CN103888213A - Precoding method and device - Google Patents

Abstract

The embodiment of the present invention discloses a precoding method and device, which relate to the communication field, are not limited by the number of antennas of the receiving end device, can reduce the computational complexity of channel precoding, and ensure the transmission performance gain of the channel. Including: obtaining the downlink channel matrix; obtaining the initial weight value corresponding to the downlink channel matrix; obtaining the equalized equivalent channel matrix according to the downlink channel matrix and the initial weight value, and obtaining the weight value corresponding to the next equivalent channel matrix according to the equivalent channel matrix ; According to the equivalent channel matrix and the weight corresponding to the next equivalent channel matrix, iteratively calculate the weight corresponding to the downlink channel matrix until the preset number of iterations is satisfied or the weight corresponding to the calculated downlink channel matrix meets the preset the convergence condition. Embodiments of the present invention are applied to channel precoding.

Description

A kind of precoding method and equipment

technical field

The present invention relates to the communication field, in particular to a precoding method and equipment.

Background technique

In the downlink Multi-User Multiple-Input Multiple-Output (MU-MIMO for short) system, the base station sends different data to multiple users on the same time-frequency domain resources, and there is Co-Channel Interference (CCI for short), theoretically, it is hoped to eliminate inter-user interference (Multi-User Interference, MUI for short) by rationally designing the transmission signal. If the transmitting end can obtain the downlink CSI, it can know the interference situation of each user, and eliminate the interference among multiple users through a reasonable precoding method.

There are three mainstream technologies used in the existing technologies. The first one is the direct channel inversion method (Zero Forcing, referred to as ZF). The idea of this method is to directly set the interference between the receiving side and the user terminal to zero, but this The first method has a limit on the number of receiving antennas on the receiving side, and the performance will seriously degrade when the number of receiving antennas exceeds the threshold; the second method is the Signal-to-leakage-and-noise Ratio (SLNR) method, which There is no limit to the number of receiving antennas on the receiving side, but it is necessary to obtain the noise power of the user terminal on the receiving side, and the performance gain drops seriously when the signal-to-noise ratio is high; the third method is an iterative scheme based on zero forcing, which is based on the downlink channel of the system The initial weight of the matrix is iteratively calculated to obtain the precoding matrix used by the downlink channel corresponding to the next transmission. This method requires eigenvalue decomposition in each iteration process, and the computational complexity is high.

In the channel precoding method provided by the prior art, the inventors found that the channel precoding process of the transmitting end device in the prior art has a limit on the number of antennas of the receiving end device. In addition, the calculation complexity is high, and the channel transmission cannot be guaranteed. performance gain.

Contents of the invention

The embodiments of the present invention provide a precoding method and device, which are not limited by the number of antennas of the receiving end device, can reduce the computational complexity of channel precoding, and ensure the transmission performance gain of the channel.

In order to achieve the above object, embodiments of the present invention adopt the following technical solutions:

In the first aspect, a precoding method is provided, including:

Obtain the downlink channel matrix;

Obtain an initial weight corresponding to the downlink channel matrix;

Obtain an equalized equivalent channel matrix according to the downlink channel matrix and the initial weight value, and obtain a weight value corresponding to the next equivalent channel matrix according to the equivalent channel matrix;

Perform iterative calculation according to the equivalent channel matrix and the weight corresponding to the next equivalent channel matrix to obtain the weight corresponding to the downlink channel matrix until the preset number of iterations is satisfied or the calculated downlink channel matrix is obtained. The corresponding weights satisfy the preset convergence conditions.

In a first possible implementation manner, in combination with the first aspect, the acquiring the initial weight corresponding to the downlink channel matrix includes:

performing singular value decomposition on the downlink channel matrix;

Zero-forcing the right singular vector of the decomposed downlink channel matrix to obtain an initial weight corresponding to the downlink channel matrix;

or,

The decomposed non-zero right singular vector of the downlink channel matrix is used as the initial weight corresponding to the downlink channel matrix.

In a second possible implementation manner, in combination with the first aspect, the acquiring the initial weight corresponding to the downlink channel matrix includes:

Obtaining a downlink channel covariance matrix according to the downlink channel matrix;

performing eigenvalue decomposition on the downlink channel covariance matrix;

Forcing the eigenvalue vector of the decomposed downlink channel covariance matrix to zero to obtain the initial weight corresponding to the downlink channel matrix;

or,

The decomposed non-zero eigenvalue vector of the downlink channel covariance matrix is used as the initial weight value corresponding to the downlink channel matrix.

In a third possible implementation manner, in combination with the first aspect, the equalized equivalent channel matrix is obtained according to the downlink channel matrix and the initial weight value, and the next equivalent channel matrix is obtained according to the equivalent channel matrix. The weight corresponding to the channel matrix, including:

Obtaining an equalized equivalent channel matrix according to the downlink channel covariance matrix and the initial weight;

The weight corresponding to the next equivalent channel matrix is obtained by using a zero-forcing algorithm according to the equalized equivalent channel matrix.

In the fourth possible implementation, in combination with the second possible implementation, the equalized equivalent channel matrix is obtained according to the downlink channel matrix and the initial weight value, and the equalized equivalent channel matrix is obtained according to the equivalent channel matrix. The weight corresponding to the next equivalent channel matrix, including:

Obtaining a downlink channel covariance matrix according to the downlink channel matrix;

Obtaining an equalized equivalent channel matrix according to the downlink channel covariance matrix and the initial weight;

The weight corresponding to the next equivalent channel matrix is obtained by using a zero-forcing algorithm according to the equalized equivalent channel matrix.

In a fifth possible implementation manner, in combination with the first aspect, the equalized equivalent channel matrix is obtained according to the downlink channel matrix and the initial weight value, and the next equivalent channel matrix is obtained according to the equivalent channel matrix. The weight corresponding to the channel matrix, including:

calculating an equivalent channel matrix for each user terminal according to the initial weight;

Obtaining the equalized equivalent channel matrix according to the equivalent channel matrix of each user terminal and the downlink channel matrix;

The weight corresponding to the next equivalent channel matrix is obtained by using a zero-forcing algorithm according to the equalized equivalent channel matrix.

In a sixth possible implementation manner, in combination with the first aspect, the equalized equivalent channel matrix is obtained according to the downlink channel matrix and the initial weight value, and the next equivalent channel matrix is obtained according to the equivalent channel matrix. The weight corresponding to the channel matrix, including:

calculating an equivalent channel matrix for each user terminal according to the initial weight;

Obtaining the equalized equivalent channel matrix according to the equivalent channel matrix of each user terminal and the interference noise covariance matrix fed back by each user terminal;

The weight corresponding to the next equivalent channel matrix is obtained by using a zero-forcing algorithm according to the equalized equivalent channel matrix.

In a seventh possible implementation, in combination with the first aspect or any one of the first to sixth possible implementations, according to the equivalent matrix and the next equivalent channel The weight corresponding to the matrix is iteratively calculated to obtain the weight corresponding to the next downlink channel matrix until the preset number of iterations is satisfied or the calculated weight corresponding to the next downlink channel matrix converges to meet the preset convergence condition, including :

Obtain the terminal receiver type sent by the user terminal;

Set the number of iterations corresponding to the terminal receiver type as the preset number of iterations.

In the eighth possible implementation manner, in conjunction with the seventh possible implementation manner, if the terminal receiver type cannot be obtained, the preset number of iterations is set to The default number of iterations.

In a second aspect, an encoding device is provided, characterized in that it includes:

a channel acquisition unit, configured to acquire a downlink channel matrix;

an initialization unit, configured to obtain an initial weight corresponding to the downlink channel matrix forwarded by the channel acquisition unit;

an iteration unit, configured to obtain an equalized equivalent channel matrix according to the downlink channel matrix forwarded by the channel acquisition unit and the initial weight value forwarded by the initialization unit, and obtain the next equalized channel matrix according to the equivalent channel matrix. The weight corresponding to the equivalent channel matrix; and perform iterative calculation according to the weight corresponding to the equivalent channel matrix and the next equivalent channel matrix to obtain the weight corresponding to the downlink channel matrix until the preset iteration is satisfied The number of times or the calculated weight corresponding to the downlink channel matrix satisfies a preset convergence condition.

In a first possible implementation manner, in combination with the second aspect, the initialization unit includes:

a singular value decomposition subunit, configured to perform singular value decomposition on the downlink channel matrix forwarded by the channel acquisition unit;

The zero-forcing calculation subunit is used for zero-forcing the right singular vector of the decomposed downlink channel matrix forwarded by the singular value decomposition subunit to obtain the initial weight corresponding to the downlink channel matrix;

or,

The zero-forcing calculation subunit is configured to use the decomposed non-zero right singular vector of the downlink channel matrix forwarded by the singular value decomposition subunit as an initial weight corresponding to the downlink channel matrix.

In a second possible implementation manner, in combination with the second aspect, the initialization unit includes:

A covariance calculation subunit, configured to obtain a downlink channel covariance matrix according to the downlink channel matrix;

The eigenvalue decomposition subunit is further configured to perform eigenvalue decomposition on the downlink channel covariance matrix forwarded by the covariance calculation subunit;

The zero-forcing calculation subunit is also used to zero-force the eigenvalue vector of the downlink channel covariance matrix decomposed by the eigenvalue decomposition subunit to obtain the initial weight corresponding to the downlink channel matrix;

or,

The zero-forcing calculation subunit is further configured to use the non-zero eigenvalue vectors of the downlink channel covariance matrix decomposed by the eigenvalue decomposition subunit as initial weights corresponding to the downlink channel matrix.

