Downlink precoding method, apparatus, device, and storage medium

Abstract

Embodiments of the present application disclose a downlink precoding method, device, equipment and storage medium. An uplink channel estimation sample is obtained according to an uplink reference signal; a beam energy matrix is determined based on the uplink channel estimation sample; and a downlink precoding matrix is determined based on the beam energy matrix. The downlink precoding method provided by the embodiments of the present application first determines the beam energy matrix based on the uplink channel estimation sample, and then determines the downlink precoding matrix based on the beam energy matrix. The system time-frequency resource overhead can be reduced, and the problems of decoding error on the user equipment side and system performance decline caused by directly using the uplink channel estimation result for downlink precoding can be avoided.

Description

Downlink precoding method, apparatus, equipment and storage medium Technical Field

[0001] The embodiments of the present invention relate to the field of communication technology, and in particular to a downlink precoding method, apparatus, device and storage medium. Background Technology

[0002] Massive Multiple-Input Multiple-Output (MIMO) technology is one of the key technologies in wireless communication systems. Compared to traditional MIMO, massive MIMO equips the base station with a large number of antennas. The narrow beam of the massive antenna array reduces signal leakage, resulting in higher spectral and energy efficiency. The key to gain in massive MIMO technology is spatial multiplexing. By serving multiple user equipment on the same time-frequency resources, multiplexing gain is achieved, which is crucial for increasing the capacity of wireless networks. Obtaining the multiplexing gain in massive MIMO requires precoding design based on downlink channel information; therefore, a high-performance precoding design method is of great significance to wireless communication systems.

[0003] In Time Division Duplex (TDD) systems, uplink and downlink transmissions use the same frequency band, and the channel is reciprocal, allowing for direct downlink precoding design based on uplink channel estimation results. However, in Frequency Division Duplex (FDD) systems, uplink and downlink transmissions use different frequency bands, and the channel is not reciprocal. Directly using uplink channel estimation results for downlink precoding design can cause the base station's transmit beam to deviate from the user equipment's (UE), resulting in the UE's inability to correctly decode the received signal and severely impacting system performance. Therefore, in FDD systems, accurate downlink channel information is required first for precoding design, followed by downlink precoding design based on this information.

[0004] Traditional downlink precoding schemes involve the base station first sending a pilot sequence to the user equipment (UE). Upon receiving the downlink pilot signal, the UE performs channel estimation to obtain downlink channel state information (CSI), which is then fed back to the base station via the uplink channel. Finally, the base station designs its precoding based on the fed-back CSI. In this scheme, the overhead of the pilot sequence sent by the base station and the time-frequency resource overhead fed back by the UE increases proportionally with the number of base station antennas. When the base station is equipped with hundreds or thousands of antennas, the overhead of this scheme is enormous. Summary of the Invention

[0005] This invention provides a downlink precoding method, apparatus, device, and storage medium, which can greatly reduce the time-frequency resource overhead of downlink precoding and avoid user equipment decoding errors and system performance degradation caused by directly using uplink channel estimation results for downlink precoding.

[0006] In a first aspect, embodiments of the present invention provide a downlink precoding method, the method being executed by a base station, the method comprising:

[0007] Obtain uplink channel estimation samples based on uplink reference signals;

[0008] The beam domain energy matrix is ​​determined based on the uplink channel estimation samples.

[0009] The downlink precoding matrix is ​​determined based on the beam domain energy matrix.

[0010] Secondly, embodiments of the present invention also provide a downlink precoding apparatus, the apparatus being disposed in a base station, the apparatus comprising:

[0011] The uplink channel estimation sample acquisition module is used to acquire uplink channel estimation samples based on the uplink reference signal;

[0012] A beam domain energy matrix determination module is used to determine the beam domain energy matrix based on the uplink channel estimation samples;

[0013] The precoding matrix determination module is used to determine the downlink precoding matrix based on the beam domain energy matrix.

[0014] Thirdly, embodiments of the present invention also provide an electronic device, the electronic device comprising:

[0015] At least one processor; and

[0016] A memory communicatively connected to the at least one processor; wherein,

[0017] The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the downlink precoding method described in the embodiments of the present invention.

[0018] Fourthly, embodiments of the present invention also provide a computer-readable storage medium storing computer instructions that are used to cause a processor to execute the downlink precoding method described in the embodiments of the present invention.

