Data transmission method and device and storage medium

Abstract

The invention provides a data transmission method and device and a storage medium, relates to the technical field of wireless communication, and is beneficial to improving spectrum efficiency. The method comprises the following steps: determining K pieces of predicted channel information of K second nodes; based on the K pieces of predicted channel information, determining K pieces of first channel state information of the K second nodes; and performing data transmission based on the K pieces of first channel state information. Wherein the first channel state information is channel state information in the first transmission mode, the first channel state information comprises at least one first precoding matrix and / or at least one modulation and coding mode, and K is a positive integer greater than 1.

Description

Technical Field

[0001] The present disclosure relates to the field of wireless communication technology, and in particular to a data transmission method, device and storage medium. Background Art

[0002] In the field of wireless communications, improving spectrum efficiency is the key to development, and multi-antenna technology is the core means to achieve this goal. Its performance optimization is highly dependent on accurate channel state information (CSI). Multiple-input multiple-output (MIMO) technology, as a typical representative of multi-antenna technology, mainly includes single user multiple-input multiple-output (SU-MIMO) and multiple users multiple-input multiple-output (MU-MIMO).

[0003] In actual applications, base stations are usually equipped with a large number of antennas, while terminal devices are generally equipped with fewer antennas due to size and cost constraints. This difference enables MU-MIMO to multiplex more data streams under the same time-frequency resource conditions compared to SU-MIMO, thereby greatly improving the system's spectrum efficiency and throughput.

[0004] Although multi-antenna technology has shown great advantages, it still faces many technical challenges in fully unleashing its performance potential, especially in multi-user scenarios. Summary of the invention

[0005] The embodiments of the present disclosure provide a data transmission method, device and storage medium, which are conducive to improving spectrum efficiency. The technical solutions provided by the embodiments of the present disclosure are as follows:

[0006] In one aspect, a data transmission method is provided, which is applied to a first node, and the method includes:

[0007] Determine K predicted channel information of K second nodes;

[0008] Determine K first channel state information of K second nodes based on the K predicted channel information;

[0009] Data transmission is performed based on the K first channel state information.

[0010] The first channel state information is channel state information under a first transmission mode, the first channel state information includes at least one first precoding matrix and / or at least one modulation and coding method, and K is a positive integer greater than 1.

[0011] On the other hand, a data transmission method is provided, which is applied to a third node, and the method includes:

[0012] receiving data sent by the first node based on the first channel state information of the third node;

[0013] Among them, the first channel state information is determined based on K predicted channel information of K second nodes; the first channel state information is the channel state information under the first transmission mode, the first channel state information includes at least one first precoding matrix and / or at least one modulation and coding method, the K second nodes include a third node, and K is a positive integer greater than 1.

[0014] In another aspect, a data transmission device is provided, applied to a first node, the device comprising:

[0015] A processing module, used to determine K predicted channel information of K second nodes;

[0016] The processing module is further used to determine K first channel state information of K second nodes based on the K predicted channel information;

[0017] The communication module is used to perform data transmission based on K first channel state information.

[0018] The first channel state information is channel state information under a first transmission mode, the first channel state information includes at least one first precoding matrix and / or at least one modulation and coding method, and K is a positive integer greater than 1.

[0019] In another aspect, a data transmission device is provided, which is applied to a third node, and includes:

[0020] A communication module, configured to receive data sent by the first node based on the first channel state information of the third node;

[0021] Among them, the first channel state information is determined based on K predicted channel information of K second nodes; the first channel state information is the channel state information under the first transmission mode, the first channel state information includes at least one first precoding matrix and / or at least one modulation and coding method, the K second nodes include a third node, and K is a positive integer greater than 1.

[0022] On the other hand, a communication device is provided, comprising: a memory and a processor; the memory and the processor are coupled; the memory is used to store computer program instructions executable by the processor; and the processor implements the data transmission method of any of the above embodiments when executing the computer program instructions.

[0023] On the other hand, a computer-readable storage medium is provided, on which computer program instructions are stored. When the computer program instructions are executed on a computer (such as a communication device or a data transmission device), the data transmission method of any of the above embodiments is implemented.

[0024] On the other hand, a computer program product is provided, which includes computer program instructions, and when the computer program instructions are executed, the data transmission method of any of the above embodiments is implemented.

[0025] The technical solution provided by the embodiment of the present disclosure determines K predicted channel information of K second nodes; based on the K predicted channel information, determines K first channel state information of K second nodes; the first channel state information is the channel state information under the first transmission mode, and the first channel state information includes at least one first precoding matrix and / or at least one modulation and coding method. It solves the problem of poor accuracy of the channel state information determined by the traditional method under the first transmission mode (including MU-MIMO mode), improves the accuracy of channel state information determination under the first transmission mode, and then improves the performance of multi-user scheduling, which is conducive to improving spectrum efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 A schematic diagram of the structure of a wireless communication system provided by an embodiment of the present disclosure;

[0027] Figure 2 A flowchart of a data transmission method provided by an embodiment of the present disclosure;

[0028] Figure 3 A flowchart of another data transmission method provided by an embodiment of the present disclosure;

[0029] Figure 4 A schematic diagram of the structure of a data transmission device provided in an embodiment of the present disclosure;

[0030] Figure 5 A schematic diagram of the structure of another data transmission device provided by an embodiment of the present disclosure;

[0031] Figure 6 A schematic diagram of the structure of a communication device provided in an embodiment of the present disclosure. DETAILED DESCRIPTION

[0032] The following will be combined with the drawings in the embodiments of the present disclosure to clearly and completely describe the technical solutions in the embodiments of the present disclosure. Obviously, the described embodiments are only part of the embodiments of the present disclosure, not all of the embodiments. Based on the embodiments in the present disclosure, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present disclosure.

[0033] It should be understood that the specific implementations described herein are only used to explain the present disclosure, and are not used to limit the present disclosure.

[0034] In the subsequent description, suffixes such as "module", "component" or "unit" used to represent elements are only used to facilitate the description of the present disclosure and have no specific meanings themselves. Therefore, "module", "component" or "unit" may be used interchangeably.

[0035] In the description of the present disclosure, unless otherwise specified, " / " means "or", for example, A / B can mean A or B. "And / or" in this article is merely a description of the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. In addition, "at least one" means one or more, and "plurality" means two or more. The words "first", "second", etc. do not limit the quantity and execution order, and the words "first", "second", etc. do not limit them to be different.

[0036] Unless the context requires otherwise, throughout the specification and claims, the term "comprise" and other forms thereof, such as the third person singular form "comprises" and the present participle form "comprising", are to be interpreted as open, inclusive, that is, "including, but not limited to". In the description of the specification, the terms "one embodiment", "some embodiments", "exemplary embodiments", "example", "specific example" or "some examples" and the like are intended to indicate that specific features, structures, materials or characteristics associated with the embodiment or example are included in at least one embodiment or example of the present disclosure. The schematic representation of the above terms does not necessarily refer to the same embodiment or example. In addition, the specific features, structures, materials or characteristics may be included in any one or more embodiments or examples in any appropriate manner.

[0037] The terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features. In the description of the present disclosure, unless otherwise specified, "plurality" means two or more.

[0038] In the embodiments of the present disclosure, words such as "exemplary" or "for example" are used to indicate examples, illustrations, or descriptions. Any embodiment or design described as "exemplary" or "for example" in the embodiments of the present disclosure should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "exemplary" or "for example" is intended to present related concepts in a specific way.

[0039] Additionally, the use of “based on” is meant to be open and inclusive, as a process, step, calculation, or other action “based on” one or more stated conditions or values ​​may, in practice, be based on additional conditions or values ​​beyond those stated.

[0040] In the field of wireless communications, improving spectrum efficiency is the key to development, and multi-antenna technology is the core means to achieve this goal, and its performance optimization is highly dependent on accurate channel state information (CSI). Multiple-input multiple-output (MIMO) technology, as a typical representative of multi-antenna technology, mainly includes single-user multiple-input multiple-output (SU-MIMO) and multi-user multiple-input multiple-output (MU-MIMO).

[0041] SU-MIMO, which can be written as SU, uses multiple antennas to send multiple data streams to a single terminal in terms of time and frequency resources, and the user also receives data through multiple antennas. This technology can significantly improve the data transmission rate of a single terminal, and its advantages are fully demonstrated in scenarios with urgent needs for high rates, such as high-definition video transmission, large file downloads, and other application scenarios, which can ensure smooth and efficient data transmission experience.

[0042] MU-MIMO, which can be written as MU, is unique in that it allows base stations to serve multiple terminals on the same time and frequency resources. Compared with the traditional single-user transmission mode, MU-MIMO greatly increases the system capacity. It performs spatial orthogonal processing on the signals of multiple terminals, allowing the signals of different users to be transmitted on the same time and frequency resources without interfering with each other, thereby fully tapping the potential of spectrum resources and effectively improving spectrum utilization. In practical applications, base stations are usually equipped with a large number of antennas, such as the common 32 antennas, 64 antennas, or even 128 antennas; while terminal devices are generally equipped with fewer antennas, mostly 2-4 antennas, due to size and cost constraints. This difference enables MU-MIMO to multiplex more data streams under the same time and frequency resource conditions compared to SU-MIMO, thereby greatly improving the system's spectrum efficiency and throughput.

[0043] Although multi-antenna technology has shown great advantages, it still faces many technical challenges to fully unleash its performance potential, especially in multi-user scenarios. First, in frequency division duplexing (FDD) mode, the interference estimation between multiple users is extremely complex. Since different user signals are transmitted simultaneously in the frequency domain, mutual interference is difficult to accurately predict and effectively suppress. However, interference estimation first requires more accurate CSI acquisition in multi-user scenarios. Secondly, there is a lack of scientific and effective methods for the reasonable pairing of multiple users.

[0044] Under the framework of traditional technology, solving the above problems faces many difficulties. Traditional interference estimation methods have high computational complexity and poor accuracy, and cannot adapt to the complex environment of dynamic changes of multiple users; multi-user pairing algorithms lack intelligence and adaptability, making it difficult to achieve optimal resource allocation; traditional means of obtaining CSI not only have limited accuracy, but also have obvious deficiencies in feedback overhead and real-time performance, which seriously restricts the performance improvement of multi-antenna technology in multi-user scenarios.

