Uplink transmission or downlink transmission method and apparatus, and communication system

Abstract

Provided in the embodiments of the present application are an uplink transmission or downlink transmission method and apparatus, and a communication system. The uplink transmission apparatus is applied to an apparatus on a network device side. The uplink transmission apparatus comprises a first communication unit. The first communication unit is configured to: configure an apparatus on a terminal device side to perform uplink transmission by using a codebook generated on the basis of an artificial intelligence function or model; and receive data uplink-transmitted by the terminal device on the basis of the codebook.

Description

Methods, apparatus and communication systems for uplink or downlink transmission Technical Field

[0001] The embodiments of this application relate to the field of communication technology. Background Technology

[0002] In 3GPP Release 18, the application of Artificial Intelligence (AI) and Machine Learning (ML) functions or models to the air interface was studied, including the application of AI / ML functions or models to Channel State Information (CSI) feedback compression. AI / ML-based CSI feedback compression employs a two-sided model, meaning the AI / ML function or model resides on both the User Equipment (UE) side and the Network (NW) side (i.e., the gNB side). In Rel-18, AI / ML-based feedback compression compresses CSI in the spatial frequency domain (SF-AI / ML CSI compression).

[0003] For the bilateral model, on the UE side, the UE performs measurements on a reference signal (e.g., Channel State Information-Reference Signal, CSI-RS) to obtain the radio channel; then, the UE can further obtain the feature vector of the radio channel, and this feature vector will be used as the input of the AI / ML function or model on the UE side, i.e., the input of the encoder, to compress the CSI; then, the UE reports the output of the encoder as a CSI feedback or sends it to the gNB; the gNB uses the received CSI feedback as the input of the AI / ML function or model on the gNB side, i.e., the input of the decoder; after decompression using the decoder, the decoder outputs the reconstructed CSI.

[0004] It should be noted that the above introduction to the technical background is only for the purpose of providing a clear and complete explanation of the technical solutions of this application and facilitating understanding by those skilled in the art. It should not be assumed that these technical solutions are known to those skilled in the art simply because they have been described in the background section of this application. Summary of the Invention

[0005] The inventors discovered that for a two-sided model architecture, it is necessary to pair the AI / ML functions or models on the terminal device side (e.g., UE side) with the AI / ML functions or models on the network device side (e.g., gNB side), and this pairing operation will cause inconvenience in use.

[0006] To address one or more of the aforementioned problems, embodiments of this application provide a method, apparatus, and communication system for uplink or downlink transmission.

[0007] According to one aspect of the embodiments of this application, an uplink transmission apparatus is provided, applied to a network device side, the uplink transmission apparatus including a first communication unit, the first communication unit being configured to:

[0008] The device on the terminal side is configured to use a codebook generated based on artificial intelligence functions or models for uplink transmission; and

[0009] Receive data transmitted uplink by the terminal device based on the codebook.

[0010] According to another aspect of the embodiments of this application, a downlink transmission apparatus is provided, applied to a network device side, the downlink transmission apparatus including a second communication unit, the second communication unit being configured to:

[0011] The terminal device is configured to report channel state information using a codebook generated based on artificial intelligence functions or models; and

[0012] Downlink transmission is performed based on the codebook.

[0013] According to another aspect of the embodiments of this application, an uplink transmission apparatus is provided, applied to a terminal device side, the uplink transmission apparatus including a third communication unit, the third communication unit being:

[0014] Configured to use a codebook generated based on artificial intelligence features or models for uplink transmission; and

[0015] Based on the codebook, the uplink data is sent to the device on the network device side.

[0016] According to another aspect of the embodiments of this application, a downlink transmission apparatus is provided, applied to a terminal device side, the downlink transmission apparatus including a fourth communication unit, the fourth communication unit being:

[0017] The device on the network equipment side is configured to report channel state information using a codebook generated based on artificial intelligence functions or models; and

[0018] The device on the network device side receives data transmitted downlink based on the codebook.

[0019] One of the beneficial effects of the embodiments of this application is that uplink or downlink transmission can be performed without pairing the AI / ML functions or models on the terminal device side (e.g., UE side) and the AI / ML functions or models on the network device side (e.g., gNB side), thereby simplifying the usage process and reducing costs.

[0020] Specific embodiments of this application are disclosed in detail with reference to the following description and accompanying drawings, indicating how the principles of this application can be adopted. It should be understood that the embodiments of this application are not limited in scope. Within the spirit and scope of the appended claims, embodiments of this application include many changes, modifications, and equivalents.

[0021] Features described and / or illustrated for one embodiment may be used in the same or similar manner in one or more other embodiments, combined with features in other embodiments, or substituted for features in other embodiments.

[0022] It should be emphasized that the term "including / comprises" as used herein refers to the presence of a feature, whole, step, or component, but does not exclude the presence or addition of one or more other features, wholes, steps, or components. Attached Figure Description

[0023] The elements and features described in one drawing or embodiment of this application may be combined with elements and features shown in one or more other drawings or embodiments. Furthermore, in the drawings, similar reference numerals denote corresponding parts in several drawings and can be used to indicate corresponding parts used in more than one embodiment.

[0024] Figure 1 is a schematic diagram of a communication system according to an embodiment of this application;

[0025] Figure 2 is a schematic diagram of an uplink transmission method according to an embodiment of this application;

[0026] Figure 3 is a schematic diagram of uplink transmission between the device on the network device side and the device on the terminal device side in Embodiment 1.

[0027] Figure 4 is a schematic diagram of uplink transmission between the device on the network device side and the device on the terminal device side in Embodiment 2.

[0028] Figure 5 is a schematic diagram of uplink transmission between the device on the network device side and the device on the terminal device side in Embodiment 3.

[0029] Figure 6 is a schematic diagram of a downlink transmission method according to an embodiment of this application;

[0030] Figure 7 is a schematic diagram of uplink transmission between the device on the network device side and the device on the terminal device side in Embodiment 4.

[0031] Figure 8 is a schematic diagram of uplink transmission between the device on the network device side and the device on the terminal device side in Embodiment 5.

[0032] Figure 9 is a schematic diagram of uplink transmission between the network device and the terminal device in Embodiment 6.

[0033] Figure 10 is another schematic diagram of the uplink transmission method according to an embodiment of this application;

[0034] Figure 11 is another schematic diagram of the downlink transmission method according to an embodiment of this application;

[0035] Figure 12 is a schematic diagram of an uplink transmission apparatus according to an embodiment of this application;

[0036] Figure 13 is a schematic diagram of a downlink transmission apparatus according to an embodiment of this application;

[0037] Figure 14 is another schematic diagram of the uplink transmission apparatus according to an embodiment of this application;

[0038] Figure 15 is another schematic diagram of a downlink transmission apparatus according to an embodiment of this application;

[0039] Figure 16 is a schematic block diagram of an electronic device according to an embodiment of this application. Detailed Implementation

[0040] Referring to the accompanying drawings, the foregoing and other features of this application will become apparent from the following description. Specific embodiments of this application are specifically disclosed in the description and drawings, illustrating partial implementations in which the principles of this application can be adopted. It should be understood that this application is not limited to the described embodiments; rather, it includes all modifications, variations, and equivalents falling within the scope of the appended claims. Various embodiments of this application are described below with reference to the accompanying drawings. These embodiments are merely exemplary and not intended to limit the scope of this application.

[0041] In the embodiments of this application, the terms "first," "second," etc., are used to distinguish different elements by name, but do not indicate the spatial arrangement or chronological order of these elements, and these elements should not be limited by these terms. The term "and / or" includes any one or more of the terms listed in association and all combinations thereof. The terms "comprising," "including," "having," etc., refer to the presence of the stated features, elements, components, or assemblies, but do not exclude the presence or addition of one or more other features, elements, components, or assemblies.

[0042] In the embodiments of this application, the singular forms "a," "the," etc., including the plural forms, should be broadly understood as "a kind" or "a class" rather than limited to the meaning of "an." Furthermore, the term "the" should be understood to include both the singular and plural forms, unless the context explicitly indicates otherwise. Additionally, the term "according to" should be understood as "at least partially based on…," and the term "based on" should be understood as "at least partially based on…," unless the context explicitly indicates otherwise.

[0043] In the embodiments of this application, the term "communication network" or "wireless communication network" may refer to a network that conforms to any of the following communication standards, such as New Radio (NR), Long Term Evolution (LTE), LTE-Advanced (LTE-A), Wideband Code Division Multiple Access (WCDMA), High-Speed ​​Packet Access (HSPA), etc.

[0044] Furthermore, communication between devices in a communication system can be carried out according to communication protocols at any stage, including but not limited to the following communication protocols: 1G (generation), 2G, 2.5G, 2.75G, 3G, 4G, 4.5G and 5G, New Radio (NR), 6G and future communication, and / or other currently known or future communication protocols.

[0045] In the embodiments of this application, the term "network device" refers, for example, to a device in a communication system that connects a terminal device to a communication network and provides services to that terminal device. Network devices may include, but are not limited to, the following devices: base station (BS), access point (AP), transmission reception point (TRP), broadcast transmitter, mobile management entity (MME), gateway, server, radio network controller (RNC), base station controller (BSC), etc.

[0046] The term "base station" can include, but is not limited to, NodeBs (or NBs), evolved NodeBs (eNodeBs or eNBs), 5G base stations (gNBs), 6G base stations, and future base stations, etc. It can also include Remote Radio Heads (RRHs), Remote Radio Units (RRUs), relays, or low-power nodes (e.g., femto, pico, etc.). The term "base station" can encompass some or all of its functions, and each base station can provide communication coverage to a specific geographic area. The term "cell" can refer to a base station and / or its coverage area, depending on the context in which the term is used.

[0047] In the embodiments of this application, the terms "User Equipment" (UE) or "Terminal Equipment" (TE) refer, for example, to a device that accesses a communication network and receives network services through a network device. User equipment can be fixed or mobile, and may also be referred to as a mobile station (MS), terminal, user, subscriber station (SS), access terminal (AT), station, mobile terminal (MT), etc.

[0048] The terminal device may include, but is not limited to, the following devices: cellular phone, personal digital assistant (PDA), wireless modem, wireless communication device, handheld device, machine-type communication device, laptop computer, cordless phone, smartphone, smartwatch, digital camera, etc.

[0049] For example, in scenarios such as the Internet of Things (IoT), user devices can also be machines or devices used for monitoring or measurement, including but not limited to: machine-type communication (MTC) terminals, vehicle-mounted communication terminals, device-to-device (D2D) terminals, machine-to-machine (M2M) terminals, terminals that support sidelink communication, and so on.

[0050] Furthermore, the terms "network side" or "network equipment side" refer to one side of the network, which can be a base station or include one or more network devices as described above. The terms "user side," "terminal side," or "terminal equipment side" refer to the side of the user or terminal, which can be a UE or include one or more terminal devices as described above. Unless otherwise specified, "equipment" can refer to either network equipment or terminal equipment.

[0051] Without causing confusion, the terms “uplink control signal” and “uplink control information (UCI)” or “physical uplink control channel (PUCCH)” are interchangeable, as are the terms “uplink data signal” and “uplink data information (PUSCH)”.

