example 3

[0212] Example 3 illustrates a schematic diagram of an embodiment of a wireless protocol architecture for the user plane and control plane according to an embodiment of this application, as shown in the attached diagram. Figure 3 As shown.

[0213] Example 3 illustrates a schematic diagram of an embodiment of a wireless protocol architecture for a user plane and a control plane according to this application, as shown in the attached diagram. Figure 3 As shown. Figure 3 This is a schematic diagram illustrating an embodiment of a radio protocol architecture for the user plane 350 and the control plane 300. Figure 3The radio protocol architecture for the control plane 300 between the first communication node device (UE, gNB, or RSU in V2X) and the second communication node device (gNB, UE, or RSU in V2X), or between two UEs, is illustrated using three layers: Layer 1, Layer 2, and Layer 3. Layer 1 (L1 layer) is the lowest layer and implements various PHY (Physical Layer) signal processing functions. Layer 1 will be referred to as PHY 301 in this document. Layer 2 (L2 layer) 305, above PHY 301, is responsible for the link between the first and second communication node devices, or between two UEs. Layer 2 305 includes the MAC (Medium Access Control) sublayer 302, the RLC (Radio Link Control) sublayer 303, and the PDCP (Packet Data Convergence Protocol) sublayer 304, which terminate at the second communication node device. The PDCP sublayer 304 provides multiplexing between different radio bearers and logical channels. PDCP sublayer 304 also provides security through encrypted data packets and supports cross-cell mobility between second communication node devices and the first communication node device. RLC sublayer 303 provides upper layer data packet segmentation and reassembly, retransmission of lost data packets, and data packet reordering to compensate for out-of-order reception due to HARQ. MAC sublayer 302 provides multiplexing between logical and transport channels. MAC sublayer 302 is also responsible for allocating various radio resources (e.g., resource blocks) within a cell between the first communication node devices. MAC sublayer 302 is also responsible for HARQ operations. The RRC (Radio Resource Control) sublayer 306 in Layer 3 (L3) of the control plane 300 is responsible for acquiring radio resources (i.e., radio bearers) and configuring the lower layer using RRC signaling between the second and first communication node devices. The radio protocol architecture of user plane 350 includes layer 1 (L1 layer) and layer 2 (L2 layer). The radio protocol architecture for the first and second communication node devices in user plane 350 is largely the same as the corresponding layers and sublayers in control plane 300 for physical layer 351, PDCP sublayer 354 in L2 layer 355, RLC sublayer 353 in L2 layer 355 and MAC sublayer 352 in L2 layer 355. However, PDCP sublayer 354 also provides header compression for upper layer data packets to reduce radio transmission overhead.The L2 layer 355 in the user plane 350 also includes an SDAP (Service Data Adaptation Protocol) sublayer 356, which is responsible for mapping between QoS streams and data radio bearers (DRBs) to support service diversity. Although not illustrated, the first communication node device may have several upper layers above the L2 layer 355, including a network layer (e.g., IP layer) terminating at the P-GW on the network side and an application layer terminating at the other end of the connection (e.g., a remote UE, server, etc.).

[0214] As an example, Appendix Figure 3 The wireless protocol architecture described above is applicable to the first node.

[0215] As an example, Appendix Figure 3 The wireless protocol architecture described above is applicable to the second node.

[0216] As an example, the higher layer mentioned in this application refers to the layer above the physical layer.

[0217] As an example, the second information block is generated in the RRC sublayer 306.

[0218] As an example, the second information block is generated in the PHY301 or the PHY351.

[0219] As an example, the second information block is generated in the MAC sublayer 302 or the MAC sublayer 352.

[0220] As an example, the first information block is generated in the RRC sublayer 306.

[0221] As an example, the first signaling is generated in the PHY301 or the PHY351.

[0222] As an example, the first signaling is generated in the MAC sublayer 302 or the MAC sublayer 352.

[0223] As an example, the RS in the first resource set is generated in the PHY301 or the PHY351.

[0224] As an example, the first channel information report is generated in the PHY301 or the PHY351.

[0225] Example 4

[0226] Example 4 illustrates a schematic diagram of a first communication device and a second communication device according to an embodiment of this application, as shown in the attached diagram. Figure 4 As shown. (Attached) Figure 4 This is a block diagram of a first communication device 410 and a second communication device 450 communicating with each other in an access network.

[0227] The first communication device 410 includes a controller / processor 475, a memory 476, a receiver processor 470, a transmitter processor 416, a multi-antenna receiver processor 472, a multi-antenna transmitter processor 471, a transmitter / receiver 418, and an antenna 420.

[0228] The second communication device 450 includes a controller / processor 459, a memory 460, a data source 467, a transmitting processor 468, a receiving processor 456, a multi-antenna transmitting processor 457, a multi-antenna receiving processor 458, a transmitter / receiver 454, and an antenna 452.

[0229] In the transmission from the first communication device 410 to the second communication device 450, at the first communication device 410, upper-layer data packets from the core network are provided to the controller / processor 475. The controller / processor 475 implements L2 layer functionality. In DL (Downlink), the controller / processor 475 provides header compression, encryption, packet segmentation and reordering, multiplexing between logical and transport channels, and radio resource allocation to the second communication device 450 based on various priority metrics. The controller / processor 475 is also responsible for HARQ operation, retransmission of lost packets, and signaling to the second communication device 450. The transmit processor 416 and the multi-antenna transmit processor 471 implement various signal processing functions for L1 layer (i.e., physical layer). Transmit processor 416 performs encoding and interleaving to facilitate forward error correction (FEC) at the second communication device 450, and constellation mapping based on various modulation schemes (e.g., binary phase shift keying (BPSK), quadrature phase shift keying (QPSK), M-phase shift keying (M-PSK), and M-quadrature amplitude modulation (M-QAM). Multi-antenna transmit processor 471 performs digital spatial precoding on the encoded and modulated symbols, including codebook-based precoding and non-codebook-based precoding, and beamforming processing, generating one or more parallel... The transmit processor 416 then maps each parallel stream to a subcarrier, multiplexes the modulated symbols with a reference signal (e.g., a pilot) in the time and / or frequency domains, and then uses an inverse fast Fourier transform (IFFT) to generate a physical channel carrying the time-domain multicarrier symbol stream. The multi-antenna transmit processor 471 then performs transmit analog precoding / beamforming operations on the time-domain multicarrier symbol stream. Each transmitter 418 converts the baseband multicarrier symbol stream provided by the multi-antenna transmit processor 471 into an RF stream, which is then provided to a different antenna 420.

[0230] In the transmission from the first communication device 410 to the second communication device 450, at the second communication device 450, each receiver 454 receives a signal through its corresponding antenna 452. Each receiver 454 recovers the information modulated onto the radio frequency carrier and converts the radio frequency stream into a baseband multicarrier symbol stream, which is then provided to the receiver processor 456. The receiver processor 456 and the multi-antenna receiver processor 458 implement various signal processing functions of the L1 layer. The multi-antenna receiver processor 458 performs receive analog precoding / beamforming operations on the baseband multicarrier symbol stream from the receiver 454. The receiver processor 456 uses a Fast Fourier Transform (FFT) to convert the baseband multicarrier symbol stream after the receive analog precoding / beamforming operations from the time domain to the frequency domain. In the frequency domain, the physical layer data signal and the reference signal are demultiplexed by the receiver processor 456, where the reference signal is used for channel estimation, and the data signal is recovered in the multi-antenna receiver processor 458 after multi-antenna detection to recover any parallel stream destined for the second communication device 450. Symbols on each parallel stream are demodulated and recovered in the receive processor 456, generating soft decisions. The receive processor 456 then decodes and deinterleaves the soft decisions to recover the upper-layer data and control signals transmitted over the physical channel by the first communication device 410. The upper-layer data and control signals are then provided to the controller / processor 459. The controller / processor 459 implements the functions of Layer 2 (L2). The controller / processor 459 may be associated with a memory 460 storing program code and data. The memory 460 may be referred to as computer-readable media. In the DL (Layered Logic), the controller / processor 459 provides multiplexing, packet reassembly, decryption, header decompression, and control signal processing between the transmission and logical channels to recover upper-layer packets from the core network. The upper-layer packets are then provided to all protocol layers above Layer 2. Various control signals may also be provided to Layer 3 (L3) for L3 processing. The controller / processor 459 is also responsible for error detection using ACK and / or NACK protocols to support HARQ operation.

[0231] In the transmission from the second communication device 450 to the first communication device 410, at the second communication device 450, a data source 467 is used to provide upper-layer data packets to the controller / processor 459. The data source 467 represents all protocol layers above the L2 layer. Similar to the transmission functions at the first communication device 410 described in the DL, the controller / processor 459 implements header compression, encryption, packet segmentation and reordering, and multiplexing between logical and transport channels based on the radio resource allocation of the first communication device 410, implementing L2 layer functions for the user plane and control plane. The controller / processor 459 is also responsible for HARQ operations, retransmission of lost packets, and signaling to the first communication device 410. Transmit processor 468 performs modulation mapping and channel coding processing, while multi-antenna transmit processor 457 performs digital multi-antenna spatial precoding, including codebook-based and non-codebook-based precoding, and beamforming processing. Subsequently, transmit processor 468 modulates the generated parallel stream into a multi-carrier / single-carrier symbol stream. After analog precoding / beamforming operations in multi-antenna transmit processor 457, the stream is provided to different antennas 452 via transmitter 454. Each transmitter 454 first converts the baseband symbol stream provided by multi-antenna transmit processor 457 into a radio frequency symbol stream before providing it to antenna 452.

[0232] In the transmission from the second communication device 450 to the first communication device 410, the function at the first communication device 410 is similar to the receiving function at the second communication device 450 described in the transmission from the first communication device 410 to the second communication device 450. Each receiver 418 receives radio frequency signals through its corresponding antenna 420, converts the received radio frequency signals into baseband signals, and provides the baseband signals to the multi-antenna receiving processor 472 and the receiving processor 470. The receiving processor 470 and the multi-antenna receiving processor 472 jointly implement the L1 layer functions. The controller / processor 475 implements the L2 layer functions. The controller / processor 475 may be associated with a memory 476 that stores program code and data. The memory 476 may be referred to as computer-readable media. The controller / processor 475 provides multiplexing, packet reassembly, decryption, header decompression, and control signal processing between the transmission and logical channels to recover upper-layer data packets from the second communication device 450. The upper-layer data packets from the controller / processor 475 may be provided to the core network. The controller / processor 475 is also responsible for error detection using ACK and / or NACK protocols to support HARQ operation.

[0233] As one embodiment, the second communication device 450 includes: at least one processor and at least one memory, the at least one memory including computer program code; the at least one memory and the computer program code are configured to be used with the at least one processor. The second communication device 450 means at least: receiving RS in a first resource set; transmitting a first channel information report; wherein the first resource set includes at least one RS resource used for at least one of channel measurement or interference measurement in the first channel information report; the first channel information report occupies M processing resources in a first time-domain resource, M being a positive integer; the M depending on the size of the first time-domain resource.

[0234] As one embodiment, the second communication device 450 includes: a memory storing a computer-readable instruction program that, when executed by at least one processor, produces actions including: receiving an RS in a first resource set; and sending a first channel information report; wherein the first resource set includes at least one RS resource used for at least one of channel measurement or interference measurement for the first channel information report; the first channel information report occupies M processing resources in a first time-domain resource, where M is a positive integer; and M depends on the size of the first time-domain resource.

[0235] As one embodiment, the first communication device 410 includes: at least one processor and at least one memory, the at least one memory including computer program code; the at least one memory and the computer program code are configured to be used with the at least one processor. The first communication device 410 means at least: transmitting RS in a first resource set; receiving a first channel information report; wherein the first resource set includes at least one RS resource used for at least one of channel measurement or interference measurement in the first channel information report; the first channel information report occupies M processing resources in a first time-domain resource, M being a positive integer; the M depending on the size of the first time-domain resource.

[0236] As one embodiment, the first communication device 410 includes: a memory storing a computer-readable instruction program, the computer-readable instruction program generating actions when executed by at least one processor, the actions including: transmitting an RS in a first resource set; receiving a first channel information report; wherein the first resource set includes at least one RS resource used for at least one of channel measurement or interference measurement for the first channel information report; the first channel information report occupies M processing resources in a first time-domain resource, M being a positive integer; the M depending on the size of the first time-domain resource.

[0237] As an example, the second node in this application includes the first communication device 410.

[0238] As an example, at least one of {the antenna 452, the receiver 454, the receiving processor 456, the multi-antenna receiving processor 458, the controller / processor 459, the memory 460, and the data source 467} is used to receive the first signaling in this application; at least one of {the antenna 420, the transmitter 418, the transmitting processor 416, the multi-antenna transmitting processor 471, the controller / processor 475, and the memory 476} is used to transmit the first signaling in this application.