[0045] In view of this, the present disclosure provides a data transmission method, which includes: determining K predicted channel information of K second nodes; based on the K predicted channel information, determining K first channel state information of the K second nodes; the first channel state information is the channel state information under the first transmission mode, and the first channel state information includes at least one first precoding matrix and / or at least one modulation and coding method. The problem of poor accuracy of the channel state information determined by the traditional method under the first transmission mode (including the multi-user multiple input multiple output mode) is solved, and the accuracy of the channel state information determination under the first transmission mode is improved, thereby improving the performance of multi-user scheduling, which is conducive to improving the spectrum efficiency. It is expected to promote the further development and application of multi-antenna technology in the field of wireless communications.

[0046] The following describes the technical means involved in the embodiments of the present disclosure.

[0047] In the present disclosure, high-layer signaling includes but is not limited to radio resource control (RRC), media access control element (MAC CE), and other high-layer signaling other than physical layer signaling. Physical layer signaling includes but is not limited to: downlink physical layer signaling transmitted on physical downlink control channel (PDCCH), uplink physical layer signaling transmitted on physical uplink control channel (PUCCH), and physical layer signaling transmitted on physical uplink shared channel (PUSCH).

[0048] In some embodiments, the physical channel is divided into a physical downlink channel and a physical uplink channel. The physical downlink channel includes but is not limited to: a physical downlink control channel (physical downlink control channel, PDCCH) and a physical downlink shared channel (physical downlink shared channel, PDSCH). The physical uplink channel includes but is not limited to: a physical uplink control channel (physical uplink control channel, PUCCH) and a physical uplink shared channel (physical uplink shared channel, PUSCH). In some embodiments, the PDCCH is mainly used to transmit downlink control information (downlink control information, DCI). The PUCCH is mainly used to transmit uplink control information (uplink control information, UCI), such as channel state information (channel state information, CSI), hybrid automatic repeat request (hybrid automatic repeat request, HARQ), scheduling request, etc. The PDSCH is mainly used to transmit downlink data and downlink signaling, etc. The PUSCH is mainly used to transmit uplink data and uplink signaling, etc.

[0049] In some embodiments, the indicators of various parameters may also be referred to as indexes or identifiers (IDs). Indications, identifiers, and indexes are equivalent concepts and may be interchangeable in some embodiments.

[0050] In some embodiments, transmission includes sending or receiving. For example, transmitting data can be understood as sending data or receiving data, and transmitting signals can be understood as sending signals or receiving signals. In some embodiments, physical layer signaling and / or high layer signaling are also a type of data.

[0051] In some embodiments, in order to obtain channel state information or perform channel estimation, mobility management, positioning, etc., the communication node needs to transmit a reference signal (reference signal, RS). Among them, the reference signal includes but is not limited to a channel state information reference signal (channel-state information reference signal, CSI-RS), a channel state information interference measurement signal (channel-state information-interference measurement, CSI-IM), a sounding reference signal (sounding reference signal, SRS), a synchronization signal block (synchronization signals block, SSB), a physical broadcast channel (physical broadcast channel, PBCH), and a synchronization signal block / physical broadcast channel (SSB / PBCH). In some embodiments, the SSB includes a synchronization signal block and / or a physical broadcast channel. In some embodiments, the channel state information reference signal includes a zero power CSI-RS (zero power CSI-RS, ZP CSI-RS) and a non-zero power CSI-RS (non-zero power CSI-RS, NZP CSI-RS). In addition, the time-frequency resources used to transmit the reference signal are called reference signal resources, and the reference signal resources include a set of one or more resource elements (ResourceElement, RE),

[0052] For example, CSI-RS resource, SRS resource, CSI-IM resource, SSB resource, etc. The reference signal is transmitted on the reference signal resource.

[0053] In some embodiments, a time instance represents a time period, such as a time instance may be a time slot, a mini slot or a symbol group. A time slot or a sub-time slot may include at least one symbol. In one embodiment, a symbol refers to a time unit in a subframe, a frame or a time slot, and the unit may be milliseconds, microseconds, nanoseconds, seconds, etc. In one embodiment, a symbol may be an orthogonal frequency division multiplexing (OFDM) symbol, a single-carrier frequency division multiple access (SC-FDMA) symbol, an orthogonal frequency division multiple access (OFDMA) symbol, or symbols corresponding to various waveforms in future communication systems, etc. In some embodiments, the time slot may be replaced by a time instance, a sub-time slot, etc.

[0054] In some embodiments, the transmission unit carrying a modulation symbol is a resource element (RE), which is the minimum time-frequency resource for transmitting a modulation symbol, including a subcarrier and a radio resource on a symbol. The time-frequency resources composed of one or more subcarriers on one or more symbols constitute a physical resource block (PRB).

[0055] In some embodiments, some threshold values, or preset threshold values, are required, and these threshold values ​​can be at least one of the following: real numbers, positive integers, integers, Boolean values, characters, and character strings. The threshold value can be agreed upon by the base station and the terminal, or a default value, or an empirical value obtained according to simulation or practice, or an indication to each other by communication nodes through high-level and / or physical layer signaling. For ease of distinction, a first threshold, a second threshold, etc. can be included, which are only used to distinguish different threshold values, not for sorting. In some other embodiments, the threshold can be replaced by a threshold group, each threshold group including one or more thresholds.

[0056] In some embodiments, the channel information is information obtained based on a reference signal (such as CSI-RS) for describing the channel environment between communication nodes. In one embodiment, the channel information is a complex matrix, which can be called a channel matrix. The size of the channel matrix is ​​related to the number of transmitting antennas Nt, the number of receiving antennas Nr, and the number of resource elements.

[0057] In some embodiments, the channel information may include at least one of the following: time domain channel information, frequency domain channel information, one or more eigenvectors of the correlation matrix corresponding to the time domain channel information, one or more singular vectors of the correlation matrix corresponding to the time domain channel information, one or more eigenvectors of the correlation matrix corresponding to the frequency domain channel information, one or more singular vectors of the correlation matrix corresponding to the frequency domain channel information, a precoding matrix corresponding to the frequency domain channel, a precoding matrix corresponding to the time domain channel, one or more codewords corresponding to the frequency domain channel, and one or more codewords corresponding to the time domain channel. Here, both the time domain channel information and the frequency domain channel information may represent information for describing channel characteristics between at least one transmitting antenna and at least one receiving antenna, and may be a matrix or a multi-dimensional array or a multi-dimensional matrix.

[0058] In some embodiments, the information processing method includes at least a linear information processing method and a nonlinear information processing method. Among them, the nonlinear information processing method includes but is not limited to various advanced information processing technologies, such as artificial intelligence (AI). In some embodiments, for the convenience of description, the nonlinear information processing method is also referred to as the first type of information processing method, and the linear information processing method is also referred to as the second type of information processing method. In one embodiment, one information processing method corresponds to one information processing technology. In one embodiment, one information processing method corresponds to one model. In one embodiment, one information processing method corresponds to one function.

[0059] In some embodiments, channel-state information (CSI) includes downlink channel state information and uplink channel state information, which are referred to as downlink channel state information and uplink channel state information, respectively.

[0060] In some embodiments, the downlink channel state information includes but is not limited to at least one of the following information: channel state information-reference signal resource indicator (CSI-RS resource indicator, CRI), synchronization signal block resource indicator (synchronization signals block resource indicator, SSBRI), layer 1 reference signal received power (L1 reference signal received power, L1-RSRP), differential RSRP (differential RSRP, differential L1-RSRP), layer 1 reference signal signal-to-interference noise ratio (L1 signal-to-interference noise ratio, L1-SINR), differential L1-SINR (differential L1-SINR, differential L1-SINR), reference signal received quality (reference signal received quality, RSRQ), differential RSRQ, channel quality indicator (channel quality indicator, CQI), wideband CQI, subband CQI, precoding matrix indicator (precoding matrix indicator, PMI), layer indicator (layer indicator, LI), rank indicator (rank indicator, RI), precoding information, channel information, capability index (CapabilityIndex), time-domain channel attributes (time-domain channelproperties, TDCP).

[0061] In some embodiments, L1-RSRP or differential RSRP is collectively referred to as L1-RSRP, referred to as RSRP for short. In some embodiments, L1-SINR or differential SINR is collectively referred to as L1-SINR, referred to as SINR for short.

[0062] In some embodiments, the uplink channel state information includes but is not limited to at least one of the following information: uplink sounding signal resource indicator (SRS resource Indicator, SRI), uplink sounding signal resource set indicator (SRS resource set Indicator, SRSI), transmission precoding matrix indicator (Transmitted Precoding Matrix Indicator, TPMI), transmission rank indicator (Transmitted Rank Indicator, TRI), modulation and coding scheme (Modulation and coding scheme, MCS) (or modulation and coding mode). In addition, TPMI and TRI may be jointly encoded, using the precoding information and number of layers field indication (i.e., Precoding information and number of layers, PINL) in the DCI.

[0063] In some embodiments, CSI includes wideband CSI and subband CSI, wherein subband CSI means that each subband corresponds to a different CSI. The CSI here may include but is not limited to at least one of the following: CRI, rank indication (RI), CQI, PMI, LI, L1-RSRP, layer 1 reference signal received quality (L1 reference signal received quality, L1-RSRQ), L1-SINR, SRI, TPMI, TRI, MCS. For example, in one embodiment, CQI is divided into wideband CQI and subband CQI. In one embodiment, PMI is divided into wideband PMI and subband PMI. In one embodiment, RI is divided into wideband RI and subband RI. In one embodiment, MCS is divided into wideband MCS and subband MCS. In some embodiments, subband CQI may also be replaced by subband differential CQI. In some embodiments, wideband PMI may also be replaced by PMI wideband information domain, and subband PMI may also be replaced by PMI subband information domain.

[0064] In some embodiments, the precoding information includes first type precoding information and second type precoding information. The precoding information may include the precoding itself or a quantization value corresponding to the precoding, various sub-band or wideband precoding matrix indicators PMI, and the like.

