WO2009076863A1 - A method and base station for transmitting downlink signals - Google Patents

Abstract

A method and base station are used for transmitting downlink signals, the method includes that assuming a precoding matrix of transmitting end is W, W is calculated according to the linear equalizing criterion, the downlink signals are processed according to the calculated W, and the processed downlink signals are transmitted. When the base station is transmitting the downlink signals, the method can make its processing course simple and its processing time shorter.

Description

 Method and base station for transmitting downlink signal The present application claims to be Chinese patent filed on December 14, 2007, the application number is 200710302112.2, and the invention title is "a method and base station for transmitting downlink signals" Priority of the application, the entire contents of which are incorporated herein by reference.

Technical field

 The present invention relates to the field of wireless communications, and in particular, to a method and a base station for transmitting a downlink signal.

Background technique

 In recent years, information theory research has shown that as an antenna technology for wireless communication, MIMO (Multi-Input Multiple-Output) can significantly improve the transmission rate of wireless communication systems. At present, the research on point-to-point single-user MIMO system has been basically determined, and the research on multi-user MIMO system has attracted the attention of international scholars. The multi-user MIMO downlink can use Time Division Multiple Access (TDMA), Code Division Multiple Access (CDMA), Orthogonal Frequency Division Multiple Access (OFDM A), and Orthogonal Frequency Division Multiple Access (OFDM). Multiple access technology such as Space Division Multiple Access (SDMA). The first three technologies all allocate system resources to a single user, so the spectrum utilization of the system is not high and the system rate is limited. Unlike the first three technologies, SDMA can support multiple users in the same time slot and frequency band, so the system capacity can be doubled. Since multiple users share system resources, and each user generally cannot cooperate to process received signals, the problem of multi-user interference suppression becomes the key to system performance. The basic way to solve this problem is to transmit precoding. Common precoding methods include: linear precoding, nonlinear precoding, and joint transceiver design.

Among them, the joint transceiver design combines the transmit precoding and the receiving matrix with certain criteria, such as the minimum mean square error (MMSE, Mininum Mean Square Error) criterion and the zero forcing criterion, so that the performance of the system is achieved. Optimal. Consider the following multi-user MIMO downlink system model: The number of base station transmit antennas is M, while the number of service users is K, and the number of receive antennas per user For N _k , the number of supported data streams is . The data S _{k of} the first user is sent to the transmitting antenna through the precoding matrix, so the signal actually transmitted by the base station is:

(1) where W = (WW ₂ ■■■ is the total precoding matrix, = s ₂ ^H ... )" is the data transmitted to the user, the elements of which are independent of each other, and satisfy the zero mean and unit variance. After the channel, it is contaminated by additive white Gaussian noise. The signal received by the first user is:

y _k = H _k x + ^ ( 2 ) where is the channel matrix between the base station and the first user, ~ Κ0, σ ² /) is additive white Gaussian noise.

 Since each user generally cannot exchange data, each user linearly processes the received signal to recover his own data. Let the first user use G as the linear receiver, then the estimate for

^ = ^G ky _k ( 3 ) In summary, the block diagram of the prior art multi-user MIMO downlink transceiver is shown in Figure 1. When the base station transmits the downlink signal, the precoding matrix is first designed by using the above method, and the designed precoding matrix is used to process the downlink signal, and the processed downlink signal is sent out.

 The disadvantages of this method are: Since the calculation of the Lagrangian multiplier is complicated and solved by the base station in solving the transmit precoding matrix, the processing of the base station when transmitting the downlink signal is complicated and the processing time is relatively complicated. long. Summary of the invention

 The embodiment of the invention provides a method for transmitting a downlink signal, which enables the base station to process the downlink signal and shorten the processing time when transmitting the downlink signal.

 The embodiment of the present invention further provides a base station, where the base station sends a downlink signal, the processing process is relatively simple, and the processing time is short.