[0052] The terms “downlink control signal” and “downlink control information (DCI)” or “physical downlink control channel (PDCCH)” are interchangeable, as are the terms “downlink data signal” and “downlink data information (PDSCH)” or “physical downlink shared channel (PDSCH)”.

[0053] Additionally, uplink signals can include uplink data signals and / or uplink control signals and / or PRACH and / or SRS (sounding reference signal), etc., and can also be referred to as uplink transmission (UL transmission), uplink information, or uplink channel. Sending / receiving uplink transmission on uplink resources can be understood as using that uplink resource to send / receive the uplink transmission. Downlink signals can include downlink data signals and / or downlink control signals and / or synchronization signals (SS, such as PSS / SSS) and / or broadcast channel (PBCH) and / or SSB (SS / PBCH block, including PSS, SSS, and PBCH and their DMRS) and / or CSI-RS, etc., and can also be referred to as downlink transmission (DL transmission), downlink information, or downlink channel. Sending / receiving downlink transmission on downlink resources can be understood as using that downlink resource to send / receive the downlink transmission.

[0054] In the embodiments of this application, higher-layer signaling may be, for example, Radio Resource Control (RRC) signaling; RRC signaling may include, for example, RRC messages, such as broadcast / public RRC messages / signaling (e.g., Master Information Block (MIB), System Information (SI), Private RRC messages / signaling; or RRC Information Element (RRC IE); or information fields (or information fields included in information fields) included in RRC messages or RRC Information Elements. Higher-layer signaling may also be, for example, Medium Access Control (MAC) signaling; or referred to as MAC control element (MAC CE). However, this application is not limited to these.

[0055] In the embodiments of this application, "at least one" and "one or more" can be used interchangeably, and "multiple" and "more than one" can be used interchangeably. "Multiple" means at least two, or two or more.

[0056] In this application embodiment, "predefined" refers to what is specified by the protocol or determined according to the rules specified by the protocol, and does not require additional configuration. "Configuration / instruction" refers to what the network device directly or indirectly configures / instructs through higher-layer signaling and / or physical layer signaling. Configuration / instruction can be achieved by introducing higher-layer parameters into the higher-layer signaling. Higher-layer parameters refer to information fields and / or information elements / information units / information cells (IEs) in the higher-layer signaling. Physical layer signaling refers to, for example, control information (DCI) carried by the physical downlink control channel or control information carried by the sequence, but is not limited to these.

[0057] For ease of description, the following text uses a base station as an example of an access network device.

[0058] In the following explanation, without causing confusion, “if…”, “in the case of…” and “when…” can be used interchangeably.

[0059] The following examples illustrate the scenarios of embodiments of this application, but this application is not limited thereto.

[0060] Figure 1 is a schematic diagram of a communication system according to an embodiment of this application, illustrating the case of a terminal device and a network device as examples. As shown in Figure 1, the communication system 100 may include a network device 101, a terminal device 102, and a terminal device 103. For simplicity, Figure 1 only illustrates the case of two terminal devices and one network device, but the embodiments of this application are not limited to this.

[0061] In this embodiment of the application, network device 101, terminal device 102, and terminal device 103 can transmit existing services or services that can be implemented in the future. For example, these services may include, but are not limited to: enhanced mobile broadband (eMBB), massive machine-type communication (mMTC), ultra-reliable and low-latency communication (URLLC), and related communications of terminal devices with reduced capabilities, etc.

[0062] Terminal devices 102 and 103 can be in RRC_IDLE, RRC_INACTIVE, or RRC_CONNECTED states. Terminal devices 102 and 103 can also communicate with network device 101. For example, taking terminal device 102 as an example, terminal device 102 can send data to network device 101 or perform data retransmission. Network device 101 can send paging messages to terminal device 102 or send data to terminal device 102, and terminal device 102 can receive data sent by network device 101. Furthermore, different terminal devices can also communicate with each other; for example, terminal device 102 and terminal device 103 can exchange data.

[0063] It is worth noting that Figure 1 shows that both terminal device 102 and terminal device 103 are within the coverage area of ​​network device 101, but this application is not limited to this. Terminal device 102 and terminal device 103 may both be outside the coverage area of ​​network device 101, or one of terminal device 102 and terminal device 103 may be within the coverage area of ​​network device 101 while the other is outside the coverage area of ​​network device 101.

[0064] In the various embodiments of this application, the following terms have the same meaning and can be used interchangeably: AI / ML, artificial intelligence, artificial intelligence, or machine learning.

[0065] In various embodiments of this application, AI / ML functionality / model may also be referred to as AI / ML function or model, artificial intelligence or machine learning function or model, artificial intelligence function or model, etc., which have the same meaning and can be used interchangeably in this application.

[0066] First aspect of the embodiments

[0067] This application provides an uplink transmission method, which is applied to a device on the network device side. The description will now proceed from the terminal device side and / or the network device side.

[0068] Figure 2 is a schematic diagram of an uplink transmission method according to an embodiment of this application. As shown in Figure 2, from the perspective of the network device, the method includes:

[0069] 201. The network device-side device is configured to use a codebook generated based on artificial intelligence functions or models for uplink transmission; and

[0070] 202. The device on the network equipment side receives the data transmitted uplink by the terminal device based on the codebook.

[0071] In this application, the codebook can be generated based on artificial intelligence functions or models. For example, the codebook is generated by a device on the network device side (i.e., the codebook for artificial intelligence functions or models is set on the device on the network device side); or, the codebook is generated by a device on the terminal device side (i.e., the codebook for artificial intelligence functions or models is set on the device on the network device side); or, the codebook is jointly generated by a device on the terminal device side and a device on the network device side.

[0072] In this application, the devices on the network device side may include network devices and / or servers on the network device side; the devices on the terminal device side may include terminal devices and / or servers on the terminal device side.

[0073] A codebook consists of multiple precoding matrices. The codebook is generated based on artificial intelligence functions or models. For example, it can refer to one or more precoding matrices in the codebook being generated based on artificial intelligence functions or models.

[0074] In this application, codebooks generated based on artificial intelligence functions or models can also be referred to as codebooks pre-trained based on artificial intelligence functions or models; the two terms have the same meaning.

[0075] In some embodiments, an AI function or model refers to an AI / ML feature or feature group enabled by a configuration that is supported based on conditions indicated by the capabilities of the end device.

[0076] For example, an AL / ML function or model can be one or more functions or models, or it can be one or more logical models, or it can be one or more sub-functions, or it can be one or more features, or it can be one or more feature groups.

[0077] The present application will now be further described with reference to specific embodiments.

[0078] Example 1

[0079] In Example 1, the codebook is generated by a device on the network device side. For example, the codebook for uplink transmission can be generated by the network device or a server on the network device side. In a specific example, the codebook for uplink transmission can be generated by the network device.

[0080] Figure 3 is a schematic diagram of uplink transmission between the network device and the terminal device in Embodiment 1. In Figure 3, the network device is, for example, a network device, and the terminal device is, for example, a terminal device.

[0081] Figure 3 includes the following operations:

[0082] 301. A device on the network equipment side generates a codebook based on artificial intelligence functions or models, the codebook including one or more pre-encoding matrices generated based on artificial intelligence functions or models;

[0083] 302. A device on the network device side sends one or more codebook sets to a device on the terminal device side. The one or more codebook sets include one or more precoding matrices generated based on artificial intelligence functions or models. In addition, the one or more codebook sets may also include one or more precoding matrices generated based on non-artificial intelligence functions or models.

[0084] 303. The device on the network equipment side is configured to use a codebook generated based on artificial intelligence functions or models for uplink transmission, corresponding to the above operation 201;

[0085] 304. The terminal device sends a channel sounding reference signal (SRS) to the network device to facilitate channel measurement;

[0086] 305. The network device side uses a method based on artificial intelligence functions or models, or a method based on non-artificial intelligence functions or models, to select a precoding matrix for uplink transmission from a codebook set; and

[0087] 306. The device on the network device side indicates or configures the selected precoding matrix for uplink transmission to the device on the terminal device side.

[0088] After operation 306, operation 202 can be performed, for example, where the device on the terminal device side uses a precoding matrix generated based on artificial intelligence functions or models selected by the network device to send uplink data, and the device on the network device side receives the uplink data.

[0089] In operation 302 of this application, the device on the network device side can send the codebook set through Layer-3 signaling, Layer-2 signaling or Layer-1 signaling, or the device on the network device side can send the codebook set through the user plane, such as the data channel.

[0090] In some examples of Operation 302, when a device on the network device side sends one or more codebook sets to a device on the terminal device side, it also sends at least one of the following:

[0091] The total number of precoding matrices;

[0092] The number of antenna ports for the precoding matrix;

[0093] The maximum rank values ​​supported by the precoding matrix in the set of codebooks, or the number of rank values ​​supported by the precoding matrix in the set of codebooks.

[0094] The number of precoding matrices for each rank value;

[0095] For each rank value, there are one or more precoding matrices corresponding to a given rank value.

[0096] For example, in a codebook set, all precoding matrices have the same number of antenna ports;

[0097] For example, in a codebook set, at least two precoding matrices may have different numbers of antenna ports, where the number of antenna ports corresponding to a certain precoding matrix can be explicitly or implicitly indicated.

[0098] For example, in a codebook set, all precoding matrices have the same rank.

[0099] For example, in a codebook set, at least two precoding matrices may have different rank values, where the rank value of a precoding matrix may be explicitly or implicitly indicated.

[0100] In operation 303, the network device-side device configures the terminal device-side device to use a codebook generated based on an artificial intelligence function or model for uplink transmission, for example, by enabling the codebook generated based on an artificial intelligence function or model for uplink transmission. The network device-side device can configure the terminal device-side device via Layer-3 signaling, such as Radio Resource Control (RRC) signaling; or, the network device-side device can configure the terminal device-side device via Layer-2 signaling, such as Media Access Control Element (MAC-CE) signaling.

[0101] In some examples, network device-side devices can decide whether to enable codebooks generated based on artificial intelligence functions or models for uplink transmission. In other examples, terminal device-side devices can trigger or request the enabling of codebooks generated based on artificial intelligence functions or models for uplink transmission.

[0102] In some cases, when there are multiple codebook sets generated based on artificial intelligence functions or models for uplink transmission, the network device can instruct or configure the terminal device on the terminal device on the information of the codebook set to be used. For example, the information may be the codebook set or the identifier (set ID) of the codebook set.

[0103] In this application, operation 304 is optional. For example, if operation 304 exists, in operation 305, the device on the network device side can select a precoding matrix based on the SRS sent by the device on the terminal device side in operation 304. Alternatively, if operation 304 does not exist, in operation 305, the device on the network device side can use the previously selected precoding matrix as the selected precoding matrix.

[0104] In some examples of operation 305, the network device side can use a method based on artificial intelligence functions or models to select the precoding matrix for uplink transmission. For example, the channel information measured by SRS based on the device on the terminal device side in operation 304 can be input into the artificial intelligence function or model, thereby outputting the selected precoding matrix for uplink transmission. The artificial intelligence function or model used in selecting the precoding matrix can be the same as or different from the artificial intelligence function or model used in generating the codebook in operation 301.

[0105] In other examples of Operation 305, devices on the network equipment side can also use methods based on non-AI functions or models to select the precoding matrix for uplink transmission.

