CN114900217B - Precoding method and related device - Google Patents

Precoding method and related device Download PDF

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CN114900217B
CN114900217B CN202210659569.3A CN202210659569A CN114900217B CN 114900217 B CN114900217 B CN 114900217B CN 202210659569 A CN202210659569 A CN 202210659569A CN 114900217 B CN114900217 B CN 114900217B
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channel
correlation matrix
matrix
precoding
channel correlation
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CN114900217A (en
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黄润
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Guangdong Oppo Mobile Telecommunications Corp Ltd
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Guangdong Oppo Mobile Telecommunications Corp Ltd
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/0413—MIMO systems
    • H04B7/0456—Selection of precoding matrices or codebooks, e.g. using matrices antenna weighting
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/0413—MIMO systems
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/06—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station
    • H04B7/0613—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission
    • H04B7/0615—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission of weighted versions of same signal
    • H04B7/0619—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission of weighted versions of same signal using feedback from receiving side
    • H04B7/0621—Feedback content
    • H04B7/0626—Channel coefficients, e.g. channel state information [CSI]
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/06—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station
    • H04B7/0613—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission
    • H04B7/0615—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission of weighted versions of same signal
    • H04B7/0619—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission of weighted versions of same signal using feedback from receiving side
    • H04B7/0621—Feedback content
    • H04B7/0632—Channel quality parameters, e.g. channel quality indicator [CQI]
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/06—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station
    • H04B7/0613—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission
    • H04B7/0615—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission of weighted versions of same signal
    • H04B7/0619—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission of weighted versions of same signal using feedback from receiving side
    • H04B7/0636—Feedback format
    • H04B7/0639—Using selective indices, e.g. of a codebook, e.g. pre-distortion matrix index [PMI] or for beam selection
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D30/00—Reducing energy consumption in communication networks
    • Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks

Abstract

The embodiment of the application discloses a precoding method and a related device, wherein the method comprises the following steps: determining a signal-to-noise ratio corresponding to each of N channel transmission layers of a first precoding matrix, wherein N is a positive integer greater than 1; reconstructing a first channel according to the first precoding matrix and the signal-to-noise ratio corresponding to each channel transmission layer to obtain a first channel correlation matrix, wherein the first channel correlation matrix is used for representing a second channel obtained after the first channel is reconstructed; performing smoothing filter processing on the first channel correlation matrix to obtain a second channel correlation matrix after the smoothing filter processing; and determining a second precoding matrix according to the second channel correlation matrix. The embodiment of the application is beneficial to improving the precoding precision and the performance gain brought by the MIMO technology.

Description

Precoding method and related device
Technical Field
The present application relates to the field of communications technologies, and in particular, to a precoding method and a related device.
Background
With the development of wireless communication technology, a large-scale Multiple-input Multiple-Output (MIMO) technology is largely applied in the fifth generation mobile communication system (5th Generation Mobile Communication Technology,5G), and the base station performs precoding on signals by acquiring channel state information (Channel State Information, CSI) and using the CSI information to exert performance gain of the MIMO technology.
However, in the current scenario of poor reciprocity or frequency division duplex (Frequency Division Duplexing, FDD), the CSI information obtained by the base station is not accurate, which greatly limits the performance gain brought by MIMO technology.
Disclosure of Invention
The embodiment of the application provides a precoding method and a related device, which are beneficial to improving the precoding precision and improving the performance gain brought by the MIMO technology.
In a first aspect, an embodiment of the present application provides a precoding method, applied to a base station, where the method includes:
determining a first precoding matrix and a signal-to-noise ratio corresponding to each of N channel transmission layers, wherein N is a positive integer greater than 1;
reconstructing a first channel according to the first precoding matrix and the signal-to-noise ratio corresponding to each channel transmission layer to obtain a first channel correlation matrix, wherein the first channel correlation matrix is used for representing a second channel obtained after the first channel is reconstructed;
performing smoothing filter processing on the first channel correlation matrix to obtain a second channel correlation matrix after the smoothing filter processing;
and determining a second precoding matrix according to the second channel correlation matrix.
In a second aspect, an embodiment of the present application provides a precoding method, applied to a terminal device, where the method includes:
acquiring CQI information corresponding to N channel transmission layers, wherein N is a positive integer greater than 1;
and determining the signal-to-noise ratio of each channel transmission layer according to the CQI information, wherein the signal-to-noise ratio is used for determining the relative weighting coefficient corresponding to each channel transmission layer.
In a third aspect, an embodiment of the present application provides a precoding apparatus applied to a base station, where the apparatus includes: a determining unit, a reconstructing unit and a filtering unit, wherein,
the determining unit is configured to determine a first precoding matrix and a signal-to-noise ratio corresponding to each of N channel transmission layers;
the reconstruction unit is configured to reconstruct a first channel according to the first precoding matrix and a signal-to-noise ratio corresponding to each channel transmission layer to obtain a first channel correlation matrix, where the first channel correlation matrix is used to characterize a second channel obtained after the first channel is reconstructed;
the filtering unit is used for carrying out smoothing filtering processing on the first channel correlation matrix to obtain a second channel correlation matrix after the smoothing filtering processing;
The determining unit is further configured to determine a second precoding matrix according to the second channel correlation matrix.
In a fourth aspect, an embodiment of the present application provides a precoding apparatus, applied to a terminal device, where the apparatus includes: an acquisition unit and a determination unit, wherein,
the acquiring unit is configured to acquire CQI information corresponding to N channel transport layers, where N is a positive integer greater than 1;
and the determining unit is used for determining the signal-to-noise ratio of each channel transmission layer according to the CQI information, wherein the signal-to-noise ratio is used for determining the relative weighting coefficient corresponding to each channel transmission layer.
In a fifth aspect, an embodiment of the present application provides an electronic device, including a processor, a memory, a communication interface, and one or more programs, where the one or more programs are stored in the memory and configured to be executed by the processor, the programs including instructions for performing steps in any of the methods of the first or second aspects of the embodiments of the present application.
In a sixth aspect, embodiments of the present application provide a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program for electronic data exchange, wherein the computer program causes a computer to perform part or all of the steps as described in any one of the methods of the first or second aspects of the embodiments of the present application.
In a seventh aspect, embodiments of the present application provide a computer program product, wherein the computer program product comprises a non-transitory computer readable storage medium storing a computer program operable to cause a computer to perform part or all of the steps described in any of the methods of the first or second aspects of the embodiments of the present application. The computer program product may be a software installation package.