In a third possible implementation manner, in combination with the second aspect, the iteration unit includes:

The equalization subunit is also used to obtain an equalized equivalent channel matrix from the downlink channel covariance matrix forwarded by the covariance calculation subunit and the initial weights forwarded by the initialization unit;

The weight calculation subunit is further configured to obtain the weight corresponding to the next equivalent channel matrix by using a zero-forcing algorithm according to the equalized equivalent channel matrix forwarded by the equalization subunit.

In a fourth possible implementation manner, in combination with the second possible implementation manner, the iteration unit includes:

The covariance calculation subunit is further configured to obtain a downlink channel covariance matrix according to the downlink channel matrix forwarded by the channel acquisition unit;

The equalization subunit is configured to obtain an equalized equivalent channel matrix according to the downlink channel covariance matrix forwarded by the covariance value subunit and the initial weight value forwarded by the initialization unit;

The weight calculation subunit is configured to obtain the weight corresponding to the next equivalent channel matrix by using a zero-forcing algorithm according to the equalized equivalent channel matrix forwarded by the equalization subunit.

In a fifth possible implementation manner, in combination with the second aspect, the iteration unit includes:

an equivalent matrix acquisition subunit, configured to calculate the equivalent channel matrix of each user terminal according to the initial weight forwarded by the initialization unit;

The equalization subunit is further configured to obtain the equalized equivalent channel matrix according to the equivalent channel matrix of each user terminal forwarded by the equivalent matrix acquisition subunit and the downlink channel matrix forwarded by the channel acquisition unit. channel matrix;

The weight calculation subunit is further configured to obtain the weight corresponding to the next equivalent channel matrix by using a zero-forcing algorithm according to the equalized equivalent channel matrix forwarded by the equalization subunit.

In a sixth possible implementation manner, in combination with the second aspect, the iteration unit includes:

an equivalent matrix acquisition subunit, configured to calculate the equivalent channel matrix of each user terminal according to the initial weight forwarded by the initialization unit;

The equalization subunit is configured to obtain the equivalent channel matrix after equalization according to the equivalent channel matrix of each user terminal forwarded by the equivalent matrix acquisition subunit and the interference noise covariance matrix fed back by each user terminal. channel matrix;

The weight calculation subunit is configured to obtain the weight corresponding to the next equivalent channel matrix by using a zero-forcing algorithm according to the equalized equivalent channel matrix forwarded by the equalization subunit.

In a seventh possible implementation manner, in combination with the second aspect or any possible implementation manner in the first to sixth possible implementation manners, the encoding device further includes:

The iteration number setting unit is configured to acquire the terminal receiver type sent by the user terminal; and set the iteration number corresponding to the terminal receiver type as the preset iteration number.

In the eighth possible implementation manner, in conjunction with the seventh possible implementation manner, the iteration number setting unit is further configured to: if the iteration number setting unit cannot obtain the terminal receiver type, according to the default user The terminal receiver type of the terminal sets the preset number of iterations as a default number of iterations.

The precoding method and device provided by the embodiments of the present invention only need to perform eigenvalue decomposition once in the calculation process of the initial weight value corresponding to the current downlink channel matrix, and then perform subsequent iterative calculations based on the initial weight value to obtain the next downlink channel matrix. The weight corresponding to the channel matrix is not limited by the number of antennas of the receiving device, and at the same time, it can reduce the computational complexity of channel precoding and ensure the transmission performance gain of the channel.

Description of drawings

In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings that need to be used in the description of the embodiments or the prior art. Obviously, the accompanying drawings in the following description are only These are some embodiments of the present invention. Those skilled in the art can also obtain other drawings based on these drawings without creative work.

FIG. 1 is a schematic flowchart of a precoding method provided by an embodiment of the present invention;

FIG. 2 is a schematic flowchart of another precoding method provided by an embodiment of the present invention;

FIG. 3 is a schematic flowchart of another precoding method provided by an embodiment of the present invention;

FIG. 4 is a schematic flowchart of another precoding method provided by an embodiment of the present invention;

FIG. 5 is a schematic flowchart of another precoding method provided by an embodiment of the present invention;

FIG. 6 is a schematic diagram of a performance simulation curve of a precoding method provided by an embodiment of the present invention;

FIG. 7 is a schematic diagram of a performance simulation curve of a precoding method provided by another embodiment of the present invention;

FIG. 8 is a schematic structural diagram of an encoding device provided by an embodiment of the present invention;

FIG. 9 is a schematic structural diagram of another encoding device provided by an embodiment of the present invention;

FIG. 10 is a schematic structural diagram of another encoding device provided by an embodiment of the present invention;

FIG. 11 is a schematic structural diagram of another encoding device provided by an embodiment of the present invention;

FIG. 12 is a schematic structural diagram of another encoding device provided by an embodiment of the present invention;

FIG. 13 is a schematic structural diagram of another encoding device provided by an embodiment of the present invention;

FIG. 14 is a schematic structural diagram of another encoding device provided by an embodiment of the present invention;

FIG. 15 is a schematic structural diagram of another encoding device provided by an embodiment of the present invention;

Fig. 16 is a schematic structural diagram of an encoding device provided by another embodiment of the present invention.

Detailed ways

The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

Here, the downlink MU-MIMO system is taken as an example. The transmitter sends different data to multiple user terminals on the same time-frequency domain resource. At this time, there is co-channel interference CCI between the cooperative user terminals. signal to eliminate interference between user terminals MUI, if the sender can obtain the downlink channel state information, it can know the interference situation of each user terminal, and eliminate the interference between multiple user terminals through a reasonable precoding method; here the precoding of the sender The coding device may be a base station, and of course may also be a module or a functional unit on the base station. In the following embodiments, the base station is taken as an example for illustration. Firstly, the signal model based on MU-MIMO system is given. Suppose N _t is the number of antennas of the base station, is the number of receiving antennas of user k, and the sending channel of user k is The weight matrix of user k is $W_k=[W_{k,1},W_{k,2},...,W_{k,N_{\mathrm{the\; s}}^k}]\∈C^{N_t\×N_{\mathrm{the\; s}}^k},$ The signal vector sent by user k is $x_k\∈C^{N_{\mathrm{the\; s}}^k\×1},$ Assuming a total of k users are paired, the signal model at the receiving end can be expressed as follows:

$\mathrm{<span\; class="notranslate">\; the\; y</span>}<span\; class="notranslate">\; =</span>{<span\; class="notranslate">\; [</span>{\mathrm{<span\; class="notranslate">\; the\; y</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}^{\mathrm{<span\; class="notranslate">\; T</span>}}<span\; class="notranslate">\; ,</span><span\; class="notranslate">\; .</span><span\; class="notranslate">\; .</span><span\; class="notranslate">\; .</span><span\; class="notranslate">\; ,</span>{\mathrm{<span\; class="notranslate">\; the\; y</span>}}_{\mathrm{<span\; class="notranslate">\; K</span>}}^{\mathrm{<span\; class="notranslate">\; T</span>}}<span\; class="notranslate">\; ]</span>}^{\mathrm{<span\; class="notranslate">\; T</span>}}<span\; class="notranslate">\; =</span>{\mathrm{<span\; class="notranslate">\; HW</span>}}_{\mathrm{<span\; class="notranslate">\; x</span>}}<span\; class="notranslate">\; +</span>\mathrm{<span\; class="notranslate">\; no</span>}$

in, $h={[h_1^T,...,h_K^T]}^T,$ $x={[x_1^T,...,x_K^T]}^T,$ W _k = [W ₁ , W ₂ , . . . , W _k ], $\mathrm{no}={[{\mathrm{no}}_1^T,...,{\mathrm{no}}_K^T]}^T,$ ${\mathrm{no}}_k\&Element;C^{N_r\&times;1}$ is the Gaussian white noise corresponding to user k.

Based on the above system model, as shown in FIG. 1, an embodiment of the present invention provides a precoding method, including:

101. The encoding device acquires a downlink channel matrix.

102. Acquire an initial weight corresponding to the downlink channel matrix.

103. Obtain an equalized equivalent channel matrix according to the downlink channel matrix and the initial weight value, and obtain a weight value corresponding to the next equivalent channel matrix according to the equivalent channel matrix.

104. Perform iterative calculation according to the weight corresponding to the equivalent channel matrix and the next equivalent channel matrix to obtain the weight corresponding to the downlink channel matrix until the preset number of iterations is satisfied or the weight corresponding to the calculated downlink channel matrix meets the preset The set convergence condition.

The precoding method provided by the embodiment of the present invention only needs to perform eigenvalue decomposition once in the calculation process of the initial weight value corresponding to the current downlink channel matrix, and then perform subsequent iterative calculations according to the initial weight value and obtain the eigenvalue corresponding to the downlink channel matrix. The weight is not limited by the number of antennas of the receiving device, and can reduce the computational complexity of channel precoding and ensure the transmission performance gain of the channel.

Specifically, as shown in FIG. 2, a precoding method provided by an embodiment of the present invention includes:

201. The encoding device acquires a downlink channel matrix H.

Of course, the downlink channel matrix H here is acquired by the base station according to the feedback from the user terminal side or the mutual dissimilarity of the uplink and downlink channels.

