CN106941367A - Multiple-input and multiple-output MIMO processing method and processing device - Google Patents

Abstract

The invention provides a kind of multiple-input and multiple-output MIMO processing method and processing device, wherein, this method includes：Base station obtains channel condition information of the terminal on row channel in base station range, and selects multiple terminals of the related sexual satisfaction preparatory condition of terminal according to channel condition information, wherein, row channel is the transmission channel between antenna in terminal and base station vertical direction；Base station determines that multiple terminals carry out the beamforming vector that pre-coding matrix calculating is obtained in vertical direction according to channel condition information；Base station obtains horizontal channel corresponding with beamforming vector according to beamforming vector, and pre-coding matrix calculating is carried out in the horizontal direction of horizontal channel by preset rules.By the present invention, solve 3D MIMO pre-coding matrix computings in correlation technique complexity it is high the problem of.

Description

Multiple-input multiple-output MIMO processing method and device

technical field

The present invention relates to the communication field, in particular, to a multiple-input multiple-output MIMO processing method and device.

Background technique

A large-scale multiple-input multiple-output (MIMO) system can greatly improve the system spectral efficiency and system capacity, but in the actual system, due to the limitation of the antenna size and the space of the base station, it is impossible to Place a large number of antennas. To solve this problem, 3D-MIMO (3-Dimension MIMO), which may also be called (Full-Dimension MIMO, FD-MIMO for short), is introduced to solve the practical implementation problem of massive MIMO. In the 3D-MIMO system, the base station uses a 2D area array active antenna. In this way, the signals between the user and the base station can be transmitted not only in the horizontal direction, but also in the vertical direction, and the vertical degree of freedom of the channel can be tapped. Therefore, the 3D-MIMO precoding design is not limited to the traditional horizontal direction, and user beamforming vectors can also be designed in the vertical direction, so as to better achieve interference suppression.

Precoding methods in traditional MIMO systems, such as Singular Value Decomposition (SVD for short), Zero Forcing (ZF for short), and Signal to Leakage and Noise Ratio (Signal to Leakage and Noise Ratio for short, SLNR for short) ) can achieve better performance. However, in 3D-MIMO with a large number of antennas, as the number of antennas increases, the computational complexity of these algorithms will also increase. Therefore, it is very necessary to conduct research on low-complexity 3D-MIMO precoding algorithms. The 3D-MIMO precoding research in related technologies, one is to obtain a simpler solution form through mathematical approximation to reduce the computational complexity; the other is to use the structural characteristics of the 2D area array to design two dimensions, so A reduction in complexity is achieved. Although the first type can reduce the computational complexity to a certain extent, the number of antennas increases and the dimension of the channel matrix is very large, which will inevitably lead to a high complexity of matrix operation; the second type is to fundamentally reduce the performance of 3D-MIMO. The complexity is generally achieved through two-step precoding design in the vertical and horizontal directions. However, most of the current discussions on this method are carried out in single-user MIMO scenarios, which is not realistic.

There is no effective solution to the problem of high complexity of 3D-MIMO precoding matrix calculation in the related art.

Contents of the invention

The present invention provides a multiple-input multiple-output MIMO processing method and device to at least solve the problem of high complexity of 3D-MIMO precoding matrix calculation in the related art.

According to one aspect of the present invention, a multiple-input multiple-output (MIMO) processing method is provided, including: the base station obtains channel state information of the terminal on the column channel within the coverage of the base station, and selects the relevant channel of the terminal according to the channel state information. a plurality of terminals that meet preset conditions, wherein the column channel is a transmission channel between the terminal and the antenna in the vertical direction of the base station; the base station determines that the plurality of terminals are vertically The beamforming vector obtained by calculating the precoding matrix in the direction; the base station obtains the horizontal channel corresponding to the beamforming vector according to the beamforming vector, and uses preset rules in the horizontal direction of the horizontal channel Calculate the precoding matrix.

Further, the acquiring the channel state information of the terminal within the coverage of the base station by the base station includes: the base station sending a channel state information reference symbol CSI-RS to the terminal within the coverage of the base station; the base station receiving the terminal according to Channel state information sent after the CSI-RS measures the channel.

Further, the selecting by the base station according to the channel state information a plurality of terminals whose terminal correlation satisfies a preset condition includes: the base station predetermines a predetermined number of the plurality of terminals satisfying a preset condition; According to the channel state information, the terminal with the best channel characteristics is selected as the initial terminal; the base station obtains multiple chordal distances between the selected initial terminal and multiple terminals to be selected; A predetermined number of the plurality of terminals that are farthest from the initial terminal chord are selected from the chord distances.

Further, before the base station determines the beamforming vectors obtained by calculating the precoding matrix of the multiple terminals in the vertical direction according to the channel state information, the method further includes: the base station configures a 2D uniform plane array UPA, wherein, the 2D uniform planar array UPA includes: N _t = N _h × N _v root antennas, N _h is the number of column antennas in the horizontal direction, N _v is the number of row antennas in the vertical direction, and the base station is the Each of the k terminals randomly distributed in each cell of the base station is configured with N _r =1 antenna; H _k represents the 3D channel matrix from the kth terminal to the base station (N _r ×(N _h ×N _v ) dimension), the Represents the channel matrix (N _r ×N _v dimension) from the user to the i-th column antenna of the base station, i=1, 2...N _h , k is a positive integer, and the value is 1, 2,..., S, where S represents The current number of users in the group.

