CN102104404A - Multi-user MIMO transmission method in wireless communication system, base station and user terminal - Google Patents

Abstract

The invention discloses a multi-user multiple-input multiple-output MU-MIMO transmission method, a base station and a user terminal in a wireless communication system. The process of the method includes: the base station receives the sounding pilot SRS of N users to perform channel estimation, and obtains downlink channel information according to the channel estimation results and the channel reciprocity of the system, wherein the N is greater than 1; The downlink channel information is subjected to QR decomposition, and the multi-user beamforming MU-BF matrix P ⁽ⁱ⁾ of the i-th user is obtained from the Q matrix obtained from the decomposition, and the downlink single-user beamforming SU-BF of the i-th user is further obtained. BF matrix V ⁽ⁱ⁾ , where i=1,...,N; the base station assigns the i-th user according to the MU-BF matrix P ⁽ⁱ⁾ and the downlink SU-BF matrix V ⁽ⁱ⁾ The transmitted data is subjected to beamforming processing. The method and device of the present invention fully utilize the channel reciprocity and QR decomposition of the system to obtain the beamforming matrix for uplink and downlink MU-MIMO transmission, which can improve the transmission performance of MU-MIMO.

Description

Transmission method, base station and user terminal of multi-user MIMO in wireless communication system

technical field

The present invention relates to the field of wireless communication, in particular to a multi-user multiple-input multiple-output (MU-MIMO) transmission method in a wireless communication system (such as an LTE-A system), a base station and a user terminal for MU-MIMO transmission.

Background technique

Multiple Input Multiple Output (MIMO) technology has become one of the key technologies of broadband wireless communication systems including 3GPP Long Term Evolution (LTE) because it can effectively improve the spectrum efficiency of wireless links. According to whether multiple users can be supported simultaneously on the same time-frequency resource, MIMO technology can be further divided into single-user MIMO (SU-MIMO) and multi-user MIMO (MU-MIMO). Among them, MU-MIMO has more advantages, such as supporting more flexible user antenna configuration, stronger adaptability to channel conditions, and multi-user diversity gain. MU-MIMO is applicable to both the uplink and downlink of the cellular system, but the downlink MU-MIMO puts forward higher requirements for the channel state information (CSIT) on the transmitter side, that is, the base station (eNB) must obtain each user (UE) downlink channel information. The acquisition of CSIT is usually divided into two situations:

For a Time Division Duplex (TDD) system, since the uplink and downlink occupy the same frequency resources, there is reciprocity between the uplink and downlink wireless channels, and the downlink channel can be easily inferred from the uplink channel, and vice versa.

For the frequency division duplex (FDD) system, because the uplink and downlink occupy different frequency resources, most of the uplink and downlink wireless channels do not have reciprocity, or the reciprocity in the FDD system is more difficult to obtain, so Most of CSIT is obtained by means of feedback channels. Of course, in order to reduce the amount of feedback, codebook design or quantization techniques can be used.

In specific implementation, SU-MIMO and MU-MIMO usually need to preprocess the transmitted signal according to CSIT to achieve the purpose of matching channels and eliminating multi-user interference (MUI, multi-userinterference). The above operations are called precoding or Beamforming. Due to the different description habits of different technical scenarios, the two names may be used interchangeably in this application, but the meanings of the two are the same.

At present, the uplink design of 3GPP LTE Rel-8 can only support virtual MU-MIMO, that is, it can support multiple single-antenna UEs to send data at the same time; while the downlink design is mainly optimized for SU-MIMO, which supports MU-MIMO very well. Limited, unable to support the transmission of multiple UEs and multiple data streams per UE. In addition, in order to simplify the system design, LTE Rel-8 adopts almost the same design for FDD and TDD, that is, both use codebook-based beamforming, and do not take advantage of the possible reciprocity of wireless channels.

As the standard formulation work of LTE Rel-8 draws to a close, 3GPP started the research work of LTE-A in mid-2008. LTE-A is the subsequent evolution of LTE, which puts higher requirements on system performance, such as requiring the LTE-A system to support MU-MIMO transmission with multiple UEs and multiple data streams per UE. Therefore, how to effectively support uplink and downlink MU-MIMO in the LTE-A system has become a research hotspot. Furthermore, in the technical discussion for LTE-A, how to make full use of the reciprocity of wireless channels to support non-codebook beamforming is attracting more and more attention, especially for TDD systems.

In view of the above problems, the most common method in the prior art is to use independent MU-MIMO transmission for the uplink and downlink of the cellular system, and the simplest implementation scheme (Scheme 1) is that the downlink MU-MIMO is based on block diagonalization (BD) for transmission, and the uplink MU-MIMO does not perform processing at the transmitting end but only uses multi-user detection (MUD) for reception. Although the first solution is simple to implement, it only considers how to eliminate the mutual interference between multiple users and does not make further use of the characteristics of the wireless channel, thus sacrificing the spectral efficiency to a certain extent.

On the basis of Solution 1, the prior art also proposes a joint MU-MIMO solution (Solution 2) for the uplink and downlink of the TDD system. That is: after the downlink MU-MIMO eliminates multi-user interference with the help of the BD criterion, the equivalent channel of each UE is decomposed by SVD, so as to realize the characteristic transmission for each UE; under the premise that the uplink and downlink use the same wireless channel for data transmission , the uplink MU-MIMO can also realize the characteristic transmission of each UE. It can be seen that the scheme 2 realizes the orthogonal transmission of multiple data streams of multiple uplink and downlink users at the same time, so that the spectrum efficiency is improved. However, the complexity of SVD decomposition is very high, and the numerical stability is poor, so there are certain obstacles in the realization of the second scheme. At the same time, solution 2 requires that the uplink and downlink must use the same wireless channel for data transmission, which sometimes cannot be satisfied in an actual cellular system, and also limits the feasibility of uplink MU-MIMO in solution 2.

Contents of the invention

In view of this, the main purpose of the present invention is to provide a MU-MIMO transmission method, base station and user terminal.

In order to achieve the above object, the technical solution of the present invention is specifically realized in the following way:

A multi-user multiple-input multiple-output MU-MIMO transmission method in a wireless communication system, comprising:

The base station receives sounding pilot SRSs sent from N user terminals UE to perform channel estimation, and generates a downlink channel information matrix according to the channel estimation results and the channel reciprocity of the system, wherein the N is greater than 1;

The base station performs QR decomposition on the generated downlink channel information matrix, obtains the multi-user beamforming MU-BF matrix P ⁽ⁱ⁾ of the i-th UE from the Q matrix obtained by the decomposition, and further obtains the i-th UE's Downlink single-user beamforming SU-BF matrix V ⁽ⁱ⁾ , where i=1,...,N;

The base station performs beamforming processing on the transmission data of the i-th UE according to the MU-BF matrix P ⁽ⁱ⁾ and the downlink SU-BF matrix V ⁽ⁱ⁾ .

The method further includes:

According to the MU-BF matrix and the downlink SU-BF matrix of the i-th UE, the base station performs transmit beamforming processing on the user-specific pilot of the UE, and sends it to the UE.