202. Calculate the covariance matrix R _hh,k of the downlink channel.

in $R_{\mathrm{hh},k}=h_k^h{h}_K.$

203. After performing singular value decomposition on the downlink channel matrix H, a zero-forcing algorithm is used to obtain an initial weight T ₁ corresponding to the downlink channel matrix.

In step 203, first perform singular value decomposition (Singular valuedecomposition, SVD) decomposition on H _k , k∈{1, 2, ..., k}, and obtain

$h_k=\left[\begin{array}{cc}{u}_k^{\left(1\right)}& u_k^{\left(0\right)}\end{array}\right]{\mathrm{\&Sigma;}}_k{\left[\begin{array}{cc}{V}_k^{\left(1\right)}& V_k^{\left(0\right)}\end{array}\right]}^{\mathrm{<figure-callout\; id="1"\; label="h\; Formula"\; filenames="HDA00002618658700041.png"\; state="\{\{state\}\}">h</figure-callout>}}$ Formula 1

个非零右奇异向量可表示如下，At this time, the front of user terminal k

A non-zero right singular vector can be expressed as follows,

${\tilde{h}}_k={\left(V_k^{\left(1\right)}(:,1:N_{\mathrm{the\; s}}^k)\right)}^{\mathrm{<figure-callout\; id="2"\; label="h\; Formula"\; filenames="HDA00002618658700041.png"\; state="\{\{state\}\}">h</figure-callout>}}$ Formula 2

对

进行迫零可以计算得到初始权值T₁，make

right

The initial weight T ₁ can be calculated by zero-forcing,

${\mathrm{<figure-callout\; id="1"\; label="T"\; filenames="HDA00002618658700041.png"\; state="\{\{state\}\}">T</figure-callout>}}_1={\tilde{h}}^h{\left(\tilde{h}{\tilde{h}}^h\right)}^{-1}\mathrm{diag}{\left(p_1\right)}^{1/2}$ Formula 3

为功率调整因子。P₁可以按照多种原则设置，包括注水原理、平均功率分配等原则。in,

is the power adjustment factor. _P1 can be set according to various principles, including water injection principle, average power distribution and other principles.

Of course, step 202 and step 203 can be performed at the same time, regardless of the order.

204. Obtain an equalized equivalent channel matrix according to the downlink channel covariance matrix and the initial weight value.

The specific calculation process of the equivalent matrix is as follows:

Let T _j,k represent the weight corresponding to the jth iteration of user k, the expression is as follows:

$T_{j,k}=T_j(:,(\underset{i=1}{\overset{k-1}{\mathrm{\&Sigma;}}}{N}_{\mathrm{the\; s}}^i+1):\left(\underset{i=1}{\overset{k}{\mathrm{\&Sigma;}}}{N}_{\mathrm{the\; s}}^i\right))$ Formula 4

Of course, j=1 is set here to obtain the initial weight.

Then, use R _{hh, k} to get the equalized equivalent channel matrix Z _j

$Z_j={[{\left(T_{j,1}^h{R}_{\mathrm{hh},1}\right)}^T,{\left(T_{j,2}^h{R}_{\mathrm{hh},2}\right)}^T,...,{\left(T_{j,k}^h{R}_{\mathrm{hh},k}\right)}^T]}^{\mathrm{<figure-callout\; id="5"\; label="T\; Formula"\; filenames="HDA00002618658700041.png"\; state="\{\{state\}\}">T</figure-callout>}}$ Formula 5

205. Obtain a weight corresponding to the next equivalent channel matrix by using a zero-forcing algorithm according to the equalized equivalent channel matrix.

Finally, the weight matrix is calculated using the zero-forcing algorithm,

$T_{j+1}=Z_j^h{\left(Z_j{Z}_j^h\right)}^{-1}\mathrm{diag}{\left(p_j\right)}^{1/2}$ Formula 6

    为功率调整因子。令j＝j+1，W＝T_j+1。

is the power adjustment factor. Let j=j+1, W=T _j +1.

206. Perform iterative calculation according to the equivalent channel matrix and the weight corresponding to the next equivalent channel matrix to obtain the weight corresponding to the downlink channel matrix until the preset number of iterations is satisfied or the calculated weight corresponding to the downlink channel matrix meets the preset The set convergence condition.

Here, the process of Formula 4 to Formula 6 is repeated until the preset number of iterations is satisfied or the calculated weight corresponding to the next downlink channel matrix satisfies the preset convergence condition.

In the present invention, the convergence condition is set according to whether the user equipment UE feeds back the receiver type. If the UE feeds back the receiver type, the base station sets the number of iterations according to the receiver type fed back by the UE. Embodiments of the present invention also include:

206a. Acquire the terminal receiver type sent by the user terminal.

206b. Set the number of iterations corresponding to the terminal receiver type as a preset number of iterations.

Of course, if the UE does not feed back the receiver type, this embodiment also includes:

206c. Set the preset number of iterations as the default number of iterations or set a convergence condition according to the default terminal receiver type of the user terminal.

Of course, the number of iterations here is an empirical value set according to the terminal receiver type of the user terminal. Common receiving types mainly include: Maximal-RatioCombining (MRC for short) receiver, Minimum Mean Square Error (MMS , referred to as MMSE) receiver, Interference Rejection Combining (Interference Rejection Combining, referred to as IRC) receiver, maximum likelihood detection (MaximumLikelihood Detection, referred to as MLD) receiver respectively set the number of iterations to N _MRC , N _MMSE , N _IRC and N _MLD , One of its possible values is shown in Table 1. If the paired users all use the same receiver, set it according to the number of iterations required by the corresponding receiver; if the paired users use different receivers, then set the maximum number of iterations required by the paired users.

N _MRC N _MMSE N _IRC N _MLD 2 user pairing 1 1 1 1 3 user pairing 3 3 1 1 4 user pairing 6 6 1 1

Table 1

If the UE does not feed back the receiver type, the base station sets a default number of iterations or sets a convergence condition. If the default number of iterations is set, it is set according to N _MRC or N _MMSE ,

Or set convergence conditions, one of which is expressed as follows:

||T _j+1 -T _j ||<ε Formula 7

Among them, ε is a constant.

In this embodiment, the acquisition of the initial weight _T1 corresponding to the downlink channel matrix is based on the calculation method of forcing the right singular vector to zero after performing singular value decomposition on the downlink channel matrix H. Of course, for the initial weight corresponding to the downlink channel matrix The acquisition of T ₁ may also be based on a calculation method of zero-forcing the non-zero right singular vector after performing singular value decomposition on the downlink channel matrix H.

Specifically, in step 203, it can also be realized in the following manner:

The non-zero right singular vector of the channel is used as the initial weight T ₁ of the MU-MIMO system. The specific description is as follows:

SVD decomposition of H _k , k ∈ {1, 2, ..., k},

$h_k=\left[\begin{array}{cc}{u}_k^{\left(1\right)}& u_k^{\left(0\right)}\end{array}\right]{\mathrm{\&Sigma;}}_k{\left[\begin{array}{cc}{V}_k^{\left(1\right)}& V_k^{\left(0\right)}\end{array}\right]}^{\mathrm{<figure-callout\; id="8"\; label="h\; Formula"\; filenames="HDA00002618658700041.png"\; state="\{\{state\}\}">h</figure-callout>}}$ Formula 8

个非零右奇异向量可以如下表示，user k's former

A non-zero right singular vector can be expressed as follows,

${\tilde{h}}_k={\left(V_k^{\left(1\right)}(:,1:N_{\mathrm{the\; s}}^k)\right)}^h$ Formula 9

采用信道的非零右奇异向量作为MU-MIMO系统的初始权值，make

The non-zero right singular vector of the channel is used as the initial weight of the MU-MIMO system,

${\mathrm{<figure-callout\; id="1"\; label="T"\; filenames="HDA00002618658700041.png"\; state="\{\{state\}\}">T</figure-callout>}}_1={\tilde{h}}^h\mathrm{diag}{\left(p_1\right)}^{1/2}$ Formula 10

为功率调整因子。p₁可以按照多种原则设置，包括注水原理、平均功率分配等原则。in,

is the power adjustment factor. p ₁ can be set according to various principles, including water injection principle, average power distribution and other principles.

The precoding method provided by the embodiment of the present invention only needs to perform eigenvalue decomposition once in the calculation process of the initial weight value corresponding to the current downlink channel matrix, and then perform subsequent iterative calculations according to the initial weight value and obtain the eigenvalue corresponding to the downlink channel matrix. The weight is not limited by the number of antennas of the receiving device, and can reduce the computational complexity of channel precoding and ensure the transmission performance gain of the channel.

Specifically, as shown in FIG. 3 , a precoding method provided by an embodiment of the present invention includes:

301. The encoding device acquires a downlink channel matrix H.

Of course, the downlink channel matrix H here is acquired by the base station according to the feedback from the user terminal side or the mutual dissimilarity of the uplink and downlink channels.

302. Calculate the downlink channel covariance matrix R _hh,k .

in $R_{\mathrm{hh},k}=h_k^h{h}_K.$

303. Perform eigenvalue decomposition on the downlink channel covariance matrix R _hh,k , and force zero the eigenvalue vectors of the decomposed downlink channel covariance matrix to obtain initial weights corresponding to the downlink channel matrix.