Further, the base station determines the beamforming vector obtained by performing the precoding matrix calculation of the plurality of terminals in the vertical direction according to the channel state information according to the following formula: the base station calculates the beamforming vector according to each column of channel information Calculate the beamforming vector for the vertical direction ((N _h ×N _v )×N _h dimensions), as shown in the following formula: Among them, the channel information of each column is Represents the i-th column channel matrix (N _r ×N _v dimensions) of the k-th user; the beamforming vector in the vertical direction ((N _h ×N _v )×N _h dimensions), The eigenvector corresponding to the largest generalized eigenvalue of , P is the transmit power, _nk is the noise received by each terminal, and σ ² is the noise power.

Further, the base station obtains a horizontal channel corresponding to the beamforming vector according to the beamforming vector, and performing precoding matrix calculation in the horizontal direction of the horizontal channel according to a preset rule includes: the base station The beamforming vector Applied to each vertical channel, the horizontal channel is calculated by the following formula: The dimension is N _r ×N _h , and the value of k is 1, 2, ..., S; the base station uses the zero-forcing ZF criterion to calculate the multiple terminal precoding matrices in the horizontal direction on the horizontal channel make ((N _r ×S)×N _h dimensions), and then the formula for obtaining the precoding matrix is (N _h ×S dimension), where each column represents the equivalent horizontal precoding matrix of the corresponding user, namely is the kth column of the above matrix, representing the equivalent horizontal precoding matrix of the kth user, where, represents the equivalent horizontal channel of the kth user, yes The conjugate transposition of .

According to another aspect of the present invention, a multiple-input multiple-output MIMO processing device is provided, which is applied to the base station side, and includes: an acquisition module, configured to acquire channel state information of a terminal on a column channel within the coverage of the base station, And according to the channel state information, select a plurality of terminals whose terminal correlation meets the preset condition, wherein the column channel is a transmission channel between the terminal and the antenna in the vertical direction of the base station; the determining module is used to determine according to the The channel state information determines the beamforming vector obtained by performing precoding matrix calculation in the vertical direction on the plurality of terminals; the processing module is used to obtain the horizontal channel corresponding to the beamforming vector according to the beamforming vector , and calculate the precoding matrix in the horizontal direction of the horizontal channel according to a preset rule.

Further, the obtaining module includes: a sending unit, configured to send a channel state information reference symbol CSI-RS to a terminal within the coverage of the base station; a receiving unit, configured to receive the channel state information reference symbol CSI-RS from the terminal according to the CSI-RS Channel state information sent after a measurement has been taken.

Further, the obtaining module further includes: a determining unit, configured to predetermine a predetermined number of the plurality of terminals satisfying a preset condition; a first selecting unit, configured to select the terminal with the best channel characteristic according to the channel state information. The terminal is used as the initial terminal; the obtaining unit is used to obtain multiple chord distances between the selected initial terminal and multiple terminals to be selected; the second selection unit is used to select from the multiple chord distances A predetermined number of the plurality of terminals that are farthest from the initial terminal chord are selected.

Further, before the base station determines the beamforming vectors obtained by calculating the precoding matrix of the multiple terminals in the vertical direction according to the channel state information, the device further includes: a first configuration module configured to configure 2D uniform area array UPA, wherein, the 2D uniform area array UPA includes: N _t =N _h ×N _v root antennas, N _h is the number of column antennas in the horizontal direction, N _v is the number of row antennas in the vertical direction, and the second A configuration module, configured to configure N _r =1 antenna for each of the k terminals randomly distributed in each cell of the base station; H _k represents the 3D channel matrix (N) from the kth terminal to the base station _r ×(N _h ×N _v ) dimension), the Indicates the channel matrix (N _r ×N _v dimension) from the user to the i-th antenna of the base station, i=1,2...N _h , and k is a positive integer.

Further, the determining module is also used for channel information of each column Calculate the beamforming vector for the vertical direction ((N _h ×N _v )×N _h dimensions), as shown in the following formula:

Among them, the channel information of each column is Represents the i-th column channel matrix (N _r ×N _v dimensions) of the k-th user; the beamforming vector in the vertical direction ((N _h ×N _v )×N _h dimensions), The eigenvector corresponding to the largest generalized eigenvalue of , P is the transmit power, _nk is the noise received by each terminal, and σ ² is the noise power.

Further, the processing module includes: a first calculation unit, configured to convert the beamforming vector Applied to each vertical channel, the horizontal channel is calculated as shown in the following formula: The dimension is N _r ×N _h , and the value of k is 1, 2, ..., S; the second calculation unit is used to calculate the multiple terminal precoding matrices in the horizontal direction on the horizontal channel using the zero-forcing ZF criterion make ((N _r ×S)×N _h dimensions), and then the formula for obtaining the precoding matrix is (N _h ×S dimension), where each column represents the equivalent horizontal precoding matrix of the corresponding user, namely is the kth column of the above matrix, representing the equivalent horizontal precoding matrix of the kth user, where, represents the equivalent horizontal channel of the kth user, yes The conjugate transposition of .

Through the present invention, the base station obtains the channel state information of the terminal on the column channel within the coverage of the base station, and selects multiple terminals whose terminal correlation meets the preset condition according to the channel state information, wherein the column channel is the antenna in the vertical direction between the terminal and the base station The transmission channel between; then the base station determines the beamforming vector obtained by performing the precoding matrix calculation of multiple terminals in the vertical direction according to the channel state information, and obtains the horizontal channel corresponding to the beamforming vector according to the beamforming vector, and passes The preset rule calculates the precoding matrix in the horizontal direction of the horizontal channel. It can be seen that in this embodiment, by analyzing the channel characteristics, a suitable set of service terminals is selected, and then the two-step precoding for channel dimensionality is used to realize multi-user precoding. The coding design can achieve better performance compared with the MIMO system that only designs the horizontal direction precoding matrix in the related art, and at the same time reduces the computational complexity, thereby solving the high complexity of the 3D-MIMO precoding matrix operation in the related art The problem.

