Communication method and apparatus

Abstract

Provided in the embodiments of the present application are a communication method and apparatus. The method comprises: a terminal device determining M first matrices on the basis of a received reference signal, wherein the M first matrices are used for determining a precoding matrix; and the terminal device sending information of M second matrices, wherein the M first matrices correspond to the M second matrices on a one-to-one basis, an ith first matrix comprises a second matrix and N elements, and the priorities of the N elements are not higher than the priorities of elements in the second matrix, with N being an integer greater than or equal to 0, and i iterating over positive integers from 1 to M. Discarding some of the elements from some or all of M first matrices before sending them to a network device can reduce resource overheads. When the elements are discarded, according to the priorities of the elements, elements with low priorities are first discarded, such that there is a small impact on the precision of the network device reconstructing a precoding matrix on the basis of M second matrices, and the network device can still determine the precoding matrix in a relatively accurate manner.

Description

A communication method and apparatus

[0001] Cross-references to related applications

[0002] This application claims priority to Chinese Patent Application No. 202510202391.3, filed on February 22, 2025, entitled "A Communication Method and Apparatus", the entire contents of which are incorporated herein by reference. Technical Field

[0003] This application relates to the field of communication technology, and in particular to a communication method and apparatus. Background Technology

[0004] Communication systems can increase system capacity and improve throughput through multiple-input multiple-output (MIMO) technology. In communication systems with multiple antennas, signals from multiple transmitting antennas of the transmitting device are superimposed on any one receiving antenna of the receiving device after transmission through the channel. Therefore, the method of signal transmission by the transmitting device affects system performance, and the process of the receiving device recovering the transmitted signal is also relatively complex. Based on this, precoding technology has emerged. Precoding can reduce system overhead and improve the system capacity of MIMO; on the other hand, it can reduce the complexity of the receiving device in eliminating inter-channel interference. For example, a network device sends a reference signal to a terminal device, the terminal device determines a precoding matrix based on the reference signal, and feeds back the determined precoding matrix to the network device. In this way, the network device can send downlink data to the terminal device based on the precoding matrix.

[0005] How to reduce the resource overhead of the feedback precoding matrix is ​​an urgent problem to be solved. Summary of the Invention

[0006] This application provides a communication method and apparatus for reducing the resource overhead of the feedback precoding matrix.

[0007] Firstly, this application provides a communication method applied to a terminal device. Without loss of generality, the terminal device can be a terminal equipment, a communication module within a terminal equipment, or a processor, circuit, or chip (such as a modem chip, also known as a baseband chip, or a system-on-chip (SoC) chip or system-in-package (SIP) chip containing a modem core) responsible for communication functions within a terminal equipment. It can also be a logical node, logical module, or software capable of implementing all or part of the functions of the terminal equipment.

[0008] Taking the application of this method to a terminal device as an example: Based on the received reference signal, the terminal device determines M first matrices, where M is an integer greater than 1; the terminal device determines M second matrices, and the M first matrices and M second matrices correspond one-to-one; at least two of the M second matrices respectively include some elements of the corresponding first matrices; the priority of the elements in the i-th second matrix is ​​not lower than the priority of the elements in the i-th first matrix, i traverses integers from 1 to M, and the M second matrices are used to determine the precoding matrix.

[0009] In this method, the terminal device can determine the precoding matrix based on the reference signal and then determine M first matrices based on the precoding matrix. If the terminal device sends the M first matrices to the network device, the network device can reconstruct the precoding matrix based on the M first matrices. However, in this application, the terminal device discards some elements from some or all of the M first matrices before sending them to the network device, which can reduce resource overhead. When discarding elements, lower priority elements are discarded first, thus having little impact on the accuracy of the network device's reconstruction of the precoding matrix based on the M second matrices, and the network device can still determine the precoding matrix relatively accurately.

[0010] In one possible implementation, the priority of an element is associated with the modulus of the element; or, the priority of a row of elements is associated with the modulus of the elements in that row; or, the priority of a column of elements is associated with the modulus of the elements in that column.

[0011] In one possible implementation, the terminal device may also receive first information, which is used to indicate a first resource for transmitting M second matrices; the terminal device sends information about the M second matrices on the first resource; wherein the number of elements included in the M second matrices is less than or equal to the upper limit of the number of elements allowed to be transmitted on the first resource; or, the number of bits corresponding to the elements included in the M second matrices is less than or equal to the upper limit of the number of bits allowed to be transmitted on the first resource.

[0012] In this implementation, the terminal device feeds back M second matrices of information to the network device, and the data volume of the second matrices does not exceed the data volume that the transmission resources configured by the network device can carry.

[0013] In one possible implementation, the M first matrices include: a first eigenvector matrix, a first eigenvalue matrix, and a first reference matrix; the first eigenvalue matrix is ​​a diagonal matrix, the first eigenvector matrix and the first eigenvalue matrix are used to determine the first transformation matrix, and the first transformation matrix and the first reference matrix are used to determine the precoding matrix; the M second matrices include: a second eigenvector matrix, a second eigenvalue matrix, and a second reference matrix; wherein: (1) the first eigenvector matrix includes r rows of elements, and the second eigenvector matrix includes x1 rows of elements; the second eigenvalue matrix is ​​the same as the first eigenvalue matrix; the first reference matrix includes r rows of elements, and the second reference matrix includes x1 rows of elements; r is an integer greater than 1, and x1 is a positive integer less than r. Integer; or, (2) The first eigenvector matrix includes r columns of elements, and the second eigenvector matrix includes x2 columns of elements; the first eigenvalue matrix includes r rows and r columns of elements, and the second eigenvalue matrix includes x2 rows and x2 columns of elements; r is an integer greater than 1, and x2 is a positive integer less than r; the second reference matrix is ​​the same as the first reference matrix; or, (3) The first eigenvector matrix includes r rows and r columns of elements, and the second eigenvector matrix includes x1 rows and x2 columns of elements; the first eigenvalue matrix includes r rows and r columns of elements, and the second eigenvalue matrix includes x2 rows and x2 columns of elements; the first reference matrix includes r rows of elements, and the second reference matrix includes x1 rows of elements; r is an integer greater than 1, and x1 and x2 are both positive integers less than r.

[0014] In this implementation, in (1), the same number of row elements are discarded from the first eigenvector matrix and the first reference matrix, while the first eigenvalue matrix remains unchanged, thus obtaining M second matrices; in (2), b columns of elements are discarded from the first eigenvector matrix, and b rows and b columns of elements are discarded from the first eigenvalue matrix, where b is a positive integer less than r, while the first reference matrix remains unchanged, thus obtaining M second matrices; in (3), a rows and b columns of elements are discarded from the first eigenvector matrix, b rows and b columns of elements are discarded from the first eigenvalue matrix, and a rows of elements are discarded from the first reference matrix, where a and b are both positive integers less than r, thus obtaining M second matrices. The amount of data retained after the discarding operation does not exceed the amount of data that the transmission resources configured for the network device can carry.

[0015] In one possible implementation, the row index of the x1 row element in the second eigenvector matrix in the first eigenvector matrix is ​​the same as the row index of the x1 row element in the second reference matrix in the first reference matrix; and / or, the column index of the x2 column element in the second eigenvector matrix in the first eigenvector matrix is ​​the same as the row and column indices of the x2 row and x2 column element in the second eigenvalue matrix in the first eigenvalue matrix.

[0016] In this implementation, there is a correspondence between the rows of the eigenvector matrix and the rows of the reference matrix, and a correspondence between the columns of the eigenvector matrix and the rows and columns of the eigenvalue matrix. When retaining (or discarding) elements, the elements of the corresponding rows and columns are retained (or discarded) simultaneously, which can improve the accuracy of network devices in reconstructing the precoding matrix.

[0017] In one possible implementation, the difference between x1 and x2 is less than a set threshold, which is a positive integer, and optionally, the threshold is 1, 2 or 3.

[0018] In this implementation, the difference between x1 and x2 is less than a set threshold, which ensures that the proportions of retained (or discarded) elements in the first eigenvector matrix, the first eigenvalue matrix, and the first reference matrix are similar. This allows for a smoother adjustment of the network device's accuracy in reconstructing the precoding matrix during continuous resource adjustments, preventing abrupt changes. Furthermore, the more resources used to transmit M second matrices, the larger the number of rows and columns retained in the matrices, meaning a larger value for both x1 and x2. For example, a threshold of 1 indicates that as the resources used to transmit M second matrices increase, x1 and x2 alternately increase.

[0019] In one possible implementation, the row index of the x1 row element in the second eigenvector matrix in the first eigenvector matrix and the row index of the x1 row element in the second reference matrix in the first reference matrix are related to the modulus (or priority) of each row element in the x1 row of the second reference matrix.

[0020] In this implementation, the row elements to be retained (or discarded) in the first reference matrix and the first eigenvector matrix are determined based on the modulus (or priority) of each row element in the first reference matrix.

[0021] In one possible implementation, the column index of the x2 column element in the second eigenvector matrix in the first eigenvector matrix and the row index and column index of the x2 row and x2 column element in the second eigenvalue matrix in the first eigenvalue matrix are related to the modulus (or priority) of the element located on the diagonal in the second eigenvalue matrix.

[0022] In this implementation, based on the modulus (or priority) of the elements located on the diagonal in the first eigenvalue matrix, the row and column elements to be retained (or discarded) in the first eigenvalue matrix are determined, as are the column elements to be retained (or discarded) in the first eigenvector matrix.

[0023] In one possible implementation, the M first matrices include: a first reference matrix and a first transformation matrix; the first reference matrix includes r rows of elements, and the first transformation matrix includes r rows and r columns of elements; the M second matrices include: a second reference matrix and a second transformation matrix; the second reference matrix includes x1 rows of elements, and the second transformation matrix includes x1 rows and x1 columns of elements, where x1 is an integer greater than or equal to 1, and x1 is a positive integer less than r.

[0024] In this implementation, one or more rows of elements are discarded from the first reference matrix, and one or more rows and one or more columns of elements are discarded from the first transformation matrix, thereby obtaining M second matrices.

[0025] In one possible implementation, the row index of the x1 row element in the second reference matrix in the first reference matrix is ​​the same as the row index and column index of the x1 row and x1 column element in the second transformation matrix in the first transformation matrix.

[0026] In this implementation, there is a correspondence between the rows and columns of the transformation matrix and the rows of the reference matrix. When retaining (or discarding) an element, the elements of the corresponding row and column are retained (or discarded) simultaneously, which can improve the accuracy of network devices in reconstructing the precoding matrix.

[0027] In one possible implementation, the row index of the x1 row element in the second reference matrix in the first reference matrix and the row index and column index of the x1 row and x1 column element in the second transformation matrix in the first transformation matrix are related to the modulus (or priority) of each row element in the x1 row of the second reference matrix.

[0028] In this implementation, based on the modulus (or priority) of each row element in the first reference matrix, the row elements to be retained (or discarded) in the first reference matrix are determined, as are the row elements and column elements to be retained (or discarded) in the first transformation matrix.

[0029] In one possible implementation, the modulus of each element in the x1 row of the second reference matrix is ​​greater than or equal to the modulus of each element in the a row of the first reference matrix; the a row elements are the elements in the r rows of the first reference matrix excluding the x1 row elements of the second reference matrix; wherein the modulus of any row element is positively correlated with the priority of that row element, and a is a positive integer less than r.

[0030] In this implementation, the priority of each row element in the first reference matrix is ​​determined based on the modulus of each row element; the smaller the modulus of any row element, the lower the priority of that row element, and the easier it is to be discarded. This implementation can be applied to the cases of (1) and (3) of the M second matrices described above, and the x1 row elements retained in the first reference matrix and the first eigenvector matrix are determined based on the modulus of each row element in the first reference matrix.

[0031] In one possible implementation, the modulus of the diagonal element in the second eigenvalue matrix is ​​greater than or equal to the modulus of the diagonal element in the b-row b-column element of the first eigenvalue matrix; the b-row b-column element is the element in the r-row r-column element of the first eigenvalue matrix excluding the x2-row x2-column element of the second eigenvalue matrix; wherein the modulus of the element is positively correlated with the priority of the element, and b is a positive integer less than r.

[0032] In this implementation, the priority of elements located on the diagonal is determined based on the modulus of the elements in the first eigenvalue matrix. The smaller the modulus of an element, the lower its priority and the more likely it is to be discarded. This implementation can be applied to cases (2) and (3) of the M second matrices described above. Based on the modulus of the elements located on the diagonal in the first eigenvalue matrix, the x2 row and x2 column elements to be retained in the first eigenvalue matrix and the x2 column elements to be retained in the first eigenvector matrix are determined.

[0033] In one possible implementation, the size of the first resource is positively correlated with x1; and / or, the size of the first resource is positively correlated with x2; wherein the first resource is the resource for transmitting M second matrices.

[0034] In this implementation, the more resources available, the larger the values ​​of x1 and / or x2, meaning the more rows and / or columns are retained.

[0035] In one possible implementation, the terminal device may also send a second message indicating the row index of the x1 row element and / or the column index of the x2 column element.

[0036] In this implementation, the terminal device indicates to the network device the position (i.e., row index and / or column index) of the elements of the second matrix in the elements of the first matrix, so that the network device can determine M third matrices similar to M first matrices based on the position, thereby improving the accuracy of reconstructing the precoding matrix based on the M third matrices.

[0037] In one possible implementation, when determining the M first matrices, the terminal device can determine the M first matrices based on the compressed matrix and the received reference signal, wherein the compressed matrix is ​​determined based on singular value decomposition.

[0038] In this implementation, M first matrices are determined based on the compression matrix. If the compression matrix is ​​determined based on singular value decomposition, the modulus of the elements of the first reference matrix in the M first matrices decreases or increases sequentially. The network device can determine the row index of row x1 by knowing the value of x1, without the terminal device needing to indicate the row index of row x1 to the network device, which can reduce signaling overhead.

[0039] In one possible implementation, the terminal device may also receive third information indicating: the number of elements included in each of the M second matrices (which can also be replaced by: the number of rows and / or columns, i.e., the values ​​of x1 and / or x2), and / or the row index and / or column index (i.e., the row index of the x1 row element and / or the column index of the x2 column element) of the elements included in each of the M second matrices in the corresponding first matrix; based on the third information, the terminal device sends information about the M second matrices.

[0040] In this implementation, the network device indicates the above content to the terminal device without requiring the terminal device to determine the above content, which simplifies the complexity of the terminal device.

[0041] In one possible implementation, the third information includes: information on a first priority, which is related to the number of elements in each of the M second matrices (or alternatively: the number of rows and / or columns, i.e., the value of x1 and / or the value of x2); and / or, the first priority is related to the row index and / or column index (i.e., the row index of the x1 row element and / or the column index of the x2 column element) of the elements in the corresponding first matrix of each of the M second matrices.

[0042] In this implementation, priority information is used for indication, which can reduce the bit overhead of the indication information.

[0043] In one possible implementation, the first priority information is associated with the first resource used to transmit M second matrices.

[0044] In one possible implementation, the terminal device determines M first matrices based on the received reference signal, including: determining the M first matrices corresponding to the f-th flow based on the received reference signal; f iterating through integers from 1 to v, where v is the number of flows supported by the network device when sending downlink data, and v is an integer greater than or equal to 1; the M first matrices corresponding to the f-th flow and the M second matrices corresponding to the f-th flow are in one-to-one correspondence; the terminal device sends information about the M second matrices, including: sending information about the M second matrices corresponding to the v flows respectively.

[0045] In this implementation, the M first matrices and M second matrices corresponding to each stream are determined separately and do not affect each other.

[0046] Secondly, this application provides a communication method applied to a network device. Without loss of generality, a network device can be a network equipment, a communication module within a network equipment, a processor, circuit, or chip responsible for communication functions in a terminal device, or a logical node, logical module, or software capable of implementing all or part of the functions of a network equipment.

