CN105208572B - A kind of beam-forming method and base station - Google Patents
A kind of beam-forming method and base station Download PDFInfo
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Abstract
The embodiment of the invention discloses a kind of beam-forming method and base stations, can optimize beamforming matrix, to maximize power system capacity.The method comprise the steps that base station obtains the first channel information；The base station determines the Signal to Interference plus Noise Ratio SINR of the UE according to first channel information；When the SINR meets preset condition, the base station determines beamforming matrix using the first optimization problem, wherein, the objective function of first optimization problem is the power system capacity determined according to the SINR, and the constraint function of first optimization problem is the constraint condition of system total transmission power；The base station carries out beam forming according to the beamforming matrix.
Description
Technical Field
The present invention relates to the field of communications technologies, and in particular, to a beamforming method and a base station.
Background
Beamforming is a digital processing technique for directional transmission of wireless signals, and the basic idea is to linearly precode multi-user signals so that each user's signal is transmitted only in the direction of the user as much as possible and to avoid interfering with other users.
The conventional beamforming method is a zero-forcing (ZF) method, and a basic idea of the ZF is to completely eliminate multi-User interference, so that each UE (User Equipment) only receives a useful signal and noise of the UE; mathematically, ZF is the pseudo-inverse of having the beamforming matrix equal to the channel matrix. However, from the viewpoint of maximizing the system capacity, it is not necessary or even harmful to try to completely eliminate the multiuser interference, because the cost of completely eliminating the multiuser interference is that the useful signal of each user becomes small, and therefore, ZF does not give a high system capacity.
Disclosure of Invention
The embodiment of the invention provides a beam forming method and a base station, which can optimize a beam forming matrix so as to maximize system capacity.
A first aspect of an embodiment of the present invention provides a beam forming method for an FDD system, including:
a base station acquires first channel information;
the base station determines the signal to interference plus noise ratio (SINR) of the UE according to the first channel information;
when the SINR meets a preset condition, the base station determines a beam forming matrix by using a first optimization problem, wherein an objective function of the first optimization problem is system capacity determined according to the SINR, and a constraint function of the first optimization problem is a constraint condition of total system transmission power;
and the base station carries out beam forming according to the beam forming matrix.
With reference to the first aspect of the embodiment of the present invention, in a first implementation manner of the first aspect of the embodiment of the present invention, the determining, by the base station, a beamforming matrix by using a first optimization problem includes:
the base station determines a beamforming matrix using a first optimization problem:
wherein R represents the system capacity, andwherein,d denotes the k UEkThe priority of the individual data streams,d denotes the k UEkA data rate of a data stream, andwherein,is the d-th UE of the k-thkSINR of each data stream;
the constraint condition of the total transmission power of the system represents that the total transmission power of the system is not more than a certain preset PTWhereind denotes the k UEkA beamforming matrix for each data stream.
With reference to the first implementation manner of the first aspect of the embodiment of the present invention, in a second implementation manner of the first aspect of the embodiment of the present invention, the determining, by the base station, a beamforming matrix by using the following first optimization problem includes:
the base station creating the first optimization problem;
the base station optimizes the first optimization problemExecuting conjugate function deformation of a logarithmic function, and acquiring an optimal solution of a first variable, wherein the first variable is a newly introduced variable in the conjugate function deformation of the logarithmic function;
the base station being deformed by the conjugate function of the implemented logarithmic functionExecuting conjugate function deformation of the quadratic function to obtain a second optimization problem, and acquiring an optimal solution of a second variable, wherein the second variable is a newly introduced variable in executing conjugate function deformation of the two functions;
the base station determines a beamforming matrix using the second optimization problem, the optimal solution for the first variable, and the optimal solution for the second variable.
With reference to the second implementation manner of the first aspect of the embodiment of the present invention, in a third implementation manner of the first aspect of the embodiment of the present invention, the determining, by the base station, a beamforming matrix by using the second optimization problem, the optimal solution of the first variable, and the optimal solution of the second variable includes:
the base station decomposes a second variable in the second optimization problem into a product of a first sub-variable and a second sub-variable to obtain a third optimization problem;
and the base station determines a beam forming matrix by using the third optimization problem, the optimal solution of the first variable and the optimal solution of the second variable.
With reference to the first aspect of the embodiment of the present invention and the first to third implementation manners of the first aspect, in a fourth implementation manner of the first aspect of the embodiment of the present invention,
the first channel information is a right singular vector of second channel information, wherein the second channel information is channel information obtained by channel estimation of a downlink channel by the UE;
the base station determining the SINR of the UE according to the first channel information includes:
and the base station takes the left singular vector of the second channel information as a filter of a linear receiver, and determines the SINR of the UE according to the first channel information.
With reference to the fourth implementation of the first aspect of the embodiments of the present invention, in a fifth implementation of the first aspect of the embodiments of the present invention,
the base station acquiring the first channel information comprises:
the base station receives third channel information sent by the UE, wherein the third channel information comprises a target right singular vector, target included angle information and a singular value; the UE carries out singular value decomposition on the second channel information to obtain a left singular vector, a right singular vector and the singular value, the UE quantizes the right singular vector into a code word with the smallest included angle with the right singular vector to obtain the target right singular vector, and calculates included angle information corresponding to quantization errors in the quantization process to obtain the target included angle information;
the base station determines first channel information by using error modeling of a channel, wherein the error modeling of the channel is constructed by corresponding relation among the first channel information, a target right singular vector and target included angle information.