The method further includes:

The i-th UE receives the downlink pilot sent by the base station to perform channel estimation, and obtains a downlink channel information matrix for the UE;

The UE performs QR decomposition on the downlink channel information matrix, and obtains its own uplink single-user beamforming SU-BF matrix U ⁽ⁱ⁾ from the decomposed Q matrix;

Perform beamforming processing on the transmit data according to the uplink SU-BF matrix.

The UE performs QR decomposition on the downlink channel information matrix to obtain the uplink SU-BF matrix including:

The i-th UE receives the user-specific pilot sent by the base station to perform channel estimation, and obtains the downlink equivalent channel matrix;

The UE performs QR decomposition on the downlink equivalent channel matrix, and uses the decomposed Q matrix as the first uplink SU-BF matrix of the UE.

The UE performs QR decomposition on the downlink channel information matrix to obtain the uplink SU-BF matrix including:

The i-th UE receives the cell-specific pilot sent by the base station to perform channel estimation, obtains the downlink physical channel matrix, and obtains the uplink physical channel matrix according to channel reciprocity;

The UE performs QR decomposition on the uplink physical channel matrix, and obtains a second uplink SU-BF matrix of the UE from the decomposed Q matrix.

The method further includes:

The UE performs conjugate transposition on the uplink SU-BF matrix;

MIMO detection is performed after performing beamforming processing on the received data of the UE according to the conjugate transposition of the uplink SU-BF matrix.

The method further includes: the UE transmits the uplink demodulation pilot DMRS to the base station after performing beamforming processing on the uplink demodulation pilot DMRS according to the uplink SU-BF matrix.

The method further includes:

The base station performs conjugate transposition on the MU-BF matrix and the downlink SU-BF matrix of the i-th UE;

According to the conjugate transposition of the MU-BF matrix of the UE, multi-user interference cancellation MUI is performed on the received data of the base station to obtain the received data of the i-th UE, and then the conjugate transpose of the downlink SU-BF matrix is used to After the received data of the UE is processed, MIMO detection is performed.

The base station obtains the downlink single-user beamforming SU-BF matrix V ⁽ⁱ⁾ of the i-th UE including:

The base station obtains H (i) P (i) according to the downlink physical channel matrix H ⁽ⁱ⁾ and MU-BF matrix P ^{(i) of} the i-th UE, and performs QR decomposition on H ^{( i)} P ⁽ⁱ⁾ , Obtain the downlink SU-BF matrix V ⁽ⁱ⁾ of the UE.

The UE obtaining its own uplink single-user beamforming SU-BF matrix U ⁽ⁱ⁾ includes:

The UE multiplies the uplink physical channel matrix H _UL ⁽ⁱ⁾ and the conjugate transposition H _UL ^(i)H of the uplink physical channel matrix to obtain H _UL ^(i)H H _UL ⁽ⁱ⁾ , and then H _UL ^{(i) H} H _UL ⁽ⁱ⁾ and U _t-1 ⁽ⁱ⁾ are multiplied and subjected to QR decomposition to obtain the uplink SU-BF matrix U _t ⁽ⁱ⁾ .

A base station for multi-user multiple-input multiple-output MU-MIMO transmission, comprising:

A channel estimation unit, configured to perform channel estimation to obtain uplink channel information of more than one user terminal UE, and obtain a downlink channel information matrix according to channel reciprocity;

The QR decomposition unit is configured to perform QR decomposition on the downlink channel information matrix, obtain the multi-user beamforming MU-BF matrix of each UE from the decomposed Q matrix, and further obtain the downlink single-user beamforming of each UE SU-BF matrix;

The transmit beamforming unit is configured to perform beamforming processing on the transmit data of the corresponding UE according to the MU-BF matrix and the downlink SU-BF matrix of each UE, and send it to the antenna of the base station for transmission.

The QR decomposition unit is further used to provide the decomposed R matrix to the MIMO detection unit;

The MIMO detection unit is configured to perform MIMO detection on the received data of the antenna according to the R matrix, and recover the transmitted data of each UE.

The QR decomposition unit is further used to perform conjugate transposition on the MU-BF matrix and the downlink SU-BF matrix of each UE, and provide them to the receiving beamforming unit;

The receiving beamforming unit is configured to perform multi-user interference cancellation (MUI) on the received data of the antenna according to the conjugate transpose of the MU-BF matrix of each UE, to obtain the received data of each UE, and then use the downlink SU- The conjugate transposition of the BF matrix processes the received data of the corresponding UE and sends it to the MIMO detection unit.

The QR decomposition unit is further configured to perform adaptive modulation and coding (AMC) control on the transmission data streams of the one or more UEs according to the R matrix obtained through decomposition.

The QR decomposition unit is used to obtain H (i) ^{P (i)} according to the downlink physical channel matrix H ⁽ⁱ⁾ and MU-BF matrix P ( ⁱ⁾ of each UE, and perform H ^{( i)} P ⁽ⁱ⁾ QR decomposition to obtain the downlink SU-BF matrix V ⁽ⁱ⁾ of each UE, where i is any integer from 1 to the number N of users.

The channel estimation unit is used to perform channel estimation according to the sounding pilot SRS sent by each UE, or obtain uplink channel information according to the uplink demodulation pilot DMRS sent by each UE, and obtain the downlink channel information matrix according to channel reciprocity .

The transmit beamforming unit is further configured to perform beamforming processing on the user-specific pilots sent to each UE according to the MU-BF matrix and the downlink SU-BF matrix of each UE.

A user terminal UE for multi-user multiple-input multiple-output MU-MIMO transmission, comprising:

A channel estimation unit, configured to perform channel estimation to obtain a downlink channel information matrix of the UE;

The QR decomposition unit is configured to perform QR decomposition on the downlink channel information matrix, and obtain the uplink single-user beamforming SU-BF matrix of the UE from the Q matrix obtained through decomposition;

The transmitting beamforming unit is configured to perform beamforming processing on the transmitting data according to the uplink SU-BF matrix of the UE, and transmit it from the antenna of the UE.

The channel estimation unit is used to perform channel estimation according to the user-specific pilot sent by the base station to obtain a downlink equivalent channel matrix;

The QR decomposition unit is configured to perform QR decomposition on the downlink equivalent channel matrix, and use the decomposed Q matrix as the first uplink SU-BF matrix of the UE.

The channel estimation unit is used to perform channel estimation according to the cell-specific pilot sent by the base station, obtain a downlink physical channel matrix, and obtain an uplink physical channel matrix according to channel reciprocity;

The QR decomposition unit is configured to perform QR decomposition on the uplink physical channel matrix, and obtain the second uplink SU-BF matrix of the UE from the Q matrix obtained through decomposition.

The QR decomposition unit is further used to provide the decomposed R matrix to the MIMO detection unit;

The MIMO detection unit is configured to perform MIMO detection on the received data of the UE according to the R matrix.

The QR decomposition unit is further used to perform conjugate transposition of the uplink SU-BF matrix of the UE, and provide it to the receiving beamforming unit;

The receiving beamforming unit is configured to process the received data of the UE according to the conjugate transposition of the uplink SU-BF matrix, and send it to the MIMO detecting unit.

The QR decomposition unit is further configured to perform adaptive modulation and coding (AMC) control on more than one transmit data stream of the UE according to the R matrix obtained through decomposition.

