CN114826347A - Beam forming method, device and storage medium for wireless communication system - Google Patents
Beam forming method, device and storage medium for wireless communication system Download PDFInfo
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- H04B7/00—Radio transmission systems, i.e. using radiation field
- H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
- H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
- H04B7/0413—MIMO systems
- H04B7/0456—Selection of precoding matrices or codebooks, e.g. using matrices antenna weighting
- H04B7/046—Selection of precoding matrices or codebooks, e.g. using matrices antenna weighting taking physical layer constraints into account
- H04B7/0473—Selection of precoding matrices or codebooks, e.g. using matrices antenna weighting taking physical layer constraints into account taking constraints in layer or codeword to antenna mapping into account
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- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04B—TRANSMISSION
- H04B7/00—Radio transmission systems, i.e. using radiation field
- H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
- H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
- H04B7/06—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station
- H04B7/0613—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission
- H04B7/0615—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission of weighted versions of same signal
- H04B7/0617—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission of weighted versions of same signal for beam forming
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Abstract
The embodiment of the invention discloses a beam forming method, a device and a storage medium of a wireless communication system, belonging to the technical field of beam forming; the method comprises the steps of obtaining the beam direction of communication data; based on the beam direction, a code word of which the pointing direction corresponds to the beam direction is called from a codebook with low main lobe gain fluctuation, and the codebook with low main lobe gain fluctuation is obtained by carrying out iterative solution on iterative parameters constructed based on array parameters of a millimeter wave large-scale array; beamforming based on the codeword. Because the codebook is a codebook with low main lobe gain fluctuation, when the beam direction is deviated from the actual beam direction, the beamforming gain close to the actual beamforming gain can still be obtained, the robustness of the data link is improved, and the robustness of the wireless communication system is improved.
Description
Technical Field
The present invention relates to the field of beamforming technologies, and in particular, to a beamforming method, apparatus and storage medium for a wireless communication system.
Background
Beamforming is a combination of antenna technology and digital signal processing technology for the transmission or reception of directional signals. The beamforming technology must adopt a multi-antenna system, i.e. a wireless communication system includes a plurality of antennas to form a large-scale array, and then beamforming can be performed in the rear. The signal-to-noise ratio is improved due to the beam forming, the signal quality is improved, and the method is widely used.
However, because the number of antennas of a large-scale array is large, the calculation amount of directly estimating and obtaining a complete channel state matrix is large in the beamforming process, and therefore, an analog beamforming strategy based on a codebook is generally adopted. Specifically, some codewords pointing to a specific direction in space are preset, and all codeword sets form a codebook. And then, the incoming wave direction is estimated, and the code word pointing to the incoming wave direction is searched in the codebook, so that the complex matrix calculation is converted into the searching problem in the codebook, and the calculation complexity is reduced. Meanwhile, the direction of each code word has a certain main lobe range, namely the space coverage range of the code word main lobe. As long as the actual incoming wave direction is within the range of the main lobe of the selected codeword, higher beamforming gain can be obtained, and the robustness of the wireless communication system is ensured.
In the range of the main lobe of each codeword, the beamforming gain fluctuates, as shown in fig. 1, the ordinate is the beam gain, the maximum value of the ordinate is the maximum gain, and the direction angle range in which the beam gain is not less than the minimum main lobe gain is the main lobe range, where the maximum gain minus 3dB is the minimum main lobe gain. Assuming that the estimated incoming wave direction is 1 direction and the actual incoming wave direction is 2 direction, the beamforming gain of 1 direction is still low because the difference between the beamforming gain of 2 direction and the beamforming gain of 1 direction is large. It follows that the beamforming gain flatness of the codeword within its main lobe is particularly important. In order to maintain the main lobe gain of the codeword, i.e. the beamforming gain within the main lobe range, at a constant value and reduce the fluctuation of the main lobe gain, the prior art defines the main lobe gain in advance, and then solves the difference between the minimum actual gain and the defined main lobe gain within the main lobe range to reduce the fluctuation of the main lobe gain. However, since the main lobe gain is predefined, i.e. fixed value, and the fixed amplitude constraint of the phase shifter is a non-convex constraint, the fixed amplitude constraint of the phase shifter needs to be relaxed and then converted into a convex problem solution. The fixed main lobe gain makes the performance of the algorithm very sensitive to the set main lobe gain, which causes the robustness of the algorithm to be reduced, influences the robustness of a wireless communication data link and further reduces the robustness of a wireless communication system.
Disclosure of Invention
In view of the above, the present invention provides a beamforming method, apparatus and storage medium for a wireless communication system, so as to solve the problem of poor robustness of the wireless communication system in the prior art. To achieve one or a part of or all of the above or other objects, the present invention provides a beamforming method, apparatus and storage medium of a wireless communication system, the first aspect of the present invention:
a beamforming method of a wireless communication system, comprising:
acquiring the beam direction of communication data;
based on the beam direction, a code word of which the pointing direction corresponds to the beam direction is called from a codebook with low main lobe gain fluctuation, and the codebook with low main lobe gain fluctuation is obtained by carrying out iterative solution on iterative parameters constructed based on array parameters of a millimeter wave large-scale array;
beamforming based on the codeword.
Preferably, after acquiring the beam direction of the communication data, the method further includes:
generating a codebook with low main lobe gain fluctuation when the codebook with low main lobe gain fluctuation is not stored; the iteration parameters comprise an average gain variable, a rotation matrix variable, a first auxiliary variable and a second auxiliary variable;
the step of generating the codebook of the low mainlobe gain fluctuation includes:
acquiring the array parameters of the millimeter wave large-scale array; the array parameters comprise a code word pointing angle, a main lobe range, the number of antennas of the large-scale array and the resolution of the phase shifter;
constructing the average gain variable, the rotation matrix variable, the first auxiliary variable, and the second auxiliary variable based on the array parameters;
sequentially and iteratively solving the first auxiliary variable, the rotation matrix variable, the average gain variable and the second auxiliary variable;
and after a preset iteration condition is met, generating a code word according to an iteration result and forming the codebook with low main lobe gain fluctuation.