With reference to the fifth implementation manner of the first aspect of the embodiment of the present invention, in a sixth implementation manner of the first aspect of the embodiment of the present invention, the determining, by the base station, the first channel information by using error modeling of a channel includes:
the base station obtains and determines first channel information based on the following model:
wherein,as the information of the first channel, it is,for the target right singular vector, the right singular vector,is the information of the target included angle,is composed ofOne orthonormal basis of the orthogonal complement space of the subspace in which,is one in dimension NB-1 random vectors uniformly distributed on a unit sphere.
A second aspect of an embodiment of the present invention provides a base station, including:
an acquisition unit configured to acquire first channel information;
a first determining unit, configured to determine a signal to interference plus noise ratio SINR of the UE according to the first channel information;
a second determining unit, configured to determine a beamforming matrix by using a first optimization problem when the SINR satisfies a preset condition, where an objective function of the first optimization problem is a system capacity determined according to the SINR, and a constraint function of the first optimization problem is a constraint condition of a total system transmit power;
and the execution unit is used for carrying out beam forming according to the beam forming matrix.
In combination with the second aspect of the embodiments of the present invention, in a first implementation of the second aspect of the embodiments of the present invention,
the second determining unit is specifically configured to determine the beamforming matrix using the following first optimization problem:
wherein R represents the system capacity, andwherein,d denotes the k UEkThe priority of the individual data streams,d denotes the k UEkA data rate of a data stream, andwherein,is the d-th UE of the k-thkSINR of each data stream;
the constraint condition of the total transmission power of the system represents that the total transmission power of the system is not more than a certain preset PTWhereind denotes the k UEkA beamforming matrix for each data stream.
With reference to the first implementation manner of the second aspect of the embodiment of the present invention, in a second implementation manner of the second aspect of the embodiment of the present invention, the second determining unit includes:
a creation module for creating the first optimization problem;
a first operation module for performing the first optimization problemExecuting conjugate function deformation of a logarithmic function, and acquiring an optimal solution of a first variable, wherein the first variable is a newly introduced variable in the conjugate function deformation of the logarithmic function;
a second operation module for transforming the conjugate function of the executed logarithm functionExecuting conjugate function deformation of the quadratic function to obtain a second optimization problem, and acquiring an optimal solution of a second variable, wherein the second variable is a newly introduced variable in executing conjugate function deformation of the two functions;
a first determining module for determining a beamforming matrix using the second optimization problem, the optimal solution for the first variable, and the optimal solution for the second variable.
With reference to the second implementation manner of the second aspect of the embodiment of the present invention, in a third implementation manner of the second aspect of the embodiment of the present invention, the first determining module includes:
the operation submodule decomposes a second variable in the second optimization problem into a product of a first sub-variable and a second sub-variable to obtain a third optimization problem;
and the determining submodule is used for determining the beam forming matrix by utilizing the third optimization problem, the optimal solution of the first variable and the optimal solution of the second variable.
With reference to the second aspect of the embodiment of the present invention and the first to third implementation manners of the second aspect, in a fourth implementation manner of the second aspect of the embodiment of the present invention,
the first channel information is a right singular vector of second channel information, wherein the second channel information is channel information obtained by channel estimation of a downlink channel by the UE;
the first determining unit is specifically configured to determine the SINR of the UE according to the first channel information by using the left singular vector of the second channel information as a filter of a linear receiver.
With reference to the fourth implementation manner of the second aspect of the embodiment of the present invention, in a fifth implementation manner of the second aspect of the embodiment of the present invention, the obtaining unit includes:
a receiving module, configured to receive third channel information sent by the UE, where the third channel information includes a target right singular vector, target included angle information, and a singular value; the UE carries out singular value decomposition on the second channel information to obtain a left singular vector, a right singular vector and the singular value, the UE quantizes the right singular vector into a code word with the smallest included angle with the right singular vector to obtain the target right singular vector, and calculates included angle information corresponding to quantization errors in the quantization process to obtain the target included angle information;
and the second determining module is used for determining the first channel information by using error modeling of the channel, wherein the error modeling of the channel is constructed by a corresponding relation among the first channel information, the target right singular vector and the target included angle information.
In combination with the fifth implementation of the second aspect of the embodiment of the present invention, in the sixth implementation of the second aspect of the embodiment of the present invention,
the second determining module is specifically configured to obtain and determine the first channel information based on the following model:
wherein,as the information of the first channel, it is,for the target right singular vector, the right singular vector,is the information of the target included angle,is composed ofOne orthonormal basis of the orthogonal complement space of the subspace in which,is one in dimension NB-1 random vectors uniformly distributed on a unit sphere.
In the technical scheme provided by the embodiment of the invention, a base station firstly acquires first channel information and determines the SINR of UE according to the first channel information; when the SINR is determined to meet the preset condition, a beam forming matrix is determined by using a first optimization problem, wherein an objective function of the first optimization problem is the system capacity determined according to the SINR, a constraint function of the first optimization problem is the constraint condition of the total transmission power of the system, and beam forming is performed according to the determined beam forming matrix.