[0065] In some embodiments, the first type of precoding information is precoding information implemented in a nonlinear manner, such as precoding information obtained based on AI and other technologies, including CSI generated by compression based on at least one dimension of space, time and frequency, such as channel state information generated based on joint compression of space and frequency and channel state information generated based on joint compression of space, time and frequency.

[0066] In some embodiments, the second type of precoding information is conventional precoding information generated based on linear technology, such as precoding information based on codebooks, such as various codebook technologies based on discrete Fourier transform (DFT) vectors. In one embodiment, the codebook may be a codebook for N antennas in long term evolution (LTE), where N is a positive integer greater than 2. In one embodiment, the codebook includes but is not limited to one of the following codebooks in NR: type I codebook, type II codebook, type II port selection codebook, enhanced type II codebook, enhanced type II selection codebook, Further enhanced type II selection codebook, Doppler codebook, coherent joint transmission (CJT) codebook, etc. In one embodiment, it may also be a codebook generated by a future wireless communication system based on linear technology, such as various DFT-based codebooks. The precoding matrix indication PMI in the present disclosure is one of the precoding information based on the codebook.

[0067] In some instances, the location information includes, but is not limited to, at least one of the following: information related to transmission time, information related to angle, information related to received reference signal quality, information related to multipath, coordinates of the first node (including absolute coordinates and relative coordinates), and coordinates of the second node.

[0068] In some embodiments, the transmission time related information includes at least one of the following: arrival time (TOA), reference signal time difference (RSTD), relative time of arrival (RTOA), Rx-Tx time difference, Tx-Rx time difference, etc.

[0069] In some embodiments, the angle-related information includes at least one of the following: angle of arrival (angle of arrival, AoA), angle of departure (angle Of departure, AOD), zenith angle of arrival (zenith angle of arrival, ZOA) and azimuth angle of departure (azimuth angle of departure, AOD), and the departure angle includes the zenith angle of departure (zenith angle of departure, ZOD) and the azimuth angle of departure (azimuth angle of departure, AOA).

[0070] In some embodiments, the received reference signal quality related information includes at least one of the following: reference signal received power (reference signal received power, RSRP or L1-RSRP), SINR (or L1-SINR), CQI, signal-to-noise ratio (signal-to-noise ratio, SNR), RSRQ.

[0071] In some embodiments, in order to transmit measurement results at the physical layer, such as channel state information. The communication node needs to configure a report (e.g., CSI report or CSI report congfig), wherein the report defines at least one of the following parameters: time-frequency resources used to transmit measurement results, report quality reportQuantity, report time domain category reportConfigType, channel measurement resources, interference measurement resources, measurement bandwidth size and other information. The report can be transmitted on uplink transmission resources, wherein the uplink transmission resources include PUSCH and PUCCH, and the report time domain category includes periodic report (e.g., periodic CSI report, P-CSI), non-periodic report (e.g., aperiodic CSIreport, AP-CSI), semi-persistent report (e.g., semi-persistent CSI report, SP-CSI). The measurement resources are transmitted on the resources specified by the CSI report, where transmission includes sending or receiving.

[0072] In some embodiments, the antenna is a physical antenna. In some embodiments, the antenna is a logical antenna. In some embodiments, the port and antenna, antenna port, reference signal port, and pilot port are interchangeable. In some embodiments, the antenna is a transmitting antenna. In some embodiments, the antenna is a receiving antenna. In some embodiments, the antenna includes an antenna pair of a transmitting antenna and a receiving antenna.

[0073] In some embodiments, the antenna includes an antenna pair of a transmitting antenna and a receiving antenna. In some embodiments, the antenna can be a uniform linear array. In some embodiments, the antenna is a uniform planar array. In some embodiments, the antenna is a uniform circular array. In some embodiments, the antenna can be a non-uniform linear array. In some embodiments, the antenna is a non-uniform planar array. In some embodiments, the antenna is a non-uniform circular array. In some embodiments, the antenna is a directional antenna, and in some embodiments, the antenna is an omnidirectional antenna. In some embodiments, the antenna is a dual-polarized antenna. In some embodiments, the antenna is a single-polarized antenna.

[0074] The communication network in the embodiments of the present disclosure includes but is not limited to the third generation mobile communication technology (3G), the fourth generation mobile communication technology (4G), the fifth generation mobile communication technology (5G), and future mobile communication networks, such as 6G, 7G, etc. The network architecture may include network side devices (for example, including but not limited to base stations) and receiving side devices (for example, including but not limited to terminals). The first communication node and the second communication node may be a base station or a terminal, respectively. The first communication node and the second communication node may be referred to as the first node and the second node, respectively. In one embodiment, the first communication node is a base station and the second communication node is a terminal. In one embodiment, the first communication node is a base station and the second communication node is a base station. In one embodiment, the first communication node is a terminal and the second communication node is a terminal. In one embodiment, the first communication node is a terminal and the second communication node is a base station. In some embodiments, the communication node includes a first node and / or a second node. In some embodiments, the communication node may also be referred to as a node, and the node may be a first node or a second node.

[0075] In some embodiments, a wireless communication system includes one or more base stations and one or more terminals. Each base station includes multiple antennas, and each terminal may include one or more antennas. The base station sends a reference signal on at least one reference signal resource, and the terminal receives the reference signal on at least one reference signal resource and measures the reference signal to obtain at least one channel state information.

[0076] Figure 1 FIG. 1 is a schematic diagram of a wireless communication system provided by an embodiment of the present disclosure. Figure 1 As shown, the wireless communication system includes but is not limited to a first node 110 and a second node 120. The first node 110 and the second node 120 can send, receive and perform related interactions on wireless signals.

[0077] In a wireless communication scenario, the first node 110 communicates with the second node 120 through a wireless channel. For example, the first node 110 is a base station, the second node 120 is a terminal, and the base station and the terminal communicate through a wireless channel. For another example, the first node 110 is a wireless router, the second node 120 is a terminal, and the wireless router and the terminal communicate through a wireless channel. For another example, the first node 110 is a first base station, the second node 120 is a second base station, and the first base station and the second base station communicate through a wireless channel. For another example, the first node 110 is a first terminal, the second node 120 is a second terminal, and the first terminal and the second terminal communicate through a wireless channel. For another example, the first node 110 is a base station, the second node 120 is a repeater, and the base station and the repeater communicate through a wireless channel. For another example, the first node 110 is a repeater, the second node 120 is a terminal, and the repeater and the terminal communicate through a wireless channel. For another example, the first node 110 is a first repeater, the second node 120 is a second repeater, and the first repeater communicates with the second repeater through a wireless channel. For another example, the first node 110 is a base station, the second node 120 is a satellite, and the satellite and the base station communicate through a wireless channel. For another example, the first node 110 is a satellite, the second node 120 is a base station, and the base station and the satellite communicate through a wireless channel. For another example, the first node 110 is a terminal, the second node 120 is a satellite, and the satellite and the terminal communicate through a wireless channel. For another example, the first node 110 is a satellite, the second node 120 is a terminal, and the terminal and the satellite communicate through a wireless channel. For another example, the first node 110 is a ground device, the second node 120 is an aircraft, and the aircraft and the ground device communicate through a wireless channel. For another example, the first node 110 is a first aircraft, the second node 120 is a second aircraft, and the first aircraft and the second aircraft communicate through a wireless channel.

[0078] In some embodiments, the base station may be a base station or an evolved base station (eNB or eNodeB) in LTE, long term evolution advanced (LTEA), a base station device in a fifth generation wireless communication system, or a base station in a future wireless communication system (such as 6G, etc.), etc. The base station may include various macro base stations, micro base stations, home base stations (Femtocell or Home eNodeB), wireless remotes, reconfigurable intelligent surfaces (RISs), routers, wireless fidelity (WIFI) devices, and other network side devices.

[0079] In some embodiments, the terminal is a device with wireless transceiver function, which can be deployed on land, including indoors or outdoors, or in a car; it can also be deployed on the water surface (such as a ship, etc.); it can also be deployed in the air (for example, on airplanes, balloons and satellites, drones, various aircraft, etc.). The terminal can be a mobile phone, a tablet computer (Pad), a computer with wireless transceiver function, a virtual reality (VR) terminal, an augmented reality (AR) terminal, a wireless terminal in industrial control, a wireless terminal in self-driving, a wireless terminal in remote medical, a wireless terminal in smart grid, a wireless terminal in transportation safety, a wireless terminal in smart city, a wireless terminal in smart home, a wireless terminal on various aircraft such as drones, etc. The embodiments of the present disclosure do not limit the application scenarios. A terminal may also be sometimes referred to as a user, user equipment (UE), access terminal, UE unit, UE station, mobile station, mobile station, remote station, remote terminal, mobile device, UE terminal, wireless communication device, UE agent or UE device, etc. The embodiments of the present disclosure are not limited thereto.

[0080] It should be noted that Figure 1 This is just an exemplary framework diagram. Figure 1 The number of devices included in the Figure 1 In addition to the devices shown, the communication system may also include other devices, such as relay nodes, core network devices, etc.

[0081] The application scenarios of the embodiments of the present disclosure are not limited. The system architecture and business scenarios described in the embodiments of the present disclosure are intended to more clearly illustrate the technical solutions of the embodiments of the present disclosure, and do not constitute a limitation on the technical solutions provided by the embodiments of the present disclosure. It is known to those skilled in the art that with the evolution of network architecture and the emergence of new business scenarios, the technical solutions provided by the embodiments of the present disclosure are also applicable to similar technical problems.

[0082] In some embodiments, data transmission between communication nodes includes a first transmission mode and a second transmission mode, wherein the first transmission mode may include MU-MIMO of joint transmission of multiple base stations and MU-MIMO of a single base station, and the second transmission mode includes SU-MIMO of joint transmission of multiple base stations and SU-MIMO of a single base station.

[0083] In some embodiments, the channel state information in the first transmission mode is called the first channel state information, including but not limited to at least one of the following: one or more first precoding matrices, one or more first channel quality indicators, one or more first MCSs, and one or more first SINRs. The channel state information in the second transmission mode is called the second channel state information.

[0084] In some embodiments, the channel state information in the second transmission mode is called second channel state information, including but not limited to at least one of the following: one or more second precoding matrices, one or more second channel quality indicators, one or more second MCSs, and one or more second SINRs.