[0019] This invention discloses a downlink precoding method, apparatus, device, and storage medium. The method involves obtaining uplink channel estimation samples based on an uplink reference signal; determining a beam domain energy matrix based on the uplink channel estimation samples; and determining a downlink precoding matrix based on the beam domain energy matrix. The downlink precoding method provided by this invention first determines the beam domain energy matrix based on the uplink channel estimation samples, and then determines the downlink precoding matrix based on the beam domain energy matrix. This can reduce system time-frequency resource overhead and avoid decoding errors on the user equipment side and system performance degradation caused by directly using the uplink channel estimation results for downlink precoding. Attached Figure Description

[0020] Figure 1 shows a model of a multi-user large-scale communication system in the prior art;

[0021] Figure 2 is a flowchart of a downlink precoding method according to Embodiment 1 of the present invention;

[0022] Figure 3 is a diagram showing the effect of a downlink precoding method according to Embodiment 1 of the present invention;

[0023] Figure 4 is a schematic diagram of a downlink precoding device according to Embodiment 2 of the present invention;

[0024] Figure 5 is a schematic diagram of the structure of an electronic device according to Embodiment 3 of the present invention. Detailed Implementation

[0025] The present invention will now be described in further detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and not intended to limit it. Furthermore, it should be noted that, for ease of description, the accompanying drawings show only the parts relevant to the present invention, and not all of the structures.

[0026] Figure 1 shows a multi-user large-scale communication system model. In the FDD scenario, the base station side is configured with a large-scale uniform planar array (UPA), totaling M t =M z M x Root transmitting antenna, of which M z M x Let be the number of antennas in the vertical and horizontal directions, respectively, with a row and column spacing of d. On the base station side, let the azimuth angle be φ, the polar angle be θ, u = cosθ represent the direction cosine of the horizontal antenna array about UPA, and v = sinθcosφ represent the direction cosine of the vertical antenna array about UPA. Let c represent the speed of light, and let the uplink carrier frequency be f. up The uplink steering vector on the base station side can be expressed as the Kronecker product between the horizontal uplink steering vector and the vertical uplink steering vector: in, This is the upward guiding vector in the horizontal direction. Let θ be the uplink steering vector in the vertical direction, where Θ = -j2πd / c, and T denotes transpose. Similarly, let the downlink carrier frequency be f. d The downlink steering vector on the base station side can be expressed as the Kronecker product between the horizontal downlink steering vector and the vertical downlink steering vector: in, This is the horizontal downward steering vector. This is the downward guiding vector in the vertical direction.

[0027] In addition to the base station, the system also includes N single-antenna user equipment. Assume the base station performs channel estimation based on the uplink reference signal and obtains uplink channel estimation samples from the N user equipments. in, The K uplink channel estimation samples for user equipment n are represented by a matrix. yes The k-th row represents the estimated uplink channel value for user equipment n. For the downlink channel, consider N user equipments transmitting signals on the same subcarrier of the same symbol in the time-frequency resource block, where the signal transmitted by the base station to user equipment n on that symbol and subcarrier is x. n Then the received signal of user equipment n on that symbol and that subcarrier can be expressed as: in It is the downlink channel from the base station to user equipment n. It is the precoding matrix of user equipment n. It is interference from other N-1 user equipments to user equipment n. It is the precoding matrix of user equipment l, z n It is Gaussian noise introduced during the signal transmission process of user equipment n.

[0028] Example 1

[0029] Figure 2 is a flowchart of a downlink precoding method provided in Embodiment 1 of the present invention. This embodiment is applicable to the case of determining the downlink precoding matrix. This method can be executed by a downlink precoding device located in a base station. As shown in Figure 2, the method specifically includes the following steps:

[0030] S110, obtain uplink channel estimation samples based on uplink reference signals.

[0031] The uplink reference signal can be understood as the reference signal transmitted by each user equipment in the system to the base station through the uplink channel. The uplink channel estimation sample can be understood as the channel estimation value at different time-frequency resource locations. In this embodiment, channel estimation is performed based on the uplink reference signal to obtain the uplink channel estimation samples of multiple access user equipments, which can be expressed as: Obtaining uplink channel estimation samples based on uplink reference signals can be achieved using existing communication technologies and methods, which are not limited here.

[0032] S120, determine the beam domain energy matrix based on uplink channel estimation samples.

[0033] The beam domain energy matrix is ​​composed of the energy of each user equipment in each beam.