Drawings
Fig. 1 is a schematic structural diagram of an FDD system according to an embodiment of the present invention;
fig. 2 is a diagram illustrating an embodiment of a beam forming method of an FDD system according to an embodiment of the present invention;
fig. 3 is a diagram illustrating another example of a beam forming method of an FDD system according to an embodiment of the present invention;
FIG. 4 is a graph showing the spectral efficiency of the present invention compared to other prior art methods;
FIG. 5 shows the convergence of the beamforming matrix algorithm proposed by the present invention;
FIG. 6 is a diagram of an embodiment of a base station in an embodiment of the present invention;
fig. 7 is a schematic diagram of another embodiment of a base station in the embodiment of the present invention.
Detailed Description
Embodiments of the present invention provide a beamforming method and a base station, which may optimize a beamforming matrix to maximize system capacity, and are described in detail below.
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The terms "first," "second," "third," "fourth," and the like in the description and in the claims, as well as in the drawings, if any, are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It will be appreciated that the data so used may be interchanged under appropriate circumstances such that the embodiments described herein may be practiced otherwise than as specifically illustrated or described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
In the present invention, an FDD system for MU-MIMO (Multi-User Multi-Input Multi-Output) communication is applied, as shown in fig. 1, the FDD system for MU-MIMO communication includes a base station 101 and k users 102 (corresponding to UEs), wherein the base station 101 is equipped with N users 102, and the base station 101 is equipped with N usersBAn antenna, user k being equipped with NU,kAn antenna.
Referring to fig. 2, an embodiment of a beamforming method of an FDD system according to the embodiment of the present invention includes:
201. a base station acquires first channel information;
in the FDD system, the base station may obtain the first channel information according to the channel information fed back by the user, and use the first channel information as a reference quantity of channel information for subsequently solving the beamforming matrix.
202. The base station determines the SINR of the user according to the first channel information;
in this embodiment, after the first channel information is obtained, the SINR may be determined according to an existing SINR (signal to interference plus noise ratio) solving formula, which is not described herein again.
203. When the SINR meets a preset condition, the base station determines a beam forming matrix by using a first optimization problem;
in the present embodiment, it is preferred that,denotes a beamforming matrix, wherein DkRepresenting the number of data streams for user k.
In this embodiment, all SINRs in the following form may be considered to satisfy the preset condition:
wherein, the total received power is represented, andand may be any parameter that does not necessarily need to have some fixed physical meaning, such as a channel matrix; is the power of additive white gaussian noise.
It should be noted that, in this embodiment, the objective function of the first optimization problem is system capacity determined according to SINR, and the constraint function is a constraint condition of total system transmit power, which may specifically be:
wherein R represents the system capacity, andwherein,data stream d representing user kkThe priority of the user's hand in the user's hand,data stream d representing user kkA data rate of, andwherein the data stream d of user kkAn expression of signal to interference plus noise ratio of (c);
the constraint condition of the total transmission power of the system represents that the total transmission power of the system is not more than a certain preset PTWhereindata stream d representing user kkThe beamforming matrix of (1).
In the actual processing process, the first optimization problem involves a logarithm operation and a matrix inversion operation, and the processing difficulty is large. For this purpose, preferably, new variables are introduced by means of a conjugate function deformationThe expression of (2) to eliminate logarithm and matrix inversion operations specifically includes:
1) base station pairExecuting conjugate function deformation of the logarithm function, and obtaining an optimal solution of a first variable;
in the process of the deformation of the conjugate function, a new variable is introduced, namely the first variable. In the present embodiment, the conjugate function of the logarithmic function is modifiedCan be expressed as an unconstrained optimization problem, whereby the base station can rely on the unconstrained optimizationThe problem of formulation may solve for an optimal solution for the first variable. It is understood that the specific process of the deformation of the conjugate function of the logarithmic function is known to the person skilled in the art from the prior art, for example, it can be understood that: given any positive number e, loge can be expressed as loge minw≥0ew-logw-1。
2) After deformation of the conjugate function of the implemented logarithmic function by the base stationExecuting conjugate function deformation of the quadratic function to obtain a second optimization problem and obtain an optimal solution of a second variable;
similarly, during the deformation of the conjugate function, a new variable, namely the second variable, is introduced. In the present embodiment, after performing the deformation of the conjugate function of the quadratic functionCan be expressed as a unconstrained optimization problem whereby, for a fixed first variable (i.e., the best solution to the solved first variable described above), the base station can solve the best solution to the second variable according to the unconstrained optimization problem. It is understood that the specific process of deformation of the conjugate function of the quadratic function is known to a person skilled in the art from the prior art, and can be understood as follows, for example: given any complex number t, positive numbers λ and J, then the number- λ2|t|2May be represented byWhereinRepresents the real part (·)*Representing conjugation.
3) The base station determines a beam forming matrix by using the second optimization problem, the optimal solution of the first variable and the optimal solution of the second variable;
in the optimization of the first problemAfter performing the above conjugate function deformation twice, the first optimization problem can be transformed into a second optimization problem, and it can be understood that the second optimization problem can be optimized by using BCD (block coordination decrease) compared to the first optimization problem, and if any two of the three variables (i.e. the beamforming matrix, the first variable, and the second variable) are fixed, the second optimization problem has a closed solution for the third variable.