[0239] As an example, at least one of {the antenna 452, the receiver 454, the receiving processor 456, the multi-antenna receiving processor 458, the controller / processor 459, the memory 460, and the data source 467} is used to receive the first information block in this application; at least one of {the antenna 420, the transmitter 418, the transmitting processor 416, the multi-antenna transmitting processor 471, the controller / processor 475, and the memory 476} is used to transmit the first information block in this application.

[0240] As an example, at least one of {the antenna 452, the receiver 454, the receiving processor 456, the multi-antenna receiving processor 458, the controller / processor 459, the memory 460, and the data source 467} is used to receive RS in the first resource set of this application; at least one of {the antenna 420, the transmitter 418, the transmitting processor 416, the multi-antenna transmitting processor 471, the controller / processor 475, and the memory 476} is used to transmit RS in the first resource set of this application.

[0241] As an example, at least one of {the antenna 452, the transmitter 454, the transmitter processor 468, the multi-antenna transmitter processor 457, the controller / processor 459, the memory 460, and the data source 467} is used to transmit the second information block in this application; at least one of {the antenna 420, the receiver 418, the receiver processor 470, the multi-antenna receiver processor 472, the controller / processor 475, and the memory 476} is used to receive the second information block in this application.

[0242] As an example, at least one of the following is used to generate the first channel information report in this application: {the antenna 452, the transmitter / receiver 454, the transmission processor 468, the multi-antenna transmission processor 457, the receiving processor 456, the multi-antenna receiving processor 458, the controller / processor 459, the memory 460, and the data source 467}.

[0243] As an example, at least one of the following is used in the first operation of this application: {the antenna 452, the transmitter / receiver 454, the transmitter processor 468, the multi-antenna transmitter processor 457, the receiver processor 456, the multi-antenna receiver processor 458, the controller / processor 459, the memory 460, and the data source 467}.

[0244] As an example, at least one of {the antenna 452, the transmitter 454, the transmitter processor 468, the multi-antenna transmitter processor 457, the receiver processor 456, the multi-antenna receiver processor 458, the controller / processor 459, the memory 460, and the data source 467} is used in the first operation of this application; at least one of {the antenna 420, the receiver 418, the receiver processor 470, the multi-antenna receiver processor 472, the transmitter processor 416, the multi-antenna transmitter processor 471, the controller / processor 475, and the memory 476} is used in the second operation of this application.

[0245] As an example, at least one of {the antenna 452, the transmitter 454, the transmitter processor 468, the multi-antenna transmitter processor 457, the controller / processor 459, the memory 460, and the data source 467} is used to transmit the first channel information report in this application; at least one of {the antenna 420, the receiver 418, the receiver processor 470, the multi-antenna receiver processor 472, the controller / processor 475, and the memory 476} is used to receive the first channel information report in this application.

[0246] Example 5

[0247] Example 5 illustrates a flowchart of a transmission according to an embodiment of this application; as attached Figure 5 As shown. In the appendix Figure 5 In this context, the second node N1 and the first node U1 are communication nodes that transmit data via the air interface. (Appendix) Figure 5 In the diagram, the steps in boxes F51 and F52 are optional.

[0248] For the second node N1, in step S521, a first information block is sent; in step S522, a first signaling is sent; in step S523, RS is sent in the first resource set; and in step S524, a first channel information report is received.

[0249] For the first node U1, in step S511, the first information block is received; in step S512, the first signaling is received; in step S513, RS is received in the first resource set; and in step S514, the first channel information is reported.

[0250] In Embodiment 5, the first information block is used to configure the first channel information reporting; the first resource set includes at least one RS resource used for at least one of channel measurement or interference measurement in the first channel information reporting; the first channel information reporting occupies M processing resources in the first time domain resources, where M is a positive integer; M depends on the size of the first time domain resources. When the step in block F52 is present, the first channel information reporting is triggered by the first signaling.

[0251] As an example, the first node U1 is the first node in this application.

[0252] As an example, the second node N1 is the second node in this application.

[0253] As one embodiment, the air interface between the second node N1 and the first node U1 includes a wireless interface between the base station equipment and the user equipment.

[0254] As one embodiment, the air interface between the second node N1 and the first node U1 includes a wireless interface between the relay node device and the user equipment.

[0255] As one embodiment, the air interface between the second node N1 and the first node U1 includes a wireless interface between user equipment and user equipment.

[0256] As one example, the second node N1 is the serving cell sustaining base station of the first node U1.

[0257] As one embodiment, the first information block is carried by higher layer signaling.

[0258] As an example, the first information block is carried by RRC (Radio Resource Control) signaling.

[0259] As one embodiment, the first information block includes some or all of the fields in one or more RRC IEs (Information Elements).

[0260] As one embodiment, the first information block includes some or all of the fields in an IE CSI-ReportConfig.

[0261] As one embodiment, the first information block includes some or all of the domains in IE ServingCellConfig.

[0262] As one embodiment, the first information block includes some or all of the domains in IE CSI-MeasConfig.

[0263] As one example, the first information block includes some or all of the domains in IE ServingCellConfigCommon.

[0264] As one embodiment, the first information block includes some or all of the domains in IE ServingCellConfig.

[0265] As one embodiment, the first information block indicates at least one of a first resource set, a reporting type of the first channel information reporting, or a reporting amount of the first channel information reporting; the first resource set includes at least one RS resource used for at least one of channel measurement or interference measurement in the first channel information reporting.

[0266] As one embodiment, the first information block indicates at least one of a first resource set, a second resource set, a reporting type of the first channel information reporting, or a reporting amount of the first channel information reporting; the first resource set includes at least one RS resource used for at least one of channel measurement or interference measurement in the first channel information reporting; the second resource set includes one or more resources.

[0267] As a sub-implementation of the above embodiments, the second resource set includes one or more RS resources.

[0268] As a sub-implementation of the above embodiments, the resources in the second resource set include at least one of antenna port, TCI status, QCL information, time-frequency resources, time-frequency code resources, beam, RS resources, vector, or matrix.

[0269] As an example, the reporting type indicates at least one of periodic reporting, semi-persistent reporting, non-periodic reporting, or event-triggered reporting.

[0270] As an example, the reporting type indicates at least one of periodic reporting, semi-persistent reporting, or non-periodic reporting.

[0271] As an example, the first channel information report includes CSI (channel state information).

[0272] As an example, the CSI includes beam information.

[0273] As an example, the CSI includes compressed CSI.

[0274] As an example, the compressed CSI is based on non-codebook channel information.

[0275] As an example, the channel parameters recovered by the target receiver of the compressed CSI based on the compressed CSI are unknown to the sender of the compressed CSI.

[0276] As an example, the compressed CSI is channel information based on artificial intelligence or machine learning.

[0277] As an example, the compressed CSI is based on channel information from a neural network.

[0278] As an example, the compressed CSI is based on channel information from CNN (Conventional Neural Networks).

[0279] As one embodiment, the first channel information report includes a channel matrix.

[0280] As one embodiment, the first channel information report includes at least one of the channel's feature values ​​or feature vectors.

[0281] As an example, the first channel information report includes one of beam information, predicted CSI, or compressed CSI.

[0282] As an example, the first channel information report includes at least one of PMI (Precoding Matrix Indicator), CRI (CSI-RS Resource Indicator), CQI (Channel Quality Indicator), RI (Rank Indicator), Layer Indicator (LI), SS / PBCH Block Resource Indicator (SSBRI), RSRP, SINR (signal-to-noise and interference ratio), capability index, TDCP (Time domain channel properties), or confidence information.

[0283] As an example, the first channel information report includes at least one of resource indication, RSRP (reference signal received power), PMI, CQI, SINR, channel matrix, eigenvalue of the channel, or eigenvector of the channel; the resource indication is used to indicate beam or RS resources.

[0284] As an example, the first channel information reporting is based on a non-codebook.

[0285] As one embodiment, the first channel information report includes a resource indication, which is used to indicate beam or RS (reference signal) resources.

[0286] As an example, the first channel information report includes at least one of a resource indication or RSRP (reference signal received power), wherein the resource indication is used to indicate a beam or RS resource.

[0287] As one embodiment, the beam information includes a resource indicator, which is used to indicate a beam or RS resource.

[0288] As an example, the beam information includes at least one of a resource indicator or RSRP (reference signal received power), wherein the resource indicator is used to indicate the beam or RS resource.

[0289] As an example, the resource indication is used to indicate one of beam, CSI-RS (Channel State Information Reference Signal) resources, or synchronization signal resources.

[0290] As an example, the resource indicator is a CRI (CSI-RS Resource Indicator, Channel State Information Reference Signal Resource Indicator) or an SS / PBCH Block Resource Indicator (SSBRI).

[0291] As one embodiment, the synchronization signal resources include at least the resources occupied by the synchronization signal.

[0292] As an example, the synchronization signal resource is an SSB (Synchronization Signal Block).

[0293] As an example, the synchronization signal resource is an SS / PBCH (Synchronization Signal / Physical Broadcast Channel) block resource.

[0294] As an example, the first channel information reported includes at least one of PMI, CQI, and RI.

[0295] As an example, the first channel information report includes at least one of resource indication, RSRP, channel matrix, channel eigenvalue, or channel eigenvector; the resource indication is used to indicate beam or RS resources.

[0296] As an example, the first channel information reported includes at least one of PMI, CQI, RI, CRI, SSBRI, RSRP, and SINR.

[0297] As an example, the first channel information report includes at least one of resource indication, RSRP, channel matrix, channel eigenvalue, channel eigenvector, or compressed CSI; the resource indication is used to indicate beam or RS resources.

[0298] As an example, the first channel information report is one of periodic reporting, semi-persistent reporting, non-periodic reporting, or event-triggered reporting.

[0299] As an example, the first channel information report is one of semipersistent reporting, non-periodic reporting, or event-triggered reporting.

[0300] As an example, the first channel information report is aperiodic.

[0301] As an example, the first channel information report is a semi-persistent report.

[0302] As an example, the first channel information report is an initial semi-persistent report.

[0303] As an example, the first channel information report is an initial report of a semi-persistent report.

[0304] As an example, the first channel information report is a semi-persistent report activated by MAC CE.

[0305] As an example, the first channel information report is a semi-persistent report activated by DCI (Downlink Control Information).

[0306] As an example, the first channel information report is the initial report in a semi-persistent report activated by DCI.

[0307] As an example, the first channel information report is the initial semi-persistent report triggered by DCI.

[0308] As an example, the first channel information report is an aperiodic report triggered by DCI.

[0309] As an example, the first channel information report is an event-triggered report.

[0310] As an example, the first channel information report is determined and sent by the first node itself.

[0311] As one embodiment, the first information block indicates the first resource set.

[0312] As one embodiment, the first resource set includes at least one RS resource used for at least one of the channel measurement or interference measurement in the first channel information reporting, wherein the first channel information reporting indicates at least one resource in the first resource set.

[0313] As one embodiment, the first resource set includes at least one RS resource used for at least one of the channel measurement or interference measurement in the first channel information reporting, the first channel information reporting indicates at least one resource in the second resource set, and the second resource set includes resources that do not belong to the first resource set.

[0314] As one embodiment, the first information block indicates the first resource set and the second resource set.

[0315] As one embodiment, the second resource set includes resources that do not belong to the first resource set.

[0316] As one embodiment, a first information block is used to configure the first channel information reporting. The first information block indicates a first resource set, which includes at least one RS resource used for at least one of channel measurements or interference measurements in the first channel information reporting. The first channel information reporting indicates at least one resource in a second resource set and an RSRP, which includes resources that do not belong to the first resource set.

[0317] As one embodiment, the first resource set includes at least one RS resource used for at least one of the channel measurement or interference measurement in the first channel information reporting; the second resource set is used for prediction.

[0318] As one embodiment, the first resource set includes at least one RS resource used for at least one of channel measurement or interference measurement in the first channel information reporting; the second resource set is used for beam prediction or channel prediction.

[0319] As an example, the first node is not required to measure some or all of the resources in the second resource set.

[0320] As one embodiment, the first node not being required to measure the second resource set includes: the first node not measuring some or all of the resources in the second resource set.

[0321] As one embodiment, the first node not being required to measure the second resource set includes: whether the first node measures some or all of the resources in the second resource set is implementation-related or determined by the first node itself.

[0322] As an example, the advantages of the above method include: reducing the overhead required to obtain channel information.

[0323] As an example, the advantages of the above method include: it can reduce the measurement resources required to obtain channel information.

[0324] As one embodiment, the second resource set includes the first resource set and resources outside the first resource set.

[0325] As one example, the second resource set includes at least one training dataset.

[0326] As an example, the second resource set is used to train an AI model.

[0327] As an example, the second resource set is used to train the first operation in this application.

