CN106603130B - Digital-analog hybrid precoding method in large-scale MIMO system - Google Patents

Abstract

The invention discloses a digital-analog mixed precoding method in a large-scale MIMO system, which comprises the following steps: the transmitting terminal calculates an ideal precoding matrix; the transmitting end respectively calculates the precoding matrixes of the analog domain and the digital domain; the transmitting end carries out precoding on the transmitted signals; the receiving end calculates an ideal merging matrix; the receiving end respectively calculates the merging matrix of the analog domain and the digital domain; the receiving end combines the received signals. The digital-analog mixed precoding method provided by the invention solves the problem of overhigh complexity of realizing a digital-analog mixed domain precoding scheme in a large-scale MIMO system, can obtain higher frequency spectrum efficiency, and has certain innovativeness and practicability.

Description

A Digital-Analog Hybrid Precoding Method in Massive MIMO System

technical field

The present invention relates to the field of communication technologies, in particular to a digital-analog hybrid precoding method in a massive MIMO system.

Background technique

Multiple-input multiple-output (MIMO) technology can make full use of space resources to combat the fading of wireless channels, thereby improving the reliability and spectrum utilization of the communication system without increasing the system bandwidth and transmit power. At present, MIMO technology has been widely used in various mobile communication standards, such as HSDPA in UMTS system, LTE/LTE-A in 3GPP, WiMAX in IEEE 802.16e/m, and WLAN/ WI-F. In the above-mentioned systems, the antennas at both ends of the transceiver are small in scale, that is, the number of antennas at the base station or access point does not exceed 8 at most, and the number of antennas at the user does not exceed 4 at most.

The 5th generation (5G) mobile communication system aims to provide users with a data transmission rate of Gbit/s. Due to the limitation of existing mobile communication licensed spectrum resources, it is very difficult to achieve this goal. Therefore, research on the application of millimeter-band unlicensed frequency bands in future mobile communications has become the focus of current domestic and foreign scholars' research. Due to the relatively short wavelength of millimeter wave, the physical size of the antenna array is greatly reduced, so large-scale antennas can be installed at the base station, so that the millimeter wave system can be perfectly combined with massive MIMO technology. As an effective technology to effectively improve the data rate of future 5G systems and relieve the pressure on spectrum resources, the research on millimeter-wave massive MIMO systems and related key technologies has become a hot research topic in the field of mobile communications. In a millimeter-wave massive MIMO system, it is particularly important to design a reasonable precoding scheme due to factors such as energy consumption and cost. The traditional small-scale MIMO precoding scheme mainly focuses on the baseband, and uses an all-digital precoder to preprocess the signal, thereby reducing the complexity of interference and receiver processing. In this scheme, the number of RF radio frequency (RF radio frequency) links is equal to the number of transceiver antennas, but the number is relatively small, so the energy consumption and cost are relatively low. However, in a millimeter-wave massive MIMO system, since the number of base station antennas is as high as dozens or even hundreds, this all-digital precoding scheme is no longer applicable. In order to solve the precoding problem in millimeter-wave massive MIMO systems, researchers have proposed multiple digital-analog hybrid precoding schemes. The related research results are mainly divided into the following two categories: The first category is based on the shared antenna design, that is, each RF link is connected to all the antennas. Literature O.El Ayach,S.Rajagopal,S.Abu-Surra,Z.Pi,andR.W.Heath,Jr.,“Spatially sparse precoding in millimeter wave MIMO systems,”IEEE Trans.Wireless Commun.,vol.13 , no.3, pp.1499–1513, Mar.2014, modeled the digital-analog hybrid precoding design as a sparse signal reconstruction problem, and proposed a digital-analog hybrid precoding scheme based on the orthogonal matching pursuit algorithm. Although this scheme can achieve better performance, the implementation complexity is relatively high. The other type is based on split antenna designs, ie each RF link is only connected to all part of the antenna. Literature X. Gao, L. Dai, S. Han, C.-L.I, and R.W. Heath, Jr., "Energy-efficient hybrid analog and digital precoding for mmWave MIMO systems with large antenna arrays," IEEE J.Sel. Areas Commun., vol. 34, no. 4, pp. 998–1009, Apr. 2016, using the idea of continuous interference cancellation, an iterative digital-analog hybrid precoding scheme is proposed. The scheme assumes that the digital domain precoding matrix has a diagonal matrix structure. This assumption makes the digital domain precoding only play the role of power allocation, resulting in a large loss of system performance.