[0085] In one embodiment, there is a wireless communication system, including at least one base station and at least one terminal. The base station includes N t The kth terminal receives the reference signal on the at least one reference signal resource and measures the channel matrix H k , it is an N r ×N t ×N rb According to the channel matrix H k The channel state information obtained on each subband (ie, the channel state information in the second transmission mode) includes but is not limited to at least one of the following: the wideband precoding matrix p k , at least one subband precoding matrix p k,u , at least one subband CQI k,u , broadband CQI k , RI, interference noise intensity, etc. The terminal sends the channel state information. The base station receives the channel state information. And processes the channel state information for scheduling.

[0086] In one example, the precoding matrix may also be a quantized value of a precoding matrix, such as a precoding matrix indicating a PMI, or a precoding matrix or a quantized value thereof may be obtained by artificial intelligence or the like. If it is a PMI, then it is necessary to map the PMI to the precoding matrix in a manner agreed upon by the base station and the terminal. If it is a quantized value of a precoding matrix output by an artificial intelligence encoder, then the base station needs to dequantize the quantized precoding to obtain a precoding matrix, and input it into a decoder to obtain the final precoding matrix. In some other embodiments, it will be directly stated that the base station obtains one or more precoding matrices from the CSI sent by the terminal, and these operations of recovering the precoding matrix from the quantized precoding matrix will not be described one by one.

[0087] In one embodiment, the subband CQI obtained by the k-th terminal is obtained by quantizing the SINR obtained by it. The calculation formula of the signal to interference noise ratio of the k-th terminal under SU is:

[0088]

[0089] Here, SINR SU,k,u is the signal to interference noise ratio on the u-th subband of the k-th terminal under SU, h k,u , w k,u , I k,u They respectively represent the channel matrix, the second precoding matrix, the noise, and the interference received from the neighboring cell of the k-th terminal under SU on the u-th subband.

[0090] In one embodiment, in order to obtain higher spectrum efficiency, the base station schedules multiple terminals on the same time-frequency resources at the same time. Multiple terminals perform spatial multiplexing transmission. In order to determine whether two or more terminals are suitable for MU, it is necessary to first calculate the SINR of the MU, and determine the spectrum efficiency or throughput of the paired user under MU transmission based on the SINR of the MU. Assume that the base station plans to allow K terminals to perform MU transmission. Then among the K terminals performing MU transmission, the SINR of the u-th subband of the k-th terminal is MU,k,u Determined by the following formula:

[0091]

[0092] Among them, h k,u , w k,u , I k,u They respectively represent the channel matrix, precoding matrix, noise, and interference from neighboring cells of the kth terminal under SU on the uth subband. w j,u They respectively represent the MU interference suffered by the k-th terminal on the u-th subband, and the second precoding matrix of the j-th terminal on the u-th subband.

[0093] In one example, the wireless communication system is a time division multiplexing system, and the base station obtains an uplink reference signal by measurement, for example, by measuring the SRS to obtain an uplink channel matrix h on the u-th subband of the k-th terminal. k,u .

[0094] In one example, the wireless communication system is a frequency division multiplexing system. In this case, the base station cannot obtain the uplink channel matrix h of the kth terminal on the uth subband. k,u Only the following channel state information of the SU sent by the terminal can be obtained, including but not limited to at least one of the following: wideband precoding matrix pk , at least one subband precoding matrix p k,u , at least one subband CQI k,u , broadband CQI k .

[0095] The following will use multiple embodiments to illustrate how the base station predicts a more accurate channel matrix and a precoding matrix of the MU based on the CSI under the SU fed back by the terminal, and how to calculate the modulation and coding scheme of each terminal in the MU based on the calculated channel matrix and precoding matrix.

[0096] In one embodiment, in order to fully obtain the performance of multi-user MIMO, multiple high-performance artificial intelligence models are saved and exist. The artificial intelligence model can be called a model. In one embodiment, artificial intelligence includes machine learning (ML), deep learning, reinforcement learning, transfer learning, deep reinforcement learning, meta-learning, etc.

[0097] In one embodiment, artificial intelligence is implemented by an artificial intelligence model (or neural network), the model includes multiple layers, each layer includes at least one node (node ​​in the neural network), in one embodiment, the neural network includes an input layer, an output layer, and at least one hidden layer. In one embodiment, the model refers to the data flow from the input to the output of the sample passing through multiple linear or nonlinear components. The model includes a neural network model, a non-artificial intelligence module for processing information, and a functional component or function that maps input information to output information, where the mapping includes linear mapping and nonlinear mapping. In one embodiment, each model corresponds to a model identity (ModelID). In one embodiment, the model identity can also have one of the following other equivalent names or concepts: model index, first identification, function indicator (ID), model indicator, etc.

[0098] In one embodiment, the model parameters are obtained by online training or offline training. For example, the model parameters are trained by inputting at least one sample. The sample includes at least one feature and at least one label. The feature of the sample is used as the input of the model, and the label of the sample is the ideal value corresponding to the output of the model, which is used for performance monitoring or calculating the loss function.

[0099] In one embodiment, a sample includes P features and Q labels, where P is a positive integer and Q is an integer greater than or equal to 0. Multiple samples constitute a data set.

[0100] In one embodiment, a feature can be an array. In one embodiment, a label is also an array. Here, the array can be a vector or a matrix, or a tensor greater than two dimensions. The dimension of the array corresponding to the sample is also referred to as the dimension of the sample array. Here, each element in the array can be a discrete value, a real value, a real value from 0 to 1, a real value from -0.5 to 0.5, and so on.

[0101] In one implementation, the base station has multiple models, wherein the models include but are not limited to one of the following neural networks, and a composite neural network of combinations thereof: feedforward neural network (FNN), convolutional neural network (CNN), recurrent neural network (RNN), long short-term memory network (LSTM), gated recurrent unit (GRU), generative adversarial network (GAN), variational autoencoder (VAE), attention mechanism network, graph neural network (GNN), capsule network, etc. In these embodiments, for ease of distinction, the models are represented as the first model, the second model, etc. The first and second here are only to distinguish different models, and do not sort the models, or to imply the priority or quality of the models.

[0102] In some embodiments, the kth terminal among multiple terminals is taken as an example, where k=1, ..., K, where K is a positive integer representing the number of terminals served by a cell or the number of terminals that need to be paired as MUs. Similar operations are performed for other terminals, which will not be described one by one.

[0103] In some embodiments, in order to facilitate better processing of the AI ​​model, a series of preprocessing is performed on the input data of the model, including but not limited to normalizing the input data, splitting the real and imaginary parts of each element of the input data, grouping the input data, filling with zeros, and dimension changes, and the processed data is input into the AI ​​model. In some embodiments, a series of subsequent processing is also required for the output of the model so that the processed data meets the requirements of the output format and other requirements. Among them, the subsequent processing can be a series of inverse processes of the preprocessing. In the following embodiments, they will not be repeated one by one.

[0104] The first transmission mode in the present disclosure may be MU-MIMO, and the second transmission mode may be SU-MIMO.

[0105] The present disclosure provides a data transmission method which can be applied to a first node. Figure 2 As shown, the method comprises the following steps:

[0106] S101. Determine K predicted channel information of K second nodes.

[0107] In some embodiments, the K predicted channel information includes predicted channel matrices on respective subbands of the K second nodes.

[0108] The predicted channel matrix on each subband of the K second nodes in the present disclosure can be expressed as k is a non-negative integer less than or equal to K. It can also be expressed as k=1,…,K, where K is the number of paired second nodes (terminals) in the first transmission mode, and is an integer greater than 1. u=1,…,U, where U is a positive integer, indicating the number of subbands or RBs of the second node (terminal).

[0109] In some embodiments, determining K predicted channel information of K second nodes includes: for a kth second node among the K second nodes, obtaining second channel state information of the kth second node; based on the second channel state information of the kth second node, determining a predicted channel matrix on each subband of the kth second node, where k is a non-negative integer less than or equal to K.

[0110] The second channel state information is the channel state information under the second transmission mode, and the second channel state information of the kth second node includes the second precoding matrix on each subband of the kth second node, and the channel quality indication on each subband of the kth second node and / or the bandwidth channel quality indication of the kth second node.

[0111] The second precoding matrix on each subband of the K second nodes in the present disclosure can be expressed as p k,u, k is a non-negative integer less than or equal to K. It can also be expressed as k=1,…,K, where K is the number of paired second nodes (terminals) in the first transmission mode, and is an integer greater than 1. u=1,…,U, where U is a positive integer, indicating the number of subbands or RBs of the second node (terminal).

[0112] Example 1, taking the first node as a base station and the second node as a terminal as an example. The base station includes a first model, and the base station receives the precoding matrix p on each subband of the kth terminal under SU-MIMO sent by the kth terminal. k,u (usually obtained through channel reciprocity or through the precoding matrix indication table feedback from the terminal, which will not be repeated hereafter), and the channel quality indication on each subband of the kth terminal under SU-MIMO (which can be expressed as CQI k,u , u=1,…,U, U is a positive integer representing the number of subbands or RBs of the terminal), in some embodiments, the channel quality indicator table is used to obtain the signal-to-interference-plus-noise ratio SINR SU,k,u , and SINR sU,k,u Replace the CQI k,u , I will not go into details later. k,u and SINR SU,k,u is a complex matrix of Nt*Ns. Multiply the precoding matrix of the i-th layer of the u-th subband of the k-th terminal under SU-MIMO by the u-th subband SINR of the k-th second node under SU-MIMO SU,k,u The i-th value of is used to obtain a weighted precoding matrix. Optionally, the weighted precoding matrix is ​​preprocessed and then input into the first model. The data output by the first model is processed to obtain the predicted channel matrix on each subband of the k-th terminal. Wherein, u=1,…,U, U is a positive integer, indicating the number of subbands or RBs of the second node.

