CN104506225A - Beamforming matrix based data joint transmission method and system - Google Patents

Abstract

The present invention provides a data joint transmission method and system based on a beamforming matrix. The method includes: the UE obtains the equivalent channel information of a BS, calculates its own beamforming matrix U _j and feeds it back to all BSs; each BS calculates its own The beamforming matrix V _i is sent to other BSs; it is judged whether the update times of V _i of each BS is greater than the preset X, if not, return to the step of calculating V _i for each BS, and if so, each BS calculates V i according to V _i Update its own beamforming weight θ _ij and inform other BSs; judge whether the update times of θ _ij of each BS is greater than the preset Y, if not, return to the step of UE calculating U _j , if so, each BS according to V _i direction The data center requests data distribution, and jointly transmits the data sent by the data center received through the backhaul link to each UE. The above method can keep the sum of mean square errors low, significantly reduce backhaul link overhead, save backhaul link resources from the data center to the sending side, and have low computational complexity.

Description

Data Joint Transmission Method and System Based on Beamforming Matrix

technical field

The present invention relates to the technical field of wireless communication, in particular to a data joint transmission method and system based on a beamforming matrix.

Background technique

As users' demand for mobile data services continues to grow, the load and coverage pressure on base stations is also increasing. Operators are considering dense deployment of cells to deal with this problem. However, a densely deployed network may cause serious inter-cell interference on the same frequency. The introduction of inter-cell cooperation technology can further suppress and utilize inter-cell interference and improve system performance.

Coordinated Multi-Point (CoMP for short) technology can alleviate the interference problem of cell edge users by introducing cooperation among cells. Two implementation schemes of CoMP technology are provided in the prior art: one is Coordinated Beamforming (CBF for short) technology, and the other is Joint Processing (JP for short) technology. Among them, the joint processing technology can perform joint transmission (Joint Transmission, JT for short) for each cooperative node to the user by realizing the sharing of user data among the cooperative nodes. In order to save time-frequency resources, a multi-user JT (Multi-user JT, MU-JT for short) technology in which the coordinating nodes simultaneously transmit for a group of users can be used.

In a Multiple-Input-Multiple-Output (MIMO) system, beamforming technology (Beamforming) can reduce the interference between users and improve the signal at the receiving end by processing the signal at the sending end or receiving end. The purpose of Signal to interference and noise ratio (SINR for short).

A backhaul link (Backhaul) is a general term for a link used to connect a cooperative base station and a cooperative base station to an upper-layer central control node or a data center. In the JT system, since all nodes need to share user data, this puts forward higher requirements on the capacity of the backhaul link. In the limited-capacity backhaul link, the cooperative base station may adopt an asymmetric transmission method, that is, the cooperative base station does not perform joint transmission for all users, but only transmits for some users, so as to save data from the data center. The overhead and resources of the backhaul link of the cooperating base stations.

In the existing beamforming design methods, most of them consider the ideal backhaul link capacity, and on this basis, the beamforming design is carried out with the objectives of minimizing the base station transmit power, maximizing the weighted rate, and so on. A part considers the beamforming design method of limited-capacity backhaul links, which only considers the goal of minimizing the transmit power. In the existing beamforming design method, the rate sum of the system has a certain relationship with the mean square error sum. In the goal of minimizing the system mean square error, there is still a lack of beamforming design schemes for limited backhaul link capacity.

In view of this, how to design a beamforming matrix that can significantly reduce the backhaul link overhead while maintaining a low mean square error sum, save backhaul link resources from the data center to the sender, and have low computational complexity , and perform joint data transmission based on the beamforming matrix, which has become a technical problem to be solved at present.

Contents of the invention

Aiming at the defects in the prior art, the present invention provides a data joint transmission method and system based on a beamforming matrix, which can maintain a low mean square error sum, significantly reduce backhaul link overhead, and save ( That is, the backhaul link resources of each cooperative base station BS), and the calculation complexity is low

In the first aspect, the present invention provides a data joint transmission method based on a beamforming matrix, including:

The user equipment UE obtains the equivalent channel information from each coordinated base station BS, calculates the beamforming matrix received by itself, and feeds back the beamforming matrix to all BSs;

Each BS calculates its own beamforming based on the beamforming matrix of other BSs, the channel information from other BSs to the UE, the beamforming matrix of the UE fed back by the UE, and the beamforming weight matrix of each BS itself matrix, and send the beamforming matrix to other BSs;

Judging whether the number of updates of the beamforming matrix of each BS is greater than a preset X;

If the number of updates of the beamforming matrix of each BS is less than or equal to X, return the beamforming matrix of each BS based on the beamforming matrix of other BSs, the channel information from other BSs to the UE, and the beamforming information of the UE fed back by the UE. a forming matrix and a beamforming weight matrix of each BS itself, and a step of calculating its own beamforming matrix;

If the update times of the beamforming matrix of each BS is greater than X, each BS updates its own beamforming weight according to the calculated beamforming matrix of itself, and informs other BSs;

judging whether the number of updates of the beamforming weights of each BS itself is greater than a preset Y;

If the number of updates of the beamforming weights of each BS is less than or equal to Y, return to the step of the user equipment UE obtaining the equivalent channel information from each coordinated base station BS, and calculating the beamforming matrix received by itself;

If the number of updates of the beamforming weights of each BS is greater than Y, each BS requests data distribution from the data center according to its own beamforming matrix after calculation, and transmits the data received by the data center through the backhaul link Data is jointly transmitted to each UE.

