Codebook reporting method, and electronic apparatus and computer program product

Abstract

Provided in the embodiments of the present disclosure are a codebook reporting method, and an electronic apparatus and a computer program product. The method comprises: determining a basis vector of a codebook, wherein an index of the basis vector of the codebook comprises an index associated with the number of antenna ports and an index used for determining a phase offset; on the basis of the basis vector of the codebook and a channel measurement result, constructing a precoding matrix; and reporting a precoding matrix indicator (PMI) by means of the codebook. Accordingly, at least the problem in the related art of terminal throughput reduction caused by severe performance degradation resulting from PMI reporting using a DFT codebook in a near-field channel can be solved.

Description

Codebook reporting methods, electronic devices and computer program products

[0001] Cross-reference of related applications

[0002] This disclosure is based on and claims priority to Chinese Patent Application No. 2025103066329, filed on March 14, 2025, entitled “Codebook Reporting Method, Electronic Device and Computer Program Product”, and incorporates the entire contents of that patent application by reference. Technical Field

[0003] This disclosure relates to the field of communication technology, and more specifically, to a codebook reporting method, electronic device, and computer program product. Background Technology

[0004] In current 5G NR protocols, terminals use Discrete Fourier Transform (DFT) codebooks to report the Precoding Matrix Indicator (PMI). This codebook is designed for far-field channels, assuming that the signal is incident parallel to the antenna array (or transmitted from the antenna array) when the terminal is far from the base station. However, as the base station antenna array grows larger and the signal frequency increases, the near-field distance of the antenna array becomes increasingly greater. In scenarios where the terminal and base station are closer, such as indoor offices, stadiums, and shopping malls, Figure 1 illustrates the near-field and far-field signals in related technologies. As shown in Figure 1, the wireless signal can no longer be considered as being incident parallel to the antenna array. For near-field channels, using DFT codebooks for PMI reporting would cause severe performance degradation, resulting in a decrease in terminal throughput. Summary of the Invention

[0005] This disclosure provides a codebook reporting method, electronic device, and computer program product to at least solve the problem in the related art that using DFT codebooks for PMI reporting in near-field channels causes severe performance loss and reduces terminal throughput.

[0006] According to one embodiment of this disclosure, a codebook reporting method is provided, applied to a terminal, comprising: determining the basis vectors of the codebook, wherein the indexes of the basis vectors of the codebook include an index associated with the number of antenna ports and an index for determining phase offset; constructing a precoding matrix based on the basis vectors of the codebook and channel measurement results; and reporting the index PMI of the precoding matrix through the codebook.

[0007] According to one embodiment of this disclosure, a codebook reporting method is provided, applied to a base station, comprising: receiving an index PMI of a precoding matrix reported by a terminal; determining a precoding matrix based on the index PMI of the precoding matrix and the codebook, wherein the index of the basis vector of the codebook includes an index associated with the number of antenna ports and an index for determining phase offset.

[0008] According to yet another embodiment of this disclosure, a computer-readable storage medium is also provided, wherein a computer program is stored therein, wherein the computer program is configured to perform the steps in any of the above method embodiments when it is run.

[0009] According to yet another embodiment of this disclosure, an electronic device is also provided, including a memory and a processor, wherein the memory stores a computer program and the processor is configured to run the computer program to perform the steps in any of the above method embodiments.

[0010] According to yet another embodiment of this disclosure, a computer program product is also provided, including a computer program that, when executed by a processor, implements the steps in any of the above method embodiments. Attached Figure Description

[0011] Figure 1 is a schematic diagram of near-field and far-field signals in related technologies;

[0012] Figure 2 is a schematic diagram of the hardware structure of the mobile terminal operating in the embodiments of the method disclosed herein;

[0013] Figure 3 is a flowchart of a codebook reporting method according to an embodiment of the present disclosure;

[0014] Figure 4 is a flowchart of CSI-RS transmission and CSI reporting between the terminal and the base station in the related technology;

[0015] Figure 5 is a flowchart of a codebook reporting method according to an embodiment of the present disclosure. Detailed Implementation

[0016] The embodiments of this disclosure will be described in detail below with reference to the accompanying drawings and examples.

[0017] It should be noted that the terms "first," "second," etc., in the specification, claims, and drawings of this disclosure are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence.