[0034] Optionally, the process of determining the beam domain energy matrix based on the uplink channel estimation samples can be as follows: obtaining the uplink carrier frequency and the oversampling factor of the first antenna; determining the uplink sampling steering matrix based on the uplink carrier frequency and the oversampling factor of the first antenna; determining the channel estimation sample statistical matrix based on the uplink sampling steering matrix and the uplink channel estimation samples; and determining the beam domain energy matrix based on the channel estimation sample statistical matrix and the oversampling factor of the first antenna.

[0035] The first antenna oversampling factor includes the horizontal antenna oversampling factor N. x and the vertical antenna oversampling factor N z The first antenna oversampling factor can be understood as a multiple of the base station's transmit antenna, and can be a positive integer greater than or equal to 1, set by the user (e.g., the algorithm user or operator). Uplink carrier frequency f up It is determined by the system and can be obtained directly.

[0036] Specifically, the process of determining the uplink sampling steering matrix based on the uplink carrier frequency and the oversampling factor of the first antenna can be as follows: determine the horizontal uplink sampling steering matrix based on the uplink carrier frequency and the horizontal antenna oversampling factor; determine the vertical uplink sampling steering matrix based on the uplink carrier frequency and the vertical antenna oversampling factor; and perform a Kronecker product between the horizontal and vertical uplink sampling steering matrices to obtain the uplink sampling steering matrix. The formula can be expressed as: in, Let u be the horizontal uplink sampling steering matrix. i (i = 0, 1, ..., N) x M x -1) represents the direction cosine of the horizontal antenna array obtained by uniformly discrete sampling from the range [-1, 1]. Let v be the upward sampling steering matrix in the vertical direction.j (j = 0, 1, ..., N) z M z -1) is the direction cosine of the vertical antenna array obtained by uniformly discrete sampling from [-1, 1]. Where Θ=-j2πd / c, M z M x Here, represents the number of antennas in the vertical and horizontal directions, respectively; d is the row and column spacing of the antennas; c is the speed of light; and M is the speed of light. t =M z M x M represents the total number of antennas. MIMO =N x N z M t .

[0037] Specifically, the process of determining the channel estimation sample statistical matrix based on the uplink sampling steering matrix and uplink channel estimation samples can be as follows: For each user equipment, the uplink channel estimation sample of that user equipment is right-multiplied by the uplink sampling steering matrix to obtain an intermediate matrix. The intermediate matrix is ​​then subjected to a Hadamard product operation with its conjugate matrix. Finally, the expected value of the result of the uplink channel estimation sample operation is calculated to obtain the channel estimation sample statistical matrix. The formula can be expressed as: Let E{} be the channel estimation sample statistics matrix for user equipment n, where E{} denotes the mathematical expectation calculation, and * denotes the conjugate of the matrix.

[0038] Optionally, the beam domain energy matrix can be determined based on the channel estimation sample statistical matrix and the oversampling factor of the first antenna as follows: if the oversampling factor of the horizontal antenna and the oversampling factor of the vertical antenna are both 1, then the channel estimation sample statistical matrix is ​​determined as the beam domain energy matrix.

[0039] In this embodiment, when both the horizontal antenna oversampling factor and the vertical antenna oversampling factor are 1, the number of beam domain samples is the same as the actual number of antennas at the base station. In this case, the channel estimation sample statistical matrix is ​​directly determined as the beam domain energy matrix. That is, Ω n =Φ n , where is the beam domain energy matrix of user equipment n.

[0040] Optionally, the beam domain energy matrix can be determined based on the channel estimation sample statistical matrix and the first antenna oversampling factor as follows: if the horizontal antenna oversampling factor and / or the vertical antenna oversampling factor are greater than 1, then the beam correlation matrix is ​​determined based on the uplink sampling steering matrix, and the channel estimation sample statistical matrix is ​​determined as the initial beam domain energy matrix; the initial beam domain energy matrix is ​​iteratively calculated based on the beam correlation matrix and the channel estimation sample statistical matrix to obtain the final beam domain energy matrix.

[0041] When the oversampling factor of the horizontal antenna and / or the oversampling factor of the vertical antenna are greater than 1, the number of samples in the beam domain is greater than the actual number of antennas in the base station. In this case, the channel beam domain energy matrix needs to be obtained by minimizing the divergence (Kullback-Leibler, KL) principle.