Description of drawings

The accompanying drawings described here are used to provide a further understanding of the present invention and constitute a part of the application. The schematic embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute improper limitations to the present invention. In the attached picture:

FIG. 1 is a flowchart of a MIMO processing method according to an embodiment of the present invention;

FIG. 2 is a structural block diagram of a MIMO processing device according to an embodiment of the present invention;

FIG. 3 is an optional structural block diagram 1 of a MIMO processing device according to an embodiment of the present invention;

FIG. 4 is an optional structural block diagram II of a MIMO processing device according to an embodiment of the present invention;

FIG. 5 is an optional structural block diagram 3 of a MIMO processing device according to an embodiment of the present invention;

FIG. 6 is a structural diagram of a 3D MU-MIMO system according to an optional embodiment of the present invention;

Fig. 7 is a schematic diagram of comparison of CDF curves of SINR of three schemes under the base station 8*8 uniform area array antenna configuration according to an optional embodiment of the present invention;

Fig. 8 is a schematic diagram of comparison of CDF curves of SINR of three schemes under the base station 8*16 uniform array antenna configuration according to an optional embodiment of the present invention;

FIG. 9 is a schematic diagram of comparison of spectral efficiency per user of different schemes when the base station deploys different numbers of antennas in the vertical direction according to an optional embodiment of the present invention;

Fig. 10 is a schematic diagram of CDF curves of different schemes of SINR when the maximum SLNR criterion is used instead of the second-step precoding ZF criterion according to an optional embodiment of the present invention.

detailed description

Hereinafter, the present invention will be described in detail with reference to the drawings and examples. It should be noted that, in the case of no conflict, the embodiments in the present application and the features in the embodiments can be combined with each other.

It should be noted that the terms "first" and "second" in the description and claims of the present invention and the above drawings are used to distinguish similar objects, but not necessarily used to describe a specific sequence or sequence.

In this embodiment, a MIMO processing method is provided. FIG. 1 is a flowchart of a MIMO processing method according to an embodiment of the present invention. As shown in FIG. 1 , the process includes the following steps :

Step S102: The base station obtains the channel state information of the terminal on the column channel within the coverage of the base station, and selects multiple terminals whose terminal correlation meets the preset conditions according to the channel state information, where the column channel is the distance between the terminal and the antenna in the vertical direction of the base station. the transmission channel;

Step S104: The base station determines the beamforming vectors obtained by calculating the precoding matrix in the vertical direction for multiple terminals according to the channel state information;

Step S106: The terminal obtains the horizontal channel corresponding to the beamforming vector according to the beamforming vector, and calculates the precoding matrix in the horizontal direction of the horizontal channel according to a preset rule.

Through the embodiment of the present invention, the base station obtains the channel state information of the terminal on the column channel within the coverage of the base station, and selects multiple terminals whose terminal correlation meets the preset condition according to the channel state information, wherein the column channel is the vertical direction between the terminal and the base station The transmission channel between the upper antennas; and then the base station determines the beamforming vector obtained by calculating the precoding matrix in the vertical direction for multiple terminals according to the channel state information, and obtains the horizontal channel corresponding to the beamforming vector according to the beamforming vector, And calculate the precoding matrix in the horizontal direction of the horizontal channel through the preset rules. It can be seen that in this embodiment, by analyzing the channel characteristics, a suitable set of service terminals is selected, and then the two-step precoding for channel dimensionality is used to realize multiple The user precoding design, compared with the MIMO system that only designs the horizontal direction precoding matrix in the related art, can achieve better performance, and at the same time reduce the computational complexity, thus solving the complex operation of the 3D-MIMO precoding matrix in the related art high degree of problem.

Regarding the manner in which the base station involved in step S102 of this embodiment obtains the channel state information of the terminal within the coverage of the base station, in an optional implementation manner of this embodiment, it may be implemented in the following manner:

Step S102-1: the base station sends a channel state information reference symbol CSI-RS to terminals within the coverage of the base station;

Step S102-2: the base station receives the channel state information sent by the terminal after measuring the channel according to the CSI-RS.

Based on the above step S102-1 and step S102-2, after the base station obtains the channel state information, it selects multiple terminals whose terminal correlation meets the preset conditions according to the channel state information, and the method of obtaining multiple terminals includes:

Step S102-3: the base station predetermines a predetermined number of multiple terminals that meet the preset condition;

Step S102-4: The base station selects the terminal with the best channel characteristics as the initial terminal according to the channel state information;

Step S102-5: the base station obtains multiple chordal distances between the selected initial terminal and multiple terminals to be selected;

Step S102-6: the base station selects a predetermined number of multiple terminals whose chord distances are farthest from the initial terminal from the multiple chord distances.

In another optional implementation manner of this embodiment, before the base station determines the beamforming vectors obtained by calculating the precoding matrix in the vertical direction for multiple terminals according to the channel state information, the method of this embodiment further includes:

Step S11: The base station configures a 2D uniform area array UPA, wherein the 2D uniform area array UPA includes: N _t =N _h ×N _v antennas, N _h is the number of column antennas in the horizontal direction, and N _v is the number of row antennas in the vertical direction ,

Step S12: The base station configures N _r =1 antenna for each of the k terminals randomly distributed in each cell of the base station; H _k represents the 3D channel matrix from the kth terminal to the base station (N _r ×(N _h ×N _v ) dimension), Represents the channel matrix (N _r ×N _v dimension) from the user to the i-th column antenna of the base station, i=1, 2...N _h , k is a positive integer, and the value of k is 1, 2, ..., S, where S represents the number of users in the current group.