[0106] In operation 306, Layer-1 signaling can be used to indicate which precoding matrices for uplink transmission, generated based on artificial intelligence functions or models, are selected or used. For example, it can indicate which precoding matrices in the codebook for uplink transmission generated based on artificial intelligence functions or models are selected or used. Layer-1 signaling is, for example, downlink control information (DCI).

[0107] In some examples, the precoding matrix generated based on artificial intelligence features or models can be indicated by one or more DCI fields. The length of the DCI field can be pre-defined based on the configuration for uplink transmission generated based on the artificial intelligence features or models, such as the Radio Resource Control (RRC) configuration. For example, the length of the DCI field is X bits, where X can be determined based on the RRC configuration, and X can be greater than, less than, or equal to the length of the Transport Precoding Matrix Indicator (TPMI) field in a traditional 5G NR system with the same maximum rank value.

[0108] For example, for a rank i, if the number of precoding matrices generated based on artificial intelligence functions or models is Ni, then the length L of the DCI field is... The maximum value of the rank i is K.

[0109] In other examples of Operation 306, for uplink transmissions with configuration authorization, RRC signaling can be used to configure which precoding matrices in the codebook generated by the AI ​​function or model are selected.

[0110] In some examples of Implementation 1, codebooks generated based on artificial intelligence functions or models can be used for all cells or transmit / receive points or sites.

[0111] In other examples of Embodiment 1, codebooks generated based on artificial intelligence functions or models can be used for specific cells or transmit / receive points or sites. In this case, different codebooks or codebook sets can be generated for different cells or transmit / receive points or sites.

[0112] In some examples, a device on the terminal device side can notify a device on the network device side whether it has received or stored a codebook set generated based on artificial intelligence functions or models. The device on the network device side can then decide whether to send a specific codebook set to the device on the terminal device side.

[0113] In Example 1, codebooks generated based on artificial intelligence functions or models can be used for near field communication in multiple-input multiple-output (MIMO) systems.

[0114] Example 2

[0115] In Embodiment 2, the codebook is generated by a device on the terminal device side. For example, the codebook for uplink transmission can be generated by the terminal device or a server on the terminal device side (e.g., an OTT server). In a specific example, the codebook for uplink transmission can be generated by the terminal device.

[0116] Figure 4 is a schematic diagram of uplink transmission between the network device side device and the terminal device side device in Embodiment 2. In Figure 4, the network device side device is, for example, a network device, and the terminal device side device is, for example, a terminal device.

[0117] Figure 4 includes the following operations:

[0118] 401. The device on the terminal side generates a codebook based on artificial intelligence functions or models, and the codebook includes one or more pre-encoding matrices generated based on artificial intelligence functions or models;

[0119] 402. A device on the terminal device side sends one or more codebook sets to a device on the network device side. The one or more codebook sets include one or more precoding matrices generated based on artificial intelligence functions or models. In addition, the one or more codebook sets may also include one or more precoding matrices generated based on non-artificial intelligence functions or models.

[0120] 403. The network device side is configured to use a codebook generated based on artificial intelligence functions or models for uplink transmission, corresponding to the above operation 201;

[0121] 404. The terminal device sends a channel sounding reference signal (SRS) to the network device to facilitate channel measurement;

[0122] 405. The network device side uses a method based on artificial intelligence functions or models, or a method based on non-artificial intelligence functions or models, to select a precoding matrix for uplink transmission from a codebook set; and

[0123] 406. The device on the network device side indicates or configures the selected precoding matrix for uplink transmission to the device on the terminal device side.

[0124] In operation 402 of this application, the device on the terminal device side can send the codebook set through Layer-3 signaling, Layer-2 signaling or Layer-1 signaling, or the device on the terminal device side can send the codebook set through a user plane, such as a data channel.

[0125] In some examples of Operation 402, when a device on the terminal device side sends one or more codebook sets to a device on the network device side, it also sends at least one of the following:

[0126] The total number of precoding matrices;

[0127] The number of antenna ports for the precoding matrix;

[0128] The maximum rank values ​​supported by the precoding matrix in the set of codebooks, or the number of rank values ​​supported by the precoding matrix in the set of codebooks.

[0129] The number of precoding matrices for each rank value;

[0130] For each rank value, there are one or more precoding matrices corresponding to a given rank value.

[0131] For example, in a codebook set, all precoding matrices have the same number of antenna ports;

[0132] For example, in a codebook set, at least two precoding matrices may have different numbers of antenna ports, where the number of antenna ports corresponding to a certain precoding matrix can be explicitly or implicitly indicated.

[0133] For example, in a codebook set, all precoding matrices have the same rank.

[0134] For example, in a codebook set, at least two precoding matrices may have different rank values, where the rank value of a precoding matrix may be explicitly or implicitly indicated.

[0135] In operation 403, the network device-side device configures the terminal device-side device to use a codebook generated based on an artificial intelligence function or model for uplink transmission, for example, by enabling the codebook generated based on an artificial intelligence function or model for uplink transmission. The network device-side device can configure the terminal device-side device via Layer-3 signaling, such as Radio Resource Control (RRC) signaling; or, the network device-side device can configure the terminal device-side device via Layer-2 signaling, such as Media Access Control Element (MAC-CE) signaling.

[0136] In some examples, network device-side devices can decide whether to enable codebooks generated based on artificial intelligence functions or models for uplink transmission. In other examples, terminal device-side devices can trigger or request the enabling of codebooks generated based on artificial intelligence functions or models for uplink transmission.

[0137] In some cases, when there are multiple codebook sets generated based on artificial intelligence functions or models for uplink transmission, the network device can instruct or configure the terminal device on the terminal device on the information of the codebook set to be used. For example, the information may be the codebook set or the identifier (set ID) of the codebook set.

[0138] In this application, operation 404 is optional. For example, if operation 404 exists, in operation 405, the device on the network device side can select a precoding matrix based on the SRS sent by the device on the terminal device side in operation 404. Alternatively, if operation 404 does not exist, in operation 405, the device on the network device side can use the previously selected precoding matrix as the selected precoding matrix.

[0139] In some examples of operation 405, the network device side can use a method based on artificial intelligence functions or models to select the precoding matrix for uplink transmission. For example, the channel information measured by SRS based on the device on the terminal device side in operation 404 can be input into the artificial intelligence function or model, thereby outputting the selected precoding matrix for uplink transmission. The artificial intelligence function or model used in selecting the precoding matrix can be the same as or different from the artificial intelligence function or model used in generating the codebook in operation 401.

[0140] In other examples of Operation 405, devices on the network device side can also use methods based on non-AI functions or models to select the precoding matrix for uplink transmission.

[0141] In operation 406, Layer-1 signaling can be used to indicate which precoding matrices for uplink transmission, generated based on artificial intelligence functions or models, are selected or used. For example, it can indicate which precoding matrices in the codebook generated based on artificial intelligence functions or models for uplink transmission are selected or used. Layer-1 signaling is, for example, downlink control information (DCI).

[0142] In some examples, the precoding matrix generated based on artificial intelligence features or models can be indicated by one or more DCI fields. The length of the DCI field can be pre-defined based on the configuration for uplink transmission generated based on the artificial intelligence features or models, such as the Radio Resource Control (RRC) configuration. For example, the length of the DCI field is X bits, where X can be determined based on the RRC configuration, and X can be greater than, less than, or equal to the length of the Transport Precoding Matrix Indicator (TPMI) field in a traditional 5G NR system with the same maximum rank value.

[0143] For example, for a rank i, if the number of precoding matrices generated based on artificial intelligence functions or models is Ni, then the length L of the DCI field is... The maximum value of the rank i is K.

[0144] In other examples of Operation 406, for uplink transmissions with configuration authorization, RRC signaling can be used to configure which precoding matrices in the codebook generated by the AI ​​function or model are selected.

[0145] In some examples of Embodiment 2, codebooks generated based on artificial intelligence functions or models can be used for all cells or transmit / receive points or sites.

[0146] In other examples of Embodiment 2, codebooks generated based on artificial intelligence functions or models can be used for specific cells or transmit / receive points or sites. In this case, different codebooks or codebook sets can be generated for different cells or transmit / receive points or sites.

[0147] In some examples, a device on the terminal device side can notify a device on the network device side whether it has received or stored a codebook set generated based on artificial intelligence functions or models. The device on the network device side can then decide whether to send a specific codebook set to the device on the terminal device side.

[0148] In Example 2, codebooks generated based on artificial intelligence functions or models can be used for near field communication in multiple-input multiple-output (MIMO) systems.

[0149] Example 3

[0150] In embodiment 3, the codebook is jointly generated by the device on the terminal device side and the device on the network device side. For example, the codebook for uplink transmission can be jointly generated by the terminal device and the network device.

[0151] Figure 5 is a schematic diagram of uplink transmission between the network device side device and the terminal device side device in Embodiment 3. In Figure 5, the network device side device is, for example, a network device, and the terminal device side device is, for example, a terminal device.

[0152] Figure 5 includes the following operations:

[0153] 501. The terminal device and the network device jointly generate a codebook based on artificial intelligence functions or models. The codebook includes one or more precoding matrices generated based on artificial intelligence functions or models. By operating 501, both the terminal device and the network device have one or more codebook sets. The one or more codebook sets include one or more precoding matrices generated based on artificial intelligence functions or models. In addition, the one or more codebook sets may also include one or more precoding matrices generated based on non-artificial intelligence functions or models.

[0154] 502. The network device side is configured to use a codebook generated based on artificial intelligence functions or models for uplink transmission, corresponding to the above operation 201;

[0155] 503. The terminal device sends a channel sounding reference signal (SRS) to the network device to facilitate channel measurement;

[0156] 504. The network device uses a method based on artificial intelligence functions or models, or a method based on non-artificial intelligence functions or models, to select a precoding matrix for uplink transmission from a codebook set; and

[0157] 505. The network device side device indicates or configures the selected precoding matrix for uplink transmission to the terminal device side device.

[0158] In some examples of Operation 501, at least one of the following messages has the same meaning for both the network device-side device and the terminal device-side device:

[0159] The total number of precoding matrices;

[0160] The number of antenna ports for the precoding matrix;

[0161] The maximum rank values ​​supported by the precoding matrix in the set of codebooks, or the number of rank values ​​supported by the precoding matrix in the set of codebooks.

[0162] The number of precoding matrices for each rank value;

[0163] For each rank value, there are one or more precoding matrices corresponding to a given rank value.

[0164] For example, in a codebook set, all precoding matrices have the same number of antenna ports;

[0165] For example, in a codebook set, at least two precoding matrices may have different numbers of antenna ports, where the number of antenna ports corresponding to a certain precoding matrix can be explicitly or implicitly indicated.

[0166] For example, in a codebook set, all precoding matrices have the same rank.

[0167] For example, in a codebook set, at least two precoding matrices may have different rank values, where the rank value of a precoding matrix may be explicitly or implicitly indicated.

[0168] In operation 502, the network device-side device configures the terminal device-side device to use a codebook generated based on an artificial intelligence function or model for uplink transmission, for example, by enabling the codebook generated based on an artificial intelligence function or model for uplink transmission. The network device-side device can configure the terminal device-side device via Layer-3 signaling, such as Radio Resource Control (RRC) signaling; or, the network device-side device can configure the terminal device-side device via Layer-2 signaling, such as Media Access Control Element (MAC-CE) signaling.