[0042] Specifically, the beam correlation matrix can be determined from the uplink sampling steering matrix by multiplying the conjugate transpose of the uplink sampling steering matrix with the uplink sampling steering matrix itself. The formula can be expressed as: Right now Where H represents the conjugate transpose operation on the rectangle, i = 0, 1, ..., M MIMO -1, j = 0, 1, ..., M MIMO -1.

[0043] In this embodiment, the square root result of the beam domain energy matrix is ​​iterated, that is, the initial information is the square root result of the initial beam domain energy matrix, which is expressed as: Let be the square root of the initial beam domain energy matrix of user equipment n. The iterative calculation of the initial beam domain energy matrix based on the beam correlation matrix and the channel estimation sample statistics matrix can be as follows: Based on the beam correlation matrix and the channel estimation sample statistics matrix, perform iterative calculations on the initial beam domain energy matrix using a predefined iterative formula. Stop the iteration when the termination condition is met, thus obtaining the final beam domain energy matrix. The iterative formula can be expressed as: This is the result of the (l-1)th iteration for user equipment n. For user equipment n, the result of the l-th iteration. Right now With M n It changes with the changes.

[0044] Specifically, the square root M of the beam domain energy matrix of each user equipment is obtained. n Then, the square root of the beam domain energy matrix formed by N user equipment is expressed as:

[0045] S130, the downlink precoding matrix is ​​determined based on the beam domain energy matrix.

[0046] Specifically, the process of determining the downlink precoding matrix based on the beam domain energy matrix can be as follows: obtaining the downlink carrier frequency and the second antenna oversampling factor; determining the downlink sampling steering matrix based on the downlink carrier frequency and the second antenna oversampling factor; and determining the downlink precoding matrix based on the downlink sampling steering matrix and the beam domain energy matrix.

[0047] The oversampling factor of the second antenna is the same as that of the first antenna. The oversampling factor of the second antenna includes the oversampling factor N of the horizontal antenna. x and the vertical antenna oversampling factor N z The oversampling factor for the second antenna can be understood as a multiple of the base station's transmit antenna; it can be a positive integer greater than or equal to 1, set by the user (e.g., the algorithm user or operator). Downlink carrier frequency f d It is determined by the system and can be obtained directly.

[0048] Specifically, the process of determining the downlink sampling steering matrix based on the downlink carrier frequency and the second antenna oversampling factor can be as follows: determine the horizontal downlink sampling steering matrix based on the downlink carrier frequency and the horizontal antenna oversampling factor; determine the vertical downlink sampling steering matrix based on the downlink carrier frequency and the vertical antenna oversampling factor; and perform a Kronecker product between the horizontal and vertical downlink sampling steering matrices to obtain the downlink sampling steering matrix. The formula can be expressed as: in, Let u be the downsampling steering matrix in the horizontal direction. i (i = 0, ... N) x M x -1) represents the direction cosine of the horizontal antenna array obtained by uniformly discrete sampling from the range [-1, 1]. Let v be the downsampling steering matrix in the vertical direction. j (j=0,…,N z M z -1) is the direction cosine of the vertical antenna array obtained by uniformly discrete sampling from [-1, 1]. Where Θ=-j2πd / c, M z M x Here, represents the number of antennas in the vertical and horizontal directions, respectively; d is the row and column spacing of the antennas; c is the speed of light; and M is the speed of light. t =M z M x M represents the total number of antennas. MIMO =N x N z M t .

[0049] Optionally, if the channel is a line-of-sight channel, the method for determining the downlink precoding matrix based on the downlink sampling steering matrix and the beam domain energy matrix can be as follows: for each user equipment, determine the beam index value corresponding to the maximum energy from its beam domain energy matrix; extract the downlink sampling steering vector corresponding to the beam index value from the downlink sampling steering matrix; concatenate the extracted downlink sampling steering vectors into a sub-downlink sampling steering matrix, and determine the downlink precoding matrix based on the sub-downlink sampling steering matrix.

[0050] Specifically, for each user equipment (UE), the process of extracting the downlink sampling steering vector corresponding to the beam index value from the downlink sampling steering matrix can be as follows: Determine the horizontal and vertical cosine index values ​​based on the beam index value, the oversampling factor of the base station-side antenna in the vertical direction, and the number of antennas in the vertical direction; determine the horizontal cosine based on the horizontal cosine index value; determine the vertical cosine based on the vertical cosine index value; and determine the downlink sampling steering vector for the UE based on the horizontal and vertical cosines. Finally, concatenate the downlink sampling steering vectors extracted from all UEs to obtain a sub-downlink sampling steering matrix.