[0047] Taking the application of this method to a network device as an example: The network device receives information from M second matrices, where M is an integer greater than 1; based on the information from the M second matrices, M third matrices are determined; the M second matrices and the M third matrices are in one-to-one correspondence; at least two of the M second matrices respectively include partial elements of the corresponding third matrices; the priority of the element in the i-th second matrix is ​​not lower than the priority of the element in the i-th third matrix; i iterates through integers from 1 to M; the M third matrices are used to determine the precoding matrix.

[0048] In one possible implementation, the priority of an element is associated with the modulus of the element; or, the priority of a row of elements is associated with the modulus of the elements in that row; or, the priority of a column of elements is associated with the modulus of the elements in that column.

[0049] In one possible implementation, the network device may also send first information indicating a first resource for transmitting M second matrices; the network device receives information about the M second matrices on the first resource; wherein the number of elements included in the M second matrices is less than or equal to the upper limit of the number of elements allowed to be transmitted on the first resource; or, the number of bits corresponding to the elements included in the M second matrices is less than or equal to the upper limit of the number of bits allowed to be transmitted on the first resource.

[0050] In one possible implementation, the M third matrices include: a third eigenvector matrix, a third eigenvalue matrix, and a third reference matrix; the third eigenvalue matrix is ​​a diagonal matrix; the M second matrices include: a second eigenvector matrix, a second eigenvalue matrix, and a second reference matrix; wherein: (1) the third eigenvector matrix has r rows of elements, and the second eigenvector matrix has x1 rows of elements; the second eigenvalue matrix and the third eigenvalue matrix are the same; the third reference matrix has r rows of elements, and the second reference matrix has x1 rows of elements; r is an integer greater than 1, and x1 is a positive integer less than r; or, (2) the third eigenvector matrix has r columns of elements, The second eigenvector matrix includes x2 columns of elements; the third eigenvalue matrix includes r rows and r columns of elements, and the second eigenvalue matrix includes x2 rows and x2 columns of elements; r is an integer greater than 1, and x2 is a positive integer less than r; the second reference matrix and the third reference matrix are the same; or, (3), the third eigenvector matrix includes r rows and r columns of elements, and the second eigenvector matrix includes x1 rows and x2 columns of elements; the third eigenvalue matrix includes r rows and r columns of elements, and the second eigenvalue matrix includes x2 rows and x2 columns of elements; the third reference matrix includes r rows of elements, and the second reference matrix includes x1 rows of elements; r is an integer greater than 2, and x1 and x2 are both positive integers less than r.

[0051] In one possible implementation, the row index of the x1 row element in the second eigenvector matrix in the third eigenvector matrix is ​​the same as the row index of the x1 row element in the second reference matrix in the third reference matrix; and / or, the column index of the x2 column element in the second eigenvector matrix in the third eigenvector matrix is ​​the same as the row and column indices of the x2 row and x2 column element in the second eigenvalue matrix in the third eigenvalue matrix.

[0052] In one possible implementation, the difference between x1 and x2 is less than a set threshold.

[0053] In one possible implementation, the M third matrices include: a third reference matrix and a third transformation matrix; the third reference matrix has r rows of elements, and the third transformation matrix has r rows and r columns of elements; the M second matrices include: a second reference matrix and a second transformation matrix; the second reference matrix has x1 rows of elements, and the second transformation matrix has x1 rows and x1 columns of elements, where r is an integer greater than 1, and x1 is a positive integer less than r.

[0054] In one possible implementation, the row index of the x1 row element in the second reference matrix in the third reference matrix is ​​the same as the row index and column index of the x1 row and x1 column element in the second transformation matrix in the third transformation matrix.

[0055] In one possible implementation, the size of the first resource is positively correlated with x1; and / or, the size of the first resource is positively correlated with x2; wherein the first resource is the resource for transmitting M second matrices.

[0056] In one possible implementation, the network device receives second information indicating the row index of the x1 row element and / or the column index of the x2 column element; the network device determines M third matrices based on the second information and M second matrices.

[0057] In one possible implementation, the network device may also send third information indicating: the number of elements included in each of the M second matrices (which may also be replaced by: the number of rows and / or columns, i.e., the values ​​of x1 and / or x2), and / or the row index and / or column index (i.e., the row index of the x1 row element and / or the column index of the x2 column element) of the elements included in each of the M second matrices in the corresponding first matrix.

[0058] In one possible implementation, the third information includes: information on a first priority, which is related to the number of elements in each of the M second matrices (or alternatively: the number of rows and / or columns, i.e., the value of x1 and / or the value of x2); and / or, the first priority is related to the row index and / or column index (i.e., the row index of the x1 row element and / or the column index of the x2 column element) of the elements in the corresponding first matrix of each of the M second matrices.

[0059] In one possible implementation, the first priority information is associated with the first resource used to transmit M second matrices.

[0060] In one possible implementation, the network device receives information about M second matrices corresponding to v flows respectively, and determines M third matrices corresponding to the f-th flow based on the information about the M second matrices corresponding to the f-th flow.

[0061] In one possible implementation, the elements in the third matrix, excluding the elements of the corresponding second matrix, are either 0 or determined based on historical information.

[0062] The second aspect and its possible technical effects can be referred to the first aspect and its possible technical effects, and will not be elaborated here.

[0063] Thirdly, a communication device is provided. The communication device can be the terminal device described in the first aspect above, and the communication device possesses the functions of the terminal device. The communication device is, for example, a functional module within the terminal device, such as a baseband device or a chip system. Alternatively, the communication device can be the network device described in the second aspect above, and the communication device possesses the functions of the network device. The communication device is, for example, a functional module within the network device, such as a baseband device or a chip system.

[0064] In one optional implementation, the communication device includes a baseband device and a radio frequency device. In another optional implementation, the communication device includes a processing unit (sometimes also called a processing module) and a transceiver unit (sometimes also called a transceiver module). The transceiver unit is capable of transmitting and receiving functions. When the transceiver unit performs the transmitting function, it can be called a transmitting unit (sometimes also called a transmitting module), and when the transceiver unit performs the receiving function, it can be called a receiving unit (sometimes also called a receiving module). The transmitting unit and the receiving unit can be the same functional module, which is called the transceiver unit and can perform both transmitting and receiving functions; or, the transmitting unit and the receiving unit can be different functional modules, and the transceiver unit is a collective term for these functional modules.

[0065] In one possible implementation, the communication device further includes a storage unit (sometimes also called a storage module), and the processing unit is configured to couple with the storage unit and execute programs or instructions in the storage unit to enable the communication device to perform the functions of the terminal device described in the first aspect or the network device described in the second aspect.

[0066] Fourthly, a communication device is provided, including an interface circuit and a processor, and optionally, a memory. The memory stores a computer program. The processor is coupled to the memory and the interface circuit. When the processor reads the computer program or instructions, it causes the communication device to execute any of the methods executed by the terminal device in the first aspect, or any of the methods executed by the network device in the second aspect. For example, the interface circuit is used to receive signals from other communication devices besides the communication device and transmit them to the processor, or to send signals from the processor to other communication devices besides the communication device. The processor, through logic circuits or executable code instructions, implements the methods executed by the terminal device in the first aspect, or the methods executed by the network device in the second aspect.

[0067] In one possible implementation, the communication device is a chip or chip system.

[0068] Fifthly, a communication device is provided, including a processor, and optionally, a memory; the processor and the memory are coupled; the memory is used to store computer programs or instructions; the processor is used to execute part or all of the computer programs or instructions in the memory, and when the part or all of the computer programs or instructions are executed, to implement the functions of the terminal device in the first aspect above, or to implement the functions of the network device in the second aspect above.

[0069] In one possible implementation, the apparatus may further include a transceiver for transmitting signals processed by the processor or receiving signals input to the processor. The transceiver may perform the transmitting or receiving actions performed by the terminal device in the first aspect, or the transmitting or receiving actions performed by the network device in the second aspect.

[0070] In one possible implementation, the processing unit in the third aspect can be implemented by the processor, the storage unit in the third aspect can be implemented by the memory, and the transceiver unit in the third aspect can be implemented by the transceiver.

[0071] In one possible implementation, the communication device is a chip or chip system.

[0072] A sixth aspect provides a communication system comprising the terminal device of the first aspect and the network device of the second aspect. For example, the terminal device may be implemented using the communication apparatus described in the fourth or fifth aspect. Similarly, the network device may be implemented using the communication apparatus described in the fourth or fifth aspect.

[0073] In a seventh aspect, a computer-readable storage medium is provided for storing a computer program or instructions that, when executed, cause any of the methods in the first aspect or any of the methods in the second aspect to be implemented.

[0074] Eighthly, a computer program product containing instructions is provided, which, when run on a computer, causes any of the methods in the first aspect above to be implemented, or causes any of the methods in the second aspect above to be implemented. Attached Figure Description

[0075] Figure 1 is a schematic diagram of the architecture of the communication system provided in an embodiment of this application;

[0076] Figure 2 is a schematic diagram of the architecture of the communication system provided in an embodiment of this application;

[0077] Figure 3 is a price diagram of the O-RAN system provided in the embodiment of this application;

[0078] Figure 4 is a schematic diagram of matrix transformation provided in an embodiment of this application;

[0079] Figure 5 is a schematic flowchart of the communication method provided in an embodiment of this application;

[0080] Figure 6 is a schematic diagram of discarded elements and element filling provided in the embodiments of this application;

[0081] Figure 7 is a schematic diagram of discarded elements provided in an embodiment of this application;

[0082] Figures 8 and 9 are structural diagrams of the communication device provided in the embodiments of this application. Detailed Implementation

[0083] The technical solution of this application can be applied to various wireless communication systems, including but not limited to fourth-generation (4G) mobile communication technology systems (also known as long term evolution (LTE) systems), fifth-generation (5G) mobile communication technology systems (also known as new radio (NR) systems), or future mobile communication systems, etc., without any specific limitations.

[0084] Furthermore, the technical solutions provided in this application can be applied to device-to-device (D2D) scenarios, such as NR-D2D scenarios, or to vehicle-to-everything (V2X) communication scenarios, such as NR-V2X scenarios. For example, they can be used in fields such as intelligent driving, assisted driving, or intelligent connected vehicles. As another example, the technical solutions provided in this application can also be applied to factory manufacturing scenarios.

[0085] Furthermore, the technical solutions provided in this application can be applied to scenarios including but not limited to: terrestrial cellular communication, non-terrestrial network (NTN), satellite communication, high altitude platform station (HAPS) communication, integrated access and backhaul (IAB) communication, and reconfigurable intelligent surface (RIS) communication.

[0086] Figure 1 is a schematic diagram of the architecture of the communication system applied in this application embodiment. The communication system 1000 shown in Figure 1 includes a wireless access network 100 and a core network 200. Optionally, the communication system 1000 also includes an Internet 300. The wireless access network 100 may include at least one network device (110a and 110b in Figure 1) and at least one terminal device (120a-120j in Figure 1). The terminal device is wirelessly connected to the network device, and the network device is wirelessly or wiredly connected to the core network 200. The core network device and the network device may be independent and different physical devices, or the functions of the core network device and the logical functions of the network device may be integrated on the same physical device, or a single physical device may integrate some of the functions of the core network device and some of the functions of the network device. Terminal devices and network devices can be interconnected via wired or wireless means. Figure 1 is only a schematic diagram; this communication system may also include other network devices, such as wireless relay devices and wireless backhaul devices, which are not shown in Figure 1.

[0087] The radio access network 100 can be a cellular system related to the 3rd generation partnership project (3GPP), such as 4G, 5G, or evolution systems beyond 5G (e.g., 6G mobile communication systems). The radio access network 100 can also be an open radio access network (open RAN, O-RAN, or ORAN) or a cloud radio access network (CRAN). The radio access network 100 can also be a communication system that integrates two or more of the above systems.

[0088] Network devices are nodes in a radio access network (RAN), also known as access network devices or RAN nodes (or devices). Network devices help terminal devices achieve wireless access. Multiple network devices in the communication system 1000 can be nodes of the same type or different types.

[0089] In one possible scenario, network equipment can be a base station, an evolved NodeB (eNodeB), a transmitting and receiving point (TRP), a transmitting point (TP), a next-generation NodeB (gNB), a next-generation base station in a 6G mobile communication system, a base station in a future mobile communication system, an access point (AP) in a satellite, an integrated access and backhaul (IAB) node, or network equipment in a mobile switching center non-terrestrial network (NTN) communication system. This means it can be deployed on high-altitude platforms or satellites. Network equipment can be a macro base station (as shown in Figure 1, 110a), a micro base station or indoor station (as shown in Figure 1, 110b), a relay node or donor node, or a radio controller in a CRAN scenario. Network equipment can also function as a base station in device-to-device (D2D) communication, vehicle-to-everything (V2X) communication, drone communication, or machine-to-machine (M2M) communication. Optionally, network equipment can also be a server, wearable device, vehicle, or in-vehicle equipment. For example, the access network equipment in V2X technology can be a roadside unit (RSU).

[0090] In another possible scenario, multiple network devices collaborate to assist terminal devices in achieving wireless access, with each network device implementing a portion of the base station's functions. For example, network devices can be one or more of the following: a central unit (CU), a distributed unit (DU), a CU-control plane (CP), a CU-user plane (UP), or a radio unit (RU). The CU and DU can be separately configured (i.e., physically separate) or included simultaneously in the same network element, such as a baseband unit (BBU); this application does not impose limitations on this. The RU can be included in radio equipment or radio units, such as a remote radio unit (RRU), an active antenna unit (AAU), or a remote radio head (RRH). It is understood that network devices can be CU nodes, DU nodes, or devices comprising both CU and DU nodes. Furthermore, the CU can be classified as a network device in the access network (RAN) or a network device in the core network (CN); this is not limited here. CU and DU can be understood as a logical functional division of a base station. Physically, CU and DU can be separate or deployed together; this application does not specifically limit this. One CU can connect to one DU, or multiple DUs can share one CU, which can save costs and facilitate network expansion.

[0091] For example, as shown in Figure 2, a RAN node can include a central unit (CU), a distributed unit (DU), or a radio unit (RU). The CU performs the functions of the base station's Radio Resource Control (RRC) and Packet Data Convergence Protocol (PDCP), and can also perform the functions of the Service Data Adaptation Protocol (SDAP). The DU performs the functions of the base station's Radio Link Control (RAN) and Media / Medium Access Control (MAC) layers, and can also perform some or all of the physical layer functions. For detailed descriptions of each of these protocol layers, please refer to the relevant 3GPP technical specifications. The RU can be used to implement radio frequency signal transmission and reception functions.

[0092] The CU and DU can be two independent RAN nodes, or they can be integrated into the same RAN node, such as within a baseband unit (BBU). The BBU communicates with the core network (CN) via a backhaul link, while the RU communicates with at least one terminal via an air interface. The BBU also communicates with at least one RU via a fronthaul link. The BBU and RU can be co-located or not. CUs and DUs integrated within a BBU can communicate via at least one midhaul link. RUs can be included in radio frequency equipment, such as in remote radio units (RRUs) or active antenna units (AAUs). CUs can be further classified into two types of RAN nodes: CU-control plane and CU-user plane.

[0093] Furthermore, the CU includes CU-CP and CU-UP. CU-CP is connected to the DU via F1-C (control plane), and CU-UP is connected to the DU via F1-U (user plane). CU-CP and CU-UP are connected via the E1 interface. CU-CP represents the gNB connected to the core network via the Ng interface.