[0169] In some examples, network device-side devices can decide whether to enable codebooks generated based on artificial intelligence functions or models for uplink transmission. In other examples, terminal device-side devices can trigger or request the enabling of codebooks generated based on artificial intelligence functions or models for uplink transmission.

[0170] In some cases, when there are multiple codebook sets generated based on artificial intelligence functions or models for uplink transmission, the network device can instruct or configure the terminal device on the terminal device on the information of the codebook set to be used. For example, the information may be the codebook set or the identifier (set ID) of the codebook set.

[0171] In this application, operation 503 is optional. For example, if operation 503 exists, in operation 504, the device on the network device side can select the precoding matrix based on the SRS sent by the device on the terminal device side in operation 503. Alternatively, if operation 503 does not exist, in operation 504, the device on the network device side can use the previously selected precoding matrix as the selected precoding matrix.

[0172] In some examples of Operation 504, the network device side can use a method based on artificial intelligence functions or models to select the precoding matrix for uplink transmission. For example, the channel information measured by SRS based on the device on the terminal device side in Operation 503 can be input into the artificial intelligence function or model, thereby outputting the selected precoding matrix for uplink transmission. The artificial intelligence function or model used in selecting the precoding matrix can be the same as or different from the artificial intelligence function or model used in generating the codebook in Operation 501.

[0173] In other examples of Operation 504, devices on the network side may also use methods based on non-AI functions or models to select the precoding matrix for uplink transmission.

[0174] In Operation 505, Layer-1 signaling can be used to indicate which precoding matrices for uplink transmission, generated based on artificial intelligence functions or models, are selected or used. For example, it can indicate which precoding matrices in the codebook generated based on artificial intelligence functions or models for uplink transmission are selected or used. Layer-1 signaling is, for example, downlink control information (DCI).

[0175] In some examples, the precoding matrix generated based on artificial intelligence features or models can be indicated by one or more DCI fields. The length of the DCI field can be pre-defined based on the configuration for uplink transmission generated based on the artificial intelligence features or models, such as the Radio Resource Control (RRC) configuration. For example, the length of the DCI field is X bits, where X can be determined based on the RRC configuration, and X can be greater than, less than, or equal to the length of the Transport Precoding Matrix Indicator (TPMI) field in a traditional 5G NR system with the same maximum rank value.

[0176] For example, for a rank i, if the number of precoding matrices generated based on artificial intelligence functions or models is Ni, then the length L of the DCI field is... The maximum value of the rank i is K.

[0177] In other examples of operation 505, for uplink transmissions with configuration authorization, RRC signaling can be used to configure which precoding matrices in the codebook generated by the AI ​​function or model are selected.

[0178] In some examples of Embodiment 3, codebooks generated based on artificial intelligence functions or models can be used for all cells or transmit / receive points or sites.

[0179] In other examples of Embodiment 3, codebooks generated based on artificial intelligence functions or models can be used for specific cells or transmit / receive points or sites. In this case, different codebooks or codebook sets can be generated for different cells or transmit / receive points or sites.

[0180] In some examples, a device on the terminal device side can notify a device on the network device side whether it has received or stored a codebook set generated based on artificial intelligence functions or models. The device on the network device side can then decide whether to send a specific codebook set to the device on the terminal device side.

[0181] In Example 3, codebooks generated based on artificial intelligence functions or models can be used for near field communication in multiple-input multiple-output (MIMO) systems.

[0182] This application provides a downlink transmission method applied to a network device side apparatus. The description will now proceed from the terminal device side and / or the network device side.

[0183] Figure 6 is a schematic diagram of a downlink transmission method according to an embodiment of this application. As shown in Figure 6, from the perspective of the network device, the method includes:

[0184] 601. The network equipment side is configured to use a codebook generated based on artificial intelligence functions or models to report Channel State Information (CSI); and

[0185] 602. The network device performs downlink transmission based on this codebook.

[0186] In operation 601 of this application, the device on the network device side configures the terminal device to report channel state information (CSI) using a codebook generated based on artificial intelligence functions or models. Thus, the device on the terminal device side can select a precoding matrix from the codebook generated based on artificial intelligence functions or models and report the selected precoding matrix to the device on the network device side. Then, in operation 602, the termination on the network device side can be based on the precoding matrix selected by the device on the terminal device side for downlink transmission (DL transmission).

[0187] In this application, the codebook can be generated based on artificial intelligence functions or models. For example, the codebook is generated by a device on the network device side (i.e., the codebook for artificial intelligence functions or models is set on the device on the network device side); or, the codebook is generated by a device on the terminal device side (i.e., the codebook for artificial intelligence functions or models is set on the device on the network device side); or, the codebook is jointly generated by a device on the terminal device side and a device on the network device side.

[0188] In this application, the devices on the network device side may include network devices and / or servers on the network device side; the devices on the terminal device side may include terminal devices and / or servers on the terminal device side.

[0189] A codebook consists of multiple precoding matrices. The codebook is generated based on artificial intelligence functions or models. For example, it can refer to one or more precoding matrices in the codebook being generated based on artificial intelligence functions or models.

[0190] In this application, codebooks generated based on artificial intelligence functions or models can also be referred to as codebooks pre-trained based on artificial intelligence functions or models; the two terms have the same meaning.

[0191] In some embodiments, an AI function or model refers to an AI / ML feature or feature group enabled by a configuration that is supported based on conditions indicated by the capabilities of the end device.

[0192] For example, an AL / ML function or model can be one or more functions or models, or it can be one or more logical models, or it can be one or more sub-functions, or it can be one or more features, or it can be one or more feature groups.

[0193] The downlink transmission method in Figure 6 will be further explained below with reference to specific embodiments.

[0194] Example 4

[0195] In Embodiment 4, the codebook is generated by a device on the terminal device side. For example, the codebook for uplink transmission can be generated by the terminal device or a server on the terminal device side (e.g., an OTT server). In a specific example, the codebook for downlink transmission can be generated by the terminal device.

[0196] Figure 7 is a schematic diagram of downlink transmission between the network device-side device and the terminal device-side device in Embodiment 4. In Figure 7, the network device-side device is, for example, a network device, and the terminal device-side device is, for example, a terminal device.

[0197] Figure 7 includes the following operations:

[0198] 701. The device on the terminal side generates a codebook based on artificial intelligence functions or models, the codebook including one or more pre-encoding matrices generated based on artificial intelligence functions or models;

[0199] 702. A device on the network device side receives one or more codebook sets sent by a device on the terminal device side, wherein the one or more codebook sets include one or more precoding matrices generated based on artificial intelligence functions or models. In addition, the one or more codebook sets may also include one or more precoding matrices generated based on non-artificial intelligence functions or models.

[0200] 703. The device on the network equipment side is configured to use a codebook generated based on artificial intelligence functions or models to report channel state information (CSI) and transmit reference signals (e.g., CSI-RS) for channel measurement to the terminal equipment, corresponding to the above operation 601;

[0201] 704. The terminal device uses a method based on artificial intelligence functions or models, or a method based on non-artificial intelligence functions or models, to select a precoding matrix for downlink transmission from a codebook set; and

[0202] 705. The device on the network device side receives information about the precoding matrix selected by the device on the terminal device side for downlink transmission.

[0203] Following operation 705, operation 602 may follow, for example, where the device on the network device side uses a precoding matrix generated based on artificial intelligence functions or models selected by the device on the terminal device side to send downlink transmitted data, and the device on the terminal device side receives the downlink transmitted data.

[0204] In operation 702 of this application, the device on the network device side can receive the codebook set through Layer-3 signaling, Layer-2 signaling, or Layer-1 signaling. Alternatively, the device on the network device side can receive the codebook set through a user plane, such as a data channel.

[0205] In some examples of operation 702, when a device on the terminal device side sends one or more codebook sets to a device on the network device side, it also sends at least one of the following:

[0206] The total number of precoding matrices;

[0207] The number of antenna ports for the precoding matrix;

[0208] The maximum rank values ​​supported by the precoding matrix in the set of codebooks, or the number of rank values ​​supported by the precoding matrix in the set of codebooks.

[0209] The number of precoding matrices for each rank value;

[0210] For each rank value, there are one or more precoding matrices corresponding to a given rank value.

[0211] For example, in a codebook set, all precoding matrices have the same number of antenna ports;

[0212] For example, in a codebook set, at least two precoding matrices may have different numbers of antenna ports, where the number of antenna ports corresponding to a certain precoding matrix can be explicitly or implicitly indicated.

[0213] For example, in a codebook set, all precoding matrices have the same rank.

[0214] For example, in a codebook set, at least two precoding matrices may have different rank values, where the rank value of a precoding matrix may be explicitly or implicitly indicated.

[0215] In operation 703, the network device-side device configures the terminal device-side device to use a codebook generated based on artificial intelligence functions or models for channel state information reporting. Furthermore, the network device-side device can also send a reference signal to the terminal device-side device for channel measurement, for example, the reference signal being a Channel State Information Reference Signal (CSI-RS). Additionally, the network device-side device can configure resource and overhead allocation for the channel state information reporting to the terminal device-side device.

[0216] The network device can configure the terminal device via Layer 3 signaling, such as Radio Resource Control (RRC) signaling; or, the network device can configure the terminal device via Layer 2 signaling, such as Media Access Control Element (MAC-CE) signaling.

[0217] In some examples, network device-side devices can decide whether to enable codebooks generated based on artificial intelligence functions or models for downlink transmission. In other examples, terminal device-side devices can trigger or request the enabling of codebooks generated based on artificial intelligence functions or models for downlink transmission.

[0218] In some cases, when there are multiple codebook sets generated based on artificial intelligence functions or models for downlink transmission, the network device can instruct or configure the terminal device on the terminal device on the information of the codebook set to be used. For example, the information may be the codebook set or the identifier (set ID) of the codebook set.

[0219] In some examples of operation 704, the device on the terminal side can use a method based on artificial intelligence functions or models to select the precoding matrix for downlink transmission. For example, the results of channel measurements performed by the device on the terminal side are input into the artificial intelligence function or model, which then outputs the selected precoding matrix for downlink transmission. The artificial intelligence function or model used in selecting the precoding matrix may be the same as or different from the artificial intelligence function or model used in generating the codebook in operation 701.

[0220] In other examples of Operation 704, the device on the terminal side can also use a method based on non-AI functions or models to select the precoding matrix for downlink transmission.

[0221] In operation 705, the device on the terminal device side can report the selected precoding matrix, for example, by reporting the index or identifier of the selected precoding matrix along with other channel state information to the device on the network device side, wherein the other channel state information is, for example, a channel quality indicator (CQI) or a rank indicator (RI).

[0222] In some examples of Embodiment 4, codebooks generated based on artificial intelligence functions or models can be used for all cells or transmit / receive points or sites.

[0223] In other examples of Embodiment 4, codebooks generated based on artificial intelligence functions or models can be used for specific cells or transmit / receive points or sites. In this case, different codebooks or codebook sets can be generated for different cells or transmit / receive points or sites.

[0224] In some examples, the terminal device can notify the network device whether it has already sent a codebook set generated based on artificial intelligence functions or models to the network device. The network device can then decide whether the terminal device should send a specific codebook set to the network device.

[0225] In Example 4, codebooks generated based on artificial intelligence functions or models can be used for near field communication in multiple-input multiple-output (MIMO) systems.