SUMMARY OF THE INVENTION

In view of the above-mentioned defects of the prior art, the technical problem to be solved by the present invention is to provide a digital-analog hybrid precoding method in a massive MIMO system, aiming to solve the problems of the existing digital-analog hybrid precoding scheme based on shared antenna design. Problems with high implementation complexity.

In order to achieve the above object, the present invention provides a digital-analog hybrid precoding method in a massive MIMO system, which is characterized by comprising the following steps:

Step 1, the transmitting end calculates an ideal precoding matrix F _opt ;

Step 2, the transmitting end calculates the precoding matrix F _RF of the analog domain and the precoding matrix F _BB of the digital domain respectively;

Step 3, the transmitting end uses F _RF and F _BB to precode the transmitted signal;

Step 4, the receiving end calculates the ideal merging matrix W _opt ;

Step 5, the receiver calculates the merging matrix W _RF of the analog domain and the merging matrix W _BB of the digital domain respectively;

In step 6, the receiving end uses W _RF and W _BB to combine the received signals.

Further, the step 1 specifically includes:

In the first step, the transmitter estimates the MIMO channel according to the feedback signal from the receiver to obtain an estimate of the MIMO channel matrix

进行奇异值分解，即

其中，Σ₁为N_R×N_T维的对角矩阵且可以表示为Σ₁＝diag(λ₁,λ₂,…,λ_r,0,…,0)，其中，λ₁,λ₂,…,λ_r为

的非零奇异值且满足λ₁＞λ₂＞…＞λ_r且

其中diag()表示对角矩阵，rank()表示求矩阵的秩；而U₁和V₁分别是N_R×N_R维和N_T×N_T维的酉矩阵且()^*表示求矩阵的共轭转置；The second step, the transmitter-to-channel matrix

Perform singular value decomposition, that is

Among them, Σ ₁ is an N _R × _NT dimensional diagonal matrix and can be expressed as Σ ₁ =diag(λ ₁ ,λ ₂ ,…,λ _r ,0,…,0), where λ ₁ ,λ ₂ , ..., _λr is

is a non-zero singular value and satisfies λ ₁ >λ ₂ >…>λ _r and

Where diag() represents a diagonal matrix, and rank() represents the rank of the matrix; U ₁ and V ₁ are N _R ×N _R -dimensional and N _T ×N _T -dimensional unitary matrices, respectively, and () ^* represents the common value of the matrix. yoke transposition;

In the third step, the leftmost N _S column of the matrix V ₁ in the second step is taken as the ideal precoding matrix F _opt .

Further, the step 2 specifically includes:

In the first step, the transmitter initializes the precoding matrix in the analog domain to F _RF =F _opt /||F _opt ||, where || || represents the F-norm of the matrix, and sets the total number of iterations to K, and Initialize the value k of the iteration counter to 0;

In the second step, the transmitter performs singular value decomposition on F _opt F _RF , that is, F _opt F _RF =U ₂ Σ ₂ (V ₂ ) ^* , where F _opt is the ideal precoding matrix obtained in step 1, and F _RF is the upper The precoding matrix in the analog domain obtained in one step; then, the transmitter calculates the precoding matrix in the digital domain as F _BB =V ₂ U ₂ ;

In the third step, the transmitter calculates the precoding matrix in the analog domain as F _RF = (Fo _pt (F _BB ) ^* )/||Fo _pt (F _BB ) ^* ||, where F _opt is the ideal precoding matrix obtained in step 1 Coding matrix, F _BB is the precoding matrix in the digital domain obtained in the previous step; then, the transmitter adds 1 to the value k of the iteration counter, that is, k=k+1;

In the fourth step, the transmitting end judges whether the current value k of the iteration counter is equal to K. If k=K, the second step ends; otherwise, it jumps to the second step.

其中，P_T为发射端的发射功率，s为N_S维的列向量且表示发射端预编码器的N_S路并行输入数据。Further, using the F _RF and F _BB obtained in step 2, the transmitting end precodes the transmitted signal, and the transmitting signal at the transmitting end is

Among them, P _T is the transmit power of the transmitter, s is an N _S -dimensional column vector and represents the N _S parallel input data of the transmitter's precoder.