The transmit beamforming unit is further configured to perform beamforming processing on the uplink demodulation pilot DMRS according to the uplink SU-BF matrix of the UE.

It can be seen from the above technical solution that the MU-MIMO transmission method of the present invention calculates the beamforming matrix (including MU-BF matrix and SU -BF matrix), and on this basis, simplify and optimize the transceiver structure (base station and user terminal) to facilitate engineering implementation. It can be seen that the present invention makes full use of the reciprocity of wireless channels in the communication system, and designs a non-codebook MU-MIMO transmission scheme for the uplink and downlink of the LTE-A system to support multi-user multi-data stream transmission. This kind of non-codebook beamforming can achieve more accurate matching of wireless channels to improve transmission performance, and at the same time, there is no need to feed back the precoding matrix index value (PMI), thereby reducing feedback overhead and improving spectral efficiency.

Description of drawings

FIG. 1 is a system model of MU-MIMO in an embodiment of the present invention;

FIG. 2 is a flow chart of MU-MIMO uplink and downlink transmission when the uplink and downlink resource allocation is the same in one embodiment of the present invention;

FIG. 3 is a schematic diagram of QRD iteration on the eNB side;

FIG. 4 is a flow chart of MU-MIMO downlink transmission when uplink and downlink resource allocations are different in one embodiment of the present invention;

FIG. 5 is a flow chart of MU-MIMO uplink transmission when uplink and downlink resource allocations are different in one embodiment of the present invention;

FIG. 6 is a schematic diagram of QRD iteration on the UE side;

FIG. 7 is a schematic structural diagram of a base station used for MU-MIMO transmission in an embodiment of the present invention;

FIG. 8 is a schematic structural diagram of a user terminal used for MU-MIMO transmission in an embodiment of the present invention;

FIG. 9 is a schematic diagram of comparison of downlink throughput performance between the prior art and the embodiment of the present invention;

FIG. 10 is a schematic diagram of a comparison between the prior art and the embodiment of the present invention in terms of uplink throughput performance.

Detailed ways

In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings and examples.

In one embodiment of the present invention, the system model of MU-MIMO transmission is shown in Figure 1. This model considers the situation of 1 base station (eNB) and 2 users (UE). These 2 UEs are selected through multi-user scheduling. independent users. The eNB has 4 antennas, and each UE has 2 antennas. It should be noted that since there may be many users in the cellular system, before MU-MIMO transmission, several users with independent spatial channels should be selected by means of multi-user scheduling algorithm to participate in MU-MIMO transmission. In the following description, only consider how to perform MU-MIMO transmission between independent users after multi-user scheduling is completed.

For the system model shown in Figure 1, the signal model of downlink MU-MIMO transmission is expressed as:

${\mathrm{<span\; class="notranslate">\; the\; y</span>}}_{\mathrm{<span\; class="notranslate">\; DL</span>}}^{<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; )</span>}<span\; class="notranslate">\; =</span>{\mathrm{<span\; class="notranslate">\; h</span>}}^{<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; )</span>}\underset{\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{\mathrm{<span\; class="notranslate">\; 2</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}}{\mathrm{<span\; class="notranslate">\; P</span>}}^{<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; )</span>}{\mathrm{<span\; class="notranslate">\; V</span>}}^{<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; )</span>}{\mathrm{<span\; class="notranslate">\; d</span>}}_{\mathrm{<span\; class="notranslate">\; DL</span>}}^{<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; )</span>}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; no</span>}}_{\mathrm{<span\; class="notranslate">\; DL</span>}}^{<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; )</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1,2</span>}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; )</span>$

in:

y _DL ⁽ⁱ⁾ is the received signal vector (2*1) of the i-th UE;

H ⁽ⁱ⁾ is the downlink channel matrix (2*4) from eNB to the i-th UE;

P ^(k) is the multi-user beamforming (MU-BF) matrix (4*2) of the kth UE;

V ^(k) is the downlink single user beamforming (SU-BF) matrix (2*2) of the kth UE;

d _DL ^(k) is the downlink data flow vector (2*1) of the i-th UE;

n _DL ⁽ⁱ⁾ is an Additive White Gaussian Noise (AWGN, Additive White Gaussian Noise) noise vector (2*1) of the i-th UE.

Assuming that the radio resource allocation of uplink and downlink is the same, the signal model of uplink MU-MIMO transmission can be expressed as:

${\mathrm{<span\; class="notranslate">\; the\; y</span>}}_{\mathrm{<span\; class="notranslate">\; UL</span>}}<span\; class="notranslate">\; =</span>\underset{\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{\mathrm{<span\; class="notranslate">\; 2</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}}{<span\; class="notranslate">\; [</span>{\mathrm{<span\; class="notranslate">\; h</span>}}^{<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; )</span>}<span\; class="notranslate">\; ]</span>}^{\mathrm{<span\; class="notranslate">\; h</span>}}{\mathrm{<span\; class="notranslate">\; u</span>}}^{<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; )</span>}{\mathrm{<span\; class="notranslate">\; d</span>}}_{\mathrm{<span\; class="notranslate">\; UL</span>}}^{<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; )</span>}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; no</span>}}_{\mathrm{<span\; class="notranslate">\; UL</span>}}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 2</span>}<span\; class="notranslate">\; )</span>$

in:

y _UL is the received signal vector (4*1) of eNB;

[H ⁽ⁱ⁾ ] ^H is the uplink channel matrix (4*2) from the i-th UE to the eNB;

U ⁽ⁱ⁾ is the uplink single user beamforming (SU-BF) matrix (2*2) of the i-th UE;

d _UL ⁽ⁱ⁾ is the uplink data flow vector (2*1) of the i-th UE;

n _UL is the AWGN noise vector (4*1) of the eNB.

It should be pointed out that in a TDD system, when the uplink and downlink occupy the same wireless channel, there is reciprocity between the uplink and downlink wireless channels, that is, if the downlink channel matrix from the eNB to the i-th UE is expressed as H ⁽ⁱ⁾ , then the uplink channel matrix from the i-th UE to the eNB can be expressed as [H ⁽ⁱ⁾ ] ^T , that is, the uplink and downlink channel matrix satisfies the transpose relationship. In the embodiment of the present invention, in order to simplify the calculation of the uplink and downlink SU-BF matrix, it is necessary to satisfy the conjugate transposition relationship between the uplink and downlink channel matrices, that is, if the downlink channel matrix from the eNB to the i-th UE is expressed as H ⁽ⁱ⁾ , then the uplink channel matrix from the i-th UE to the eNB is expressed as [H ⁽ⁱ⁾ ] ^T . In order to satisfy the conjugate transpose relationship, it is only necessary to perform a conjugate operation once before the uplink signal is transmitted and before the uplink received signal is processed.

Based on the model in Figure 1, under the premise that the uplink and downlink radio resources are allocated the same, the process of joint uplink and downlink MU-MIMO transmission is shown in Figure 2, including the following steps:

Step 201: multiple UEs (assuming that the number of users is N, and N is greater than 1) send sounding pilots (SRS) to the eNB, wherein the i-th UE is UE _i , i=1, . . . , N. In this embodiment, N=2.