In this embodiment, the optimal solution of the first variable and the optimal solution of the second variable may be substituted into the second optimization problem to determine an initial beamforming matrix and initialize the beamforming matrix, and then the beamforming matrix, the first variable, and the second variable are alternately updated iteratively, and when a preset iteration stop condition is satisfied, a final beamforming matrix is determined. Here, the preset iteration stop condition may include that the number of iterations reaches a preset value or that a target value of the second optimization problem increases by less than a certain threshold, and in an actual application process, the preset iteration stop condition may also be a combination of the two manners or another manner, and is not limited herein.
Considering that a Water-filling algorithm (Water-filling) is needed to be used when the BCD is directly used to solve the beamforming matrix, the computation complexity is high, so that the embodiment further provides a third optimization problem on the basis of the second optimization problem to avoid the Water-filling algorithm and reduce the computation complexity, and the method specifically includes:
1) decomposing the first variable of the second optimization problem into a product of the first sub-variable and the second sub-variable to obtain a third optimization problem;
the second variable is decomposed into product terms of two sub-variables to transform the second optimization problem into a third optimization problem, and it can be understood that, in the third optimization problem, four groups of variables are included, respectively: compared with the second optimization problem, the third optimization problem has a closed solution for solving the beamforming matrix and the first sub-variable, so that the beamforming matrix does not need to be solved by a water filling algorithm, and the complexity of solving the beamforming matrix can be reduced.
In this embodiment, the optimal solution of the first variable and the optimal solution of the second variable may be substituted into the third optimization problem to determine an initial beamforming matrix and initialize the beamforming matrix, and then the second sub-variable, the first variable, the beamforming matrix, and the second sub-variable are alternately updated iteratively, and when a preset iteration stop condition is satisfied, the final beamforming matrix is determined. Here, the preset iteration stop condition may include that the number of iterations reaches a preset value or that a target value of the second optimization problem increases by less than a certain threshold, and in an actual application process, the preset iteration stop condition may also be a combination of the two manners or another manner, and is not limited herein.
204. The base station carries out beam forming according to the beam forming matrix;
in particular, how to perform beamforming by using the beamforming matrix is not described in detail herein, and those skilled in the art can obtain a corresponding processing flow according to the prior art.
In the technical scheme provided by the embodiment of the invention, a base station firstly acquires first channel information and determines the SINR of UE according to the first channel information; when the SINR is determined to meet the preset condition, a beam forming matrix is determined by using a first optimization problem, wherein an objective function of the first optimization problem is the system capacity determined according to the SINR, a constraint function of the first optimization problem is the constraint condition of the total transmission power of the system, and beam forming is performed according to the determined beam forming matrix.
On the basis of the embodiment shown in fig. 2, the following describes in detail a specific process of acquiring the first channel information by the base station, and with reference to fig. 3 in particular, another embodiment of the beamforming method of the FDD system in the embodiment of the present invention includes:
301. the user carries out channel estimation according to the downlink pilot frequency sent by the base station to obtain second channel information Hk；
In the FDD system, channel information of the base station is obtained through user (i.e., UE) feedback. In this embodiment, HkAnd representing the channel information obtained by the user k by performing channel estimation on the downlink channel, and recording the channel information as second channel information.
302. User pair HkPerforming singular value decomposition;
in this embodiment, the user pairs HkThe singular value decomposition specifically includes:
wherein,are respectively HkThe left and right singular value matrices of (a),is a matrix of singular values.
Thus, left singular vectors can be obtainedRight singular vectorAnd singular valuesWherein D iskRespectively the number of data streams for user k.
303. User right singular vectorQuantized and right singular vectorThe code word with the minimum included angle is obtained
In this embodiment, user k generates a codebookTo quantize the right singular vectorEach of which is a code wordThe constraint condition that the norm is 1 is satisfied, and the codebook generation method may be based on LTE protocol generation or random generation, which is not limited herein.
In this embodiment, each right singular vectorAre all quantified asCode word with minimum included angleNamely:
304. calculating included angle information of quantization errors by a user;
in this embodiment, the user k calculates the angle information of the quantization error in the quantization processWherein is the angle between them, i.e. the angle
305. The user feeds back the third channel information to the base station;
in this embodiment, the third channel information includes a target right singular vector, target angle information, and singular values, where the target right singular vector is the singular value in step 303Object angle information, step 304Singular values, i.e. in step 302That is, the channel information feedback amount (i.e. the third channel information) fed back by the user to the base station includes:
wherein,andmay be a passing amountThe feedback may also be directly fed back to the base station without quantization, and is not limited herein.
It should be emphasized that the third channel information in this embodiment is easier to perform channel information error statistics and avoid excessive feedback overhead, compared with directly feeding back the second channel information to the base station. However, in the prior art, if the channel information obtained by estimation is directly fed back to the base station, too much overhead is caused to the uplink channel, and generally, to reduce the overhead of the uplink channel, only a few bits are used to quantize and feed back the channel information, which causes a large error in the channel information at the base station end, whereas the channel information feedback amount designed in this embodiment is a channel information feedback amountExcessive feedback overhead can be avoided while ensuring channel information accuracy.