[0018] The method embodiments provided in this disclosure can be executed in a mobile terminal, computer terminal, or similar computing device. Taking running on a mobile terminal as an example, FIG2 is a schematic diagram of the hardware structure of the mobile terminal running in the method embodiments of this disclosure. As shown in FIG2, the mobile terminal may include one or more (only one is shown in FIG2) processors 102 (processor 102 may include, but is not limited to, processing devices such as microprocessors MCUs or programmable logic devices FPGAs) and a memory 104 for storing data. The mobile terminal may also include a transmission device 106 for communication functions and an input / output device 108. Those skilled in the art will understand that the structure shown in FIG2 is only illustrative and does not limit the structure of the mobile terminal. For example, the mobile terminal may also include more or fewer components than shown in FIG2, or have a different configuration than shown in FIG2.

[0019] The memory 104 can be used to store computer programs, such as application software programs and modules, like the computer program corresponding to the codebook reporting method in this embodiment. The processor 102 executes various functional applications and data processing by running the computer program stored in the memory 104, thus implementing the above-described method. The memory 104 may include high-speed random access memory and non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 104 may further include memory remotely located relative to the processor 102, and these remote memories can be connected to the mobile terminal via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0020] The transmission device 106 is used to receive or send data via a network. Specific examples of the network described above may include a wireless network provided by the mobile terminal's communication provider. In one example, the transmission device 106 includes a Network Interface Controller (NIC), which can connect to other network devices via a base station to communicate with the Internet. In another example, the transmission device 106 may be a Radio Frequency (RF) module used for wireless communication with the Internet.

[0021] This embodiment provides a codebook reporting method running on the above-described mobile terminal or network architecture. Figure 3 is a flowchart of the codebook reporting method according to an embodiment of this disclosure. As shown in Figure 3, the method is applied to a terminal and includes the following steps:

[0022] In step S302, a base vector of the codebook is determined, wherein an index of the base vector of the codebook includes an index associated with the number of antenna ports and an index for determining a phase offset.

[0023] In step S304, a precoding matrix is constructed according to the base vector of the codebook and the channel measurement result.

[0024] In step S306, an index PMI of the precoding matrix is reported on the codebook.

[0025] Through the above steps S302 to S306, at least the problem that in the related art, the PMI reporting using the DFT codebook for the near-field channel causes serious performance loss and reduces the terminal throughput can be solved, the codebook index related to the phase offset is added in the base vector of the existing codebook, the reporting accuracy of the codebook is higher, and the throughput performance of the terminal can be further improved.

[0026] In a wireless communication system, the codebook reporting mechanism is a key link for feeding back channel state information (CSI) in multiple-input multiple-output (MIMO) technology, which allows a terminal (such as a mobile phone) to report the best precoding matrix to the base station to optimize data transmission. The index associated with the number of antenna ports included in the base vector index of the codebook is used to indicate the size and structure of the base vector in the codebook, to ensure that the precoding matrix matches the antenna configuration of the base station. The phase offset index is used to fine-tune the precoding matrix to adapt to the phase changes of the channel and improve the accuracy of data transmission. For example, when the base station is configured with 8 antenna ports, the terminal will select a base vector from the codebook containing 8 antenna ports and adjust the precoding matrix through an additional phase offset index to adapt to the current channel conditions. The present technical solution introduces indexes related to the number of antenna ports and the phase offset, realizes fine adjustment of the precoding matrix, solves the problem of insufficient flexibility of the traditional codebook reporting mechanism under different antenna configurations and channel environments, and improves the transmission efficiency and reliability of the wireless communication system. In practical applications, this method can dynamically adjust the precoding strategy according to the antenna configuration of the base station to adapt to changing channel environments, and provides strong support for high data rate and low latency communication requirements.

[0027] In the embodiments of the present disclosure, the phase offset refers to a square term included in each vector element in the base vector of the codebook. The introduction of the phase offset is essentially a fine tuning of the phase of the base vector of the codebook to optimize the matching degree of the precoding matrix to the actual channel. For example, if the elements in the base vector are in complex form, the phase offset can be realized by adjusting the phase angle of these complex numbers, to ensure that the precoding matrix can better adapt to the phase characteristics of the channel, thereby improving the performance of data transmission.

[0028] Furthermore, the phase shift value is related to at least one of the following: the aperture of the antenna array; the number of antenna ports; the signal center frequency; and the distance between the terminal and the base station. The phase shift value is not fixed but dynamically adjusted according to the actual communication environment. For example, the aperture of the antenna array (i.e., the physical distance between antennas) affects the magnitude of the phase shift because the propagation path length between different antennas varies, leading to phase changes. Increasing the signal center frequency also increases the phase shift because higher frequencies experience faster phase changes. Changes in the distance between the terminal and the base station, especially in high-speed mobile scenarios, can cause the Doppler effect, affecting the phase shift.