[0113] Example 2, taking the first node as a base station and the second node as a terminal as an example. The base station includes a second model, and the base station receives the precoding matrix p on each subband of the kth terminal under SU-MIMO sent by the kth terminal. k,u , and each subband of the kth terminal under SU-MIMO corresponds to a wideband channel quality indicator (which can be expressed as CQI k ), in this embodiment or other embodiments, the channel quality indicator table is used to obtain the signal to interference noise ratio SINR SU,k , and SINR SU,k Replace CQI k , which will not be described in detail later. k,u is a complex matrix of Nt*Ns. Multiply the precoding matrix of the i-th layer of the u-th subband of the k-th terminal under SU-MIMO by the wideband SINRsu,k The i-th value of is used to obtain a weighted precoding matrix. Optionally, the weighted precoding matrix is ​​preprocessed and then input into the second model. The data output by the second model is processed to obtain the predicted channel matrix on each subband of the k-th terminal. u=1,…,U, where U is a positive integer and represents the number of subbands or RBs of the terminal.

[0114] In some embodiments, the channel quality indication on each subband of the k-th second node is determined based on the bandwidth channel quality indication of the k-th second node.

[0115] Example 3, taking the first node as a base station and the second node as a terminal as an example. The base station includes a third model, the base station receives the precoding matrix p on each subband of the kth terminal under SU-MIMO sent by the kth terminal k,u , and each subband of the kth terminal under SU-MIMO corresponds to a wideband channel quality indicator (CQI k ) Look up the table to get SINR SU,j . And use a model to convert the SINR SU,k Predict and generate the channel quality indicator (SINR) on each subband of the kth terminal SU,k,u , u=1,…,U, U is a positive integer, representing the number of subbands or RBs of the terminal). Among them, p k,u and SINR SU,k,u is a complex matrix of Nt*Ns. Multiply the precoding matrix of the i-th layer of the u-th subband of the k-th terminal by the u-th subband SINR of the k-th terminal SU,k,u The i-th value of is used to obtain a weighted precoding matrix. Optionally, the weighted precoding matrix is ​​preprocessed and then input into a third model. The data output by the third model is processed to obtain a predicted channel matrix on each subband of the k-th terminal.

[0116] In some embodiments, based on the second channel state information of the kth second node, determining the predicted channel matrix on each subband of the kth second node includes: measuring the detection reference signal sent by the kth second node to obtain the uplink channel information of the kth second node; based on the uplink channel information of the kth second node and the second channel state information of the kth second node, determining the predicted channel matrix on each subband of the kth second node, k is a non-negative integer less than or equal to K.

[0117] Example 4, taking the first node as a base station and the second node as a terminal as an example. The kth terminal receives the configuration information related to the SRS resource of the base station, and transmits the SRS according to the configuration information related to the SRS resource. The base station receives the SRS on the SRS resource, and measures and obtains the uplink channel information of the kth terminal (the uplink channel information of the kth terminal can be expressed as u=1,…,U, where U is a positive integer representing the number of subbands or RBs of the terminal); after a series of preprocessing is performed on the uplink channel information, the weighted precoding matrix obtained in Example 1, Example 2, or Example 3 is used as the input of the fourth model, and the data output by the fourth model is processed to obtain the predicted channel matrix on each subband of the kth terminal

[0118] In some embodiments, determining K predicted channel information of K second nodes includes: acquiring position information of the K second nodes; and determining a predicted channel matrix on each subband of the K second nodes based on the position information of the K second nodes.

[0119] In some embodiments, obtaining the location information of the K second nodes includes: obtaining the location information of the K second nodes through synaesthesia technology or artificial intelligence-based positioning technology.

[0120] Example 5, taking the first node as a base station and the second node as a terminal as an example. The base station obtains the location information of the terminal. In one example, the base station receives the location information of the terminal to obtain the location information of the terminal. In one example, the location information sent by the location manager is received to obtain the location information of the terminal. In one example, the location information of the terminal is obtained by its own single base station positioning algorithm. In one example, the location information of the terminal is obtained by the synaesthesia technology. The description of these obtaining location information will not be repeated one by one later.

[0121] The base station performs a series of preprocessing on the location information of the terminal as the input of the fifth model. The data output by the fifth model is processed to obtain the predicted channel matrix on each subband of the kth terminal. u=1, ..., U, where U is a positive integer and represents the number of subbands or RBs of the terminal. The fifth model has the ability to reconstruct channel information according to position information.

[0122] In some embodiments, determining a predicted channel matrix on each subband of the K second nodes based on the position information of the K second nodes includes:

[0123] For a k-th second node among the K second nodes, obtaining second channel state information of the k-th second node;

[0124] Determine a predicted channel matrix on each subband of the kth second node based on the position information of the K second nodes and the second channel state information of the kth second node;

[0125] The second channel state information is the channel state information under the second transmission mode, and the second channel state information of the kth second node includes the second precoding matrix on each subband of the kth second node, and the channel quality indication on each subband of the kth second node and / or the bandwidth channel quality indication of the kth second node, where k is a non-negative integer less than or equal to K.

[0126] Example 6, taking the first node as a base station and the second node as a terminal as an example. The base station obtains the location information of the terminal. After the base station performs a series of preprocessing on the location information of the terminal, it combines the weighted precoding matrix obtained in the above example 1, example 2, or example 3 as the input of the sixth model. The data output by the sixth model is processed to obtain the predicted channel matrix on each subband of the kth terminal. u=1,…,U, where U is a positive integer and represents the number of subbands or RBs of the terminal.

[0127] In some embodiments, determining a predicted channel matrix on each subband of the kth second node based on the position information of the K second nodes and the second channel state information of the kth second node includes:

[0128] Measuring a sounding reference signal sent by the k-th second node to obtain uplink channel information of the k-th second node;

[0129] Based on the position information of K second nodes, the uplink channel information of the kth second node and the second channel state information of the kth second node, the predicted channel matrix on each subband of the kth second node is determined, where k is a non-negative integer less than or equal to K.

[0130] Example 7, taking the first node as a base station and the second node as a terminal as an example. The base station obtains the location information of the terminal. After the base station performs a series of preprocessing on the location information of the terminal, it combines the weighted precoding matrix obtained in the above example 1, example 2, or example 3, and the uplink channel information of the kth terminal obtained in the above example 4 as the input of the seventh model. The data output by the seventh model is processed to obtain the predicted channel matrix on each subband of the kth terminal. u=1,…,U, where U is a positive integer and represents the number of subbands or RBs of the terminal.

[0131] In some embodiments, determining the predicted channel matrix on each subband of the K second nodes based on the position information of the K second nodes includes:

[0132] Measuring a sounding reference signal sent by the k-th second node to obtain uplink channel information of the k-th second node;

[0133] Based on the position information of K second nodes and the uplink channel information of the kth second node, a predicted channel matrix on each subband of the kth second node is determined, where k is a non-negative integer less than or equal to K.

[0134] Example 8, taking the first node as a base station and the second node as a terminal as an example. The base station obtains the location information of the terminal. After the base station performs a series of preprocessing on the location information of the terminal, it combines the uplink channel information obtained in the above example 4 as the input of the eighth model. The data output by the eighth model is processed to obtain the predicted channel matrix on each subband of the kth terminal u=1,…,U, where U is a positive integer and represents the number of subbands or RBs of the terminal.

[0135] S102: Determine K first channel state information of K second nodes based on K predicted channel information.

[0136] The first channel state information is channel state information under a first transmission mode, the first channel state information includes at least one first precoding matrix and / or at least one modulation and coding method, and K is a positive integer greater than 1.

[0137] The first precoding matrix on each subband of the K second nodes in the present disclosure can be expressed as w k,u k is a non-negative integer less than or equal to K. It can also be expressed as k=1,…,K, where K is the number of paired second nodes (terminals) in a transmission mode and is an integer greater than 1. u=1,…,U, where U is a positive integer, indicating the number of subbands or RBs of the second node (terminal).

[0138] In some embodiments, based on K predicted channel information, K first channel state information of K second nodes is determined, including: based on the predicted channel matrix on each subband of the K second nodes, determining the first precoding matrix on each subband of the K second nodes.

[0139] Exemplarily, the predicted channel matrix on each subband of the kth second node and the predicted channel matrix on each subband of the second node paired under MU are input into the artificial intelligence model to obtain the first precoding matrix of the kth second node and the second node paired under MU.

[0140] Example 9, taking the first node as a base station and the second node as a terminal as an example. The base station obtains the predicted channel matrix on each subband of K terminals according to any method in the above examples or embodiments. The predicted channel matrix As the input of the ninth model, the data output by the ninth model is processed by some subsequent steps to obtain the precoding matrix w when K terminals act as MUs k,u .

[0141] In some embodiments, based on the predicted channel matrix on each subband of the K second nodes, a first precoding matrix on each subband of the K second nodes may be determined by a zero flag (ZF) algorithm.

[0142] For example, the precoding method includes a ZF algorithm, and the first precoding matrix on each subband of the second node is a precoding matrix under a zero-breaking algorithm.

[0143] Example 10, taking the first node as a base station and the second node as a terminal as an example. The base station obtains the predicted channel matrix on each subband of K terminals according to any method in the above examples or embodiments. The predicted channel matrix As the input of the tenth model, the tenth model outputs a diagonal loading coefficient. Of course, in other embodiments, the diagonal loading coefficient α can also be obtained by outputting other contents to the model, such as neighboring cell interference and other information. And the diagonal loading coefficient is brought into the calculation formula corresponding to the first precoding matrix under the following zero-breaking algorithm to obtain the precoding matrix W when K terminals are MU. u k=1,…,K, K is the number of MU-MIMO paired terminals, which is an integer greater than 1. u=1,…,U, U is a positive integer, indicating the number of subbands or RBs of the terminal.

[0144] In some embodiments, the first precoding matrix on each subband of the K second nodes under the zero-breaking algorithm is determined by the following formula:

[0145]

[0146] in, is the predicted channel matrix on the u-th subband of the i-th node among the K second nodes, i is a positive integer less than or equal to K; W u is the first precoding matrix on the u-th subband of the K second nodes; w j,u is the first precoding matrix on the u-th subband of the j-th node among the K second nodes, j is a positive integer less than or equal to K; α is the diagonal loading coefficient, I is the unit matrix, and u is a positive integer.

[0147] It is understandable that α is the diagonal loading coefficient. If this coefficient is too high, the zero-breaking algorithm will be too poor, while if it is too small, the matrix Pathological conditions occur, and the accuracy of its inversion decreases. The diagonal loading coefficient obtained by AI can improve the performance of the zero-breaking algorithm. It should be noted that in the zero-breaking algorithm, each second node (terminal) is treated as a layer. If a user has multiple layers, they will also be broken into zeros, resulting in a decrease in performance. One solution is block diagonalization.