Optionally, the equivalent channel information includes:

The product of the channel H _ij matrix from each BS to the UE and the beamforming matrix V _ij that each BS performs beamforming to the corresponding UE; and

The received beamforming matrix U _j calculated by the UE is:

${\mathrm{<span\; class="notranslate">\; u</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; =</span>{<span\; class="notranslate">\; (</span>\underset{\mathrm{<span\; class="notranslate">\; i</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}\underset{\mathrm{<span\; class="notranslate">\; the\; s</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}{\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; ij</span>}}{\mathrm{<span\; class="notranslate">\; V</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}{\mathrm{<span\; class="notranslate">\; V</span>}}_{\mathrm{<span\; class="notranslate">\; the\; s</span>}}^{\mathrm{<span\; class="notranslate">\; h</span>}}{\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; sj</span>}}^{\mathrm{<span\; class="notranslate">\; h</span>}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; \&sigma;</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}^{\mathrm{<span\; class="notranslate">\; 2</span>}}\mathrm{<span\; class="notranslate">\; I</span>}<span\; class="notranslate">\; )</span>}^{<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; 1</span>}}\underset{\mathrm{<span\; class="notranslate">\; i</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}{\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; ij</span>}}{\mathrm{<span\; class="notranslate">\; V</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}{\mathrm{<span\; class="notranslate">\; B</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; ,</span>$

Among them, V _i =[V _i1 ,V _i2 ,...,V _iK ] is the transmit beamforming matrix of BSi for all UEs, B _j is the data selection matrix of UEj, j∈{1, 2,..., K}, satisfy as well as l≠j; V _s is the beamforming matrix of other BSs except BSi, H _sj is the channel matrix from other BSs to UE except BSi, s≠i, is the variance of Gaussian white noise on UEj channel.

Optionally, the overhead of the backhaul link is the sum of the zero norms of the transmit beamforming matrices of all BSs to the UE, specifically:

$\underset{\mathrm{<span\; class="notranslate">\; i</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}<span\; class="notranslate">\; =</span>{<span\; class="notranslate">\; |</span><span\; class="notranslate">\; |</span>{<span\; class="notranslate">\; |</span><span\; class="notranslate">\; |</span>{\mathrm{<span\; class="notranslate">\; V</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; |</span><span\; class="notranslate">\; |</span>}_{\mathrm{<span\; class="notranslate">\; f</span>}}^{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; ,</span><span\; class="notranslate">\; |</span><span\; class="notranslate">\; |</span>{{\mathrm{<span\; class="notranslate">\; V</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; |</span><span\; class="notranslate">\; |</span>}_{\mathrm{<span\; class="notranslate">\; f</span>}}^{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; ,</span><span\; class="notranslate">\; .</span><span\; class="notranslate">\; .</span><span\; class="notranslate">\; .</span>{<span\; class="notranslate">\; |</span><span\; class="notranslate">\; |</span>{\mathrm{<span\; class="notranslate">\; V</span>}}_{\mathrm{<span\; class="notranslate">\; ik</span>}}<span\; class="notranslate">\; |</span><span\; class="notranslate">\; |</span>}_{\mathrm{<span\; class="notranslate">\; f</span>}}^{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; |</span><span\; class="notranslate">\; |</span>}_{\mathrm{<span\; class="notranslate">\; 0</span>}}<span\; class="notranslate">\; .</span>$

Optionally, each BS is calculated according to the beamforming matrix of other BSs, the channel information from other BSs to the UE, the beamforming matrix of the UE fed back by the UE, and the beamforming weight matrix of each BS itself. The beamforming matrix V _i of its own is:

V _i =P _i Y _i ;

Among them, P _i is an orthogonal matrix, and P _i is calculated by the first formula,

The first formula is:

${\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}^{\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; =</span>{\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}{\stackrel{<span\; class="notranslate">\; \&OverBar;</span>}{\mathrm{<span\; class="notranslate">\; h</span>}}}_{\mathrm{<span\; class="notranslate">\; i</span>}}{\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}^{\mathrm{<span\; class="notranslate">\; h</span>}}<span\; class="notranslate">\; ,</span>$

is through the pair matrix Obtained by Hessenberg decomposition, is the Hessenberg matrix;

Each column of matrix Y _i It is calculated according to the second formula,

The second formula is:

${\mathrm{<span\; class="notranslate">\; the\; y</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}^{\mathrm{<span\; class="notranslate">\; l</span>}}<span\; class="notranslate">\; =</span><span\; class="notranslate">\; [</span>{\stackrel{<span\; class="notranslate">\; \&OverBar;</span>}{\mathrm{<span\; class="notranslate">\; h</span>}}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; +</span><span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; \&theta;</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; \&lambda;</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span>\mathrm{<span\; class="notranslate">\; I</span>}{<span\; class="notranslate">\; ]</span>}^{<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}^{\mathrm{<span\; class="notranslate">\; l</span>}}<span\; class="notranslate">\; ,</span>$

For the nth element on the diagonal of each BS's own beamforming weight matrix _Θi , is the lth column vector of matrix F _i , matrix matrix $G_i=\underset{j}{\mathrm{\&Sigma;}}{h}_{\mathrm{ij}}^h{u}_j{B}_j-\underset{\mathrm{the\; s}\&NotEqual;i}{\mathrm{\&Sigma;}}\underset{j}{\mathrm{\&Sigma;}}{h}_{\mathrm{ij}}^h{u}_j{u}_j^h{h}_{\mathrm{sj}}{V}_{\mathrm{the\; s}},$ matrix $Q_{i,\mathrm{no}}{=Z}_{i,\mathrm{no}}^h{f}_{\mathrm{no}}^i{f}_{\mathrm{no}}^{\mathrm{i\; H}}{Z}_{i,\mathrm{no}},$ $f_{\mathrm{no}}^i$ is the ith column vector of matrix F _i , the matrix The eigenvalues of are decomposed into The diagonal matrix Ξ is the matrix The eigenvalue matrix of , λ _i is obtained by performing a binary search on the third formula,