 The technical solution of the present invention is implemented as follows:

A method for transmitting a downlink signal, comprising: assuming that a precoding matrix of the transmitting end is W, and a receiving matrix of the receiving end is G = g (5, wherein the g is a common coefficient of the receiving matrix; Calculate w according to linear equilibrium criteria;

 The downlink signal is processed according to the calculated w, and the processed downlink signal is transmitted. A base station, the base station includes:

 a calculation module, configured to assume that the precoding matrix of the transmitting end is W, and when the receiving matrix of the receiving end is G=g, calculate W according to a linear equalization criterion, where the g is a common coefficient of the receiving matrix;

 And a processing and sending module, configured to process the downlink signal according to the W calculated by the computing module, and send the processed downlink signal.

 It can be seen that the method for transmitting a downlink signal and the base station in the embodiment of the present invention provide a common coefficient by calculating a pre-coding matrix for each user's receiver when calculating the pre-coding matrix, so that the base station is transmitting downlink. The processing of the link signal is simple, and the processing time is short. BRIEF DESCRIPTION OF THE DRAWINGS The accompanying drawings, which are incorporated in the claims Other drawings may also be obtained from these drawings without the inventive labor.

 1 is a block diagram of a prior art multi-user MIMO downlink transceiver design;

 2 is a block diagram showing a design of a multi-user MIMO downlink transceiver according to an embodiment of the present invention;

 3 is a convergence performance curve of different embodiments of the present invention at different signal to noise ratios;

 4 is a erroneous symbol rate performance curve 1 calculated by using MMSE according to an embodiment of the present invention; FIG. 5 is a second erroneous symbol rate performance curve calculated by using MMSE according to an embodiment of the present invention; FIG. 6 is a calculation using ZF criterion according to an embodiment of the present invention. Error symbol rate performance curve. detailed description

 BRIEF DESCRIPTION OF THE DRAWINGS The technical solutions in the embodiments of the present invention will be described in detail with reference to the accompanying drawings. All other embodiments obtained by a person of ordinary skill in the art based on the embodiments of the present invention without creative work are within the scope of the present invention.

The embodiment of the present invention provides a method for transmitting a downlink signal, which includes: assuming that a precoding matrix of the transmitting end is W, and a receiving matrix of the receiving end is G=g, where the g is a common matrix of the receiving matrix. Coefficient

 Calculate W according to linear equilibrium criteria;

 The downlink signal is processed according to the calculated W, and the processed downlink signal is transmitted. The linear equalization criterion used when calculating the precoding matrix is W may be the MMSE criterion. The calculation method using the MMSE criterion is specifically described below.

 Referring to FIG. 2, FIG. 2 is a block diagram of a multi-user MIMO downlink transceiver according to an embodiment of the present invention. The k-th user's Mean Square Error (MSE) is

MSE _k = E{ ')

因此收发机的设计问题转化为如下优化问题： (H _k WW ^H H^ + ² I)G _k + 1 - gG^H _k W _k - gW _k ^H H^G _k ] The total MSE of the system is

Therefore, the design problem of the transceiver translates into the following optimization problems:

Minimize {MSE} , st tr(WW ^H ) < P

 (6) where is the total transmit power of the system. According to formula (6), the following Lagrangian function can be written:

 K

J = MSE _t + [tr(WW ^H ) - P] (7) where I is a Lagrangian multiplier. According to the optimization conditions (such as KKT, Karush-kuhn-Tucker conditions), the following equations can be listed: + ² I) G _k - gH _k W _k = 0 (8)

 dJ

H = g ² H ^H HW― gH ^H +λΨ = 0 (9) dW

[tr(WW ^H )-P] = 0 (11) λ≥0 ( 12) Where G ... G^), H^DH, H^(H- H ... H )" ₍ by the equation (9) left by W" gives g ² W ^H H ^H HW - gW ^H H ^H + W ^H W = 0 ( _{13 ) is} derived from the properties of the Hermite matrix:

W ^H H ^H =HW (14) Available from equations (13), (14) and (10):

2g - tr(a ² DD ^H ) + 2g ^l tr(g ² W ^H H ^H HW - gW ^H H ^H ) = 2g- tr(a ² DD ^H ) - 2 g- ^l tr(WW ^H ) = 0 ( 15) Further available:

Tr(a ^z DD ^H )

 λ =

Tr(WW ' ^ΗH , ) ( 16) Obviously here > 0. Therefore, the _KKT conditional formula ( _u ) is available: ir WW" ) = P. Substituting ( ₁₆ ) is available:

2 tr(a ² DD ^H ) _Δ , ₂

 λ = ^ ^ ρ ^ (17) Substituting equation ( 17 ) into equation ( 9 ),

W = g~ ^l H ^H [HH ^H +ξΐγ ^ι (18) and can be obtained from equation (8):

+a²I)~^lH_kW_k (19) 将式（19)代入式（18)可得： G _k =

+a ² I)~ ^l H _k W _k (19) Substituting equation (19) into equation (18) gives:

W = g ¹ H ^H D ^H [DHH ^H D ^H + ξΐγ ¹

= g- ² H ^H D ^H [g- ² DHH ^H D ^H + _§ - ² μΐγ

(20) = H ^H D ^H [DHH ^H D ^H + μΐγ ¹ where /

It can be seen from equation (20) that after the common gain factor g is introduced, the precoding matrix of the transmitting end has a closed solution, and the closed solution is independent of g. Although equation (20) is cleaner than existing linear coding methods, and there is only one unknown matrix variable in the transmit precoding matrix in the equation, it is still difficult to solve W directly, because /) is dependent on W. However, it is worth noting that the solution of W at this time can be solved independently of the pair, that is, W can be solved directly by iteration. The following two iterative solution schemes are proposed here:

 (1) Alternating iterative solution: Optimizing the transmit precoding array and receiver successively

1. Initialize 0 _k = I _xNk , k = l, ..., K ;

 2. Calculate the updated value of W using equation (18), and determine g by the transmit power constraint;

 3. The updated value calculated using equation (19);

 4. When the Frobenius norm of the difference between the last two updated values is greater than the preset value (such as 0.0001), return to step 2; otherwise, go to step 5.

 5. Normalize the resulting W by transmit power;

6. Each user individually designs the receiver G _k according to the MMSE criteria. The transmitting end processes the pilot signal according to the calculated w, and transmits the processed pilot signal; after receiving the processed pilot signal, the receiving end calculates the receiving end receiving matrix G according to the MMSE criterion.

 (2) Directly iteratively solve the originating precoding matrix:

1. Initialize w = / _Mxe ; where β is the sum of the number of data streams supported by all users;

 2. Calculate the updated value of W using equation (20);

 3. When the Frobenius norm of the difference between the last two updated values is greater than the preset value (such as 0.0001), return to step 2; otherwise, go to step 4;

 4. Normalize the resulting W by transmit power;

5. Each user individually designs the receiver G _k according to the MMSE criteria.

 One of the benefits of direct iteration is that you don't have to calculate g during each iteration, as long as the transmit power is normalized after the final W array is converged. Therefore, from the perspective of computational complexity, the direct iterative scheme is better than the alternate iterative scheme.

 The following is a summary of the convergence of the alternating iterative scheme. Since the problem is a multi-parameter optimization problem, and the parameters are coupled to each other, direct solution is difficult. The alternate optimization iteration first divides the parameters to be optimized into several groups. When optimizing one of the parameters, it is assumed that other group parameters have been fixed, and when the updated values of the group parameters are obtained, they can be used for optimization of other group parameters.

也是最优 的， 即 From the above analysis, it can be known that under the premise of <3⁄4") (k = l,..., K), the W ^w obtained by equation (18) is optimal, that is, MSE(W ⁽ⁿ⁾ , g ⁿ G[ ⁿ⁾ ) < MSE(W, g, G _k ⁽ⁿ⁾ ), VW; Vg (21 ) Similarly, when w ^w , g ^{w is} given, by equation (i9 ) got " ⁺¹ "

Also optimal, ie

MSE(W ⁱⁿ⁾ , g ⁽ⁿ G; ^{( +1)} ) < MSE(W ⁱⁿ⁾ , g ⁽ⁿ G _k ), V(3⁄4 (22) is obtained by equations (21), (22)

0 ≤ MSE(W ⁽ⁿ⁾ , g ⁽ⁿ⁾ , G _k ⁽ⁿ⁺¹⁾ ) ≤ MSE(W ⁽ⁿ⁾ , g ⁽ⁿ⁾ , G _k ⁽ⁿ⁾ ) ≤ MSE(W ⁽ⁿ ~ ^l) , g ⁽ⁿ ~ ^l) , G _k ⁽ⁿ⁾ ) (23 ) Therefore, the alternate optimization iterative scheme can always reduce the MSE of the system and finally converge to a stable point. Of course, this stable point may be globally optimal or locally optimal.