[0051] For user equipment n, assume the beam index value corresponding to the maximum energy is idx. n Then the cosine index value in the horizontal direction can be represented as: idx n,x =idx n / M z N z The horizontal cosine is expressed as: The cosine index value in the vertical direction can be represented as idx. n,z =idx n %M z N z %, where % represents the remainder. The cosine in the vertical direction is represented as: The sub-downsampling steering matrix can then be expressed as:

[0052] Specifically, the process of determining the downlink precoding matrix based on the sub-downlink sampling steering matrix can be as follows: obtain the power normalization factor, and determine the downlink precoding matrix based on the power normalization factor, the sub-downlink sampling steering matrix, and its transpose conjugate matrix. The formula can be expressed as: Where β is the power normalization factor, used to control the power of the transmitted signal.

[0053] Optionally, if the channel is a non-line-of-sight channel, the process of determining the downlink precoding matrix based on the downlink sampling steering matrix and the beam domain energy matrix can be as follows: obtain the diagonal matrix of the square root of the beam domain energy matrix; determine the downlink precoding matrix based on the diagonal matrix, the downlink sampling steering matrix, and the square root of the beam domain energy matrix.

[0054] In this embodiment, the downlink precoding matrix is ​​determined directly based on the beam domain energy matrix and line sampling steering matrix determined by the uplink channel estimation samples. This eliminates the need for user equipment (UE) to feed the downlink precoding matrix back to the base station, meaning the feedback overhead is zero. In contrast, traditional schemes require UE to feed the downlink precoding matrix back to the base station, and the resource overhead for this feedback is proportional to the number of UEs, the number of antennas on the base station side, and the feedback frequency. Clearly, this scheme significantly reduces system resource overhead compared to traditional schemes.

[0055] Specifically, the method for determining the downlink precoding matrix based on the square roots of the diagonal matrix, the downlink sampling steering matrix, and the beam domain energy matrix can be as follows: The diagonal matrices containing the square roots of the beam domain energy matrices of each user equipment are summed. The downlink precoding matrix is ​​then determined based on the summed diagonal matrix, the downlink sampling steering matrix, and the square roots of the spliced ​​beam domain energy matrix. The formula can be expressed as: P = β(Υ) d M sum (Υ d ) H ) -1 (M(Υ d ) H ) H Where β is the power normalization factor, [M n ] diag For M n The diagonal matrix is ​​denoted by M; M is the square root of the spliced ​​beam domain energy matrix, which is obtained by splicing the square roots of the beam domain energy matrices of each user equipment.

[0056] The technical solution of this embodiment obtains uplink channel estimation samples based on the uplink reference signal; determines the beam domain energy matrix based on the uplink channel estimation samples; and determines the downlink precoding matrix based on the beam domain energy matrix. The downlink precoding method provided by this embodiment first determines the beam domain energy matrix based on the uplink channel estimation samples, and then determines the downlink precoding matrix based on the beam domain energy matrix. This can reduce system time-frequency resource overhead and avoid the decoding errors on the user equipment side and system performance degradation caused by directly using the uplink channel estimation results for downlink precoding.

[0057] For example, Figure 3 shows the performance of the downlink precoding method in this embodiment. As shown in Figure 3, in an FDD scenario, when the channel is a weighted white Gaussian noise (AWGN) channel, the SZF curve is the performance curve of downlink precoding using the method of this embodiment, and the ZF curve is the performance curve of downlink precoding using existing technology (directly using the ZF precoding algorithm based on the uplink channel estimation results). Two user equipments (UEs) with orientations of 87.5° and 92.5° were tested, showing the block error rate (BLER) versus signal-to-noise ratio (SNR) on the UE side. The figure shows that the downlink precoding method of this embodiment exhibits a slower change in BLER with SNR, showing a 4dB advantage when the UE orientations are 87.5° and 92.5°. Furthermore, tests on different UE orientations reveal that the greater the difference between the UE orientation and 90°, the more significant the advantage of the downlink precoding method in this embodiment.

[0058] Example 2

[0059] Figure 4 is a schematic diagram of a downlink precoding device provided in Embodiment 2 of the present invention. As shown in Figure 4, the device includes:

[0060] Uplink channel estimation sample acquisition module 310 is used to acquire uplink channel estimation samples based on uplink reference signals;

[0061] Beam domain energy matrix determination module 320 is used to determine the beam domain energy matrix based on the uplink channel estimation samples;

[0062] The precoding matrix determination module 330 is used to determine the downlink precoding matrix based on the beam domain energy matrix.