[0029] In one embodiment, the index of the codebook's basis vectors directly or indirectly indexes the codebook's basis vectors. A direct index means the index directly corresponds to a specific basis vector in the codebook, while an indirect index may determine the basis vector through an index mapping table. For example, a direct index might be a number that directly points to a specific basis vector in the codebook; while an indirect index might be a composite index that needs to be determined through a pre-agreed mapping rule between the base station and the terminal to determine the specific basis vector. This technical solution, through a flexible indexing mechanism, solves the problems of indexing efficiency and resource consumption caused by the large size of the codebook in massive MIMO systems, improving the flexibility and efficiency of codebook reporting.

[0030] If the PMI directly indexes the basis vectors of the codebook, the PMI uses the number of basis vectors in the horizontal and vertical dimensions as the index. Using an index associated with the number of antenna ports, the newly added codebook index i... 1,h The index that determines the phase offset is the base vector of the codebook. The index associated with the number of antenna ports includes the index of the base vector of the codebook oversampled in both the horizontal and vertical dimensions.

[0031] If the basis vectors of the PMI indirect index codebook determine an orthogonal basis set, and L basis vectors are determined in the orthogonal basis set, the PMI index orthogonal basis set and the L basis vectors are used for L-layer transmission.

[0032] In this embodiment of the disclosure, step S304 may further include: selecting at least one basis vector from the set of basis vectors in the codebook; and constructing a precoding matrix based on the at least one basis vector. The construction of the precoding matrix is ​​based on the basis vectors in the codebook and the channel state information measured by the terminal. For example, the terminal may measure the amplitude and phase information of the channel, and select the best-matching basis vector from the codebook based on this information, and then fine-tune it through phase offset indexing to construct the final precoding matrix.

[0033] In one embodiment, when the number of transmission layers in the precoding matrix is ​​no more than 4, each layer independently selects one basis vector and one polarization phase {+1,+j,-1,-j}, and the basis vectors selected by any two layers are orthogonal or the same. When the number of transmission layers is small, each layer can independently select its basis vector and polarization phase to adapt to different channel characteristics. For example, when the number of transmission layers is 2, the first layer may select basis vector A and polarization phase +1, while the second layer may select basis vector B and polarization phase -j. As long as A and B are orthogonal, independent transmission of the two layers of signals can be achieved, avoiding interference between signals.

[0034] In one embodiment, when any two layers select the same basis vector, the two layers achieve orthogonality of the precoding matrices by selecting polarization phases. When two layers select the same basis vector, orthogonality of the precoding matrices can be achieved by selecting different polarization phases, thereby avoiding interference between signals. For example, if both the first and second layers select basis vector A, the first layer can choose polarization phase +1, while the second layer can choose polarization phase +j. In this way, although the two layers use the same basis vector, orthogonal transmission is achieved through different polarization phases.

[0035] In another embodiment, when the number of transmission layers in the precoding matrix is ​​greater than 4, one basis vector and one set of polarization phases are independently selected for every two layers, either (1,-1) or (j,-j), and the basis vectors selected by the two layers are orthogonal to the basis vectors selected by any other two layers. At high transmission layers, to reduce resource consumption and complexity, multiple signal layers can be grouped, with each group of two layers independently selecting basis vectors and polarization phases. However, the basis vectors between different groups must remain orthogonal to avoid interference between signals. For example, when the number of transmission layers is 6, the signals can be divided into three groups, each selecting a different basis vector, while the two layers within a group achieve orthogonality by selecting polarization phases.

[0036] Furthermore, when the number of transmission layers in the precoding matrix is ​​greater than 4 and is odd, the additional layer independently selects one basis vector and an independent polarization phase {+1,+j,-1,-j}, and the selected basis vector is orthogonal to the basis vectors of other layers. When the number of transmission layers is odd and greater than 4, in addition to dividing the signal into even groups, there is another layer of signal that needs to be processed independently. For example, when the number of transmission layers is 7, the signal can be divided into three groups, each with two signal layers, and an independent signal layer. The independent layer selects basis vectors and polarization phases orthogonal to those of the other groups.