The direct iterative solution method has the same convergence performance because it is a cylindrical form of alternating iterative solution. Referring to Figure 3, Figure 3 is a graph showing convergence performance at different signal to noise ratios using an embodiment of the present invention. As the signal-to-noise ratio increases, the convergence speed becomes slower. However, when the signal-to-noise ratio is less than 10 dB, the iterations of about 5 times have basically converged. The effect of signal-to-noise ratio on the convergence speed is mainly due to the influence of μ on the convergence, which can be seen from equation (20). The effect of 〃 is similar to diagonal filling, which is often used in array signal processing, which speeds up the convergence of algorithm iterations.怛^ SNR→∞ , that is, when ^ ² _→ 0 Μ → 0, the proportion of the equation (20) similar to the diagonal filling becomes smaller, so it has a certain influence on the convergence speed.

The simulation of the embodiment of the present invention is as follows: The simulation environment is as follows: The channel between the base station and each user is Rayleigh flat fading, the channel remains unchanged in one data frame, and can be accurately known on the base station side. For the base station M antenna, each user, each user N antenna, each user supports the downlink system cylinder of the ^^ data stream as [M, K, N, L _s ]. In order to prevent the convergence rate from being too slow in some cases, the upper bound of the number of iterations is limited, that is, I _UB = 50. The information symbols in all simulations are QPSK modulated, and the number of Monte Carlo simulations is more than 10,000 times under various parameter configurations. Referring to FIG. 4 and FIG. 5, FIG. 4 is a performance rate curve 1 of the symbol error rate calculated by using the MMSE according to the embodiment of the present invention, and FIG. 5 is a second performance curve of the symbol error rate calculated by using the MMSE according to the embodiment of the present invention.

Alternatively, the embodiment of the present invention may also calculate W by using a zero forcing (ZF, Zero Forcing) criterion. The difference between this method and the above-mentioned MMSE calculation W is that the additive white Gaussian noise is not considered, that is, the power equivalent to additive white Gaussian noise is cr ² = 0.

ε _Δ tr(a ² DD ^H ) _Λ

Then from (17) above, you can get: =—— -—— =0 From ^^^ = ² above, 〃 = 0; Substituting σ ² , ξ, 〃 into (18), (19) and (20) above:

w = g- ^l H ^H [M ^H y ^l ( 18' )

W = H ^H D ^H [DHH ^H D ^H Y ^l ( 20' ) Also use the similar alternating iterative solution and direct iterative solution described above, the only difference is that ( 18 ' ), ( 19 ' ) and ( 20 ' ) are used. The formula is calculated instead of the above formulas (18), (19), and (20).

 A good simulation effect can be achieved by using the ZF calculation. As shown in Fig. 6, Fig. 6 is a graph showing the error symbol rate performance curve calculated by the ZF criterion in the embodiment of the present invention.

 As can be seen, the method for transmitting a downlink signal proposed by the present invention has a calculation method when designing a linear transceiver, so that when the base station transmits a downlink signal, the process is processed and the processing time is compared. short.

 The embodiment of the invention further provides a base station, including:

 The initialization and calculation module is configured to assume that the precoding matrix of the transmitting end is W, and when the receiving matrix of the receiving end is Gf =, calculate W according to a linear equalization criterion, where g is a common coefficient of the receiving matrix; processing and transmitting module, The downlink signal is processed according to the W calculated by the initialization and calculation module, and the processed downlink signal is transmitted.

 The linear equalization criterion used in the initialization and calculation module may be an MMSE criterion, a ZF criterion, or the like.