It can be seen that, in the embodiment of the present application, the terminal device may determine the signal-to-noise ratio of each channel transmission layer, so as to facilitate the base station to reconstruct the first channel according to the signal-to-noise ratio and the first precoding matrix corresponding to each channel transmission layer, so as to obtain a reconstructed first channel correlation matrix, and facilitate to improve the channel reconstruction accuracy; and finally, performing smoothing filtering processing according to the reconstructed second channel, namely performing smoothing filtering processing on the first channel correlation matrix to obtain a second channel correlation matrix, and determining a second precoding matrix according to the second channel correlation matrix, thereby being beneficial to improving the precoding gain, improving the precoding precision, fully playing the advantages of the MIMO technology and bringing about larger precoding gain.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the embodiments or the description of the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and that other drawings can be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a schematic structural diagram of a communication system according to an embodiment of the present application;
fig. 2 is a schematic flow chart of a precoding method according to an embodiment of the present application;
fig. 3 is a schematic flow chart of a precoding method according to an embodiment of the present application;
fig. 4 is an interaction schematic diagram of a precoding method provided in an embodiment of the present application;
fig. 5 is a schematic structural diagram of an electronic device according to an embodiment of the present application;
fig. 6 is a schematic structural diagram of an electronic device according to an embodiment of the present application;
fig. 7 is a functional unit composition block diagram of a precoding device provided in an embodiment of the present application;
fig. 8 is a functional unit composition block diagram of a precoding device provided in an embodiment of the present application.
Detailed Description
In order that those skilled in the art will better understand the present application, a technical solution in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in which it is apparent that the described embodiments are only some embodiments of the present application, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
The terms first, second and the like in the description and in the claims and in the above-described figures are used for distinguishing between different objects and not necessarily for describing a sequential or chronological order. Furthermore, the terms "comprise" and "have," as well as any variations thereof, are intended to cover a non-exclusive inclusion. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those listed steps or elements but may include other steps or elements not listed or inherent to such process, method, article, or apparatus.
Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment may be included in at least one embodiment of the application. The appearances of such phrases in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. Those of skill in the art will explicitly and implicitly appreciate that the embodiments described herein may be combined with other embodiments.
1) The electronic device may be a portable electronic device that also contains other functions such as personal digital assistant or music player functions, such as a cell phone, tablet computer, wearable electronic device with wireless communication functions (e.g., smart watch, smart glasses), vehicle-mounted device, etc. Exemplary embodiments of portable electronic devices include, but are not limited to, portable electronic devices that are equipped with IOS systems, android systems, microsoft systems, or other operating systems. The portable electronic device may also be other portable electronic devices such as a Laptop computer (Laptop) or the like. It should also be appreciated that in other embodiments, the electronic device described above may not be a portable electronic device, but rather a desktop computer. In the embodiment of the present application, the electronic device may be a base station or a terminal device, and the terminal device may be a User Equipment (UE).
2) Multiple-input Multiple-Input and Multiple-Output (MIMO) technology, i.e. a base station and a terminal device are configured with Multiple transmit-receive antennas, which can doubly improve the capacity and spectrum utilization of a communication system without increasing bandwidth and transmit power, and also can resist wireless channel fading and improve the error code performance of the system.
With the development of wireless communication technology, a large-scale MIMO technology is introduced into a fifth generation mobile communication system, and a base station configures hundreds or even more antennas, so that performance of various aspects of the system is further improved.
The key point of the MIMO technology is how the base station obtains accurate CSI, and the CSI may be used to precode the transmitted signal to achieve the effect of signal space domain shaping. In the 5G time division duplex (Time Division Duplexing, TDD) mode, the base station may obtain a more accurate channel in downlink communications by transmitting a specific reference signal through the UE using channel diversity, and then solve an optimal precoding matrix.
However, in the case of poor diversity or frequency division duplex (Frequency Division Duplexing, FDD), CSI information can only be obtained by quantization of a terminal device and then uplink feedback, and includes Precoding Matrix Indicator (PMI) information, channel quality Indicator (Channel Quality Indicator, CQI) information, channel Rank Indicator (RI), and the like. Due to the fact that quantization brings certain precision loss, the CSI information obtained by the base station is inaccurate, and finally the precoding gain is low.
Accordingly, in view of the above problems, the present application provides a precoding method and related devices, which are described in detail below.
As shown in fig. 1, a schematic structure of a communication system used in the present application may include: a base station 100a and a terminal device 100b.
The base station 100a and the terminal device 100b may be used as electronic devices in the embodiments of the present application. For example, the terminal device 100b may be a terminal device such as a mobile phone, a tablet computer, or the like.
The method and the device are suitable for 5G downlink scenes.
Wherein, the terminal device 100b may quantize (Channel State Information, CSI) information on a channel estimated from the reference signal, and the quantized CSI information may include at least one of the following: channel quality Indication (Channel Quality Indicator, CQI) information, channel Rank Indication (RI), precoding Matrix Indication (PMI), and signal-to-noise ratio (snr) corresponding to each channel transport layer, etc., and feeds back downlink channel state information to the base station 100a through a dedicated feedback channel.
Wherein the base station 100a may determine the channel in the downlink communication and may be represented by a plurality of components, i.e., N channel transport layers. In the embodiment of the application, the MIMO channel corresponds to N parallel channel transmission layers.
Wherein each channel transport layer may correspond to CQI information.
Wherein the precoding matrix used by the base station 100a in precoding may be determined according to the reconstructed channel matrix of the terminal equipment 100 b.
In one possible example, the terminal device 100b obtains CQI information corresponding to N channel transport layers, where N is a positive integer greater than 1; determining a signal-to-noise ratio of each channel transmission layer according to the CQI information, wherein the signal-to-noise ratio is used for determining a relative weighting coefficient corresponding to each channel transmission layer; the terminal equipment carries the signal-to-noise ratio of each channel transmission layer through the CQI information; the terminal device 100b reports the channel state information and the codebook to the base station 100 a; the base station 100a determines a relative weighting coefficient of each channel transmission layer pair according to the signal-to-noise ratio of each channel transmission layer; the base station 100a acquires channel state information and a codebook reported by the terminal equipment 100 b; the base station 100a determines the first precoding matrix according to the channel state information and the codebook; the base station 100a reconstructs a first channel according to the first precoding matrix and the relative weighting coefficient of each channel transmission layer to obtain a first channel correlation matrix, wherein the channel correlation matrix is used for representing a second channel obtained after the first channel is reconstructed; the base station 100a performs smoothing filtering processing on the first channel correlation matrix to obtain a second channel correlation matrix after the smoothing filtering processing; the base station 100a determines a second precoding matrix based on the second channel correlation matrix. In this way, the terminal device 100b may determine the signal-to-noise ratio of each channel transmission layer, thereby being beneficial to helping the base station 100a determine the relative weighting coefficient for characterizing the channel quality according to the signal-to-noise ratio corresponding to each channel transmission layer, and further, the base station 100a may reconstruct the first channel based on the relative weighting coefficient and the first precoding matrix, so as to obtain the channel correlation matrix after reconstruction, which is beneficial to improving the channel reconstruction precision; finally, the second precoding matrix can be determined according to the reconstructed channel, namely the channel correlation matrix, which is favorable for improving the precoding gain, thereby being favorable for improving the precoding precision, giving full play to the advantages of the MIMO technology and bringing about larger precoding gain.