[0328] As one embodiment, the second resource set includes one or more RS (Reference Signal) resource sets, and an RS resource set includes one or more RS resources.

[0329] As an example, a first information block is used to configure the first channel information reporting, the first information block indicates a first identifier, and the second resource set depends on the first identifier in the first information block.

[0330] As one embodiment, the second resource set depends on the first identifier, which is used to identify the second resource set.

[0331] As one embodiment, the second resource set depends on the first identifier, which is used to identify a reference resource set, and the second resource set includes some or all of the resources in the reference resource set.

[0332] As one embodiment, the second resource set depends on the first identifier, which includes: the first identifier being used to identify a reference resource set, the second resource set including some or all of the resources in the reference resource set, and the first information block being used to indicate the second resource set from the reference resource set.

[0333] As one embodiment, the first information block is used to configure the first channel information reporting, and the information outside the first information block indicates the second resource set.

[0334] As a sub-implementation of the above embodiments, the information indicating the second resource set in addition to the first information block includes higher-level parameters.

[0335] As a sub-implementation of the above embodiment, the information indicating the second resource set in addition to the first information block includes RRC parameters.

[0336] As a sub-implementation of the above embodiments, the information indicating the second resource set, other than the first information block, includes part or all of an RRC IE field.

[0337] As a sub-implementation of the above embodiments, the information indicating the second resource set in addition to the first information block includes MAC CE.

[0338] As a sub-implementation of the above embodiments, the information indicating the second resource set other than the first information block includes DCI (downlink control information).

[0339] As an example, the first channel information report is generated based on inference.

[0340] As an example, the reasoning includes AI reasoning.

[0341] As an example, the first channel information report is calculated or generated through artificial intelligence or machine learning.

[0342] As one embodiment, the generation of the first channel information report includes: the calculation of the first channel information report.

[0343] As an example, the generation of the first channel information report includes: the inference of the first channel information report.

[0344] As an example, the generation of the first channel information report includes: reasoning to obtain the first channel information report.

[0345] As one embodiment, the generation of the first channel information report includes: calculation or inference of the first channel information report.

[0346] As an example, the first channel information report is generated based on inference; the generation of the first channel information report includes: the inference of the first channel information report.

[0347] As an example, the first channel information report is generated based on inference; the generation of the first channel information report includes: inference to obtain the first channel information report.

[0348] As one embodiment, the first channel information report is generated based on inference; the generation of the first channel information report includes: the sender of the first channel information report performing a first operation, the first channel information report depending on the output of the first operation, the first operation including inference.

[0349] As one example, the first channel information report is generated based on inference, including: the first channel information report is calculated or generated through artificial intelligence or machine learning.

[0350] As one embodiment, the first channel information report is generated based on inference, including: the generation of the first channel information report is based on training.

[0351] As an example, the first channel information report is generated based on inference, including the generation of the first channel information report using an AI model.

[0352] As one example, the first channel information report is generated based on inference, including: the generation of the first channel information report uses information generated based on artificial intelligence or machine learning.

[0353] As one embodiment, the first channel information report is generated based on inference, including: the generation of the first channel information report uses information generated based on a neural network.

[0354] As an example, the first channel information report is generated based on inference, including: the generation of the first channel information report uses information generated based on CNN (Conventional Neural Networks).

[0355] As one embodiment, the first channel information report is generated based on inference, including: the first channel information report includes information generated based on artificial intelligence or machine learning.

[0356] As one embodiment, the first channel information report is based on inference and includes: the first channel information report includes information generated based on a neural network.

[0357] As one embodiment, the first channel information report is generated based on inference and includes: the first channel information report includes information generated based on CNN (Conventional Neural Networks).

[0358] As one embodiment, the first channel information report is generated based on inference and includes: the generation of the first channel information report corresponding to the first identifier.

[0359] As an example, in the case where the first channel information report is generated based on inference, how the first channel information report is generated is determined by the manufacturer of the first node, or is implementation-related. A typical but non-limiting implementation is described below:

[0360] The first node measures the RS resources used for channel measurement to obtain the channel parameter matrix H. r×t Where r and t are the number of receiving antennas and the number of antenna ports, respectively; at least the channel parameter matrix H r×t Alternatively, its feature vector is input into an AI model, and the output of the AI ​​model is used to obtain the first channel information report.

[0361] If the first channel information reporting requires the first node to estimate interference (including noise), the first node can measure the RS resources used for interference measurement to obtain the measured interference.

[0362] In one implementation, measurement interference is also input into the AI ​​model.

[0363] In another implementation, the measurement interference is not input into the AI ​​model; the output of the AI ​​model and the measurement interference are used together to generate the first channel information report.

[0364] Without loss of generality, the AI ​​model or the parameters of the AI ​​model used to generate the first channel information report are determined by the manufacturer of the first node.

[0365] As one embodiment, the first signaling is physical layer signaling.

[0366] As one embodiment, the first signaling includes control information.

[0367] As an example, the first signaling is DCI.

[0368] As one embodiment, the first signaling is transmitted on the physical layer control channel.

[0369] As an example, the first signaling is DCI transmitted on PDCCH (Physical Downlink Control Channel).

[0370] As one embodiment, the first signaling includes a first field, which includes at least one bit; the first field in the first signaling triggers the first channel information reporting.

[0371] As an example, the first field is the CSI request field.

[0372] As an example, the first signaling includes MAC CE.

[0373] As one embodiment, the first channel information reporting being triggered by the first signaling includes: the first signaling including MAC CE, and the first channel information reporting being a semi-persistent reporting activated by the first signaling.

[0374] As one embodiment, the first channel information reporting being triggered by the first signaling includes: the first signaling including physical layer signaling, and the first channel information reporting being a semi-persistent reporting activated by the first signaling.

[0375] As one embodiment, the first channel information report being triggered by the first signaling includes: the first signaling including physical layer signaling, and the first channel information report being the initial report in a semi-persistent report activated by the first signaling.

[0376] As one embodiment, the first channel information reporting being triggered by the first signaling includes: the first signaling including physical layer signaling, and the first channel information reporting being a non-periodic reporting triggered by the first signaling.

[0377] As one embodiment, the first channel information reporting being triggered by the first signaling includes: the first signaling including DCI, and the first channel information reporting being a semi-persistent reporting activated by the first signaling.

[0378] As one embodiment, the first channel information report being triggered by the first signaling includes: the first signaling including DCI, and the first channel information report being the initial report in a semi-persistent report activated by the first signaling.

[0379] As one embodiment, the first channel information reporting being triggered by the first signaling includes: the first signaling including DCI, and the first channel information reporting being a non-periodic reporting triggered by the first signaling.

[0380] As one embodiment, the first channel information reporting being triggered by the first signaling includes: the first signaling including physical layer signaling, and the first channel information reporting being an aperiodic reporting or an initial semi-persistent reporting triggered by the first signaling.

[0381] As one embodiment, the first channel information reporting being triggered by the first signaling includes: the first signaling including DCI, and the first channel information reporting being an aperiodic reporting or an initial semi-persistent reporting triggered by the first signaling.

[0382] As an example, the first node deploys the first operation.

[0383] As one embodiment, the deployment of the first operation includes: obtaining the first operation.

[0384] As an example, the deployment first operation includes: loading the first operation.

[0385] As one embodiment, the deployment of the first operation includes: submitting a request to load the first operation.

[0386] As an example, the advantages of the above method include that it provides sufficient freedom for the first node, adapting to various different scenarios and terminals, and has adaptability and flexibility.

[0387] As an example, the advantages of the above method include: training for the first operation can be performed outside the first node, reducing the processing power requirements and power consumption of the first node.

[0388] As an example, the first operation is used for CSI prediction, beam prediction, or CSI compression.

[0389] As an example, the first operation is used for beam prediction or CSI prediction.

[0390] As one embodiment, the first node performs a first operation, and the second node performs a second operation; wherein, the first channel information report is generated based on inference.

[0391] As one embodiment, the second node performs a second operation; wherein the first channel information report is generated based on inference, the first node performs a first operation, the first operation includes inference, the output of the first operation includes a first CSI, the first channel information report carries the first CSI, and the first CSI is used as input to the second operation to generate a second CSI.

[0392] As an example, the second node deploys the second operation.

[0393] As one embodiment, the deployment of the second operation includes: obtaining the second operation.

[0394] As an example, the deployment of the second operation includes: loading the second operation.

[0395] As one embodiment, the deployment of the second operation includes: submitting a request to load the second operation.

[0396] As an example, the advantages of the above method include that it provides sufficient freedom for the second node, adapting to various different scenarios and terminals, and possessing adaptability and flexibility.

[0397] As an example, the advantages of the above method include: training for the second operation can be performed outside the second node, reducing the processing power requirements and power consumption of the second node.

[0398] As one example, the second operation is based on training or AI.

[0399] As one example, the second operation includes reasoning.

[0400] As one example, the second operation includes AI inference for CSI recovery.

[0401] As one example, the second operation includes AI inference for CSI decompression.

[0402] As an example, the first operation is used for CSI compression, and the second operation is used for CSI recovery.

[0403] As an example, the first channel information report is generated based on inference, the output of the first operation includes a first CSI, the first channel information report carries the first CSI, and the first CSI is used by the second node as input to the second operation to generate a second CSI.

[0404] As an example, the reasoning includes AI reasoning.

[0405] As an example, the AI ​​(Artificial Intelligence) includes ML (Machine Learning).

[0406] As an example, the first CSI is used to generate the first channel information report.

[0407] As an example, the first channel information report includes the first CSI.

[0408] As an example, the first CSI includes a compressed CSI.

[0409] As one example, the first CSI includes compressed predicted channel information.

[0410] As an example, the first CSI is post-processed and used to generate the first channel information report.

[0411] As one embodiment, the first channel information report includes the first CSI after post-processing.

[0412] As an example, the first channel information report carries the first CSI after post-processing.

[0413] As an example, the first CSI is truncated and / or quantized and used to generate the first channel information report.

[0414] As one embodiment, the first channel information reported includes the first CSI after truncation and / or quantization.

[0415] As an example, the first channel information report carries the first CSI after truncation and / or quantization.

[0416] As one embodiment, the first CSI includes a channel matrix.

[0417] As one example, the first CSI includes a feature vector.

[0418] As an example, the first CSI includes a feature vector and feature values.

[0419] As an example, the first CSI includes precoded information.

[0420] As one embodiment, the first CSI includes pre-encoded information based on a non-codebook.

[0421] As an example, the first CSI is used to determine at least one precoding matrix.

[0422] As an example, the first CSI indicates at least one precoding matrix.

[0423] As an example, the precoding matrix is ​​in the spatial-frequency domain.

[0424] As an example, the precoding matrix is ​​angular-delay domain projection.

[0425] As one embodiment, the first CSI includes information on the relative phase, amplitude, and / or coefficients between multiple antenna ports.

[0426] As an example, the first CSI includes a compressed CSI.

[0427] As an example, the first CSI includes predicted / estimated CSI.

[0428] As one embodiment, the second CSI includes the recovery of at least a portion of the input of the first operation.

[0429] As one embodiment, the second CSI includes a channel matrix.

[0430] As one embodiment, the second CSI includes a feature vector and / or feature values.

[0431] As one embodiment, the second CSI includes a precoding matrix.

[0432] As one embodiment, the second CSI includes one or more of the following: channel matrix, eigenvector, eigenvalue, or precoding matrix.

[0433] As an example, the second operation is the inverse operation of the first operation.

[0434] Examples 6A-6B

[0435] Examples 6A-6B respectively illustrate schematic diagrams of the first condition according to an embodiment of this application; as shown in the appendix. Figures 6A-6B As shown.

[0436] In embodiment 6A, M depends on the size of the first time-domain resource only when the first condition is met; the first condition includes at least one of the following: the first channel information report is generated based on inference or the first channel information report generates a corresponding first identifier.

[0437] As an example, the first condition includes the first channel information report being generated based on inference.

[0438] As one embodiment, the first condition includes the generation of the first identifier corresponding to the first channel information reported.

[0439] As one embodiment, the first condition includes: the first channel information report is generated based on inference, and the generation of the first channel information report corresponds to a first identifier.

[0440] As one embodiment, the first condition includes at least one of the following: the first channel information report is generated based on inference or the first channel information report generates a corresponding first identifier; the first condition further includes: the reported amount of the first channel information report belongs to a first reported amount set, the first reported amount set includes only a portion of the reported amounts among all candidate reported amounts of channel information reports.

[0441] The following are some non-limiting implementations of the first set of reported quantities, for example:

[0442] As one embodiment, the first set of reported data includes reported data used for CSI compression.

[0443] As one embodiment, the first set of reported data includes reported data used for CSI prediction.

[0444] As an example, the first set of reported data does not include reported data used for beam prediction.