The initialization and calculation module may include: an initialization module, configured to initialize =/ _> ^, where: =1, . The number of users, the number of data streams supported by the first user, and the number of receiving antennas of the first user;

计算 ¾的更新值； 其中， 所述 CT²为加性高斯 白噪声的功率； The first calculation module is configured to calculate the updated value of the <3⁄4 =/^^ initialized by the initialization module or the <3⁄4 calculated by the second calculation module according to W = _g ^l H ^H [HH ^H + ξΐ γ ^ι W The updated value, while determining the g by the transmit power constraint; wherein, ^0H, D = diag{G^ Gf ... (3⁄4) , H = (HH ... H )", H _x , H ₂ are the second users The channel matrix, , " _p ' , _σ ² is the power of the additive white Gaussian noise, Ρ is the total transmission power of the system, / is the unit matrix; the second calculation module is used to calculate the W of the first calculation module Update the value, use (3⁄4 =

Calculating an updated value of 3⁄4; wherein, the CT ² is the power of additive white Gaussian noise;

 a determining module, configured to determine whether a norm of a difference between the updated value of the current W calculated by the second calculating module and the updated value of the last W is greater than a preset threshold, and if yes, indicating the first calculating The module recalculates the updated value of W. Otherwise, it determines that the updated value of this time W is calculated.

计算 ¾的更新值。 Alternatively, if the linear equalization criterion used is the zero-forcing ZF criterion, the first calculation module may further calculate the updated value of W according to W = g- ¹ , and the second calculation module utilizes (3⁄4 =

Calculate the updated value of 3⁄4.

 Alternatively, the initialization and calculation module may include:

An initialization module, configured to initialize W = / _Mxe , where G is the sum of the number of data streams supported by all users, M is the number of transmitting antennas, / is an identity matrix;

A calculation module for initializing W = / _{Mxe of the} initialization module. If the linear equalization criterion is zero-forcing MSME criterion, use W = H ^H D ^H [DHH ^H D ^H + μΙ\ ^{χ to} calculate the updated value of W Wherein, the H all (HH ... Κ) Η, , Η ₂ are respectively the channel matrix of the second user, D ^ G ... G _K ^H ) , μ = ξ ² , ξ ^ ^σ ^ ° σ ² The power of additive white Gaussian noise is the total transmit power of the system;

 a determining module, configured to determine whether a norm of a difference between the updated value of the current W calculated by the calculating module and the updated value of the last W is greater than a preset threshold, and if yes, instructing the computing module to recalculate The updated value of W, otherwise, it is determined that the update value of this time W is calculated.

Alternatively, if the linear equalization criterion used is the zero-forcing ZF criterion, the initialization and calculation module may further calculate the updated value of w by using W = "Z^ [DHH" Γ ¹ .

In the foregoing base station, the W determining module may be configured to determine that a norm of a difference between an update value of the current W calculated by the calculation module or the first calculation module and an update value of the last W is not greater than a preset For the threshold value, the updated value of the obtained W is normalized according to the transmission power, and the updated value of W after the normalization is determined as the calculated W.

 The above base station may further include:

 The pilot signal processing transmitting module is configured to process the pilot signal determined according to the W determined by the W determining module, and send the processed pilot signal.

 In summary, the method and base station for transmitting a downlink signal according to an embodiment of the present invention propose an improved transceiver structure, and propose an effective iterative algorithm to solve the problem of solving the precoding matrix at the transmitting end, so that the transmitting problem is When the downlink signal is used, the complexity of the base station processing process is reduced, and the processing time of the base station is made shorter.

 In addition, one of ordinary skill in the art can understand that all or part of the process in implementing the foregoing embodiments may be completed by a program instructing related hardware, and the program may be stored in a computer readable storage medium. The program, when executed, may include the flow of an embodiment of the methods as described above. The storage medium may be a magnetic disk, an optical disk, a read-only memory (ROM), or a random access memory (RAM).

 In summary, the foregoing is merely illustrative of the spirit of the invention and is not intended to limit the scope of the invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and scope of the present invention are intended to be included within the scope of the present invention.

Claims

Rights request  A method for transmitting a downlink signal, the method comprising: Assume that the precoding matrix of the transmitting end is W, and the receiving matrix of the receiving end is G.