It should be noted that, in the present application, a plurality may refer to two or more, and will not be described in detail later.
Referring to fig. 2, fig. 2 is a flow chart of a precoding method according to an embodiment of the present application, which is applied to a base station, and as shown in the figure, the precoding method includes the following operations.
S201, a base station determines a first precoding matrix and a signal to noise ratio corresponding to each channel transmission layer in N channel transmission layers, wherein N is a positive integer greater than 1.
Wherein, the channel gains transmitted by each layer in the channel transmission layers are different, namely, the channel quality is different. The above relative weighting coefficients may be used to indicate the channel quality at the time of transmission of each layer in the channel. The channel may be divided into N channel transport layers.
In a specific implementation, the base station can process the CSI information fed back by the terminal device to obtain a signal to noise ratio corresponding to each channel transmission layer.
The base station may determine the first precoding matrix according to the codebook and CQI information reported by the terminal device, where the first precoding matrix may refer to an unprocessed precoding matrix, and may refer to an original precoding matrix.
S202, the base station reconstructs a first channel according to the first precoding matrix and the signal-to-noise ratio corresponding to each channel transmission layer to obtain a first channel correlation matrix, wherein the first channel correlation matrix is used for representing a second channel obtained after the first channel is reconstructed.
The second channel obtained after the base station reconstructs the first channel determined by the downlink can be represented by the first channel correlation matrix.
It can be seen that, in this example, the above-mentioned relative weighting coefficient is determined according to the signal-to-noise ratio corresponding to each channel transmission layer, and the base station is not directly determined according to the PMI information and the CQI information fed back by the terminal device, but considers the signal-to-noise ratio of each channel transmission layer. Therefore, the method is not only used for roughly recovering the channel, but also is beneficial to improving the performance gain brought by the MIMO technology and improving the channel reconstruction precision under the scene of larger signal-to-noise ratio difference of each layer or each channel transmission layer.
And S203, the base station performs smoothing filter processing on the first channel correlation matrix to obtain a second channel correlation matrix after the smoothing filter processing.
The smoothing filtering processing method may be set by the user or default by the system, and is not limited herein. For example, filtering of the reconstructed channel to correct parameters in the channel correlation matrix may be implemented by an infinite impulse response digital filter (Infinite Impulse Response, IIR).
S204, the base station determines a second precoding matrix according to the second channel correlation matrix.
Wherein the second precoding matrix is different from the first precoding matrix.
In a specific implementation, the second channel correlation matrix can be processed through Block Diagonalization (BD) of Singular Value Decomposition (SVD) to obtain a second precoding matrix, so that inter-user interference in a downlink MIMO system can be eliminated, which is beneficial to fully exerting advantages of MIMO technology and bringing about larger precoding gain.
It should be noted that, the algorithm for determining the second precoding matrix may also be implemented by other linear and/or nonlinear precoding techniques, which is not limited herein.
It can be seen that, in this example, the above precoding method may solve the problem that when FDD or dissimilarity is poor, the terminal device quantizes the CSI information and loses precision, so that the CSI information acquired by the base station is inaccurate, resulting in a situation that the precoding gain is low, thereby being beneficial to improving the precoding gain.
It can be seen that, according to the precoding method described in the embodiment of the present application, a base station may determine a signal-to-noise ratio corresponding to each of N channel transmission layers of a first precoding matrix, where N is a positive integer greater than 1; reconstructing a first channel according to the first precoding matrix and the signal-to-noise ratio corresponding to each channel transmission layer to obtain a first channel correlation matrix, wherein the first channel correlation matrix is used for representing a second channel obtained after the first channel is reconstructed; performing smoothing filter processing on the first channel correlation matrix to obtain a second channel correlation matrix after the smoothing filter processing; and determining a second precoding matrix according to the second channel correlation matrix. Therefore, the channel quality of each channel transmission layer can be represented by the relative weighting coefficients corresponding to the N channel transmission layers, and the characteristics of the original channel can be ensured to the greatest extent; reconstructing the first channel according to the first precoding matrix on the basis of the first precoding matrix to obtain a reconstructed channel, which is beneficial to improving the channel reconstruction precision; finally, the second precoding matrix can be determined according to the reconstructed channel, namely the channel correlation matrix, which is favorable for improving the precoding gain, thereby being favorable for improving the precoding precision, giving full play to the advantages of the MIMO technology and bringing about larger precoding gain.
In one possible example, after the determining the first precoding matrix and the signal-to-noise ratio corresponding to each of the N channel transmission layers, the method may further include the steps of: and determining the relative weighting coefficient of each channel transmission layer pair according to the signal-to-noise ratio of each channel transmission layer.
Wherein, the relative weighting coefficient of each channel transmission layer can be determined according to the signal-to-noise ratio of each channel transmission layer, which can be expressed as: sigma (sigma) i I=1, 2, …, N, where N is a positive integer greater than 1.
In one possible example, the reconstructing the first channel according to the first precoding matrix and the signal-to-noise ratio corresponding to each channel transmission layer may include the following steps: and reconstructing the first channel according to the first precoding matrix and the relative weighting coefficient of each channel transmission layer.
In one possible example, the reconstructing the first channel according to the first precoding matrix and the relative weighting coefficient of each channel transmission layer to obtain a first channel correlation matrix may include the following steps: determining components of each channel transmission layer according to the first precoding matrix and the relative weighting coefficient of each channel transmission layer to obtain N components; and carrying out weighted summation on the N components to obtain the first channel correlation matrix.
Wherein, can pass through W= [ W 1 ,w 2 ,...,w N ]To represent a first precoding matrix.
In particular implementation, the principle of eigenvalue decomposition can be used, namely R=H H H＝QΣQ H Obtaining the components of each channel transport layerAnd carrying out weighted summation on the N independent components obtained by the decomposition to obtain a first channel correlation matrix, wherein the channel correlation matrix can be expressed as: />Where Λ=diag (σ 1 σ 2 … σ N )。
In this example, the integral channel can be decomposed into a plurality of independent components by using the eigenvalue decomposition of the channel correlation matrix, which is beneficial to ensuring the characteristics of the original channel to the maximum extent and improving the subsequent precoding precision.
In one possible example, the smoothing filter processing is performed on the first channel correlation matrix to obtain a second channel correlation matrix after the smoothing filter processing, and the method may include the following steps: acquiring a plurality of transmission time intervals; and carrying out smoothing filter processing on the first channel correlation matrix according to the transmission time intervals to obtain the second channel correlation matrix after smoothing processing.
Wherein the transmission time interval (Transport Time Interval, TTI) may refer to the length of an independently decoded transmission in the radio link. The TTI is related to the size of the data block from the higher network layer to the radio link layer.