[0148] In some embodiments, based on the predicted channel matrix on each subband of the K second nodes, a first precoding matrix on each subband of the K second nodes is determined by a block diagonalization algorithm (BD).

[0149] For example, the precoding method includes a BD algorithm, and the first precoding matrix on each subband of the K second nodes is a precoding matrix under a precoding block diagonalization algorithm.

[0150] Example 11, taking the first node as a base station and the second node as a terminal as an example. The base station obtains the predicted channel matrix on each subband of K terminals according to any method in the above example or embodiment. The first precoding matrix under the BD algorithm can be obtained by the following steps. k = 1, ..., K, K is the number of MU-MIMO paired terminals, which is an integer greater than 1. u = 1, ..., U, U is a positive integer, indicating the number of subbands or RBs of the terminal.

[0151] Calculate the first precoding matrix under the BD algorithm of the terminal, that is:

[0152] Calculate the interfering user channel of the i-th terminal

[0153] Get H i,u The null space of: [U i,u ,D i,u ,V i,u ]=svd(H i,u );

[0154] Select at least one column of the null space as the first precoding matrix for the i-th terminal: w i,u =V i,u [:,1:,N i,s ];

[0155] in N i,s is the channel rank of the i-th terminal.

[0156] In some embodiments, the null space of each terminal may be selected by artificial intelligence.

[0157] In some embodiments, determining K first channel state information of K second nodes based on K predicted channel information further includes:

[0158] For a kth second node among the K second nodes, obtaining a second SINR on each subband of the kth second node;

[0159] Determine a first SINR on each subband of the kth second node based on a second SINR on each subband of the kth second node, a predicted channel matrix on each subband of the K second nodes, and a first precoding matrix on each subband of the K second nodes;

[0160] Based on the first SINR on each subband of the kth second node, a modulation and coding mode of the kth second node is determined, where k is a non-negative integer less than or equal to K.

[0161] In some embodiments, the first signal to interference noise ratio on each subband of the kth second node is determined by the following formula:

[0162]

[0163] Among them, SINR MU,k,u is the first SINR of the u-th subband of the k-th second node, SINR SU,k,u is the second SINR of the kth second node on the uth subband; β k,k,u is determined by predicting through an artificial intelligence system and / or based on a predicted channel matrix on the u-th subband of the k-th second node and / or a first precoding matrix on the u-th subband of the k-th second node; β k,j,u It is predicted by an artificial intelligence system and / or determined based on a predicted channel matrix on the u-th subband of the k-th second node and / or a first precoding matrix on the u-th subband of the j-th second node among the K second nodes, where u is a positive integer and j is a non-negative integer less than or equal to K.

[0164] In some embodiments, β k,k,u can be predicted by AI systems. k,k,u It can also be in, is the predicted channel matrix on the u-th subband of the k-th second node, w k,u is the first precoding matrix on the u-th subband of the k-th second node. k,j,u Can be is the predicted channel matrix on the u-th subband of the k-th second node, w j,u is the first precoding matrix on the u-th subband of the second node.

[0165] Example 12, taking the first node as a base station and the second node as a terminal as an example. The base station obtains the predicted channel matrices of multiple terminals according to a method in the above example or embodiment. And according to the method of Example 10 or Example 11, the first precoding matrix w under MU of multiple terminals is obtained. k,u , then it can be based on w k,u Calculate the SINR of each terminal under MU. k = 1, ..., K, K is the number of terminals paired with MU-MIMO, which is an integer greater than 1. u = 1, ..., U, U is a positive integer, indicating the number of subbands or RBs of the terminal.

[0166] In some embodiments, the SINR of each second node under MU is re-looked up in a table to obtain the MCS when each second node acts as MU.

[0167] S103: Perform data transmission based on K pieces of first channel state information.

[0168] Exemplarily, data transmission is performed based on the MCS obtained in Example 12 and the first precoding matrix under MU obtained in Example 10 or Example 11.

[0169] In some embodiments, K first channel state information are sent, wherein the first channel state information may include an identifier of the second node, so that the second node receives matching first channel state information and performs data transmission based on the first channel state information.

[0170] The present disclosure provides a data transmission method that can be applied to a third node. Figure 3 As shown, the method comprises the following steps:

[0171] S201. Receive data sent by a first node based on first channel state information of a third node.

[0172] The first channel state information is determined based on K predicted channel information of K second nodes. The first channel state information is channel state information under a first transmission mode, the first channel state information includes at least one first precoding matrix and / or at least one modulation and coding method, the K second nodes include a third node, and K is a positive integer greater than 1.

[0173] In some embodiments, the first channel state information of the third node sent by the first node is received, so that the first node performs intelligent processing based on the first channel state information to further improve the performance of the current multi-user scheduling.

[0174] In some embodiments, the K predicted channel information includes predicted channel matrices on respective subbands of the K second nodes.

[0175] In some embodiments, the predicted channel matrix on each subband of the kth second node among the K second nodes is determined based on the second channel state information of the kth second node;

[0176] The second channel state information is the channel state information under the second transmission mode, and the second channel state information of the kth second node includes the second precoding matrix on each subband of the kth second node, and the channel quality indication on each subband of the kth second node and / or the bandwidth channel quality indication of the kth second node, where k is a non-negative integer less than or equal to K.

[0177] In some embodiments, second channel state information of a third node is sent.

[0178] In some embodiments, the predicted channel matrix on each subband of the kth second node among the K second nodes is determined based on the uplink channel information of the kth second node and the second channel state information of the kth second node;

[0179] The uplink channel information of the k-th second node is obtained based on measuring a sounding reference signal sent by the k-th second node.

[0180] In some embodiments, the predicted channel matrix on each subband of the kth second node among the K second nodes is determined based on the position information of the K second nodes, where k is a non-negative integer less than or equal to K.

[0181] In some embodiments, the location information of the K second nodes is obtained through synaesthesia technology or artificial intelligence-based positioning technology.

[0182] In some embodiments, the predicted channel matrix on each subband of the kth second node among the K second nodes is determined based on the position information of the K second nodes and the second channel state information of the kth second node;

[0183] The second channel state information is the channel state information under the second transmission mode, and the second channel state information of the kth second node includes the second precoding matrix on each subband of the kth second node, and the channel quality indication on each subband of the kth second node and / or the bandwidth channel quality indication of the kth second node.

[0184] In some embodiments, the predicted channel matrix on each subband of the kth second node among the K second nodes is determined based on the position information of the K second nodes, the uplink channel information of the kth second node, and the second channel state information of the kth second node;

[0185] The uplink channel information of the k-th second node is obtained based on measuring a sounding reference signal sent by the k-th second node.

[0186] In some embodiments, the kth second node receives the configuration information related to the sounding reference signal resource sent by the first node, and transmits the sounding reference signal according to the configuration information related to the sounding reference signal resource. The first node receives the sounding reference signal on the sounding reference signal resource, and measures and obtains the uplink channel information of the kth second node.

[0187] In some embodiments, the predicted channel matrix on each subband of the kth second node among the K second nodes is determined based on the position information of the K second nodes and the uplink channel information of the kth second node;

[0188] The uplink channel information of the k-th second node is obtained based on measuring a sounding reference signal sent by the k-th second node.

[0189] In some embodiments, the channel quality indication on each subband of the k-th second node is determined based on the bandwidth channel quality indication of the k-th second node.

[0190] In some embodiments, the first precoding matrix on each subband of the third node is determined based on the predicted channel matrix on each subband of the K second nodes.

[0191] In some embodiments, the first precoding matrix on each subband of the third node is based on the predicted channel matrix on each subband of the K second nodes and is determined by a zero-breaking algorithm.

[0192] For example, the precoding method includes a zero-breaking algorithm, and the first precoding matrix on each subband of the third node is a precoding matrix under the zero-breaking algorithm.

[0193] In some embodiments, the first precoding matrix on each subband of the third node is based on the predicted channel matrix on each subband of the K second nodes and is determined by a block diagonalization algorithm.

[0194] For example, the precoding method includes a precoding block diagonalization algorithm, and the first precoding matrix on each subband of the third node is a precoding matrix under the precoding block diagonalization algorithm.

[0195] In some embodiments, the modulation and coding scheme of the third node is determined based on the first SINR on each subband of the third node. The first SINR on each subband of the third node is determined based on the second SINR on each subband of the third node, the predicted channel matrix on each subband of the K second nodes, and the first precoding matrix on each subband of the K second nodes.

[0196] For a more detailed description of S201, a more detailed description of each technical feature therein, a description of beneficial effects, etc., please refer to the description in the above embodiments or examples, and will not be repeated here.

[0197] The above mainly introduces the scheme of the embodiment of the present disclosure from the perspective of the method. A data transmission device is also shown below, which is used to execute the data transmission method in any of the above embodiments and possible implementations thereof. It can be understood that in order to implement the data transmission method, the data transmission device includes a hardware structure and / or software module corresponding to each function; those skilled in the art should easily realize that, in combination with the algorithm steps of each example described in the embodiment of the present disclosure, the present disclosure can be implemented in the form of hardware or a combination of hardware and computer software. Whether a function is executed in the form of hardware or computer software driving hardware depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present disclosure.

[0198] The embodiments of the present disclosure may divide the data transmission device into functional modules according to the above method embodiments. For example, each functional module may be divided corresponding to each function, or two or more functions may be integrated into one functional module. The above integrated modules may be implemented in the form of hardware or software. It should be noted that the division of modules in the embodiments of the present disclosure is schematic and is only a logical function division. There may be other division methods in actual implementation. The following is an example of dividing each functional module corresponding to each function.

[0199] Figure 4 300 is a schematic diagram of a data transmission device provided by an embodiment of the present disclosure, and is applied to a first node. The data transmission device 300 includes a processing module 301 , a communication module 302 and a measurement module 303 .

[0200] Wherein, the processing module 301 is used to determine K predicted channel information of K second nodes;

[0201] The processing module 301 is further used to determine K first channel state information of K second nodes based on the K predicted channel information;

[0202] A communication module 302, configured to perform data transmission based on K first channel state information;

[0203] The first channel state information is channel state information in a first transmission mode. The first channel state information includes at least one first precoding matrix and / or at least one modulation and coding scheme, and K is a positive integer greater than 1.