Step 202: The eNB performs channel estimation according to the SRS, obtains the uplink physical channels of multiple UEs, and then infers the downlink physical channels according to the channel reciprocity $h_{\mathrm{DL}}\stackrel{\mathrm{\&Delta;}}{=}\left[\begin{array}{c}{h}^{\left(1\right)}\\ h^{\left(2\right)}\end{array}\right].$

Step 203: The eNB performs 4*4QR decomposition (QRD, QR decomposition), and calculates a respective MU-BF matrix P ⁽ⁱ⁾ for each UE, where i=1,2. Among them, QR decomposition is also called orthogonal matrix triangulation, that is, a certain matrix A is decomposed into an orthogonal matrix Q and an upper triangular matrix R.

Taking P ⁽²⁾ as an example, perform QRD on the conjugate transpose H ^H of _HDL , and obtain H ^H =QR. Among them, Q is a 4*4 unitary matrix, R is a 4*4 upper triangular matrix, and the first 2 columns and the last 2 columns of Q are written as 2 sub-arrays, that is, Q=[Q ⁽¹⁾ Q ⁽²⁾ ] . Then, P ⁽²⁾ = Q ⁽²⁾ is the MU-BF matrix of UE2, satisfying H ⁽¹⁾ P ⁽²⁾ = 0 _2×2

Step 204: eNB calculates H (i) P (i) according to UE _i 's downlink physical channel H ⁽ⁱ⁾ and MU ^- BF matrix P ^{(i) ,} i=1, 2, for H ⁽ⁱ⁾ P ⁽ⁱ⁾ , i=1, 2 to perform 2*2 QRD iterations to obtain the downlink SU-BF matrix V ⁽ⁱ⁾ of UE _i .

The specific iterative process is shown in Figure 3. As the number of iterations increases, the interference between multiple data streams of UE _i decreases, but the calculation delay increases accordingly, and usually one iteration can achieve better performance.

Step 205: The eNB uses the cascaded BF matrix P ⁽ⁱ⁾ V ⁽ⁱ⁾ to perform beamforming (Tx-BF) on the transmission data.

Step 206: The eNB also performs the same beamforming on the user-specific pilot (UE-specific RS).

Step 207: The eNB sends downlink control information (DCI, Downlink Control Information) for data transmission to each UE. It should be noted that this step is optional.

Step 208: the eNB sends beamformed user-specific pilots and data to each UE.

Step 209: The UE performs channel estimation according to the received user-specific pilot to obtain the downlink equivalent channel ${\tilde{h}}_{\mathrm{DL}}^{\left(i\right)}=h^{\left(i\right)}{P}^{\left(i\right)}{V}^{\left(i\right)}.$

Step 210: The UE performs 2*2QRD on the downlink equivalent channel, and the obtained Q matrix is the first uplink SU-BF matrix U ₁ ⁽ⁱ⁾ of the UE. That is to say, the first uplink SU-BF matrix U ₁ ⁽ⁱ⁾ is based on the downlink equivalent channel owned.

需要指出，该步骤是可选的。Step 211: Use the conjugate transpose [U ₁ ⁽ⁱ⁾ ] ^H of the first uplink SU-BF matrix U ₁ ⁽ⁱ⁾ of the UE as the receive beamforming (Rx-BF) of the UE to obtain the received beamformed data

It should be noted that this step is optional.

${\stackrel{<span\; class="notranslate">\; ~</span>}{\mathrm{<span\; class="notranslate">\; d</span>}}}_{\mathrm{<span\; class="notranslate">\; DL</span>}}^{<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; )</span>}<span\; class="notranslate">\; =</span>{<span\; class="notranslate">\; [</span>{\mathrm{<span\; class="notranslate">\; u</span>}}^{<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; )</span>}<span\; class="notranslate">\; ]</span>}^{\mathrm{<span\; class="notranslate">\; h</span>}}{\mathrm{<span\; class="notranslate">\; the\; y</span>}}_{\mathrm{<span\; class="notranslate">\; DL</span>}}^{<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; )</span>}<span\; class="notranslate">\; =</span>{\mathrm{<span\; class="notranslate">\; R</span>}}_{\mathrm{<span\; class="notranslate">\; DL</span>}}^{<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; )</span>}{\mathrm{<span\; class="notranslate">\; d</span>}}_{\mathrm{<span\; class="notranslate">\; DL</span>}}^{<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; )</span>}<span\; class="notranslate">\; +</span>{\stackrel{<span\; class="notranslate">\; ~</span>}{\mathrm{<span\; class="notranslate">\; no</span>}}}_{\mathrm{<span\; class="notranslate">\; DL</span>}}^{<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; )</span>}$

进行2*2QRD之后得到的上三角阵；d_DL ⁽ⁱ⁾为第i个UE的下行数据流矢量(2*1)； ${\tilde{n}}_{\mathrm{DL}}^{\left(i\right)}={\left[U^{\left(i\right)}\right]}^H{n}_{\mathrm{DL}}^{\left(i\right)}.$ in, $R_{\mathrm{DL}}^{\left(i\right)}=\left[\begin{array}{cc}{r}_{\mathrm{DL},11}^{\left(i\right)}& r_{\mathrm{DL},12}^{\left(i\right)}\\ 0& r_{\mathrm{DL},\mathrm{twenty\; two}}^{\left(i\right)}\end{array}\right],$ The R _DL ⁽ⁱ⁾ is the downlink equivalent channel

The upper triangular matrix obtained after performing 2*2QRD; d _DL ⁽ⁱ⁾ is the downlink data flow vector (2*1) of the i-th UE; ${\widetilde{\mathrm{no}}}_{\mathrm{DL}}^{\left(i\right)}={\left[u^{\left(i\right)}\right]}^h{\mathrm{no}}_{\mathrm{DL}}^{\left(i\right)}.$

Step 212: The UE performs MIMO detection on the received data.

进行MIMO检测。考虑到LTE-A系统的下行链路基于正交频分多址(OFDMA)，R_DL ⁽ⁱ⁾的这种上三角结构可以支持多种不同的MIMO检测算法，包括QR-SIC、QRM-MLD、SD等。需要指出的是，在图2所示的MU-MIMO传输中，接收波束成型的操作是可选的，因此也可直接对y_DL ⁽ⁱ⁾进行ZF/MMSE检测或ML检测。If step 211 is executed, after receiving beamforming, the UE

Perform MIMO detection. Considering that the downlink of the LTE-A system is based on Orthogonal Frequency Division Multiple Access (OFDMA), this upper triangular structure of R _DL ⁽ⁱ⁾ can support a variety of different MIMO detection algorithms, including QR-SIC, QRM-MLD , SD, etc. It should be pointed out that in the MU-MIMO transmission shown in FIG. 2 , the operation of receive beamforming is optional, so ZF/MMSE detection or ML detection can also be directly performed on y _DL ⁽ⁱ⁾ .

Step 213: The UE uses the first uplink SU-BF matrix U ₁ ⁽ⁱ⁾ to send data, and performs the same beamforming on the uplink demodulation pilot (DMRS).

Step 214: UE sends the beamforming processed DMRS and data to eNB.