[0094] In different systems, CU (or CU-CP and CU-UP), DU, or RU may have different names, but those skilled in the art will understand their meaning. For example, in an ORAN system, CU can also be called O-CU (open CU), DU can also be called O-DU, CU-CP can also be called O-CU-CP, CU-UP can also be called O-CU-UP, and RU can also be called O-RU. For ease of description, this application uses CU, CU-CP, CU-UP, DU, and RU as examples. Any of the units among CU (or CU-CP, CU-UP), DU, and RU in this application can be implemented through software modules, hardware modules, or a combination of software and hardware modules.

[0095] A terminal device is a device with wireless transceiver capabilities, capable of sending signals to or receiving signals from network devices. Terminal devices include, but are not limited to, terminal equipment, user equipment (UE), mobile stations, and mobile terminals. Terminal devices can be widely used in various scenarios, such as device-to-device (D2D), vehicle-to-everything (V2X) communication, machine-type communication (MTC), the Internet of Things (IoT), virtual reality, augmented reality, industrial control, autonomous driving, telemedicine, smart grids, smart furniture, smart offices, smart wearables, intelligent transportation, and smart cities. Specifically, terminal devices can be mobile phones, tablets, computers with wireless transceiver capabilities, wearable devices, vehicles, aircraft, ships, robots, robotic arms, smart home devices, etc. The embodiments of this application do not limit the specific technologies or device forms used in the terminal devices.

[0096] Network devices and terminal devices can be fixed in location or mobile. They can be deployed on land, including indoors or outdoors, handheld or vehicle-mounted; they can also be deployed on water; and they can be deployed on aircraft, balloons, and artificial satellites. The embodiments of this application do not limit the application scenarios of the network devices and terminal devices.

[0097] The roles of network devices and terminal devices can be relative. For example, the helicopter or drone 120i in Figure 1 can be configured as a mobile network device. For terminal devices 120j that access the wireless access network 100 via 120i, terminal device 120i is a network device; however, for network device 110a, 120i is a terminal device, meaning that 110a and 120i communicate via a wireless air interface protocol. Of course, 110a and 120i can also communicate via a network device-to-network device interface protocol. In this case, relative to 110a, 120i is also a network device. Therefore, both network devices and terminal devices can be collectively referred to as communication devices. 110a and 110b in Figure 1 can be called communication devices with network device functions, and 120a-120j in Figure 1 can be called communication devices with terminal device functions.

[0098] Communication between network devices and terminal devices, between network devices, and between terminal devices can be conducted using licensed spectrum, unlicensed spectrum, or both simultaneously. Communication can be conducted using spectrum below 6 GHz, spectrum above 6 GHz, or both simultaneously. The embodiments of this application do not limit the spectrum resources used for wireless communication.

[0099] In the embodiments of this application, the functions of the network device can be executed by modules (such as chips) within the network device, or by a control subsystem that includes network device functions. This control subsystem, including network device functions, can be a control center in the aforementioned application scenarios such as smart grids, industrial control, intelligent transportation, and smart cities. Similarly, the functions of the terminal device can be executed by modules (such as chips or modems) within the terminal device, or by a device that includes terminal device functions.

[0100] In this application, the base station sends downlink signals or downlink information to the terminal, with the downlink information carried on the downlink channel; the terminal sends uplink signals or uplink information to the base station, with the uplink information carried on the uplink channel. In order to communicate with the base station, the terminal needs to establish a radio connection with a cell controlled by the base station. The cell with which the terminal has established a radio connection is called the terminal's serving cell. When the terminal communicates with this serving cell, it is also subject to interference from signals from neighboring cells.

[0101] Figure 3 illustrates the network element division and protocol layer structure in the O-RAN system. In some examples, the CU (Core Unit) is a logical node carrying the Radio Resource Control (RRC) layer, Service Data Adaptation Protocol (SDAP) layer, Packet Data Convergence Protocol (PDCP) layer, and other control functions of the access network equipment. The CU connects to network nodes such as the core network through interfaces, which can be interfaces such as E2 interfaces. Optionally, the CU may have some core network functions. The CU (e.g., PDCP layer and higher layers) connects to the DU (e.g., RLC layer and lower layers) through interfaces, which can be interfaces such as F1 interfaces. In some examples, these interfaces (e.g., F1 interfaces) can provide control plane (C-plane) and user plane (U-plane) functions (e.g., interface management, system information management, UE context management, RRC message transmission, etc.). F1AP is the application protocol of the F1 interface, defining the F1 signaling procedures in some examples. The F1 interface supports control plane F1-C and user plane F1-U.

[0102] In some examples, the CU can be split into CU-CP and CU-UP. CU-CP is a logical node carrying the RRC layer and PDCP-C (Control plane part of PDCP) layer, used to implement the CU's control plane functions. CU-CP can interact with network elements in the core network used to implement control plane functions. These network elements in the core network can be access and mobility function (AMF) network elements, such as the AMF network element in a 5G system. The AMF network element is responsible for mobility management in the mobile network, such as terminal location updates, terminal registration with the network, and terminal handover. CU-UP is a logical node carrying the SDAP layer and PDCP-U (User plane part of PDCP) layer, used to implement the CU's user plane functions. CU-UP can interact with network elements in the core network used to implement user plane functions. These network elements in the core network, such as the UPF network element in a 5G system, are responsible for forwarding and receiving data in the terminal. The above CU and DU configurations are merely examples; the functions of the CU and DU can be configured as needed. For instance, the CU or DU can be configured to have more protocol layer functions, or only some protocol layer processing functions. For example, some RLC layer functions and protocol layer functions above the RLC layer can be placed in the CU, while the remaining RLC layer functions and protocol layer functions below the RLC layer can be placed in the DU. Furthermore, the functions of the CU or DU can be divided according to service type or other system requirements, such as by latency. Functions that require low latency can be placed in the DU, while functions that do not require low latency can be placed in the CU.

[0103] In some examples, a DU is a logical node that carries the radio link control (RLC) layer, MAC layer, higher physical layer (PHY) layer, and other functions. In some examples, a DU can control at least one RU. The DU connects to the RU through interfaces, which can be fronthaul interfaces. In some examples, the higher PHY layer includes the PHY layer processing, such as forward error correction (FEC) encoding and decoding, scrambling, modulation, and demodulation.

[0104] In some examples, the RU is a logical node that carries both lower physical layer (PHY) and radio frequency (RF) processing. In some examples, the RU can be a 3GPP transmission reception point (TRP), a remote radio head (RRH), or other similar entities. In some examples, the low-PHY includes portions of the PHY processing, such as fast Fourier transform (FFT), inverse fast Fourier transform (IFFT), digital beamforming, and filtering. The RU communicates with one or more UEs via a radio link.

[0105] The DU and RU may or may not be co-located. The DU and RU exchange control plane and user plane information via a lower-layer split cus-plane (LLS-CUS) interface through a fronthaul link. LLS-CUS may include LLS-C and LLS-U interfaces, respectively providing control plane (C-plane) and user plane (U-plane) access. In some examples, the control plane refers to real-time control between the DU and RU. The DU and RU exchange management information via an LLS-M interface on the fronthaul link; the management plane (M-plane) refers to non-real-time management operations between the DU and RU.

[0106] DU and RU can cooperate to implement the functions of the PHY layer. A DU can be connected to one or more RUs. The functions of DU and RU can be configured in various ways depending on the design. For example, a DU can be configured to implement baseband functions, and an RU can be configured to implement mid-RF functions. Another example is that a DU can be configured to implement higher-level functions in the PHY layer, and an RU can be configured to implement lower-level functions in the PHY layer, or to implement both lower-level and RF functions. Higher-level functions in the physical layer can include a portion of the physical layer's functions that are closer to the MAC layer, while lower-level functions in the physical layer can include another portion of the physical layer's functions that are closer to the mid-RF side.

[0107] Optionally, any one of CU, CU-CP, CU-UP, DU, and RU can be a software module, a hardware structure, or a combination of software and hardware structures, without limitation. The different entities can exist in the same or different forms. For example, CU, CU-CP, CU-UP, and DU are software modules, and RU is a hardware structure. For the sake of brevity, not all possible combinations are listed here. These modules and their executed methods are also within the protection scope of the embodiments of this application. For example, when the method of the embodiments of this application is executed by an access network device, it can be executed by at least one of CU, CU-CP, CU-UP, or DU.

[0108] Communication systems can increase system capacity and improve throughput through MIMO technology. In multi-antenna communication systems, signals from multiple transmitting antennas of the transmitting device, after transmission through the channel, can be superimposed on any one receiving antenna of the receiving device. Therefore, the method of signal transmission by the transmitting device affects system performance, and the process of the receiving device recovering the transmitted signal is also relatively complex. In this context, precoding technology can be used to reduce system overhead and improve the system capacity of MIMO; on the other hand, it can reduce the complexity of the receiving device in eliminating inter-channel interference. Precoding technology can be implemented using a precoding matrix. For example, a network device sends a reference signal to a terminal device, the terminal device determines a precoding matrix based on the reference signal, and feeds back the determined precoding matrix to the network device. In this way, the network device can send downlink data to the terminal device based on the precoding matrix.

[0109] The following describes an example of a terminal device feeding back a precoding matrix to a network device, as shown in Figure 4. This example includes steps 1 to 4a:

[0110] Step 1: The terminal device receives a reference signal from the network device and determines the channel matrix H on different sub-bands based on the reference signal.

[0111] For example, the reference signal is the channel state information reference signal (CSI-RS). Network devices use N... TX The reference signal is transmitted by N antennas, and the terminal device uses N... RX Each antenna receives the reference signal, and the reference signal is in N sub Transmission on each sub-band, N sub These are positive integers, such as 64, 128, etc. The channel matrix H includes N... RX Line N TX Based on this reference signal, the terminal device can determine N. sub A channel matrix H.

[0112] Step 2: The terminal device determines the precoding matrices (W1, W2, ..., W...) corresponding to each of the v spatial streams based on the channel matrix H. v ).

[0113] For example, the terminal device uses singular value decomposition (SVD) to determine the right singular matrix Y of each channel matrix H, where the right singular matrix Y includes N TX The array consists of rows and columns v, where v represents the number of spatial streams (also known as tiers or rank) supported by the network device for downlink data transmission, and v is an integer greater than or equal to 1. For example, H = XSY H In this equation, H on the left side represents the channel matrix H, and X, S, and Y on the right side represent the left singular matrix, singular value matrix, and right singular matrix of the channel matrix H, respectively; Y H This represents the conjugate transpose of matrix Y.

[0114] Then, the terminal device will N sub By concatenating the right singular matrices of each subband, we can obtain v precoding matrices W1, W2, ..., W... v Each precoding matrix includes N TX Line N sub Column elements. The v precoding matrices can be understood as the precoding matrices fed back from the terminal device to the network device, with each v precoding matrix corresponding one-to-one with a v spatial stream. One concatenation method is to... sub The right singular matrices of each sub-band are denoted as: Will The f-th columns of each are concatenated together to obtain the f-th precoding matrix W. f For example, the first column of Y1 is the first column of W1, and the first column of Y2 is the second column of W1. The first column is the Nth column of W1 sub Column; the second column of Y1 is the first column of W2, and the second column of Y2 is the second column of W2. The second column is the Nth column of W2. sub Column; the 3rd column of Y1 is the 1st column of W3, and the 3rd column of Y2 is the 2nd column of W3. The 3rd column is the Nth column of W3 sub And so on.

[0115] Step 3: The terminal device precodes the matrix W corresponding to the f-th spatial stream (where f takes the value of an integer from 1 to v). f Compression is performed to obtain the f-th compressed precoding matrix.

[0116] For example, according to the protocol predefined, network devices and terminal devices are pre-configured with a compression matrix Q.f Alternatively, the terminal device obtains the compressed matrix Q through online training. f Compression matrix Q f Including N TX The elements are in rows and columns r, where r represents the row size of the compressed precoding matrix; the terminal device uses Q. f Spatial compression reduces the amount of data, resulting in a compressed precoding matrix. Q f H Representation matrix Q f The conjugate transpose of the compressed precoding matrix Including r rows N sub Column elements, r is greater than 1 and less than N TX Integers.

[0117] Step 4a: The terminal device uses the f-th compressed precoding matrix as a basis. Calculate the f-th transformation matrix G f .

[0118] Transformation matrix G f Including r rows and r columns, step 4a can be understood as the terminal device determining a transformation matrix G. f To meet W k，f Approaching G f k-1 W 1，f , or, |G f k-1 W 1，f -W k，f |<γ, where γ is greater than 0 and less than 1. W 1，f W represents the reference matrix (or baseline matrix). 1，f It is the compressed precoding matrix The first s' column corresponds to the first sub-band, where s' is greater than or equal to 1 and less than N. sub Integer; W k，f It is the compressed precoding matrix The (k-1)s'+1th column to the ks'th column correspond to the kth sub-band, where k takes the value of an integer from 1 to K; the k sub-bands include N sub Sub-bands, where K = N sub / s',G f k-1 G represents f The k-1 power. If s' is 1, the reference matrix is ​​the compressed precoding matrix. The first column, the reference matrix, can also be called the reference vector or the base vector; if s' is 2, the reference matrix is ​​the compressed precoding matrix. The first and second columns. The larger the value of s', the more data the terminal device transmits, and the higher the accuracy of the network device in reconstructing the precoding matrix; the smaller the value of s', the less data the terminal device transmits, saving transmission overhead.

[0119] Step 4b: The terminal device sends the transformation matrices (G1, ..., G1) corresponding to v spatial streams to the network device. v ) and reference matrix (W 1，1 ... W 1，v The terminal device feeds back the transformation matrix and the reference matrix corresponding to the first sub-band to the network device for each spatial stream, without needing to report N. sub Each sub-band has a corresponding reference matrix, which can reduce the amount of feedback data and lower feedback overhead.

[0120] Further, optionally, after step 4a, step 5a is performed: the terminal device determines the f-th transformation matrix G. f Generalized feature decomposition, for example, G f Approaching ψ f Λ f ψ f H , or, |G f -ψ f Λ f ψ f H |<α, α is greater than 0 and less than 1; where, Λ f Let G be the transformation matrix. f eigenvalue matrix, Λ f It is a diagonal matrix, ψ f The transformation matrix G f eigenvector matrix, Λ f and ψ f Each includes r rows and r columns of elements.

[0121] Step 5b: The terminal device can send the feature vector matrices (ψ1, ..., ψ2) corresponding to v spatial streams to the network device. v ), eigenvalue matrix (Λ1, ..., Λ) v ) and reference matrix (W 1，1 ... W 1，v Step 4b is not required.

[0122] Step 6: The network device determines the compressed precoding matrix based on the information from the terminal device in step 4b or step 5b.

[0123] For example, the network device is based on the f-th reference matrix W in step 5b. 1，f The f-th eigenvalue matrix Λ f and the f-th eigenvector matrix ψ fDetermine the f-th compressed precoding matrix

[0124] For example, based on the f-th reference matrix W 1，f The f-th eigenvalue matrix Λ f and the f-th eigenvector matrix ψ f Calculate the matrix W corresponding to the k-th sub-band. k，f For example, W k，f Approaching ψ f Λ f k-1 ψ f H W 1，f , or, |W k，f -ψ f Λ f k-1 ψ f H W 1，f |<β, β is greater than 0 and less than 1; where Λ f k-1 Represents Λ f The k-1th power; then, based on N sub Each sub-band corresponds to W k，f (k takes the value of an integer from 1 to K), concatenate to obtain the f-th compressed precoding matrix. For example,

[0125] Based on the information in step 4b, the network device determines the f-th compressed precoding matrix. The principle is similar, so I won't go into details.