Based on the above step S11 and step S12, the base station in this embodiment determines the beamforming vector obtained by calculating the precoding matrix of multiple terminals in the vertical direction according to the channel state information according to the following formula:

According to the channel information of each column, the base station Calculate the beamforming vector in the vertical direction ((N _h ×N _v )×N _h dimensions), as shown in the following formula:

Among them, the channel information of each column is Represents the i-th column channel matrix (N _r ×N _v dimensions) of the k-th user; the beamforming vector in the vertical direction ((N _h ×N _v )×N _h dimensions), The eigenvector corresponding to the largest generalized eigenvalue of , P is the transmit power, _nk is the noise received by each terminal, and σ ² is the noise power.

Based on the above beamforming vector, the base station involved in this embodiment obtains the horizontal channel corresponding to the beamforming vector according to the beamforming vector, and calculates the precoding matrix in the horizontal direction of the horizontal channel through preset rules , which can be achieved by:

Step S21: The base station converts the beamforming vector Applied to each vertical channel, the horizontal channel is calculated as shown in the following formula: The dimension is N _r ×N _h , and the value of k is 1, 2, ..., S;

Step S22: The base station uses the zero-forcing ZF criterion to calculate multiple terminal precoding matrices in the horizontal direction on the horizontal channel make ((N _r ×S)×N _h dimensions), and then the formula for obtaining the precoding matrix is (N _h ×S dimension), where each column represents the equivalent horizontal precoding matrix of the corresponding user, namely is the kth column of the above matrix, representing the equivalent horizontal precoding matrix of the kth user. in, represents the equivalent horizontal channel of the kth user, yes The conjugate transposition of .

Through the description of the above embodiments, those skilled in the art can clearly understand that the method according to the above embodiments can be implemented by means of software plus a necessary general-purpose hardware platform, and of course also by hardware, but in many cases the former is better implementation. Based on such an understanding, the essence of the technical solution of the present invention or the part that contributes to the prior art can be embodied in the form of software products, and the computer software products are stored in a storage medium (such as ROM/RAM, disk, CD) contains several instructions to enable a terminal device (which may be a mobile phone, a computer, a server, or a network device, etc.) to execute the methods described in various embodiments of the present invention.

In this embodiment, a multiple-input multiple-output MIMO processing device is also provided, and the device is used to implement the above-mentioned embodiments and preferred implementation manners, and those that have already been described will not be repeated. As used below, the term "module" may be a combination of software and/or hardware that realizes a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, implementations in hardware, or a combination of software and hardware are also possible and contemplated.

FIG. 2 is a structural block diagram of a multiple-input multiple-output MIMO processing device according to an embodiment of the present invention. The device is applied to the base station side. As shown in FIG. The channel state information on the column channel, and select multiple terminals whose terminal correlation meets the preset conditions according to the channel state information, wherein the column channel is the transmission channel between the terminal and the antenna in the vertical direction of the base station; the determination module 24, and the acquisition module 22 is coupled and connected, and is used to determine the beamforming vector obtained by performing the precoding matrix calculation of multiple terminals in the vertical direction according to the channel state information; the processing module 26 is coupled and connected to the determining module 24, and is used to obtain the beamforming vector according to the beamforming vector The horizontal channel corresponding to the beamforming vector, and the calculation of the precoding matrix is performed in the horizontal direction of the horizontal channel according to a preset rule.

FIG. 3 is an optional structural block diagram 1 of a MIMO processing device according to an embodiment of the present invention. As shown in FIG. 3 , the acquisition module 22 includes: a sending unit 302 configured to send channels to terminals within the coverage of the base station The state information refers to CSI-RS; the receiving unit 304 is coupled to the sending unit 302, and is used for receiving the channel state information sent by the terminal after measuring the channel according to the CSI-RS.

In addition, the acquisition module 22 also includes: a determining unit 306, coupled to the receiving unit 304, used to predetermine a predetermined number of multiple terminals satisfying preset conditions; a first selection unit 308, coupled to the determining unit 306, used to According to the channel state information, the terminal with the best channel characteristics is selected as the initial terminal; the obtaining unit 310 is coupled to the selection unit 308, and is used to obtain multiple chords between the selected initial terminal and multiple terminals to be selected. Distance; the second selection unit 312, coupled to the acquisition unit 310, is configured to select a predetermined number of terminals that are farthest from the initial terminal chord from the multiple chord distances.

Fig. 4 is an optional structural block diagram 2 of a MIMO processing device according to an embodiment of the present invention. As shown in Fig. 4 , the base station determines that multiple terminals perform precoding matrix calculation in the vertical direction according to the channel state information Before the beamforming vector, the device further includes: a first configuration module 42 coupled to a second configuration module 44 for configuring a 2D uniform plane array UPA, wherein the 2D uniform plane array UPA includes: N _t =N _h ×N _v root antennas, N _h is the number of antennas in the horizontal direction, and N _v is the number of antennas in the vertical direction; the second configuration module 44 is coupled and connected with the acquisition module 22, and is used for randomly distributed k in each sub-district of the base station Each of the terminals is configured with N _r =1 antenna; H _k represents the 3D channel matrix (N _r ×(N _h ×N _v ) dimension) from the kth terminal to the base station, Indicates the channel matrix (N _r ×N _v dimension) from the user to the i-th antenna of the base station, i=1,2...N _h , and k is a positive integer.

Based on the first configuration module 42 and the second configuration module in FIG. 4, the determination module 24 involved in this embodiment is also used to Calculate the beamforming vector in the vertical direction ((N _h ×N _v )×N _h dimensions), as shown in the following formula:

Among them, the channel information of each column is Represents the i-th column channel matrix (N _r ×N _v dimensions) of the k-th user; the beamforming vector in the vertical direction ((N _h ×N _v )×N _h dimensions), The eigenvector corresponding to the largest generalized eigenvalue of , P is the transmit power, _nk is the noise received by each terminal, and σ ² is the noise power.