306. Base station determining first channel information using error modeling of channel
In this embodiment, after receiving the second channel information fed back by the user, the base station needs to perform statistics on the channel error, which may specifically include:
modeling the error of the channel:
wherein,is composed ofOne orthonormal basis of the orthogonal complement space of the subspace in which,is one in dimension NB-1 random vectors uniformly distributed on a unit sphere.
Order:
then, equation (3) can be expressed as:
wherein,representThe expected value of (c) is,representing the quantization error of the right singular vector.
Thereby, the first channel information can be obtained
As can be known from the error modeling process of the channel, the channel information feedback quantity designed in this embodiment is easier to count the channel information error at the base station.
307. The base station determines the SINR of the user according to the first channel information;
the downlink transmission signal of the base station is:
wherein,and DkThe data signal, the beamforming matrix, and the number of data streams for user k, respectively.
The signal received by user k is represented as:
yk＝Hk'x+υk(6)
wherein upsilon iskIs additive white Gaussian noise with a power ofAnd isSatisfy the requirement of
In the embodiment, the base station converts the left singular vector of the second channel informationAs a filter for a linear receiver, whereby the base station assumes that user k uses the left singular vectorTo recover its d-thkThe data streams, namely:
substituting the formula (4) and the formula (5) into the formula (7) and arranging to obtain:
the SINR is then expressed as:
wherein,indicating the expected value.
Through the process of simplification, the method has the advantages of simple process,can be expressed as:
here, comparing the formulas (8) and (8a) with the formulas (1) and (1a), if the formulas (1) and (1a) are:
then the equations (8), (8a) can be obtained, from which it can be seen that,the preset condition is satisfied.
308. When the SINR meets a preset condition, the base station determines a beam forming matrix by using a first optimization problem;
in this embodiment, when acquiring the SINR and determining that the SINR satisfies the preset condition, the base station further constructs a first optimization problem, specifically including:
where R represents the system capacity, and where, is a constant greater than 0, which represents the data stream d for user kkPriority of (2), indicating data flow d of user kkA data rate of, and
the constraint condition of the total transmission power of the system represents that the total transmission power of the system is not more than a certain preset PTWhereind denotes the k UEkA beamforming matrix for each data stream.
It can be seen that the goal of beamforming in this embodiment is to achieve a total system transmit power no greater than PTIn this case, the total data rate of the system is maximized, thereby optimizing the system capacity.
In the actual processing process, the first optimization problem (9) involves a logarithm operation and a matrix inversion operation, and the processing difficulty is high. To this end, preferably, new variables are introduced by means of a conjugate function deformationToThe expression of (2) to eliminate logarithm and matrix inversion operations specifically includes:
first, by matrix inversion lemma, willExpressed as:
introducing a first variableTo pairPerforming a conjugate function deformation of the logarithmic function to obtain:
wherein const. denotes a certain constant.
Then in formula (11)The optimal solution of (a) is:
reintroducing the second variableFor in formula (11)Performing a conjugate function deformation of a quadratic function, willAnd (3) converting into:
wherein,represents the real part (·)*Representing conjugation.
For a fixedIn the formula (13)The optimal solution of (a) is:
substituting equation (13) into the first optimization problem (9), the first optimization problem (9) can be equivalently converted into a second optimization problem, specifically:
second bestThe optimization problem (15) may be optimized by using a BCD (block coordinated reduction), and in order to avoid a water injection algorithm and reduce the computational complexity, this embodiment further optimizes the block coordinated reduction (BCD)Decomposed into the form of the product of two sub-variables, i.e.The second optimization problem can be further equivalently converted into a third optimization problem, specifically:
the third optimization problem (16) includes four sets of variables:and β, andand β, the solution of the beamforming matrix and the first sub-variables in the third optimization problem (16) has a closed solution compared to the second optimization problem (15), so that the solution of the beamforming matrix using a water-filling algorithm is not required and the complexity of the solution of the beamforming matrix can be reduced.
Wherein,the solution of (a) is:
the solution of (a) is:
the solution of sum β is:
wherein,
and β should be satisfied
To pairAnd β, determining the final beam forming matrix when a preset iteration stop condition is satisfied, wherein the preset iteration stop condition may include that the number of iterations reaches a preset value or the target value of the second optimization problem increases by less than a certain threshold value, and during practical application, the second optimization problem is further updated by alternative iterationsThe above two modes can be combined or other modes, and the details are not limited herein.
309. Performing beamforming according to the beamforming matrix;
in acquiring a target beamforming matrixThen, can be based onPerforming beamforming, particularly how to utilize hereThe beamforming is not described in detail, and those skilled in the art can obtain a corresponding processing flow according to the prior art.
Therefore, in this embodiment, it can be assumed that the filter of the linear receiver used by the user is the left singular vector of the second channel informationIn this case, the system capacity is optimized.
The beamforming method in the embodiment shown in fig. 3 is simulated using the following simulation parameters, in which the number N of base station antennas is usedB8, 4, user antenna number NU,kNumber of user data streams D2k1, the channel is a gaussian channel, and the user feedback codebook CkFor random generation, 8-bit feedback is used.