[0226] Example 5

[0227] In embodiment 5, the codebook is generated by a device on the network device side. For example, the codebook for uplink transmission can be generated by the network device or a server on the network device side. In a specific example, the codebook for downlink transmission can be generated by the network device.

[0228] Figure 8 is a schematic diagram of downlink transmission between the network device-side device and the terminal device-side device in Embodiment 5. In Figure 8, the network device-side device is, for example, a network device, and the terminal device-side device is, for example, a terminal device.

[0229] Figure 8 includes the following operations:

[0230] 801. A device on the network equipment side generates a codebook based on an artificial intelligence function or model, the codebook including one or more pre-coding matrices generated based on an artificial intelligence function or model;

[0231] 802. A device on the network device side sends one or more codebook sets to a device on the terminal device side. The one or more codebook sets include one or more precoding matrices generated based on artificial intelligence functions or models. In addition, the one or more codebook sets may also include one or more precoding matrices generated based on non-artificial intelligence functions or models.

[0232] 803. The device on the network equipment side is configured to use a codebook generated based on artificial intelligence functions or models to report channel state information (CSI) and transmit reference signals (e.g., CSI-RS) for channel measurement to the terminal equipment, corresponding to the above operation 601;

[0233] 804. The terminal device uses a method based on artificial intelligence functions or models, or a method based on non-artificial intelligence functions or models, to select a precoding matrix for downlink transmission from a codebook set; and

[0234] 805. The device on the network device side receives information about the precoding matrix selected by the device on the terminal device side for downlink transmission.

[0235] Following operation 805, operation 602 may follow, for example, where the device on the network device side uses a precoding matrix generated based on artificial intelligence functions or models selected by the device on the terminal device side to send downlink transmitted data, and the device on the terminal device side receives the downlink transmitted data.

[0236] In operation 802 of this application, the device on the network device side can send the codebook set through Layer-3 signaling, Layer-2 signaling or Layer-1 signaling, or the device on the network device side can send the codebook set through the user plane, which is, for example, a data channel.

[0237] In some examples of 802 operation, when a device on the network device side sends one or more codebook sets to a device on the terminal device side, it also sends at least one of the following:

[0238] The total number of precoding matrices;

[0239] The number of antenna ports for the precoding matrix;

[0240] The maximum rank values ​​supported by the precoding matrix in the set of codebooks, or the number of rank values ​​supported by the precoding matrix in the set of codebooks.

[0241] The number of precoding matrices for each rank value;

[0242] For each rank value, there are one or more precoding matrices corresponding to a given rank value.

[0243] For example, in a codebook set, all precoding matrices have the same number of antenna ports;

[0244] For example, in a codebook set, at least two precoding matrices may have different numbers of antenna ports, where the number of antenna ports corresponding to a certain precoding matrix can be explicitly or implicitly indicated.

[0245] For example, in a codebook set, all precoding matrices have the same rank.

[0246] For example, in a codebook set, at least two precoding matrices may have different rank values, where the rank value of a precoding matrix may be explicitly or implicitly indicated.

[0247] In operation 803, the network device-side device configures the terminal device-side device to use a codebook generated based on artificial intelligence functions or models for channel state information reporting. Furthermore, the network device-side device can also send a reference signal to the terminal device-side device for channel measurement, for example, the reference signal being a Channel State Information Reference Signal (CSI-RS). Additionally, the network device-side device can configure resource and overhead allocation for the channel state information reporting to the terminal device-side device.

[0248] The network device can configure the terminal device as described above using Layer-3 signaling, such as Radio Resource Control (RRC) signaling; or, the network device can configure the terminal device using Layer-2 signaling, such as Media Access Control Element (MAC-CE) signaling.

[0249] In some examples, network device-side devices can decide whether to enable codebooks generated based on artificial intelligence functions or models for downlink transmission. In other examples, terminal device-side devices can trigger or request the enabling of codebooks generated based on artificial intelligence functions or models for downlink transmission.

[0250] In some cases, when there are multiple codebook sets generated based on artificial intelligence functions or models for downlink transmission, the network device can instruct or configure the terminal device on the terminal device on the information of the codebook set to be used. For example, the information may be the codebook set or the identifier (set ID) of the codebook set.

[0251] In some examples of operation 804, the device on the terminal side can use a method based on artificial intelligence functions or models to select the precoding matrix for downlink transmission. For example, the results of channel measurements performed by the device on the terminal side are input into the artificial intelligence function or model, which then outputs the selected precoding matrix for downlink transmission. The artificial intelligence function or model used in selecting the precoding matrix may be the same as or different from the artificial intelligence function or model used in generating the codebook in operation 801.

[0252] In other examples of Operation 804, the device on the terminal side can also use a method based on non-AI functions or models to select the precoding matrix for downlink transmission.

[0253] In operation 805, the device on the terminal device side may report the selected precoding matrix, for example, by reporting the index or identifier of the selected precoding matrix along with other channel state information to the device on the network device side, wherein the other channel state information is, for example, a channel quality indicator (CQI) or a rank indicator (RI).

[0254] In some examples of Implementation 5, codebooks generated based on artificial intelligence functions or models can be used for all cells or transmit / receive points or sites.

[0255] In other examples of Embodiment 5, codebooks generated based on artificial intelligence functions or models can be used for specific cells or transmit / receive points or sites. In this case, different codebooks or codebook sets can be generated for different cells or transmit / receive points or sites.

[0256] In some examples, the terminal device can notify the network device whether it has already sent a codebook set generated based on artificial intelligence functions or models to the network device. The network device can then decide whether the terminal device should send a specific codebook set to the network device.

[0257] In Example 5, codebooks generated based on artificial intelligence functions or models can be used for near field communication in multiple-input multiple-output (MIMO) systems.

[0258] Example 6

[0259] In embodiment 6, the codebook is jointly generated by devices on the network device side and devices on the terminal device side. For example, the codebook for uplink transmission can be jointly generated by the network device and the terminal device.

[0260] Figure 9 is a schematic diagram of downlink transmission between the network device-side device and the terminal device-side device in Embodiment 6. In Figure 9, the network device-side device is, for example, a network device, and the terminal device-side device is, for example, a terminal device.

[0261] Figure 9 includes the following operations:

[0262] 901. The network device-side device and the terminal device-side device jointly generate a codebook based on artificial intelligence functions or models. The codebook includes one or more precoding matrices generated based on artificial intelligence functions or models. By operating 901, the network device-side device and the terminal device-side device have one or more codebook sets. The one or more codebook sets include one or more precoding matrices generated based on artificial intelligence functions or models. In addition, the one or more codebook sets may also include one or more precoding matrices generated based on non-artificial intelligence functions or models.

[0263] 902. The device on the network equipment side is configured to use a codebook generated based on artificial intelligence functions or models to report channel state information (CSI) and transmit reference signals (e.g., CSI-RS) for channel measurement to the terminal equipment, corresponding to the above operation 601;

[0264] 903. The terminal device uses a method based on artificial intelligence functions or models, or a method based on non-artificial intelligence functions or models, to select a precoding matrix for downlink transmission from a codebook set; and

[0265] 904. The device on the network device side receives information about the precoding matrix selected by the device on the terminal device side for downlink transmission.

[0266] Following operation 904, operation 602 may follow, for example, where the device on the network device side uses a precoding matrix generated based on artificial intelligence functions or models selected by the device on the terminal device side to send downlink transmitted data, and the device on the terminal device side receives the downlink transmitted data.

[0267] In some instances, at least one of the following information has the same meaning for both the network device-side device and the terminal device-side device:

[0268] The total number of precoding matrices;

[0269] The number of antenna ports for the precoding matrix;

[0270] The maximum rank values ​​supported by the precoding matrix in the set of codebooks, or the number of rank values ​​supported by the precoding matrix in the set of codebooks.

[0271] The number of precoding matrices for each rank value;

[0272] For each rank value, there are one or more precoding matrices corresponding to a given rank value.

[0273] For example, in a codebook set, all precoding matrices have the same number of antenna ports;

[0274] For example, in a codebook set, at least two precoding matrices may have different numbers of antenna ports, where the number of antenna ports corresponding to a certain precoding matrix can be explicitly or implicitly indicated.

[0275] For example, in a codebook set, all precoding matrices have the same rank.

[0276] For example, in a codebook set, at least two precoding matrices may have different rank values, where the rank value of a precoding matrix may be explicitly or implicitly indicated.

[0277] In operation 902, the network device-side apparatus configures the terminal device-side apparatus to use a codebook generated based on artificial intelligence functions or models for channel state information reporting. Furthermore, the network device-side apparatus can also send a reference signal to the terminal device-side apparatus for channel measurement, for example, the reference signal being a Channel State Information Reference Signal (CSI-RS). Additionally, the network device-side apparatus can configure resource and overhead allocation for the channel state information reporting to the terminal device-side apparatus.

[0278] The network device can configure the terminal device via Layer 3 signaling, such as Radio Resource Control (RRC) signaling; or, the network device can configure the terminal device via Layer 2 signaling, such as Media Access Control Element (MAC-CE) signaling.

[0279] In some examples, network device-side devices can decide whether to enable codebooks generated based on artificial intelligence functions or models for downlink transmission. In other examples, terminal device-side devices can trigger or request the enabling of codebooks generated based on artificial intelligence functions or models for downlink transmission.

[0280] In some cases, when there are multiple codebook sets generated based on artificial intelligence functions or models for downlink transmission, the network device can instruct or configure the terminal device on the terminal device on the information of the codebook set to be used. For example, the information may be the codebook set or the identifier (set ID) of the codebook set.

[0281] In some examples of Operation 903, the device on the terminal side can use a method based on artificial intelligence functions or models to select the precoding matrix for downlink transmission. For example, the results of channel measurements performed by the device on the terminal side are input into the artificial intelligence function or model, which then outputs the selected precoding matrix for downlink transmission. The artificial intelligence function or model used in selecting the precoding matrix may be the same as or different from the artificial intelligence function or model used in generating the codebook in Operation 901.

[0282] In other examples of Operation 903, the device on the terminal side can also use a method based on non-AI functions or models to select the precoding matrix for downlink transmission.

[0283] In operation 904, the device on the terminal device side may report the selected precoding matrix, for example, by reporting the index or identifier of the selected precoding matrix along with other channel state information to the device on the network device side, wherein the other channel state information is, for example, a channel quality indicator (CQI) or a rank indicator (RI).

[0284] In some examples of Implementation 6, codebooks generated based on artificial intelligence functions or models can be used for all cells or transmit / receive points or sites.

[0285] In other examples of Embodiment 6, codebooks generated based on artificial intelligence functions or models can be used for specific cells or transmit / receive points or sites. In this case, different codebooks or codebook sets can be generated for different cells or transmit / receive points or sites.

[0286] In some examples, the terminal device can notify the network device whether it has already sent a codebook set generated based on artificial intelligence functions or models to the network device. The network device can then decide whether the terminal device should send a specific codebook set to the network device.

[0287] In Example 6, codebooks generated based on artificial intelligence functions or models can be used for near field communication in multiple-input multiple-output (MIMO) systems.

[0288] According to the embodiments of the first aspect, uplink or downlink transmission can be performed without pairing the AI / ML functions or models on the terminal device side (e.g., UE side) and the network device side (e.g., gNB side), thereby simplifying the usage process and reducing costs.