[0063] Optionally, the beam domain energy matrix determination module 320 is also used for:

[0064] Obtain the uplink carrier frequency and the oversampling factor of the first antenna; wherein, the oversampling factor of the first antenna includes the oversampling factor of the horizontal antenna and the oversampling factor of the vertical antenna;

[0065] The uplink sampling steering matrix is ​​determined based on the uplink carrier frequency and the first antenna oversampling factor.

[0066] The channel estimation sample statistics matrix is ​​determined based on the uplink sampling steering matrix and the uplink channel estimation samples.

[0067] The beam domain energy matrix is ​​determined based on the channel estimation sample statistics matrix and the oversampling factor of the first antenna.

[0068] Optionally, the beam domain energy matrix determination module 320 is also used for:

[0069] If the oversampling factor of the horizontal antenna and the oversampling factor of the vertical antenna are both 1, then the channel estimation sample statistics matrix is ​​determined as the beam domain energy matrix.

[0070] Optionally, the beam domain energy matrix determination module 320 is also used for:

[0071] If the oversampling factor of the horizontal antenna and / or the oversampling factor of the vertical antenna are greater than 1, then the beam correlation matrix is ​​determined according to the uplink sampling steering matrix, and the channel estimation sample statistics matrix is ​​determined as the initial beam domain energy matrix.

[0072] The initial beam domain energy matrix is ​​iteratively calculated based on the beam correlation matrix and the channel estimation sample statistics matrix to obtain the final beam domain energy matrix.

[0073] Optionally, the precoding matrix determination module 330 is also used for:

[0074] Obtain the downlink carrier frequency and the second line oversampling factor;

[0075] The downlink sampling steering matrix is ​​determined based on the downlink carrier frequency and the second antenna oversampling factor.

[0076] The downlink precoding matrix is ​​determined based on the downlink sampling steering matrix and the beam domain energy matrix.

[0077] Optionally, if the channel is a line-of-sight channel, the precoding matrix determination module 330 is also used for:

[0078] Determine the beam index value corresponding to the maximum energy from the beam domain energy matrix;

[0079] Extract the downlink sampling steering vector corresponding to the beam index value from the downlink sampling steering matrix, and concatenate the extracted downlink sampling steering vectors into a sub-downlink sampling steering matrix;

[0080] The downlink precoding matrix is ​​determined based on the sub-downlink sampling steering matrix.

[0081] Optionally, if the channel is a non-line-of-sight channel, the precoding matrix determination module 330 is also used for:

[0082] Obtain the diagonal matrix of the square root of the beam domain energy matrix;

[0083] The downlink precoding matrix is ​​determined based on the square root of the diagonal matrix, the downlink sampling steering matrix, and the beam domain energy matrix.

[0084] The above-described apparatus can execute the methods provided in all the foregoing embodiments of the present invention, and has the corresponding functional modules and beneficial effects for executing the above methods. Technical details not described in detail in this embodiment can be found in the methods provided in all the foregoing embodiments of the present invention.

[0085] Example 3

[0086] Figure 5 illustrates a schematic diagram of an electronic device 10 that can be used to implement embodiments of the present invention. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0087] As shown in Figure 5, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer programs stored in the ROM 12 or loaded from storage unit 18 into the RAM 13. The RAM 13 can also store various programs and data required for the operation of the electronic device 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0088] Multiple components in electronic device 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of displays, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0089] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as downlink precoding methods.

[0090] In some embodiments, the downlink precoding method may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or mounted on electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the downlink precoding method described above may be performed. Alternatively, in other embodiments, processor 11 may be configured to perform the downlink precoding method by any other suitable means (e.g., by means of firmware).