Wherein g is a common coefficient of the receiving matrix;  Calculate W according to linear equilibrium criteria;  The downlink signal is processed according to the calculated W, and the processed downlink signal is transmitted. 2. The method according to claim 1, wherein the linear equalization criterion is a minimum mean square error MMSE criterion; Then the calculation is as follows: Initialization (3⁄4=/ _>3⁄4 , where the = 1,..., , is the number of users of the same month, the number of data streams supported by the first user, for the first user Number of receiving antennas; Calculate the updated value of W according to W = g~ ^l H ^H [HH ^H + ,, and determine g by the transmit power constraint; where, ^ (···· G _K ^H ), HH ... H _K ^H ) ^H ,

H ₂ is the channel matrix of the second user, ~~ -, (T ² is the power of additive white Gaussian noise, Ρ is the total transmit power of the system, / is the unit matrix; Calculating the updated value of 3⁄4 using <3⁄4=g- ¹ (stomf ^ff f + σ ² /) - ^^; wherein _σ ² is the power of additive white Gaussian noise;  Determining whether the norm of the difference between the updated value of the current W and the updated value of the last W is greater than a preset threshold value, and if so, re-executing the step of calculating the updated value of W; otherwise, determining W The update value is the calculated ^. 3. The method according to claim 1, wherein the linear equalization criterion is an MMSE criterion; Then the calculation is as follows: Initialize W = / _Mxe , where β is the sum of the number of data streams supported by all users, Μ is the number of transmitting antennas, / is the unit matrix; Calculating the updated value of W by using w = H ^H D ^H [DHH ^H D ^H + μΙ\ ^ι , where ^{_{H = (HH ... K H)}} , H x, H 2 , respectively, for the first ₁₂ user channel matrix, to add

The power of the Gaussian white noise, the total transmission power of the system;  Determining whether the norm of the difference between the updated value of the current W and the updated value of the last W is greater than a preset threshold value, and if so, re-executing the step of calculating the updated value of W; otherwise, determining W The update value is the calculated ^. The method according to claim 1, wherein the linear equalization criterion is a zero-forcing ZF criterion; The calculation is as follows: Initialization & _k =I _xNk , where ^ = 1,...,^ , is the number of concurrent users, the number of data streams supported by the first user, and W _fe is the first user Receiving the number of antennas; then calculating the updated value of w according to W:^^^^"]- ¹ , and determining g by the transmission power constraint; wherein, the H

H ₂ is the channel matrix of the i-th and the second users, respectively;  Use (3⁄4 = stomach " /f /^ to calculate the updated value of 3⁄4;  Determining whether the norm of the difference between the updated value of the current w and the updated value of the last w is greater than a preset threshold value, and if so, re-executing the step of calculating the updated value of w; otherwise, determining w The update value is the calculated ^. 5. The method according to claim 1, wherein the linear equalization criterion is a ZF criterion; The calculation is as follows: Initialize W = / _Mxe , where β is the sum of the number of data streams supported by all users, which is the number of transmitting antennas, / is the unit matrix; Use W

Calculating an updated value of W, wherein H = (H Η ... Η _Κ ^Η , ^Η , Η _χ , Η ₂ are the channel matrix of the second user, respectively D^diag^ Gf ... G _K ^H ); Then, it is determined whether the norm of the difference between the updated value of the current w and the updated value of the last W is greater than a preset threshold value, and if so, the step of calculating the updated value of the W is re-executed; otherwise, determining W More The new value is the calculated w. The method according to any one of claims 2 to 5, wherein, if the determination result is no, the method further comprises: normalizing the obtained updated value of W according to the transmission power, and determining the normalization. The updated value of W is the calculated W. The method according to any one of claims 2 to 5, wherein the method further comprises:  The base station processes the pilot signal according to the calculated W, and transmits the processed pilot signal; after receiving the processed pilot signal, the receiving end calculates the receiving matrix of the receiving end. A base station, the base station comprising:  The initialization and calculation module is configured to assume that the precoding matrix of the transmitting end is W, and when the receiving matrix of the receiving end is Gf =, calculate W according to a linear equalization criterion, where g is a common coefficient of the receiving matrix; processing and transmitting module, The downlink signal is processed according to the W calculated by the initialization and calculation module, and the processed downlink signal is transmitted. The base station according to claim 8, wherein if the linear equalization criterion is a minimum mean square error MMSE criterion, the initialization and calculation module comprises: An initialization module, configured to initialize <3⁄4 = ^>^, wherein: = 1,..., , is the number of simultaneous users, the number of data streams supported by the first user, and W _fe is the receiving of the first user Number of antennas; a first calculating module, configured to be initialized by the initialization module or calculated by the second calculating module (3⁄4 of the updated value,