[0126] Transform matrix G f After further decomposition, during reconstruction, the diagonal matrix Λ f Multiplying k-1 times is relatively simple because all off-diagonal elements in the diagonal matrix are 0. This simplifies the process by performing multiplication on each diagonal element individually, reducing the complexity of the receiver's recovery process and lowering the G-value. f The cumulative error caused by multiple multiplications improves the reconstruction accuracy.

[0127] Step 7: The network device uses the f-th compressed precoding matrix as a basis. Left-multiplying the compression matrix Q f The precoding matrix W corresponding to the f-th spatial stream is obtained. f The value of f is an integer from 1 to v, resulting in v precoding matrices.

[0128] As the number of antenna elements in terminal and network devices increases to support more spatial streams, the dimension of the precoding matrix is ​​also increasing significantly. The amount of data fed back from terminal devices to network devices is also increasing, and how to reduce the resource overhead of the feedback precoding matrix needs to be discussed.

[0129] Based on this, this application provides a communication method in which a terminal device determines M first matrices based on a received reference signal, where M is an integer greater than 1; the terminal device determines M second matrices, and the M first matrices and M second matrices correspond one-to-one; at least two of the M second matrices respectively include a portion of the corresponding first matrices; the priority of the elements in the i-th second matrix is ​​not lower than the priority of the elements in the i-th first matrix, i iterates through integers from 1 to M, and the M second matrices are used to determine the precoding matrix.

[0130] In this method, the terminal device can determine the precoding matrix based on the reference signal and then determine M first matrices based on the precoding matrix. If the terminal device sends the M first matrices to the network device, the network device can reconstruct the precoding matrix based on the M first matrices. However, in this application, the terminal device discards some elements from some or all of the M first matrices before sending them to the network device, which can reduce resource overhead. When discarding elements, lower priority elements are discarded first, thus having little impact on the accuracy of the network device's reconstruction of the precoding matrix based on the M second matrices, and the network device can still determine the precoding matrix relatively accurately.

[0131] The relevant terms used in the embodiments of this application will be explained below. It should be noted that these explanations are for the purpose of making the embodiments of this application easier to understand, and should not be regarded as limiting the scope of protection claimed by this application.

[0132] 1. Eigenvector matrix, eigenvalue matrix, reference matrix, and transformation matrix:

[0133] The eigenvector matrix consists of r rows and r columns of elements. This matrix is ​​used to represent the eigenvectors obtained through generalized eigenvalue decomposition. The eigenvector matrix can also be called the feature matrix.

[0134] The eigenvalue matrix consists of r rows and r columns of elements, forming a diagonal matrix. This matrix is ​​used to represent the eigenvalues ​​obtained through generalized eigenvalue decomposition. The eigenvalue matrix can also be called the eigenvalue array.

[0135] The reference matrix, also known as the baseline matrix, consists of r rows and s' columns, where s' is an integer greater than or equal to 1. When s' is 1, the reference matrix can also be called the reference vector or baseline vector; this matrix is ​​used to represent the reference information to be fed back.

[0136] The transformation matrix consists of r rows and r columns of elements. This matrix is ​​used to represent the transformation information for recovering other information based on reference information. The transformation matrix can also be called a transformation array.

[0137] The r mentioned above is an integer greater than 1; optionally, r is less than N. TX integers, N TX The number of antennas that transmit reference signals for network devices.

[0138] For ease of distinction, the matrix determined by the terminal device based on the reference signal from the network device is called the first matrix. For example, the first matrix may be: the first eigenvector matrix, the first eigenvalue matrix, the first reference matrix, or the first transformation matrix.

[0139] The matrix sent from the terminal device to the network device is called the second matrix. Examples of second matrices include: second eigenvector matrix, second eigenvalue matrix, second reference matrix, or second transformation matrix.

[0140] The matrix determined by the network device based on the information from the second matrix from the terminal device is called the third matrix. For example, the third matrix may be the third eigenvector matrix, the third eigenvalue matrix, the third reference matrix, or the third transformation matrix.

[0141] 2. Stream: In a spatially multiplexed MIMO system, multiple parallel data streams can be transmitted simultaneously on the same frequency domain resources. Each data stream is called a stream. Streams in MIMO may also have other names, such as layer, spatial layer, transport layer, data layer, or spatial stream, etc. As long as they have the same meaning, they are all within the scope of protection of this application.

[0142] 3. The method executed by the terminal device in the embodiments of this application can also be implemented by the communication module in the terminal device, or the circuit or chip responsible for the communication function in the terminal device (such as a modem chip (also known as a baseband chip), or a system on chip (SoC) chip containing a modem core, or a system in package (SIP) chip).

[0143] 4. The method executed by the network device in the embodiments of this application can also be implemented by a module (e.g., circuit, chip or chip system) in the network device, or a logical node, logical module or software that can implement all or part of the functions of the network device.

[0144] 5. In this application, "instruction" or "for instruction" may include explicit instruction (or direct instruction) and implicit instruction (or indirect instruction). When describing information for instructing A, it may include whether the information explicitly instructs A or implicitly instructs A, but does not necessarily mean that the information carries A.

[0145] The indication methods involved in the embodiments of this application should be understood to cover various methods that enable the party to be indicated to obtain the information to be indicated. The information to be indicated can be sent as a whole or divided into multiple sub-information and sent separately. Moreover, the sending period and / or sending time of these sub-information can be the same or different, without limitation.

[0146] In the embodiments of this application, "information" can be an explicit indication, that is, a direct indication through signaling, or obtained by combining other rules or parameters with parameters indicated by signaling, or by deduction. It can also be an implicit indication, that is, obtained based on rules or relationships, or based on other parameters, or by deduction. No limitation is imposed.

[0147] 6. In this application, communication between different devices can refer to direct communication between different devices (i.e., without the need for relaying or forwarding by other devices), or communication between different devices through other devices (i.e., requiring relaying or forwarding by other devices), or communication between a functional unit within a device and other devices through another functional unit. For example, "sending information to…(terminal)" can be understood as the destination of the information being the terminal, and may include sending information directly or indirectly to the terminal. "Receiving information from…(terminal)" can be understood as the source of the information being the terminal, and may include receiving information directly or indirectly from the terminal. Information may undergo necessary processing between the source and destination, such as format changes, digital-to-analog conversion, amplification, filtering, etc., but the destination can understand the valid information from the source. Similar expressions in this application can be understood in a similar way, and will not be elaborated further here.

[0148] The naming of each message / information in this application is merely illustrative and limits the names of each message / information.

[0149] 7. In this application, the words "exemplarily," "for example," "for instance," and "example" are used to indicate examples, illustrations, or explanations, and are not intended to limit the scope of protection of this application. It should be understood that the examples in this application may also be implemented in other ways.

[0150] 8. In this application, "greater than or equal to" and "greater than" are interchangeable; and / or, "less than" and "less than or equal to" are interchangeable.

[0151] 9. In the embodiments of this application, "when," "if," and "if" all refer to the device taking corresponding actions under certain objective circumstances, and are not time-limited, nor do they require the device to perform a judgment action, nor do they imply any other limitations. Unless otherwise specified, "if" and "if" can be substituted, and "when" and "in the case of" can be substituted. "When" and "if" / "if" can be substituted.

[0152] 10. In the embodiments of this application, the number of nouns, unless otherwise specified, refers to "singular nouns or plural nouns," that is, "one or more." "At least one" means one or more, and "more than one" means two or more. "And / or" describes the relationship between related objects, indicating that there can be three relationships. For example, A and / or B can mean: A exists alone, A and B exist simultaneously, or B exists alone, where A or B can be singular or plural. The character " / " generally indicates that the related objects before and after are in an "or" relationship. For example, A / B means: A or B. Expressions such as "at least one of the following" or "one or more of them" refer to any combination of these items, including any combination of single or plural items. For example, at least one of a, b, or c, or one or more of a, b, or c, means: a, b, c, a and b, a and c, b and c, or a and b and c. Each of a, b, and c can be single or multiple.

[0153] 11. In the embodiments of this application, the ordinal numbers such as "first" and "second" are used to distinguish multiple objects and are not used to limit the size, content, order, timing, priority, or importance of the multiple objects. Furthermore, such names do not indicate differences in the content, sending / receiving end, sending order, size, application scenario, priority, or importance of the two pieces of information. Additionally, the numbering of steps in the various embodiments described in this application is only to distinguish different steps and is not used to limit the order of steps.

[0154] To better illustrate the embodiments of this application, the methods provided by the embodiments of this application are described below with reference to the accompanying drawings. Unless otherwise specified below, the steps indicated by dashed lines in the accompanying drawings corresponding to the various embodiments of this application are optional steps. It should be noted that the technical details of the multiple embodiments provided in this application can be referenced to each other, each embodiment described below can exist independently, and multiple embodiments can also be combined with each other as an embodiment in the absence of logical errors.

[0155] Figure 5 is a flowchart illustrating a communication method provided in an embodiment of this application.

[0156] Step 500: The network device sends a reference signal; correspondingly, the terminal device receives the reference signal. For example, the reference signal is CSI-RS or demodulation reference signal (DMRS).

[0157] Step 501: The terminal device determines M first matrices based on the received reference signals, where M is an integer greater than or equal to 2.

[0158] For example, based on the reference signal from step 500, the terminal device determines the compression information (or dynamic mode decomposition (DMD) information) corresponding to v spatial streams, where v is an integer greater than or equal to 1, and v is the number of spatial streams supported by the network device during downlink data transmission. Referring to steps 1-5a described above, in one example, the compression information includes: v transformation matrices (G1, ..., G...). v ) and v reference matrices (W 1，1 ... W 1，v In another example, the compressed information includes: v eigenvector matrices (ψ1, ..., ψ2). v v eigenvalue matrices (Λ1, ..., Λ) v ) and v reference matrices (W 1，1 ... W 1，v The M first matrices can be understood as: compressed information (or DMD information) corresponding to any spatial stream.

[0159] Example 1: The M first matrices include a first transformation matrix and a first reference matrix; this can also be understood as the first transformation matrix and the first reference matrix corresponding to the f-th spatial flow. Example 2: The M first matrices include a first eigenvector matrix, a first eigenvalue matrix, and a first reference matrix; this can also be understood as the first eigenvector matrix, the first eigenvalue matrix, and the first reference matrix corresponding to the f-th spatial flow. The first eigenvalue matrix is ​​a diagonal matrix. The first eigenvector matrix and the first eigenvalue matrix are used to determine the transformation matrix, and the first reference matrix and the transformation matrix are used to determine the precoding matrix (e.g., the precoding matrix corresponding to the f-th spatial flow).

[0160] For example, the M first matrices are used to determine the precoding matrix (e.g., the precoding matrix W in step 2 above). f Alternatively, M first matrices are used to determine the compressed (dimensionality-reduced) precoding matrix (e.g., the compressed precoding matrix in step 3 above). It should be noted that the number of rows in the compressed precoding matrix is ​​less than the number of rows in the uncompressed precoding matrix, and the number of columns in the compressed precoding matrix is ​​less than or equal to the number of columns in the uncompressed precoding matrix.

[0161] Step 502a: The terminal device determines M second matrices.

[0162] The second matrix is ​​used to determine the precoding matrix. There is a one-to-one correspondence between the M first matrices and the M second matrices. The i-th first matrix includes: the i-th second matrix and N elements; the N elements are all elements of the i-th first matrix excluding the elements of the i-th second matrix; i iterates through integers from 1 to M, and N is an integer greater than or equal to 0. When N is greater than 0, it indicates that the number of elements in the i-th second matrix is ​​less than the number of elements in the i-th first matrix; when N = 0, it indicates that the i-th second matrix is ​​the same as the i-th first matrix. Among the M second matrices, there exist at least two second matrices whose number of elements is less than the number of elements in their corresponding first matrices (i.e., at least two of the M second matrices each include a portion of the elements of their corresponding first matrices). The values ​​of N corresponding to the M second matrices are not necessarily the same.

[0163] The priority of the N elements in the i-th first matrix is ​​no higher than the priority of the elements in the i-th second matrix. In other words, the priority of the elements in the i-th second matrix is ​​no lower than the priority of the elements in the i-th first matrix. The higher the priority of an element, the easier it is to retain it; the lower the priority of an element, the easier it is to discard it. For example, the priority of an element is associated with its modulus; or, the priority of a row of elements is associated with the modulus of the elements in that row; or, the priority of a column of elements is associated with the modulus of the elements in that column.

[0164] Step 502b: The terminal device sends information about M second matrices; correspondingly, the network device receives information about M second matrices.

[0165] When a terminal device sends information from M second matrices, it can be understood that the terminal device converts the elements of the M second matrices into bit sequences and sends the corresponding bit sequences. During the conversion to bit sequences, the values ​​of the elements can be quantized based on quantization precision; for example, complex values ​​can be quantized to a certain precision, and then the quantized values ​​can be converted back into bit sequences.

[0166] In addition, if in step 501 the terminal device determines the M first matrices corresponding to the v spatial streams based on the received reference signals, then in step 502b the terminal device sends information about the M second matrices corresponding to the v spatial streams, and the M first matrices corresponding to the f-th spatial stream and the M second matrices corresponding to the f-th spatial stream are in one-to-one correspondence.

[0167] For example, the information of the M second matrices, or the information of the M second matrices corresponding to the v spatial streams, is carried in the channel state information (CSI).

[0168] Optionally, before the terminal device sends information about M second matrices to the network device (i.e., step 502b), the network device sends first information to the terminal device; correspondingly, the terminal device receives the first information, which is used to indicate a first resource for transmitting the M second matrices; one possible implementation of step 502b is: the terminal device sends information about M second matrices on the first resource; the network device receives information about M second matrices on the first resource. For example, the number of elements included in the M second matrices is less than or equal to the upper limit of the number of elements allowed to be transmitted on the first resource; or, the number of bits corresponding to the elements included in the M second matrices is less than or equal to the upper limit of the number of bits allowed to be transmitted on the first resource. The first information can be carried in RRC signaling, or MAC-control element (CE), or downlink control information (DCI).

[0169] Optionally, the first resource is a resource for transmitting M second matrices (v×M second matrices) corresponding to v spatial streams respectively. One possible implementation of step 502b is: the terminal device sends information about the M second matrices corresponding to the v spatial streams respectively on the first resource; correspondingly, the network device receives information about the M second matrices corresponding to the v spatial streams respectively on the first resource. For example, the number of elements included in the M second matrices (v×M second matrices) corresponding to the v spatial streams is less than or equal to the upper limit of the number of elements allowed to be transmitted on the first resource; or, the number of bits corresponding to the elements of the M second matrices (v×M second matrices) corresponding to the v spatial streams is less than or equal to the upper limit of the number of bits allowed to be transmitted on the first resource.

[0170] Step 503: The network device determines M third matrices based on the information from the M second matrices.

[0171] There is a one-to-one correspondence between the M second matrices and the M third matrices; the i-th third matrix includes the i-th second matrix and N elements; the M third matrices are used to determine the precoding matrix; in other words, at least two of the M second matrices each include a portion of the elements of their corresponding third matrices. Furthermore, the priority of the elements in the i-th second matrix is ​​no lower than the priority of the elements in the i-th third matrix. The process by which the network device determines the precoding matrix based on the M third matrices can be referred to steps 6 and 7 above, and will not be elaborated upon here.

[0172] If, in step 502b, the network device receives information about the M second matrices corresponding to the v spatial streams respectively, then in step 503, the network device determines the third matrix corresponding to the f-th spatial stream based on the information about the M second matrices corresponding to the f-th spatial stream. The M third matrices corresponding to the f-th spatial stream and the M second matrices corresponding to the f-th spatial stream are in one-to-one correspondence. This application uses the first, second, and third matrices of any spatial stream as an example for illustration.