FIG. 5 is an optional structural block diagram three of a MIMO processing device according to an embodiment of the present invention. As shown in FIG. Applied to each vertical channel, the horizontal channel is calculated as shown in the following formula: The second calculation unit 54 is coupled and connected with the first calculation unit 52, and is used to calculate multiple terminal precoding matrices in the horizontal direction on the horizontal channel using the zero-forcing ZF criterion make ((N _r ×S)×N _h dimensions), and then the formula for obtaining the precoding matrix is (N _h ×S dimension), where each column represents the equivalent horizontal precoding matrix of the corresponding user, namely is the kth column of the above matrix, representing the equivalent horizontal precoding matrix of the kth user. in, represents the equivalent horizontal channel of the kth user, yes The conjugate transposition of .

It should be noted that each of the above-mentioned modules can be implemented by software or hardware. For the latter, it can be implemented in the following manner, but not limited to this: the above-mentioned modules are all located in the same processor; or, the above-mentioned modules are respectively located in multiple in the processor.

The present invention will be illustrated below in conjunction with optional embodiments of the present invention;

This optional embodiment provides a method for reducing system complexity. The technical solution of the method is outlined as two-step precoding and a user selection solution applicable to 3D scenes. The detailed process may be: the base station selects users according to the column-channel correlation of users (corresponding to the terminals in the above embodiments), and selects users with poor column-channel correlation and serving on the same time-frequency resource. Then perform two-step precoding: the first step: design the beamforming vector in the vertical direction according to the column channel information of the user, so as to achieve the purpose of distinguishing the users in the vertical direction first; the second step: use the vertical beamforming vector designed in the first step The beamforming vector is used to calculate the equivalent horizontal channel, and then according to the equivalent horizontal channel, a zero-forcing (ZF) method is used to design the precoding matrix in the horizontal direction. It should be noted that the column channel refers to the transmission channel between the user and a certain column of antennas in the vertical direction of the base station. Through the above method of this optional embodiment, the interference between users can be greatly reduced.

The following further describes the process of the transmission method for reducing system complexity in this optional embodiment:

FIG. 6 is a structural diagram of a 3D MU-MIMO system according to an optional embodiment of the present invention. As shown in FIG. 6, the base station deploys a 2D uniform area array (UPA), and BS represents a base station; MS represents a user; the system contains a base station and K randomly distributed users, the base station configures a 2D uniform area array (UPA), including N _t = N _h × N _v antennas, N _h is the number of column antennas in the horizontal direction, N _v is the number of row antennas in the vertical direction, Each user is equipped with N _r =1 antenna. H _k represents the 3D channel matrix (N _r ×(N _h ×N _v ) dimension) from the kth user to the base station. For the convenience of subsequent representation, let in (i=1,2...N _h ) represents the channel matrix (N _r ×N _v dimensions) from the user to the i-th column of antennas. Assume that the transmit power of the base station is P, the receiving noise of each user is _nk , and the noise power is σ ² .

The received signal y _k of user k can be expressed as:

Wherein, in the formula (1), x _k is the sending signal of the kth user; Represents the vertical precoding matrix of the kth user, where is a N _v ×1-dimensional vector, and (N _h ×1 dimension, ) represents the precoding matrix of the kth user in the horizontal direction. The receiving signal-to-interference-noise ratio (SINR) of the kth user can be obtained from formula (1), as shown in formula (2):

The total spectral efficiency of the system and the average spectral efficiency per user are shown in formula (3) and formula (4) respectively:

Based on the above analysis, the technical solution of the low-complexity 3D MU-MIMO transmission solution provided in this optional embodiment is as follows:

In the first stage, the base station sends CSI-RS to the user, and the user measures the channel state information according to the received CSI-RS, and then feeds back the channel state information to the base station. User selection, selecting S (S≤N _h ) user sets with small vertical user correlation for service. The user-selected method steps include:

Step S41: Define the initial user set Ω={1,2,...K}, initialize the selected user set

Step S42: Select the first user using proportional fairness (PF) criterion, namely: Update the remaining user set Ω=Ω-{s ₁ } and the selected user set γ=γ+{s ₁ }, and let represents the ith column of the channel matrix of the initial user;

Step S43: For l=2:S users, select according to the maximal chord distance criterion Update the remaining users and the selected set Ω=Ω-{s _l }, γ=γ+{s _l }, and update

Step S44: After the Sth user is selected, the loop ends, and the algorithm terminates.

It should be noted that the chord distance: is a quantity that characterizes the correlation between matrices (vectors), and the larger the chord distance, the smaller the correlation between matrices (vectors). It is defined as follows:

in is the orthonormal basis obtained after Schmidt orthogonalization of matrices (vectors) H ₁ and H ₂ .

In the second stage, the calculation of the two-step precoding matrix is performed on the selected user set at the base station, which is divided into the following two steps:

The first step: the base station according to the channel information of each column of the user Calculate the beamforming vector for each column in the vertical direction based on the criterion of maximizing the vertical signal-to-leakage-to-noise ratio (SLNR) (N _v ×1 dimension), as shown in the following formula:

Among them, st k=1,...,S

The solution to this problem is: The eigenvector corresponding to the largest generalized eigenvalue of (6)

in, Indicates the i-th column channel matrix (N _r ×N _v dimensions) of the k-th user.