$R_{\mathrm{hh},k}=\left[\begin{array}{cc}{V}_k^{\left(1\right)}& V_k^{\left(0\right)}\end{array}\right]{\mathrm{\&Sigma;}}_k^2{\left[\begin{array}{cc}{V}_k^{\left(1\right)}& V_k^{\left(0\right)}\end{array}\right]}^h$ Formula 11

个非零特征值向量可表示如下，At this time, the front of user terminal k

A vector of non-zero eigenvalues can be expressed as follows,

${\tilde{h}}_k={\left(V_k^{\left(1\right)}(:,1:N_{\mathrm{the\; s}}^k)\right)}^{\mathrm{<figure-callout\; id="12"\; label="h\; Formula"\; filenames="HDA00002618658700041.png"\; state="\{\{state\}\}">h</figure-callout>}}$ Formula 12

make right The initial weight T ₁ can be calculated by zero-forcing,

${\mathrm{<figure-callout\; id="1"\; label="T"\; filenames="HDA00002618658700041.png"\; state="\{\{state\}\}">T</figure-callout>}}_1={\tilde{h}}^h{\left(\tilde{h}{\tilde{h}}^h\right)}^{-1}\mathrm{diag}{\left(p_1\right)}^{1/2}$ Formula 13

为功率调整因子。P₁可以按照多种原则设置，包括注水原理、平均功率分配等原则。in,

is the power adjustment factor. _P1 can be set according to various principles, including water injection principle, average power distribution and other principles.

304. Obtain an equalized equivalent channel matrix according to the downlink channel covariance matrix and the initial weight value.

The specific calculation process of the equivalent matrix is as follows:

Let T _j,k represent the weight corresponding to the jth iteration of user k, the expression is as follows:

$T_{j,k}=T_j(:,(\underset{i=1}{\overset{k-1}{\mathrm{\&Sigma;}}}{N}_{\mathrm{the\; s}}^i+1):\left(\underset{i=1}{\overset{k}{\mathrm{\&Sigma;}}}{N}_{\mathrm{the\; s}}^i\right))$ Formula 14

Of course, j=1 is set here to obtain the initial weight.

Then, use R _{hh, k} to get the equalized equivalent channel matrix Z _j

$Z_j={[{\left(T_{j,1}^h{R}_{\mathrm{hh},1}\right)}^T,{\left(T_{j,2}^h{R}_{\mathrm{hh},2}\right)}^T,...,{\left(T_{j,k}^h{R}_{\mathrm{hh},k}\right)}^T]}^{\mathrm{<figure-callout\; id="15"\; label="T\; Formula"\; filenames="HDA00002618658700041.png"\; state="\{\{state\}\}">T</figure-callout>}}$ Formula 15

305. Acquire weights corresponding to the next equivalent channel matrix by using a zero-forcing algorithm according to the equalized equivalent channel matrix.

Finally, the weight matrix is calculated using the zero-forcing algorithm,

$T_{j+1}=Z_j^h{\left(Z_j{Z}_j^h\right)}^{-1}\mathrm{diag}{\left(p_j\right)}^{1/2}$ Formula 16

    为功率调整因子。令j＝j+1，W＝T_j+1。

is the power adjustment factor. Let j=j+1, W=T _j +1.

306. Perform iterative calculation according to the equivalent channel matrix and the weight corresponding to the next equivalent channel matrix to obtain the weight corresponding to the downlink channel matrix until the preset number of iterations is satisfied or the calculated weight corresponding to the downlink channel matrix satisfies the preset The set convergence condition.

Here, the process of formula 14 to formula 16 is repeated until the preset number of iterations is satisfied or the calculated weight corresponding to the next downlink channel matrix satisfies the preset convergence condition.

In the present invention, the convergence condition is set according to whether the user equipment UE feeds back the receiver type. If the UE feeds back the receiver type, the base station sets the number of iterations according to the receiver type fed back by the UE. Embodiments of the present invention also include:

306a. Acquire the terminal receiver type sent by the user terminal.

306b. Set the number of iterations corresponding to the terminal receiver type as a preset number of iterations.

Of course, if the UE does not feed back the receiver type, this embodiment also includes:

306c. Set the preset number of iterations as the default number of iterations or set a convergence condition according to the default terminal receiver type of the user terminal.

Of course, the number of iterations here is an empirical value set according to the terminal receiver type of the user terminal. For the setting of the terminal receiver type, the number of iterations corresponding to different terminal receivers, and the default convergence conditions, refer to the previous embodiment for details. Let me repeat.

In this embodiment, the acquisition of the initial weight _T1 corresponding to the downlink channel matrix is based on performing eigenvalue decomposition on the downlink channel covariance matrix R _{hh, k} , and then performing an eigenvalue vector on the decomposed downlink channel covariance matrix The method of zero-forcing calculation, of course, may also be based on performing eigenvalue decomposition on the downlink channel covariance matrix and using a non-zero eigenvalue vector as the initial weight T ₁ for the initial weight T ₁ corresponding to the downlink channel matrix.

Specifically, in step 303, it can also be realized in the following ways:

After performing eigenvalue decomposition on the downlink channel covariance matrix, the non-zero eigenvalue vector is used as the initial weight T ₁ of the MU-MIMO system. The specific description is as follows:

SVD decomposition of H _k , k ∈ {1, 2, ..., k},

$R_{\mathrm{hh},k}=\left[\begin{array}{cc}{V}_k^{\left(1\right)}& V_k^{\left(0\right)}\end{array}\right]{\mathrm{\&Sigma;}}_k^2{\left[\begin{array}{cc}{V}_k^{\left(1\right)}& V_k^{\left(0\right)}\end{array}\right]}^h$ Formula 17

个非零特征值向量可以如下表示，user k's former

A vector of non-zero eigenvalues can be expressed as follows,

${\tilde{h}}_k={\left(V_k^{\left(1\right)}(:,1:N_{\mathrm{the\; s}}^k)\right)}^{\mathrm{<figure-callout\; id="18"\; label="h\; Formula"\; filenames="HDA00002618658700041.png"\; state="\{\{state\}\}">h</figure-callout>}}$ Formula 18

采用信道的非零右奇异向量作为MU-MIMO系统的初始权值，make

The non-zero right singular vector of the channel is used as the initial weight of the MU-MIMO system,

${\mathrm{<figure-callout\; id="1"\; label="T"\; filenames="HDA00002618658700041.png"\; state="\{\{state\}\}">T</figure-callout>}}_1={\tilde{h}}^h\mathrm{diag}{\left(p_1\right)}^{1/2}$ Formula 19

为功率调整因子。p₁可以按照多种原则设置，包括注水原理、平均功率分配等原则。in,

is the power adjustment factor. p ₁ can be set according to various principles, including water injection principle, average power distribution and other principles.

The precoding method provided by the embodiment of the present invention only needs to perform eigenvalue decomposition once in the calculation process of the initial weight value corresponding to the current downlink channel matrix, and then perform subsequent iterative calculations according to the initial weight value and obtain the eigenvalue corresponding to the downlink channel matrix. The weight is not limited by the number of antennas of the receiving device, and can reduce the computational complexity of precoding and ensure the transmission performance gain of the channel.

Embodiments of the present invention provide a precoding method, as shown in FIG. 4 , including:

401. The encoding device acquires a downlink channel matrix H.

Of course, the downlink channel matrix H here is acquired by the base station according to the feedback from the user terminal side or the mutual dissimilarity of the uplink and downlink channels.

402. After performing singular value decomposition on the downlink channel matrix H, a zero-forcing algorithm is used to obtain an initial weight T ₁ corresponding to the downlink channel matrix.

In step 402, first perform SVD decomposition on H _k , k ∈ {1, 2, ..., k}, to obtain,

$h_k=\left[\begin{array}{cc}{u}_k^{\left(1\right)}& u_k^{\left(0\right)}\end{array}\right]{\mathrm{\&Sigma;}}_k{\left[\begin{array}{cc}{V}_k^{\left(1\right)}& V_k^{\left(0\right)}\end{array}\right]}^{\mathrm{<figure-callout\; id="20"\; label="h\; Formula"\; filenames="HDA00002618658700041.png"\; state="\{\{state\}\}">h</figure-callout>}}$ Formula 20

个非零右奇异向量可表示如下，At this time, the front of user terminal k

A non-zero right singular vector can be expressed as follows,

对

进行迫零可以计算得到初始权值T₁，make

right

The initial weight T ₁ can be calculated by zero-forcing,

${\mathrm{<figure-callout\; id="1"\; label="T"\; filenames="HDA00002618658700041.png"\; state="\{\{state\}\}">T</figure-callout>}}_1={\tilde{h}}^h{\left(\tilde{h}{\tilde{h}}^h\right)}^{-1}\mathrm{diag}{\left(p_1\right)}^{1/2}$ Formula 21

为功率调整因子。P₁可以按照多种原则设置，包括注水原理、平均功率分配等原则。in,

is the power adjustment factor. _P1 can be set according to various principles, including water injection principle, average power distribution and other principles.