It can be seen that in this example, the smoothing filter processing can be performed on the first channel correlation matrix according to the transmission time interval, which is beneficial to making the reconstructed second channel have a certain continuity and correlation in the time domain.
In one possible example, the plurality of transmission time intervals includes a first transmission time interval and a second transmission time interval, wherein the first transmission time interval is earlier than the second transmission time interval.
The first transmission time interval and the second transmission time interval may be any two consecutive transmission time intervals among a plurality of transmission time intervals, and the first transmission time interval is earlier than the second transmission time interval.
In one possible example, the smoothing filter processing is performed on the first channel correlation matrix according to the multiple transmission time intervals to obtain the smoothed second channel correlation matrix, and the method may include the following steps: determining a first instantaneous channel correlation matrix reconstructed by the first transmission time interval and a second instantaneous channel correlation matrix reconstructed by the second transmission time interval; determining a filtering factor; and obtaining the smoothed second channel correlation matrix according to the filtering factor, the first instantaneous channel correlation matrix and the second instantaneous channel correlation matrix.
The first instantaneous channel correlation matrix corresponding to the first transmission time interval and the second instantaneous channel correlation matrix corresponding to the second transmission time interval can be obtained through reconstruction by the same method as the determination of the first channel correlation matrix.
The filtering factor may be set by the user or default by the system, which is not limited herein. The filter factor may be set: alpha epsilon (0, 1).
In a specific implementation, the two transmission time intervals, namely the first transmission time interval TTI1 and the second transmission time interval TTI2, can be combined, and the channel is reconstructed to obtain a first instantaneous channel correlation matrix R T1 And a second instantaneous channel correlation matrix R T2 The method comprises the steps of carrying out a first treatment on the surface of the And the first instantaneous channel correlation matrix R is subjected to a filtering factor alpha T1 And a second instantaneous channel correlation matrix R T2 And filtering to obtain a second channel correlation matrix after smoothing:
in this example, the first instantaneous channel correlation matrix and the second instantaneous channel correlation matrix after reconstruction, which respectively correspond to the current TTI (second transmission time interval) can be determined by smoothing filtering and combining the current TTI (first transmission time interval) with the current TTI (second transmission time interval), and the second channel correlation matrix can be obtained by smoothing filtering. The correlation parameters in the first channel correlation matrix are favorably corrected, so that the second channel correlation matrix has certain continuity and correlation in the time domain.
In one possible example, the determining the first precoding matrix may include the steps of: acquiring channel state information (CSI information) and a codebook reported by terminal equipment; and determining the first precoding matrix according to the channel state information and the codebook.
The codebook corresponding to the terminal device may be pre-stored in the base station, and the CSI information may include at least one of the following: the signal-to-noise ratio, CQI information, RI information, PMI information, etc. corresponding to each channel transport layer are not limited herein.
In a specific implementation, a base station may acquire CSI information, PMI information and a codebook reported by a terminal device, determine parameters such as an initial channel direction and channel quality of the terminal device according to the CSI information, the PMI information and the codebook, and determine a first precoding matrix corresponding to the terminal device according to the parameters:
W＝[w 1 w 2 … w N ]。
in this example, the initial first precoding matrix of the terminal device may be determined according to the information reported by the terminal device, so that it is beneficial to determine the relative weighting coefficients of the N channel transmission layers and the first precoding matrix according to the first precoding matrix, so as to help the base station reconstruct the first channel subsequently.
Referring to fig. 3, fig. 3 is a flow chart of a precoding method provided in an embodiment of the present application, which is applied to a terminal device, and as shown in the figure, the precoding method includes the following operations.
S301, the terminal equipment acquires CQI information corresponding to N channel transmission layers, wherein N is a positive integer greater than 1.
The terminal device may quantize CSI information of the channel estimated by the reference signal to obtain CQI information, RI information, PMI information, and the like, which is not limited herein.
Wherein for a MIMO channel there are N parallel channel transport layers. The terminal device can comprehensively evaluate the CQI values of the N channel transport layers to obtain CQI information, where the CQI value is a comprehensive value, and can comprehensively calculate to obtain the CQI value in the reporting process, for example, if there are 2 channel transport layers, when the RI restriction set aperiodic reporting is triggered, the average value of the current and first reporting values can be calculated in the second reporting event, so as to obtain a comprehensive CQI value, where the CQI value can be the CQI value corresponding to the 2 channel transport layers.
Wherein N is a positive integer greater than 1.
S302, the terminal equipment determines the signal-to-noise ratio of each channel transmission layer according to the CQI information, wherein the signal-to-noise ratio is used for determining the relative weighting coefficient corresponding to each channel transmission layer.
The terminal device puts the signal-to-noise ratio of each channel transmission layer into the CSI information, and after reporting the CSI information to the base station, the base station can determine the relative weighting coefficient corresponding to each channel transmission layer through the signal-to-noise ratio.
It can be seen that, in the precoding method described in the embodiment of the present application, a terminal device may obtain CQI information corresponding to N channel transmission layers, where N is a positive integer greater than 1; and determining the signal-to-noise ratio of each channel transmission layer according to the CQI information, wherein the signal-to-noise ratio is used for determining the relative weighting coefficient corresponding to each channel transmission layer. In this way, the terminal device can determine the signal-to-noise ratio corresponding to each channel transmission layer according to the CQI information, so that the base station can determine the relative weighting coefficient for representing the channel quality according to the signal-to-noise ratio corresponding to each channel transmission layer.
In one possible example, before the acquiring CQI information corresponding to the N channel transport layers, the method may further include the following steps: acquiring a channel rank indication; and determining CQI information corresponding to the N channel transmission layers to be reported according to the channel rank indication.
Among them, CQI information corresponding to the N channel transport layers obtained is affected by different downlink physical channel resource allocation schemes (e.g., type 0, type 1, and type 2).
After the CSI information is quantized to obtain channel Rank Indication (RI) information, it can determine how many or how many layers of channels corresponding to the integrated CQI value need to be reported through the RI (channel rank indication) information. For example, when ri=3, reporting the combined CQI value of the first layer, the second layer and the third layer; when ri=5, the comprehensive CQI value of the corresponding channel of the first 5 channel transport layers is reported.
In the embodiment of the present application, when the rank of LTE is 3 or 4, or a New Radio, NR, the terminal device only feeds back the comprehensive CQI information of the comprehensive channel correlation matrix (used for characterizing the channel) corresponding to one RI value, and may trigger the aperiodic reporting of the RI restriction set to obtain the CQI information of the channels corresponding to different channel transmission layers (e.g., layer 2, layer 3, layer 5, etc.).
In a specific implementation, for NR type 2/type 2, the signal to noise ratios of each layer are sequentially arranged, and when ri=1, the first layer (single layer) CQI is reported, when ri=2, the first sub-layer and the second layer comprehensive CQI are reported, and when ri=n, the comprehensive CQI information corresponding to the first 1-N channel transmission layers, that is, the total CQI information corresponding to the N-1 channel transmission layers, is reported; further, the terminal device may process the integrated CQI information to obtain a signal-to-noise ratio for each channel transport layer in the sequence.