The corresponding simulation results can be seen in fig. 4 and 5. Fig. 4 shows a comparison between the spectral efficiency of the present invention and other prior art methods, where a curve a corresponds to the spectral efficiency of the present invention, a curve b corresponds to the spectral efficiency of beamforming with WMMSE (weighted minimum mean square error) in the prior art, and a curve c corresponds to the spectral efficiency of beamforming with ZF (zero-forcing) in the prior art, as can be seen from fig. 4, the method provided by the present invention can significantly improve the spectral efficiency of the system. Fig. 5 shows a convergence situation of the beamforming matrix algorithm proposed by the present invention, where the abscissa is the number of iterations and the ordinate is the objective function value (i.e. the system capacity expression in the third optimization problem) that can be achieved by the beamforming matrix obtained in each iteration, and the convergence conditions under three channel instances are respectively shown in the figure, as can be seen from fig. 5, the convergence can be achieved basically in 7 iterations.
With reference to fig. 6, a beam forming method of an FDD system in an embodiment of the present invention is described above, and a base station in an embodiment of the present invention is described below, where an embodiment of the base station in the embodiment of the present invention includes:
the base station in the embodiment of the present invention may implement the procedure in the embodiment shown in fig. 2, where the base station includes:
an obtaining unit 601, configured to obtain first channel information;
a first determining unit 602, configured to determine a signal to interference plus noise ratio SINR of the UE according to the first channel information;
a second determining unit 603, configured to determine a beamforming matrix by using a first optimization problem when the SINR satisfies a preset condition, where an objective function of the first optimization problem is a system capacity determined according to the SINR, and a constraint function of the first optimization problem is a constraint condition of a total system transmit power;
an performing unit 604, configured to perform beamforming according to the beamforming matrix.
For convenience of understanding, a specific application scenario is taken as an example below to describe the internal operation flow of the base station in this embodiment:
the acquisition unit 601 acquires first channel information; a first determining unit 602 determines a signal to interference plus noise ratio SINR of the UE according to the first channel information; when the SINR satisfies a preset condition, the second determining unit 603 determines a beamforming matrix according to a first optimization problem, where an objective function of the first optimization problem is system capacity determined according to the SINR, and a constraint function of the first optimization problem is a constraint condition of total system transmit power; the performing unit 604 performs beamforming according to the beamforming matrix.
In the technical solution provided in the embodiment of the present invention, an obtaining unit 601 of a base station first obtains first channel information, and a first determining unit 602 determines an SINR of a UE according to the first channel information; when it is determined that the SINR satisfies the preset condition, the second determining unit 603 determines a beamforming matrix by using the first optimization problem, where an objective function of the first optimization problem is the system capacity determined according to the SINR, a constraint function of the first optimization problem is a constraint condition of the total system transmit power, and then the performing unit 604 performs beamforming according to the determined beamforming matrix, so that compared with the prior art, the beamforming matrix in the embodiment of the present invention is an optimal solution determined by using the system capacity as an objective function and the constraint condition of the total system transmit power as a constraint function, and compared with a pseudo-inverse matrix in the prior art, which makes the beamforming matrix equal to a channel matrix, the beamforming matrix is optimized from the perspective of maximizing the system capacity, so that the system capacity can be optimized.
Optionally, in this embodiment, the second determining unit 603 may be specifically configured to determine the beamforming matrix by using the following first optimization problem:
wherein R represents the system capacity, andwherein,d denotes the k UEkThe priority of the individual data streams,d denotes the k UEkA data rate of a data stream, andwherein,is the d-th UE of the k-thkSINR of each data stream;
the constraint condition of the total transmission power of the system represents that the total transmission power of the system is not more than a certain preset PTWhereind denotes the k UEkA beamforming matrix for each data stream.
Optionally, in this embodiment, the second determining unit 603 may include:
a creating module 6031 for creating the first optimization problem;
a first operation module 6032 for the first optimization problemExecuting conjugate function deformation of a logarithmic function, and acquiring an optimal solution of a first variable, wherein the first variable is a newly introduced variable in the conjugate function deformation of the logarithmic function;
a second operation module 6033 for executingAfter deformation of the conjugate function of the logarithmic functionExecuting conjugate function deformation of the quadratic function to obtain a second optimization problem, and acquiring an optimal solution of a second variable, wherein the second variable is a newly introduced variable in executing conjugate function deformation of the two functions;
a first determining module 6034 for determining a beamforming matrix using the second optimization problem, the optimal solution for the first variable, and the optimal solution for the second variable.
Optionally, in this embodiment, the first determining module 6034 may include:
the operation submodule decomposes a second variable in the second optimization problem into a product of a first sub-variable and a second sub-variable to obtain a third optimization problem;
and the determining submodule is used for determining the beam forming matrix by utilizing the third optimization problem, the optimal solution of the first variable and the optimal solution of the second variable.
Now, how the base station acquires the first channel information is described in detail based on the embodiment shown in fig. 6, and referring to fig. 7 in detail, another embodiment of the base station in the embodiment of the present invention includes:
the base station in the embodiment of the present invention may implement the procedure in the embodiment shown in fig. 3, where the base station includes:
an obtaining unit 701, configured to obtain first channel information;
a first determining unit 702, configured to determine a signal to interference plus noise ratio SINR of the UE according to the first channel information;
a second determining unit 703, configured to determine a beamforming matrix by using a first optimization problem when the SINR satisfies a preset condition, where an objective function of the first optimization problem is a system capacity determined according to the SINR, and a constraint function of the first optimization problem is a constraint condition of a total system transmit power;
an performing unit 704, configured to perform beamforming according to the beamforming matrix.