[0289] Second aspect of the embodiments

[0290] This application provides an uplink transmission method, applied to a device on the terminal equipment side, which corresponds to the method in the first aspect embodiment. The contents that are the same as those in the first aspect embodiment will not be repeated.

[0291] Figure 10 is a schematic diagram of this uplink transmission method. As shown in Figure 10, the method includes:

[0292] 1001. The terminal device is configured to use a codebook generated based on artificial intelligence functions or models for uplink transmission; and

[0293] 1002. The terminal device sends uplink transmission data to the network device based on the codebook.

[0294] In some embodiments, the codebook is generated by a device on the network device side, or by a device on the terminal device side, or by a device on the terminal device side and a device on the network device side jointly.

[0295] In some embodiments, the codebook is generated by a device on the network device side, and the method further includes:

[0296] The terminal device receives one or more codebook sets sent by the network device, wherein the one or more codebook sets include one or more precoding matrices generated based on artificial intelligence functions or models; and

[0297] The device on the terminal device side is configured or instructs the device on the network device side to use a method based on artificial intelligence functions or models or a method based on non-artificial intelligence functions or models to select a precoding matrix for uplink transmission from the codebook set.

[0298] The device on the terminal side receives at least one of the following information:

[0299] The total number of precoding matrices;

[0300] The number of antenna ports in the precoding matrix;

[0301] The maximum rank supported by the precoding matrix in the codebook set;

[0302] Number of precoded matrices per rank;

[0303] Each rank value corresponds to one or more precoding matrices.

[0304] In some embodiments, the codebook is generated by a device on the terminal device side, and the method further includes:

[0305] The device on the terminal side sends one or more codebook sets, wherein the one or more codebook sets include one or more precoding matrices generated based on artificial intelligence functions or models; and

[0306] The device on the terminal device side is configured or instructs the device on the network device side to use a method based on artificial intelligence functions or models or a method based on non-artificial intelligence functions or models to select a precoding matrix for uplink transmission from the codebook set.

[0307] The device on the terminal side also sends at least one of the following information:

[0308] The total number of precoding matrices;

[0309] The number of antenna ports in the precoding matrix;

[0310] The maximum rank supported by the precoding matrix in the codebook set;

[0311] Number of precoded matrices per rank;

[0312] Each rank value corresponds to one or more precoding matrices.

[0313] In some embodiments, the codebook is jointly generated by a device on the terminal device side and a device on the network device side, and the method further includes:

[0314] The device on the terminal device side is configured or instructs the device on the network device side to select a precoding matrix for uplink transmission from the codebook set using a method based on artificial intelligence functions or models or a method based on non-artificial intelligence functions or models.

[0315] Wherein, at least one of the following information has the same meaning for both the network device-side device and the terminal device-side device:

[0316] The total number of precoding matrices;

[0317] The number of antenna ports in the precoding matrix;

[0318] The maximum rank supported by the precoding matrix in the codebook set;

[0319] Number of precoded matrices per rank;

[0320] Each rank value corresponds to one or more precoding matrices.

[0321] In some embodiments, the codebook generated based on artificial intelligence functions or models is used for all cells or transmitting / receiving points or sites, or for specific cells or transmitting / receiving points or sites.

[0322] In some embodiments, the codebook generated based on artificial intelligence features or models is used for near-field communication in a multiple-input multiple-output (MIMO) system.

[0323] This application also provides a downlink transmission method. Figure 11 is a schematic diagram of the downlink transmission method. As shown in Figure 11, the method includes:

[0324] 1101. The terminal device is configured by the network device to report channel state information using a codebook generated based on artificial intelligence functions or models; and

[0325] 1102. Receive data transmitted downlink by the device on the network device side based on the codebook.

[0326] In some embodiments, the codebook is generated by a device on the terminal device side, or by a device on the network device side, or by a device on the terminal device side and a device on the network device side jointly.

[0327] In some embodiments, the codebook is generated by a device on the terminal device side, and the method further includes:

[0328] The device on the terminal side sends one or more codebook sets, the one or more codebook sets including one or more precoding matrices generated based on artificial intelligence functions or models;

[0329] The terminal device uses a method based on artificial intelligence functions or models, or a method based on non-artificial intelligence functions or models, to select a precoding matrix for downlink transmission from the codebook set; and

[0330] The device on the terminal side reports the precoding matrix selected by the device on the terminal side for downlink transmission.

[0331] The device on the terminal side also sends at least one of the following information:

[0332] The total number of precoding matrices;

[0333] The number of antenna ports in the precoding matrix;

[0334] The maximum rank supported by the precoding matrix in the codebook set;

[0335] Number of precoded matrices per rank;

[0336] Each rank value corresponds to one or more precoding matrices.

[0337] In some embodiments, the codebook is generated by a device on the network device side, and the method further includes:

[0338] The device on the terminal side receives one or more codebook sets, wherein the one or more codebook sets include one or more precoding matrices generated based on artificial intelligence functions or models;

[0339] The terminal device uses a method based on artificial intelligence functions or models, or a method based on non-artificial intelligence functions or models, to select a precoding matrix for downlink transmission from the codebook set; and

[0340] The device on the terminal side reports the selected precoding matrix for downlink transmission.

[0341] The device on the terminal side also receives at least one of the following information:

[0342] The total number of precoding matrices;

[0343] The number of antenna ports in the precoding matrix;

[0344] The maximum rank supported by the precoding matrix in the codebook set;

[0345] Number of precoded matrices per rank;

[0346] Each rank value corresponds to one or more precoding matrices.

[0347] In some embodiments, the codebook is jointly generated by a device on the terminal device side and a device on the network device side, and the method further includes:

[0348] The terminal device uses a method based on artificial intelligence functions or models, or a method based on non-artificial intelligence functions or models, to select a precoding matrix for downlink transmission from the codebook set; and

[0349] The device on the terminal side reports the selected precoding matrix for downlink transmission.

[0350] In some embodiments, at least one of the following information has the same meaning for both the network device-side device and the terminal device-side device:

[0351] The total number of precoding matrices;

[0352] The number of antenna ports in the precoding matrix;

[0353] The maximum rank supported by the precoding matrix in the codebook set;

[0354] Number of precoded matrices per rank;

[0355] Each rank value corresponds to one or more precoding matrices.

[0356] In some embodiments, the codebook generated based on artificial intelligence functions or models is used for all cells or transmitting / receiving points or sites, or for specific cells or transmitting / receiving points or sites.

[0357] In some embodiments, the codebook generated based on artificial intelligence features or models is used for near-field communication in a multiple-input multiple-output (MIMO) system.

[0358] Third aspect of the embodiments

[0359] This application provides an uplink transmission apparatus. This apparatus is applied to a network device side device. The uplink transmission apparatus can be, for example, a network device, or one or more components or parts configured within the network device. It corresponds to the method applied to the network device side in the first aspect embodiment, and the content identical to that in the first aspect embodiment will not be repeated.

[0360] Figure 12 is a schematic diagram of an uplink transmission device. As shown in Figure 12, the uplink transmission device 1200 includes a first communication unit 1201, which is configured to:

[0361] The device on the terminal side is configured to use a codebook generated based on artificial intelligence functions or models for uplink transmission; and

[0362] Receive data transmitted uplink by the terminal device based on the codebook.

[0363] In some embodiments, the codebook is generated by a device on the network device side, or by a device on the terminal device side, or by a device on the terminal device side and a device on the network device side jointly.

[0364] In some embodiments, the codebook is generated by a device on the network device side, and the first communication unit is further configured to:

[0365] Send one or more codebook sets to the device on the terminal device side, wherein the one or more codebook sets include one or more precoding matrices generated based on artificial intelligence functions or models;

[0366] The precoding matrix for uplink transmission is selected from the codebook set using either an artificial intelligence-based method or a non-artificial intelligence-based method; and

[0367] The selected precoding matrix for uplink transmission is indicated or configured to the means on the terminal device side.

[0368] In some embodiments, the first communication unit further transmits at least one of the following:

[0369] The total number of precoding matrices;

[0370] The number of antenna ports in the precoding matrix;

[0371] The maximum rank supported by the precoding matrix in the codebook set;

[0372] Number of precoded matrices per rank;

[0373] Each rank value corresponds to one or more precoding matrices.

[0374] In some embodiments, the codebook is generated by a device on the terminal device side, and the first communication unit is further configured to:

[0375] The device receives one or more codebook sets sent by the terminal device, wherein the one or more codebook sets include one or more precoding matrices generated based on artificial intelligence functions or models;

[0376] The precoding matrix for uplink transmission is selected from the codebook set using either an artificial intelligence-based method or a non-artificial intelligence-based method; and

[0377] The selected precoding matrix for uplink transmission is indicated or configured to the means on the terminal device side.

[0378] In some embodiments, the first communication unit is further configured to receive at least one of the following:

[0379] The total number of precoding matrices;

[0380] The number of antenna ports in the precoding matrix;

[0381] The maximum rank supported by the precoding matrix in the codebook set;

[0382] Number of precoded matrices per rank;

[0383] Each rank value corresponds to one or more precoding matrices.

[0384] In some embodiments, the codebook is jointly generated by a device on the terminal device side and a device on the network device side, and the first communication unit is further configured to:

[0385] The precoding matrix for uplink transmission is selected from the codebook set using either an artificial intelligence-based method or a non-artificial intelligence-based method; and

[0386] The selected precoding matrix for uplink transmission is indicated or configured to the means on the terminal device side.

[0387] In some embodiments, at least one of the following information has the same meaning for both the network device-side device and the terminal device-side device:

[0388] The total number of precoding matrices;

[0389] The number of antenna ports in the precoding matrix;

[0390] The maximum rank supported by the precoding matrix in the codebook set;

[0391] Number of precoded matrices per rank;

[0392] Each rank value corresponds to one or more precoding matrices.

[0393] In some embodiments, the codebook generated based on artificial intelligence functions or models is used for all cells or transmitting / receiving points or sites, or for specific cells or transmitting / receiving points or sites.

[0394] In some embodiments, the codebook generated based on artificial intelligence features or models is used for near-field communication in a multiple-input multiple-output (MIMO) system.

[0395] This application also provides a downlink transmission apparatus. This apparatus is applied to a network device side device. The downlink transmission apparatus can be, for example, a network device, or one or more components or parts configured within the network device. It corresponds to the method applied to the network device side in the first aspect embodiment, and the content identical to that in the first aspect embodiment will not be repeated.

[0396] Figure 13 is a schematic diagram of a downlink transmission device. As shown in Figure 13, the downlink transmission device 1300 includes a second communication unit 1301, which is configured to:

[0397] The terminal device is configured to report channel state information using a codebook generated based on artificial intelligence functions or models; and

[0398] Downlink transmission is performed based on the codebook.

[0399] In some embodiments, the codebook is generated by a device on the terminal device side, or by a device on the network device side, or by a device on the terminal device side and a device on the network device side jointly.

[0400] In some embodiments, wherein the codebook is generated by a device on the terminal device side, the second communication unit is further configured to:

[0401] The device receives one or more codebook sets sent by the terminal device, wherein the one or more codebook sets include one or more precoding matrices generated based on artificial intelligence functions or models; and

[0402] The receiving device on the terminal side selects a precoding matrix for downlink transmission from the codebook set using a method based on artificial intelligence functions or models or a method based on non-artificial intelligence functions or models.