At the same time, g is determined by the transmission power constraint; wherein, H, D ^ diag iG, "G ₂ ^H · · · G _K ^H ), H = (HH ... H _K ^H , ", Η _χ , H ₂ are respectively The channel matrix of 2 users, ξ = ^DD ), _σ ² is the power of additive white Gaussian noise, and Ρ is the total transmit power of the system. Rate, / is a unit matrix; a second calculation module, configured to use the updated value of W calculated by the first calculation module, using (3⁄4

Calculating an updated value of 3⁄4; wherein, the σ ² is the power of additive white Gaussian noise;  a determining module, configured to determine whether a norm of a difference between the updated value of the current W calculated by the second calculating module and the updated value of the last W is greater than a preset threshold, and if yes, indicating The first calculation module recalculates the updated value of w, otherwise, it determines that the update value of the current W is calculated. The base station according to claim 8, wherein if the linear equalization criterion is an MMSE criterion, the initialization and calculation module comprises: An initialization module, configured to initialize W = / _Mxe , where β is the sum of the number of data streams supported by all users, Μ is the number of transmitting antennas, / is a unit matrix; a calculation module, configured to use W = / _Mxe initialized by the initialization module W = H ^H D ^H [DHH ^H D ^H + μΐ calculates the updated value of W, where H = (HH ... H _K ^H , ", H _x , H ₂ ^ are the channels of the first and second users, respectively Matrix, _σ ² is

The power of additive white Gaussian noise, the total transmission power of the system; a determining module, configured to determine whether a norm of a difference between the updated value of the current W calculated by the calculating module and the updated value of the last W is greater than a preset threshold, and if yes, indicating the The calculation module recalculates the updated value of W. Otherwise, it determines that the update value of this time W is calculated. The base station according to claim 8, wherein if the linear equalization criterion is a zero-forcing ZF criterion, the initialization and calculation module includes:  An initialization module, configured to initialize <3⁄4 = ^>^, wherein: = 1,..., , is the number of users simultaneously serving, the number of data streams supported by the first user, and the receiving antenna of the first user Number a first calculation module, configured to initialize the initialization module by = /^ _χΛ ^, or Calculated by the calculation module (3⁄4 update value, calculate the update value of w according to ^2^ ¹ ^^"]- ¹ , and determine g by the transmit power constraint; wherein, the ϋ ϋ όΗ , D ^ diagiG, " 6 ··· G _K ^H ) , H = (H Η ... H _K ^H , ^H , Η _χ , Η ₂ ^ are the channel matrices of the first and second users, respectively;  a second calculating module, configured to use the updated value of W calculated by the first calculating module G _k =

 a determining module, configured to determine whether a norm of a difference between the updated value of the current W calculated by the second calculating module and the updated value of the last W is greater than a preset threshold, and if yes, indicating The first calculation module recalculates the updated value of w, otherwise, it determines that the update value of the current W is calculated. The base station according to claim 8, wherein if the linear equalization criterion is a ZF criterion, the initialization and calculation module comprises: An initialization module, configured to initialize W = / _Mxe , where β is the sum of the number of data streams supported by all users, Μ is the number of transmitting antennas, / is a unit matrix; a calculation module, configured to use W = / _Mxe initialized by the initialization module

Η · · · Η _Κ ^Η ) ^Η , χ , Η ₂ are the channel matrices of the first and second users respectively.

 a determining module, configured to determine whether a norm of a difference between the updated value of the current W calculated by the calculating module and the updated value of the last W is greater than a preset threshold, and if yes, indicating the The calculation module recalculates the updated value of W. Otherwise, it determines that the update value of this time W is calculated. The base station according to any one of claims 9 to 12, wherein the W determining module is configured to determine an update value of the current W calculated by the calculation module or the first calculation module. When the norm of the difference from the updated value of the last W is not greater than the preset threshold value, the obtained updated value of the current W is normalized by the transmission power, and the updated value of W after the normalization is determined. For the calculation of ^. The base station according to any one of claims 9 to 12, wherein the base station further comprises: a pilot signal processing transmitting module, configured to perform a W-guided calculation according to the determination determined by the W determining module The frequency signal is processed and the processed pilot signal is transmitted.

Figure 4

Figure 5

Figure 6