[0204] In some embodiments, the K predicted channel information includes predicted channel matrices on respective subbands of the K second nodes.

[0205] In some embodiments, the processing module 301 is specifically configured to:

[0206] For a k-th second node among the K second nodes, obtaining second channel state information of the k-th second node;

[0207] Determine, based on the second channel state information of the k-th second node, a predicted channel matrix on each subband of the k-th second node, where k is a non-negative integer less than or equal to K;

[0208] The second channel state information is the channel state information under the second transmission mode, and the second channel state information of the kth second node includes the second precoding matrix on each subband of the kth second node, and the channel quality indication on each subband of the kth second node and / or the bandwidth channel quality indication of the kth second node.

[0209] In some embodiments, the measurement module 303 is used to measure the detection reference signal sent by the kth second node to obtain the uplink channel information of the kth second node; the processing module 301 is used to determine the predicted channel matrix on each subband of the kth second node based on the uplink channel information of the kth second node and the second channel state information of the kth second node, where k is a non-negative integer less than or equal to K.

[0210] In some embodiments, the communication module 302 is used to obtain the position information of the K second nodes; the processing module 301 is used to determine the predicted channel matrix on each subband of the K second nodes based on the position information of the K second nodes.

[0211] In some embodiments, the communication module 302 is used to obtain the location information of K second nodes through synaesthesia technology or artificial intelligence-based positioning technology.

[0212] In some embodiments, the communication module 302 is configured to obtain, for a k-th second node among the K second nodes, second channel state information of the k-th second node;

[0213] The processing module 301 is used to determine the predicted channel matrix on each subband of the k-th second node based on the position information of the K second nodes and the second channel state information of the k-th second node;

[0214] The second channel state information is the channel state information under the second transmission mode, and the second channel state information of the kth second node includes the second precoding matrix on each subband of the kth second node, and the channel quality indication on each subband of the kth second node and / or the bandwidth channel quality indication of the kth second node, where k is a non-negative integer less than or equal to K.

[0215] In some embodiments, the measurement module 303 is configured to measure the sounding reference signal sent by the kth second node to obtain uplink channel information of the kth second node;

[0216] The processing module 301 is used to determine the predicted channel matrix on each subband of the kth second node based on the position information of K second nodes, the uplink channel information of the kth second node and the second channel state information of the kth second node.

[0217] In some embodiments, the measurement module 303 is used to measure the detection reference signal sent by the kth second node to obtain the uplink channel information of the kth second node; the processing module 301 is used to determine the predicted channel matrix on each subband of the kth second node based on the position information of K second nodes and the uplink channel information of the kth second node, where k is a non-negative integer less than or equal to K.

[0218] In some embodiments, the channel quality indication on each subband of the k-th second node is determined based on the bandwidth channel quality indication of the k-th second node.

[0219] In some embodiments, the processing module 301 is configured to determine a first precoding matrix on each subband of the K second nodes based on a predicted channel matrix on each subband of the K second nodes.

[0220] In some embodiments, the processing module 301 is configured to determine a first precoding matrix on each subband of the K second nodes by a zero-breaking algorithm based on a predicted channel matrix on each subband of the K second nodes.

[0221] In some embodiments, the first precoding matrix on each subband of the K second nodes is determined by the following formula:

[0222]

[0223] in, is the predicted channel matrix on the u-th subband of the i-th node among the K second nodes, i is a positive integer less than or equal to K; W u is the first precoding matrix on the u-th subband of the K second nodes; w j,u is the first precoding matrix on the u-th subband of the j-th node among the K second nodes, j is a positive integer less than or equal to K; α is the diagonal loading coefficient, I is the unit matrix, and u is a positive integer.

[0224] In some embodiments, the processing module 301 is configured to determine a first precoding matrix on each subband of the K second nodes by a block diagonalization algorithm based on a predicted channel matrix on each subband of the K second nodes.

[0225] In some embodiments, the communication module 302 is configured to obtain, for a k-th second node among the K second nodes, a second signal to interference and noise ratio on each subband of the k-th second node;

[0226] The processing module 301 is used to determine the first signal to interference and noise ratio on each subband of the kth second node based on the second signal to interference and noise ratio on each subband of the kth second node, the predicted channel matrix on each subband of the K second nodes, and the first precoding matrix on each subband of the K second nodes;

[0227] The processing module 301 is further configured to determine a modulation and coding scheme of the kth second node based on a first signal to interference noise ratio on each subband of the kth second node, where k is a non-negative integer less than or equal to K.

[0228] In some embodiments, the second signal to interference noise ratio on each subband of the kth second node is determined by the following formula:

[0229]

[0230] Among them, SINR MU,k,u is the first signal to interference noise ratio of the u-th subband of the k-th second node, SINR SU,k,u is the second signal to interference noise ratio on the u-th subband of the k-th second node; β k,k,u is determined by predicting through an artificial intelligence system and / or based on a predicted channel matrix on the u-th subband of the k-th second node and / or a first precoding matrix on the u-th subband of the k-th second node; β k,j,u It is predicted by an artificial intelligence system and / or determined based on a predicted channel matrix on the u-th subband of the k-th second node and / or a first precoding matrix on the u-th subband of the j-th second node among the K second nodes, where u is a positive integer and j is a non-negative integer less than or equal to K.

[0231] For a more detailed description of the processing module 301, the communication module 302 and the measurement module 303, as well as a more detailed description of each technical feature therein, and a description of the beneficial effects, etc., please refer to the corresponding method embodiment part above, which will not be repeated here.

[0232] Figure 5 4 is a schematic diagram of a data transmission device provided by an embodiment of the present disclosure, and is applied to a third node. The data transmission device 400 includes: a communication module 401 and a processing module 402.

[0233] Wherein, the communication module 401 is used to receive data sent by the first node based on the first channel state information of the third node;

[0234] The first channel state information is determined based on K predicted channel information of K second nodes; the first channel state information is the channel state information under the first transmission mode, the first channel state information includes at least one first precoding matrix and / or at least one modulation and coding method, the K second nodes include a third node, and K is a positive integer greater than 1.

[0235] In some embodiments, the processing module 402 is configured to determine second channel state information of a third node.

[0236] The communication module 401 is configured to send second channel state information of a third node.

[0237] For a more detailed description of the communication module 401 and the processing module 402, as well as a more detailed description of each technical feature therein and a description of the beneficial effects, etc., please refer to the corresponding method embodiment part above, which will not be repeated here.

[0238] It should be noted that Figure 4 and / or Figure 5 The modules in the communication module may also be referred to as units. For example, the communication module may be referred to as a communication unit. Figure 4 and / or Figure 5 In the embodiment shown in the figure, the names of the modules may not be the names shown in the figure. For example, the communication module may also be called a sending module or a receiving module.

[0239] Figure 4 and / or Figure 5 If the various units or modules in the embodiment are implemented in the form of software function modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the embodiment of the present disclosure is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) or a processor (processor) to perform all or part of the steps of the various embodiments of the present disclosure. The storage medium for storing computer software products includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk and other media that can store program codes.

[0240] In the case of implementing the functions of the above-mentioned integrated modules in the form of hardware, the embodiment of the present disclosure also provides a possible structure of a communication device, which is used to execute the data transmission method provided by the embodiment of the present disclosure. Figure 6As shown, the communication device 500 includes: a communication interface 503, a processor 502 and a bus 504. Optionally, the communication device may further include a memory 501.

[0241] The processor 502 may be a processor that implements or executes various exemplary logic blocks, modules, and circuits described in conjunction with the embodiments of the present disclosure. The processor 502 may be a central processing unit, a general-purpose processor, a digital signal processor, an application-specific integrated circuit, a field programmable gate array, or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. It may implement or execute various exemplary logic blocks, modules, and circuits described in conjunction with the embodiments of the present disclosure. The processor 502 may also be a combination that implements computing functions, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, and the like.

[0242] The communication interface 503 is used to connect with other devices via a communication network, such as Ethernet, wireless access network, wireless local area network (WLAN), etc.

[0243] The memory 501 may be a read-only memory (ROM) or other types of static storage devices that can store static information and instructions, a random access memory (RAM) or other types of dynamic storage devices that can store information and instructions, or an electrically erasable programmable read-only memory (EEPROM), a disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store desired program codes in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto.

[0244] As a possible implementation, the memory 501 may exist independently of the processor 502, and the memory 501 may be connected to the processor 502 via a bus 504 to store instructions or program codes. When the processor 502 calls and executes the instructions or program codes stored in the memory 501, the data transmission method provided in the embodiment of the present disclosure can be implemented.

[0245] In another possible implementation, the memory 501 may also be integrated with the processor 502 .

[0246] The bus 504 may be an extended industry standard architecture (EISA) bus, etc. The bus 504 may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 6 Only one thick line is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0247] Some embodiments of the present disclosure provide a computer-readable storage medium (e.g., a non-transitory computer-readable storage medium), which stores computer program instructions. When the computer program instructions are executed on a computer, the computer executes the data transmission method described in any of the above embodiments.

[0248] In an exemplary implementation, the computer may be the above-mentioned data transmission device, and the present disclosure does not limit the specific form of the computer.

[0249] In some embodiments, the above-mentioned computer-readable storage medium may include, but is not limited to: magnetic storage devices (e.g., hard disks, floppy disks, or magnetic tapes, etc.), optical disks (e.g., compact disks (CDs), digital versatile disks (DVDs), etc.), smart cards, and flash memory devices (e.g., erasable programmable read-only memory (EPROM), cards, sticks, or key drives, etc.). The various computer-readable storage media described in the present disclosure may represent one or more devices and / or other machine-readable storage media for storing information. The term "machine-readable storage medium" may include, but is not limited to, wireless channels and various other media capable of storing, containing, and / or carrying instructions and / or data.

[0250] An embodiment of the present disclosure provides a computer program product including instructions. When the computer program product is run on a computer, the computer is enabled to execute the data transmission method described in any one of the above embodiments.