[0403] In some embodiments, the second communication unit is configured to receive at least one of the following:

[0404] The total number of precoding matrices;

[0405] The number of antenna ports in the precoding matrix;

[0406] The maximum rank supported by the precoding matrix in the codebook set;

[0407] Number of precoded matrices per rank;

[0408] Each rank value corresponds to one or more precoding matrices.

[0409] In some embodiments, the codebook is generated by a device on the network device side, and the second communication unit is further configured to:

[0410] Sending one or more codebook sets to the device on the terminal device side, wherein the one or more codebook sets include one or more precoding matrices generated based on artificial intelligence functions or models; and

[0411] The receiving device on the terminal side selects a precoding matrix for downlink transmission from the codebook set using a method based on artificial intelligence functions or models or a method based on non-artificial intelligence functions or models.

[0412] In some embodiments, the second communication unit is further configured to send at least one of the following:

[0413] The total number of precoding matrices;

[0414] The number of antenna ports in the precoding matrix;

[0415] The maximum rank supported by the precoding matrix in the codebook set;

[0416] Number of precoded matrices per rank;

[0417] Each rank value corresponds to one or more precoding matrices.

[0418] In some embodiments, the codebook is jointly generated by a device on the terminal device side and a device on the network device side, and the second communication unit is further configured to:

[0419] The receiving device on the terminal side selects a precoding matrix for downlink transmission from the codebook set using a method based on artificial intelligence functions or models or a method based on non-artificial intelligence functions or models.

[0420] In some embodiments, at least one of the following information has the same meaning for both the network device-side device and the terminal device-side device:

[0421] The total number of precoding matrices;

[0422] The number of antenna ports in the precoding matrix;

[0423] The maximum rank supported by the precoding matrix in the codebook set;

[0424] Number of precoded matrices per rank;

[0425] Each rank value corresponds to one or more precoding matrices.

[0426] In some embodiments, the codebook generated based on artificial intelligence functions or models is used for all cells or transmitting / receiving points or sites, or for specific cells or transmitting / receiving points or sites.

[0427] In some embodiments, the codebook generated based on artificial intelligence features or models is used for near-field communication in a multiple-input multiple-output (MIMO) system.

[0428] The above embodiments are merely illustrative examples of embodiments of this application, but this application is not limited thereto, and appropriate modifications can be made based on the above embodiments. For example, the above embodiments can be used alone, or one or more of the above embodiments can be combined.

[0429] It is worth noting that the above description only covers the components or modules relevant to this application, but this application is not limited thereto. Device 1200 or 1300 may also include other components or modules; for details regarding these components or modules, please refer to related technologies.

[0430] Furthermore, for simplicity, Figures 12 or 13 only exemplarily illustrate the connection relationships or signal flows between the various components or modules. However, those skilled in the art should understand that various related technologies, such as bus connections, can be employed. The aforementioned components or modules can be implemented using hardware facilities such as processors, memory, transmitters, and receivers; this application does not limit this implementation.

[0431] Fourth aspect of the embodiment

[0432] This application provides an uplink transmission apparatus. This apparatus is applied to a terminal device. The uplink transmission apparatus can be, for example, the terminal device itself, or one or more components or parts configured within the terminal device. It corresponds to the method applied to the terminal device side in the first aspect embodiment, and the same content as in the second aspect embodiment will not be repeated.

[0433] Figure 14 is a schematic diagram of an uplink transmission device. As shown in Figure 14, the uplink transmission device 1400 includes a third communication unit 1401, which is configured to:

[0434] Configured to use a codebook generated based on artificial intelligence features or models for uplink transmission; and

[0435] Based on the codebook, the uplink data is sent to the device on the network device side.

[0436] In some embodiments, the codebook is generated by a device on the network device side, or by a device on the terminal device side, or by a device on the terminal device side and a device on the network device side jointly.

[0437] In some embodiments, the codebook is generated by a device on the network device side, and the third communication unit:

[0438] The device receives one or more codebook sets sent by the network equipment side, wherein the one or more codebook sets include one or more precoding matrices generated based on artificial intelligence functions or models; and

[0439] The device configured or instructed on the network device side uses a precoding matrix selected from the codebook set for uplink transmission using a method based on artificial intelligence functions or models or a method based on non-artificial intelligence functions or models.

[0440] In some embodiments, the third communication unit receives at least one of the following:

[0441] The total number of precoding matrices;

[0442] The number of antenna ports in the precoding matrix;

[0443] The maximum rank supported by the precoding matrix in the codebook set;

[0444] Number of precoded matrices per rank;

[0445] Each rank value corresponds to one or more precoding matrices.

[0446] In some embodiments, the codebook is generated by a device on the terminal device side, and the third communication unit:

[0447] Send one or more codebook sets, wherein the one or more codebook sets include one or more precoding matrices generated based on artificial intelligence functions or models; and

[0448] The device configured or instructed on the network device side uses a precoding matrix selected from the codebook set for uplink transmission using a method based on artificial intelligence functions or models or a method based on non-artificial intelligence functions or models.

[0449] In some embodiments, the third communication unit also sends at least one of the following:

[0450] The total number of precoding matrices;

[0451] The number of antenna ports in the precoding matrix;

[0452] The maximum rank supported by the precoding matrix in the codebook set;

[0453] Number of precoded matrices per rank;

[0454] Each rank value corresponds to one or more precoding matrices.

[0455] In some embodiments, the codebook is jointly generated by a device on the terminal device side and a device on the network device side, wherein the third communication unit:

[0456] The device configured or instructed on the network device side selects a precoding matrix for uplink transmission from the codebook set using a method based on artificial intelligence functions or models or a method based on non-artificial intelligence functions or models.

[0457] In some embodiments, at least one of the following information has the same meaning for both the network device-side device and the terminal device-side device:

[0458] The total number of precoding matrices;

[0459] The number of antenna ports in the precoding matrix;

[0460] The maximum rank supported by the precoding matrix in the codebook set;

[0461] Number of precoded matrices per rank;

[0462] Each rank value corresponds to one or more precoding matrices.

[0463] In some embodiments, the codebook generated based on artificial intelligence functions or models is used for all cells or transmitting / receiving points or sites, or for specific cells or transmitting / receiving points or sites.

[0464] In some embodiments, the codebook generated based on artificial intelligence features or models is used for near-field communication in a multiple-input multiple-output (MIMO) system.

[0465] This application also provides a downlink transmission apparatus. This apparatus is applied to a terminal device. The downlink transmission apparatus can be, for example, the terminal device itself, or one or more components or parts configured within the terminal device. It corresponds to the method applied to the terminal device side in the first aspect embodiment, and the same content as in the second aspect embodiment will not be repeated.

[0466] Figure 15 is a schematic diagram of a downlink transmission device. As shown in Figure 15, the downlink transmission device 1500 includes a fourth communication unit 1501, which is configured to:

[0467] The device on the network equipment side is configured to report channel state information using a codebook generated based on artificial intelligence functions or models; and

[0468] The device on the network device side receives data transmitted downlink based on the codebook.

[0469] In some embodiments, the codebook is generated by a device on the terminal device side, or by a device on the network device side, or by a device on the terminal device side and a device on the network device side jointly.

[0470] In some embodiments, the codebook is generated by a device on the terminal device side, and the fourth communication unit:

[0471] Send one or more codebook sets, wherein the one or more codebook sets include one or more pre-encoding matrices generated based on artificial intelligence functions or models;

[0472] A precoding matrix for downlink transmission selected from the codebook set using methods based on artificial intelligence functions or models, or methods based on non-artificial intelligence functions or models; and

[0473] The report describes the precoding matrix selected by the device on the terminal side for downlink transmission.

[0474] In some embodiments, the device on the terminal device side further sends at least one of the following information:

[0475] The total number of precoding matrices;

[0476] The number of antenna ports in the precoding matrix;

[0477] The maximum rank supported by the precoding matrix in the codebook set;

[0478] Number of precoded matrices per rank;

[0479] Each rank value corresponds to one or more precoding matrices.

[0480] In some embodiments, the codebook is generated by a device on the network device side, and the fourth communication unit:

[0481] Receive one or more codebook sets, wherein the one or more codebook sets include one or more precoding matrices generated based on artificial intelligence functions or models;

[0482] A precoding matrix for downlink transmission selected from the codebook set using methods based on artificial intelligence functions or models, or methods based on non-artificial intelligence functions or models; and

[0483] The report selects the precoding matrix for downlink transmission.

[0484] In some embodiments, the device on the terminal device side further receives at least one of the following:

[0485] The total number of precoding matrices;

[0486] The number of antenna ports in the precoding matrix;

[0487] The maximum rank supported by the precoding matrix in the codebook set;

[0488] Number of precoded matrices per rank;

[0489] Each rank value corresponds to one or more precoding matrices.

[0490] In some embodiments, the codebook is jointly generated by a device on the terminal device side and a device on the network device side, wherein the fourth communication unit:

[0491] A precoding matrix for downlink transmission selected from the codebook set using methods based on artificial intelligence functions or models, or methods based on non-artificial intelligence functions or models; and

[0492] The report selects the precoding matrix for downlink transmission.

[0493] In some embodiments, at least one of the following information has the same meaning for both the network device-side device and the terminal device-side device:

[0494] The total number of precoding matrices;

[0495] The number of antenna ports in the precoding matrix;

[0496] The maximum rank supported by the precoding matrix in the codebook set;

[0497] Number of precoded matrices per rank;

[0498] Each rank value corresponds to one or more precoding matrices.

[0499] In some embodiments, the codebook generated based on artificial intelligence functions or models is used for all cells or transmitting / receiving points or sites, or for specific cells or transmitting / receiving points or sites.

[0500] In some embodiments, the codebook generated based on artificial intelligence features or models is used for near-field communication in a multiple-input multiple-output (MIMO) system.

[0501] The above embodiments are merely illustrative examples of embodiments of this application, but this application is not limited thereto, and appropriate modifications can be made based on the above embodiments. For example, the above embodiments can be used alone, or one or more of the above embodiments can be combined.

[0502] It is worth noting that the above description only covers the components or modules relevant to this application, but this application is not limited thereto. Device 1400 or 1500 may also include other components or modules; for details regarding these components or modules, please refer to related technologies.

[0503] Furthermore, for simplicity, Figures 14 or 15 only exemplarily illustrate the connection relationships or signal flows between the various components or modules. However, those skilled in the art should understand that various related technologies, such as bus connections, can be employed. The aforementioned components or modules can be implemented using hardware facilities such as processors, memory, transmitters, and receivers; this application does not limit this implementation.

[0504] Fifth aspect of the embodiment

[0505] This application provides a communication system, including a terminal device and a network device.

[0506] For example, the structure of the communication system can be seen with reference to FIG1. ​​As shown in FIG1, the communication system 100 includes network device 101 and terminal devices 102 and 103. At least one of the terminal devices 102, 103 and network device 101 may have the configuration of the electronic device shown in FIG16.

[0507] Figure 16 is a schematic block diagram of the electronic device. As shown in Figure 16, the electronic device 1600 may include a processor 1610 and a memory 1620; the memory 1620 is coupled to the processor 1610. The memory 1620 can store various data; in addition, it also stores an information processing program 1630, and executes the program 1630 under the control of the processor 1610 to receive or send various information.