Further, the step 4 specifically includes:

In the first step, the receiving end estimates the MIMO channel according to the training signal sent by the transmitting end to obtain an estimate of the MIMO channel matrix

进行奇异值分解，即

其中，Σ₃为N_R×N_T维的对角矩阵且可以表示为Σ₃＝diag(η₁,η₂,…,η_r,0,…,0)，其中，η₁,η₂,…,η_r为

的非零奇异值且满足η₁＞η₂＞…＞η_r且

其中diag()表示对角矩阵，rank()表示求矩阵的秩；而U₃和V₃分别是N_R×N_R维和N_T×N_T维的酉矩阵且()^*表示求矩阵的共轭转置；The second step, the receiver to the channel matrix

Perform singular value decomposition, that is

where Σ ₃ is an N _R × _NT dimensional diagonal matrix and can be expressed as Σ ₃ =diag(η ₁ ,η ₂ ,...,η _r ,0,...,0), where η ₁ ,η ₂ , ..., η _r is

non-zero singular values of and satisfy η ₁ >η ₂ >…>η _r and

Where diag() represents a diagonal matrix, and rank() represents the rank of the matrix; and U ₃ and V ₃ are N _R ×N _R -dimensional and N _T ×N _T -dimensional unitary matrices, respectively, and () ^* represents the common value of the matrix. yoke transposition;

In the third step, the leftmost N _S column of the matrix U ₃ in the second step is taken as the ideal precoding matrix W _opt .

Further, the step 5 specifically includes:

In the first step, the receiver initializes the combined matrix of the analog domain as W _RF =Wo _pt /||Wo _pt ||, where || || represents the F-norm of the matrix, and sets the total number of iterations to K, and The value k of the iteration counter is initialized to 0;

In the second step, the receiver performs singular value decomposition on W _opt W _RF , that is, W _opt W _RF =U ₄ Σ ₄ (V ₄ ) ^* , where W _opt is the ideal merging matrix obtained in step 4, and W _RF is the above step The combined matrix of the analog domain obtained in one step; then, the receiving end calculates the combined matrix of the digital domain as W _BB =V ₄ U ₄ ;

In the third step, the receiver calculates the merging matrix in the analog domain as W _RF = (W _opt (W _BB ) ^* )/||W _opt (W _BB ) ^* ||, where W _opt is the ideal merging matrix obtained in step 4 , W _BB is the combined matrix of the digital domain obtained in the previous step; then, the receiving end adds 1 to the value k of the iteration counter, that is, k=k+1;

In the fourth step, the receiving end judges whether the current value k of the iteration counter is equal to K, and if k=K, the fifth step ends; otherwise, it jumps to the second step.

Further, the receiving end uses the W _RF and W _BB obtained in step 5 to combine the received signals, and the combined output signal is y=(W _BB ) ^* (W _RF ) ^* Hx, where y is an N _S dimension column The vector also represents the N _S parallel output data combined by the receiving end, x is the transmitted signal of the transmitting end, H represents the actual MIMO channel between the transmitting end and the receiving end, () ^* represents the conjugate transpose of the matrix.

The beneficial effects of the present invention are as follows: the digital-analog hybrid precoding method proposed by the present invention solves the problem that the implementation complexity of the digital-analog hybrid domain precoding scheme in the massive MIMO system is too high, and at the same time, higher spectral efficiency can be obtained, and it has certain advantages. innovation and practicality.

The concept, specific structure and technical effects of the present invention will be further described below in conjunction with the accompanying drawings, so as to fully understand the purpose, characteristics and effects of the present invention.

Description of drawings

FIG. 1 is a flowchart of a digital-analog hybrid precoding method in a massive MIMO system provided by an embodiment of the present invention.

FIG. 2 is a model diagram of a digital-analog hybrid precoding method in a massive MIMO system provided by an embodiment of the present invention.

FIG. 3 is an implementation flowchart of Embodiment 1 provided by an embodiment of the present invention.

FIG. 4 is an implementation flowchart of step 2 provided by an embodiment of the present invention.

FIG. 5 is an implementation flowchart of step 4 provided by an embodiment of the present invention.

FIG. 6 is a schematic diagram of a spectrum efficiency curve of a massive MIMO system provided by an embodiment of the present invention using the proposed and existing digital-analog hybrid precoding methods respectively.

Detailed ways

As shown in FIG. 1 , a digital-analog hybrid precoding solution in a massive MIMO system provided by an embodiment of the present invention includes the following steps:

S101: The transmitting end calculates an ideal precoding matrix;

S102: The transmitter calculates the precoding matrices in the analog domain and the digital domain respectively;

S103: The transmitting end precodes the transmitted signal;

S104: the receiving end calculates an ideal combining matrix;

S105: The receiver calculates the combined matrix of the analog domain and the digital domain respectively;

S106: The receiving end combines the received signals.