Step 215: The eNB uses the conjugate transpose [P ⁽ⁱ⁾ ] ^H of the MU-BF matrix to perform multi-user interference (MUI) cancellation, thereby separating uplink data streams of different UEs. It should be noted that this step is optional.

Step 216: The eNB performs channel estimation according to the DMRS.

需要指出，这两个步骤也是可选的。Steps 217-218: The eNB obtains the UE's downlink SU-BF matrix V ⁽ⁱ⁾ through QRD, and uses its conjugate transpose [V ⁽ⁱ⁾ ] ^H to perform receive beamforming to obtain beamformed received data

It should be pointed out that these two steps are also optional.

${\stackrel{<span\; class="notranslate">\; ~</span>}{\mathrm{<span\; class="notranslate">\; d</span>}}}_{\mathrm{<span\; class="notranslate">\; DL</span>}}^{<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; )</span>}<span\; class="notranslate">\; =</span>{<span\; class="notranslate">\; [</span>{\mathrm{<span\; class="notranslate">\; V</span>}}^{<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; )</span>}<span\; class="notranslate">\; ]</span>}^{\mathrm{<span\; class="notranslate">\; h</span>}}{<span\; class="notranslate">\; [</span>{\mathrm{<span\; class="notranslate">\; P</span>}}^{<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; )</span>}<span\; class="notranslate">\; ]</span>}^{\mathrm{<span\; class="notranslate">\; h</span>}}{\mathrm{<span\; class="notranslate">\; the\; y</span>}}_{\mathrm{<span\; class="notranslate">\; UL</span>}}<span\; class="notranslate">\; =</span>{\mathrm{<span\; class="notranslate">\; R</span>}}_{\mathrm{<span\; class="notranslate">\; UL</span>}}^{<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; )</span>}{\mathrm{<span\; class="notranslate">\; d</span>}}_{\mathrm{<span\; class="notranslate">\; UL</span>}}^{<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; )</span>}<span\; class="notranslate">\; +</span>{\stackrel{<span\; class="notranslate">\; ~</span>}{\mathrm{<span\; class="notranslate">\; no</span>}}}_{\mathrm{<span\; class="notranslate">\; UL</span>}}^{<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; )</span>}$

in, $R_{\mathrm{UL}}^{\left(i\right)}=\left[\begin{array}{cc}{r}_{\mathrm{UL},11}^{\left(i\right)}& r_{\mathrm{UL},12}^{\left(i\right)}\\ 0& r_{\mathrm{UL},\mathrm{twenty\; two}}^{\left(i\right)}\end{array}\right],$ The R _UL ⁽ⁱ⁾ is the uplink equivalent channel at this time ${\tilde{h}}_{\mathrm{UL}}^{\left(i\right)}={\left[V^{\left(i\right)}\right]}^h{\left[P^{\left(i\right)}\right]}^h{\left[h^{\left(i\right)}\right]}^h{u}^{\left(i\right)}$ The upper triangular matrix obtained after performing 2*2QRD; d _UL ⁽ⁱ⁾ is the uplink data flow vector (2*1) of the i-th UE; ${\widetilde{\mathrm{no}}}_{\mathrm{UL}}^{\left(i\right)}={\left[V^{\left(i\right)}\right]}^h{\left[P^{\left(i\right)}\right]}^h{\mathrm{no}}_{\mathrm{UL}}.$ Considering that the uplink of the LTE-A system is based on single carrier frequency division multiple access (SC-FDMA), this upper triangular structure of R _UL ⁽ⁱ⁾ can support the MIMO detection algorithm based on QR-SIC.

Step 219: the eNB uses R _UL ⁽ⁱ⁾ to perform MIMO detection.

It should be noted that, in the process shown in FIG. 2, there are two situations after step 214:

(1) If the eNB performs uplink joint detection, it does not need to perform receive beamforming operations. Then, eNB performs channel estimation according to DMRS to obtain the uplink equivalent channel ${\tilde{h}}_{\mathrm{UL}}^{\left(i\right)}={\left[h^{\left(i\right)}\right]}^h{u}^{\left(i\right)},$ Then directly perform ZF/MMSE detection on _yUL .

进行MIMO检测。(2) If ^the eNB performs uplink independent detection, use the conjugate transpose [P ⁽ⁱ⁾ ] ^H of the MU-BF matrix to separate the uplink data streams of different UEs, and then use the common Yoke transpose [V ⁽ⁱ⁾ ] ^H for receive beamforming, and then

Perform MIMO detection.

So far, a complete downlink MU-MIMO+uplink MU-MIMO transmission process is completed. Among them, the eNB uses the MU-BF matrix P ⁽ⁱ⁾ and the downlink SU-BF matrix V ⁽ⁱ⁾ to perform Tx-BF, and each UE participating in MU-MIMO transmission uses the first uplink SU-BF matrix U ₁ ⁽ⁱ⁾ to perform Tx-BF Tx-BF. Optionally, each UE can also use the conjugate transpose of the first uplink SU-BF matrix to perform Rx-BF, and the eNB can also use the conjugate transpose of the MU-BF matrix and the downlink SU-BF matrix to perform Rx-BF .

(见步骤209)和(见步骤216)继续进行下去。当信道条件发生改变时，则需要重新开始一轮图2所示的流程。On the premise that the channel condition does not change, the uplink and downlink MU-MIMO transmission can be based on the obtained P ⁽ⁱ⁾ , V ⁽ⁱ⁾ and U ⁽ⁱ⁾ , and

(see step 209) and (see step 216) proceed. When the channel condition changes, it is necessary to restart a round of the process shown in FIG. 2 .

In the above process, the specific iteration of step 204 is shown in Figure 3, including: the matrix H ⁽ⁱ⁾ P ⁽ⁱ⁾ passes through the Hermitian transposer 301 to obtain P ^(i)H H ^(i)H , and the other path passes through the matrix multiplier 302 and $V_{t-1}^{\left(i\right)}(V_0^{\left(i\right)}=I_{2\&times;2})$ Multiply to get H ⁽ⁱ⁾ P ⁽ⁱ⁾ V _t-1 ⁽ⁱ⁾ . H ⁽ⁱ⁾ P ⁽ⁱ⁾ V _t-1 ⁽ⁱ⁾ gets U _t-1 ⁽ⁱ⁾ after passing through the QR decomposer 303, and U _t-1 ⁽ⁱ⁾ passes through the matrix multiplier 304 and P ^{(i) H} H ^{( i) Multiply H} to get P ^(i)H H ^(i)H U _t-1 ⁽ⁱ⁾ . P ^{(i) H} H ^{(i) H} U _t-1 ⁽ⁱ⁾ passes through the QR decomposer 305 to obtain V _t ⁽ⁱ⁾ and R _t ⁽ⁱ⁾ respectively. According to the preset number of iterations, V _t ⁽ⁱ⁾ can also be used as $V_{t-1}^{\left(i\right)}(V_0^{\left(i\right)}=I_{2\&times;2})$ Feedback to the matrix multiplier 302.