[0508] In one embodiment, processor 1610 may be configured to perform the channel state information enhancement method in the first aspect embodiment and / or the channel state information enhancement method in the second aspect embodiment.

[0509] Furthermore, as shown in Figure 16, the electronic device 1600 may also include a transceiver 1640 and an antenna 1650, etc.; the functions of the above components are similar to those in the prior art, and will not be described in detail here. It is worth noting that the electronic device 1600 does not necessarily include all the components shown in Figure 16; in addition, the electronic device 1600 may also include components not shown in Figure 16, which can be referred to in the prior art.

[0510] This application also provides a computer program, wherein when the program is executed on a device on the network device side, the program causes the terminal device to perform the method described in the first aspect of the embodiment.

[0511] This application also provides a storage medium storing a computer program, wherein the computer program causes a device on a network device side to perform the method described in the first aspect embodiment.

[0512] This application also provides a computer program, wherein when the program is executed in a device on the terminal device side, the program causes the device on the terminal device side to perform the method described in the second aspect of the embodiment.

[0513] This application also provides a storage medium storing a computer program, wherein the computer program causes a device on a terminal device side to perform the method described in the second aspect of the embodiment.

[0514] The apparatus and methods described above in this application can be implemented in hardware or in combination with software. This application relates to a computer-readable program that, when executed by a logic component, enables the logic component to implement the apparatus or components described above, or to implement the various methods or steps described above. This application also relates to storage media for storing the above programs, such as hard disks, magnetic disks, optical disks, DVDs, flash memory, etc.

[0515] The methods / apparatus described in conjunction with the embodiments of this application can be directly embodied in hardware, software modules executed by a processor, or a combination of both. For example, one or more and / or combinations of one or more functional block diagrams shown in the figures can correspond to various software modules in a computer program flow, or to various hardware modules. These software modules can correspond to the various steps shown in the figures, respectively. These hardware modules can be implemented, for example, using a field-programmable gate array (FPGA) to embed these software modules.

[0516] The software module can reside in RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, hard disk, removable disk, CD-ROM, or any other form of storage medium known in the art. A storage medium can be coupled to the processor, enabling the processor to read information from and write information to the storage medium; or the storage medium can be an integral part of the processor. The processor and storage medium can reside in an ASIC. The software module can be stored in the memory of a mobile terminal or in a memory card that can be inserted into the mobile terminal. For example, if the device (such as a mobile terminal) uses a high-capacity MEGA-SIM card or a high-capacity flash memory device, the software module can be stored in the MEGA-SIM card or the high-capacity flash memory device.

[0517] One or more and / or one or more combinations of functional blocks described in the figures can be implemented as a general-purpose processor, digital signal processor (DSP), application-specific integrated circuit (ASIC), field-programmable gate array (FPGA), or other programmable logic device, discrete gate or transistor logic device, discrete hardware component, or any suitable combination thereof for performing the functions described in this application. One or more and / or one or more combinations of functional blocks described in FIG9 or FIG10 can also be implemented as a combination of computing devices, such as a combination of a DSP and a microprocessor, multiple microprocessors, one or more microprocessors in communication with a DSP, or any other such configuration.

[0518] The present application has been described above with reference to specific embodiments. However, those skilled in the art should understand that these descriptions are exemplary and not intended to limit the scope of protection of the present application. Those skilled in the art can make various modifications and variations to the present application based on its spirit and principles, and these modifications and variations are also within the scope of the present application.

[0519] According to the various embodiments disclosed in this application, the following notes are also disclosed:

[0520] 1. An uplink transmission method, applied to a network device side apparatus, the method comprising:

[0521] The network device-side device is configured to allow the terminal device-side device to perform uplink transmission using a codebook generated based on artificial intelligence functions or models; and

[0522] The device on the network device side receives the data transmitted uplink by the terminal device based on the codebook.

[0523] 2. A downlink transmission method, applied to a network device side apparatus, the method comprising:

[0524] The network device-side device is configured to enable the terminal device-side device to report channel state information using a codebook generated based on artificial intelligence functions or models; and

[0525] The network device performs downlink transmission based on the codebook.

[0526] 3. An uplink transmission method, applied to a device on the terminal equipment side, the method comprising:

[0527] The device on the terminal side is configured to perform uplink transmission using a codebook generated based on artificial intelligence functions or models; and

[0528] The terminal device sends uplink data to the network device based on the codebook.

[0529] 4. A downlink transmission method, applied to an apparatus on a terminal device side, the method comprising:

[0530] The terminal device is configured by the network device to report channel state information using a codebook generated based on artificial intelligence functions or models; and

[0531] The device on the network device side receives data transmitted downlink based on the codebook.

[0532] 5. A network device comprising a memory and a processor, the memory storing a computer program and the processor being configured to execute the computer program to implement the method as described in Appendix 1 or 2.

[0533] 6. A terminal device comprising a memory and a processor, the memory storing a computer program and the processor being configured to execute the computer program to implement the method as described in Appendix 3 or 4.

[0534] 7. A computer program product comprising at least a computer program that, when executed by a processor, causes a network device to perform the method as described in Appendix 1 or 2.

[0535] 8. A computer program product comprising at least a computer program that, when executed by a processor, causes a terminal device to perform the method as described in Appendix 3 or 4.

Claims

1. An uplink transmission apparatus, applied on the network device side, the uplink transmission apparatus comprising a first communication unit configured to: The device on the terminal side is configured to use a codebook generated based on artificial intelligence functions or models for uplink transmission; and Receive data transmitted uplink by the terminal device based on the codebook.

2. The method as described in claim 1, wherein, The codebook is generated by a device on the network device side, or by a device on the terminal device side, or by a combination of a device on the terminal device side and a device on the network device side.

3. The method as described in claim 2, wherein, The codebook is generated by a device on the network device side, and the first communication unit is further configured to: Send one or more codebook sets to the device on the terminal device side, wherein the one or more codebook sets include one or more precoding matrices generated based on artificial intelligence functions or models; The precoding matrix for uplink transmission is selected from the codebook set using either an artificial intelligence-based function or model-based method or a non-artificial intelligence-based function or model-based method. as well as The selected precoding matrix for uplink transmission is indicated or configured to the means on the terminal device side.

4. The method of claim 3, wherein, The first communication unit also sends at least one of the following: The total number of precoding matrices; The number of antenna ports in the precoding matrix; The maximum rank supported by the precoding matrix in the codebook set; Number of precoded matrices per rank; Each rank value corresponds to one or more precoding matrices.

5. The method of claim 2, wherein, The codebook is generated by a device on the terminal device side, and the first communication unit is further configured to: The device receives one or more codebook sets sent by the terminal device, wherein the one or more codebook sets include one or more precoding matrices generated based on artificial intelligence functions or models; The precoding matrix for uplink transmission is selected from the codebook set using either an artificial intelligence-based function or model-based method or a non-artificial intelligence-based function or model-based method. as well as The selected precoding matrix for uplink transmission is indicated or configured to the means on the terminal device side.

6. The method of claim 5, wherein, The first communication unit is also configured to receive at least one of the following: The total number of precoding matrices; The number of antenna ports in the precoding matrix; The maximum rank supported by the precoding matrix in the codebook set; Number of precoded matrices per rank; Each rank value corresponds to one or more precoding matrices.

7. The method of claim 2, wherein, The codebook is jointly generated by the device on the terminal device side and the device on the network device side, and the first communication unit is further configured to: The precoding matrix for uplink transmission is selected from the codebook set using either an artificial intelligence-based function or model-based method or a non-artificial intelligence-based function or model-based method. as well as The selected precoding matrix for uplink transmission is indicated or configured to the means on the terminal device side.

8. The method of claim 7, wherein, The meaning of at least one of the following information is the same for both the network device-side device and the terminal device-side device: The total number of precoding matrices; The number of antenna ports in the precoding matrix; The maximum rank supported by the precoding matrix in the codebook set; Number of precoded matrices per rank; Each rank value corresponds to one or more precoding matrices.

9. The method of claim 1, wherein, The codebook generated based on artificial intelligence functions or models may be used for all cells or transmitting / receiving points or sites, or for specific cells or transmitting / receiving points or sites.

10. The method of claim 1, wherein, The codebooks generated based on artificial intelligence functions or models are used for near-field communication in multiple-input multiple-output (MIMO) systems.

11. A downlink transmission apparatus, applied on the network device side, the downlink transmission apparatus comprising a second communication unit configured to: The terminal device is configured to report channel state information using a codebook generated based on artificial intelligence functions or models; and Downlink transmission is performed based on the codebook.

12. The method of claim 11, wherein, The codebook is generated by a device on the terminal device side, or by a device on the network device side, or by a combination of a device on the terminal device side and a device on the network device side.

13. The method of claim 12, wherein, The codebook is generated by a device on the terminal equipment side, and the second communication unit is further configured to: The device receives one or more codebook sets sent by the terminal device, wherein the one or more codebook sets include one or more precoding matrices generated based on artificial intelligence functions or models; as well as The receiving device on the terminal side selects a precoding matrix for downlink transmission from the codebook set using a method based on artificial intelligence functions or models or a method based on non-artificial intelligence functions or models.

14. The method of claim 13, wherein, The second communication unit is configured to receive at least one of the following: The total number of precoding matrices; The number of antenna ports in the precoding matrix; The maximum rank supported by the precoding matrix in the codebook set; Number of precoded matrices per rank; Each rank value corresponds to one or more precoding matrices.

15. The method of claim 12, wherein, The codebook is generated by a device on the network equipment side, and the second communication unit is further configured to: Send one or more codebook sets to the device on the terminal device side, wherein the one or more codebook sets include one or more precoding matrices generated based on artificial intelligence functions or models; as well as The receiving device on the terminal side selects a precoding matrix for downlink transmission from the codebook set using a method based on artificial intelligence functions or models or a method based on non-artificial intelligence functions or models.

16. The method of claim 15, wherein, The second communication unit is also configured to send at least one of the following: The total number of precoding matrices; The number of antenna ports in the precoding matrix; The maximum rank supported by the precoding matrix in the codebook set; Number of precoded matrices per rank; Each rank value corresponds to one or more precoding matrices.

17. The method of claim 12, wherein, The codebook is jointly generated by the device on the terminal device side and the device on the network device side, and the second communication unit is further configured to: The receiving device on the terminal side selects a precoding matrix for downlink transmission from the codebook set using a method based on artificial intelligence functions or models or a method based on non-artificial intelligence functions or models.

18. The method of claim 17, wherein, The meaning of at least one of the following information is the same for both the network device-side device and the terminal device-side device: The total number of precoding matrices; The number of antenna ports in the precoding matrix; The maximum rank supported by the precoding matrix in the codebook set; Number of precoded matrices per rank; Each rank value corresponds to one or more precoding matrices.

19. The method of claim 11, wherein, The codebook generated based on artificial intelligence functions or models may be used for all cells or transmitting / receiving points or sites, or for specific cells or transmitting / receiving points or sites.

20. The method of claim 11, wherein, The codebooks generated based on artificial intelligence functions or models are used for near-field communication in multiple-input multiple-output (MIMO) systems.

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