The application principle of the present invention will be further described below with reference to specific embodiments.

Example 1:

The model of the digital-analog hybrid precoding scheme in the massive MIMO system adopted in the embodiment of the present invention is shown in FIG. 2 , in which the transmitting end is equipped with N _T transmitting antennas and N _S radio frequency links, and the receiving end is equipped with _NR Transmitting antenna, N _S RF links. The wireless link between transmission and reception can be represented by a channel matrix H of ×N _R N _T dimension.

As shown in Figure 3, the implementation steps of the embodiment of the present invention are as follows:

Step 1, the transmitter calculates an ideal precoding matrix F _opt , and the specific steps are as follows:

具体估计方法可参见文献：H.Jin,D.Gesbert,M.Filippou,and Y.Liu,“A coordinatedapproach to channel estimation in large-scale multiple-antenna systems,”IEEEJ.Sel.Areas Commun,vol.31,no.2,pp.264–273,Feb.2013等；1a) The transmitter estimates the MIMO channel according to the feedback signal from the receiver to obtain the estimation of the MIMO channel matrix

The specific estimation method can be found in the literature: H. Jin, D. Gesbert, M. Filippou, and Y. Liu, "A coordinated approach to channel estimation in large-scale multiple-antenna systems," IEEE J. Sel. Areas Commun, vol.31 , no.2, pp.264–273, Feb.2013, etc.;

进行奇异值分解，即

其中，Σ₁为N_R×N_T维的对角矩阵且可以表示为Σ₁＝diag(λ₁,λ₂,…,λ_r,0,…,0)，其中，λ₁,λ₂,…,λ_r为

的非零奇异值且满足λ₁＞λ₂＞…＞λ_r且

其中diag()表示对角矩阵，rank()表示求矩阵的秩；而U₁和V₁分别是N_R×N_R维和N_T×N_T维的酉矩阵且()^*表示求矩阵的共轭转置。1b) Transmitter-to-channel matrix

Perform singular value decomposition, that is

Among them, Σ ₁ is an N _R × _NT dimensional diagonal matrix and can be expressed as Σ ₁ =diag(λ ₁ ,λ ₂ ,…,λ _r ,0,…,0), where λ ₁ ,λ ₂ , ..., _λr is

is a non-zero singular value and satisfies λ ₁ >λ ₂ >…>λ _r and

Where diag() represents a diagonal matrix, and rank() represents the rank of the matrix; U ₁ and V ₁ are N _R ×N _R -dimensional and N _T ×N _T -dimensional unitary matrices, respectively, and () ^* represents the common value of the matrix. Yoke transposed.

1c) Take the leftmost N _S column of the matrix V ₁ in step 1b) as the ideal precoding matrix F _opt .

Step 2, according to the flowchart shown in FIG. 4 , the transmitter uses the following iterative method to calculate the precoding matrix F _RF in the analog domain and the precoding matrix F _BB in the digital domain, respectively. The specific steps are as follows:

2a) The transmitter initializes the precoding matrix in the analog domain to F _RF =F _opt /||F _opt ||, where || || represents the F-norm of the matrix, and sets the total number of iterations to K, and iterates The value k of the counter is initialized to 0;

2b) The transmitter performs singular value decomposition on F _opt F _RF , that is, F _opt F _RF =U ₂ Σ ₂ (V ₂ ) ^* , where F _opt is the ideal precoding matrix obtained in step 1, and F _RF is step 2a) The obtained precoding matrix in the analog domain; then, the transmitter calculates the precoding matrix in the digital domain as F _BB =V ₂ U ₂ ;

2c) The precoding matrix calculated by the transmitter in the analog domain is F _RF = (F _opt (F _BB ) ^* )/||F _opt (F _BB ) ^* ||, where F _opt is the ideal precoding matrix obtained in step 1 , F _BB is the precoding matrix in the digital domain obtained in step 2b); then, the transmitter adds 1 to the value k of the iteration counter, that is, k=k+1;

2d) The transmitter determines whether the current value k of the iteration counter is equal to K. If k=K, step 2 ends; otherwise, jump to step 2b).