[0173] After discarding (or omitting, or deleting) some elements from M first matrices, the terminal device obtains M second matrices and sends the information of the M second matrices to the network device. The network device fills in the M second matrices to obtain M third matrices. These matrices can be filled with 0 (i.e., all N elements in any third matrix are 0), or filled based on historical information, such as the values ​​of the N elements in the matrix that did not discard elements in the most recent feedback from the terminal device (which can be understood as the most recent feedback first matrix). In other words, the elements in the third matrix, excluding the corresponding elements in the second matrix, are 0, or their values ​​are determined based on historical information. The number of rows and columns in the i-th third matrix is ​​the same as the number of rows and columns in the i-th first matrix. Optionally, the position (i.e., row index and / or column index) of the i-th second matrix in the i-th first matrix is ​​the same as its position in the i-th third matrix. That is, the position where the network device fills in the elements is the same as the position where the terminal device discards the elements; however, some positions may differ.

[0174] Figure 6 illustrates a method for discarding and filling elements. The M first matrices include: a first eigenvector matrix, a first eigenvalue matrix, and a first reference matrix; the M second matrices include: a second eigenvector matrix, a second eigenvalue matrix, and a second reference matrix; the M third matrices include: a third eigenvector matrix, a third eigenvalue matrix, and a third reference matrix.

[0175] The first eigenvector matrix is ​​partially decomposed to obtain the second eigenvector matrix; the second eigenvector matrix is ​​then padded with elements to obtain the third eigenvector matrix; the third eigenvector matrix and the first eigenvector matrix have the same dimensions (i.e., the number of rows and columns). Optionally, the second eigenvector matrix can occupy the same position within the third and first eigenvector matrices.

[0176] The first eigenvalue matrix is ​​partially discarded to obtain the second eigenvalue matrix. Elements are then padded to the second eigenvalue matrix to obtain the third eigenvalue matrix. The third eigenvalue matrix has the same size as the first eigenvalue matrix. Optionally, the elements from the second eigenvalue matrix occupy the same positions in both matrices. The eigenvalue matrices are diagonal matrices, and the elements on the diagonal are interchanged. For example, the first element might be placed in the third position, and the third element in the first position. This usually does not affect the accuracy of the reconstructed precoding matrix.

[0177] The first reference matrix is ​​partially discarded to obtain the second reference matrix; the second reference matrix is ​​then padded with elements to obtain the third reference matrix. The third reference matrix has the same size as the first reference matrix, and optionally, the second reference matrix can occupy the same position within both the third and first reference matrices.

[0178] It is understood that Figure 6 is merely a schematic diagram of element discarding and element filling, and does not impose any limitation on the discarding position. For example, the position of the discarded element in the first eigenvector matrix can be in the last few rows or columns, or in the first few rows or columns, or even in any row or column. Similarly, the position of the discarded element in the first reference matrix and the first eigenvalue matrix can be arbitrary. Furthermore, among the three matrices—the first eigenvector matrix, the first eigenvalue matrix, and the first reference matrix—only two matrices may have elements discarded, or all three matrices may have elements discarded.

[0179] In this method, the precoding is decomposed into M first matrices. The terminal device sends information from these M first matrices to the network device. Compared to directly sending the precoding matrix information, this reduces the resource overhead of feeding back the precoding matrix. Furthermore, by discarding a portion of the elements from some or all of the M first matrices before sending them to the network device, resource overhead can be further reduced. When discarding elements, lower-priority elements (i.e., elements with low importance) are discarded first, thus minimizing the impact on the accuracy of the network device in determining the precoding matrix based on the M second matrices; the network device can still determine the precoding matrix relatively accurately.

[0180] The following describes the dimensional relationships between the M first matrices, the M second matrices, and the M third matrices:

[0181] Example 1: M first matrices include: a first eigenvector matrix, a first eigenvalue matrix, and a first reference matrix; M second matrices include: a second eigenvector matrix, a second eigenvalue matrix, and a second reference matrix; M third matrices include: a third eigenvector matrix, a third eigenvalue matrix, and a third reference matrix. The third eigenvector matrix has the same size as the first eigenvector matrix, the third eigenvalue matrix has the same size as the first eigenvalue matrix, and the third reference matrix has the same size as the first reference matrix. (See Figure 7.)

[0182] Example 1-1: Discard elements in the first eigenvector matrix and the first reference matrix.

[0183] The first eigenvector matrix includes r rows of elements (optionally, including r columns), and the second eigenvector matrix includes x1 rows of elements (optionally, including r columns); the second eigenvalue matrix is ​​the same as the first eigenvalue matrix (optionally, including r rows and r columns); the first reference matrix includes r rows of elements (optionally, including s' columns), and the second reference matrix includes x1 rows of elements (optionally, including s' columns); x1 is a positive integer less than r.

[0184] Let the difference between r and x1 be a. Then the second eigenvector matrix has a fewer a rows of elements than the first eigenvector matrix, and the second reference matrix has a fewer a rows of elements than the first reference matrix. Here, a is an integer greater than or equal to 1 and less than r.

[0185] One example 1-2 involves discarding elements from the first eigenvector matrix and the first eigenvalue matrix.

[0186] The first eigenvector matrix includes r columns of elements (optionally, including r rows of elements), and the second eigenvector matrix includes x2 columns of elements (optionally, including r rows of elements); the first eigenvalue matrix includes r rows and r columns of elements, and the second eigenvalue matrix includes x2 rows and x2 columns of elements; x2 is a positive integer less than r; the second reference matrix is ​​the same as the first reference matrix (optionally, including r rows and s' columns of elements).

[0187] Let b be the difference between r and x2. Then the second eigenvector matrix is ​​reduced by b columns compared to the first eigenvector matrix, and the second eigenvalue matrix is ​​reduced by b rows and b columns compared to the first eigenvalue matrix, where b is an integer greater than or equal to 1 and less than r.

[0188] In one example 1-3, elements in the first eigenvector matrix, the first eigenvalue matrix, and the first reference matrix are discarded.

[0189] The first eigenvector matrix consists of r rows and r columns of elements, and the second eigenvector matrix consists of x1 rows and x2 columns of elements; the first eigenvalue matrix consists of r rows and r columns of elements, and the second eigenvalue matrix consists of x2 rows and x2 columns of elements; the first reference matrix consists of r rows of elements (optionally, including s' columns of elements), and the second reference matrix consists of x1 rows of elements (optionally, including s' columns of elements); x1 and x2 are both positive integers less than r.

[0190] In this example, the second eigenvector matrix has a fewer a rows and b columns than the first eigenvector matrix, the second eigenvalue matrix has a fewer b rows and b columns than the first eigenvalue matrix, and the second reference matrix has a fewer a rows than the first reference matrix.

[0191] It's important to note that Figure 7 uses the example of "row x1 elements being the preceding x1 elements of row r, and column x2 elements being the preceding x2 elements of column r (i.e., the reduced row a elements are the following row a elements of row r, and the reduced column b elements are the following column b elements of column r)" for illustration. In real-world scenarios, row x1 elements can be the preceding or following row x1 elements of row r, or consecutive or non-consecutive row x1 elements (i.e., the reduced row a elements can be the preceding or following row a elements of row r, or any consecutive or non-connected row a elements); similarly, column x2 elements can be the preceding or following column x2 elements of column r, or consecutive or non-consecutive column x2 elements (i.e., the reduced column b elements can be the preceding or following column b elements of column r, or any consecutive or non-connected column b elements).

[0192] Optionally, the difference between x1 and x2 is less than a set threshold, which can be 1, 2, or 3. A difference between x1 and x2 less than the set threshold ensures that the proportions of elements retained (or discarded) in the first eigenvector matrix, the first eigenvalue matrix, and the first reference matrix are close. This allows for a smoother adjustment of the network device's accuracy in reconstructing the precoding matrix during continuous adjustment of transmission resources, preventing abrupt changes.

[0193] Example 2: The M first matrices include a first reference matrix and a first transformation matrix; the first reference matrix has r rows of elements (optionally including s' columns), and the first transformation matrix has r rows and r columns of elements. The M second matrices include a second reference matrix and a second transformation matrix; the second reference matrix has x1 rows of elements (optionally including s' columns), and the second transformation matrix has x1 rows and x1 columns of elements, where x1 is less than r. The M third matrices include a third reference matrix and a third transformation matrix; the third reference matrix and the first reference matrix have the same size, and the third transformation matrix and the first transformation matrix have the same size.

[0194] In this example, the second transformation matrix has a fewer than 'a' rows and 'a' columns compared to the first transformation matrix, and the second reference matrix has a fewer than 'a' rows compared to the first reference matrix. The x1 row elements can be the preceding or following x1 rows of the r-row elements, or consecutive or discontinuous x1 rows (i.e., the reduced 'a' rows can be the preceding or following x1 rows of the r-row elements, or any consecutive or discontinuous x1 rows); the x1 column elements can be the preceding or following x1 columns of the r-column elements, or consecutive or discontinuous x1 columns (i.e., the reduced 'a' columns can be the preceding or following x1 columns of the r-column elements, or any consecutive or discontinuous x1 columns).

[0195] Network devices can send indication information to terminal devices, specifying which element in the matrix to discard. For example, four examples can be indicated using at least two bits: 00 indicates discarding the element using example 1-1, 01 indicates discarding the element using example 1-2, 10 indicates discarding the element using example 1-3, and 11 indicates discarding the element using example 2. Alternatively, the protocol can specify which method to discard the element.

[0196] The following describes the positional relationships (i.e., row indices and / or column indices) of the elements in the second eigenvector matrix, the second eigenvalue matrix, and the second reference matrix:

[0197] There is a correspondence between the rows of the first eigenvector matrix and the rows of the first reference matrix. For example, there is a correspondence between the e1-th row of the first eigenvector matrix and the e1-th row of the first reference matrix. Similarly, there is a correspondence between the columns of the first eigenvector matrix and the rows and columns of the first eigenvalue matrix. For example, there is a correspondence between the e2-th column of the first eigenvector matrix and the e2-th row and e2-th column of the first eigenvalue matrix. When discarding or retaining elements, corresponding rows and columns can be discarded or retained simultaneously, which improves the accuracy of the network device in determining (reconstructing, recovering) the precoding matrix (or the compressed precoding matrix).

[0198] In Examples 1-1 and 1-3 above, the row index of the x1 row element in the second eigenvector matrix in the first eigenvector matrix is ​​the same as the row index of the x1 row element in the second reference matrix in the first reference matrix. That is, the row index of the a-row element removed from the first eigenvector matrix in the first eigenvector matrix is ​​the same as the row index of the a-row element removed from the first reference matrix in the first reference matrix.

[0199] Correspondingly, the row index of the x1 row element in the second eigenvector matrix in the third eigenvector matrix is ​​the same as the row index of the x1 row element in the second reference matrix in the third reference matrix. For example, if x1 = 4, the row indices of the x1 row element in the second eigenvector matrix are 1, 2, 3, 4, and the row indices of the x1 row element in the second reference matrix are also 1, 2, 3, 4.

[0200] It is understood that this application does not exclude the following situation: the row indices of the x1 row elements in the second eigenvector matrix and the row indices of the x1 row elements in the second reference matrix are partially the same as and partially different from those in the first reference matrix. For example, if x1 = 4, the row indices of the x1 row elements in the second eigenvector matrix are 1, 2, 3, 4, and the row indices of the x1 row elements in the second reference matrix are 1, 2, 3, 5.

[0201] In Examples 1-2 and 1-3 above, the column indices of the x2 column elements in the second eigenvector matrix in the first eigenvector matrix are the same as the row and column indices of the x2 row and x2 column elements in the first eigenvalue matrix. That is, the column indices of the b-column elements removed from the first eigenvector matrix in the first eigenvector matrix are the same as the row and column indices of the b-row and b-column elements removed from the first eigenvalue matrix in the first eigenvalue matrix. For example, if x2 = 4, the column indices of the x2 column elements in the second eigenvector matrix are 1, 2, 3, and 4, and the row and column indices of the x2 row elements in the second reference matrix are both 1, 2, 3, and 4.

[0202] Correspondingly, the column index of the x2 column element in the second eigenvector matrix in the third eigenvector matrix is ​​the same as the row index and column index of the x2 row and x2 column element in the second eigenvalue matrix in the third eigenvalue matrix.

[0203] It is understood that this application does not exclude the following situation: the column indices of the x2 column elements in the second eigenvector matrix and the row and column indices of the x2 row and x2 column elements in the second eigenvalue matrix are partially the same and partially different. For example, if x2 = 4, the column indices of the x2 column elements in the second eigenvector matrix are 1, 2, 3, 4, and the row and column indices of the x2 row elements in the second reference matrix are 1, 2, 3, 5.

[0204] In Example 2 above, the row index of the x1 row element in the second reference matrix in the first reference matrix is ​​the same as the row and column indices of the x1 row and x1 column element in the second transformation matrix in the first transformation matrix. That is, the row index of the a-row element removed from the first reference matrix in the first reference matrix is ​​the same as the row and column indices of the a-row and a-column element removed from the first transformation matrix in the first transformation matrix.

[0205] Correspondingly, the row index of the x1 row element in the second reference matrix in the third reference matrix is ​​the same as the row index and column index of the x1 row and x1 column element in the second transformation matrix in the third transformation matrix.

[0206] It is understood that this application does not exclude the following situation: the row index of the x1 row element in the second reference matrix in the first reference matrix is ​​partially the same as and partially different from the row index and column index of the x1 row and x1 column in the second transformation matrix in the first transformation matrix.

[0207] The following describes several ways to determine the positions (row and / or column indices) of the elements retained in the M first matrices based on their modulus (i.e., priority):

[0208] The terminal device determines the positions of elements to be retained (or discarded) in the M first matrices based on their priorities, thereby determining the M second matrices (i.e., one possible implementation of step 502a). Higher priority elements are more likely to be retained, while lower priority elements are more likely to be discarded. One way to determine element priority is based on the element's modulus. The modulus and priority of an element are positively correlated: the larger the modulus, the higher the priority; the smaller the modulus, the lower the priority.

[0209] For example, the row index of the x1 row element in the second eigenvector matrix in the first eigenvector matrix and the row index of the x1 row element in the second reference matrix in the first reference matrix are related to the modulus (or priority) of each row element in the x1 row of the second reference matrix. In this implementation, the row elements to be retained (or discarded) in the first reference matrix and the first eigenvector matrix are determined based on the modulus (or priority) of each row element in the first reference matrix.

[0210] For example, the column index of the x2 column element in the second eigenvector matrix in the first eigenvector matrix, the row index and column index of the x2 row and x2 column element in the second eigenvalue matrix in the first eigenvalue matrix, and the modulus (or priority) of the element located on the diagonal in the second eigenvalue matrix are all related. In this implementation, based on the modulus (or priority) of the element located on the diagonal in the first eigenvalue matrix, the row and column elements to be retained (or discarded) in the first eigenvalue matrix, and the column elements to be retained (or discarded) in the first eigenvector matrix are determined.

[0211] For example, the row index of the x1 row element in the second reference matrix and the row and column indices of the x1 row and x1 column element in the second transformation matrix are related to the modulus (or priority) of each row element in the x1 row of the second reference matrix. In this implementation, based on the modulus (or priority) of each row element in the first reference matrix, the row elements to be retained (or discarded) in the first reference matrix, and the row and column elements to be retained (or discarded) in the first transformation matrix are determined.

[0212] The following provides a detailed introduction to different examples (Example 1-1, Example 1-2, Example 1-3):

[0213] In Example 1-1 above, the elements in row x1 of the first reference matrix are retained, while the elements in row a are discarded; similarly, the elements in row x1 of the first eigenvector matrix are retained, while the elements in row a are discarded. The terminal device determines the row index of the element in row x1 as follows:

[0214] Method 1a: Determine the row index of the x1 row element based on the modulus of each row element in the first reference matrix.