[0091] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0092] Computer programs used to implement the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0093] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0094] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0095] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or computing systems that include middleware components (e.g., application servers), or computing systems that include frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0096] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0097] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0098] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A downlink precoding method, characterized in that, The method is executed by a base station and includes: acquiring uplink channel estimation samples based on an uplink reference signal; determining a beam domain energy matrix based on the uplink channel estimation samples; and determining a downlink precoding matrix based on the beam domain energy matrix. The step of determining the beam domain energy matrix based on the uplink channel estimation samples includes: acquiring an uplink carrier frequency and a first antenna oversampling factor for uplink channel processing; wherein the first antenna oversampling factor includes a horizontal antenna oversampling factor and a vertical antenna oversampling factor; determining an uplink sampling steering matrix based on the uplink carrier frequency and the first antenna oversampling factor; and determining the uplink sampling steering matrix based on the uplink channel estimation samples. The process involves: determining a channel estimation sample statistical matrix; determining a beam domain energy matrix based on the channel estimation sample statistical matrix and the oversampling factor of the first antenna; and determining the beam domain energy matrix based on the channel estimation sample statistical matrix and the oversampling factor of the first antenna, which includes: if the oversampling factor of the horizontal antenna and / or the oversampling factor of the vertical antenna is greater than 1, then determining a beam correlation matrix based on the uplink sampling steering matrix, and determining the channel estimation sample statistical matrix as the initial beam domain energy matrix; and performing iterative calculations on the initial beam domain energy matrix based on the beam correlation matrix and the channel estimation sample statistical matrix to obtain the final beam domain energy matrix.

2. The method according to claim 1, wherein determining the beam domain energy matrix based on the channel estimation sample statistical matrix and the first antenna oversampling factor includes: If the oversampling factor of the horizontal antenna and the oversampling factor of the vertical antenna are both 1, then the channel estimation sample statistics matrix is ​​determined as the beam domain energy matrix.

3. The method according to claim 1, characterized in that, Determining the downlink precoding matrix based on the beam domain energy matrix includes: obtaining the downlink carrier frequency and the oversampling factor of the second antenna used for downlink channel processing; determining the downlink sampling steering matrix based on the downlink carrier frequency and the oversampling factor of the second antenna; and determining the downlink precoding matrix based on the downlink sampling steering matrix and the beam domain energy matrix.

4. The method according to claim 3, characterized in that, If the channel is a line-of-sight channel, the downlink precoding matrix is ​​determined based on the downlink sampling steering matrix and the beam domain energy matrix, including: determining the beam index value corresponding to the maximum energy from the beam domain energy matrix; extracting the downlink sampling steering vector corresponding to the beam index value from the downlink sampling steering matrix, and concatenating the extracted downlink sampling steering vectors into a sub-downlink sampling steering matrix; and determining the downlink precoding matrix based on the sub-downlink sampling steering matrix.

5. The method according to claim 3, characterized in that, If the channel is a non-line-of-sight channel, the downlink precoding matrix is ​​determined based on the downlink sampling steering matrix and the beam domain energy matrix, including: obtaining the diagonal matrix of the square root of the beam domain energy matrix; and determining the downlink precoding matrix based on the diagonal matrix, the downlink sampling steering matrix, and the square root of the beam domain energy matrix.

6. A downlink precoding apparatus, characterized in that, The device is installed in a base station and includes: an uplink channel estimation sample acquisition module, used to acquire uplink channel estimation samples based on an uplink reference signal; a beam domain energy matrix determination module, used to determine a beam domain energy matrix based on the uplink channel estimation samples; and a precoding matrix determination module, used to determine a downlink precoding matrix based on the beam domain energy matrix. The beam domain energy matrix determination module is further used to: acquire an uplink carrier frequency and a first antenna oversampling factor for uplink channel processing; wherein the first antenna oversampling factor includes a horizontal antenna oversampling factor and a vertical antenna oversampling factor; and determine the uplink sampling based on the uplink carrier frequency and the first antenna oversampling factor. The uplink sampling steering matrix is ​​used to determine a channel estimation sample statistical matrix based on the uplink sampling steering matrix and the uplink channel estimation samples. The beam domain energy matrix is ​​determined based on the channel estimation sample statistical matrix and the oversampling factor of the first antenna. The beam domain energy matrix determination module is further configured to: if the oversampling factor of the horizontal antenna and / or the oversampling factor of the vertical antenna is greater than 1, determine a beam correlation matrix based on the uplink sampling steering matrix and determine the channel estimation sample statistical matrix as the initial beam domain energy matrix; and perform iterative calculations on the initial beam domain energy matrix based on the beam correlation matrix and the channel estimation sample statistical matrix to obtain the final beam domain energy matrix.

7. An electronic device, characterized in that, The electronic device includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores a computer program executable by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the downlink precoding method according to any one of claims 1-5.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that cause a processor to execute the downlink precoding method according to any one of claims 1-5.

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