Thus, the final precoding matrix in the vertical direction is:

The second step: the vertical beamforming vector obtained in the first step Applied to each vertical channel, the equivalent horizontal channel is obtained as follows:

Then use the zero-forcing (ZF) criterion to design the multi-user precoding matrix in the horizontal direction make

in represents the equivalent horizontal channel of the kth user, yes The conjugate transposition of . Then the horizontal precoding matrix looks like this:

The above process will be described below in conjunction with the flow of this optional embodiment;

1. Acquisition of channel status information of the base station:

Step S31: the base station sends a channel state information reference symbol (CSI-RS) to the user;

Step S32: The user performs channel measurement according to the received CSI-RS;

Step S33: the user feeds back the measured channel to the base station;

2. User selection, the process can be:

According to the number of users served, the base station defines the initial user set Ω={1,2,...K}, and initializes the selected user set

According to the obtained user channel state information, first select a user with the largest column channel norm as the selected initial user, that is, And update the remaining users and the selected user collection, Ω=Ω-{s ₁ }, γ=γ+{s ₁ };

For l=2:S users, select according to the maximal chord distance criterion Update remaining users and selected collections Ω=Ω-{s _l }, γ=γ+{s _l }

After the Sth user is selected, the loop ends and the algorithm terminates.

3. Precoding:

The base station obtains the beamforming vector in the vertical direction according to the solution of (5) above The base station gets the vertical beamforming vector Then calculate the horizontal direction precoding matrix according to formulas (8) to (10) After the user selection and precoding operations are completed, signal transmission is performed according to the signal model of formula (1). It should be noted that the SNR refers to the ratio of the target user's signal power to the sum of the interference power and noise power leaked to other users.

It can be seen that the user selection scheme applicable to the two-step precoding in the 3DMIMO system provided by this optional embodiment adopts that before precoding, user selection is performed according to the channel correlation of the user column, and the user column with poor channel correlation is selected. The user then performs the service. 2) A new two-step 3D multi-user precoding scheme is given, which is different from the traditional single-step precoding and the existing two-step precoding: In the first step, according to the vertical SLNR maximization criterion, design Beamforming is performed in the vertical direction, and the weight vectors of the antennas in each column are the same; in the second step, MU-MIMO precoding is performed in the horizontal direction using the equivalent channel.

The following describes this optional embodiment in detail in conjunction with specific embodiments of the optional embodiment of the present invention;

Embodiment one:

In this optional embodiment, taking 100 users in a 3D-UMi single cell as an example, the channel between the base station and the users is a WINNER II/+3D channel model. The base station configures an 8*8 uniform array of antennas, that is, 8 rows of antennas in the horizontal direction and 8 columns of antennas in the vertical direction, and the horizontal and vertical antenna spacing is 0.5λ (λ indicates the wavelength). Each user is equipped with a single antenna. The downtilt angle of the antenna is set to 16 degrees. Base station transmit power Power=44dBm, noise power Noise=-174dBm/Hz. Simulate 20 Drops, each containing 100 TTIs.

Fig. 7 is a schematic diagram of comparing the CDF curves of the SINR of the three schemes under the base station 8*8 uniform area array antenna configuration according to an optional embodiment of the present invention. As shown in Fig. 7, this simulation compares this scheme with the traditional one without vertical beam The shaping scheme (marked as: NV scheme in Fig. 7) and the random beamforming scheme (marked as: RV scheme in Fig. 7) in the vertical direction are compared; the scheme of this optional embodiment is compared with the NV scheme and the RV scheme . The cumulative distribution (CDF) curves of the signal-to-interference-noise ratio (SINR) of the three schemes are compared as shown in FIG. 7 . Under the configuration of 8*8 antennas, the user SINR distribution of the scheme of this optional embodiment is obviously better than that of the NV scheme and the RV scheme. Table 1 shows the average spectral efficiency per user under the configuration of 8*8 antennas. It can be seen that the solution of this optional embodiment improves 20.64% compared with the NV solution, and the RV solution can only improve 10.04% compared with the NV solution.

Table 1

Embodiment two:

This optional embodiment has the same application scenario as the first embodiment, except that the antenna configuration of the base station is changed to an 8*16 uniform array, that is, the number of antennas in the vertical direction is changed to 16.

Figure 8 is a schematic diagram of the comparison of the CDF curves of the SINR of the three schemes under the base station 8*16 uniform array antenna configuration according to an optional embodiment of the present invention. The scheme of the second embodiment is compared with the NV scheme and the RV scheme, and the three schemes The CDF curve of the user SINR of the solution is shown in FIG. 8 , and this optional embodiment can achieve better performance under the configuration of 8*16 antennas. Fig. 9 is a schematic diagram of comparing the spectral efficiency of each user in different schemes when the base station deploys different numbers of antennas in the vertical direction according to an optional embodiment of the present invention. As shown in Fig. 9, the number of antennas in the vertical direction is 8 and 16 When comparing the average spectral efficiency of each user, it can be seen that when the number of vertical antennas is 16, a higher user spectral efficiency can be achieved than when the number of vertical antennas is 8. Further, Table 2 shows the average spectral efficiency per user under the configuration of 8*16 antennas. It can be seen from Table 2 that when the number of antennas in the vertical direction is 16, the average spectral efficiency per user in this optional embodiment is better than that of the NV scheme Compared with the NV scheme, the RV scheme can only improve the performance by 21.17%.

Table 2

algorithm Average spectral efficiency per user (bit/s/Hz) Percentage growth compared with NV scheme (%) The second embodiment 1.3508 38.57 RV plan 1.1812 21.17 NV plan 0.9748

Embodiment three:

For the precoding involved in the above, in this embodiment, the base station adopts an alternative criterion of maximizing SLNR, and other application scenario parameters are the same as those in Embodiment 1.