The third formula is:

$\underset{\mathrm{<span\; class="notranslate">\; no</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}\underset{\mathrm{<span\; class="notranslate">\; m</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}\frac{<span\; class="notranslate">\; [</span>{\mathrm{<span\; class="notranslate">\; Q</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; no</span>}}{<span\; class="notranslate">\; ]</span>}_{\mathrm{<span\; class="notranslate">\; m</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; m</span>}}}{{<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; \&xi;</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; no</span>}}^{<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; m</span>}<span\; class="notranslate">\; )</span>}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; \&lambda;</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span>}^{\mathrm{<span\; class="notranslate">\; 2</span>}}}<span\; class="notranslate">\; =</span>{\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; ,</span>$

The molecule [Q _i,n ] _m,m means to take the elements on the diagonal of the matrix, are the elements on the diagonal of matrix Ξ _i,n , where n and m are each data stream and transmit antenna, respectively.

Optionally, if the update times of each BS's own beamforming matrix is greater than X, each BS updates its own beamforming weight according to the calculated own beamforming matrix, and notifies other BSs, include:

If the number of updates of the beamforming matrix of each BS is greater than X, each BS updates its own beamforming weight θ _ij according to the fourth formula according to the calculated beamforming matrix of itself, and informs other BSs;

Wherein, the fourth formula is:

${\mathrm{<span\; class="notranslate">\; \&theta;</span>}}_{\mathrm{<span\; class="notranslate">\; ij</span>}}<span\; class="notranslate">\; =</span>{<span\; class="notranslate">\; (</span>{<span\; class="notranslate">\; |</span><span\; class="notranslate">\; |</span>{\mathrm{<span\; class="notranslate">\; V</span>}}_{\mathrm{<span\; class="notranslate">\; ij</span>}}<span\; class="notranslate">\; |</span><span\; class="notranslate">\; |</span>}_{\mathrm{<span\; class="notranslate">\; f</span>}}<span\; class="notranslate">\; +</span>\sqrt{\mathrm{<span\; class="notranslate">\; \&epsiv;</span>}}<span\; class="notranslate">\; )</span>}^{<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; ,</span>$

ε is a positive number close to 0.

Optionally, if the number of updates of the beamforming weights of each BS is greater than Y, each BS requests data distribution from the data center according to the calculated beamforming matrix of itself, including:

If the number of updates of the beamforming weights of each BS is greater than Y, each BS station according to the calculated beamforming matrix of its own, if the Frobenius norm of the beamforming matrix for a certain UE by the BS satisfies is close to zero, the BS requests the data center to distribute the data of the corresponding UE through the backhaul link; otherwise, the request is not sent.

Optionally, the feeding back the beamforming matrix to all BSs includes:

The beamforming matrix is fed back to all BSs through additional channels.

Optionally, the preset X is: the inner loop termination counter preset X; and

The preset Y is: the preset Y of the outer loop termination counter.

Optionally, each BS interacts with its own beamforming matrix and channel matrix through an inter-BS cooperation interface.

In a second aspect, the present invention provides a beamforming matrix-based joint data transmission system, including: multiple user equipment UEs at the receiving end, multiple cooperative base stations BS at the sending end, and a data center;

Each user equipment UE includes: a first calculation module, configured to obtain equivalent channel information from each coordinated base station BS, calculate a beamforming matrix received by itself, and feed back the beamforming matrix to all BSs;

Each cooperative base station BS includes:

The second calculation module is used for each BS according to the beamforming matrix of other BSs, the channel information from other BSs to the UE, the beamforming matrix of the UE fed back by the UE, and the beamforming weight matrix of each BS itself , calculate its own beamforming matrix, and send the beamforming matrix to other BSs;

The first judging module is used to judge whether the number of updates of the beamforming matrix of each BS is greater than preset X, and if the number of updates of the beamforming matrix of each BS is less than or equal to X, return to the second calculation module;

An updating module, configured to update the beamforming weight of each BS according to the calculated beamforming matrix of itself if the number of updates of the beamforming matrix of each BS is greater than X, and notify other BSs;

The second judging module is used to judge whether the number of updates of the beamforming weight of each BS is greater than the preset Y, and if the number of updates of the beamforming weight of each BS is less than or equal to Y, return the UE's first a computing module;

The data joint transmission module is used to request data distribution from the data center according to the calculated beamforming matrix of each BS if the number of updates of the beamforming weight of each BS is greater than Y, and will pass the backhaul link The received data sent by the data center is jointly transmitted to each UE.

It can be seen from the above technical solution that the joint data transmission method and system based on the beamforming matrix of the present invention can significantly reduce the cost of the backhaul link while maintaining a low sum of mean square errors, and save the cost from the data center to the sending side. Backhaul link resources, and has a low computational complexity.

Description of drawings

FIG. 1 is a schematic flowchart of a data joint transmission method based on a beamforming matrix provided by an embodiment of the present invention;

FIG. 2 is a schematic structural diagram of a data joint transmission system based on a beamforming matrix provided by an embodiment of the present invention;

FIG. 3 is a schematic diagram of a communication model of a data joint transmission system based on a beamforming matrix with three coordinated base stations provided by an embodiment of the present invention;

FIG. 4 is a schematic structural diagram of each BS at the sending end in the joint data transmission system based on the beamforming matrix shown in FIG. 2;

FIG. 5 is a schematic structural diagram of each UE located at the receiving end in the joint data transmission system based on the beamforming matrix shown in FIG. 2;

Fig. 6 is a schematic diagram of the simulation results of the backhaul link overhead as the number of users increases according to the technical solution provided by the embodiment of the present invention;

FIG. 7 is a schematic diagram of simulation results of the sum of mean square errors of all UEs as the number of users increases according to the technical solution provided by the embodiment of the present invention;

Fig. 8 is a schematic diagram of the simulation results of the sum of mean square errors of all UEs under different numbers of transmitting and receiving antennas as the power-to-white noise ratio SNR of the transmitting end increases according to the technical solution provided by the embodiment of the present invention.