其中，P_T为发射端的发射功率，s为N_S维的列向量且表示发射端预编码器的N_S路并行输入数据。Step 3, using the F _RF and F _BB obtained in step 2, the transmitting end precodes the transmitted signal. The signal sent by the transmitter is

Among them, P _T is the transmit power of the transmitter, s is an N _S -dimensional column vector and represents the N _S parallel input data of the transmitter's precoder.

Step 4, the receiving end calculates the ideal merging matrix W _opt , and the specific steps are as follows:

具体估计方法可参见文献：H.Jin,D.Gesbert,M.Filippou,and Y.Liu,“Acoordinated approach to channel estimation in large-scale multiple-antennasystems,”IEEE J.Sel.Areas Commun,vol.31,no.2,pp.264–273,Feb.2013等；4a) The receiving end estimates the MIMO channel according to the training signal sent by the transmitting end to obtain the estimation of the MIMO channel matrix

The specific estimation method can be found in the literature: H.Jin, D.Gesbert, M.Filippou, and Y.Liu, "Acoordinated approach to channel estimation in large-scale multiple-antennasystems," IEEE J.Sel.Areas Commun, vol.31 , no.2, pp.264–273, Feb.2013, etc.;

进行奇异值分解，即

其中，Σ₃为N_R×N_T维的对角矩阵且可以表示为Σ₃＝diag(η₁,η₂,…,η_r,0,…,0)，其中，η₁,η₂,…,η_r为

的非零奇异值且满足η₁＞η₂＞…＞η_r且

其中diag()表示对角矩阵，rank()表示求矩阵的秩；而U₃和V₃分别是N_R×N_R维和N_T×N_T维的酉矩阵且()^*表示求矩阵的共轭转置。4b) Receiver-to-channel matrix

Perform singular value decomposition, that is

where Σ ₃ is an N _R × _NT dimensional diagonal matrix and can be expressed as Σ ₃ =diag(η ₁ ,η ₂ ,...,η _r ,0,...,0), where η ₁ ,η ₂ , ..., η _r is

non-zero singular values of and satisfy η ₁ >η ₂ >…>η _r and

Where diag() represents a diagonal matrix, and rank() represents the rank of the matrix; and U ₃ and V ₃ are N _R ×N _R -dimensional and N _T ×N _T -dimensional unitary matrices, respectively, and () ^* represents the common value of the matrix. Yoke transposed.

4c) Take the leftmost N _S column of the matrix U ₃ in step 4b) as the ideal precoding matrix W _opt .

Step 5, according to the flow chart shown in FIG. 5, the receiving end uses the following iterative method to calculate the merging matrix W _RF of the analog domain and the merging matrix W _BB of the digital domain respectively, and the specific steps are as follows:

5a) The receiver initializes the combined matrix of the analog domain as W _RF =W _opt /||W _opt ||, where || || represents the F-norm of the matrix, and sets the total number of iterations to K, and sets the iteration counter to The value of k is initialized to 0;

5b) The receiver performs singular value decomposition on W _opt W _RF , that is, W _opt W _RF =U ₄ Σ ₄ (V ₄ ) ^* , where W _opt is the ideal merging matrix obtained in step 4, and W _RF is obtained in step 5a) The combined matrix of the analog domain; then, the receiving end calculates the combined matrix of the digital domain as W _BB =V ₄ U ₄ ;

5c) The receiving end calculates the merging matrix in the analog domain as W _RF =(W _opt (W _BB ) ^* )/||W _opt (W _BB ) ^* ||, where W _opt is the ideal merging matrix obtained in step 4, W _BB is the combined matrix of the digital domain obtained in step 5b); then, the receiving end adds 1 to the value k of the iteration counter, that is, k=k+1;

5d) The receiving end judges whether the current value k of the iteration counter is equal to K. If k=K, step 5 ends; otherwise, jump to step 5b).

其中，y为N_S维的列向量且表示接收端合并后的N_S路并行输出数据，x是发送端发送信号，H表示发射端与接收端之间实际的MIMO信道，()^*表示求矩阵的共轭转置。Step 6, using the W _RF and W _BB obtained in step 5, the receiving end combines the received signals, and the combined output signal is

Among them, y is an N _S -dimensional column vector and represents the N _S channels of parallel output data combined by the receiving end, x is the signal sent by the transmitting end, H is the actual MIMO channel between the transmitting end and the receiving end, and () ^* represents the Conjugate transpose of a matrix.