In this example, when the terminal device needs to feed back CQI information, it may utilize the limiting RI (channel rank indication) to feed back the comprehensive CQI information of the channels corresponding to the multiple corresponding channel transmission layers, thereby helping the base station calculate and solve the relative weighting coefficients of the channel transmission layers, and improving the precoding accuracy.
Referring to fig. 4, fig. 4 is an interaction schematic diagram of a precoding method according to an embodiment of the present application, where the precoding method includes the following operations.
S401, the terminal equipment acquires CQI information corresponding to N channel transmission layers, wherein N is a positive integer greater than 1.
S402, the terminal equipment determines the signal-to-noise ratio of each channel transmission layer according to the CQI information, wherein the signal-to-noise ratio is used for determining the relative weighting coefficient corresponding to each channel transmission layer.
S403, the terminal equipment loads the signal-to-noise ratio of each channel transmission layer through the CQI information.
Wherein, the channel state information, i.e. CSI information, may comprise a signal to noise ratio of each channel transport layer.
S404, the terminal equipment reports the channel state information and the codebook to the base station.
S405, the base station determines the signal-to-noise ratio of each channel transmission layer of N channel transmission layers, and determines the relative weighting coefficient of each channel transmission layer pair according to the signal-to-noise ratio of each channel transmission layer, wherein N is a positive integer greater than 1.
S406, the base station acquires channel state information and a codebook reported by the terminal equipment.
S407, the base station determines the first precoding matrix according to the channel state information and the codebook.
S408, the base station reconstructs the first channel according to the first precoding matrix and the relative weighting coefficient of each channel transmission layer to obtain a first channel correlation matrix, wherein the first channel correlation matrix is used for representing a second channel obtained after the first channel is reconstructed.
S409, the base station performs smoothing filter processing on the first channel correlation matrix to obtain a second channel correlation matrix after the smoothing filter processing.
S410, the base station determines a second precoding matrix according to the second channel correlation matrix.
The steps S401 to S404 may refer to the steps S301 to S302 and their related descriptions in the precoding method described in fig. 3. The steps S405 to S410 may refer to the steps S201 to S204 and their related descriptions in the precoding method described in fig. 2, and are not described herein.
It can be seen that, according to the precoding method and the related device described in the embodiments of the present application, a terminal device obtains CQI information corresponding to N channel transmission layers, where N is a positive integer greater than 1; determining a signal-to-noise ratio of each channel transmission layer according to the CQI information, wherein the signal-to-noise ratio is used for determining a relative weighting coefficient corresponding to each channel transmission layer; the terminal equipment carries the signal-to-noise ratio of each channel transmission layer through the CQI information; the terminal equipment reports channel state information and a codebook to the base station; the base station determines the signal-to-noise ratio of each channel transmission layer of N channel transmission layers, and determines the relative weighting coefficient of each channel transmission layer pair according to the signal-to-noise ratio of each channel transmission layer; the base station acquires channel state information and a codebook reported by the terminal equipment; the base station determines the first precoding matrix according to the channel state information and the codebook; the base station reconstructs a first channel according to the first precoding matrix and the relative weighting coefficient of each channel transmission layer to obtain a first channel correlation matrix, wherein the first channel correlation matrix is used for representing a second channel obtained after the first channel is reconstructed; the base station carries out smoothing filter processing on the first channel correlation matrix to obtain a second channel correlation matrix after the smoothing filter processing; and the base station determines a second precoding matrix according to the second channel correlation matrix. In this way, the terminal equipment can determine the signal-to-noise ratio of each channel transmission layer, thereby being beneficial to helping the base station reconstruct the first channel according to the signal-to-noise ratio corresponding to each channel transmission layer and the first precoding matrix, so as to obtain a reconstructed first channel correlation matrix and being beneficial to improving the channel reconstruction precision; and finally, performing smoothing filtering processing according to the reconstructed second channel, namely performing smoothing filtering processing on the first channel correlation matrix to obtain a second channel correlation matrix, and determining a second precoding matrix according to the second channel correlation matrix, thereby being beneficial to improving the precoding gain, improving the precoding precision, fully playing the advantages of the MIMO technology and bringing about larger precoding gain.
Referring to fig. 5, fig. 5 is a schematic structural diagram of an electronic device according to an embodiment of the present application, as shown in the drawing, the electronic device includes a processor, a memory, a communication interface, and one or more programs applied to a base station, wherein the one or more programs are stored in the memory, and the one or more programs are configured by the processor to execute instructions for:
determining a first precoding matrix and a signal-to-noise ratio corresponding to each of N channel transmission layers, wherein N is a positive integer greater than 1;
reconstructing a first channel according to the first precoding matrix and the signal-to-noise ratio corresponding to each channel transmission layer to obtain a first channel correlation matrix, wherein the first channel correlation matrix is used for representing a second channel obtained after the first channel is reconstructed;
performing smoothing filter processing on the first channel correlation matrix to obtain a second channel correlation matrix after the smoothing filter processing;
and determining a second precoding matrix according to the second channel correlation matrix.
It can be seen that, in the electronic device described in the embodiment of the present application, a signal-to-noise ratio corresponding to each of N channel transmission layers of the first precoding matrix may be determined, where N is a positive integer greater than 1; reconstructing a first channel according to the first precoding matrix and the signal-to-noise ratio corresponding to each channel transmission layer to obtain a first channel correlation matrix, wherein the first channel correlation matrix is used for representing a second channel obtained after the first channel is reconstructed; performing smoothing filter processing on the first channel correlation matrix to obtain a second channel correlation matrix after the smoothing filter processing; and determining a second precoding matrix according to the second channel correlation matrix. Therefore, the channel quality of each channel transmission layer can be represented by the relative weighting coefficients corresponding to the N channel transmission layers, and the characteristics of the original channel can be ensured to the greatest extent; reconstructing the first channel according to the first precoding matrix on the basis of the first precoding matrix to obtain a reconstructed channel, which is beneficial to improving the channel reconstruction precision; finally, the second precoding matrix can be determined according to the reconstructed channel, namely the channel correlation matrix, which is favorable for improving the precoding gain, thereby being favorable for improving the precoding precision, giving full play to the advantages of the MIMO technology and bringing about larger precoding gain.
In one possible example, after the determining the first precoding matrix and the signal-to-noise ratio corresponding to each of the N channel transport layers, the program further includes instructions for:
and determining the relative weighting coefficient of each channel transmission layer pair according to the signal-to-noise ratio of each channel transmission layer.