In this embodiment, the first channel information may be a right singular vector of second channel information, where the second channel information is channel information obtained by performing channel estimation on a downlink channel by the UE;
the first determining unit 702 may be specifically configured to determine the SINR of the UE according to the first channel information by using the left singular vector of the second channel information as a filter of a linear receiver.
Optionally, in this embodiment, the obtaining unit 701 may include:
a receiving module 7011, configured to receive third channel information sent by the UE, where the third channel information includes a target right singular vector, target included angle information, and a singular value; the UE carries out singular value decomposition on the second channel information to obtain a left singular vector, a right singular vector and the singular value, the UE quantizes the right singular vector into a code word with the smallest included angle with the right singular vector to obtain the target right singular vector, and calculates included angle information corresponding to quantization errors in the quantization process to obtain the target included angle information;
a second determining module 7012, configured to determine the first channel information by using error modeling of a channel, where the error modeling of the channel is configured to include a corresponding relationship between the first channel information, the target right singular vector, and the target included angle information.
Optionally, in this embodiment, the second determining module 7012 may be specifically configured to obtain and determine the first channel information based on the following model:
wherein,as the information of the first channel, it is,for the target right singular vector, the right singular vector,is the information of the target included angle,is composed ofOne orthonormal basis of the orthogonal complement space of the subspace in which,is one in dimension NB-1 random vectors uniformly distributed on a unit sphere.
Optionally, in this embodiment, the second determining unit 703 may be specifically configured to determine the beamforming matrix by using the following first optimization problem:
wherein R represents the system capacity, andwherein,d denotes the k UEkThe priority of the individual data streams,d denotes the k UEkA data rate of a data stream, andwherein,is the d-th UE of the k-thkSINR of each data stream;
the constraint condition of the total transmission power of the system represents that the total transmission power of the system is not more than a certain preset PTWhereind denotes the k UEkA beamforming matrix for each data stream.
Optionally, in this embodiment, the second determining unit 703 may include:
a creating module 7031 for creating said first optimization problem
A first operation module 7032 for solving said first optimization problemExecuting conjugate function deformation of a logarithmic function, and acquiring an optimal solution of a first variable, wherein the first variable is a newly introduced variable in the conjugate function deformation of the logarithmic function;
a second operation module 7033, for transforming the conjugate function of the executed logarithm functionThe conjugate function deformation of the quadratic function is performed,obtaining a second optimization problem and obtaining an optimal solution of a second variable, wherein the second variable is a newly introduced variable in the deformation of a conjugate function of the two numbers of functions;
a first determining module 7034 is configured to determine a beamforming matrix using the second optimization problem, the optimal solution for the first variable, and the optimal solution for the second variable.
Optionally, in this embodiment, the first determining module 7034 may include:
the operation submodule decomposes a second variable in the second optimization problem into a product of a first sub-variable and a second sub-variable to obtain a third optimization problem;
and the determining submodule is used for determining the beam forming matrix by utilizing the third optimization problem, the optimal solution of the first variable and the optimal solution of the second variable.
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the several embodiments provided in the present application, it should be understood that the disclosed system, apparatus and method may be implemented in other manners. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units is only one logical division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
The above-mentioned embodiments are only used for illustrating the technical solutions of the present invention, and not for limiting the same; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (12)
1. A method of beamforming in a frequency division duplex, FDD, system, comprising:
a base station acquires first channel information;
the base station determines the signal to interference plus noise ratio (SINR) of the UE according to the first channel information; the first channel information is a right singular vector of second channel information, wherein the second channel information is channel information obtained by channel estimation of a downlink channel by the UE;
the base station determining the SINR of the UE according to the first channel information includes:
the base station takes the left singular vector of the second channel information as a filter of a linear receiver, and determines the SINR of the UE according to the first channel information;
when the SINR meets a preset condition, the base station determines a beam forming matrix by using a first optimization problem, wherein an objective function of the first optimization problem is system capacity determined according to the SINR, and a constraint function of the first optimization problem is a constraint condition of total system transmission power;
and the base station carries out beam forming according to the beam forming matrix.
2. The method for beamforming in an FDD system according to claim 1 wherein the base station determining the beamforming matrix using a first optimization problem comprises:
the base station determines a beamforming matrix using a first optimization problem:
wherein R represents the system capacity, andwherein,d denotes the k UEkThe priority of the individual data streams,d denotes the k UEkA data rate of a data stream, andwherein,is the d-th UE of the k-thkSINR of each data stream;the constraint condition of the total transmission power of the system represents that the total transmission power of the system is not more than a certain preset PTWhereind denotes the k UEkA beamforming matrix for each data stream.
3. The beamforming method for an FDD system according to claim 2, wherein the base station determines the beamforming matrix using a first optimization problem comprising:
the base station creating the first optimization problem;
the base station optimizes the first optimization problemExecuting conjugate function deformation of a logarithmic function, and acquiring an optimal solution of a first variable, wherein the first variable is a newly introduced variable in the conjugate function deformation of the logarithmic function;
the base station being deformed by the conjugate function of the implemented logarithmic functionExecuting the conjugate function deformation of the quadratic function to obtain a second optimization problem, and acquiring an optimal solution of a second variable, wherein the second variable is a newly introduced variable in the conjugate function deformation of the quadratic function;
the base station determines a beamforming matrix using the second optimization problem, the optimal solution for the first variable, and the optimal solution for the second variable.