Detailed ways

In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments It is only some embodiments of the present invention, but not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without creative efforts fall within the protection scope of the present invention.

In the actual system, the cooperative base station BS needs to obtain the data to be sent from the upper layer control node or data center through the backhaul link Backhaul. Due to the capacity limitation under the non-ideal backhaul link, when the number of cooperative users to be served increases When , the cooperative base station needs to determine for which users to obtain data, and design the corresponding beamforming matrix. On the other hand, the entire network also needs to maintain certain properties, such as mean square error and metrics. Therefore, the beamforming and data distribution method of the present invention not only considers the system performance, but also considers reducing the overhead on the backhaul link.

Fig. 3 shows a schematic diagram of a communication model of a data joint transmission system based on a beamforming matrix with 3 coordinated base stations provided by an embodiment of the present invention. For example, as shown in Fig. 3 , there may be Three cooperating base stations BS. Assuming that the embodiment of the present invention has M cooperative base stations BS (ie BS1, BS2, ..., BSM), each BS has _NT transmit antennas, and the cooperation information is exchanged between the BSs through the cooperation interface. Since joint transmission is introduced to suppress and utilize inter-cell interference, the BS is generally composed of a series of base stations geographically close to each other. In this embodiment, the base station deployment method as shown in Figure 2 is adopted. There are K user equipment UEs (ie UE1, UE2, ..., UEK) in the BS edge coverage area, each UE has _NR receiving antennas, and each UE will request to initiate d independent stream data transmission. The data of all UEs are shared among the coordinated base stations and sent to all UEs simultaneously through multi-user MIMO technology.

FIG. 1 shows a schematic flowchart of a beamforming matrix-based joint data transmission method provided by an embodiment of the present invention. As shown in FIG. 1 , the beamforming matrix-based data joint transmission method of this embodiment is as follows.

101. The user equipment UE acquires equivalent channel information from each coordinated base station BS, calculates a beamforming matrix received by itself, and feeds back the beamforming matrix to all BSs.

Wherein, the equivalent channel information includes:

The product of the channel H _ij matrix from each BS to the UE and the beamforming matrix V _ij that each BS performs beamforming to the corresponding UE; and

The received beamforming matrix U _j calculated by the UE is:

${\mathrm{<span\; class="notranslate">\; u</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; =</span>{<span\; class="notranslate">\; (</span>\underset{\mathrm{<span\; class="notranslate">\; i</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}\underset{\mathrm{<span\; class="notranslate">\; the\; s</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}{\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; ij</span>}}{\mathrm{<span\; class="notranslate">\; V</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}{\mathrm{<span\; class="notranslate">\; V</span>}}_{\mathrm{<span\; class="notranslate">\; the\; s</span>}}^{\mathrm{<span\; class="notranslate">\; h</span>}}{\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; sj</span>}}^{\mathrm{<span\; class="notranslate">\; h</span>}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; \&sigma;</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}^{\mathrm{<span\; class="notranslate">\; 2</span>}}\mathrm{<span\; class="notranslate">\; I</span>}<span\; class="notranslate">\; )</span>}^{<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; 1</span>}}\underset{\mathrm{<span\; class="notranslate">\; i</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}{\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; ij</span>}}{\mathrm{<span\; class="notranslate">\; V</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}{\mathrm{<span\; class="notranslate">\; B</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; ,</span>$

Among them, V _i =[V _i1 ,V _i2 ,...,V _iK ] is the transmit beamforming matrix of BSi for all UEs, B _j is the data selection matrix of UEj, j∈{1, 2,..., K}, satisfy as well as l≠j; V _s is the beamforming matrix of other BSs except BSi, H _sj is the channel matrix from other BSs to UE except BSi, s≠i, is the variance of Gaussian white noise on UEj channel.

In a specific application, in this step 101, the first beamforming matrix may be fed back to all BSs through an additional channel.

102. Each BS calculates its own beam according to the beamforming matrix of other BSs, the channel information from other BSs to the UE, the beamforming matrix of the UE fed back by the UE, and the beamforming weight matrix of each BS itself beamforming matrix, and send the beamforming matrix to other BSs.

In a specific application, the beamforming matrix V _i calculated in step 102 is:

V _i =P _i Y _i ;

Among them, P _i is an orthogonal matrix, and P _i is calculated by the first formula,

The first formula is:

is through the pair matrix Obtained by Hessenberg decomposition, is the Hessenberg matrix;

Each column of matrix Y _i It is calculated according to the second formula,

The second formula is: ${\mathrm{the\; y}}_i^l=[{\stackrel{\&OverBar;}{h}}_i+({\mathrm{\&theta;}}_i+{\mathrm{\&lambda;}}_i)I{]}^{-1}{f}_i^l,$

For the nth element on the diagonal of each BS's own beamforming weight matrix _Θi , is the lth column vector of matrix F _i , matrix matrix $G_i=\underset{j}{\mathrm{\&Sigma;}}{h}_{\mathrm{ij}}^h{u}_j{B}_j-\underset{\mathrm{the\; s}\&NotEqual;i}{\mathrm{\&Sigma;}}\underset{j}{\mathrm{\&Sigma;}}{h}_{\mathrm{ij}}^h{u}_j{u}_j^h{h}_{\mathrm{sj}}{V}_{\mathrm{the\; s}},$ matrix $Q_{i,\mathrm{no}}{=Z}_{i,\mathrm{no}}^h{f}_{\mathrm{no}}^i{f}_{\mathrm{no}}^{\mathrm{i\; H}}{Z}_{i,\mathrm{no}},$ $f_{\mathrm{no}}^i$ is the ith column vector of matrix F _i , the matrix The eigenvalues of are decomposed into The diagonal matrix Ξ is the matrix The eigenvalue matrix of , λ _i is obtained by performing a binary search on the third formula,