In one possible example, in the reconstructing the first channel according to the first precoding matrix and the signal-to-noise ratio corresponding to each channel transmission layer, the program includes instructions for:
and reconstructing the first channel according to the first precoding matrix and the relative weighting coefficient of each channel transmission layer.
In one possible example, in the aspect of reconstructing the first channel according to the relative weighting coefficients of the first precoding matrix and each channel transmission layer to obtain a first channel correlation matrix, the program includes instructions for performing the following steps:
determining components of each channel transmission layer according to the first precoding matrix and the relative weighting coefficient of each channel transmission layer to obtain N components;
And carrying out weighted summation on the N components to obtain the first channel correlation matrix.
In one possible example, in the aspect of smoothing the first channel correlation matrix to obtain the second channel correlation matrix after the smoothing, the program includes instructions for performing the following steps:
acquiring a plurality of transmission time intervals;
and carrying out smoothing filter processing on the first channel correlation matrix according to the transmission time intervals to obtain the second channel correlation matrix after smoothing processing.
In one possible example, the plurality of transmission time intervals includes a first transmission time interval and a second transmission time interval, wherein the first transmission time interval is earlier than the second transmission time interval.
In one possible example, in the aspect of smoothing the first channel correlation matrix according to the multiple transmission time intervals to obtain the smoothed second channel correlation matrix, the program includes instructions for performing the following steps:
determining a first instantaneous channel correlation matrix reconstructed by the first transmission time interval and a second instantaneous channel correlation matrix reconstructed by the second transmission time interval;
Determining a filtering factor;
and obtaining the smoothed second channel correlation matrix according to the filtering factor, the first instantaneous channel correlation matrix and the second instantaneous channel correlation matrix.
In one possible example, in said determining the first precoding matrix, the above-mentioned program comprises instructions for:
acquiring channel state information and a codebook reported by terminal equipment;
and determining the first precoding matrix according to the channel state information and the codebook.
Referring to fig. 6, fig. 6 is a schematic structural diagram of an electronic device according to an embodiment of the present application, as shown in the drawing, the electronic device includes a processor, a memory, a communication interface, and one or more programs applied to a terminal device, where the one or more programs are stored in the memory, and the one or more programs are configured by the processor to execute instructions for:
acquiring CQI information corresponding to N channel transmission layers, wherein N is a positive integer greater than 1;
and determining the signal-to-noise ratio of each channel transmission layer according to the CQI information, wherein the signal-to-noise ratio is used for determining the relative weighting coefficient corresponding to each channel transmission layer.
It can be seen that, in the electronic device described in the embodiment of the present application, CQI information corresponding to N channel transport layers may be obtained, where N is a positive integer greater than 1; and determining the signal-to-noise ratio of each channel transmission layer according to the CQI information, wherein the signal-to-noise ratio is used for determining the relative weighting coefficient corresponding to each channel transmission layer. In this way, the terminal device can determine the signal-to-noise ratio corresponding to each channel transmission layer according to the CQI information, so that the base station can determine the relative weighting coefficient for representing the channel quality according to the signal-to-noise ratio corresponding to each channel transmission layer.
In one possible example, before the acquiring CQI information corresponding to the N channel transport layers, the program includes instructions for:
acquiring a channel rank indication;
and determining CQI information corresponding to the N channel transmission layers to be reported according to the channel rank indication.
The foregoing description of the embodiments of the present application has been presented primarily in terms of a method-side implementation. It will be appreciated that the electronic device, in order to achieve the above-described functions, includes corresponding hardware structures and/or software modules that perform the respective functions. Those of skill in the art will readily appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as hardware or combinations of hardware and computer software. Whether a function is implemented as hardware or computer software driven hardware depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
The embodiment of the application can divide the functional units of the electronic device according to the method example, for example, each functional unit can be divided corresponding to each function, and two or more functions can be integrated in one processing unit. The integrated units may be implemented in hardware or in software functional units. It should be noted that, in the embodiment of the present application, the division of the units is schematic, which is merely a logic function division, and other division manners may be implemented in actual practice.
In the case of dividing each functional module by corresponding each function, fig. 7 shows a schematic diagram of a precoding apparatus, which is applied to a base station as shown in fig. 7, the precoding apparatus 700 may include: a determination unit 701, a reconstruction unit 702 and a filtering unit 703, wherein,
the determining unit 701 is configured to determine a first precoding matrix and a signal-to-noise ratio corresponding to each of N channel transmission layers, where N is a positive integer greater than 1;
the reconstructing unit 702 is configured to reconstruct a first channel according to the first precoding matrix and a signal-to-noise ratio corresponding to each channel transmission layer to obtain a first channel correlation matrix, where the first channel correlation matrix is used to characterize a second channel obtained after the first channel is reconstructed;
The filtering unit 703 is configured to perform smoothing filtering on the first channel correlation matrix to obtain a second channel correlation matrix after the smoothing filtering;
the determining unit 701 is further configured to determine a second precoding matrix according to the second channel correlation matrix.
It can be seen that, according to the precoding device described in the embodiment of the present application, the signal-to-noise ratio corresponding to each of N channel transmission layers of the first precoding matrix can be determined, where N is a positive integer greater than 1; reconstructing a first channel according to the first precoding matrix and the signal-to-noise ratio corresponding to each channel transmission layer to obtain a first channel correlation matrix, wherein the first channel correlation matrix is used for representing a second channel obtained after the first channel is reconstructed; performing smoothing filter processing on the first channel correlation matrix to obtain a second channel correlation matrix after the smoothing filter processing; and determining a second precoding matrix according to the second channel correlation matrix. Therefore, the channel quality of each channel transmission layer can be represented by the relative weighting coefficients corresponding to the N channel transmission layers, and the characteristics of the original channel can be ensured to the greatest extent; reconstructing the first channel according to the first precoding matrix on the basis of the first precoding matrix to obtain a reconstructed channel, which is beneficial to improving the channel reconstruction precision; finally, the second precoding matrix can be determined according to the reconstructed channel, namely the channel correlation matrix, which is favorable for improving the precoding gain, thereby being favorable for improving the precoding precision, giving full play to the advantages of the MIMO technology and bringing about larger precoding gain.
In one possible example, after the determining the first precoding matrix and the signal-to-noise ratio corresponding to each of the N channel transmission layers, the determining unit 701 is further configured to:
and determining the relative weighting coefficient of each channel transmission layer pair according to the signal-to-noise ratio of each channel transmission layer.
In one possible example, in the aspect of reconstructing the first channel according to the first precoding matrix and the signal-to-noise ratio corresponding to each channel transmission layer, the reconstructing unit 702 is specifically configured to:
and reconstructing the first channel according to the first precoding matrix and the relative weighting coefficient of each channel transmission layer.
In one possible example, in the aspect of reconstructing the first channel according to the relative weighting coefficients of the first precoding matrix and the transmission layer of each channel to obtain a first channel correlation matrix, the reconstructing unit 702 is specifically configured to:
determining components of each channel transmission layer according to the first precoding matrix and the relative weighting coefficient of each channel transmission layer to obtain N components;
and carrying out weighted summation on the N components to obtain the first channel correlation matrix.