4. The method of beamforming in an FDD system according to claim 3, wherein the base station determining a beamforming matrix using the second optimization problem, the optimal solution for the first variable and the optimal solution for the second variable comprises:
the base station decomposes a second variable in the second optimization problem into a product of a first sub-variable and a second sub-variable to obtain a third optimization problem;
and the base station determines a beam forming matrix by using the third optimization problem, the optimal solution of the first variable and the optimal solution of the second variable.
5. The beamforming method for an FDD system according to claim 1,
the base station acquiring the first channel information comprises:
the base station receives third channel information sent by the UE, wherein the third channel information comprises a target right singular vector, target included angle information and a singular value; the UE carries out singular value decomposition on the second channel information to obtain a left singular vector, a right singular vector and the singular value, the UE quantizes the right singular vector into a code word with the smallest included angle with the right singular vector to obtain the target right singular vector, and calculates included angle information corresponding to quantization errors in the quantization process to obtain the target included angle information;
the base station determines first channel information by using error modeling of a channel, wherein the error modeling of the channel is constructed by corresponding relation among the first channel information, a target right singular vector and target included angle information.
6. The method of beamforming in an FDD system according to claim 5, wherein the base station determining the first channel information using error modeling of the channel comprises:
the base station obtains and determines first channel information based on the following model:
wherein,as the information of the first channel, it is,for the target right singular vector, the right singular vector,is the information of the target included angle,is composed ofOne orthonormal basis of the orthogonal complement space of the subspace in which,is one in dimension NB-1 random vectors uniformly distributed on a unit sphere.
7. A base station, comprising:
an acquisition unit configured to acquire first channel information;
a first determining unit, configured to determine a signal to interference plus noise ratio SINR of the UE according to the first channel information; the first channel information is a right singular vector of second channel information, wherein the second channel information is channel information obtained by channel estimation of a downlink channel by the UE;
the first determining unit is specifically configured to determine, according to the first channel information, an SINR of the UE by using a left singular vector of the second channel information as a filter of a linear receiver;
a second determining unit, configured to determine a beamforming matrix by using a first optimization problem when the SINR satisfies a preset condition, where an objective function of the first optimization problem is a system capacity determined according to the SINR, and a constraint function of the first optimization problem is a constraint condition of a total system transmit power;
and the execution unit is used for carrying out beam forming according to the beam forming matrix.
8. The base station of claim 7,
the second determining unit is specifically configured to determine the beamforming matrix using the following first optimization problem:
wherein R represents the system capacity, andwherein,d denotes the k UEkThe priority of the individual data streams,d denotes the k UEkA data rate of a data stream, andwherein,is the d-th UE of the k-thkSINR of each data stream;the constraint condition of the total transmission power of the system represents that the total transmission power of the system is not more than a certain preset PTWhereind denotes the k UEkA beamforming matrix for each data stream.
9. The base station of claim 8, wherein the second determining unit comprises:
a creation module for creating the first optimization problem;
a first operation module for performing the first optimization problemExecuting conjugate function deformation of a logarithmic function, and acquiring an optimal solution of a first variable, wherein the first variable is a newly introduced variable in the conjugate function deformation of the logarithmic function;
a second operation module for transforming the conjugate function of the executed logarithm functionExecuting the conjugate function deformation of the quadratic function to obtain a second optimization problem, and acquiring an optimal solution of a second variable, wherein the second variable is a newly introduced variable in the conjugate function deformation of the quadratic function;
a first determining module for determining a beamforming matrix using the second optimization problem, the optimal solution for the first variable, and the optimal solution for the second variable.
10. The base station of claim 9, wherein the first determining module comprises:
the operation submodule decomposes a second variable in the second optimization problem into a product of a first sub-variable and a second sub-variable to obtain a third optimization problem;
and the determining submodule is used for determining the beam forming matrix by utilizing the third optimization problem, the optimal solution of the first variable and the optimal solution of the second variable.
11. The base station of claim 7, wherein the acquisition unit comprises:
a receiving module, configured to receive third channel information sent by the UE, where the third channel information includes a target right singular vector, target included angle information, and a singular value; the UE carries out singular value decomposition on the second channel information to obtain a left singular vector, a right singular vector and the singular value, the UE quantizes the right singular vector into a code word with the smallest included angle with the right singular vector to obtain the target right singular vector, and calculates included angle information corresponding to quantization errors in the quantization process to obtain the target included angle information;
and the second determining module is used for determining the first channel information by using error modeling of the channel, wherein the error modeling of the channel is constructed by a corresponding relation among the first channel information, the target right singular vector and the target included angle information.
12. The base station of claim 11,
the second determining module is specifically configured to obtain and determine the first channel information based on the following model:
wherein,as the information of the first channel, it is,for the target right singular vector, the right singular vector,is the information of the target included angle,is composed ofOne orthonormal basis of the orthogonal complement space of the subspace in which,is one in dimension NB-1 random vectors uniformly distributed on a unit sphere.
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