403. Calculate an equivalent channel matrix of each user terminal according to the initial weight.

To calculate the user's equivalent channel R _k,j , first, the received signal of user k can be expressed as follows,

${\mathrm{the\; y}}_{k,j}=h_k{T}_{J}x+{\mathrm{no}}_k=h_k\underset{i=1}{\overset{K}{\mathrm{\&Sigma;}}}{T}_{j,i}{x}_i+{\mathrm{no}}_{\mathrm{<figure-callout\; id="22"\; label="k\; Formula"\; filenames="HDA00002618658700041.png"\; state="\{\{state\}\}">k</figure-callout>}}$ Formula 22

Then the equivalent channel matrix of user k is:

R _{k, j} = H _k T _{j, k} Equation 23

Among them, T _{j, k} represents the weight corresponding to the jth iteration of user k,

$T_{j,k}=T_j(:,(\underset{i=1}{\overset{k-1}{\mathrm{\&Sigma;}}}{N}_{\mathrm{the\; s}}^i+1):\left(\underset{i=1}{\overset{k}{\mathrm{\&Sigma;}}}{N}_{\mathrm{the\; s}}^i\right))$ Formula 24

404. Obtain an equalized equivalent channel matrix according to the equivalent channel matrix of each user terminal.

The matrix Z _j is obtained by using R _k,j . At this time, no matter what receiver the UE uses, it is assumed that the UE uses an MRC receiver. At this time, the expression of Z _j is:

$Z_j={[{\left({\mathrm{<figure-callout\; id="1"\; label="R"\; filenames="HDA00002618658700041.png"\; state="\{\{state\}\}">R</figure-callout>}}_{1,j}^h{h}_1\right)}^T,{\left({\mathrm{<figure-callout\; id="2"\; label="R"\; filenames="HDA00002618658700041.png"\; state="\{\{state\}\}">R</figure-callout>}}_{2,j}^h{h}_2\right)}^T,...,{\left(R_{K,j}^h{h}_k\right)}^T]}^{\mathrm{<figure-callout\; id="25"\; label="T\; Formula"\; filenames="HDA00002618658700041.png"\; state="\{\{state\}\}">T</figure-callout>}}$ Formula 25

405. Acquire weights corresponding to the next equivalent channel matrix by using a zero-forcing algorithm according to the equalized equivalent channel matrix.

$T_{j+1}=Z_j^h{\left(Z_j{Z}_j^h\right)}^{-1}\mathrm{diag}{\left(p_j\right)}^{1/2}$ Formula 26

    为功率调整因子，令j＝j+1，W＝T_j+1。

is the power adjustment factor, let j=j+1, W=T _j +1.

406. Perform iterative calculation according to the equivalent channel matrix and the weight corresponding to the next equivalent channel matrix to obtain the weight corresponding to the next downlink channel matrix until the preset number of iterations is satisfied or the weight corresponding to the calculated next downlink channel matrix is obtained. The weights satisfy the preset convergence conditions.

The process of Formula 16 to Formula 17 is repeated until the preset number of iterations is met or the calculated weight corresponding to the next downlink channel matrix satisfies the preset convergence condition.

In the present invention, the convergence condition is set according to whether the user equipment UE feeds back the receiver type. If the UE feeds back the receiver type, the base station sets the number of iterations according to the receiver type fed back by the UE. Embodiments of the present invention also include:

406a. Obtain the terminal receiver type sent by the user terminal.

406b. Set the number of iterations corresponding to the terminal receiver type as a preset number of iterations.

Of course, if the UE does not feed back the receiver type, this embodiment also includes:

406c. Set the preset number of iterations as the default number of iterations or set a convergence condition according to the terminal receiver type of the user terminal.

Of course, the number of iterations here is an empirical value set according to the terminal receiver type of the user terminal. For the setting of the terminal receiver type, the number of iterations corresponding to different terminal receivers, and the default convergence conditions, refer to the previous embodiment for details. Let me repeat.

In this embodiment, the acquisition of the initial weight _T1 corresponding to the downlink channel matrix is based on the calculation method of forcing the right singular vector to zero after performing singular value decomposition on the downlink channel matrix H. Of course, for the initial weight corresponding to the downlink channel matrix The acquisition of T ₁ may also be based on a calculation method of zero-forcing the non-zero right singular vector after performing singular value decomposition on the downlink channel matrix H.

Specifically, in step 402, it can also be realized in the following ways:

The non-zero right singular vector of the channel is used as the initial weight T ₁ of MU-MIMO. The specific description is as follows.

SVD decomposition of H _k , k ∈ {1, 2, ..., k},

$h_k=\left[\begin{array}{cc}{u}_k^{\left(1\right)}& u_k^{\left(0\right)}\end{array}\right]{\mathrm{\&Sigma;}}_k{\left[\begin{array}{cc}{V}_k^{\left(1\right)}& V_k^{\left(0\right)}\end{array}\right]}^h$ Formula 27

个非零右奇异向量可以如下表示，user k's former

A non-zero right singular vector can be expressed as follows,

${\tilde{h}}_k={\left(V_k^{\left(1\right)}(:,1:N_{\mathrm{the\; s}}^k)\right)}^h$ Formula 28

采用信道的非零右奇异向量作为MU-MIMO系统的初始权值，make

The non-zero right singular vector of the channel is used as the initial weight of the MU-MIMO system,

${\mathrm{<figure-callout\; id="1"\; label="T"\; filenames="HDA00002618658700041.png"\; state="\{\{state\}\}">T</figure-callout>}}_1={\tilde{h}}^h\mathrm{diag}{\left(p_1\right)}^{1/2}$ Formula 29

为功率调整因子。p₁可以按照多种原则设置，包括注水原理、平均功率分配等原则。in,

is the power adjustment factor. p ₁ can be set according to various principles, including water injection principle, average power distribution and other principles.

In addition, step 402 may also be replaced by obtaining the initial weight T ₁ by performing eigenvalue decomposition on the downlink channel covariance matrix described in steps 302 and 303 .

The precoding method provided by the embodiment of the present invention only needs to perform eigenvalue decomposition once in the calculation process of the initial weight value corresponding to the current downlink channel matrix, and then perform subsequent iterative calculations according to the initial weight value and obtain the eigenvalue corresponding to the downlink channel matrix. The weight is not limited by the number of antennas of the receiving device, and can reduce the computational complexity of channel precoding and ensure the transmission performance gain of the channel.

Referring to Figure 5, an embodiment of the present invention provides a precoding method, including the following steps:

501. The encoding device acquires a downlink channel matrix H.

Of course, the downlink channel matrix H here is acquired by the base station according to the feedback from the user terminal side or the mutual dissimilarity of the uplink and downlink channels.

502. After performing singular value decomposition on the downlink channel matrix H, a zero-forcing algorithm is used to obtain an initial weight T ₁ corresponding to the downlink channel matrix.

In step 502, SVD decomposition is first performed on H _K , k∈{1, 2, 3..., k}, to obtain

$h_k=\left[\begin{array}{cc}{u}_k^{\left(1\right)}& u_k^{\left(0\right)}\end{array}\right]{\mathrm{\&Sigma;}}_k{\left[\begin{array}{cc}{V}_k^{\left(1\right)}& V_k^{\left(0\right)}\end{array}\right]}^{\mathrm{<figure-callout\; id="30"\; label="h\; Formula"\; filenames="HDA00002618658700041.png"\; state="\{\{state\}\}">h</figure-callout>}}$ Formula 30

个非零右奇异向量可表示如下，At this time, the front of user terminal k

A non-zero right singular vector can be expressed as follows,

${\tilde{h}}_k={\left(V_k^{\left(1\right)}(:,1:N_{\mathrm{the\; s}}^k)\right)}^h$ Formula 31

对进行迫零可以计算得到初始权值T₁，make

right The initial weight T ₁ can be calculated by zero-forcing,

${\mathrm{<figure-callout\; id="1"\; label="T"\; filenames="HDA00002618658700041.png"\; state="\{\{state\}\}">T</figure-callout>}}_1={\tilde{h}}^h{\left(\tilde{h}{\tilde{h}}^h\right)}^{-1}\mathrm{diag}{\left(p_1\right)}^{1/2}$ Formula 32

为功率调整因子。P₁可以按照多种原则设置，包括注水原理、平均功率分配等原则。in,

is the power adjustment factor. _P1 can be set according to various principles, including water injection principle, average power distribution and other principles.

503. Calculate an equivalent channel matrix of each user terminal according to the initial weight.

To calculate the user's equivalent channel R _k,j , first, the received signal of user k can be expressed as follows,

${\mathrm{the\; y}}_{k,j}=h_k{T}_{J}x+{\mathrm{no}}_k=h_k\underset{i=1}{\overset{K}{\mathrm{\&Sigma;}}}{T}_{j,i}{x}_i+{\mathrm{no}}_k$ Formula 33

Then the equivalent channel matrix of user k is:

R _k,j = H _k T _j,k Equation 34

Among them, T _{j, k} represents the weight corresponding to the jth iteration of user k,

$T_{j,k}=T_j(:,(\underset{i=1}{\overset{k-1}{\mathrm{\&Sigma;}}}{N}_{\mathrm{the\; s}}^i+1):\left(\underset{i=1}{\overset{k}{\mathrm{\&Sigma;}}}{N}_{\mathrm{the\; s}}^i\right))$ Formula 35

504. Obtain an equalized equivalent channel matrix according to the equivalent channel matrix of each user terminal and the interference noise covariance matrix fed back by each user terminal.