[0445] As an example, the first set of reported data does not include RSRP.

[0446] As an example, the first condition includes multiple sub-conditions; the first condition is satisfied only when all of the multiple sub-conditions are satisfied; one of the multiple sub-conditions includes at least one of the following: the first channel information report is generated based on inference or the first channel information report generates a corresponding first identifier.

[0447] As an example, the first condition includes multiple sub-conditions; the first condition is satisfied when one of the multiple sub-conditions is satisfied; one of the multiple sub-conditions includes at least one of the following: the first channel information report is generated based on inference or the first channel information report generates a corresponding first identifier.

[0448] In the above method, the total amount of processing resources occupied by channel information reports generated solely based on inference depends on the size of the first time-domain resources. The advantages of this method include: better adaptability to various types of channel information reports, and good flexibility and adaptability.

[0449] As an example, the first identifier is a non-negative integer.

[0450] As an example, the first identifier is a string.

[0451] As an example, the first identifier is different from the reporting configuration identifier of the first channel information report.

[0452] As an example, the first identifier is used to identify the AI ​​model.

[0453] As an example, the first identifier is used to identify the AI ​​model, and the first channel information report is generated based on inference using the AI ​​model identified by the first identifier.

[0454] As an example, the first identifier is used by the first node to identify an AI model.

[0455] As an example, the first identifier is used by the first node to determine the AI ​​model used in the first operation of this application.

[0456] As an example, the first identifier is used to identify the AI ​​entity.

[0457] As an example, the first identifier is used to identify AI functionality.

[0458] As an example, the advantages of the above method include that identifying an AI model / entity / function through the first identifier simplifies the design and unifies the understanding of different AI entities or functions across multiple nodes.

[0459] As one embodiment, the first identifier is used to identify or indicate a set of resources.

[0460] As one embodiment, the first identifier is used to identify or indicate a set of resources, the measurement of which is used to obtain a training dataset.

[0461] As one embodiment, the first identifier is used to identify or indicate a resource set, the resource set identified or indicated by the first identifier including one or more RS resources.

[0462] As an example, the first identifier is used to identify or indicate the training dataset.

[0463] As an example, the benefits of the above method include identifying the inference generated by an AI training or AI training dataset by identifying the AI ​​training or AI training dataset, establishing consensus among different AI functions, and further simplifying the design.

[0464] In embodiment 6B, M depends on the size of the first time-domain resource only when the first condition is met; the first condition includes at least one of the first channel information report being generated based on inference or the first channel information report being generated corresponding to the first identifier; the first condition also includes the first channel information report being triggered by physical layer signaling.

[0465] As an example, M depends on the size of the first time-domain resource only when the first condition is met; the first condition includes that the first channel information reporting is generated based on inference and that the first channel information reporting is triggered by physical layer signaling.

[0466] As an example, M depends on the size of the first time-domain resource only when the first condition is met; the first condition includes the generation of the first channel information report corresponding to the first identifier, and the first channel information report is triggered by physical layer signaling.

[0467] As an example, M depends on the size of the first time-domain resource only when the first condition is met; the first condition includes that the first channel information report is generated based on inference, the generation of the first channel information report corresponds to at least one of the first identifiers, and the first channel information report is triggered by physical layer signaling.

[0468] As one embodiment, the first channel information reporting being triggered by physical layer signaling includes: the first channel information reporting being aperiodic or initial semi-persistent reporting.

[0469] As one embodiment, the first condition includes at least one of the following: the first channel information report is generated based on inference or the first channel information report generates a corresponding first identifier; the first condition further includes: the first channel information report is triggered by physical layer signaling, and the reported amount of the first channel information report belongs to a first report amount set, the first report amount set includes only a portion of the reported amounts among all candidate report amounts of channel information reports.

[0470] As an example, the first channel information report is triggered by physical layer signaling, where the physical layer signaling is signaling transmitted on the physical layer channel.

[0471] As an example, the first channel information report is triggered by physical layer signaling, where the physical layer signaling is control signaling transmitted on the physical layer channel.

[0472] As an example, the physical layer signaling in the first channel information reporting triggered by physical layer signaling is DCI.

[0473] As an example, the first channel information report is triggered by physical layer signaling, where the physical layer signaling is DCI transmitted on the PDCCH.

[0474] Examples 7A-7C

[0475] Examples 7A-7C respectively illustrate schematic diagrams of a first time-domain resource according to an embodiment of this application; as shown in the appendix. Figures 7A-7C As shown.

[0476] In Embodiment 7A, the first node in this application receives the first signaling; wherein the first channel information reporting is triggered by the first signaling; the first time domain resource starts after the physical layer channel carrying the first signaling, or the first time domain resource starts after the first symbol of the physical layer channel carrying the first signaling.

[0477] As one embodiment, the first channel information report is either an aperiodic report triggered by the first signaling or an initial semi-persistent report.

[0478] As an example, the first channel information report is an aperiodic report triggered by the first signaling.

[0479] As an example, the first channel information report is an initial semi-persistent report triggered by the first signaling.

[0480] As an example, the first channel information reporting is triggered by the first signaling; the first time-domain resource begins after the physical layer channel carrying the first signaling.

[0481] As an example, the first channel information reporting is triggered by the first signaling; the first time-domain resource begins at the first symbol following the physical layer channel carrying the first signaling.

[0482] As an example, the first channel information reporting is triggered by the first signaling; the first time-domain resource begins at least a first time interval after the physical layer channel carrying the first signaling.

[0483] As an example, the first channel information reporting is triggered by the first signaling; the first time-domain resource begins at least after the first symbol following the physical layer channel carrying the first signaling, at least after a first time interval.

[0484] As a sub-implementation of the above embodiments, the first time interval is configurable.

[0485] As a sub-implementation of the above embodiments, the first time interval is predefined.

[0486] As a sub-implementation of the above embodiments, the first time interval is reported by the first node.

[0487] Typically, the first symbol refers to the earliest symbol.

[0488] In Example 7B, the first time-domain resource begins with the first symbol of the earliest RS time in the first time set; the first time set includes at least one RS time in the first resource set.

[0489] As an example, the first channel information report is a periodic channel information report or a non-initial semi-persistent channel information report; the first time-domain resource begins with the first symbol of the earliest RS time in the first time set; the first time set includes at least one RS time in the first resource set.

[0490] As an example, the first channel information reporting is periodic; the first time-domain resource begins with the first symbol of the earliest RS time in the first time set; the first time set includes at least one RS time in the first resource set.

[0491] As an example, the first channel information report is a non-initial semi-persistent channel information report; the first time-domain resource begins with the first symbol of the earliest RS time in the first time set; the first time set includes at least one RS time in the first resource set.

[0492] As one embodiment, the first timing set includes at least one RS timing in the first resource set that is no later than a reference time, wherein the reference time is earlier than the physical layer channel carrying the first channel information reported.

[0493] As one embodiment, the first timing set includes some or all of the RS timings (occasion(s)) in the first resource set that are no later than a reference time, wherein the reference time is earlier than the physical layer channel carrying the first channel information reported.

[0494] As one embodiment, the first timing set includes at least one RS timing in the first resource set that is no later than the CSI reference resource reported by the first channel information.

[0495] As one embodiment, the first timing set includes some or all of the RS timings of the CSI reference resources in the first resource set that are no later than the first channel information reported.

[0496] As an example, the first timing set includes at least the latest RS timing of at least one RS resource in the first resource set, which is no later than the CSI reference resource reported by the first channel information.

[0497] As one embodiment, the first timing set includes at least the latest RS timing for each RS resource in the first resource set, no later than the CSI reference resource reported by the first channel information.

[0498] As one embodiment, the first timing set includes at least one RS resource in the first resource set, and some or all of the RS timings are no later than the CSI reference resource reported by the first channel information.

[0499] As one embodiment, the first timing set includes some or all of the RS timings for each RS resource in the first resource set that are no later than the CSI reference resource reported by the first channel information.

[0500] In embodiment 7C, the first time-domain resource terminates at the last symbol of the physical layer channel carrying the first channel information report.

[0501] As an example, the first channel information reporting is triggered by the first signaling; the first time domain resource starts after the physical layer channel carrying the first signaling, or the first time domain resource starts after the first symbol of the physical layer channel carrying the first signaling; the first time domain resource terminates at the last symbol of the physical layer channel carrying the first channel information reporting.

[0502] As an example, the first time-domain resource begins with the first symbol of the earliest RS time in the first time set; the first time set includes at least one RS time in the first resource set; and the first time-domain resource terminates with the last symbol of the physical layer channel carrying the first channel information report.

[0503] As an example, the first channel information report is an aperiodic report triggered by the first signaling or an initial semi-persistent report; the first time domain resource begins after the physical layer channel carrying the first signaling, or the first time domain resource begins at the first symbol after the physical layer channel carrying the first signaling; the first time domain resource terminates at the last symbol of the physical layer channel carrying the first channel information report.

[0504] As an example, the first channel information report is a periodic channel information report or a non-initial semi-persistent channel information report; the first time-domain resource begins with the first symbol of the earliest RS time in the first time set; the first time set includes at least one RS time in the first resource set; the first time-domain resource terminates with the last symbol of the physical layer channel carrying the first channel information report.

[0505] As one embodiment, the first channel information report is a periodic channel information report or a non-initial semi-persistent channel information report; the first time domain resource begins with the first symbol of the earliest RS time in the first time set; the first time set includes some or all RS time of the CSI reference resource in the first resource set that is no later than the first channel information report; the first time domain resource terminates with the last symbol of the physical layer channel carrying the first channel information report.

[0506] Typically, the last symbol refers to the latest symbol.

[0507] Examples 8A-8B

[0508] Examples 8A-8B respectively illustrate schematic diagrams of the total number of processing resources occupied by the first channel information reporting in the first time domain resources according to an embodiment of this application; as shown in the attached diagrams. Figures 8A-8B As shown. In the appendix Figures 8A-8B In the first time domain resource, processing resources #1, ..., processing resources #M are the M processing resources occupied by the first channel information reporting in the first time domain resource.

[0509] In Example 8A, the first channel information reporting occupies M processing resources in the first time domain resources, where M is a positive integer; M depends on the size of the first time domain resources.

[0510] In embodiment 8B, the first channel information reporting occupies M processing resources in the first time domain resources, where M is a positive integer; M depends on the size of the first time domain resources; the generation of the first channel information reporting corresponds to a first identifier, and M also depends on the first identifier.

[0511] As an example, the value of M depends on the first identifier.

[0512] As an example, the range of candidate values ​​for M depends on the first identifier.

[0513] As one embodiment, the relationship between M and the size of the first time-domain resource depends on the first identifier.

[0514] As an example, the value of M is specific to the first identifier.

[0515] As an example, the range of candidate values ​​for M is specific to the first identifier.

[0516] As an example, the relationship between M and the size of the first time-domain resource is relative to the first identifier.

[0517] As an example, when the size of the first time-domain resource is less than the first threshold, M is a first positive integer; when the size of the first time-domain resource is greater than the first threshold, M is a second positive integer; the second positive integer is less than the first positive integer; the generation of the first channel information report corresponds to a first identifier, and the first threshold depends on the first identifier.

[0518] As an example, the N1 positive integers correspond to N1 size ranges, where N1 is a positive integer greater than 1; the size of the first time-domain resource belongs to a first size range, which is one of the N1 size ranges; M is a positive integer among the N1 positive integers corresponding to the first size range; the N integer sets correspond to N identifiers, where N is a positive integer greater than 1; the generation of the first channel information report corresponds to a first identifier, which is one of the N identifiers; the integer set among the N integer sets corresponding to the first identifier includes the N1 positive integers.

[0519] Examples 9A-9B

[0520] Examples 9A-9B respectively illustrate schematic diagrams of M depending on the size of the first temporal resource according to an embodiment of this application; as shown in the appendix. Figures 9A-9B As shown.

[0521] In Embodiment 9A, when the size of the first time-domain resource is less than the first threshold, M is a first positive integer; when the size of the first time-domain resource is greater than the first threshold, M is a second positive integer; the second positive integer is less than the first positive integer.

[0522] As an example, when the size of the first time-domain resource is equal to the first threshold, M is the first positive integer.

[0523] As an example, when the size of the first time-domain resource is equal to the first threshold, M is the second positive integer.

[0524] As an example, the first threshold is a positive integer.

[0525] As an example, the first threshold is a positive real number.

[0526] As an example, the first threshold is configurable.

[0527] As an example, the first threshold is predefined.

[0528] As an example, the first threshold is reported by the first node.

[0529] As an example, the first threshold belongs to the capability information of the first node.

[0530] As one embodiment, the first node sends a second information block, the second information block indicating the first threshold.

[0531] As one embodiment, the second node receives a second information block, which indicates the first threshold.