The third formula is: $\underset{\mathrm{no}}{\mathrm{\&Sigma;}}\underset{m}{\mathrm{\&Sigma;}}\frac{[Q_{i,\mathrm{no}}{]}_{m,m}}{{({\mathrm{\&xi;}}_{i,\mathrm{no}}^{\left(m\right)}+{\mathrm{\&lambda;}}_i)}^2}=P_i,$

The molecule [Q _i,n ] _m,m means to take the elements on the diagonal of the matrix, are the elements on the diagonal of matrix Ξ _i,n , where n and m are each data stream and transmit antenna, respectively.

103. Determine whether the update times of the beamforming matrix of each BS is greater than preset X, and return to step 102 if the update times of the beamforming matrix of each BS is less than or equal to X.

In a specific application, the preset X is: the preset X of the inner loop termination counter.

104. If the update times of each BS's own beamforming matrix is greater than X, each BS updates its own beamforming weight according to the calculated own beamforming matrix, and informs other BSs.

In a specific application, this step 104 may include:

If the number of updates of the beamforming matrix of each BS is greater than X, each BS updates its own beamforming weight θ _ij according to the fourth formula according to the calculated beamforming matrix of itself, and informs other BSs;

Wherein, the fourth formula is:

${\mathrm{<span\; class="notranslate">\; \&theta;</span>}}_{\mathrm{<span\; class="notranslate">\; ij</span>}}<span\; class="notranslate">\; =</span>{<span\; class="notranslate">\; (</span>{<span\; class="notranslate">\; |</span><span\; class="notranslate">\; |</span>{\mathrm{<span\; class="notranslate">\; V</span>}}_{\mathrm{<span\; class="notranslate">\; ij</span>}}<span\; class="notranslate">\; |</span><span\; class="notranslate">\; |</span>}_{\mathrm{<span\; class="notranslate">\; f</span>}}<span\; class="notranslate">\; +</span>\sqrt{\mathrm{<span\; class="notranslate">\; \&epsiv;</span>}}<span\; class="notranslate">\; )</span>}^{<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; ,</span>$

ε is a positive number close to 0.

105. Determine whether the update times of the beamforming weights of each BS is greater than preset Y, and if the update times of the beamforming weights of each BS is less than or equal to Y, return to step 101.

In a specific application, the preset Y is: the preset Y of the outer loop termination counter.

106. If the number of updates of the beamforming weights of each BS is greater than Y, each BS requests data distribution from the data center according to the calculated beamforming matrix of itself, and sends the received data through the backhaul link to the data center. The data is jointly transmitted to each UE.

In a specific application, the overhead of the backhaul link is the sum of the zero norms of the transmit beamforming matrices of all BSs to the UE, specifically:

$\underset{\mathrm{<span\; class="notranslate">\; i</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}<span\; class="notranslate">\; =</span>{<span\; class="notranslate">\; |</span><span\; class="notranslate">\; |</span>{<span\; class="notranslate">\; |</span><span\; class="notranslate">\; |</span>{\mathrm{<span\; class="notranslate">\; V</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; |</span><span\; class="notranslate">\; |</span>}_{\mathrm{<span\; class="notranslate">\; f</span>}}^{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; ,</span><span\; class="notranslate">\; |</span><span\; class="notranslate">\; |</span>{{\mathrm{<span\; class="notranslate">\; V</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; |</span><span\; class="notranslate">\; |</span>}_{\mathrm{<span\; class="notranslate">\; f</span>}}^{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; ,</span><span\; class="notranslate">\; .</span><span\; class="notranslate">\; .</span><span\; class="notranslate">\; .</span>{<span\; class="notranslate">\; |</span><span\; class="notranslate">\; |</span>{\mathrm{<span\; class="notranslate">\; V</span>}}_{\mathrm{<span\; class="notranslate">\; ik</span>}}<span\; class="notranslate">\; |</span><span\; class="notranslate">\; |</span>}_{\mathrm{<span\; class="notranslate">\; f</span>}}^{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; |</span><span\; class="notranslate">\; |</span>}_{\mathrm{<span\; class="notranslate">\; 0</span>}}<span\; class="notranslate">\; .</span>$

In a specific application, this step 106 may include:

If the number of updates of the beamforming weights of each BS is greater than Y, each BS station according to the calculated beamforming matrix of its own, if the Frobenius norm of the beamforming matrix for a certain UE by the BS satisfies is close to zero, the BS requests the data center to distribute the data of the corresponding UE through the backhaul link; otherwise, the request is not sent.

In a specific application, each BS in this embodiment interacts with its own beamforming matrix and channel matrix through an inter-BS cooperation interface.

It should be noted that, in a specific application, in step 102 of this embodiment, after receiving the beamforming matrix of the UE fed back by the UE, all BSs retrieve the beamforming matrix sent by other BSs from the cooperative storage unit. The matrix V _s , s≠i, the channel matrix H _sj , s≠i from other BSs to the UE, the beamforming matrix of the UE fed back by the UE, and the beamforming weight matrix Θ _i of the BS itself, all users The goal is to minimize the sum of the mean square error and the sum of the backhaul link overhead. Under the power constraint P _i of each base station, the respective transmit beamforming matrices are calculated in parallel.