[0037] In one embodiment, when the number of transmission layers is greater than one, all layers use the same index to determine the additional phase offset. In multi-layer transmission, to simplify the complexity of feedback information, it can be specified that all transmission layers use the same additional phase offset index. For example, if the number of transmission layers is 6, then all 6 layers of signals will use the same phase offset index for fine-tuning when constructing the precoding matrix.

[0038] Optionally, the codebook only supports a number of antenna ports greater than or equal to X, where X is a positive integer. In certain antenna configurations, such as massive MIMO systems, the codebook may only be applicable to scenarios where the number of antenna ports is greater than or equal to a certain threshold X. For example, if X is set to 8, then the basis vectors and phase offset indices in the codebook will only be applicable to base station configurations with 8 or more antenna ports.

[0039] Figure 4 is a flowchart illustrating the CSI-RS transmission and CSI reporting process between the terminal and the base station in related technologies. As shown in Figure 4, before transmitting the Channel State Information-Reference Signal (CSI-RS), the base station first configures the terminal with higher layers, including parameters such as CSI-RS resources, transmission mode (periodic, semi-persistent, aperiodic, etc.), reporting quality, and codebook type. Subsequently, the base station transmits the CSI-RS, and the terminal performs measurements and reports the CSI. Currently, the format of the Type 1 codebook in 5G NR (codebookMode = 1, 1-layer) is shown in Table 1.

[0040] Table 1

[0041] Where N1 and N2 are the number of antenna ports in the horizontal and vertical dimensions, respectively, and P CSI-RS =2N1N2 represents the number of ports in CSI-RS, O1 and O2 represent the oversampling coefficients in the horizontal and vertical dimensions, respectively, i 1,1 i 1,2 i2 represents the PMI reported by the terminal. l,m ,u m ,and They are represented as follows:

[0042] In the existing 5G NR standard, the values ​​of N1 and N2, O1 and O2 are shown in Table 2.

[0043] Table 2

[0044] The codebook for CSI reporting proposed in this disclosure has higher reporting accuracy compared to existing 5G NR codebooks, which can further improve the throughput performance of the terminal. The specific solution is as follows:

[0045] 1. The basis vectors of the codebook.

[0046] Compared with existing 5G NR codebooks, the base vectors of the codebook in this embodiment have the following characteristics: an additional codebook index related to distance is added to the codebook structure; an additional phase offset is added to the base vectors of the codebook, and the phase offset includes the square of the vector element index, parameters related to the near-field distance of the antenna array, and a partitioning coefficient.

[0047] For example, the following are two forms of codebook basis vectors:

[0048] Type 1: Add 2 codebook indices.

[0049] h and v represent the codebook indices for horizontal and vertical distances, respectively, v l,m,h,v Codebook index, α v and α h Let represent the near-field coefficients in the horizontal and vertical dimensions, respectively, and denoted by d, the antenna spacing d in the horizontal and vertical dimensions of the antenna array, respectively. h d v The signal wavelength λ and the minimum distance r between the terminal and the base station. min Related. For example, α v and α h They are represented as follows:

[0050] Type2: Add 1 codebook index.

[0051] i 1,k This represents the base vector index of the additional codebook, with values ​​ranging from 0, 1, ..., N. k -1. α represents the near-field coefficient, which is related to the antenna spacing d of the antenna array, the signal wavelength λ, and the minimum distance r between the terminal and the base station. min Related. For example, α can be represented as:

[0052] 2. Codebook reporting structure.

[0053] The codebook has two different structures, and the reporting methods for the two structures are different.

[0054] Structure 1: The reporting structure of type 1 directly indexes the basis vectors. In this way, the PMI used to determine the basis vectors of the horizontal and vertical dimensions is directly indexed by the number of basis vectors in the horizontal and vertical dimensions.

[0055] Structure 2: Type 2 reporting structure, used for determining the basis vectors of the horizontal and vertical dimensions. The PMI first determines a set of orthogonal bases, and then determines the basis vectors from this set of orthogonal bases. In this case, the PMI used to determine the basis vectors is of two types: the first type is used to index a set of orthogonal bases i. 1,1 i 1,h i 1,v or i 1,k The second type is used to index the L basis vectors i in the orthogonal basis set. 1,2 , used for L-layer transmission.

[0056] The following uses a single-layer codebook as an example to describe the specific codebook forms of Structure 1 and Structure 2 respectively.