In one possible example, in the aspect of performing smoothing filtering on the first channel correlation matrix to obtain the second channel correlation matrix after the smoothing filtering, the filtering unit 703 is specifically configured to:
acquiring a plurality of transmission time intervals;
and carrying out smoothing filter processing on the first channel correlation matrix according to the transmission time intervals to obtain the second channel correlation matrix after smoothing processing.
In one possible example, the plurality of transmission time intervals includes a first transmission time interval and a second transmission time interval, wherein the first transmission time interval is earlier than the second transmission time interval.
In one possible example, in the aspect of performing smoothing filtering processing on the first channel correlation matrix according to the multiple transmission time intervals to obtain the smoothed second channel correlation matrix, the determining unit 701 is specifically configured to:
determining a first instantaneous channel correlation matrix reconstructed by the first transmission time interval and a second instantaneous channel correlation matrix reconstructed by the second transmission time interval;
determining a filtering factor;
and obtaining the smoothed second channel correlation matrix according to the filtering factor, the first instantaneous channel correlation matrix and the second instantaneous channel correlation matrix.
In one possible example, in the aspect of determining the first precoding matrix, the determining unit 701 is specifically configured to:
acquiring channel state information and a codebook reported by terminal equipment;
and determining the first precoding matrix according to the channel state information and the codebook.
Referring to fig. 8, fig. 8 shows a schematic diagram of a precoding apparatus, as shown in fig. 8, where the apparatus is applied to a terminal device, and the precoding apparatus 800 may include: an acquisition unit 801, and a determination unit 802, wherein,
the acquiring unit 801 is configured to acquire CQI information corresponding to N channel transport layers, where N is a positive integer greater than 1;
the determining unit 802 is configured to determine a signal-to-noise ratio of each channel transport layer according to the CQI information, where the signal-to-noise ratio is used to determine a relative weighting coefficient corresponding to each channel transport layer.
It can be seen that, according to the precoding device described in the embodiment of the present application, CQI information corresponding to N channel transmission layers can be obtained, where N is a positive integer greater than 1; and determining the signal-to-noise ratio of each channel transmission layer according to the CQI information, wherein the signal-to-noise ratio is used for determining the relative weighting coefficient corresponding to each channel transmission layer. In this way, the terminal device can determine the signal-to-noise ratio corresponding to each channel transmission layer according to the CQI information, so that the base station can determine the relative weighting coefficient for representing the channel quality according to the signal-to-noise ratio corresponding to each channel transmission layer.
In one possible example, before acquiring CQI information corresponding to N channel transport layers, the determining unit 802 is specifically configured to:
acquiring a channel rank indication;
and determining CQI information corresponding to the N channel transmission layers to be reported according to the channel rank indication.
It should be noted that, all relevant contents of each step related to the above method embodiment may be cited to the functional description of the corresponding functional module, which is not described herein.
The electronic device provided in this embodiment is configured to perform the device communication method, so that the same effects as those of the implementation method can be achieved.
In case an integrated unit is employed, the electronic device may comprise a processing module, a storage module and a communication module. The processing module may be configured to control and manage actions of the electronic device, for example, may be configured to support the electronic device to perform the steps performed by the determining unit 701, the reconstructing unit 702, and the filtering unit 703, and/or the acquiring unit 801 and the determining unit 802. The memory module may be used to support the electronic device to execute stored program code, data, etc. And the communication module can be used for supporting the communication between the electronic equipment and other electronic equipment.
Wherein the processing module may be a processor or a controller. Which may implement or perform the various exemplary logic blocks, modules and circuits described in connection with this disclosure. A processor may also be a combination that performs computing functions, e.g., including one or more microprocessors, digital signal processing (digital signal processing, DSP) and microprocessor combinations, and the like. The memory module may be a memory. The communication module can be a radio frequency circuit, a Bluetooth chip, a Wi-Fi chip and other equipment which interact with other electronic equipment.
The embodiment of the application also provides a computer storage medium, wherein the computer storage medium stores a computer program for electronic data exchange, and the computer program makes a computer execute part or all of the steps of any one of the above method embodiments, and the computer includes an electronic device.
Embodiments of the present application also provide a computer program product comprising a non-transitory computer-readable storage medium storing a computer program operable to cause a computer to perform part or all of the steps of any one of the methods described in the method embodiments above. The computer program product may be a software installation package, said computer comprising an electronic device.
It should be noted that, for simplicity of description, the foregoing method embodiments are all described as a series of acts, but it should be understood by those skilled in the art that the present application is not limited by the order of acts described, as some steps may be performed in other orders or concurrently in accordance with the present application. Further, those skilled in the art will also appreciate that the embodiments described in the specification are all preferred embodiments, and that the acts and modules referred to are not necessarily required for the present application.
In the foregoing embodiments, the descriptions of the embodiments are emphasized, and for parts of one embodiment that are not described in detail, reference may be made to related descriptions of other embodiments.
In the several embodiments provided by the present application, it should be understood that the disclosed apparatus may be implemented in other manners. For example, the above-described apparatus embodiments are merely illustrative, such as the above-described division of units, merely a division of logic functions, and there may be additional manners of dividing in actual implementation, such as multiple units or components may be combined or integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be an indirect coupling or communication connection via some interfaces, devices or units, or may be in electrical or other forms.
The units described above as separate components may or may not be physically separate, and components shown as units may or may not be physical units, may be located in one place, or may be distributed over a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in the embodiments of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.
The integrated units described above, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable memory. Based on such understanding, the technical solution of the present application may be embodied in essence or a part contributing to the prior art or all or part of the technical solution in the form of a software product stored in a memory, comprising several instructions for causing a computer device (which may be a personal computer, a server or a network device, etc.) to perform all or part of the steps of the above-mentioned method of the various embodiments of the present application. And the aforementioned memory includes: a U-disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a removable hard disk, a magnetic disk, or an optical disk, or other various media capable of storing program codes.
Those of ordinary skill in the art will appreciate that all or a portion of the steps in the various methods of the above embodiments may be implemented by a program that instructs associated hardware, and the program may be stored in a computer readable memory, which may include: flash disk, read-only memory, random access memory, magnetic or optical disk, etc.
The foregoing has outlined rather broadly the more detailed description of embodiments of the application, wherein the principles and embodiments of the application are explained in detail using specific examples, the above examples being provided solely to facilitate the understanding of the method and core concepts of the application; meanwhile, as those skilled in the art will have variations in the specific embodiments and application scope in accordance with the ideas of the present application, the present description should not be construed as limiting the present application in view of the above.