6-8 show schematic diagrams of simulation results of the technical solutions provided by the embodiments of the present invention. Fig. 6 shows a schematic diagram of the simulation results of the backhaul link overhead as the number of users increases according to the technical solution provided by the embodiment of the present invention. As shown in Fig. 6, it can be seen from the simulation results that compared with the The beamforming design scheme (IBA) under the ideal backhaul link with road capacity limitation, the beamforming method of the present invention can obviously reduce the backhaul link overhead. At the same time, although the scheme using Exhaustive Search (EXS) can have the lowest backhaul link overhead, its complexity is too large, especially when the number of users increases. Therefore, this method can not only significantly reduce the overhead of the backhaul link, but also has low complexity;

Fig. 7 shows a schematic diagram of the simulation results of the sum of mean square errors of all UEs as the number of users increases according to the technical solution provided by the embodiment of the present invention. As shown in Fig. 7, it can be seen from the simulation results that, compared with the The beamforming design scheme of the ideal backhaul link under the limitation of the backhaul link capacity, the present invention can achieve performance similar to the sum of mean square errors, indicating that this method can also achieve a lower sum of mean square errors. Combined with the results in Figure 6, it can be seen that this method can significantly reduce the overhead of the backhaul link while maintaining a low sum of mean square errors;

Fig. 8 is a schematic diagram showing the simulation results of the sum of mean square errors of all UEs under different numbers of transmitting and receiving antennas as the ratio SNR of the transmitting end power to white noise increases according to the technical solution provided by the embodiment of the present invention, as shown in Fig. 8 , It can be seen from the simulation results that in this method, if more transmitting antennas or receiving antennas are used, as the SNR of the transmitting end increases, the mean square error sum can be further reduced, thereby further improving the system performance .

In the joint data transmission method based on the beamforming matrix of this embodiment, by designing the beamforming matrix and performing joint data transmission based on the beamforming matrix, the sum of mean square errors can be kept low, and the overhead of the backhaul link can be significantly reduced. The resources of the backhaul link from the data center to the sending side (that is, each cooperative base station BS) are saved, and the calculation complexity is low.

Fig. 2 shows a schematic structural diagram of a data joint transmission system based on a beamforming matrix provided by an embodiment of the present invention, and Fig. 4 shows each of the sending ends in the beamforming matrix-based data joint transmission system shown in Fig. 2 A schematic structural diagram of a BS. FIG. 5 shows a schematic structural diagram of each UE at the receiving end in the beamforming matrix-based joint data transmission system shown in FIG. 2. For example, FIG. 3 shows an embodiment of the present invention Provided is a schematic diagram of a communication model of a beamforming matrix-based joint data transmission system with three coordinated base stations. The beamforming matrix-based data joint transmission system in this embodiment includes: multiple user equipment UE13 located at the receiving end, located at Multiple cooperative base stations BS12 and data centers 11 at the sending end;

Each user equipment UE13 includes: a first calculation module 13a, configured to obtain equivalent channel information from each coordinated base station BS, calculate the beamforming matrix received by itself, and feed back the beamforming matrix to all BSs;

Each cooperative base station BS12 includes:

The second calculation module 12a is used for each BS according to the beamforming matrix of other BSs, the channel information from other BSs to the UE, the beamforming matrix of the UE fed back by the UE, and the beamforming weight of each BS itself Matrix, calculating its own beamforming matrix, and sending the beamforming matrix to other BSs;

The first judging module 12b is used to judge whether the number of updates of the beamforming matrix of each BS is greater than the preset X, and if the number of updates of the beamforming matrix of each BS is less than or equal to X, return to the second calculation module 12a;

The update module 12c is configured to update the beamforming weight of each BS according to the calculated beamforming matrix of itself if the number of updates of the beamforming matrix of each BS is greater than X, and notify other BSs;

The second judging module 12d is used to judge whether the update times of the beamforming weights of each BS is greater than the preset Y, and if the update times of the beamforming weights of each BS is less than or equal to Y, return the UE's a first calculation module 13a;

The joint data transmission module 12e is used to request data distribution from the data center according to the calculated beamforming matrix of each BS if the number of updates of the beamforming weights of each BS is greater than Y, and transmit data through the backhaul chain The data received by the road and sent by the data center are jointly transmitted to each UE.

In a specific application, the preset X is: preset X of the inner loop termination counter; and

The preset Y is: the preset Y of the outer loop termination counter.

The joint data transmission system based on the beamforming matrix in this embodiment can maintain a low sum of mean square errors, significantly reduce backhaul link overhead, and save backhaul link resources from the data center to the sending side (that is, each cooperative base station BS) , and the computational complexity is low.

The beamforming matrix-based joint data transmission system of this embodiment can be used to implement the technical solution of the aforementioned method embodiment shown in FIG. 1 , and its implementation principle and technical effect are similar, and will not be repeated here.

In this embodiment, "first", "second", "third" and "fourth" do not stipulate the sequence, but only distinguish the names. In this embodiment, no any restrictions.

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

Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present invention, rather than limiting them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: It is still possible to modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some or all of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions depart from the scope defined by the claims of the present invention .