[0057] In structure 1, for codebook Type 1 (with two additional codebook indices), the basis vectors in the horizontal and vertical dimensions are respectively represented by i. 1,1 i 1,2 i 1,h i 1,v Represents the index of the basis vectors of different dimensions, where i 1,1 i 1,2 Let i be the base vector indices of the codebooks oversampled in the horizontal and vertical dimensions, respectively, with values ​​ranging from 0 to N1O1-1 and 0 to N2O2-1. 1,1 i 1,2 Indexing is done directly using the index of the basis vector. For Structure 1, with basis vector Type1, when only one codebook index is added (codebook), the codebook format is shown in Table 3.

[0058] Table 3

[0059] i 1,h and i 1,v These represent the base vector indices of the codebook for the additional horizontal and vertical dimensions, respectively, with values ​​ranging from 0, 1, ..., N. h -1 and 0,1,...,N v -1, N v and N h It is a positive integer greater than 1. For structure 1, the basis vector is Type2, and only one codebook index is added (codebook), the codebook form is shown in Table 4.

[0060] Table 4

[0061] In structure 2, for codebook Type1, i is also used. 1,1 i 1,2 i 1,h i 1,v And i2 to index the basis vector of the codebook, i1,h i 1,v The meanings of i2 and i2 are the same as in structure 1, i 1,1 i 1,2 Unlike structure 1. i 1,1 Used to determine an orthogonal basis from the O1*O2 orthogonal basis group, i 1,2 This is used to determine the L basis vectors under this orthogonal basis, which are used for transmission at different layers. Therefore, i 1,1 and i 1,2 The structure is as follows:

[0062] i 1,1 =[q1q2];

[0063] q1∈{0,1,...,O1-1};

[0064] q2∈{0,1,...,O2-1};

[0065] Where q1 and q2 represent the indices of the orthogonal basis set, and each orthogonal basis set has N1N2 orthogonal basis vectors. This represents the number of combinations of selecting L basis vectors from N1N2 basis vectors, i.e., i 1,2 We can determine L basis vectors in an orthogonal basis for multilayer transmission; for single-layer transmission, L = 1. Assume i 1,2 The horizontal and vertical indices of the determined L basis vectors are respectively... and This represents the index of the basis vectors at different levels. Then, the level indices of these L basis vectors... and vertical index They are represented as:

[0066] At this point, the single-layer Type1 codebook is shown in Table 5 (taking the base vector Type1 as an example):

[0067] Table 5

[0068] In Table 5, Replace with This is the codebook for Type 1, which will not be listed here.

[0069] With more ports and a larger antenna array, the terminal is more likely to appear in the near-field region of the antenna array. Therefore, the codebook will support more ports, which can be achieved in the following two ways:

[0070] Method 1: Not only does it support all antenna port configurations in Table 2, but it also supports 48 ports, 64 ports and 128 ports. The (N1,N2) and (O1,O2) configurations supported by the codebook are shown in Table 6.

[0071] Table 6

[0072] Method 2: The codebook only supports partial port configurations and can only be used when the number of antenna ports is greater than X. When X = 32, the codebook supports antenna ports 48, 64, and 128. The (N1, N2) and (O1, O2) configurations supported by the codebook are shown in Table 7 below.

[0073] Table 7

[0074] 3. Multi-layered codebook.

[0075] To ensure that different layers do not interfere with each other, the codewords of different layers need to be orthogonal. For multi-layer codebooks, there are two ways to select different layer basis vectors. The following describes two multi-layer codebooks using basis vector Type2 as an example.

[0076] Option 1: After determining the base vector of the strongest layer (with the best channel conditions), the base vectors of other layers are the same as, adjacent to, or near the base vector of the strongest layer, and are orthogonal to the code base vector of the strongest layer. In addition, the codebook indices related to the near field are the same for all layers (including 1-4 and 5-8).

[0077] In this approach, the codebook reporting structure adopts Structure 1, and the spacing between the horizontal and vertical PMI indices of the basis vectors of other layers and the basis vector of the strongest layer is an integer multiple of the horizontal and vertical oversampling coefficients. Below is an example of the codebook for Layer 2 transmission (taking Type 2 as an example). Examples of codebooks for layers 3, 4, 5, 7, and 8 are shown in Table 12-22. The codewords for Layer 2 are shown in Table 8.