Claims (12)

1. A precoding method applied to a base station, comprising:
determining a first precoding matrix and a signal-to-noise ratio corresponding to each of N channel transmission layers, wherein N is a positive integer greater than 1;
reconstructing a first channel according to the first precoding matrix and the signal-to-noise ratio corresponding to each channel transmission layer to obtain a first channel correlation matrix, wherein the first channel correlation matrix is used for representing a second channel obtained after the first channel is reconstructed;
Performing smoothing filter processing on the first channel correlation matrix to obtain a second channel correlation matrix after the smoothing filter processing;
and determining a second precoding matrix according to the second channel correlation matrix.
2. The method of claim 1, wherein after the determining the first precoding matrix and the corresponding signal-to-noise ratio for each of the N channel transport layers, the method further comprises:
determining a relative weighting coefficient of each channel transmission layer pair according to the signal-to-noise ratio of each channel transmission layer;
the reconstructing the first channel according to the first precoding matrix and the signal-to-noise ratio corresponding to each channel transmission layer includes:
and reconstructing the first channel according to the first precoding matrix and the relative weighting coefficient of each channel transmission layer.
3. The method of claim 2, wherein reconstructing the first channel based on the first precoding matrix and the relative weighting coefficients of each channel transport layer to obtain a first channel correlation matrix comprises:
determining components of each channel transmission layer according to the first precoding matrix and the relative weighting coefficient of each channel transmission layer to obtain N components;
And carrying out weighted summation on the N components to obtain the first channel correlation matrix.
4. A method according to claim 2 or 3, wherein said smoothing the first channel correlation matrix to obtain a second channel correlation matrix after said smoothing, comprises:
acquiring a plurality of transmission time intervals;
and carrying out smoothing filter processing on the first channel correlation matrix according to the transmission time intervals to obtain the second channel correlation matrix after smoothing processing.
5. The method of claim 4, wherein the plurality of transmission time intervals comprises a first transmission time interval and a second transmission time interval, wherein the first transmission time interval is earlier than the second transmission time interval;
and performing smoothing filtering processing on the first channel correlation matrix according to the multiple transmission time intervals to obtain a second channel correlation matrix after the smoothing processing, where the smoothing processing includes:
determining a first instantaneous channel correlation matrix reconstructed by the first transmission time interval and a second instantaneous channel correlation matrix reconstructed by the second transmission time interval;
determining a filtering factor;
And obtaining the smoothed second channel correlation matrix according to the filtering factor, the first instantaneous channel correlation matrix and the second instantaneous channel correlation matrix.
6. The method of claim 1, wherein the determining the first precoding matrix comprises:
acquiring channel state information and a codebook reported by terminal equipment;
and determining the first precoding matrix according to the channel state information and the codebook.
7. A precoding method applied to a terminal device, comprising:
acquiring CQI information corresponding to N channel transmission layers, wherein N is a positive integer greater than 1;
and determining a signal-to-noise ratio of each channel transmission layer according to the CQI information, wherein the signal-to-noise ratio is used for determining a relative weighting coefficient corresponding to each channel transmission layer, the relative weighting coefficient corresponding to each channel transmission layer is used for reconstructing a first channel according to a first coding matrix to obtain a first channel correlation matrix, the first coding matrix is determined by channel state information and a codebook reported by the terminal equipment, the first channel correlation matrix is used for smoothing filtering to obtain a second channel correlation matrix, and the second channel correlation matrix is used for determining a second precoding matrix.
8. The method of claim 7, wherein prior to the obtaining CQI information for the N channel transport layers, the method further comprises:
acquiring a channel rank indication;
and determining CQI information corresponding to the N channel transmission layers to be reported according to the channel rank indication.
9. A precoding device applied to a base station, the device comprising: a determining unit, a reconstructing unit and a filtering unit, wherein,
the determining unit is configured to determine a first precoding matrix and a signal-to-noise ratio corresponding to each of N channel transmission layers, where N is a positive integer greater than 1;
the reconstruction unit is configured to reconstruct a first channel according to the first precoding matrix and a signal-to-noise ratio corresponding to each channel transmission layer to obtain a first channel correlation matrix, where the first channel correlation matrix is used to characterize a second channel obtained after the first channel is reconstructed;
the filtering unit is used for carrying out smoothing filtering processing on the first channel correlation matrix to obtain a second channel correlation matrix after the smoothing filtering processing;
the determining unit is further configured to determine a second precoding matrix according to the second channel correlation matrix.
10. A precoding device applied to a terminal device, the device comprising: an acquisition unit and a determination unit, wherein,
the acquiring unit is configured to acquire CQI information corresponding to N channel transport layers, where N is a positive integer greater than 1;
the determining unit is configured to determine, according to the CQI information, a signal-to-noise ratio of each channel transport layer, where the signal-to-noise ratio is used to determine a relative weighting coefficient corresponding to each channel transport layer, and the relative weighting coefficient corresponding to each channel transport layer is used to reconstruct a first channel according to a first coding matrix to obtain a first channel correlation matrix, where the first coding matrix is determined by channel state information and a codebook reported by the terminal device, and the first channel correlation matrix is used to perform smoothing filtering processing to obtain a second channel correlation matrix, and the second channel correlation matrix is used to determine a second precoding matrix.
11. An electronic device comprising a processor, a memory, a communication interface, and one or more programs stored in the memory and configured to be executed by the processor, the programs comprising instructions for performing the steps in the method of any of claims 1-6 or 7-8.
12. A computer-readable storage medium, characterized in that a computer program for electronic data exchange is stored, wherein the computer program causes a computer to perform the method according to any of claims 1-6 or 7-8.
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Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR20120127391A (en) * 2010-01-18 2012-11-21 엘지전자 주식회사 A method and an apparatus for providing channel quality information in a wireless communication system
JP2013126011A (en) * 2011-12-13 2013-06-24 Nippon Telegr & Teleph Corp <Ntt> Radio transmission method and radio transmitter
JP2013214970A (en) * 2012-03-31 2013-10-17 Fujitsu Ltd Channel estimation method and facility

Family Cites Families (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR101426788B1 (en) * 2007-11-20 2014-08-06 삼성전자주식회사 Apparatus and method for reporting channel quality indicator in wireless communication system
CN102624432B (en) * 2011-01-26 2017-04-05 中兴通讯股份有限公司 Multilamellar beam-forming method and realize the terminal of multilamellar beam shaping
US9191256B2 (en) * 2012-12-03 2015-11-17 Digital PowerRadio, LLC Systems and methods for advanced iterative decoding and channel estimation of concatenated coding systems

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR20120127391A (en) * 2010-01-18 2012-11-21 엘지전자 주식회사 A method and an apparatus for providing channel quality information in a wireless communication system
JP2013126011A (en) * 2011-12-13 2013-06-24 Nippon Telegr & Teleph Corp <Ntt> Radio transmission method and radio transmitter
JP2013214970A (en) * 2012-03-31 2013-10-17 Fujitsu Ltd Channel estimation method and facility

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