The uplink and downlink MU-MIMO transmission process shown in FIG. 2 requires that the uplink and downlink radio resource allocations are the same. When the wireless resource allocation of uplink and downlink is different, the transmission process of downlink MU-MIMO and uplink MU-MIMO should be carried out independently, as shown in Figure 4 and Figure 5 respectively, but the reciprocity of uplink and downlink wireless channels can still be used .

It can be seen from FIG. 4 that the difference in resource allocation does not affect the downlink MU-MIMO transmission process. This process is similar to steps 201-212 in FIG. 2 and will not be repeated here. Wherein, optional steps (such as steps 407, 410, 411) are shown by dotted lines.

Fig. 5 is an uplink MU-MIMO transmission process when the uplink and downlink resource allocations are different in one embodiment of the present invention. This process is different from that in Fig. 2, specifically including:

For steps 501-504, refer to the corresponding steps in FIG. 2 . Specifically, step 501 is similar to step 201, step 502 is similar to step 202, step 503 is similar to step 207, and step 504 is similar to step 208. The difference is that the eNB in FIG. RS).

Step 505: The UE performs channel estimation according to the cell-specific pilot sent by the eNB, obtains the 2*4 downlink physical channel H ⁽ⁱ⁾ , and then deduces the 4*2 uplink physical channel H _UL ⁽ⁱ⁾ according to channel reciprocity as [ H ⁽ⁱ⁾ ] ^T .

Step 506: According to the uplink physical channel matrix H _UL ⁽ⁱ⁾ , the UE performs 2*2QRD iteration to obtain the second uplink SU-BF matrix U ₂ ⁽ⁱ⁾ (also denoted as U _phy ⁽ⁱ⁾ ), the iteration can be obtained by Set a different number of iterations to control. It should be noted that the second uplink SU-BF matrix U ₂ ⁽ⁱ⁾ at this time is calculated based on the uplink physical channel, which is different from the first uplink SU-BF matrix U ₁ calculated based on the downlink equivalent channel in Figure 2 ⁽ⁱ⁾ .

Step 507: The UE uses the second uplink SU-BF matrix U ₂ ⁽ⁱ⁾ to transmit data, and the DMRS also needs to perform the same transmit beamforming.

Step 508: UE sends beamformed DMRS and data to eNB.

Steps 509-510: The eNB performs channel estimation according to the DMRS to obtain an equivalent channel, and performs joint ZF/MMSE detection.

In addition, the specific iteration of step 506 is shown in Figure 6, including: sending the uplink physical channel matrix H _UL ⁽ⁱ⁾ to the Hermitian transposer 601 to obtain H _UL ^{(i) H} , and sending the other way to the matrix multiplier 602 and H _UL ^(i)H is multiplied to obtain H _UL ^(i)H H _UL ⁽ⁱ⁾ ; H _UL ^(i)H H _UL ⁽ⁱ⁾ is sent to matrix multiplier 603 and U _t-1 (U ₀ =I) After multiplication, U _t is obtained through the QR decomposer 604; U _t is fed back to the matrix multiplier 602 as U _t-1 (U ₀ =I).

Of course, the method described in the embodiment of the present invention can be directly extended to the situation of any number of users and antennas, as long as the constraint relationship (3) is satisfied.

${\mathrm{<span\; class="notranslate">\; no</span>}}_{\mathrm{<span\; class="notranslate">\; eNB</span>}}<span\; class="notranslate">\; \&Greater\; Equal;</span>\underset{\mathrm{<span\; class="notranslate">\; i</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}{\mathrm{<span\; class="notranslate">\; no</span>}}_{\mathrm{<span\; class="notranslate">\; UEi</span>}}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 3</span>}<span\; class="notranslate">\; )</span>$

Wherein, n _eNB is the number of antennas of the eNB, n _UEi is the number of antennas of the i-th UE, and i≥1.

It can be seen that the QRD-based uplink and downlink MU-MIMO transmission method provided by the present invention utilizes the reciprocity between the uplink and downlink channels in the system (such as TDD or FDD system), so that the uplink and downlink channels of the LTE-A system On the road, it can effectively support the orthogonal or quasi-orthogonal transmission of multi-user and multi-data streams.

Further, an embodiment of the present invention provides a base station for MU-MIMO transmission, including: multiple antennas, a switch unit 701, a channel estimation unit 702, a QR decomposition unit 703, a transmit beamforming unit 704, and each A MIMO detection unit, a receive beamforming unit 706 , and an MUI cancellation processing unit 707 are set by the UE. In this embodiment, it is set that the eNB has 4 antennas, the number N of users participating in MU-MIMO transmission is 2, and each user is provided with 2 antennas, then the MIMO detection unit includes: the MIMO detection unit 7051 of UE1 and the MIMO detection unit 7051 of UE2 Detection unit 7052.

During actual work, the channel estimation unit 702 provides the channel estimation result to the QR decomposition unit 703, and the QR decomposition unit 703 decomposes the channel matrix to obtain the MU-BF matrix and the downlink SU-BF matrix of each user. In this embodiment, are P ⁽¹⁾ , P ⁽²⁾ , V ⁽¹⁾ , V ⁽²⁾ , and are provided to the transmit beamforming unit 704 . Further, the QR decomposition unit 703 provides V ^(1)H and V ^(2)H to the receiving beamforming unit 706 , and provides P ^(1)H and P ^(2)H to the MUI cancellation processing unit 707 . Further, the QR decomposition unit 703 provides the R matrix generated in the decomposition to the MIMO detection unit, so as to perform MIMO detection. Further, the QR decomposition unit 703 will also generate an AMC control signal (for example, by using the R matrix generated in the decomposition) to control the transmit data stream so as to adapt to different channel conditions.

During data transmission, the transmit beamforming unit 704 uses V ⁽¹⁾ to perform SU-BF matrix processing on the transmit data stream 1 and transmit data stream 2 of UE1, and then uses P ⁽¹⁾ to perform MU-BF matrix processing to obtain 4 channels of data stream a1-d1. Similarly, the transmit beamforming unit 704 uses V ⁽²⁾ to perform SU-BF matrix processing on UE2’s transmit data stream 1 and transmit data stream 2, and then uses P ⁽²⁾ to perform MU-BF matrix processing to obtain 4 channels of data Stream a2-d2. The data streams obtained by UE1 and UE2 after transmit beamforming are superimposed and then output to the antenna, for example, the data stream a1 of UE1 and the data stream a2 of UE2 are superimposed and sent to an antenna for transmission.

During data reception, 4 data streams a3-d3 are received from 4 antennas, and each data stream is sent to the MUI cancellation processing unit 707 of multiple users, and then sent to the receiving beamforming unit 706. For example, send the data stream a3 to the MUI elimination processing units of UE1 and UE2, respectively use P ^(1)H and P ^(2)H to eliminate MUI, and then use the conjugate transposition of SU-BF V ^(1)H and V ^(2)H performs receive beamforming. It should be pointed out that the MUI cancellation processing unit 707 and the receiving beamforming unit 706 are optional units on the eNB. Afterwards, after processing by the MIMO detection unit, the transmit data stream of the UE is restored.