[0078] Table 8

[0079] In Table 8, during two-layer transmission, the basis vector of the first layer is v. l,m,k The basis vector of the second layer is v l′,m′,k Where l′=l+k1, m′=m+k2, k1 is an integer multiple of O1, and k2 is an integer multiple of O2. Assume the codebook uses i... 1,3 To determine the values ​​of k1 and k, i 1,3 The mapping relationship with k1 and k2 is shown in Table 9.

[0080] Table 9

[0081] Option 2:

[0082] When transmitting at layers 1-4, the following characteristics are present:

[0083] Each layer independently selects one basis vector from the orthogonal basis set, and each layer independently selects the polarization phase {+1,+j,-1,-j};

[0084] At most two layers can select the same basis vector, and when two layers select the same basis vector, the codewords of the two layers need to be orthogonal through polarization phase.

[0085] When transmitting at layers 5-8, the following characteristics exist:

[0086] Each two layers share a common basis vector, meaning a total of [number] base vectors are needed. N1N2 basis vectors are selected independently from the orthogonal N1N2 basis vectors. Indicates rounding up;

[0087] If the number of layers is odd, the extra basis vector is used for the extra layer (the third layer for 5 layers, the fifth layer for 7 layers);

[0088] The polarization phases of two layers using the same basis vector are paired, divided into two pairs {(1,-1),(j,-j)}. However, the polarization phase of the extra layer (the third layer in 5 layers, the fifth layer in 7 layers) is not subject to this restriction and is the same as that of layers 1-4.

[0089] Furthermore, all layers (including 1-4 and 5-8) have the same codebook index related to the near field.

[0090] For option 2, the codebook reporting structure adopts structure 2. Below are two examples of multi-layer codebooks, one with 2 layers and the other with 5 layers. For structure 2, the basis vector is Type 1, and the 2-layer codebook is shown in Table 10.

[0091] Table 10

[0092] In Table 10, This represents the polarization phase of the i-th layer, with values ​​ranging from {+1,+j,-1,-j}. When two layers select the same basis vector, in order to ensure that the codewords of different layers are orthogonal, the polarization phases of the two layers are selected in groups. For structure 2, the basis vector is Type1, and the 5-layer codebook is shown in Table 11.

[0093] Table 11

[0094] As can be seen in Table 11, layers 1 and 2 and layers 4 and 5 share the same basis vector, while layer 3 uses its own basis vector. and This represents a pair of polarization phases used by two layers that share the same basis vector, i.e. The value of can be {(1,-1),(j,-j)}.

[0095] 1) Examples of codebooks with 3, 4, 5, 6, 7, and 8 layers when structure 1 and option 1 are used (taking Type 2 as an example).

[0096] For structure 1, option 1, and type 1, the near field codebook for 3-layer is shown in Table 12.

[0097] Table 12

[0098] For structure 1, option 1, type 1, near field codebook for 4-layer, see Table 13.

[0099] Table 13

[0100] For structure 1, option 1, and type 1, the near field codebook for 5-layer is shown in Table 14.

[0101] Table 14

[0102] For structure 1, option 1, type 1, near field codebook for 6-layer, see Table 15.

[0103] Table 15

[0104] For structure 1, option 1, type 1, near field codebook for 7-layer, see Table 16.

[0105] Table 16

[0106] For structure 1, option 1, type 1, near field codebook for 8-layer, see Table 17.

[0107] Table 17

[0108] 2) Examples of codebooks for structure 2, option 2, with layers 3, 4, 6, 7, and 8 (taking base vector Type2 as an example).

[0109] For structure 2, the basis vectors Type2 and Type1 near the field codebook for 3-layer are shown in Table 18.

[0110] Table 18

[0111] For structure 2, the basis vectors Type2 and Type1 near the field codebook for 4-layer are shown in Table 19.

[0112] Table 19

[0113] For structure 2, the basis vectors Type2 and Type1 near the field codebook for 6-layer are shown in Table 20.

[0114] Table 20

[0115] For structure 2, the basis vectors Type2 and Type1 near the field codebook for 7-layer are shown in Table 21.

[0116] Table 21

[0117] For structure 2, the basis vectors Type2 and Type1 near the field codebook for 8-layer are shown in Table 22.

[0118] Table 22

[0119] This disclosure also provides a codebook reporting method. Figure 5 is a flowchart of a codebook reporting method according to an embodiment of this disclosure. As shown in Figure 5, the method is applied to a base station and includes the following steps:

[0120] Step S502: Receive the index PMI of the precoding matrix reported by the terminal;

[0121] Step S504: Determine the precoding matrix based on the index PMI of the precoding matrix and the codebook, wherein the index of the basis vector of the codebook includes an index associated with the number of antenna ports and an index used to determine the phase offset.