[0532] As an example, the first node sends a second information block, the second information block indicating at least one of the first threshold, the first positive integer, or the second positive integer.

[0533] As an example, the second node receives a second information block, which indicates at least one of the first threshold, the first positive integer, or the second positive integer.

[0534] As an example, the first positive integer is configurable.

[0535] As an example, the first positive integer is predefined.

[0536] As an example, the first positive integer is reported by the first node.

[0537] As one example, the second positive integer is configurable.

[0538] As an example, the second positive integer is predefined.

[0539] As an example, the second positive integer is reported by the first node.

[0540] In the above method, the first time-domain resource refers to the time during which processing resources are occupied. A longer time for processing resources to be occupied reduces the total number of processing resources required. The advantages include: flexibly adjusting the total number of processing resources based on the duration of occupation allows for more efficient use of processing resources, minimizing the amount of necessary processing resources and reducing energy consumption.

[0541] In Example 9B, N1 positive integers correspond to N1 size ranges, where N1 is a positive integer greater than 1; the size of the first time-domain resource belongs to a first size range, which is one of the N1 size ranges; M is a positive integer among the N1 positive integers that corresponds to the first size range. (See Appendix...) Figure 9BIn this context, size range #1, ..., size range #N1 are the N1 size ranges; positive integers #1, ..., positive integers #N1 are the N1 positive integers.

[0542] As an example, the size of the first time-domain resource belongs to N2 of the N1 size ranges, where N2 is a positive integer greater than 1 and not greater than N1; the N2 positive integers among the N1 positive integers correspond to the N2 size ranges respectively, and M is the minimum value among the N2 positive integers.

[0543] As an example, any one of the N1 size ranges includes one or more positive integers.

[0544] As an example, any one of the N1 size ranges is a positive integer.

[0545] As an example, the N1 positive integers are arranged in ascending order, and the maximum values ​​of the N1 ranges are arranged in descending order.

[0546] As an example, the N1 positive integers are arranged in ascending order, and the minimum values ​​of the N1 size ranges are arranged in descending order.

[0547] As an example, the N1 positive integers are arranged in descending order, and the maximum values ​​of the N1 size ranges are arranged in ascending order.

[0548] As an example, the N1 positive integers are arranged in descending order, and the minimum values ​​of the N1 size ranges are arranged in ascending order.

[0549] As an example, the first reference range and the second reference range are two ranges among the N1 ranges. The first reference range corresponds to the first parameter positive integer among the N1 positive integers, and the second reference range corresponds to the second parameter positive integer among the N1 positive integers. The first reference positive integer is less than the second reference positive integer, and the maximum value in the first reference range is greater than the maximum value in the second reference range.

[0550] As an example, the first reference range and the second reference range are two ranges among the N1 ranges. The first reference range corresponds to the first parameter positive integer among the N1 positive integers, and the second reference range corresponds to the second parameter positive integer among the N1 positive integers. The first reference positive integer is less than the second reference positive integer, and the minimum value in the first reference range is greater than the minimum value in the second reference range.

[0551] As an example, any one of the N1 size ranges is a positive integer; the N1 positive integers are arranged in ascending order, and the N1 size ranges are arranged in descending order.

[0552] As an example, any one of the N1 size ranges is a positive integer; the N1 positive integers are arranged in descending order, and the N1 size ranges are arranged in ascending order.

[0553] As an example, any one of the N1 size ranges is a positive integer; the first reference range and the second reference range are two size ranges among the N1 size ranges, the first reference range corresponds to the first parameter positive integer among the N1 positive integers, and the second reference range corresponds to the second parameter positive integer among the N1 positive integers; the first reference positive integer is less than the second reference positive integer, and the first reference range is greater than the second reference range.

[0554] As an example, in the above method, the processing time is longer, but the total number of processing resources required can be less. The advantages include: flexibly adjusting the total number of processing resources used based on the duration of processing time allows for more efficient use of processing resources, minimizing the amount of necessary processing resources and reducing energy consumption.

[0555] As an example, the N1 positive integers are predefined.

[0556] As an example, the N1 positive integers are configurable.

[0557] As an example, the N1 positive integers are reported by the first node.

[0558] As an example, at least one of the N1 positive integers or N1 size ranges belongs to the capability information of the first node.

[0559] As an example, the first node sends a second information block; the second information block indicates at least one of the N1 positive integers or N1 size ranges.

[0560] As one embodiment, the second node receives a second information block; the second information block indicates at least one of the N1 positive integers or N1 size ranges.

[0561] As one embodiment, the second information block is carried by higher-layer signaling.

[0562] As one example, the second information block includes one or more fields in one or more IEs (information elements).

[0563] As one example, the second information block includes a MAC CE.

[0564] As one embodiment, the second information block includes control information.

[0565] As one embodiment, the second information block includes UCI (uplink control information).

[0566] As one embodiment, the second information block is carried by physical layer signaling.

[0567] As one embodiment, the second information block is carried by physical layer uplink signaling.

[0568] As one embodiment, the second information block is transmitted on a physical layer channel.

[0569] As one embodiment, the second information block is transmitted on the physical layer uplink channel.

[0570] As an example, the second information block is transmitted on PUCCH (Physical Uplink Control Channel).

[0571] As an example, the second information block is transmitted on PUSCH (Physical Uplink Shared Channel).

[0572] As one example, the second information block belongs to the capability information of the first node.

[0573] As one embodiment, the second information block includes the capability information of the first node.

[0574] As one embodiment, the second information block includes one or more capability parameters of the first node.

[0575] As one embodiment, the second information block includes one or more fields in a UE (user equipment) capability IE (information element).

[0576] As one embodiment, the second information block includes one or more fields in one or more UE (user equipment) capability IE (information element).

[0577] As one embodiment, the second information block includes one or more parameters in one or more UE (user equipment) capability IEs.

[0578] As an example, after receiving a UE Capability Enquiry from the network, the first node transmits its own capability information, and the second information block belongs to the first node's capability information.

[0579] As an example, the capability information of the first node includes UECapabilityInformation.

[0580] As an example, the capability information of the first node includes the radio access capability of the first node.

[0581] As an example, the second information block explicitly indicates at least one of the N1 positive integers or N1 size ranges.

[0582] As an example, the second information block implicitly indicates at least one of the N1 positive integers or N1 size ranges.

[0583] As an example, at least one of the N1 positive integers or N1 size ranges depends on the information indicated by the second information block.

[0584] As an example, the second information block indicates a first parameter, wherein at least one of the N1 positive integers or N1 size ranges depends on the value of the first parameter.

[0585] As an example, the value of the first parameter is an integer.

[0586] As an example, the value of the first parameter is a real number.

[0587] As an example, the value of the first parameter is a character or a string.

[0588] As an example, at least one of the N1 positive integers or N1 size ranges has a linear relationship with the first parameter.

[0589] As an example, at least one of the N1 positive integers or N1 size ranges has a non-linear relationship with the first parameter.

[0590] As an example, at least one of the N1 positive integers or N1 size ranges is mapped to the value of the first parameter.

[0591] As an example, the calculation formula for at least one of the N1 positive integers or N1 size ranges depends on the first parameter.

[0592] As an example, the calculation formula for at least one of the N1 positive integers or N1 size ranges is linearly related to the first parameter.

[0593] As an example, the calculation formula for at least one of the N1 positive integers or N1 size ranges and the first parameter have a non-linear relationship.

[0594] Example 10

[0595] Example 10 illustrates a schematic diagram of the relationship between a first threshold and a first identifier according to an embodiment of this application; as attached. Figure 10 As shown.

[0596] In Example 10, the generation of the first channel information report corresponds to a first identifier, and the first threshold depends on the first identifier.

[0597] As an example, the first threshold is for the first identifier.

[0598] As one example, the first threshold is predefined for the first identifier.

[0599] As an example, the first threshold is configured for the first identifier.

[0600] As an example, the first threshold is for the first identifier reported by the first node.

[0601] As an example, the N thresholds correspond to N identifiers, where N is a positive integer greater than 1; the generation of the first channel information report corresponds to the first identifier, which is one of the N identifiers; the first threshold is a threshold among the N thresholds that corresponds to the first identifier.

[0602] As an example, at least one of the N thresholds or the N identifiers is predefined.

[0603] As an example, at least one of the N thresholds or the N identifiers is configurable.

[0604] As an example, at least one of the N thresholds or the N identifiers is reported by the first node.

[0605] As an example, at least one of the N thresholds or the N identifiers belongs to the capability information of the first node.

[0606] As an example, the first node sends a second information block, which indicates at least one of the N thresholds or the N identifiers.

[0607] As an example, the second node receives a second information block, which indicates at least one of the N thresholds or the N identifiers.

[0608] As an example, any one of the N identifiers is a non-negative integer.

[0609] As an example, any one of the N identifiers includes one or more characters.

[0610] As an example, any one of the N identifiers is used to identify one or more processing resources.

[0611] As an example, any one of the N identifiers is used to identify a resource group, which includes one or more processing resources.

[0612] As an example, any one of the N identifiers is different from the reporting configuration identifier of the first channel information report.

[0613] As an example, any one of the N identifiers is used to identify the AI ​​model.

[0614] As an example, any one of the N identifiers is used to identify the inference used to generate channel information reports.

[0615] As an example, any one of the N identifiers is used to identify the AI ​​entity.

[0616] As an example, any one of the N identifiers is used to identify the AI ​​function.

[0617] As an example, the advantages of the above method include that by identifying N AI models / entities / functions respectively through the N identifiers, the design is simplified and the understanding of different AI entities or functions is unified across multiple nodes.

[0618] As an example, any one of the N identifiers is used to identify or indicate a set of resources.

[0619] As an example, any one of the N identifiers is used to identify or indicate a resource set, and the measurement of the resource set is used to obtain a training dataset.

[0620] As an example, any one of the N identifiers is used to identify or indicate a resource set, and the resource set identified or indicated by any one of the N identifiers includes one or more RS resources.

[0621] As an example, any one of the N identifiers is used to identify or indicate the training dataset.

[0622] As an example, the benefits of the above method include identifying the inference generated by an AI training or AI training dataset by identifying the AI ​​training or AI training dataset, establishing consensus among different AI functions, and further simplifying the design.

[0623] Example 11

[0624] Example 11 illustrates a schematic diagram of the relationship between N1 positive integers and a first identifier according to an embodiment of this application; as shown in the appendix. Figure 11 As shown.

[0625] In Example 11, the N integer sets correspond to N identifiers, where N is a positive integer greater than 1; the generation of the first channel information report corresponds to a first identifier, which is one of the N identifiers; the integer set corresponding to the first identifier in the N integer sets includes the N1 positive integers. (See Appendix...) Figure 10 In the above, identifiers #1, ..., #n, ..., #N are the N identifiers; integer sets #1, ..., #n, ..., #N are the N integer sets.

[0626] As an example, at least one of the N integer sets or the N identifiers is predefined.

[0627] As an example, at least one of the N integer sets or the N identifiers is configurable.

[0628] As an example, at least one of the N integers or the N identifiers is reported by the first node.

[0629] As an example, at least one of the N integer sets or the N identifiers belongs to the capability information of the first node.

[0630] As an example, the first node sends a second information block, which indicates at least one of the N integer sets or the N identifiers.

[0631] As one embodiment, the second node receives a second information block, which indicates at least one of the N integer sets or the N identifiers.

[0632] As an example, any one of the N integer sets includes one or more positive integers.

[0633] As an example, any one of the N integer sets includes one or more non-negative integers.

[0634] Examples 12A-12C

[0635] Examples 12A-12C respectively illustrate schematic diagrams of generating a corresponding first identifier in the first channel information reporting according to an embodiment of this application; as attached Figures 12A-12C As shown.

[0636] In embodiment 12A, the generation of the first channel information report corresponding to the first identifier includes: a first information block is used to configure the first channel information report, and the first information block indicates the first identifier.

[0637] In the above method, the generation of the first channel information report corresponds to the first identifier indicated by the first information block.

[0638] As an example, the advantages of the above method include: simplified design, and the ability to flexibly configure the corresponding first identifier for the first channel information reporting.

[0639] In embodiment 12B, the generation of the first channel information report corresponding to the first identifier includes: the first node or the generator of the first channel information report performing a first operation, the first channel information report depending on the output of the first operation, and the first operation corresponding to the first identifier.

[0640] As an example, the generation of the first channel information report corresponding to the first identifier includes: the first node or the generator of the first channel information report performing a first operation, the first operation including inference, the first channel information report depending on the output of the first operation, and the first operation corresponding to the first identifier.

[0641] As an example, the first operation is based on training or AI.

[0642] As an example, the first operation includes inference.

[0643] As one example, the first operation includes an AI entity.

[0644] As an example, the first operation includes an AI entity for inference.