The matrix Z _j is obtained by using R _k,j . At this time, no matter what receiver the UE uses, it is assumed that the UE uses an IRC receiver. At this time, the expression of Z _j is:

For user k, the jth iteration, if it is assumed that the UE uses an IRC receiver:

${\mathrm{<figure-callout\; id="1"\; label="G"\; filenames="HDA00002618658700041.png"\; state="\{\{state\}\}">G</figure-callout>}}_{1,j}^h=R_{k,j}^h(R_{k,j}{R}_{k,j}^h+R_{\mathrm{u\; u},k})$ Formula 36

Among them, R _uu,k represents the interference noise covariance matrix of user k. The expression of this Z _j is as follows:

$Z_j={[{\left({\mathrm{<figure-callout\; id="1"\; label="G"\; filenames="HDA00002618658700041.png"\; state="\{\{state\}\}">G</figure-callout>}}_{1,j}^h{h}_1\right)}^T,{\left({\mathrm{<figure-callout\; id="2"\; label="G"\; filenames="HDA00002618658700041.png"\; state="\{\{state\}\}">G</figure-callout>}}_{2,j}^h{h}_2\right)}^T,...,{\left(G_{K,j}^h{h}_K\right)}^T]}^T$ Formula 37

505. Acquire weights corresponding to the next equivalent channel matrix by using a zero-forcing algorithm according to the equalized equivalent channel matrix.

$T_{j+1}=Z_j^h{\left(Z_j{Z}_j^h\right)}^{-1}\mathrm{diag}{\left(p_j\right)}^{1/2}$ Formula 38

    为功率调整因子，令j＝j+1，W＝T_j+1。

is the power adjustment factor, let j=j+1, W=T _j +1.

506. Perform iterative calculation according to the equivalent channel matrix and the weight corresponding to the next equivalent channel matrix to obtain the weight corresponding to the next downlink channel matrix until the preset number of iterations is satisfied or the weight corresponding to the calculated next downlink channel matrix is obtained. The weights satisfy the preset convergence conditions.

Specifically, step 502 can also be realized in the following manner:

The non-zero right singular vector of the channel is used as the initial weight T ₁ of the MU-MIMO system. The specific description is as follows.

SVD decomposition of H _k , k ∈ {1, 2, ..., k},

$h_k=\left[\begin{array}{cc}{u}_k^{\left(1\right)}& u_k^{\left(0\right)}\end{array}\right]{\mathrm{\&Sigma;}}_k{\left[\begin{array}{cc}{V}_k^{\left(1\right)}& V_k^{\left(0\right)}\end{array}\right]}^h$ Formula 39

user k's former A non-zero right singular vector can be expressed as follows,

${\tilde{h}}_k={\left(V_k^{\left(1\right)}(:,1:N_{\mathrm{the\; s}}^k)\right)}^h$ Formula 40

采用信道的非零右奇异向量作为MU-MIMO系统的初始权值。make

The non-zero right singular vector of the channel is used as the initial weight of the MU-MIMO system.

${\mathrm{<figure-callout\; id="1"\; label="T"\; filenames="HDA00002618658700041.png"\; state="\{\{state\}\}">T</figure-callout>}}_1={\tilde{h}}^h\mathrm{diag}{\left(p_1\right)}^{1/2}$ Formula 41

为功率调整因子。p₁可以按照多种原则设置，包括注水原理、平均功率分配等原则。in,

is the power adjustment factor. p ₁ can be set according to various principles, including water injection principle, average power distribution and other principles.

In the present invention, the convergence condition is set according to whether the user equipment UE feeds back the receiver type. If the UE feeds back the receiver type, the base station sets the number of iterations according to the receiver type fed back by the UE. Embodiments of the present invention also include:

506a. Acquire the terminal receiver type sent by the user terminal.

506b. Set the number of iterations corresponding to the terminal receiver type as a preset number of iterations.

Of course, if the UE does not feed back the receiver type, this embodiment also includes:

506c. Set the preset number of iterations as the default number of iterations or set a convergence condition according to the default terminal receiver type of the user terminal.

Of course, the number of iterations here is an empirical value set according to the type of terminal receiver of the user terminal, wherein the type of terminal receiver, the number of iterations corresponding to different terminal receivers, and the setting of default convergence conditions refer to the above embodiments for details. repeat.

In addition, step 502 may also be replaced by obtaining the initial weight T ₁ by performing eigenvalue decomposition on the downlink channel covariance matrix described in steps 302 and 303 .

The meaning of the mathematical operation symbols used in the above embodiments is specifically as follows: ( ) ^H represents the conjugate transposition of ( ); ( ) ^-1 represents the inversion of ( ); ( ) ^T represents the inversion of ( ) ) seeks the transpose; (·) ^* represents to (·) seeks the conjugate; tr(·) represents (·) to seek the trace; diag(·) represents to form the diagonal matrix by the element of the vector of (·); I _n Indicates the n×n identity matrix; A(:, m:n) indicates the selection of the mth to nth columns of the matrix A.

In addition, as shown in Figure 6, a transmitter device with 4 transmit antennas, 2 user terminals and each user terminal with 2 receive antenna models is given, and Figure 7 shows a transmitter device with 4 transmit antennas, 2 user terminals per user terminal 4. Receiving antenna model, wherein Fig. 6 and Fig. 7 are the simulation performance when each user terminal is paired with a single stream when the channel precoding method provided by the embodiment shown in Fig. 2 of the present invention is adopted, that is, the signal-to-noise ratio (Signal/Noise , referred to as SNR) and performance (capacity) curve diagram, wherein the downlink channel corresponding to the user terminal is randomly generated during the simulation process, which shows the scheme 1, scheme 2 and scheme 3 provided by the prior art and the scheme provided by the present invention Below the graph of the relationship between signal-to-noise ratio (Signal/Noise, referred to as SNR) and performance (capacity), it can be seen that the method provided by the present invention is different from the methods provided by the prior art scheme 1, scheme 2 and scheme 3. The increase in noise ratio has the best performance gain effect, among which scheme 1 is the direct channel inversion method (Zero Forcing, referred to as ZF), and scheme 2 is the signal-to-leakage-and-noise ratio (Signal-to-leakage-and-noise Ratio, referred to as SLNR) method ; Scheme 3 is an iterative scheme based on zero-forcing, wherein the total number of receiving antennas of the user terminal corresponding to Figure 6 is greater than the number of transmitting antennas of the base station, so scheme 1 cannot be used, so the graph of scheme 1 is not given.

The precoding method provided by the embodiment of the present invention only needs to perform eigenvalue decomposition once in the calculation process of the initial weight value corresponding to the current downlink channel matrix, and then perform subsequent iterative calculations according to the initial weight value and obtain the eigenvalue corresponding to the downlink channel matrix. The weight is not limited by the number of antennas of the receiving device, and can reduce the computational complexity of channel precoding and ensure the transmission performance gain of the channel.

An embodiment of the present invention provides an encoding device. As shown in FIG. 8, the encoding device 6 includes: a channel acquisition unit 61, an initialization unit 62, and an iteration unit 63, wherein:

The channel acquisition unit 61 is configured to acquire a downlink channel matrix.

The initialization unit 62 is configured to obtain an initial weight corresponding to the downlink channel matrix forwarded by the channel acquisition unit 61 .

The iteration unit 63 is used to obtain the equalized equivalent channel matrix and the weight corresponding to the next equivalent channel matrix obtained according to the equivalent channel matrix according to the downlink channel matrix forwarded by the channel acquisition unit 61 and the initial weight value forwarded by the initialization unit 62. value; and perform iterative calculation according to the equivalent channel matrix forwarded by the equalization unit 63 and the weight corresponding to the next equivalent channel matrix to obtain the corresponding weight of the downlink channel matrix until the preset number of iterations or the calculated downlink channel matrix are satisfied The corresponding weights satisfy the preset convergence conditions.

Further optionally, as shown in FIG. 9, the initialization unit 62 includes:

The singular value decomposition subunit 621a is configured to perform singular value decomposition on the downlink channel matrix forwarded by the channel acquisition unit 61 .

The zero-forcing calculation subunit 622a is used for zero-forcing the right singular vector of the decomposed downlink channel matrix forwarded by the singular value decomposition subunit 621a to obtain the initial weight corresponding to the downlink channel matrix;

or,

The zero-forcing calculation subunit 622a is configured to use the non-zero right singular vector of the decomposed downlink channel matrix forwarded by the singular value decomposition subunit 621a as the initial weight value corresponding to the downlink channel matrix.

Optionally, as shown in FIG. 10, the initialization unit 62 includes:

The covariance calculation subunit 621b is used to obtain the downlink channel covariance matrix according to the downlink channel matrix,

The eigenvalue decomposition subunit 622b is also used to perform eigenvalue decomposition on the downlink channel covariance matrix forwarded by the covariance calculation subunit 621b,

The zero-forcing calculation subunit 623b is also used to use the eigenvalue vector of the downlink channel covariance matrix decomposed by the eigenvalue decomposition subunit 622b as the initial weight corresponding to the downlink channel matrix;

or,

The zero-forcing calculation subunit 623b is also used to use the non-zero eigenvalue vectors of the downlink channel covariance matrix decomposed by the eigenvalue decomposition subunit 622b as initial weights corresponding to the downlink channel matrix.