[0122] In the codebook-based precoding matrix feedback mechanism, the base station reconstructs the precoding matrix for data transmission based on the PMI (precoding matrix indicator) reported by the user equipment (terminal) and a specific codebook structure.

[0123] For a single-layer Type 1 codebook, assuming the terminal reports CSI in an indoor environment, the base station is configured with codebook structure 1, i.e., the form of direct indexed basis vectors. The terminal measures the channel state and selects the corresponding basis vector indices based on near-field characteristics, including indices associated with the number of antenna ports and indices used to determine phase offset. After receiving the PMI, the base station identifies the indices associated with the number of antenna ports. As shown in Table 3 or 4, the base station can parse the terminal-reported indices and the indices that are associated with the oversampled codebook basis vectors in the horizontal and vertical dimensions, respectively. Then, the phase offset indices are determined, and the base station further parses the indices and the indices that are included in the phase offset formula, which are related to the minimum distance between the terminal and the base station. Finally, the precoding matrix is ​​reconstructed. The base station selects the correct basis vectors based on the parsed indices and applies the corresponding phase offset to reconstruct the precoding matrix.

[0124] For Type 1 codebook Option 1 in multi-layer transmission scenarios, the base station configures Option 1 of the codebook, meaning that the basis vectors of each layer maintain a certain distance and orthogonality from the strongest layer's basis vector. For example, in 2-layer transmission, after receiving the PMI reported by the terminal, the base station determines the strongest layer's basis vector. The base station determines the first layer's basis vector based on the reported PMI and PMI. It selects orthogonal or nearby basis vectors and selects the second layer's basis vector based on its relative position to the first layer's basis vector. As shown in Table 9, the values ​​of PMI and PMI depend on the correlation between PMI and PMI. Phase offset is adjusted by applying a phase offset related to the antenna array's near-field distance to the selected basis vectors to ensure orthogonality between different layers.

[0125] For the Type 1 codebook Option 2 of multi-layer transmission, the base station configures a codebook with multiple layers of independently selected basis vectors and polarization phases. For example, 5-layer transmission:

[0126] Independent selection of basis vectors: The base station determines the basis vectors for each layer based on the PMI reported by the terminal, as shown in Table 11.

[0127] Independent polarization phase selection: For layers 1-4, each layer independently selects its polarization phase {+1,+j,-1,-j}; for layers 5-8, every two layers share a basis vector, but use paired polarization phases {(1,-1),(j,-j)} to ensure orthogonality between different layers.

[0128] Handling layers with shared basis vectors: If two layers use the same basis vectors, the base station will check whether the polarization phase reported by the terminal meets the orthogonality requirement.

[0129] Through the above embodiments, the base station can select an appropriate precoding matrix based on the PMI reported by the terminal and the configured codebook structure, thereby improving the performance of wireless communication in near-field environments. These embodiments highlight the innovation of the codebook in handling near-field effects of antenna arrays and maintaining multilayer transmission orthogonality.

[0130] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods according to the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solutions of the embodiments of this disclosure, or the parts that contribute to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods described in the various embodiments of this disclosure.

[0131] This embodiment also provides a codebook reporting device, which is used to implement the above embodiments and preferred embodiments; details already described will not be repeated. As used below, the term "module" can be a combination of software and / or hardware that implements a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated. Applied to a terminal, the device includes:

[0132] The first determining module is configured to determine the basis vectors of the codebook, wherein the indexes of the basis vectors of the codebook include an index associated with the number of antenna ports and an index for determining the phase offset;

[0133] The construction module is configured to construct a precoding matrix based on the basis vectors of the codebook and the channel measurement results;

[0134] The reporting module is configured to report the index PMI of the precoding matrix through the codebook.

[0135] This embodiment also provides a codebook reporting device applied to a base station, the device comprising:

[0136] The receiving module is configured to receive the index PMI of the precoding matrix reported by the terminal;

[0137] The second determining module is configured to determine the precoding matrix based on the index PMI of the precoding matrix and the codebook, wherein the index of the basis vector of the codebook includes an index associated with the number of antenna ports and an index used to determine the phase offset.

[0138] It should be noted that the above modules can be implemented by software or hardware. For the latter, they can be implemented in the following ways, but are not limited to: all the above modules are located in the same processor; or, the above modules are located in different processors in any combination.