[0645] As an example, the first operation includes a portion of an AI entity.

[0646] As an example, the first operation includes a portion of an AI entity used for inference.

[0647] As one embodiment, the first operation includes inference for obtaining the first channel information report.

[0648] As an example, the reasoning includes AI (Artificial Intelligence) inference.

[0649] As an example, the first operation includes AI inference for obtaining CSI.

[0650] As one example, the first operation includes AI inference for obtaining channel information.

[0651] As one example, the first operation includes AI inference for obtaining information other than channel information.

[0652] As an example, the first operation is used for an AI function.

[0653] As an example, the first operation is performed by the physical layer of the first node.

[0654] As an example, the first operation is performed at a higher level than the first node.

[0655] As an example, the model for the first operation is obtained through training.

[0656] As an example, the training for the first operation is performed by the first node.

[0657] As an example, the training for the first operation is performed by the target receiver that reports the first channel information.

[0658] As an example, the training for the first operation is performed by the core network.

[0659] As an example, the training of the first operation is performed by an AI training producer.

[0660] As an example, the training of the first operation is performed by the MDA function (Management Data Analytics Function).

[0661] As an example, the training of the first operation is performed by the MDA function located at the first node.

[0662] As an example, the training of the first operation is performed by the MDA function of the target receiver where the first channel information is reported.

[0663] As an example, the training of the first operation is performed by NWDAF (NetworkDataAnalyticsFunction).

[0664] As an example, the training of the first operation is performed by the MDAS (Management Data Analytics Service) producer.

[0665] As an example, the training of the first operation is performed by the MnS (Management Service) producer.

[0666] As an example, the first operation requires deployment.

[0667] As an example, the first operation is obtained by loading.

[0668] As an example, the first operation is obtained from the serving cell of the first node.

[0669] As an example, the first operation is obtained from the sustaining base station of the serving cell of the first node.

[0670] As an example, the first node deploys the first operation.

[0671] As an example, the first operation does not require deployment.

[0672] As an example, the first operation is obtained from the core network.

[0673] As an example, the first operation is based on artificial intelligence or machine learning.

[0674] As an example, the first operation is based on a neural network.

[0675] As an example, the first operation is based on CNN (Conventional Neural Networks).

[0676] As one example, the first operation includes preprocessing.

[0677] As one example, the first operation includes post-processing.

[0678] As one example, the post-processing includes DFT.

[0679] As one example, the post-processing includes quantization.

[0680] As an example, the post-processing includes one or more of the following: angular domain to spatial domain transformation, spatial domain to angular domain transformation, time domain to frequency domain transformation, and frequency domain to time domain transformation.

[0681] As one example, the post-processing includes truncation and / or padding.

[0682] As an example, the first operation includes one or more of convolution, pooling, cascading, and activation.

[0683] As one embodiment, the first operation includes a fully connected layer.

[0684] As an example, the first operation includes a pooling layer.

[0685] As an example, the first operation includes at least one convolutional layer.

[0686] As an example, the first operation includes at least one encoding layer.

[0687] As an example, an encoding layer includes at least one convolutional layer and one pooling layer.

[0688] As an example, in a convolutional layer, at least one convolutional kernel is used to convolve the input to generate a corresponding feature map, and at least one feature map output by the convolutional layer is reshaped into a vector and input to a fully connected layer; the fully connected layer transforms the vector into an output.

[0689] As an example, some or all of the following parameters in the first operation—convolution kernel size, number of convolutional layers, convolution stride, pooling kernel size, pooling kernel stride, pooling function, activation function, and number of feature maps—are obtained through training.

[0690] As an example, some or all of the convolution kernel, pooling kernel, pooling function, activation function, parameters of the pooling function, and parameters of the activation function in the first operation are obtained through training.

[0691] As an example, the output of the first operation includes channel information.

[0692] As an example, the output of the first operation includes information other than channel information.

[0693] As an example, the output of the first operation includes a channel matrix.

[0694] As an example, the output of the first operation includes CSI.

[0695] As an example, the output of the first operation includes compressed CSI.

[0696] As an example, the output of the first operation includes non-codebook-based CSI.

[0697] As an example, the output of the first operation includes a channel impulse response.

[0698] As an example, the output of the first operation includes small-scale characteristics.

[0699] As an example, the output of the first operation is used to determine one or more precoding matrices.

[0700] As an example, the first operation includes CSI compression based on artificial intelligence or machine learning.

[0701] As an example, the first operation includes an encoder for CSI compression based on artificial intelligence or machine learning.

[0702] As an example, the first operation includes CSI prediction or CSI estimation based on artificial intelligence or machine learning.

[0703] As one example, the first operation includes beam management based on artificial intelligence or machine learning.

[0704] As one embodiment, the beam management includes at least one of beam prediction, beam switching, beam failure prediction, or beam failure recovery.

[0705] As an example, the input to the first operation includes measurements obtained based on at least one RS resource.

[0706] As an example, the input to the first operation includes channel measurements obtained based on CSI-RS resources or SS / PBCH block resources.

[0707] As an example, the input to the first operation includes interference measurements obtained based on CSI-RS resources or CSI-IM resources.

[0708] As an example, the input to the first operation includes the reception quality of at least one physical channel or physical signal.

[0709] As an example, the input to the first operation includes a matrix or vector obtained by preprocessing the channel matrix obtained from measurements based on at least one RS resource.

[0710] As one example, the AI ​​function includes AI inference functionality.

[0711] As one example, the AI ​​functionality includes AI training functionality.

[0712] As one example, the AI ​​functionality includes AI management functionality.

[0713] As one example, the AI ​​function includes AI performance monitoring.

[0714] As one example, the AI ​​includes ML (Machine Learning).

[0715] As one example, the AI ​​includes AI and ML.

[0716] As one example, the AI ​​includes AI or ML.

[0717] As an example, the preprocessing includes one or more of the following: quantization, DFT (Discrete Fourier Transform), matrix decomposition, matrix transformation or projection, spatial-to-angular-domain transformation, angular-to-spatial-domain transformation, frequency-to-time-domain transformation, time-to-frequency-domain transformation, truncation, padding, mapping, or labeling.

[0718] As an example, the preprocessing includes DFT (Discrete Fourier Transform).

[0719] As one example, the preprocessing includes one or more of matrix decomposition, matrix transformation, or projection.

[0720] As an example, the preprocessing includes one or more of the following: quantization, spatial-to-angular-domain transformation, angular-to-spatial-domain transformation, frequency-to-time-domain transformation, or time-to-frequency-domain transformation.

[0721] As one example, the preprocessing includes truncation and / or padding.

[0722] As one example, the preprocessing includes mapping.

[0723] As one example, the preprocessing includes mapping to vectors.

[0724] As one example, the preprocessing includes labeling.

[0725] As an example, the label refers to a mark made with a label.

[0726] As one example, the post-processing includes DFT.

[0727] As one example, the post-processing includes quantization.

[0728] As an example, the post-processing includes one or more of the following: angular domain to spatial domain transformation, spatial domain to angular domain transformation, time domain to frequency domain transformation, and frequency domain to time domain transformation.

[0729] As one example, the post-processing includes truncation and / or padding.

[0730] As an example, an encoding layer includes at least one convolutional layer and one pooling layer.

[0731] As an example, in a convolutional layer, at least one convolutional kernel is used to convolve the input to generate a corresponding feature map, and at least one feature map output by the convolutional layer is reshaped into a vector and input to a fully connected layer; the fully connected layer transforms the vector into an output.

[0732] As one embodiment, the first operation corresponding to the first identifier includes: the first operation being identified by the first identifier.

[0733] As an example, the first operation corresponding to the first identifier includes: the AI ​​model used in the first operation is identified by the first identifier.

[0734] As one embodiment, the first operation corresponding to the first identifier includes: the AI ​​entity included in the first operation is identified by the first identifier.

[0735] As one embodiment, the first operation corresponding to the first identifier includes: the AI ​​function to which the first operation is used is identified by the first identifier.

[0736] As an example, the advantages of the above method include that identifying an AI entity or function through the first identifier simplifies the design and unifies the understanding of different AI entities or functions across multiple nodes.

[0737] As one embodiment, the first operation corresponding to the first identifier includes: the AI ​​entity performing the first operation is identified by the first identifier.

[0738] As one embodiment, the first operation corresponding to the first identifier includes: the first identifier is used by the first node to determine the AI ​​model adopted by the first operation.

[0739] As an example, the advantages of the above method include that identifying an AI model / entity / function through the first identifier simplifies the design and unifies the understanding of different AI entities / functions across multiple nodes.

[0740] As one embodiment, the first operation corresponding to the first identifier includes: the first identifier is used to identify or indicate a set of RS resources, and the measurement of the set of RS resources is used to obtain a training dataset for the first operation.

[0741] As one embodiment, the first operation corresponding to the first identifier includes: obtaining the training for the first operation identified by the first identifier.

[0742] As one embodiment, the first operation corresponding to the first identifier includes: the dataset used for training the first operation is identified by the first identifier.

[0743] As an example, the benefits of the above method include identifying the inference generated by an AI training or AI training dataset by identifying the AI ​​training or AI training dataset, establishing consensus among different AI functions, and further simplifying the design.

[0744] As one embodiment, the first operation corresponding to the first identifier includes: the first operation performs spatial beam prediction for a second resource set based on measurements of a first resource set, the second resource set depending on the first identifier.

[0745] As an example, the advantages of the above method include reduced RS overhead and reduced feedback latency.

[0746] As one embodiment, the first operation corresponding to the first identifier includes: the first operation performs channel information prediction for a second resource set based on the measurement of a first resource set, the second resource set depending on the first identifier.

[0747] As one embodiment, the first operation corresponding to the first identifier includes: the first operation performs temporal beam prediction for a second resource set based on historical measurements of a first resource set, the second resource set depending on the first identifier.

[0748] As an example, the advantages of the above method include reducing beam feedback delay and improving the real-time performance of beam acquisition.

[0749] As one embodiment, the first operation corresponding to the first identifier includes: the first operation predicts temporal channel information for a second resource set based on historical measurements of a first resource set, the second resource set depending on the first identifier.

[0750] As an example, the advantages of the above method include reducing channel information feedback delay and improving the real-time performance of channel information acquisition.

[0751] As an example, the output of the first operation is used to generate the first channel information report.

[0752] As an example, the first channel information report includes the output of the first operation.

[0753] As an example, the first channel information report includes the post-processed output of the first operation.

[0754] As one embodiment, the first channel information report includes the truncated and / or quantized output of the first operation.

[0755] As an example, the output of the first operation, after post-processing, is used to generate the first channel information report.

[0756] As an example, the output of the first operation, after being truncated and / or quantized, is used to generate the first channel information report.

[0757] As an example, some or all of the output of the first operation, after post-processing, is used to generate the first channel information report.

[0758] As an example, some or all of the output of the first operation, after being truncated and / or quantized, is used to generate the first channel information report.

[0759] As an example, the output of the first operation includes a first CSI, which is used to generate the first channel information report.

[0760] As an example, the advantages of the above method include improved CSI reporting performance by leveraging the advantages of the first operation, including more accurate reporting and / or lower overhead.

[0761] As one example, how to generate the first channel information report based on the first operation is determined by the manufacturer of the first node, or is implementation-related. A typical but non-limiting implementation is described below:

[0762] The first node first measures the RS resources used for channel measurement to obtain the channel parameter matrix H. r×t Where r and t are the number of receiving antennas and the number of antenna ports, respectively; at least the channel parameter matrix H r×t Alternatively, its feature vector is input into an AI model, and the output of the AI ​​model is used to obtain the first channel information report.

[0763] If the first channel information reporting requires the first node to estimate interference (including noise), the first node can measure the RS resources used for interference measurement to obtain the measured interference.

[0764] In one implementation, measurement interference is also input into the AI ​​model.

[0765] In another implementation, the measurement interference is not input into the AI ​​model; the output of the AI ​​model and the measurement interference are used together to generate the first channel information report.

[0766] Without loss of generality, the AI ​​model or the parameters of the AI ​​model used to generate the first channel information report are determined by the manufacturer of the first node.

[0767] In embodiment 12C, the generation of the first channel information report corresponding to the first identifier includes: the generation of the first channel information report uses an AI model identified by the first identifier, or the first channel information report is generated in an AI entity identified by the first identifier, or the first channel information report is used for an AI function identified by the first identifier.

[0768] As an example, the generation of the first channel information report corresponding to the first identifier includes: the first identifier is used to identify an AI model, and the first channel information report is generated based on inference using the AI ​​model identified by the first identifier.

[0769] As an example, the generation of the first channel information report uses an AI model identified by the first identifier.

[0770] As an example, the first channel information report is generated in the AI ​​entity identified by the first identifier.