In this scenario, this embodiment is compared with the NV scheme and the RV scheme. Figure 10 is a schematic diagram of the CDF curves of different schemes SINR when the maximum SLNR criterion is used instead of the second-step precoding ZF criterion according to an optional embodiment of the present invention. As shown in Figure 10, the SINR of these three schemes is compared The cumulative distribution (CDF) curve of (SINR). It can be seen that in the case of using the maximum SLNR criterion, performance similar to that of using the ZF criterion in Embodiment 1 can be achieved. Table 3 is a table of the average spectral efficiency of each user replaced by the maximizing SLNR criterion for precoding. As shown in Table 3, the average spectral efficiency of each user in this scenario is given in step. It can be seen that the scheme of the present invention is better than the NV scheme. 22.12%, the RV scheme is 11.20% higher than the NV scheme, which shows that the second step can use the SLNR criterion to replace the ZF criterion.

table 3

algorithm Average spectral efficiency per user (bit/s/Hz) Percentage increase compared to NV scheme (%) The third embodiment 1.1797 22.12 RV plan 1.0742 11.20 NV plan 0.9660

System computational complexity analysis:

From the perspective of computational complexity, the main computational complexity of the 3D precoding algorithm of the present invention lies in the eigenvalue decomposition of the _Nv × _Nv dimensional matrix in the first step, and the eigenvalue decomposition of the _Nh × _Nh dimensional matrix in the second step. Inverse (when maximizing SLNR, find eigenvalue decomposition), the total computational complexity is Under the same number of antennas, the complexity of the traditional one-step precoding algorithm is: Ο((N _v ×N _h ) ³ ). Assuming N _v =8, N _h =8, then the complexity of the scheme of the present invention is Ο(2×8 ³ ), and the complexity of the traditional algorithm is Ο(64 ³ )=O(8 ⁵ ), thus it can be seen that the traditional algorithm The complexity is much higher than the scheme of the present invention. In addition, the user selection of the scheme of the present invention is only carried out according to the column channel (1×N _v dimension), and if the same user selection scheme is used, the traditional scheme needs to select the overall channel (1×(N _h ×N _v ) dimension), its computational complexity is also far higher than that of the solution in this embodiment. It can be seen from the above that, while ensuring the performance, this optional embodiment also greatly reduces the complexity of the system when there are many antennas.

The embodiment of the invention also provides a storage medium. Optionally, in this embodiment, the above-mentioned storage medium may be configured to store program codes for performing the following steps:

S1: The base station obtains the channel state information of the terminal on the column channel within the coverage of the base station, and selects multiple terminals whose terminal correlation meets the preset conditions according to the channel state information, where the column channel is the distance between the terminal and the antenna in the vertical direction of the base station transmission channel;

S2: The base station determines the beamforming vector obtained by calculating the precoding matrix in the vertical direction for multiple terminals according to the channel state information;

S3: The terminal obtains the horizontal channel corresponding to the beamforming vector according to the beamforming vector, and performs precoding matrix calculation in the horizontal direction of the horizontal channel according to a preset rule.

Optionally, for specific examples in this embodiment, reference may be made to the examples described in the foregoing embodiments and optional implementation manners, and details are not repeated in this embodiment.

Obviously, those skilled in the art should understand that each module or each step of the above-mentioned present invention can be realized by a general-purpose computing device, and they can be concentrated on a single computing device, or distributed in a network formed by multiple computing devices Alternatively, they may be implemented in program code executable by a computing device so that they may be stored in a storage device to be executed by a computing device, and in some cases in an order different from that shown here The steps shown or described are carried out, or they are separately fabricated into individual integrated circuit modules, or multiple modules or steps among them are fabricated into a single integrated circuit module for implementation. As such, the present invention is not limited to any specific combination of hardware and software.

The above descriptions are only preferred embodiments of the present invention, and are not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and changes. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention shall be included within the protection scope of the present invention.

Claims (12)