Claims (10)

1. A data joint transmission method based on a beamforming matrix, characterized in that, comprising: The user equipment UE obtains the equivalent channel information from each coordinated base station BS, calculates the beamforming matrix received by itself, and feeds back the beamforming matrix to all BSs; Each BS calculates its own beamforming based on the beamforming matrix of other BSs, the channel information from other BSs to the UE, the beamforming matrix of the UE fed back by the UE, and the beamforming weight matrix of each BS itself matrix, and send the beamforming matrix to other BSs; Judging whether the number of updates of the beamforming matrix of each BS is greater than a preset X; If the number of updates of the beamforming matrix of each BS is less than or equal to X, return the beamforming matrix of each BS based on the beamforming matrix of other BSs, the channel information from other BSs to the UE, and the beamforming information of the UE fed back by the UE. a forming matrix and a beamforming weight matrix of each BS itself, and a step of calculating its own beamforming matrix; If the update times of the beamforming matrix of each BS is greater than X, each BS updates its own beamforming weight according to the calculated beamforming matrix of itself, and informs other BSs; judging whether the number of updates of the beamforming weights of each BS itself is greater than a preset Y; If the number of updates of the beamforming weights of each BS is less than or equal to Y, return to the step of the user equipment UE obtaining the equivalent channel information from each coordinated base station BS, and calculating the beamforming matrix received by itself; If the number of updates of the beamforming weights of each BS is greater than Y, each BS requests data distribution from the data center according to its own beamforming matrix after calculation, and transmits the data received by the data center through the backhaul link Data is jointly transmitted to each UE. 2. The method according to claim 1, wherein the equivalent channel information comprises: The product of the channel H _ij matrix from each BS to the UE and the beamforming matrix V _ij that each BS performs beamforming to the corresponding UE; and The received beamforming matrix U _j calculated by the UE is: ${\mathrm{<span\; class="notranslate">\; u</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; =</span>{<span\; class="notranslate">\; (</span>\underset{\mathrm{<span\; class="notranslate">\; i</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}\underset{\mathrm{<span\; class="notranslate">\; the\; s</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}{\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; ij</span>}}{\mathrm{<span\; class="notranslate">\; V</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}{\mathrm{<span\; class="notranslate">\; V</span>}}_{\mathrm{<span\; class="notranslate">\; the\; s</span>}}^{\mathrm{<span\; class="notranslate">\; h</span>}}{\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; sj</span>}}^{\mathrm{<span\; class="notranslate">\; h</span>}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; \&sigma;</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}^{\mathrm{<span\; class="notranslate">\; 2</span>}}\mathrm{<span\; class="notranslate">\; I</span>}<span\; class="notranslate">\; )</span>}^{<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; 1</span>}}\underset{\mathrm{<span\; class="notranslate">\; i</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}{\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; ij</span>}}{\mathrm{<span\; class="notranslate">\; V</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}{\mathrm{<span\; class="notranslate">\; B</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; ,</span>$ Among them, V _i =[V _i1 ,V _i2 ,...,V _iK ] is the transmit beamforming matrix of BSi for all UEs, B _j is the data selection matrix of UEj, j∈{1,2,...,K },satisfy as well as l≠j; V _s is the beamforming matrix of other BSs except BSi, H _sj is the channel matrix from other BSs to UE except BSi, s≠i, is the variance of Gaussian white noise on UEj channel. 3. The method according to claim 2, wherein the overhead of the backhaul link is the sum of the zero norms of the transmit beamforming matrices of all BSs to the UE, specifically: $\underset{\mathrm{<span\; class="notranslate">\; i</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}{<span\; class="notranslate">\; |</span><span\; class="notranslate">\; |</span>{<span\; class="notranslate">\; |</span><span\; class="notranslate">\; |</span>{\mathrm{<span\; class="notranslate">\; V</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; |</span><span\; class="notranslate">\; |</span>}_{\mathrm{<span\; class="notranslate">\; f</span>}}^{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; ,</span>{<span\; class="notranslate">\; |</span><span\; class="notranslate">\; |</span>{\mathrm{<span\; class="notranslate">\; V</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; |</span><span\; class="notranslate">\; |</span>}_{\mathrm{<span\; class="notranslate">\; f</span>}}^{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; ,</span><span\; class="notranslate">\; .</span><span\; class="notranslate">\; .</span><span\; class="notranslate">\; .</span>{<span\; class="notranslate">\; |</span><span\; class="notranslate">\; |</span>{\mathrm{<span\; class="notranslate">\; V</span>}}_{\mathrm{<span\; class="notranslate">\; ik</span>}}<span\; class="notranslate">\; |</span><span\; class="notranslate">\; |</span>}_{\mathrm{<span\; class="notranslate">\; f</span>}}^{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; |</span><span\; class="notranslate">\; |</span>}_{\mathrm{<span\; class="notranslate">\; 0</span>}}<span\; class="notranslate">\; .</span>$ 4. The method according to claim 2, wherein each BS is based on the beamforming matrix of other BSs, the channel information from other BSs to the UE, the beamforming matrix of the UE fed back by the UE, and each The beamforming weight matrix of the BS itself, the calculated beamforming matrix V _i of itself is: V _i =P _i Y _i ; Among them, P _i is an orthogonal matrix, and P _i is calculated by the first formula, The first formula is: ${\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}^{\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; =</span>{\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}{\stackrel{<span\; class="notranslate">\; \&OverBar;</span>}{\mathrm{<span\; class="notranslate">\; h</span>}}}_{\mathrm{<span\; class="notranslate">\; i</span>}}{\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}^{\mathrm{<span\; class="notranslate">\; h</span>}}<span\; class="notranslate">\; ,</span>$ is through the pair matrix Obtained by Hessenberg decomposition, is the Hessenberg matrix; Each column of matrix Y _i It is calculated according to the second formula, The second formula is: ${\mathrm{<span\; class="notranslate">\; the\; y</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}^{\mathrm{<span\; class="notranslate">\; l</span>}}<span\; class="notranslate">\; =</span>{<span\; class="notranslate">\; [</span>{\stackrel{<span\; class="notranslate">\; \&OverBar;</span>}{\mathrm{<span\; class="notranslate">\; h</span>}}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; +</span><span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; \&theta;</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; \&lambda;</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span>\mathrm{<span\; class="notranslate">\; I</span>}<span\; class="notranslate">\; ]</span>}^{<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}^{\mathrm{<span\; class="notranslate">\; l</span>}}<span\; class="notranslate">\; ,</span>$ For the nth element on the diagonal of each BS's own beamforming weight matrix _Θi , is the lth column vector of matrix F _i , matrix matrix $G_i=\underset{j}{\mathrm{\&Sigma;}}{h}_{\mathrm{ij}}^h{u}_j{B}_j-\underset{\mathrm{the\; s}\&NotEqual;i}{\mathrm{\&Sigma;}}\underset{j}{\mathrm{\&Sigma;}}{h}_{\mathrm{ij}}^h{u}_j{u}_j^h{h}_{\mathrm{sj}}{V}_{\mathrm{the\; s}},$ matrix $Q_{i,\mathrm{no}}=Z_{i,\mathrm{no}}^h{f}_{\mathrm{no}}^i{f}_{\mathrm{no}}^H{Z}_{i,\mathrm{no}},$ is the ith column vector of matrix F _i , the matrix The eigenvalues of are decomposed into The diagonal matrix Ξ is the matrix The eigenvalue matrix of , λ _i is obtained by performing a binary search on the third formula, The third formula is: $\underset{\mathrm{<span\; class="notranslate">\; no</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}\underset{\mathrm{<span\; class="notranslate">\; m</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}\frac{{<span\; class="notranslate">\; [</span>{\mathrm{<span\; class="notranslate">\; Q</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; no</span>}}<span\; class="notranslate">\; ]</span>}_{\mathrm{<span\; class="notranslate">\; m</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; m</span>}}}{{<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; \&xi;</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; no</span>}}^{<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; m</span>}<span\; class="notranslate">\; )</span>}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; \&lambda;</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span>}^{\mathrm{<span\; class="notranslate">\; 2</span>}}}<span\; class="notranslate">\; =</span>{\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; ,</span>$ The molecule [Q _i,n ] _m,m means to take the elements on the diagonal of the matrix, are the elements on the diagonal of matrix Ξ _i,n , where n and m are each data stream and transmit antenna, respectively. 5. The method according to claim 2, wherein if the update times of the beamforming matrix of each BS is greater than X, each BS updates itself according to the calculated beamforming matrix of itself beamforming weights and inform other BSs, including: If the number of updates of the beamforming matrix of each BS is greater than X, each BS updates its own beamforming weight θ _ij according to the fourth formula according to the calculated beamforming matrix of itself, and informs other BSs; Wherein, the fourth formula is: ${\mathrm{<span\; class="notranslate">\; \&theta;</span>}}_{\mathrm{<span\; class="notranslate">\; ij</span>}}<span\; class="notranslate">\; =</span>{<span\; class="notranslate">\; (</span>{<span\; class="notranslate">\; |</span><span\; class="notranslate">\; |</span>{\mathrm{<span\; class="notranslate">\; V</span>}}_{\mathrm{<span\; class="notranslate">\; ij</span>}}<span\; class="notranslate">\; |</span><span\; class="notranslate">\; |</span>}_{\mathrm{<span\; class="notranslate">\; f</span>}}<span\; class="notranslate">\; +</span>\sqrt{\mathrm{<span\; class="notranslate">\; \&epsiv;</span>}}<span\; class="notranslate">\; )</span>}^{<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; ,</span>$ ε is a positive number close to 0. 6. The method according to claim 1, wherein if the number of updates of the beamforming weights of each BS is greater than Y, each BS sends data to the data center according to the calculated beamforming matrix of itself. Request data distribution, including: If the number of updates of the beamforming weights of each BS is greater than Y, each BS station according to the calculated beamforming matrix of its own, if the Frobenius norm of the beamforming matrix for a certain UE by the BS satisfies is close to zero, the BS requests the data center to distribute the data of the corresponding UE through the backhaul link; otherwise, the request is not sent. 7. The method according to claim 1, wherein the feeding back the beamforming matrix to all BSs comprises: The beamforming matrix is fed back to all BSs through additional channels. 8. The method according to claim 1, wherein the preset X is: preset X of the inner loop termination counter; and The preset Y is: the preset Y of the outer loop termination counter. 9. The method according to any one of claims 1-8, wherein each BS interacts with its respective beamforming matrix and channel matrix through an inter-BS cooperation interface. 10. A data joint transmission system based on a beamforming matrix, characterized in that it includes: multiple user equipment UEs located at the receiving end, multiple cooperative base stations BS located at the transmitting end, and a data center; Each user equipment UE includes: a first calculation module, configured to obtain equivalent channel information from each coordinated base station BS, calculate a beamforming matrix received by itself, and feed back the beamforming matrix to all BSs; Each cooperative base station BS includes: The second calculation module is used for each BS according to the beamforming matrix of other BSs, the channel information from other BSs to the UE, the beamforming matrix of the UE fed back by the UE, and the beamforming weight matrix of each BS itself , calculate its own beamforming matrix, and send the beamforming matrix to other BSs; The first judging module is used to judge whether the number of updates of the beamforming matrix of each BS is greater than preset X, and if the number of updates of the beamforming matrix of each BS is less than or equal to X, return to the second calculation module; An updating module, configured to update the beamforming weight of each BS according to the calculated beamforming matrix of itself if the number of updates of the beamforming matrix of each BS is greater than X, and notify other BSs; The second judging module is used to judge whether the number of updates of the beamforming weight of each BS is greater than the preset Y, and if the number of updates of the beamforming weight of each BS is less than or equal to Y, return the UE's first a computing module; The data joint transmission module is used to request data distribution from the data center according to the calculated beamforming matrix of each BS if the number of updates of the beamforming weight of each BS is greater than Y, and will pass the backhaul link The received data sent by the data center is jointly transmitted to each UE.