[0771] As an example, the first channel information report is used for the AI ​​function identified by the first identifier.

[0772] As an example, the advantages of the above method include: better adaptability to various application scenarios or terminals, and good flexibility and adaptability.

[0773] Examples 13A-13B

[0774] Examples 13A-13B respectively illustrate schematic diagrams of the deployment of the first operation of the first node according to an embodiment of this application; as shown in the attached figures. Figures 13A-13B As shown.

[0775] In Example 13A, the first node requests the first producer to load the first operation and obtains the first operation from the first producer.

[0776] As one embodiment, the deployment includes obtaining the first operation.

[0777] As one example, the deployment includes obtaining an AI entity.

[0778] As one example, the deployment includes obtaining an AI entity that performs the first operation.

[0779] As one example, the deployment includes obtaining an AI entity that includes AI functions to perform the first operation.

[0780] As one example, the deployment includes loading the first operation.

[0781] As one example, the deployment includes submitting a request to load the first operation.

[0782] As an example, the first operation is obtained from the serving cell of the first node.

[0783] As an example, the first operation is obtained from the sustaining base station of the serving cell of the first node.

[0784] As an example, the first operation is obtained from the core network.

[0785] As an example, the first operation is obtained from loading from the first producer.

[0786] As an example, the deployment is accomplished by an AI function.

[0787] As an example, the deployment is accomplished by AI functionality deployed on the first node.

[0788] As an example, the deployment is accomplished by an AI deployment function.

[0789] As an example, the deployment is accomplished by the AI ​​deployment function deployed on the first node.

[0790] As an example, the deployment is accomplished by AI inference functionality.

[0791] As an example, the deployment is accomplished by an AI inference function deployed on the first node.

[0792] As an example, the deployment is performed by an AI entity.

[0793] As an example, the deployment is performed by an AI entity deployed on the first node.

[0794] As an example, the deployment is performed by an AI entity with a deployment function.

[0795] As an example, the deployment is performed by an AI entity with deployment capabilities deployed on the first node.

[0796] As an example, the deployment is performed by an AI entity with an inference function.

[0797] As an example, the deployment is performed by an AI entity with reasoning capabilities deployed on the first node.

[0798] As one embodiment, the deployment includes obtaining the first operation from a first producer.

[0799] As one embodiment, the deployment includes requesting a first producer to load the first operation.

[0800] As one embodiment, the deployment includes loading the first operation from the first producer.

[0801] As an example, the first producer generates and provides the AL entity.

[0802] As an example, the first producer generates and provides AL functionality.

[0803] As an example, the first producer is the producer of the first operation.

[0804] As an example, the first producer includes an AL entity producer.

[0805] As one example, the first producer includes an AL function producer.

[0806] As one example, the first producer includes an AL deployment producer.

[0807] As one example, the first producer includes an AL loading producer.

[0808] As one example, the first producer includes an AL-trained producer.

[0809] As an example, the first producer includes an AL inference producer.

[0810] As an example, the first producer includes the producer of the AL entity deployment.

[0811] As one example, the first producer includes the producer that loads the AL entity.

[0812] As an example, the first producer includes an MnS (Management Service) producer.

[0813] In one embodiment, the sender of the first information block is the first producer.

[0814] As an example, the sender of the first information block is different from the first producer.

[0815] As an example, the training for obtaining the first operation is performed by the first producer.

[0816] As an example, the executor used to obtain the training for the first operation is different from the first producer.

[0817] As one example, the AI ​​includes ML (Machine Learning).

[0818] In Example 13B, the first node requests the second producer to load the first operation and obtains the first operation from the first producer.

[0819] As one embodiment, the deployment includes obtaining the first operation.

[0820] As one example, the deployment includes obtaining an AI entity or AI function to perform the first operation.

[0821] As one example, the deployment includes loading the first operation.

[0822] As one example, the deployment includes submitting a request to load the first operation.

[0823] As an example, the deployment is accomplished by AI functionality deployed on the first node.

[0824] As an example, the deployment is accomplished by the AI ​​deployment function deployed on the first node.

[0825] As an example, the deployment is performed by an AI entity with a deployment function.

[0826] As one example, the second producer generates and provides AI entities or AI functions.

[0827] As one example, the second producer includes an MnS (Management Service) producer.

[0828] As an example, the second producer includes the producer of the AI ​​model training.

[0829] In one embodiment, the second producer is the target receiver of the first channel information report.

[0830] In one embodiment, the second producer is different from the target receiver that reported the first channel information.

[0831] As one example, the second producer is the serving cell of the first node.

[0832] As one example, the second producer is the maintenance base station of the serving cell of the first node.

[0833] As one example, the second producer is the core network.

[0834] As an example, the first operation is obtained from the serving cell of the first node.

[0835] As an example, the first operation is obtained from the sustaining base station of the serving cell of the first node.

[0836] As an example, the first operation is obtained from the core network.

[0837] As an example, the training for obtaining the first operation is performed by the second producer.

[0838] As an example, the second producer is different from the first producer.

[0839] As an example, the first producer generates and provides the AL entity.

[0840] As an example, the first producer generates and provides AL functionality.

[0841] As an example, the first producer is the producer of the first operation.

[0842] As an example, the first producer includes an AL entity producer.

[0843] As one example, the first producer includes an AL function producer.

[0844] As one example, the first producer includes an AL deployment producer.

[0845] As one example, the first producer includes an AL loading producer.

[0846] As one example, the first producer includes an AL-trained producer.

[0847] As an example, the first producer includes an AL inference producer.

[0848] As an example, the first producer includes the producer of the AL entity deployment.

[0849] As one example, the first producer includes the producer that loads the AL entity.

[0850] As an example, the first producer includes an MnS (Management Service) producer.

[0851] Example 14

[0852] Example 14 illustrates a schematic diagram of the deployment of AI / ML functionality in a RAN (Radio Access Network) domain according to an embodiment of this application; as shown in the attached diagram. Figure 14 As shown. In Example 14, the gNB can be replaced with, for example, an eNB, or a network device such as a 6G base station.

[0853] AI / ML related functions include ML training (also known as AI training, or AI / ML training), ML testing, and ML inference (also known as AI inference, or AI / ML inference), etc. ML training, ML testing, and ML inference functions can be deployed independently or co-located. Deployment of AI / ML related functions can be implemented through software, such as downloading and / or running executable files; or it can be implemented through a combination of software and hardware, such as accelerating specific computing units through hardware to improve computing speed or save power.

[0854] ML training functions can be deployed in a cross-domain management system or a domain-specific management system; the domain-specific management system is used to manage the RAN domain or the CN (Core Network) domain. For example, ML training functions for MDA (Management Data Analytics) can be deployed in MDAF (MDA Function); ML training for network data analytics can be deployed in NWDAF (Network Data Analytics Function), meaning the ML training function is an MTLF (Model Training Logical Function).

[0855] The ML inference function can also be deployed in a cross-domain management system or a domain-specific management system; for example, the ML inference function is MDAF, or the ML inference function is AnLF (Analytics logical function) located in NWDAF.

[0856] Similarly, ML testing capabilities can also be deployed in cross-domain management systems or domain-specific management systems.

[0857] In Example 14, the RAN domain ML training function 1402 is located in the RAN domain management function 1403; while the ML inference function is located in the base station, that is, the AI / ML inference function 1404 is located in gNB 1405, the AI / ML inference function 1406 is located in gNB 1407, and so on.

[0858] Appendix Figure 14 In this context, the management of ML inference functions across multiple base stations is handled by the RAN domain management function 1403, which interacts with the RAN domain MnS (Management Service) consumer / cross-domain management 1401 (as shown in the attached diagram). Figure 14 (As shown by the dashed arrow in the image).

[0859] Optionally, the management of ML inference function can also be completed by the base station itself, that is, each base station can independently interact with the RAN domain MnS consumer / cross-domain management 1401.

[0860] It should be noted that Example 14 is merely a non-limiting implementation; optionally, the ML training function of the RAN domain may also be deployed at the base station; or optionally, some base stations may deploy both the ML inference function and the ML training function of the RAN domain, while some base stations may only deploy the ML inference function.

[0861] As an example, one of the gNBs (or base stations) in Example 14 is the second node of this application.

[0862] As one embodiment, the second processor in this application includes an appendix. Figure 14 One of the AL / ML inference functions, namely 1404 or 1406.

[0863] Example 15

[0864] Example 15 illustrates a schematic diagram of the deployment of AI / ML functions in a UE according to an embodiment of this application; as shown in the appendix. Figure 15 As shown. (Attached) Figure 15 The RAN domain ML training function 1505 is optional.

[0865] UE function 1504 is deployed in the first node of this application, and the UE function 1504 includes AI / ML inference function 1506; the AI / ML inference function 1506 uses an ML model (also called an AI model) for inference; an ML model is typically trained before being used for AI / ML inference.

[0866] As an example, the first channel information report in this application is obtained through inference by the AI / ML inference function 1506.

[0867] As one embodiment, the first processor in this application includes an appendix. Figure 15 One of the AL / ML inference functions is 1506.

[0868] As an example, the UE function 1504 includes a RAN domain ML training function 1505, which runs training data through an ML model to obtain a relevant loss and adjusts the parameters of the ML model based on the calculated loss; the ML training includes at least one of ML initial training, ML re-training, and reinforcement learning.

[0869] The above embodiments can reduce the complexity of the base station, or save air interface resources caused by reporting training data; however, the above embodiments place high demands on the processing capabilities of the UE side.

[0870] Optionally, the UE function 1504 also includes a CN domain ML training function ( Figure 15 (Not included in the text).

[0871] Optionally, the UE function 1504 also includes an AI / ML deployment function. Figure 15 It is not included in the list, which is used to load ML models and data.

[0872] As an example, the first node indicates whether it supports ML training function (RAN domain or CN domain) through capability reporting. The capability reporting is RRC signaling or NAS (Non-Access Stratum) signaling.

[0873] As an example, the ML model and the associated metadata are loaded by the first node from a network device or a remote server.

[0874] Optionally, the UE function 1504 is an MnS (Management Service) producer that provides data to the CN domain MnF (Management Function) 1501, and / or the RAN domain MnF 1502, and / or the cross-domain management system 1503 for management or analysis (as shown by double arrow 1507).

[0875] Optionally, the UE function 1504 is an MnS consumer that loads data from the CN domain MnF (Management Function) 1501, and / or the RAN domain MnF 1502, and / or the cross-domain management system 1503 for AI / ML-related management, such as managing data requests, ML model activation, and / or ML training (as shown by double arrow 1507).

[0876] As an example, the ML model is based on a neural network.

[0877] As an example, the ML model is based on CNN (Conventional Neural Networks).

[0878] As an example, the ML model is based on the Transformer architecture.

[0879] Example 16

[0880] Example 16 illustrates a schematic diagram of a processing system based on artificial intelligence or machine learning according to an embodiment of this application; as shown in the appendix. Figure 16 As shown. (Attached) Figure 16 (a) Includes the third, fourth, and fifth processors, with appendices Figure 16 (b) Includes the third, fourth, fifth and sixth processors.

[0881] In Example 16(a), the third processor sends a first dataset to the fourth processor and a second dataset to the fifth processor; the fourth processor generates a target first-class parameter set based on the first dataset, and sends the generated target first-class parameter set to the fifth processor; the fifth processor processes the second dataset using the target first-class parameter set to obtain a first-class output. (See Appendix...) Figure 16 (a) The first type of feedback is optional.

[0882] In Example 16(b), the third processor sends a first dataset to the fourth processor and a second dataset to the fifth processor; the fourth processor generates a target first-class parameter set based on the first dataset, and sends the generated target first-class parameter set to the fifth processor; the fifth processor processes the second dataset using the target first-class parameter set to obtain a first-class output, and sends the first-class output to the sixth processor. (See Appendix...) Figure 16 (b) First type of feedback and second type of feedback are optional.

[0883] As an example, Appendix Figure 16 In (a), the fifth processor sends the first type of output to the second node in this application.

[0884] As an example, Appendix Figure 16 (a) Using a single-side AI model, the fifth processor performs the first operation in this application.

[0885] As an example, Appendix Figure 16 (b) Using a two-sided AI model, the fifth processor performs the first operation in this application, and the sixth processor includes the second operation in this application.

[0886] As an example, the AI ​​includes ML (Machine Learning) inference.

[0887] As an example, the fifth processor performs the first operation in this application.

[0888] As one embodiment, the sixth processor includes the second operation described in this application.

[0889] As an example, the fifth processor sends a first type of feedback to the fourth processor, and the first type of feedback is used to trigger a recalculation or update of the target first type of parameter group.

[0890] As one embodiment, the sixth processor sends a second type of feedback to the third processor, the second type of feedback being used to generate the first dataset or the second dataset, or the second type of feedback being used to trigger the sending of the first dataset or the second dataset.