[0215] For example, the modulus of each element in the x1 row of the second reference matrix is ​​greater than or equal to the modulus of each element in the a row of the first reference matrix; the a row elements are the elements in the r row of the first reference matrix other than the x1 row elements of the second reference matrix.

[0216] For example, the terminal device determines the row index of the retained x1 row elements (or the row index of the discarded a row elements) in the first reference matrix based on the modulus of each row element in the first reference matrix, and then determines the second reference matrix. Additionally, the terminal device determines the second eigenvector matrix based on the row index of the x1 row elements of the second reference matrix in the first reference matrix, and the "positional relationship between the elements in the second eigenvector matrix and the second reference matrix" described earlier.

[0217] Method 1b: Determine the row index of the x1 row element based on the modulus of each row element in the first eigenvector matrix.

[0218] For example, the modulus of each element in the x1 row of the second eigenvector matrix is ​​greater than or equal to the modulus of each element in the a row of the first eigenvector matrix; the a row elements are the elements in the r row of the first eigenvector matrix other than the x1 row elements of the second eigenvector matrix.

[0219] For example, the terminal device determines the row index of the retained x1 row elements (or the row index of the discarded a row elements) in the first eigenvector matrix based on the modulus of each row element in the first eigenvector matrix, and then determines the second eigenvector matrix. Additionally, the terminal device determines the second reference matrix based on the row index of the x1 row elements of the second eigenvector matrix in the first eigenvector matrix and the "positional relationship between the elements in the second eigenvector matrix and the second reference matrix" described earlier.

[0220] In Examples 1-2 above, x2 elements are retained and b elements are discarded from the r columns of the first eigenvector matrix; x2 elements are retained and b elements are discarded from the r diagonal elements of the first eigenvalue matrix. The terminal device determines the column index of the x2 column element as follows:

[0221] Method 2a: Determine the column index of column x2 based on the modulus of each element located on the diagonal in the first eigenvalue matrix.

[0222] For example, the modulus of each element in the second eigenvalue matrix located on the diagonal is greater than or equal to the modulus of each element in the b-row b-column element of the first eigenvalue matrix located on the diagonal; the b-row b-column element is the element in the r-row r-column element of the first eigenvalue matrix other than the x2-row x2-column element of the second eigenvalue matrix.

[0223] For example, based on the modulus of each element located on the diagonal of the first eigenvalue matrix, the terminal device determines the row and column indices corresponding to the x2 elements retained on the diagonal (i.e., the row and column indices of the retained x2 rows and x2 columns, or the row and column indices of the discarded b rows and b columns), and then determines the second eigenvalue matrix. Additionally, the terminal device determines the second eigenvector matrix based on the row indices of the x2 rows of the second eigenvalue matrix in the first eigenvector matrix and the previously described "positional relationship between the elements in the second eigenvector matrix and the second eigenvalue matrix."

[0224] Method 2b: Determine the column index of the x2 column element based on the modulus of each column element in the first eigenvector matrix.

[0225] For example, the modulus of each element in the x2 column of the second eigenvector matrix is ​​greater than or equal to the modulus of each element in the b column of the first eigenvector matrix; the b column elements are the elements in the r column of the first eigenvector matrix other than the x2 column elements of the second eigenvector matrix.

[0226] For example, the terminal device determines the column index of the retained x2 columns (or the column index of the discarded b columns) of the first eigenvector matrix based on the modulus of each column element in the first eigenvector matrix, and then determines the second eigenvector matrix. Additionally, the terminal device determines the second eigenvalue matrix based on the column indices of the x2 columns of the second eigenvector matrix in the first eigenvector matrix and the previously described "positional relationship between the elements in the second eigenvector matrix and the second eigenvalue matrix".

[0227] In Examples 1-3 above, the first reference matrix retains row x1 elements and discards row a elements from its r rows; the first eigenvector matrix retains row x1 elements and discards row a elements from its r rows, retains column x2 elements from its r columns, and discards column b elements; the first eigenvalue matrix retains row x2 elements from its r diagonal positions and discards column b elements. The terminal device determines the row index of row x1 and the column index of column x2 as follows:

[0228] Based on the two methods for determining the row index of row element x1 (method 1a and method 1b) and the two methods for determining the column index of column element x2 (method 2a and method 2b) introduced earlier, in Example 1-3, there are four combinations for determining the row index of row element x1 and the column index of column element x2: method 1a and method 2a, method 1a and method 2b, method 1b and method 2a, and method 1b and method 2a. Additionally, there is one method: based on method 2a, determine the column index of column element x2, and set x2 = x1, so that the row index of row element x1 and the column index of column element x2 are the same.

[0229] In the combination of methods 1b and 2b, the terminal device determines the row index (or the row index of the discarded row a) of the retained x1 row elements in the first eigenvector matrix based on the modulus of each row element; and determines the column index (or the column index of the discarded column b) of the retained x2 column elements in the first eigenvector matrix based on the modulus of each column element, thereby determining the second eigenvector matrix. Furthermore, based on the row and column indices of the x1 row and x2 column elements of the second eigenvector matrix in the first eigenvector matrix, and the positional relationship of the elements in the second eigenvector matrix, the second eigenvalue matrix, and the second reference matrix described earlier, the second reference matrix and the second eigenvalue matrix are determined. The principle is similar in other methods and will not be elaborated further.

[0230] In Example 2 above, the first reference matrix retains row x1 elements and discards row a elements in its r-row elements; the first transformation matrix retains row x1 elements and discards row a elements in its r-row elements, and retains column x1 elements and discards column a elements in its r-column elements. The terminal device determines the row index of row x1 and the column index of column x1 as follows:

[0231] The terminal device determines the row index of the retained x1 row elements (or the row index of the discarded a row elements) in the first reference matrix based on the modulus of each row element in the first reference matrix, and then determines the second reference matrix. For example, the modulus of each row element in the x1 row of the second reference matrix is ​​greater than or equal to the modulus of each row element in the a row of the first reference matrix; the a row elements are the elements in the r rows of the first reference matrix excluding the x1 row elements of the second reference matrix. Furthermore, the second transformation matrix is ​​determined based on the row index of the x1 row elements of the second reference matrix in the first reference matrix and the "positional relationship between the elements in the second transformation matrix and the second reference matrix" described above.

[0232] The following describes possible implementations of the terminal device determining M second matrices (i.e., step 502a) and the network device determining M third matrices (i.e., step 503):

[0233] First, it should be noted that the "first resource" below can be the resource corresponding to one flow, in which case the "size of the resource" in the correspondence maintained by the terminal device and / or network device is the size of the resource corresponding to one flow; the "first resource" below can also be the resource corresponding to v flows, in which case the "size of the resource" in the correspondence maintained by the terminal device and / or network device is the size of the resource corresponding to v flows, where v is an integer greater than or equal to 1.

[0234] When a network device indicates the resources of v flows to a terminal device, the terminal device and the network device can determine the size of the resources corresponding to a flow based on the value of v, that is, divide the resources of the v flows into v parts to obtain the size of the resources corresponding to a flow.

[0235] Implementation 1: The terminal device determines the number of elements included in each of the M second matrices based on the size of the first resource, and then determines the M second matrices (a possible implementation of step 502a).

[0236] For example, a terminal device might maintain the correspondence between the size of a resource and the number of rows and columns in each of the M second matrices. Another example is the correspondence between the size of a resource and the value of x1 (x1 being the element in row x1 mentioned earlier); and / or, the correspondence between the size of a resource and the value of x2 (x2 being the element in column x2 mentioned earlier). These correspondences can be presented in tabular form or other formats.

[0237] After obtaining the size of the first resource, the terminal device can determine the number of rows and columns (or the specific values ​​of x1 and / or x2) of each second matrix based on the correspondence. Then, based on the M first matrices and the number of rows and columns (or the specific values ​​of x1 and / or x2) of each second matrix, the terminal device determines M second matrices. Optionally, the terminal device determines the M second matrices based on the priority (e.g., modulus) of the elements in the M first matrices and the number of rows and columns (or the specific values ​​of x1 and / or x2) of each second matrix.

[0238] Table 1 below illustrates the possible correspondence between the size of the resource, the value of x1, and the value of x2.

[0239] Table 1:

[0240] In all embodiments of this application, the size of a resource can be represented by the number of bits, or by the number of resource elements (REs) or resource blocks (RBs). B1, B2, B3, B4, B5, ..., increase sequentially.

[0241] In Table 1 above, and in all subsequent tables, the resource size (B1, B2, B3, B4, B5…) in any row represents the resource size required for the elements reserved in that row. For example, the elements in row 1 of the first reference matrix, row 1 of the first eigenvector matrix, and row 1 of the first eigenvalue matrix (or one element on the diagonal) require at least B1 resource transfers. Similarly, the elements in rows 2 of the first reference matrix, row 2 of the first eigenvector matrix, and row 1 of the first eigenvalue matrix (or one element on the diagonal) require at least B2 resource transfers.

[0242] Alternatively, the resources required for the elements held in that row are less than or equal to the resources in that row.

[0243] Alternatively, the amount of additional resources required to retain the elements in this row compared to the elements retained in the previous row. For example, if x1 is 2 and x2 is 1 (second row), compared to x1 being 1 and x2 being 1 (first row), the first reference matrix retains one more row of elements, and the first eigenvector matrix also retains one more row of elements. The amount of additional resources required to retain these extra elements is B2.

[0244] In all embodiments of this application, the size of the resource is positively correlated with the value of x1; and / or, the size of the resource is positively correlated with the value of x2. That is, the more resources there are, the larger the values ​​of x1 and / or x2.

[0245] Optionally, in Examples 1-3, the difference between x1 and x2 is less than a set threshold, for example, a threshold of 1, 2, or 3. This can be understood as follows: when the initial resource increases, x1 and x2 increase alternately; either x1 increases first, followed by x2, or x2 increases first, followed by x1. When x1 and x2 increase, they can either increase by adding 1 or by adding 2. In Table 1 above, x1 increases first, followed by x2, and both increases by adding 1.

[0246] After receiving information about M second matrices, the network device can determine M third matrices based on the information about the M second matrices and their positions (i.e., row indices and / or column indices) in the M first matrices (or third matrices) (a possible implementation of step 503).

[0247] The following describes how network devices determine the positions of M second matrices within M first matrices (or third matrices):

[0248] Method a: The terminal device indicates to the network device the positions of the M second matrices in the M first matrices.

[0249] For example, a terminal device sends indication information to a network device; correspondingly, the network device receives the indication information; the indication information indicates the row index and / or column index of each element in the M second matrices within the elements of the corresponding first matrix; or, the indication information indicates the row index of the x1 row element and / or the column index of the x2 column element. Based on this indication information, the network device determines the position of the M second matrices within the M first matrices.

[0250] For example, this instruction information can be carried in uplink control information (UCI).

[0251] Method b: The network device determines the positions of the M second matrices in the M first matrices.

[0252] When the terminal device determines M first matrices based on the reference signal (step 501), it can determine the M first matrices based on the compressed matrix and the reference signal. If the compressed matrix is ​​determined based on singular value decomposition, the modulus of the elements of the first reference matrix in the M first matrices shows a decreasing or increasing trend. That is, the priority of each row element in the first reference matrix decreases or increases sequentially. In the scenario where the row index of the x1 row element is determined based on the modulus of the elements in the first reference matrix (e.g., method 1a in Example 1-1, Example 1-3, and Example 2), the network device can determine the row index of the x1 row by knowing the value of x1, without the terminal device needing to indicate the row index of the x1 row to the network device, thus reducing signaling overhead. For example, if the priority of each row element in the first reference matrix decreases sequentially, then the value of x1 is 1 to x1; if the priority of each row element in the first reference matrix increases sequentially, then the value of x1 is r-x1+1 to r.

[0253] In the example (Example 1) of M first matrices including a first reference matrix, a first eigenvector matrix, and a first eigenvalue matrix, the first eigenvector matrix and the first eigenvalue matrix are obtained by eigenvalue decomposition of the first transformation matrix. Typically, the magnitudes of the diagonal elements in the first eigenvalue matrix tend to decrease or increase, meaning the priority of the diagonal elements in the first eigenvalue matrix decreases or increases sequentially. In scenarios where the column index of column x2 is determined based on the magnitude of the diagonal elements in the first eigenvalue matrix (e.g., method 2a in Example 1-2, Example 1-3), the network device can determine the column index of column x2 by knowing its value, eliminating the need for the terminal device to indicate the column index of column x2 to the network device, thus reducing signaling overhead. For example, if the priority of the diagonal elements in the first eigenvalue matrix decreases sequentially, then the value of x2 is 1 to x2; if the priority of the diagonal elements in the first eigenvalue matrix increases sequentially, then the value of x2 is r-x2+1 to r.

[0254] The network device learns the values ​​of x1 and x2 in the following way:

[0255] For example, a terminal device sends information about a second matrix to a network device, and the network device can determine the values ​​of x1 and / or x2 based on the information about the second matrix.

[0256] For example, a terminal device sends indication information to a network device. This indication information indicates the values ​​of x1 and / or x2; or, it indicates the number of rows and / or columns in each second matrix; or, it indicates the number of elements in each of the M second matrices. The network device, knowing the number of rows and columns in each first matrix, can calculate the number of rows and / or columns in each second matrix (or, the specific values ​​of x1 and / or x2) based on the number of elements in each matrix. For example, this indication information can be carried in uplink control information.

[0257] For example, a network device maintains the correspondence between the size of a resource and the number of rows and columns in each of the M second matrices. For another example, a network device maintains the correspondence between the size of a resource and the value of x1 (x1 being the element in row x1 mentioned earlier); and / or, the correspondence between the size of a resource and the value of x2 (x2 being the element in column x2 mentioned earlier). These correspondences can be represented in tabular form, such as Table 1, or other forms. Based on the size of the first resource and this correspondence, the network device can determine the number of rows and columns (or, the specific values ​​of x1 and / or x2) in each second matrix.

[0258] Implementation 2: The network device determines the number of elements in each of the M second matrices and instructs the terminal device accordingly.

[0259] For example, a network device might maintain the correspondence between the size of a resource and the number of rows and columns in each of the M second matrices. Another example is the correspondence between the size of a resource and the value of x1 (x1 being the element in row x1 mentioned earlier); and / or the correspondence between the size of a resource and the value of x2 (x2 being the element in column x2 mentioned earlier). These correspondences can be represented in tabular form or other formats. For example, a network device could maintain Table 1.

[0260] The network device can determine the number of rows and columns (or the specific values ​​of x1 and / or x2) of each second matrix based on the size of the first resource and the correspondence. Then, the network device sends indication information to the terminal device, which indicates the number of rows and columns (or the specific values ​​of x1 and / or x2) of each second matrix. The terminal device determines M second matrices based on M first matrices and the number of rows and columns (or the specific values ​​of x1 and / or x2) of each second matrix indicated by the indication information (one possible implementation of step 502a). Optionally, the terminal device determines M second matrices based on the priority (e.g., modulus) of the elements in the M first matrices and the number of rows and columns (or the specific values ​​of x1 and / or x2) of each second matrix indicated by the indication information (one possible implementation of step 502a).

[0261] For example, the indication information may include the number of rows and columns included in each second matrix (or, the specific values ​​of x1 and / or x2).

[0262] For example, the indication information includes first priority information (which can be understood as a sequence number / number / level), which is related to the number of elements in each of the M second matrices (or alternatively: the number of rows and / or columns, i.e., the value of x1 and / or the value of x2). Based on the first priority information, the terminal device can determine the number of elements in each of the M second matrices (or, the value of x1 and / or the value of x2).

[0263] The instruction information sent by the network device to the terminal device can be carried in radio resource control (RRC) signaling or downlink control information (DCI).