Further optionally, as shown in Figure 11, the iteration unit 63 also includes:

The equalization subunit 631a is also used to obtain an equalized equivalent channel matrix from the downlink channel covariance matrix forwarded by the covariance value subunit 621a and the initial weights forwarded by the initialization unit 62,

The weight calculation subunit 632a is further configured to obtain the weight corresponding to the next equivalent channel matrix by using a zero-forcing algorithm according to the equalized equivalent channel matrix forwarded by the equalization subunit 631a.

Optionally, as shown in Figure 12, the iteration unit 63 includes:

The covariance calculation subunit 631b acquires the downlink channel covariance matrix according to the downlink channel matrix forwarded by the channel acquisition unit 61 .

The equalization subunit 632b is used to obtain an equalized equivalent channel matrix from the downlink channel covariance matrix forwarded by the covariance value subunit 631b and the initial weights forwarded by the initialization unit 62 .

The weight calculation subunit 633b is configured to obtain the weight corresponding to the next equivalent channel matrix by using a zero-forcing algorithm according to the equalized equivalent channel matrix forwarded by the equalization subunit 632b.

Optionally, as shown in Figure 13, the iteration unit 63 also includes:

The equivalent matrix acquisition subunit 631c is configured to calculate the equivalent channel matrix of each user terminal according to the initial weight forwarded by the initialization unit 62,

The equalization subunit 632c is further configured to obtain an equalized equivalent channel matrix according to the equivalent channel matrix of each user terminal forwarded by the equivalent matrix acquisition subunit 631c and the downlink channel matrix forwarded by the channel acquisition unit 61,

The weight calculation subunit 633c is further configured to obtain the weight corresponding to the next equivalent channel matrix by using a zero-forcing algorithm according to the equalized equivalent channel matrix forwarded by the equalization subunit 632c.

Optionally, as shown in Figure 14, the iteration unit 63 also includes:

The equivalent matrix acquisition subunit 631d is also used to calculate the equivalent channel matrix of each user terminal according to the initial weight forwarded by the initialization unit 62,

The equalization subunit 632d is further configured to obtain an equalized equivalent channel matrix according to the equivalent channel matrix of each user terminal forwarded by the equivalent matrix acquisition subunit 631b and the interference noise covariance matrix fed back by each user terminal,

The weight calculation subunit 633d is further configured to obtain the weight corresponding to the next equivalent channel matrix by using a zero-forcing algorithm according to the equalized equivalent channel matrix forwarded by the equalization subunit 632d.

Optionally, as shown in FIG. 15 , the encoding device 6 further includes: an iteration number setting unit 64, configured to obtain the terminal receiver type sent by the user terminal; and set the iteration number corresponding to the terminal receiver type as a preset the number of iterations.

Optionally, if the iteration number setting unit 64 cannot acquire the terminal receiver type, then set the preset iteration number as the default generation number according to the default terminal receiver type of the user terminal.

The encoding device provided by the embodiments of the present invention only needs to perform eigenvalue decomposition once in the calculation process of the initial weight value corresponding to the current downlink channel matrix, and then perform subsequent iterative calculations according to the initial weight value and obtain the weight corresponding to the downlink channel matrix. The value is not limited by the number of antennas of the receiving device, and at the same time, it can reduce the computational complexity of channel precoding and ensure the transmission performance gain of the channel.

FIG. 16 is a schematic structural diagram of an encoding device provided by another embodiment of the present invention. The encoding device 7 includes at least one processor 71 , a memory 72 , a communication bus 73 and at least one communication interface 74 .

Wherein, the communication bus 73 is used to realize connection and communication between the above components, and the communication interface 74 is used to connect and communicate with external devices.

Program codes to be executed are stored in the memory 72 , and these program codes may specifically include: a channel acquisition unit 721 , an initialization unit 722 and an iteration unit 723 .

The processor 71 is used to execute the units stored in the memory 72. When the above units are executed by the processor 71, the following functions are realized:

The channel acquisition unit 721 is configured to acquire a downlink channel matrix.

The initialization unit 722 is configured to obtain an initial weight corresponding to the downlink channel matrix forwarded by the channel acquisition unit 721 .

The iteration unit 723 is configured to obtain the equalized equivalent channel matrix and the weight corresponding to the next equivalent channel matrix obtained according to the equivalent channel matrix according to the downlink channel matrix forwarded by the channel acquisition unit 721 and the initial weight value forwarded by the initialization unit 722 value; and iteratively calculate the weight corresponding to the downlink channel matrix according to the equivalent matrix and the weight corresponding to the next equivalent channel matrix, until the preset number of iterations is satisfied or the calculated weight corresponding to the downlink channel matrix satisfies the preset The set convergence condition.

Further optionally, the initialization unit 722 includes:

The singular value decomposition subunit is configured to perform singular value decomposition on the downlink channel matrix forwarded by the channel acquisition unit 721 .

The zero-forcing calculation subunit is used for zero-forcing the right singular vector of the decomposed downlink channel matrix forwarded by the singular value decomposition subunit to obtain the corresponding initial weight of the downlink channel matrix;

or,

The zero-forcing calculation subunit is used to use the non-zero right singular vector of the decomposed downlink channel matrix forwarded by the singular value decomposition subunit as an initial weight value corresponding to the downlink channel matrix.

Optionally, the initialization unit 722 includes:

The covariance calculation subunit is used to obtain the downlink channel covariance matrix according to the downlink channel matrix.

The eigenvalue decomposition subunit is also used to perform eigenvalue decomposition on the downlink channel covariance matrix forwarded by the covariance calculation subunit.

The zero-forcing calculation subunit is also used to use the eigenvalue vector of the downlink channel covariance matrix decomposed by the eigenvalue decomposition subunit as the initial weight corresponding to the downlink channel matrix;

or,

The zero-forcing calculation subunit is also used to use the non-zero eigenvalue vectors of the downlink channel covariance matrix decomposed by the eigenvalue decomposition subunit as initial weights corresponding to the downlink channel matrix.

Further optionally, the iteration unit 723 also includes:

The equalization subunit is also used to obtain an equalized equivalent channel matrix from the downlink channel covariance matrix forwarded by the covariance value acquisition subunit and the initial weights forwarded by the initialization unit 722 .

The weight calculation subunit is also used to obtain the weight corresponding to the next equivalent channel matrix by using a zero-forcing algorithm according to the equalized equivalent channel matrix forwarded by the equalization subunit.

Optionally, iteration unit 723 includes:

The covariance calculation subunit acquires the downlink channel covariance matrix according to the downlink channel matrix forwarded by the channel acquisition unit 721 .

The equalization subunit is used to obtain an equalized equivalent channel matrix from the downlink channel covariance matrix forwarded by the covariance value subunit and the initial weights forwarded by the initialization unit 722 .

The weight calculation subunit is configured to obtain the weight corresponding to the next equivalent channel matrix by using a zero-forcing algorithm according to the equalized equivalent channel matrix forwarded by the equalization subunit 632b.

Optionally, iteration unit 723 also includes:

The equivalent matrix acquisition subunit is configured to calculate the equivalent channel matrix of each user terminal according to the initial weights forwarded by the initialization unit 722 .

The equalization subunit is further configured to obtain an equalized equivalent channel matrix according to the equivalent channel matrix of each user terminal forwarded by the equivalent matrix acquisition subunit and the downlink channel matrix forwarded by the channel acquisition unit 721 .

The weight calculation subunit is also used to obtain the weight corresponding to the next equivalent channel matrix by using a zero-forcing algorithm according to the equalized equivalent channel matrix forwarded by the equalization subunit.

Optionally, iteration unit 723 also includes:

The equivalent matrix acquiring subunit is further configured to calculate the equivalent channel matrix of each user terminal according to the initial weights forwarded by the initialization unit 722 .

The equalization subunit is further configured to obtain an equalized equivalent channel matrix according to the equivalent channel matrix of each user terminal forwarded by the equivalent matrix acquisition subunit and the interference noise covariance matrix fed back by each user terminal.

The weight calculation subunit is also used to obtain the weight corresponding to the next equivalent channel matrix by using a zero-forcing algorithm according to the equalized equivalent channel matrix forwarded by the equalization subunit.

Optionally, the memory 72 further includes: an iteration number setting unit 724, configured to acquire the terminal receiver type sent by the user terminal; and set the iteration number corresponding to the terminal receiver type as a preset iteration number.

Optionally, if the iteration number setting unit 724 cannot obtain the terminal receiver type, then set the preset iteration number as the default number of generations according to the default terminal receiver type of the user terminal.

The encoding device provided by the embodiments of the present invention only needs to perform eigenvalue decomposition once in the calculation process of the initial weight value corresponding to the current downlink channel matrix, and then perform subsequent iterative calculations according to the initial weight value and obtain the weight corresponding to the downlink channel matrix. The value is not limited by the number of antennas of the receiving device, and at the same time, it can reduce the computational complexity of channel precoding and ensure the transmission performance gain of the channel.

Those of ordinary skill in the art can understand that all or part of the steps for realizing the above-mentioned method embodiments can be completed by hardware related to program instructions, and the aforementioned program can be stored in a computer-readable storage medium. When the program is executed, the It includes the steps of the above method embodiments; and the aforementioned storage medium includes: ROM, RAM, magnetic disk or optical disk and other various media that can store program codes.