Further, an embodiment of the present invention provides a user terminal for MU-MIMO transmission, including: multiple antennas, a switch unit 801, a channel estimation unit 802, a QR decomposition unit 803, a transmit beamforming unit 804, and a MIMO detection unit Unit 805 and receiving beamforming unit 806 . Wherein, the transmitting beamforming unit 804 includes a SU-BF processing unit 8041 , and the receiving beamforming unit 806 includes a SU receiving beamforming unit 8061 . It should be pointed out that the receiving beamforming unit 806 is optional on the user terminal.

The QR decomposition unit 803 decomposes the channel matrix according to the channel estimation result provided by the channel estimation unit to obtain the uplink SU-BF matrix U ⁽ⁱ⁾ (which may be the first uplink SU-BF matrix U ₁ ^{(i) or the first uplink SU-BF matrix U 1 (i} ) Two uplink SU-BF matrix U ₂ ⁽ⁱ⁾ ), and further obtain the conjugate transpose [U ⁽ⁱ⁾ ] ^H of the uplink SU-BF matrix, which is provided to the SU-BF processing unit 8041 and the SU receiving beamforming unit 8061 respectively . Further, the QR decomposition unit 803 provides the decomposed R matrix to the MIMO detection unit 805, or for AMC control.

It can be seen that the method of the present invention, the base station and the user terminal do not need to rely on high-complexity SVD when performing MU-MIMO transmission, and even when MMSE detection is not used, high-complexity matrix inversion may not be used, but Beamforming with less complex QRDs. On the one hand, the unitary matrix generated by QRD can be used for MU-BF and SU-BF, and can be used for both transmit and receive beamforming; on the other hand, the upper triangular matrix generated by QRD can be used for MIMO detection and adaptive modulation coding (AMC ). For example, according to the diagonal elements of the upper triangular matrix, the channel gain of each (quasi) orthogonal channel can be obtained, and the signal-to-noise ratio (SNR) can be calculated by combining the noise power, and accordingly for each (quasi) orthogonal channel selection A suitable modulation and coding scheme (MCS) includes selecting to close the data stream when the channel condition is not enough to support the lowest level of MCS, so as to realize the adaptive change of the transmission order (Rank).

Using the simulation parameters shown in Table 1, a link-level simulation is performed on the method provided by the embodiment of the present invention. In this simulation, it is assumed that multi-user scheduling has been completed currently, the wireless channels of the two UEs are always kept independent, and each UE supports two data streams. If SU-BF is considered in MU-BF, then the two data streams adopt 64QAM and 4QAM modulation respectively; if SU-BF is not considered in MU-BF, then the two data streams adopt the same modulation method, both are 16QAM . In addition, ideal channel estimation is assumed in this simulation, but beamforming is performed based on the average channel within the resource block (rather than the instantaneous channel of each subcarrier), which will lead to a certain degree of performance degradation, but it is more in line with the actual system Require.

Table 1 Simulation parameters

Fig. 8 is a schematic diagram of comparing the downlink throughput between the prior art and the embodiment of the present invention. Among them, the downlink uniformly adopts the MMSE detection algorithm, and the simulation obtains a total of five performance curves for the three downlink MU-MIMO methods, which are BD, BD+SVD, and the method based on QRD in the present invention (that is, curves BD-QRD _eq ⁰ , BD-QRD _eq ¹ , BD-QRD _eq ² ), where the number of iterations of SU-BF is set to 0, 1, 2, respectively. When the number of iterations is 0, it means that there is no SU-BF, only MU-BF.

It can be seen from Figure 8 that: ① For MU-BF, the performance based on QRD is better than that of traditional BD, because the QRD-based MU-BF matrix further realizes the sub-diagonalization on the basis of block diagonalization. The triangulation of the block array can reduce the interference between data streams; ②For SU-BF, the iterative convergence speed based on QRD is very fast, and it only takes 1-2 iterations to achieve the performance of SVD.

FIG. 9 is a schematic diagram of comparison of uplink throughput between the prior art and the embodiment of the present invention. The joint MMSE detection algorithm is uniformly adopted for uplink, and a total of seven performance curves for four uplink MU-MIMO methods are obtained through simulation. The four uplink MU-MIMO ^methods are: _the originator does not perform beamforming ₍ NoBF) ^, SVD, _the present invention performs QRD for ^equivalent The channels perform QRD (ie curves QRD _phy ¹ , QRD _phy ² ). Among them, when QRD is performed on the equivalent channel, only one QRD is performed on the uplink, and the iterations of the downlink QRD are set to 0, 1, and 2 respectively; when QRD is performed on the physical channel, the uplink iterations are set to 1 and 2, respectively.

It can be seen from Figure 9 that: ① When the uplink and downlink resource allocation is the same, the QRD based on the equivalent channel can achieve the same performance as SVD, and the uplink performance is less dependent on the number of downlink QRD iterations; ② When the uplink and downlink resource allocation is different At the same time, QRD iterations can be performed based on physical channels. Although the performance is lower than that of QRD or SVD based on equivalent channels, there is still a significant performance gain compared with no beamforming.

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

Claims (24)