[0264] In terminal and network devices, maintain the correspondence between priority and the number of elements (or the values ​​of x1 and / or x2) in each of the M second matrices; this correspondence can be represented in tabular form or other forms. For example, Table 2 can be maintained in terminal and network devices.

[0265] Table 2 below illustrates the possible relationships between priority information, the value of x1, and the value of x2. Priorities decrease sequentially from 1 to 5.

[0266] Table 2:

[0267] In all embodiments of this application, the priority level is positively correlated with the value of x1; and / or, the priority level is positively correlated with the value of x2. That is, the higher the priority, the larger the values ​​of x1 and / or x2.

[0268] Optionally, in Examples 1-3, the difference between x1 and x2 is less than a set threshold, for example, a threshold of 1, 2, or 3. This can be understood as follows: as priority increases, x1 and x2 increase alternately; x1 can increase first, followed by x2, or vice versa. When x1 and x2 increase, they can either increase by adding 1 or by adding 2. In Table 2 above, x1 increases first, followed by x2, and both increases by adding 1.

[0269] Optionally, the first priority information is related to the size of the first resource used to transmit the M second matrices. The network device can maintain the correspondence between the resource size, priority information, and the number of rows and columns (or, the values ​​of x1 and / or x2) included in each of the M second matrices. For example, the network device can maintain Table 1 and Table 2, or a table combining Table 1 and Table 2.

[0270] The network device can determine the positions of the M second matrices in the M first matrices (or third matrices) by referring to methods a and b in implementation 1.

[0271] Implementation 3: The priority (e.g., modulus) of the elements in the M first matrices exhibits an increasing or decreasing trend, for example, as described in implementation method b of Implementation 1. When retaining (or discarding) elements in the matrix, discarding begins from the last row and last column, or from the first row and first column.

[0272] Terminal and network devices can maintain the following correspondence: the size of a resource and the positions (or, the row index of row x1 and the column index of column x2) of the M second matrices within the M first matrices. This correspondence can be represented in tabular form or other forms.

[0273] After the terminal device learns the size of the first resource, it can determine the position of the M second matrices in the M first matrices based on the correspondence (or the row index of row x1 and the column index of column x2), and then select the element at the corresponding position in the M first matrices to determine the M second matrices (a possible implementation of step 502a).

[0274] The network device can also determine the positions of the M second matrices in the M first matrices based on the size of the first resource and the correspondence (or the row index of row x1 and the column index of column x2), and then determine the M third matrices based on the M second matrices (a possible implementation of step 503).

[0275] There is no need for terminal devices and network devices to exchange location information, which can save signaling overhead.

[0276] Table 3 below illustrates the possible correspondence between: resource size, row index of row x1, and column index of column x2.

[0277] Table 3:

[0278] In Table 3 above, the row index of row x1 is added first, and then the column index of column x2 is added. In other examples, the column index of column x2 can also be added first, and then the row index of row x1 can be added.

[0279] Table 4 below illustrates the possible correspondences between the size of the resources and the positions of the M second matrices in the M first matrices.

[0280] Table 4:

[0281] It should be noted that the "element in row 1, column 1" in Table 4 above, and Tables 5, 7 and 8 below, includes the first element in row 1, or alternatively, the first element in column 1. "element in row 1-i, column 1" includes the first to the first element in column 1. "element in row 1, column 1-j" includes the first to the first element in row 1.

[0282] "Elements in rows 1-i and columns 1-j" includes: the first 1-i elements in column 1, the first 1-i elements in column 2, and so on, up to the first 1-i elements in column j. Alternatively, it can be described as including: the first 1-j elements in row 1, the first 1-j elements in row 2, and so on, up to the first 1-j elements in row i. For example, "Elements in rows 1-3 and columns 1-2" includes: the first 1-3 elements in column 1 and the first 1-3 elements in column 2; or alternatively, it includes: the first 1-2 elements in row 1, the first 1-2 elements in row 2, and the first 1-2 elements in row 3.

[0283] In all embodiments of this application, "row index of row x1, column index of column x2" and "position of M second matrices in M ​​first matrices" can be interchanged.

[0284] Table 5 below illustrates the possible correspondences between: the size of the resources and the positions of the M second matrices in the M first matrices.

[0285] Table 5

[0286] The positional information corresponding to B2 is further preserved compared to the positional information corresponding to B1; compared to the positional information corresponding to B1, the positional information corresponding to B2 retains one more row of elements in the first reference matrix and one more row of elements in the eigenvector matrix. The positional information corresponding to B3 is further preserved compared to the positional information corresponding to B2; compared to the positional information corresponding to B2, the positional information corresponding to B3 retains one more element on the diagonal of the first eigenvalue matrix and one more column of elements in the first eigenvector matrix.

[0287] In a table, the size of a resource is the amount of resources needed to increase the size of the elements retained in a certain row compared to the elements retained in the previous row. For example, if the second row retains one more row of elements in the first reference matrix and one more row of elements in the first eigenvector matrix compared to the first row, the additional resources required for these extra elements are B2. When the size of the first resource is B... max At that time, the terminal device and the network device can determine the nth row such that B1 + B2 + ... + B n ≤B max B1+B2+…+B n +B n+1 >B max The elements corresponding to the position information of all rows up to and including row n are retained. For example, if n = 3, then the elements corresponding to the position information of rows 1, 2, and 3 are retained.

[0288] Implementation 4: Terminal devices require no maintenance: The correspondence between the size of resources and the positions of the M second matrices in the M first matrices (or, the row index of row x1 and the column index of column x2).

[0289] The network device determines the positions of M second matrices within M first matrices (or, the row index of row x1 and the column index of column x2), and sends indication information to the terminal device. This indication information indicates the positions of the M second matrices within the M first matrices (or, the row index of row x1 and the column index of column x2). This implementation method reduces the complexity of the terminal device. This indication information can be carried in RRC signaling or DCI sent by the network device to the terminal device.

[0290] The method by which a network device determines the positions (or, the row index of row x1 and the column index of column x2) of M second matrices within M first matrices:

[0291] For example, network device maintenance involves the correspondence between the size of a resource and the positions (or, the row index of row x1 and the column index of column x2) of the M second matrices within the M first matrices. The network device can determine the positions (or, the row index of row x1 and the column index of column x2) of the M second matrices within the M first matrices based on the size of the first resource and this correspondence.

[0292] For example, before step 501, the network device sends a reference signal to the terminal device. The terminal device determines the information of the first matrix based on the reference signal and sends the information of the first matrix back to the network device. Based on the modulus of the elements of the previously received first matrix, the network device determines the position of the elements to be retained (or discarded), and then determines the position of the M second matrices in the M first matrices (or, the row index of row x1 and the column index of column x2).

[0293] The indication information indicates the position of the M second matrices within the M first matrices (or, the row index of row x1 and the column index of column x2) in the following way:

[0294] For example, the indication information may include: the position of the M second matrices in the M first matrices (or, the row index of row x1 and the column index of column x2).

[0295] For example, the indication information may include: first priority information (which can be understood as sequence number / number / level), which is related to the position of the M second matrices in the M first matrices (or, the row index of row x1 and the column index of column x2). Based on the first priority information, the terminal device can determine the position of the M second matrices in the M first matrices (or, the row index of row x1 and the column index of column x2).

[0296] In terminal and network devices, maintain the following correspondence between priorities and the positions of the M second matrices in the M first matrices (or, the row index of row x1 and the column index of column x2); this correspondence can be represented in tabular form or other forms. For example, terminal and network devices can maintain Table 6, Table 7, or Table 8.

[0297] Table 6 below illustrates the possible relationships between priority information, the value of x1, and the value of x2. Priorities decrease sequentially from 1 to 5.

[0298] Table 6:

[0299] Table 7 below illustrates the possible priorities, the possible values ​​of x1, and the corresponding relationships between the values ​​of x2. Priorities decrease sequentially from 1 to 5.

[0300] Table 7:

[0301] Table 8 below describes the possible information: priority information, and the correspondence between the positions of the M second matrices in the M first matrices.

[0302] Table 8:

[0303] Optionally, the first priority information is related to the size of the first resource used to transmit the M second matrices. The network device can maintain the correspondence between the resource size, priority information, and the positions of the M second matrices in the M first matrices (or, the row index of row x1, the column index of column x2). For example, the network device can maintain tables 3 and 6, or a combination of tables 3 and 6. Similarly, the network device can maintain tables 4 and 7, or a combination of tables 4 and 7. And finally, the network device can maintain tables 5 and 8, or a combination of tables 5 and 8.

[0304] When the size of the first resource is B max At that time, the network device can determine the nth row such that B1 + B2 + ... + B n ≤B max B1+B2+…+B n +B n+1 >B max The elements corresponding to the position information of the nth row and all preceding rows are retained. For example, if n=3, then the elements corresponding to the position information of the 1st, 2nd, and 3rd rows are retained. The network device sends the priority information corresponding to the nth row to the terminal device. Based on this priority information, the terminal device retains the elements at positions with a priority no lower than that priority (i.e., the position information of the row corresponding to that priority and all preceding rows).

[0305] In implementations 1 to 4 above, the correspondence or table maintained in the terminal device can be indicated to the terminal device by the network device or can be specified by the protocol.

[0306] In the embodiments of this application, the terminal device and the network device can be interchanged; that is, the network device executes the method executed by the terminal device in the above scheme, and the terminal device executes the method executed by the network device in the above scheme. It should be noted that, regarding the first resource, it is still the network device that instructs the terminal device, and there is no need to replace it with the terminal device instructing the network device.

[0307] It is understood that, in order to achieve the functions in the above embodiments, the terminal device and network device include hardware structures and / or software modules corresponding to perform each function. Those skilled in the art should readily recognize that, based on the units and method steps of the various examples described in conjunction with the embodiments disclosed in this application, this application can be implemented in hardware or a combination of hardware and computer software. Whether a function is executed by hardware or by computer software driving hardware depends on the specific application scenario and design constraints of the technical solution.

[0308] Figures 8 and 9 are schematic diagrams of possible communication devices provided in embodiments of this application. These communication devices can be used to implement the functions of the terminal devices and network devices in the above method embodiments, and thus can also achieve the beneficial effects of the above method embodiments.

[0309] As shown in Figure 8, the communication device 800 may include modules or units for implementing the methods described in the embodiments above. In one possible design, the communication device 800 includes a processing unit 810 and a transceiver unit 820. Optionally, the communication device 800 may further include a storage unit 830 for storing device program code and / or data.

[0310] The communication device 800 can be a terminal-side device in the above embodiments, such as a terminal device, a communication module in a terminal device, a circuit, chip, or chip system in a terminal device that is responsible for communication functions.

[0311] The transceiver unit 820 can perform the receiving and sending actions performed on the terminal side in the above method embodiments. The processing unit 810 can perform other actions performed on the terminal side in the above method embodiments besides the sending and receiving actions.

[0312] For example, the processing unit 810 is configured to: determine M first matrices based on the received reference signal; determine M first matrices based on the received reference signal, where M is an integer greater than 1; determine M second matrices, wherein the M second matrices correspond one-to-one with the M first matrices, and at least two of the M second matrices respectively include partial elements of the corresponding first matrices; the priority of the elements in the i-th second matrix is ​​not lower than the priority of the elements in the i-th first matrix; i iterates through integers from 1 to M; the transceiver unit 820 is configured to: send information about the M second matrices.

[0313] In one possible implementation, the transceiver unit 820 is further configured to: receive first information, the first information being used to indicate a first resource for transmitting the M second matrices; specifically, the transceiver unit 820 is configured to: transmit information of the M second matrices on the first resource; wherein the number of elements included in the M second matrices is less than or equal to the upper limit of the number of elements allowed to be transmitted on the first resource, or the number of bits corresponding to the elements included in the M second matrices is less than or equal to the upper limit of the number of bits allowed to be transmitted on the first resource.

[0314] In one possible implementation, the processing unit 810 is specifically configured to: determine the M first matrices based on the compression matrix and the received reference signal, wherein the compression matrix is ​​determined based on singular value decomposition.

[0315] In one possible implementation, the transceiver unit 820 is further configured to: receive third information, the third information being used to indicate the number of elements included in each of the M second matrices, and / or the row index and / or column index of the elements included in each of the M second matrices in the elements of the corresponding first matrix; the transceiver unit 820 is specifically configured to: send information of the M second matrices based on the third information.

[0316] The communication device 800 can be a network-side device in the above embodiments, such as a network device, a communication module in a network device, a circuit, chip, or chip system in a network device that is responsible for communication functions.

[0317] The transceiver unit 820 can perform the receiving and sending actions performed on the network side in the above method embodiments. The processing unit 810 can perform other actions performed on the network side in the above method embodiments besides the sending and receiving actions.

[0318] For example, the transceiver unit 820 is configured to: receive information from M second matrices, where M is an integer greater than 1; the processing unit 810 is configured to: determine M third matrices based on the information from the M second matrices; the M second matrices and the M third matrices correspond one-to-one; at least two of the M second matrices respectively include partial elements of the corresponding third matrices; the priority of the element in the i-th second matrix is ​​not lower than the priority of the element in the i-th third matrix; i iterates through integers from 1 to M; the M third matrices are used to determine the precoding matrix.

[0319] In one possible implementation, the transceiver unit 820 is further configured to: send first information, the first information being used to indicate a first resource for transmitting the M second matrices; the transceiver unit 820 is specifically configured to: receive information of the M second matrices on the first resource, wherein the number of elements included in the M second matrices is less than or equal to the upper limit of the number of elements allowed to be transmitted on the first resource, or the number of bits corresponding to the elements included in the M second matrices is less than or equal to the upper limit of the number of bits allowed to be transmitted on the first resource.

[0320] In one possible implementation, the transceiver unit 820 is further configured to: send third information; the third information is used to indicate the number of elements included in each of the M second matrices, and / or the row index and / or column index of the elements included in each of the M second matrices in the elements of the corresponding first matrix.

[0321] A more detailed description of the processing unit 810 and the transceiver unit 820 can be obtained directly from the relevant description in the method embodiment shown in Figure 5, and will not be repeated here.

[0322] It is understood that the division of units in the above-described device is merely a logical functional division. One function can correspond to one functional unit, or two or more functions can be integrated into one functional unit. In actual implementation, all or some units can be integrated onto a single physical entity, or distributed across different physical entities. Furthermore, the aforementioned functional units can be implemented in hardware, software, or a combination of both. Whether a function is executed in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for specific applications, but such implementations should not be considered beyond the scope of this application.

[0323] In one example, the functional unit in any of the above devices may be one or more integrated circuits configured to implement the above methods, such as: one or more application-specific integrated circuits (ASICs), or one or more central processing units (CPUs), one or more microcontroller units (MCUs), one or more digital signal processors (DSPs), or one or more field-programmable gate arrays (FPGAs), or a combination of at least two of these integrated circuit forms.

[0324] In one example, storage unit 830 may include random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, and / or registers, etc. Processing unit 810 can be implemented by a processor, and transceiver unit 820 can be implemented by a transceiver.

[0325] As shown in Figure 9, the communication device 900 includes a processor 910 and an interface circuit 920. The processor 910 and the interface circuit 920 are coupled to each other. It is understood that the interface circuit 920 can be a transceiver or an input / output interface. Optionally, the communication device 900 may also include a memory 930 for storing instructions executed by the processor 910, or storing input data required for the processor 910 to execute instructions, or storing data generated after the processor 910 executes instructions. Sometimes, the interface circuit 920 can also be understood as part of the processor 910, in which case the communication device 900 includes the processor 910.

[0326] When the communication device 900 is used to implement the above-mentioned terminal device and network device method, the processor 910 is used to implement the function of the above-mentioned processing unit 810, the interface circuit 920 is used to implement the function of the above-mentioned transceiver unit 820, and the memory 930 is used to implement the function of the above-mentioned storage unit 830.