1. A processing method for multiple-input multiple-output MIMO, characterized in that, comprising: The base station obtains the channel state information of the terminal on the column channel within the coverage of the base station, and selects a plurality of terminals whose terminal correlation meets a preset condition according to the channel state information, wherein the column channel is the channel between the terminal and the The transmission channel between the antennas in the vertical direction of the base station; The base station determines, according to the channel state information, beamforming vectors obtained by calculating precoding matrices in the vertical direction for the multiple terminals; The base station obtains the horizontal channel corresponding to the beamforming vector according to the beamforming vector, and performs precoding matrix calculation in the horizontal direction of the horizontal channel according to a preset rule. 2. The method according to claim 1, wherein the obtaining, by the base station, the channel state information of the terminals within the coverage of the base station comprises: The base station sends a channel state information reference symbol CSI-RS to terminals within the coverage of the base station; The base station receives the channel state information sent by the terminal after measuring the channel according to the CSI-RS. 3. The method according to claim 2, wherein the base station selects a plurality of terminals whose terminal correlations meet preset conditions according to the channel state information comprising: The base station predetermines a predetermined number of the plurality of terminals satisfying a preset condition; The base station selects the terminal with the best channel characteristics as the initial terminal according to the channel state information; The base station obtains multiple chordal distances between the selected initial terminal and multiple terminals to be selected; The base station selects, from the plurality of chord distances, a predetermined number of the plurality of terminals whose chordal distances are farthest from the initial terminal. 4. The method according to claim 1, wherein before the base station determines the beamforming vectors obtained by performing precoding matrix calculation in the vertical direction on the multiple terminals according to the channel state information, the Methods also include: The base station is configured with a 2D uniform area array UPA, wherein the 2D uniform area array UPA includes: N _t =N _h ×N _v root antennas, N _h is the number of column antennas in the horizontal direction, and N _v is the number of row antennas in the vertical direction number, The base station configures N _r =1 antenna for each of the k terminals randomly distributed in each cell of the base station; H _k represents the 3D channel matrix (N _r × (N _h ×N _v ) dimension), the Represents the channel matrix (N _r ×N _v dimension) from the user to the i-th column antenna of the base station, i=1, 2...N _h , k is a positive integer, and the value is 1, 2,..., S, where S represents The current number of users in the group. 5. The method according to claim 4, wherein the base station determines the beamforming vectors obtained by calculating the precoding matrix of the plurality of terminals in the vertical direction according to the channel state information through the following formula: The base station according to each column of channel information Calculate the beamforming vector for the vertical direction ((N _h ×N _v )×N _h dimensions), as shown in the following formula: Among them, the channel information of each column is Represents the i-th column channel matrix (N _r ×N _v dimensions) of the k-th user; the beamforming vector in the vertical direction ((N _h ×N _v )×N _h dimensions), The eigenvector corresponding to the largest generalized eigenvalue of , P is the transmit power, _nk is the noise received by each terminal, and σ ² is the noise power. 6. The method according to claim 5, wherein the base station obtains the horizontal channel corresponding to the beamforming vector according to the beamforming vector, and uses preset rules at the level of the horizontal channel The calculation of the precoding matrix in the direction includes: The base station transforms the beamforming vector Applied to each vertical channel, the horizontal channel is calculated by the following formula: The dimension is N _r ×N _h , and the value of k is 1, 2, ..., S; The base station uses a zero-forcing ZF criterion to calculate the multiple terminal precoding matrices in the horizontal direction on the horizontal channel make ((N _r ×S)×N _h dimensions), and then the formula for obtaining the precoding matrix is (N _h ×S dimension), where each column represents the equivalent horizontal precoding matrix of the corresponding user, namely is the kth column of the above matrix, representing the equivalent horizontal precoding matrix of the kth user, where, represents the equivalent horizontal channel of the kth user, yes The conjugate transposition of . 7. A processing device for multiple-input multiple-output MIMO, applied to the base station side, characterized in that it comprises: An acquisition module, configured to acquire channel state information of a terminal on a column channel within the coverage of the base station, and select a plurality of terminals whose terminal correlation satisfies a preset condition according to the channel state information, wherein the column channel is the a transmission channel between the antenna in the vertical direction between the terminal and the base station; A determining module, configured to determine, according to the channel state information, beamforming vectors obtained by performing precoding matrix calculations in the vertical direction on the multiple terminals; A processing module, configured to obtain a horizontal channel corresponding to the beamforming vector according to the beamforming vector, and perform precoding matrix calculation in the horizontal direction of the horizontal channel according to a preset rule. 8. The device according to claim 7, wherein the acquiring module comprises: a sending unit, configured to send a channel state information reference symbol CSI-RS to terminals within the coverage of the base station; The receiving unit is configured to receive channel state information sent by the terminal after measuring the channel according to the CSI-RS. 9. The device according to claim 8, wherein the acquiring module further comprises: a determining unit, configured to predetermine a predetermined number of the plurality of terminals satisfying a preset condition; A first selection unit, configured to select a terminal with the best channel characteristics as an initial terminal according to the channel state information; an acquiring unit, configured to acquire multiple chord distances between the selected initial terminal and multiple terminals to be selected; The second selection unit is configured to select, from the plurality of chord distances, a predetermined number of terminals whose chord distances from the initial terminal are the farthest. 10. The device according to claim 7, wherein before the base station determines the beamforming vectors obtained by performing precoding matrix calculations for the multiple terminals in the vertical direction according to the channel state information, the The device also includes: The first configuration module is used to configure a 2D uniform area array UPA, wherein the 2D uniform area array UPA includes: N _t =N _h ×N _v root antennas, N _h is the number of antennas in the horizontal direction, and N _v is the number of vertical antennas The number of directional row antennas, The second configuration module is configured to configure N _r =1 antenna for each of the k terminals randomly distributed in each cell of the base station; H _k represents the 3D channel matrix from the kth terminal to the base station (N _r ×(N _h ×N _v ) dimension), the Indicates the channel matrix (N _r ×N _v dimension) from the user to the i-th antenna of the base station, i=1,2...N _h , and k is a positive integer. 11. The apparatus of claim 10, wherein: The determining module is also configured to: according to each column of channel information Calculate the beamforming vector for the vertical direction ((N _h ×N _v )×N _h dimensions), as shown in the following formula: Among them, the channel information of each column is Represents the i-th column channel matrix (N _r ×N _v dimensions) of the k-th user; the beamforming vector in the vertical direction ((N _h ×N _v )×N _h dimensions), The eigenvector corresponding to the largest generalized eigenvalue of , P is the transmit power, _nk is the noise received by each terminal, and σ ² is the noise power. 12. The device according to claim 11, wherein the processing module comprises: The first calculation unit is used to convert the beamforming vector Applied to each vertical channel, the horizontal channel is calculated as shown in the following formula: The dimension is N _r ×N _h , and the value of k is 1, 2, ..., S; A second calculation unit, configured to calculate the plurality of terminal precoding matrices in the horizontal direction on the horizontal channel by using a zero-forcing ZF criterion make $\tilde{h}={\[{\left({\tilde{h}}_1^h\right)}^h,{\left({\tilde{h}}_2^h\right)}^h...{\left({\tilde{h}}_S^h\right)}^h\]}^h$ ((N _r ×S)×N _h dimensions), and then the formula for obtaining the precoding matrix is (N _h ×S dimension), where each column represents the equivalent horizontal precoding matrix of the corresponding user, namely is the kth column of the above matrix, representing the equivalent horizontal precoding matrix of the kth user, where, represents the equivalent horizontal channel of the kth user, yes The conjugate transposition of .