1. a transmission method of multi-user multi-input multi-output MU-MIMO in a wireless communication system, it is characterized in that, comprising: The base station receives sounding pilot SRSs sent from N user terminals UE to perform channel estimation, and generates a downlink channel information matrix according to the channel estimation results and the channel reciprocity of the system, wherein the N is greater than 1; The base station performs QR decomposition on the generated downlink channel information matrix, obtains the multi-user beamforming MU-BF matrix P ⁽ⁱ⁾ of the i-th UE from the Q matrix obtained by the decomposition, and further obtains the i-th UE's Downlink single-user beamforming SU-BF matrix V ⁽ⁱ⁾ , where i=1,...,N; The base station performs beamforming processing on the transmission data of the i-th UE according to the MU-BF matrix P ⁽ⁱ⁾ and the downlink SU-BF matrix V ⁽ⁱ⁾ . 2. The method according to claim 1, further comprising: According to the MU-BF matrix and the downlink SU-BF matrix of the i-th UE, the base station performs transmit beamforming processing on the user-specific pilot of the UE, and sends it to the UE. 3. The method of claim 1, further comprising: The i-th UE receives the downlink pilot sent by the base station to perform channel estimation, and obtains a downlink channel information matrix for the UE; The UE performs QR decomposition on the downlink channel information matrix, and obtains its own uplink single-user beamforming SU-BF matrix U ⁽ⁱ⁾ from the decomposed Q matrix; Perform beamforming processing on the transmit data according to the uplink SU-BF matrix. 4. The method according to claim 3, wherein the UE performs QR decomposition on the downlink channel information matrix to obtain the uplink SU-BF matrix comprising: The i-th UE receives the user-specific pilot sent by the base station to perform channel estimation, and obtains the downlink equivalent channel matrix; The UE performs QR decomposition on the downlink equivalent channel matrix, and uses the decomposed Q matrix as the first uplink SU-BF matrix of the UE. 5. The method according to claim 3, wherein the UE performs QR decomposition on the downlink channel information matrix to obtain the uplink SU-BF matrix comprising: The i-th UE receives the cell-specific pilot sent by the base station to perform channel estimation, obtains the downlink physical channel matrix, and obtains the uplink physical channel matrix according to channel reciprocity; The UE performs QR decomposition on the uplink physical channel matrix, and obtains a second uplink SU-BF matrix of the UE from the decomposed Q matrix. 6. The method of claim 3, further comprising: The UE performs conjugate transposition on the uplink SU-BF matrix; MIMO detection is performed after performing beamforming processing on the received data of the UE according to the conjugate transposition of the uplink SU-BF matrix. 7. The method according to any one of claims 3-6, further comprising: the UE performs transmit beamforming processing on the uplink demodulation pilot DMRS according to the uplink SU-BF matrix, and then sends to the base station. 8. The method of claim 1, further comprising: The base station performs conjugate transposition on the MU-BF matrix and the downlink SU-BF matrix of the i-th UE; According to the conjugate transposition of the MU-BF matrix of the UE, multi-user interference cancellation MUI is performed on the received data of the base station to obtain the received data of the i-th UE, and then the conjugate transpose of the downlink SU-BF matrix is used to After the received data of the UE is processed, MIMO detection is performed. 9. The method according to claim 1, wherein the base station obtains the downlink single-user beamforming SU-BF matrix V ⁽ⁱ⁾ of the i-th UE comprising: The base station obtains H (i) P (i) according to the downlink physical channel matrix H ⁽ⁱ⁾ and MU-BF matrix P ^{(i) of} the i-th UE, and performs QR decomposition on H ^{( i)} P ⁽ⁱ⁾ , Obtain the downlink SU-BF matrix V ⁽ⁱ⁾ of the UE. 10. The method according to claim 3, wherein the UE obtaining its own uplink single-user beamforming SU-BF matrix U ⁽ⁱ⁾ comprises: The UE multiplies the uplink physical channel matrix H _UL ⁽ⁱ⁾ and the conjugate transposition H _UL ^(i)H of the uplink physical channel matrix to obtain H _UL ^(i)H H _UL ⁽ⁱ⁾ , and then H _UL ^{(i) H} H _UL ⁽ⁱ⁾ and U _t-1 ⁽ⁱ⁾ are multiplied and subjected to QR decomposition to obtain the uplink SU-BF matrix U _t ⁽ⁱ⁾ . 11. A base station for multi-user multiple-input multiple-output MU-MIMO transmission, characterized in that, comprising: A channel estimation unit, configured to perform channel estimation to obtain uplink channel information of more than one user terminal UE, and obtain a downlink channel information matrix according to channel reciprocity; The QR decomposition unit is configured to perform QR decomposition on the downlink channel information matrix, obtain the multi-user beamforming MU-BF matrix of each UE from the decomposed Q matrix, and further obtain the downlink single-user beamforming of each UE SU-BF matrix; The transmit beamforming unit is configured to perform beamforming processing on the transmit data of the corresponding UE according to the MU-BF matrix and the downlink SU-BF matrix of each UE, and send it to the antenna of the base station for transmission. 12. The base station according to claim 11, wherein the QR decomposition unit is further used to provide the R matrix decomposed to the MIMO detection unit; The MIMO detection unit is configured to perform MIMO detection on the received data of the antenna according to the R matrix, and recover the transmitted data of each UE. 13. The base station according to claim 12, wherein the QR decomposition unit is further configured to perform conjugate transposition on the MU-BF matrix and the downlink SU-BF matrix of each UE, and provide them to the receiving beamforming unit ; The receiving beamforming unit is configured to perform multi-user interference cancellation (MUI) on the received data of the antenna according to the conjugate transpose of the MU-BF matrix of each UE, to obtain the received data of each UE, and then use the downlink SU- The conjugate transposition of the BF matrix processes the received data of the corresponding UE and sends it to the MIMO detection unit. 14. The base station according to any one of claims 11-13, wherein the QR decomposition unit is further configured to perform adaptive modulation and coding on the transmit data streams of the one or more UEs according to the R matrix obtained through decomposition AMC control. 15. The base station according to any one of claims 11-13, wherein the QR decomposition unit is used to obtain the physical downlink channel matrix H ⁽ⁱ⁾ and MU-BF matrix P ⁽ⁱ⁾ of each UE H ⁽ⁱ⁾ P ⁽ⁱ⁾ , and perform QR decomposition on H ⁽ⁱ⁾ P ⁽ⁱ⁾ to obtain the downlink SU-BF matrix V ⁽ⁱ⁾ of each UE, where i is any number from 1 to the number of users N integer. 16. The base station according to any one of claims 11-13, wherein the channel estimation unit is configured to perform channel estimation according to the sounding pilot SRS sent by each UE, or to perform channel estimation according to the uplink solution sent by each UE The uplink channel information is obtained by adjusting the pilot frequency DMRS, and the downlink channel information matrix is obtained according to the channel reciprocity. 17. The base station according to any one of claims 11-13, wherein the transmit beamforming unit is further configured to transmit to each UE according to the MU-BF matrix and the downlink SU-BF matrix of each UE The UE's user-specific pilot is subjected to beamforming processing. 18. A user terminal UE for multi-user multiple-input multiple-output MU-MIMO transmission, characterized in that it includes: A channel estimation unit, configured to perform channel estimation to obtain a downlink channel information matrix of the UE; The QR decomposition unit is configured to perform QR decomposition on the downlink channel information matrix, and obtain the uplink single-user beamforming SU-BF matrix of the UE from the Q matrix obtained through decomposition; The transmitting beamforming unit is configured to perform beamforming processing on the transmitting data according to the uplink SU-BF matrix of the UE, and transmit it from the antenna of the UE. 19. The UE according to claim 18, wherein the channel estimation unit is configured to perform channel estimation according to user-specific pilots sent by the base station to obtain a downlink equivalent channel matrix; The QR decomposition unit is configured to perform QR decomposition on the downlink equivalent channel matrix, and use the decomposed Q matrix as the first uplink SU-BF matrix of the UE. 20. The UE according to claim 18, wherein the channel estimation unit is configured to perform channel estimation according to the cell-specific pilot sent by the base station, obtain a downlink physical channel matrix, and obtain an uplink physical channel according to channel reciprocity matrix; The QR decomposition unit is configured to perform QR decomposition on the uplink physical channel matrix, and obtain the second uplink SU-BF matrix of the UE from the Q matrix obtained through decomposition. 21. The UE according to any one of claims 18-20, wherein the QR decomposition unit is further configured to provide the R matrix obtained by decomposition to the MIMO detection unit; The MIMO detection unit is configured to perform MIMO detection on the received data of the UE according to the R matrix. 22. The UE according to claim 21, wherein the QR decomposition unit is further configured to perform conjugate transposition on the uplink SU-BF matrix of the UE, and provide it to the receiving beamforming unit; The receiving beamforming unit is configured to process the received data of the UE according to the conjugate transposition of the uplink SU-BF matrix, and send it to the MIMO detecting unit. 23. The UE according to any one of claims 18-20, wherein the QR decomposition unit is further configured to perform adaptive modulation and coding on more than one transmit data stream of the UE according to the R matrix obtained by decomposition AMC control. 24. The UE according to any one of claims 18-20, wherein the transmit beamforming unit is further configured to perform beamforming processing on the uplink demodulation pilot DMRS according to the uplink SU-BF matrix of the UE .

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