[0251] The above is only a specific implementation of the present disclosure, but the protection scope of the present disclosure is not limited thereto. Any changes or substitutions within the technical scope disclosed in the present disclosure should be included in the protection scope of the present disclosure. Therefore, the protection scope of the present disclosure should be based on the protection scope of the claims.

Claims

1. A data transmission method, characterized in that: Applied to the first node, the method comprises: Determine K predicted channel information of K second nodes; Determine K first channel state information of the K second nodes based on the K predicted channel information; Performing data transmission based on the K first channel state information; The first channel state information is channel state information under a first transmission mode, the first channel state information includes at least one first precoding matrix and / or at least one modulation and coding method, and K is a positive integer greater than 1.

2. The method according to claim 1, characterized in that The K predicted channel information includes predicted channel matrices on each subband of the K second nodes.

3. The method according to claim 2, characterized in that The determining K predicted channel information of K second nodes includes: For a k-th second node among the K second nodes, acquiring second channel state information of the k-th second node; Determine, based on the second channel state information of the k-th second node, a predicted channel matrix on each subband of the k-th second node, where k is a non-negative integer less than or equal to K; The second channel state information is the channel state information under the second transmission mode, and the second channel state information of the kth second node includes the second precoding matrix on each subband of the kth second node, and the channel quality indication on each subband of the kth second node and / or the bandwidth channel quality indication of the kth second node.

4. The method according to claim 3, characterized in that The determining, based on the second channel state information of the k-th second node, a predicted channel matrix on each subband of the k-th second node comprises: Measuring a sounding reference signal sent by the k-th second node to obtain uplink channel information of the k-th second node; Based on the uplink channel information of the kth second node and the second channel state information of the kth second node, a predicted channel matrix on each subband of the kth second node is determined, where k is a non-negative integer less than or equal to K.

5. The method according to claim 2, characterized in that: The determining K predicted channel information of K second nodes includes: Obtaining location information of the K second nodes; Based on the position information of the K second nodes, a predicted channel matrix on each subband of the K second nodes is determined.

6. The method according to claim 5, characterized in that The obtaining the location information of the K second nodes includes: The location information of the K second nodes is obtained through synaesthesia technology or artificial intelligence-based positioning technology.

7. The method according to claim 5, characterized in that The step of determining the predicted channel matrix on each subband of the K second nodes based on the position information of the K second nodes includes: For a k-th second node among the K second nodes, acquiring second channel state information of the k-th second node; Determine a predicted channel matrix on each subband of the kth second node based on the position information of the K second nodes and the second channel state information of the kth second node; The second channel state information is the channel state information under the second transmission mode, and the second channel state information of the kth second node includes the second precoding matrix on each subband of the kth second node, and the channel quality indication on each subband of the kth second node and / or the bandwidth channel quality indication of the kth second node, where k is a non-negative integer less than or equal to K.

8. The method according to claim 7, characterized in that The determining, based on the position information of the K second nodes and the second channel state information of the k-th second node, a predicted channel matrix on each subband of the k-th second node comprises: Measuring a sounding reference signal sent by the k-th second node to obtain uplink channel information of the k-th second node; Based on the position information of the K second nodes, the uplink channel information of the kth second node and the second channel state information of the kth second node, a predicted channel matrix on each subband of the kth second node is determined.

9. The method according to claim 5, characterized in that The step of determining the predicted channel matrix on each subband of the K second nodes based on the position information of the K second nodes includes: Measuring a sounding reference signal sent by the k-th second node to obtain uplink channel information of the k-th second node; Based on the position information of the K second nodes and the uplink channel information of the kth second node, a predicted channel matrix on each subband of the kth second node is determined, where k is a non-negative integer less than or equal to K.

10. The method according to claim 3 or 7, characterized in that: The channel quality indication on each subband of the k-th second node is determined based on the bandwidth channel quality indication of the k-th second node.

11. The method according to claim 2, characterized in that The determining, based on the K predicted channel information, K first channel state information of the K second nodes includes: Based on the predicted channel matrix on each subband of the K second nodes, a first precoding matrix on each subband of the K second nodes is determined.

12. The method according to claim 11, characterized in that The determining, based on the predicted channel matrix on each subband of the K second nodes, a first precoding matrix on each subband of the K second nodes comprises: Based on the predicted channel matrix on each subband of the K second nodes, a first precoding matrix on each subband of the K second nodes is determined by a zero-breaking algorithm.

13. The method according to claim 12, characterized in that The first precoding matrix on each subband in the K second nodes is determined by the following formula: in, is the predicted channel matrix on the u-th subband of the i-th node among the K second nodes, i is a positive integer less than or equal to K; W u is the first precoding matrix on the u-th subband of the K second nodes; w j,u is the first precoding matrix on the u-th subband of the j-th node among the K second nodes, j is a positive integer less than or equal to K; α is the diagonal loading coefficient, I is the unit matrix, and u is a positive integer.

14. The method according to claim 11, characterized in that The determining, based on the predicted channel matrix on each subband of the K second nodes, a first precoding matrix on each subband of the K second nodes comprises: Based on the predicted channel matrix on each subband of the K second nodes, a first precoding matrix on each subband of the K second nodes is determined by a block diagonalization algorithm.

15. The method according to claim 11, characterized in that The determining, based on the K predicted channel information, K first channel state information of the K second nodes further includes: For a kth second node among the K second nodes, obtaining a second signal to interference noise ratio on each subband of the kth second node; Determine a first signal to interference and noise ratio on each subband of the kth second node based on a second signal to interference and noise ratio on each subband of the kth second node, a predicted channel matrix on each subband of the K second nodes, and a first precoding matrix on each subband of the K second nodes; Based on the first signal to interference noise ratio on each subband of the kth second node, a modulation and coding mode of the kth second node is determined, where k is a non-negative integer less than or equal to K.

16. The method according to claim 15, characterized in that The first signal to interference noise ratio on each subband of the k-th second node is determined by the following formula: Among them, SINR MU,k,u is the first signal to interference noise ratio of the u-th subband of the k-th second node, SINR SU,k,u is the second signal to interference noise ratio on the u-th subband of the k-th second node; β k,k,u is predicted by an artificial intelligence system and / or determined based on a predicted channel matrix on the u-th subband of the k-th second node and / or a first precoding matrix on the u-th subband of the k-th second node; β k,j,u It is predicted by an artificial intelligence system and / or determined based on a predicted channel matrix on the u-th subband of the k-th second node and / or a first precoding matrix on the u-th subband of the j-th second node among the K second nodes, where u is a positive integer and j is a non-negative integer less than or equal to K.

17. A data transmission method, characterized in that: Applied to the third node, the method includes: receiving data sent by the first node based on the first channel state information of the third node; Among them, the first channel state information is determined based on K predicted channel information of K second nodes; the first channel state information is the channel state information under the first transmission mode, the first channel state information includes at least one first precoding matrix and / or at least one modulation and coding method, the K second nodes include the third node, and K is a positive integer greater than 1.

18. The method according to claim 17, characterized in that The K predicted channel information includes predicted channel matrices on each subband of the K second nodes.

19. The method according to claim 18, characterized in that A predicted channel matrix on each subband of a k-th second node among the K second nodes is determined based on the second channel state information of the k-th second node; The second channel state information is the channel state information under the second transmission mode, and the second channel state information of the kth second node includes the second precoding matrix on each subband of the kth second node, and the channel quality indication on each subband of the kth second node and / or the bandwidth channel quality indication of the kth second node, where k is a non-negative integer less than or equal to K.

20. The method according to claim 19, characterized in that The method further comprises: Sending second channel state information of the third node.

21. The method according to claim 19, characterized in that A predicted channel matrix on each subband of a k-th second node among the K second nodes is determined based on uplink channel information of the k-th second node and second channel state information of the k-th second node; The uplink channel information of the k-th second node is obtained based on measuring a sounding reference signal sent by the k-th second node.

22. The method according to claim 18, characterized in that The predicted channel matrix on each subband of the kth second node among the K second nodes is determined based on the position information of the K second nodes, where k is a non-negative integer less than or equal to K.

23. The method according to claim 22, characterized in that The location information of the K second nodes is obtained through synaesthesia technology or artificial intelligence-based positioning technology.

24. The method according to claim 22, characterized in that A predicted channel matrix on each subband of a k-th second node among the K second nodes is determined based on the position information of the K second nodes and the second channel state information of the k-th second node; The second channel state information is the channel state information under the second transmission mode, and the second channel state information of the kth second node includes the second precoding matrix on each subband of the kth second node, and the channel quality indication on each subband of the kth second node and / or the bandwidth channel quality indication of the kth second node.

25. The method according to claim 24, characterized in that The predicted channel matrix on each subband of the k-th second node among the K second nodes is determined based on the position information of the K second nodes, the uplink channel information of the k-th second node and the second channel state information of the k-th second node; The uplink channel information of the k-th second node is obtained based on measuring a sounding reference signal sent by the k-th second node.

26. The method according to claim 22, characterized in that A predicted channel matrix on each subband of a k-th second node among the K second nodes is determined based on the position information of the K second nodes and the uplink channel information of the k-th second node; The uplink channel information of the k-th second node is obtained based on measuring a sounding reference signal sent by the k-th second node.

27. The method according to claim 19 or 24, characterized in that The channel quality indication on each subband of the k-th second node is determined based on the bandwidth channel quality indication of the k-th second node.

28. The method according to claim 18, characterized in that The first precoding matrix on each subband of the third node is determined based on the predicted channel matrix on each subband of the K second nodes.

29. The method according to claim 28, characterized in that The modulation and coding mode of the third node is determined based on a first signal to interference and noise ratio on each subband of the third node; The first signal to interference and noise ratio on each subband of the third node is determined based on the second signal to interference and noise ratio on each subband of the third node, the predicted channel matrix on each subband of the K second nodes, and the first precoding matrix on each subband of the K second nodes.

30. A communication device, characterized in that: include: Memory and processor; Memory and processor coupling; The memory is used to store instructions executable by the processor; When the processor executes the instructions, the method according to any one of claims 1 to 29 is performed.

31. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and when the computer instructions are executed on a communication device, the communication device is caused to perform the method according to any one of claims 1 to 29.

32. A computer program product, characterized in that When the computer program product is executed, the method according to any one of claims 1 to 29 is implemented.

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