[0327] When the aforementioned communication device is a chip applied to a terminal device, the terminal device chip implements the functions of the terminal device in the above method embodiments. The terminal device chip receives information from a network device, which can be understood as the information being first received by other modules (such as an RF module or antenna) in the terminal device, and then sent to the terminal device chip by these modules. The terminal device chip sends information to a network device, which can be understood as the information being first sent to other modules (such as an RF module or antenna) in the terminal device, and then sent to the network device by these modules.

[0328] When the aforementioned communication device is a chip applied to a network device, the network device chip implements the functions of the network device in the above method embodiments. The network device chip receives information from the terminal device, which can be understood as the information being first received by other modules (such as radio frequency modules or antennas) in the network device, and then sent to the network device chip by these modules. The network device chip sends information to the terminal device, which can be understood as the information being sent down to other modules (such as radio frequency modules or antennas) in the network device, and then sent to the terminal device by these modules. Here, the network device module can be the baseband chip of the network device, or a DU (Digital Unit) or other modules. The DU here can be a DU under the Open Radio Access Network (O-RAN) architecture.

[0329] In this application, entity A sends information to entity B, either directly or indirectly through other entities. Similarly, entity B receives information from entity A, either directly or indirectly through other entities. Entities A and B can be network devices or terminal devices, or modules within network devices or terminal devices. The sending and receiving of information can be between network devices and terminal devices, between two network devices (e.g., CU and DU), or between different modules within a single device (e.g., a terminal device chip and other modules within the terminal device, or a network device chip and other modules within the network device).

[0330] It is understood that the processor in the embodiments of this application can be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. A general-purpose processor can be a microprocessor or any conventional processor.

[0331] This application also provides a computer-readable storage medium storing a computer program that, when executed by a computer, enables the computer to perform the aforementioned communication method. Alternatively, the computer program includes instructions for implementing the aforementioned communication method.

[0332] This application also provides a computer program product, including: computer program code, which, when run on a computer, enables the computer to execute the communication method provided above.

[0333] This application also provides a communication system, which includes a terminal device and a network device for performing the above-described communication method.

[0334] The method steps in the embodiments of this application can be implemented in hardware or by a processor executing software instructions. The software instructions can consist of corresponding software modules, which can be stored in random access memory, flash memory, read-only memory, programmable read-only memory, erasable programmable read-only memory, electrically erasable programmable read-only memory, registers, hard disks, portable hard disks, compact disc read-only memory (CD-ROM), or any other form of storage medium known in the art. An exemplary storage medium is coupled to a processor, enabling the processor to read information from and write information to the storage medium. Of course, the storage medium can also be a component of the processor. The processor and storage medium can reside in an ASIC. Alternatively, the ASIC can reside in a base station or terminal. Of course, the processor and storage medium can also exist as discrete components in the base station or terminal.

[0335] In the above embodiments, implementation can be achieved entirely or partially through software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented entirely or partially in the form of a computer program product. The computer program product includes one or more computer programs or instructions. When the computer program or instructions are loaded and executed on a computer, the processes or functions described in the embodiments of this application are performed entirely or partially. The computer can be a general-purpose computer, a special-purpose computer, a computer network, a network device, a user equipment, or other programmable device. The computer program or instructions can be stored in a computer-readable storage medium or transferred from one computer-readable storage medium to another. For example, the computer program or instructions can be transferred from one website, computer, server, or data center to another website, computer, server, or data center via wired or wireless means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that integrates one or more available media. The available medium can be a magnetic medium, such as a floppy disk, hard disk, or magnetic tape; it can also be an optical medium, such as a digital video optical disc; or it can be a semiconductor medium, such as a solid-state drive. The computer-readable storage medium may be a volatile or non-volatile storage medium, or may include both types of storage media.

Claims

1. A communication method, characterized in that, include: Based on the received reference signal, M first matrices are determined, where M is an integer greater than 1; M second matrices are determined, each corresponding one-to-one with one of the M first matrices. At least two of the M second matrices include a portion of the elements of their respective first matrices. The priority of the elements in the i-th second matrix is ​​no lower than the priority of the elements in the i-th first matrix. The i-th matrix iterates through integers from 1 to M. The M second matrices are used to determine the precoding matrix. Send the information of the M second matrices.

2. The method as described in claim 1, characterized in that, The priority of an element is associated with the modulus of the element; or, the priority of a row of elements is associated with the modulus of the row of elements; or, the priority of a column of elements is associated with the modulus of the column of elements.

3. The method as described in claim 1 or 2, characterized in that, Also includes: Receive first information, the first information being used to indicate the first resource for transmitting the M second matrices; The transmission of information for M second matrices includes: Transmit the information of the M second matrices on the first resource; wherein the number of elements included in the M second matrices is less than or equal to the upper limit of the number of elements allowed to be transmitted on the first resource, or the number of bits corresponding to the elements included in the M second matrices is less than or equal to the upper limit of the number of bits allowed to be transmitted on the first resource.

4. The method according to any one of claims 1-3, characterized in that, The M first matrices include: a first eigenvector matrix, a first eigenvalue matrix, and a first reference matrix; the first eigenvalue matrix is ​​a diagonal matrix. The M second matrices include: a second eigenvector matrix, a second eigenvalue matrix, and a second reference matrix; wherein... The first eigenvector matrix includes r rows of elements, and the second eigenvector matrix includes x1 rows of elements; the second eigenvalue matrix is ​​the same as the first eigenvalue matrix; the first reference matrix includes r rows of elements, and the second reference matrix includes x1 rows of elements; where r is an integer greater than 1, and x1 is a positive integer less than r; or, The first eigenvector matrix includes r columns of elements, and the second eigenvector matrix includes x2 columns of elements; the first eigenvalue matrix includes r rows and r columns of elements, and the second eigenvalue matrix includes x2 rows and x2 columns of elements; where r is an integer greater than 1, and x2 is a positive integer less than r; the second reference matrix is ​​the same as the first reference matrix; or, The first eigenvector matrix includes r rows and r columns of elements, and the second eigenvector matrix includes x1 rows and x2 columns of elements; the first eigenvalue matrix includes r rows and r columns of elements, and the second eigenvalue matrix includes x2 rows and x2 columns of elements; the first reference matrix includes r rows of elements, and the second reference matrix includes x1 rows of elements; where r is an integer greater than 1, and x1 and x2 are both positive integers less than r.

5. The method as described in claim 4, characterized in that, The row index of the x1 row element in the second eigenvector matrix within the first eigenvector matrix is ​​the same as the row index of the x1 row element in the second reference matrix within the first reference matrix; and / or, The column index of the x2 column element in the second eigenvector matrix in the first eigenvector matrix is ​​the same as the row index and column index of the x2 row and x2 column element in the second eigenvalue matrix in the first eigenvalue matrix.

6. The method according to any one of claims 3-5, characterized in that, The difference between x1 and x2 is less than a set threshold.

7. The method according to any one of claims 3 to 6, wherein, The row index of the x1 row element in the second eigenvector matrix within the first eigenvector matrix and the row index of the x1 row element in the second reference matrix within the first reference matrix are related to the modulus of each row element in the x1 row of the second reference matrix; and / or, The column index of the x2 column element in the second eigenvector matrix in the first eigenvector matrix and the row index and column index of the x2 row and x2 column element in the second eigenvalue matrix in the first eigenvalue matrix are related to the modulus of the element located on the diagonal in the second eigenvalue matrix.

8. The method of any one of claims 1-3, wherein, The M first matrices include: a first reference matrix and a first transformation matrix; the first reference matrix includes r rows of elements, and the first transformation matrix includes r rows and r columns of elements. The M second matrices include: a second reference matrix and a second transformation matrix; the second reference matrix includes x1 row elements, and the second transformation matrix includes x1 row and x1 column elements; r is an integer greater than 1, and x1 is a positive integer less than r.

9. The method of claim 8, wherein, The row index of the x1 row element in the second reference matrix in the first reference matrix is ​​the same as the row index and column index of the x1 row and x1 column element in the second transformation matrix in the first transformation matrix.

10. The method of claim 8 or 9, wherein, The row index of the x1 row element in the second reference matrix and the row index and column index of the x1 row and x1 column element in the second transformation matrix are related to the modulus of each row element in the x1 row of the second reference matrix.

11. The method according to any one of claims 4 to 10, wherein, The modulus of each element in the x1 row of the second reference matrix is ​​greater than or equal to the modulus of each element in the a row of the first reference matrix; the a row elements are the elements in the r rows of the first reference matrix excluding the x1 row elements of the second reference matrix; wherein, the modulus of any row element is positively correlated with the priority of the row element, and a is a positive integer less than r.

12. The method of any one of claims 4-7, wherein, The modulus of the element located on the diagonal in the second eigenvalue matrix is ​​greater than or equal to the modulus of the element located on the diagonal in row b of the first eigenvalue matrix; the element in row b is the element in row r of the first eigenvalue matrix excluding the element in row x2 of the second eigenvalue matrix; wherein the modulus of the element is positively correlated with the priority of the element, and b is a positive integer less than r.

13. The method of any one of claims 4-12, wherein, The size of the first resource is positively correlated with x1; and / or the size of the first resource is positively correlated with x2; wherein the first resource is the resource for transmitting the M second matrices.

14. The method of any one of claims 4-13, wherein, Also includes: Send a second message, which indicates the row index of the x1 row element and / or the column index of the x2 column element.

15. The method of any one of claims 1-14, wherein, The determination of M first matrices based on the received reference signals includes: Based on the compression matrix and the received reference signal, the M first matrices are determined, wherein the compression matrix is ​​determined based on singular value decomposition.

16. The method of any one of claims 1-13, wherein, Also includes: Receive third information, the third information being used to indicate the number of elements included in each of the M second matrices, and / or the row index and / or column index of the elements included in each of the M second matrices in the elements of the corresponding first matrix; The sending of information about the M second matrices includes: Based on the third information, the information of the M second matrices is sent.

17. A communication method, characterized in that, include: Receive information from M second matrices, where M is an integer greater than 1; Based on the information of the M second matrices, M third matrices are determined; the M second matrices and the M third matrices correspond one-to-one; at least two of the M second matrices each include partial elements of the corresponding third matrices; The priority of the element in the i-th second matrix is ​​no lower than the priority of the element in the i-th third matrix; i traverses positive integers from 1 to M; the M third matrices are used to determine the precoding matrix.

18. The method as described in claim 17, characterized in that, The priority of an element is associated with the modulus of the element; or, the priority of a row of elements is associated with the modulus of the row of elements; or, the priority of a column of elements is associated with the modulus of the column of elements.

19. The method as described in claim 17 or 18, characterized in that, Also includes: Send a first message, the first message being used to indicate the transmission of a first resource of the M second matrices; The receipt of information from M second matrices includes: The information of the M second matrices is received on the first resource, wherein the number of elements included in the M second matrices is less than or equal to the upper limit of the number of elements allowed to be transmitted on the first resource, or the number of bits corresponding to the elements included in the M second matrices is less than or equal to the upper limit of the number of bits allowed to be transmitted on the first resource.

20. The method according to any one of claims 17-19, characterized in that, The M third matrices include: a third eigenvector matrix, a third eigenvalue matrix, and a third reference matrix; the third eigenvalue matrix is ​​a diagonal matrix. The M second matrices include: a second eigenvector matrix, a second eigenvalue matrix, and a second reference matrix; wherein... The third eigenvector matrix includes r rows of elements, and the second eigenvector matrix includes x1 rows of elements; the second eigenvalue matrix and the third eigenvalue matrix are the same; the third reference matrix includes r rows of elements, and the second reference matrix includes x1 rows of elements; where r is an integer greater than 1, and x1 is a positive integer less than r; or, The third eigenvector matrix includes r columns of elements, and the second eigenvector matrix includes x2 columns of elements; the third eigenvalue matrix includes r rows and r columns of elements, and the second eigenvalue matrix includes x2 rows and x2 columns of elements; where r is an integer greater than 1, and x2 is a positive integer less than r; the second reference matrix and the third reference matrix are the same; or, The third eigenvector matrix includes r rows and r columns of elements, and the second eigenvector matrix includes x1 rows and x2 columns of elements; the third eigenvalue matrix includes r rows and r columns of elements, and the second eigenvalue matrix includes x2 rows and x2 columns of elements; the third reference matrix includes r rows of elements, and the second reference matrix includes x1 rows of elements; where r is an integer greater than 1, and x1 and x2 are both positive integers less than r.

21. The method as described in claim 20, characterized in that, The row index of the x1 row element in the second eigenvector matrix in the third eigenvector matrix is ​​the same as the row index of the x1 row element in the second reference matrix in the third reference matrix; and / or, The column index of the x2 column element in the second eigenvector matrix in the third eigenvector matrix is ​​the same as the row index and column index of the x2 row and x2 column element in the second eigenvalue matrix in the third eigenvalue matrix.

22. The method as described in claim 20 or 21, characterized in that, The difference between x1 and x2 is less than a set threshold.

23. The method according to any one of claims 17-19, characterized in that, The M third matrices include: a third reference matrix and a third transformation matrix; the third reference matrix includes r rows of elements, and the third transformation matrix includes r rows and r columns of elements. The M second matrices include: a second reference matrix and a second transformation matrix; the second reference matrix includes x1 row elements, and the second transformation matrix includes x1 row and x1 column elements; r is an integer greater than 1, and x1 is a positive integer less than r.

24. The method as described in claim 23, characterized in that, The row index of the x1 row element in the second reference matrix in the third reference matrix is ​​the same as the row index and column index of the x1 row and x1 column element in the second transformation matrix in the third transformation matrix.

25. The method according to any one of claims 20-24, characterized in that, The size of the first resource is positively correlated with x1; and / or the size of the first resource is positively correlated with x2; wherein the first resource is the resource for transmitting the M second matrices.

26. The method according to any one of claims 20-25, characterized in that, Also includes: Receive second information, the second information being used to indicate the row index of the x1 row element and / or the column index of the x2 column element; The process of determining M third matrices based on the information from the M second matrices includes: Based on the second information and the information of the M second matrices, the M third matrices are determined.

27. The method according to any one of claims 17-26, characterized in that, Also includes: Send a third message; the third message is used to indicate the number of elements included in each of the M second matrices, and / or the row index and / or column index of the elements included in each of the M second matrices in the corresponding elements of the first matrix.

28. The method according to any one of claims 17-27, characterized in that, The elements in the third matrix, excluding the corresponding elements of the second matrix, are all 0.

29. A communication device, characterized in that, Includes modules for performing the method as described in any one of claims 1-16, or modules for performing the method as described in any one of claims 17-28.

30. A communication device, characterized in that, Including the processor; The processor is configured to execute some or all of the computer programs or instructions in the memory, and when the some or all of the computer programs or instructions are executed, to implement the method as described in any one of claims 1-16, or to implement the method as described in any one of claims 17-28.

31. The communication device as claimed in claim 30, characterized in that, Also includes: Memory; The memory is used to store computer programs or instructions, which, when some or all of the computer programs or instructions are run, enable the execution of the method as described in any one of claims 1-16 or the method as described in any one of claims 17-28.

32. A communication system, characterized in that, The communication system includes: a terminal device that performs the method as described in any one of claims 1-16 and a network device that performs the method as described in any one of claims 17-28.

33. A computer-readable storage medium, characterized in that, The storage medium stores a computer program or instructions, which, when executed by a communication device, implement the method as described in any one of claims 1-16 or the method as described in any one of claims 17-28.

34. A computer program product, characterized in that, The computer program product includes: computer instructions that, when executed on a computer, cause the method as described in any one of claims 1-16 to be implemented, or the method as described in any one of claims 17-28 to be implemented.

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