The application effect of the present invention will be described in detail below in conjunction with simulation.

1) Simulation conditions:

Assuming that in the massive MIMO system adopted in the present invention, the number of antennas configured at the transmitter and the receiver is equal to 128, that is, N _t =N _r =128, and the number of parallel data streams between the transmitter and receiver takes the following two values : _Ns =2 and _Ns =4. For the channel model, please refer to the millimeter-wave MIMO channel model adopted by the existing precoding scheme. For details, please refer to the literature: El Ayach, S. Rajagopal, S. Abu-Surra, Z. Pi, and RWHeath, Jr., "Spatially sparse precoding in millimeter wave MIMO systems,” IEEE Trans.Wireless Commun., vol. 13, no. 3, pp. 1499–1513, Mar. 2014. In the above channel model, it is assumed that the number of scattering clusters is N _cl =3, and the number of transmission paths is N _ray =18. In addition, it is assumed that the noise at the receiving end is additive white Gaussian noise with a mean value of zero and a variance of N ₀ . The abscissa in the simulation results is the signal-to-noise ratio, which is defined as 10log ₁₀ (P _T /N ₀ ), where P _T represents the transmit power of the transmitter.

2) Simulation content and results:

而本发明提出的预编码方案的实现复杂度为

其中，N_S为收发之间的并行数据流个数，而N_T和N_R分别为收发两端的天线数。所以，通过以上比较可以看出，本发明提出的预编码方案可以获得比现有的预编码方案更高的频谱效率且实现复杂度更低。For the massive MIMO system adopting the precoding scheme proposed by the present invention, a computer is used to simulate the spectral efficiency of the system, and the simulation result is shown in FIG. 6 . It can be seen from FIG. 6 that the precoding scheme proposed by the present invention can obtain higher spectral efficiency than the existing precoding scheme, and with the increase of the number of parallel data streams N _S between sending and receiving, the The performance advantage of the precoding scheme is more obvious. In addition, through the analysis of the algorithm implementation complexity, it can be obtained that the implementation complexity of the existing precoding scheme is:

And the implementation complexity of the precoding scheme proposed by the present invention is:

Among them, N _S is the number of parallel data streams between transceivers, and _NT and _NR are the number of antennas at both ends of the transceiver. Therefore, it can be seen from the above comparison that the precoding scheme proposed by the present invention can obtain higher spectral efficiency and lower implementation complexity than the existing precoding scheme.

The preferred embodiments of the present invention have been described in detail above. It should be understood that those skilled in the art can make numerous modifications and changes according to the concept of the present invention without creative efforts. Therefore, all technical solutions that can be obtained by those skilled in the art through logical analysis, reasoning or limited experiments on the basis of the prior art according to the concept of the present invention shall fall within the protection scope determined by the claims.

Claims (6)

1. A digital-analog mixed precoding method in a large-scale MIMO system is characterized by comprising the following steps:

step one, a transmitting terminal calculates an ideal precoding matrix F_opt；

Step two, the transmitting end respectively calculates the precoding matrix F of the analog domain_RFAnd a precoding matrix F in the digital domain_BB；

Step three, the transmitting terminal utilizes F_RFAnd F_BBPrecoding a transmission signal;

step four, the receiving end calculates an ideal merging matrix W_opt；

Step five, the receiving end respectively calculates the merging matrix W of the analog domain_RFAnd a merging matrix W in the digital domain_BB；

Step six, the receiving end utilizes W_RFAnd W_BBCombining the received signals;

the first step specifically comprises:

firstly, a transmitting end estimates an MIMO channel according to a feedback signal of a receiving end to obtain the estimation of an MIMO channel matrix

Second, the transmitting end pairs channel matrix

Performing singular value decomposition, i.e.

Wherein, sigma₁Is N_R×N_TDiagonal matrix of dimensions and can be expressed as Σ₁＝diag(λ₁,λ₂,…,λ_r0, …,0), where λ₁,λ₂,…,λ_rIs composed of

And satisfies lambda₁＞λ₂＞…＞λ_rAnd is

Wherein diag () represents a diagonal matrix, and rank () represents the rank of the matrix; and U₁And V₁Are each N_R×N_RAnd N_T×N_TUnitary matrix of dimension ()^*Representing the conjugate transpose of the matrix;

thirdly, taking the matrix V in the second step₁Leftmost N_SPrecoding matrix F with ideal columns_opt。