The above is only a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Anyone skilled in the art can easily think of changes or substitutions within the technical scope disclosed in the present invention. Should be covered within the protection scope of the present invention. Therefore, the protection scope of the present invention should be determined by the protection scope of the claims.

Claims (18)

1. A precoding method, characterized in that, comprising: Obtain the downlink channel matrix; Obtain an initial weight corresponding to the downlink channel matrix; Obtain an equalized equivalent channel matrix according to the downlink channel matrix and the initial weight value, and obtain a weight value corresponding to the next equivalent channel matrix according to the equivalent channel matrix; Perform iterative calculation according to the equivalent channel matrix and the weight corresponding to the next equivalent channel matrix to obtain the weight corresponding to the downlink channel matrix until the preset number of iterations is satisfied or the calculated downlink channel matrix is obtained. The corresponding weights satisfy the preset convergence conditions. 2. The method according to claim 1, wherein said obtaining the initial weight corresponding to said downlink channel matrix comprises: performing singular value decomposition on the downlink channel matrix; Zero-forcing the right singular vector of the decomposed downlink channel matrix to obtain an initial weight corresponding to the downlink channel matrix; or, The decomposed non-zero right singular vector of the downlink channel matrix is used as the initial weight corresponding to the downlink channel matrix. 3. The method according to claim 1, wherein said obtaining the initial weight corresponding to said downlink channel matrix comprises: Obtaining a downlink channel covariance matrix according to the downlink channel matrix; performing eigenvalue decomposition on the downlink channel covariance matrix; Forcing the eigenvalue vector of the decomposed downlink channel covariance matrix to zero to obtain the initial weight corresponding to the downlink channel matrix; or, The decomposed non-zero eigenvalue vector of the downlink channel covariance matrix is used as the initial weight value corresponding to the downlink channel matrix. 4. The method according to claim 3, wherein the equalized equivalent channel matrix is obtained according to the downlink channel matrix and the initial weight value, and the next equivalent channel matrix is obtained according to the equivalent channel matrix. The weight corresponding to the channel matrix, including: Obtaining an equalized equivalent channel matrix according to the downlink channel covariance matrix and the initial weight; The weight corresponding to the next equivalent channel matrix is obtained by using a zero-forcing algorithm according to the equalized equivalent channel matrix. 5. The method according to claim 1, wherein the equalized equivalent channel matrix is obtained according to the downlink channel matrix and the initial weight value, and the next equivalent channel matrix is obtained according to the equivalent channel matrix. The weight corresponding to the channel matrix, including: Obtaining a downlink channel covariance matrix according to the downlink channel matrix; Obtaining an equalized equivalent channel matrix according to the downlink channel covariance matrix and the initial weight; The weight corresponding to the next equivalent channel matrix is obtained by using a zero-forcing algorithm according to the equalized equivalent channel matrix. 6. The method according to claim 1, wherein the equalized equivalent channel matrix is obtained according to the downlink channel matrix and the initial weight value, and the next equivalent channel matrix is obtained according to the equivalent channel matrix. The weight corresponding to the channel matrix, including: calculating an equivalent channel matrix for each user terminal according to the initial weight; Obtaining the equalized equivalent channel matrix according to the equivalent channel matrix of each user terminal and the downlink channel matrix; The weight corresponding to the next equivalent channel matrix is obtained by using a zero-forcing algorithm according to the equalized equivalent channel matrix. 7. The method according to claim 1, wherein the equalized equivalent channel matrix is obtained according to the downlink channel matrix and the initial weight value, and the next equivalent channel matrix is obtained according to the equivalent channel matrix. The weight corresponding to the channel matrix, including: calculating an equivalent channel matrix for each user terminal according to the initial weight; Obtaining the equalized equivalent channel matrix according to the equivalent channel matrix of each user terminal and the interference noise covariance matrix fed back by each user terminal; The weight corresponding to the next equivalent channel matrix is obtained by using a zero-forcing algorithm according to the equalized equivalent channel matrix. 8. The method according to any one of claims 1 to 7, characterized in that, performing iterative calculations according to the weights corresponding to the equivalent matrix and the next equivalent channel matrix to obtain the corresponding weight of the next downlink channel matrix Weight, until the preset number of iterations is met or the calculated weight corresponding to the next downlink channel matrix converges to meet the preset convergence condition, it also includes: Obtain the terminal receiver type sent by the user terminal; Set the number of iterations corresponding to the terminal receiver type as the preset number of iterations. 9. The method according to claim 8, wherein if the type of the terminal receiver cannot be obtained, the preset number of iterations is set as the default number of iterations according to the default type of the terminal receiver of the user terminal. 10. An encoding device, characterized in that it comprises: a channel acquisition unit, configured to acquire a downlink channel matrix; an initialization unit, configured to obtain an initial weight corresponding to the downlink channel matrix forwarded by the channel acquisition unit; an iteration unit, configured to obtain an equalized equivalent channel matrix according to the downlink channel matrix forwarded by the channel acquisition unit and the initial weight value forwarded by the initialization unit, and obtain the next equalized channel matrix according to the equivalent channel matrix. The weight corresponding to the equivalent channel matrix; and perform iterative calculation according to the weight corresponding to the equivalent channel matrix and the next equivalent channel matrix to obtain the weight corresponding to the downlink channel matrix until the preset iteration is satisfied The number of times or the calculated weight corresponding to the downlink channel matrix satisfies a preset convergence condition. 11. The encoding device according to claim 10, wherein the initialization unit comprises: a singular value decomposition subunit, configured to perform singular value decomposition on the downlink channel matrix forwarded by the channel acquisition unit; The zero-forcing calculation subunit is used for zero-forcing the right singular vector of the decomposed downlink channel matrix forwarded by the singular value decomposition subunit to obtain the initial weight corresponding to the downlink channel matrix; or, The zero-forcing calculation subunit is configured to use the decomposed non-zero right singular vector of the downlink channel matrix forwarded by the singular value decomposition subunit as an initial weight corresponding to the downlink channel matrix. 12. The encoding device according to claim 10, wherein the initialization unit comprises: A covariance calculation subunit, configured to obtain a downlink channel covariance matrix according to the downlink channel matrix; The eigenvalue decomposition subunit is further configured to perform eigenvalue decomposition on the downlink channel covariance matrix forwarded by the covariance calculation subunit; The zero-forcing calculation subunit is further configured to use the eigenvalue vector of the downlink channel covariance matrix decomposed by the eigenvalue decomposition subunit as the initial weight value corresponding to the downlink channel matrix; or, The zero-forcing calculation subunit is further configured to use the non-zero eigenvalue vectors of the downlink channel covariance matrix decomposed by the eigenvalue decomposition subunit as initial weights corresponding to the downlink channel matrix. 13. The encoding device according to claim 12, wherein the iteration unit comprises: The equalization subunit is also used to obtain an equalized equivalent channel matrix from the downlink channel covariance matrix forwarded by the covariance calculation subunit and the initial weights forwarded by the initialization unit; The weight calculation subunit is further configured to obtain the weight corresponding to the next equivalent channel matrix by using a zero-forcing algorithm according to the equalized equivalent channel matrix forwarded by the equalization subunit. 14. The encoding device according to claim 10, wherein the iteration unit comprises: The covariance calculation subunit is further configured to obtain a downlink channel covariance matrix according to the downlink channel matrix forwarded by the channel acquisition unit; The equalization subunit is configured to obtain an equalized equivalent channel matrix according to the downlink channel covariance matrix forwarded by the covariance value subunit and the initial weight value forwarded by the initialization unit; The weight calculation subunit is configured to obtain the weight corresponding to the next equivalent channel matrix by using a zero-forcing algorithm according to the equalized equivalent channel matrix forwarded by the equalization subunit. 15. The encoding device according to claim 10, wherein the iteration unit comprises: an equivalent matrix acquisition subunit, configured to calculate the equivalent channel matrix of each user terminal according to the initial weight forwarded by the initialization unit; An equalization subunit, configured to obtain the equalized equivalent channel according to the equivalent channel matrix of each user terminal forwarded by the equivalent matrix acquisition subunit and the downlink channel matrix forwarded by the channel acquisition unit matrix; The weight calculation subunit is configured to obtain the weight corresponding to the next equivalent channel matrix by using a zero-forcing algorithm according to the equalized equivalent channel matrix forwarded by the equalization subunit. 16. The encoding device according to claim 10, wherein the iteration unit comprises: an equivalent matrix acquisition subunit, configured to calculate the equivalent channel matrix of each user terminal according to the initial weight forwarded by the initialization unit; The equalization subunit is configured to obtain the equivalent channel matrix after equalization according to the equivalent channel matrix of each user terminal forwarded by the equivalent matrix acquisition subunit and the interference noise covariance matrix fed back by each user terminal. channel matrix; The weight calculation subunit is configured to obtain the weight corresponding to the next equivalent channel matrix by using a zero-forcing algorithm according to the equalized equivalent channel matrix forwarded by the equalization subunit. 17. The encoding device according to any one of claims 10-16, wherein the encoding device further comprises: The iteration number setting unit is configured to acquire the terminal receiver type sent by the user terminal; and set the iteration number corresponding to the terminal receiver type as the preset iteration number. 18. The encoding device according to claim 17, wherein the iteration number setting unit is further configured to, if the iteration number setting unit cannot obtain the terminal receiver type, then according to the terminal of the default user terminal The receiver type sets the preset number of iterations as the default number of iterations.

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