[0139] Embodiments of this disclosure also provide a computer-readable storage medium storing a computer program configured to perform the steps in any of the above method embodiments when executed.

[0140] In one exemplary embodiment, the aforementioned computer-readable storage medium may include, but is not limited to, various media capable of storing computer programs, such as a USB flash drive, read-only memory (ROM), random access memory (RAM), portable hard drive, magnetic disk, or optical disk.

[0141] Embodiments of this disclosure also provide an electronic device including a memory and a processor, the memory storing a computer program and the processor being configured to run the computer program to perform the steps in any of the above method embodiments.

[0142] In one exemplary embodiment, the electronic device may further include a transmission device and an input / output device, wherein the transmission device is connected to the processor and the input / output device is connected to the processor.

[0143] Specific examples in this embodiment can be found in the examples described in the above embodiments and exemplary implementations, and will not be repeated here.

[0144] It is obvious to those skilled in the art that the modules or steps of this disclosure described above can be implemented using general-purpose computing devices. They can be centralized on a single computing device or distributed across a network of multiple computing devices. They can be implemented using computer-executable program code, and thus can be stored in a storage device for execution by a computing device. In some cases, the steps shown or described can be performed in a different order than those presented herein, or they can be fabricated as separate integrated circuit modules, or multiple modules or steps can be fabricated as a single integrated circuit module. Thus, this disclosure is not limited to any particular combination of hardware and software.

[0145] The above description is merely a preferred embodiment of this disclosure and is not intended to limit this disclosure. Various modifications and variations can be made to this disclosure by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the principles of this disclosure should be included within the scope of protection of this disclosure.

Claims

1. A codebook reporting method, applied to a terminal, comprising: Determine the basis vectors of the codebook, wherein the indices of the basis vectors of the codebook include an index associated with the number of antenna ports and an index for determining the phase offset; Construct a precoding matrix based on the basis vectors of the codebook and the channel measurement results; The index PMI of the precoding matrix is ​​reported through the codebook.

2. The method according to claim 1, wherein, The phase offset refers to the squared term contained in each vector element of the codebook's basis vectors.

3. The method according to claim 1, wherein, The value of the phase offset is related to at least one of the following: The aperture of the antenna array; Number of antenna ports; Signal center frequency; The distance between the terminal and the base station.

4. The method according to claim 1, wherein, The indexes of the base vectors of the codebook directly or indirectly index the base vectors of the codebook.

5. The method according to claim 1, wherein, Constructing the precoding matrix based on the basis vectors of the codebook and channel measurement results includes: Select at least one basis vector from the set of basis vectors of the codebook; The precoding matrix is ​​constructed based on at least one basis vector.

6. The method according to claim 1, wherein, When the number of transmission layers of the precoding matrix is ​​no more than 4, each layer independently selects 1 basis vector and 1 polarization phase {+1,+j,-1,-j}, and the basis vectors selected by any two layers are orthogonal or the same.

7. The method according to claim 6, wherein, When any two layers choose the same basis vector, the two layers make the precoding matrices orthogonal by choosing polarization phase.

8. The method according to claim 1, wherein, When the number of transmission layers of the precoding matrix is ​​greater than 4, one basis vector and one set of polarization phases are independently selected for every two layers, (1,-1) or (j,-j), and the basis vectors selected by the two layers are orthogonal to the basis vectors selected by any other two layers.

9. The method according to claim 8, wherein, When the number of transmission layers of the precoding matrix is ​​greater than 4 and is odd, the extra layer independently selects one basis vector and independently selects a polarization phase {+1,+j,-1,-j}, and the selected basis vector is orthogonal to the basis vectors of other layers.

10. The method according to claim 1, wherein, When the number of transport layers is greater than 1, all layers use the same index to determine the additional phase offset.

11. The method according to any one of claims 1 to 10, wherein, The codebook only supports a number of antenna ports greater than or equal to X, where X is a positive integer.

12. A codebook reporting method, applied to a base station, comprising: Receive the index PMI of the precoding matrix reported by the client; The precoding matrix is ​​determined based on the index PMI of the precoding matrix and the codebook, wherein the indexes of the basis vectors of the codebook include an index associated with the number of antenna ports and an index for determining the phase offset.

13. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the computer program, performs the steps of the method according to any one of claims 1 to 11, 12.

14. A computer program product comprising a computer program that, when executed by a processor, implements the steps of the method described in any one of claims 1 to 11 and 12.

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