2. The digital-analog hybrid precoding method in the massive MIMO system as claimed in claim 1, wherein the second step specifically comprises:

firstly, a transmitting end initializes a precoding matrix of an analog domain to F_RF＝F_opt/||F_optL, wherein l represents the F norm of the matrix; setting the total iteration number as K, and initializing the value K of an iteration counter to 0;

second, the transmitting end pair F_optF_RFPerforming singular value decomposition, i.e. F_optF_RF＝U₂Σ₂(V₂)^*Wherein F is_optFor the ideal precoding matrix obtained in step one, F_RFThe precoding matrix of the analog domain obtained in the last step; then, the transmitting end calculates the precoding matrix of the digital domain as F_BB＝V₂U₂；

Thirdly, the transmitting end calculates the precoding matrix of the analog domain as F_RF＝(F_opt(F_BB)^*)/||F_opt(F_BB)^*I, |, wherein F_optFor the ideal precoding matrix obtained in step one, F_BBThe precoding matrix of the digital domain obtained in the last step; then, the transmitting end adds 1 to the value k of the iteration counter, namely k equals to k + 1;

fourthly, the transmitting end judges whether the current value K of the iterative counter is equal to K, if the current value K of the iterative counter is equal to K, the second step is finished; otherwise, jumping to the second step.

3. The digital-to-analog hybrid precoding method in massive MIMO system as claimed in claim 1, wherein F obtained in step two is used_RFAnd F_BBThe transmitting end carries out precoding on the transmitting signal, and the transmitting signal of the transmitting end is

Wherein, P_TIs the transmitting power of the transmitting end, s is N_SColumn vector of dimension and representing N of the transmit-side precoder_SParallel transmissionAnd inputting data.

4. The digital-analog hybrid precoding method in the massive MIMO system as claimed in claim 1, wherein the fourth step specifically comprises:

firstly, the receiving end estimates the MIMO channel according to the training signal sent by the transmitting end to obtain the estimation of the MIMO channel matrix

Second, the receiving end pairs channel matrix

Performing singular value decomposition, i.e.

Wherein, sigma₃Is N_R×N_TDiagonal matrix of dimensions and can be expressed as Σ₃＝diag(η₁,η₂,…,η_r0, …,0), wherein, η₁,η₂,…,η_rIs composed of

And satisfies η₁＞η₂＞…＞η_rAnd is

Wherein diag () represents a diagonal matrix, and rank () represents the rank of the matrix; and U₃And V₃Are each N_R×N_RAnd N_T×N_TUnitary matrix of dimension ()^*Representing the conjugate transpose of the matrix;

thirdly, taking the matrix U in the second step₃Leftmost N_SMerged matrix W with columns as ideals_opt。

5. The digital-analog hybrid precoding method in the massive MIMO system as claimed in claim 1, wherein the step five specifically includes:

firstly, the receiving end initializes the merging matrix of the analog domain to W_RF＝W_opt/||W_optL, wherein l represents the F norm of the matrix; setting the total iteration number as K, and initializing the value K of an iteration counter to 0;

second, receiving port pair W_optW_RFPerforming singular value decomposition, i.e. W_optW_RF＝U₄Σ₄(V₄)^*Wherein W is_optFor the ideal merged matrix obtained in step four, W_RFMerging matrix of the analog domain obtained in the last step; then, the receiving end calculates the merging matrix of the digital domain as W_BB＝V₄U₄；

Thirdly, the receiving end calculates the merging matrix of the analog domain as W_RF＝(W_opt(W_BB)^*)/||W_opt(W_BB)^*L, wherein W_optFor the ideal merged matrix obtained in step four, W_BBMerging the digital domains obtained in the previous step; then, the receiving end adds 1 to the value k of the iteration counter, namely k is k + 1;

fourthly, the receiving end judges whether the current value K of the iterative counter is equal to K, if the current value K of the iterative counter is equal to K, the fifth step is finished; otherwise, jumping to the second step.

6. The digital-analog hybrid precoding method in massive MIMO system as claimed in claim 1, wherein the receiving end utilizes W obtained in step five_RFAnd W_BBThe received signals are combined, and the combined output signal is y ═ W_BB)^*(W_RF)^*Hx, wherein y is N_SColumn vector of dimension and represents N after receiving end merging_SThe paths output data in parallel, x is the sending signal of the sending end, H represents the actual MIMO channel matrix between the sending end and the receiving end, ()^*Representing the conjugate transpose of the matrix.

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