[0891] As one embodiment, the third processor generates the first dataset and the second dataset based on measurements of a first type of wireless signal, the first type of wireless signal including downlink RS.

[0892] As one embodiment, the fifth processor belongs to the first node, and the sixth processor belongs to the second node.

[0893] As an example, the first channel information report belongs to the first type of output.

[0894] As an example, the second dataset includes the input of the first operation.

[0895] As an example, for the first operation in this application, the second dataset includes information obtained based on the first information block.

[0896] As an example, the first dataset includes training data.

[0897] As an example, the fourth processor belongs to the producer of the first operation.

[0898] As one embodiment, the fourth processor includes an AI training producer.

[0899] As one embodiment, the fourth processor includes an AI training function.

[0900] As an example, the fourth processor is used for model training, and the trained model is described by the target first class of parameter sets.

[0901] As an example, the fourth processor belongs to the first node.

[0902] The above embodiments avoid passing the first dataset to the second node.

[0903] As one example, the fourth processor belongs to the second node.

[0904] The above embodiments support joint training and optimize system performance.

[0905] As an example, the fourth processor belongs to the core network.

[0906] The above embodiments support network-wide joint training, further optimizing system performance.

[0907] As an example, the second dataset includes inference data.

[0908] As one embodiment, the fifth processor includes an AI inference producer.

[0909] As one embodiment, the fifth processor includes an AI inference function.

[0910] As an example, the fifth processor belongs to the first node.

[0911] As an example, the fifth processor constructs a model based on the target first type of parameter group, and then inputs the second dataset into the constructed model to obtain the first type of output.

[0912] As an example, the first operation is described by the target first type of parameter group.

[0913] As an example, the target first type of parameter group is used to construct the first operation.

[0914] As one embodiment, the fifth processor includes the second operation.

[0915] As an example, the fifth processor generates a recovery dataset based on the first type of output, and the error between the recovery dataset and the second dataset is used to generate the first type of feedback.

[0916] As a sub-example of the above embodiment, the generation of the recovery dataset adopts a similar operation to the second one.

[0917] As an example, the first type of feedback is used to reflect the performance of the trained model; when the performance of the trained model fails to meet the requirements, the fourth processing opportunity recalculates the target first type of parameter set.

[0918] As an example, when the error is too large or the update has not been performed for too long, the performance of the trained model is considered to be unsatisfactory.

[0919] As an example, the target first type of parameter group includes one or more of the following: convolution kernel size, number of convolution layers, convolution stride, pooling kernel size, pooling kernel stride, pooling function, activation function, or number of feature maps.

[0920] As an example, the target first type of parameter group includes one or more of the following: convolution kernel, pooling kernel, pooling function, activation function, parameters of pooling function, or parameters of activation function.

[0921] Example 17

[0922] Example 17 illustrates a structural block diagram of a processing apparatus for a first node according to an embodiment of this application; as shown in the appendix. Figure 17 As shown. In the appendix Figure 17 In the first node, the processing device 1800 includes a first processor 1801.

[0923] As one example, the first node is a user equipment.

[0924] As an example, the first node is a relay node device.

[0925] As an example, the first processor 1801 includes at least one of the following in embodiment 4: {antenna 452, receiver / transmitter 454, receiver processor 456, transmitter processor 468, multi-antenna receiver processor 458, multi-antenna transmitter processor 457, controller / processor 459, memory 460, data source 467}.

[0926] The first processor 1801 receives RS from the first resource set and sends the first channel information report.

[0927] In embodiment 17, the first resource set includes at least one RS resource used for at least one of channel measurement or interference measurement in the first channel information reporting; the first channel information reporting occupies M processing resources in the first time domain resources, where M is a positive integer; M depends on the size of the first time domain resources.

[0928] As an example, M depends on the size of the first time-domain resource only when the first condition is met; the first condition includes at least one of the following: the first channel information report is generated based on inference or the first channel information report generates a corresponding first identifier.

[0929] As an example, the generation of the first channel information report corresponds to a first identifier, and M also depends on the first identifier.

[0930] As an example, when the size of the first time-domain resource is less than a first threshold, M is a first positive integer; when the size of the first time-domain resource is greater than the first threshold, M is a second positive integer; the second positive integer is less than the first positive integer.

[0931] As an example, the generation of the first channel information report corresponds to a first identifier, and the first threshold depends on the first identifier.

[0932] As an example, the N1 positive integers correspond to N1 size ranges, where N1 is a positive integer greater than 1; the size of the first time-domain resource belongs to a first size range, which is one of the N1 size ranges; and M is a positive integer among the N1 positive integers that corresponds to the first size range.

[0933] As an example, the N integer sets correspond to N identifiers, where N is a positive integer greater than 1; the generation of the first channel information report corresponds to a first identifier, which is one of the N identifiers; the integer set corresponding to the first identifier in the N integer sets includes the N1 positive integers.

[0934] As one embodiment, it includes:

[0935] The first processor 1801 receives the first signaling;

[0936] The first channel information reporting is triggered by the first signaling; the first time domain resource starts after the physical layer channel carrying the first signaling, or the first time domain resource starts after the first symbol of the physical layer channel carrying the first signaling.

[0937] As an example, the first time-domain resource begins with the first symbol of the earliest RS time in the first time set; the first time set includes at least one RS time in the first resource set.

[0938] As an example, the first time-domain resource terminates at the last symbol of the physical layer channel carrying the first channel information report.

[0939] As one embodiment, it includes:

[0940] The first processor 1801 receives the first information block;

[0941] The first information block is used to configure the first channel information reporting.

[0942] Example 18

[0943] Example 18 illustrates a structural block diagram of a processing apparatus for a second node according to an embodiment of this application; as shown in the appendix. Figure 18 As shown. In the appendix Figure 18 In the second node, the processing device 1900 includes a second processor 1901.

[0944] In one embodiment, the second node is a base station device.

[0945] In one embodiment, the second node is a user equipment.

[0946] As one embodiment, the second node is a relay node device.

[0947] As an example, the second processor 1901 includes at least one of the following in embodiment 4: {antenna 420, receiver / transmitter 418, receiver processor 470, transmitter processor 416, multi-antenna receiver processor 472, multi-antenna transmitter processor 471, controller / processor 475, memory 476}.

[0948] The second processor 1901 transmits RS in the first resource set and receives the first channel information report.

[0949] In embodiment 18, the first resource set includes at least one RS resource used for at least one of channel measurement or interference measurement in the first channel information reporting; the first channel information reporting occupies M processing resources in the first time domain resources, where M is a positive integer; M depends on the size of the first time domain resources.

[0950] As an example, M depends on the size of the first time-domain resource only when the first condition is met; the first condition includes at least one of the following: the first channel information report is generated based on inference or the first channel information report generates a corresponding first identifier.

[0951] As an example, the generation of the first channel information report corresponds to a first identifier, and M also depends on the first identifier.

[0952] As an example, when the size of the first time-domain resource is less than a first threshold, M is a first positive integer; when the size of the first time-domain resource is greater than the first threshold, M is a second positive integer; the second positive integer is less than the first positive integer.

[0953] As an example, the generation of the first channel information report corresponds to a first identifier, and the first threshold depends on the first identifier.

[0954] As an example, the N1 positive integers correspond to N1 size ranges, where N1 is a positive integer greater than 1; the size of the first time-domain resource belongs to a first size range, which is one of the N1 size ranges; and M is a positive integer among the N1 positive integers that corresponds to the first size range.

[0955] As an example, the N integer sets correspond to N identifiers, where N is a positive integer greater than 1; the generation of the first channel information report corresponds to a first identifier, which is one of the N identifiers; the integer set corresponding to the first identifier in the N integer sets includes the N1 positive integers.

[0956] As one embodiment, it includes:

[0957] The second processor 1901 sends the first signaling;

[0958] The first channel information reporting is triggered by the first signaling; the first time domain resource starts after the physical layer channel carrying the first signaling, or the first time domain resource starts after the first symbol of the physical layer channel carrying the first signaling.

[0959] As an example, the first time-domain resource begins with the first symbol of the earliest RS time in the first time set; the first time set includes at least one RS time in the first resource set.

[0960] As an example, the first time-domain resource terminates at the last symbol of the physical layer channel carrying the first channel information report.

[0961] As one embodiment, it includes:

[0962] The second processor 1901 sends the first information block;

[0963] The first information block is used to configure the first channel information reporting.

[0964] Those skilled in the art will understand that all or part of the steps in the above methods can be implemented by a program instructing related hardware, and the program can be stored in a computer-readable storage medium, such as a read-only memory, hard disk, or optical disk. Optionally, all or part of the steps in the above embodiments can also be implemented using one or more integrated circuits. Accordingly, each module unit in the above embodiments can be implemented in hardware or in the form of software functional modules. This application is not limited to any specific combination of software and hardware. The user equipment, terminal, and UE in this application include, but are not limited to, drones, communication modules on drones, remote-controlled aircraft, aircraft, small aircraft, mobile phones, tablets, laptops, vehicle-mounted communication equipment, vehicles, RSUs, wireless sensors, internet access cards, IoT terminals, RFID terminals, NB-IoT terminals, MTC (Machine Type Communication) terminals, eMTC (enhanced MTC) terminals, data cards, internet access cards, vehicle-mounted communication equipment, low-cost mobile phones, low-cost tablets, and other wireless communication devices. The base stations or system equipment in this application include, but are not limited to, macrocell base stations, microcell base stations, small cell base stations, home base stations, relay base stations, eNBs, gNBs, TRPs (Transmitter Receiver Points), GNSS, relay satellites, satellite base stations, airborne base stations, RSUs (Road Side Units), drones, and testing equipment, such as transceivers or signaling testers that simulate some functions of a base station, and other wireless communication equipment.

[0965] Those skilled in the art will understand that the present invention can be practiced in other specified forms without departing from its core or essential characteristics. Therefore, the embodiments disclosed herein should in any way be considered descriptive rather than restrictive. The scope of the invention is defined by the appended claims rather than the foregoing description, and all modifications within their equivalent meaning and scope are considered to be included therein.

Claims

1. A first node used for wireless communication, characterized in that, include: The first processor receives RS from the first resource set; Send the first channel information report; The first resource set includes at least one RS resource used for at least one of the channel measurement or interference measurement in the first channel information reporting; the first channel information reporting occupies M processing resources in the first time domain resources, where M is a positive integer; and M depends on the size of the first time domain resources.

2. The first node according to claim 1, characterized in that, M depends on the size of the first time-domain resource only when the first condition is met; the first condition includes at least one of the following: the first channel information report is generated based on inference or the first channel information report generates a corresponding first identifier.

3. The first node according to claim 1 or 2, characterized in that, The generation of the first channel information report corresponds to the first identifier, and M also depends on the first identifier.

4. The first node according to any one of claims 1 to 3, characterized in that, When the size of the first time-domain resource is less than the first threshold, M is a first positive integer; when the size of the first time-domain resource is greater than the first threshold, M is a second positive integer; the second positive integer is less than the first positive integer.

5. The first node according to claim 4, characterized in that, The generation of the first channel information report corresponds to the first identifier, and the first threshold depends on the first identifier.

6. The first node according to any one of claims 1 to 5, characterized in that, The N1 positive integers correspond to N1 size ranges, where N1 is a positive integer greater than 1; the size of the first time-domain resource belongs to a first size range, which is one of the N1 size ranges; M is a positive integer among the N1 positive integers that corresponds to the first size range.

7. The first node according to claim 6, characterized in that, The N integer sets correspond to N identifiers, where N is a positive integer greater than 1; the generation of the first channel information report corresponds to the first identifier, which is one of the N identifiers; the integer set corresponding to the first identifier in the N integer sets includes the N1 positive integers.

8. A second node used for wireless communication, characterized in that, include: The second processor sends RS in the first resource set; Receive the first channel information report; The first resource set includes at least one RS resource used for at least one of the channel measurement or interference measurement in the first channel information reporting; the first channel information reporting occupies M processing resources in the first time domain resources, where M is a positive integer; and M depends on the size of the first time domain resources.

9. A method used in a first node of wireless communication, characterized in that, include: Receive RS in the first resource set; Send the first channel information report; The first resource set includes at least one RS resource used for at least one of the channel measurement or interference measurement in the first channel information reporting; the first channel information reporting occupies M processing resources in the first time domain resources, where M is a positive integer; and M depends on the size of the first time domain resources.

10. A method used in a second node of wireless communication, characterized in that, include: Send RS in the first resource set; Receive the first channel information report; The first resource set includes at least one RS resource used for at least one of the channel measurement or interference measurement in the first channel information reporting; the first channel information reporting occupies M processing resources in the first time domain resources, where M is a positive integer; and M depends on the size of the first time domain resources.

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