Preferably, the step of sequentially and iteratively solving the first auxiliary variable, the rotation matrix variable, the average gain variable, and the second auxiliary variable includes:
constructing an optimization condition using the first auxiliary variable, the rotation matrix variable, the average gain variable, and the second auxiliary variable;
and sequentially and iteratively solving the first auxiliary variable, the rotation matrix variable, the average gain variable and the second auxiliary variable in turn based on the optimization condition.
Preferably, the step of constructing an optimization condition using the first auxiliary variable, the rotation matrix variable, the average gain variable, and the second auxiliary variable comprises:
obtaining a first optimization condition KKT based on an upper wheel first auxiliary variable, an upper wheel rotation matrix variable, an upper wheel average gain variable and an upper wheel second auxiliary variable;
the step of sequentially and iteratively solving the first auxiliary variable, the rotation matrix variable, the average gain variable and the second auxiliary variable in turn based on the optimization condition comprises:
obtaining a minimum first auxiliary variable meeting a feasible domain from the first optimization condition, and assigning the minimum first auxiliary variable to the current round of first auxiliary variables;
assigning the first auxiliary variable of the upper round to the first auxiliary variable of the present round when the first auxiliary variable satisfying the feasible region is not obtained from the first optimization condition;
replacing the first auxiliary variable of the previous round in the first optimization condition with the first auxiliary variable of the current round to obtain a second optimization condition;
obtaining a rotation matrix variable of the current round based on the second optimization condition;
replacing the upper wheel rotation matrix variable in the second optimization condition with the current wheel rotation matrix variable to obtain a third optimization condition;
obtaining a minimum average gain variable from the third optimization condition, and assigning the minimum average gain variable to the current round of average gain variables;
obtaining a second auxiliary variable of the current round based on the second auxiliary variable of the upper round, the average gain variable of the current round and the rotation matrix variable of the current round, and completing iteration of the current round;
and carrying out the next round of iterative solution step when the iterative condition is not met.
Preferably, the step of obtaining the rotation matrix variable of the current round based on the second optimization condition comprises:
obtaining a minimum rotation matrix variable from the second optimization condition, and endowing the minimum rotation matrix variable to the current initial rotation matrix variable;
alternately solving a minimum sequence value and a minimum double product value according to the current initial rotation matrix variable;
and obtaining the rotation matrix variable of the current wheel after meeting the preset alternation condition.
Preferably, the step of obtaining a first optimization condition based on the first upper-wheel auxiliary variable, the upper-wheel rotation matrix variable, the upper-wheel average gain variable, and the second upper-wheel auxiliary variable includes:
obtaining a real part intermediate quantity according to the upper wheel second auxiliary variable, the upper wheel average gain variable and the upper wheel rotation matrix variable;
obtaining an imaginary part intermediate quantity according to the upper wheel second auxiliary variable, the upper wheel average gain variable and the upper wheel rotation matrix variable;
and obtaining the first optimization condition according to the first auxiliary variable of the upper wheel, the real part intermediate quantity and the imaginary part intermediate quantity.
Preferably, the optimization condition includes a step size;
after the obtaining a minimum average gain variable from the third optimization condition and assigning the minimum average gain variable to the current round of average gain variables, the method further includes:
obtaining a first step length intermediate quantity according to the current round average gain variable and the current round rotation matrix variable;
obtaining a second step length intermediate quantity according to the upper wheel average gain variable and the upper wheel rotation matrix variable;
obtaining the step length of the current round after the difference is made between the first step length intermediate quantity and the second step length intermediate quantity;
the step of judging whether the iteration condition is satisfied comprises the following steps:
and when the iteration times are equal to a preset iteration threshold or the step length of the current round is smaller than a preset step length threshold, judging that the iteration condition is met.
Preferably, the step of constructing an average gain variable, a rotation matrix variable, a first auxiliary variable and a second auxiliary variable based on the array parameters comprises:
obtaining an angle control parameter based on the codeword pointing angle;
obtaining a main lobe width control parameter based on the main lobe range, the number of antennas, and the angle control parameter;
constructing a ZC sequence according to the number of the antennas, the angle control parameters and the main lobe width control parameters;
acquiring the number of sampling points;
obtaining the average gain variable based on the number of antennas, the angle control parameter, the main lobe width control parameter, the ZC sequence and the number of sampling points;
constructing the rotation matrix variable based on a diagonal matrix model;
defining the first auxiliary variable;
and constructing the second auxiliary variable based on a Lagrangian model.
Preferably, the step of constructing an average gain variable, a rotation matrix variable, a first auxiliary variable and a second auxiliary variable based on the array parameters comprises:
obtaining an angle control parameter based on the codeword pointing angle;
obtaining a main lobe width control parameter based on the main lobe range, the number of antennas, and the angle control parameter;
constructing a ZC sequence according to the number of the antennas, the angle control parameters and the main lobe width control parameters;
acquiring the number of sampling points;
obtaining the average gain variable based on the number of antennas, the angle control parameter, the main lobe width control parameter, the ZC sequence and the number of sampling points;
constructing the rotation matrix variable based on a diagonal matrix model;
defining the first auxiliary variable;
and constructing the second auxiliary variable based on a Lagrangian model.
In a second aspect:
a beamforming apparatus of a wireless communication system comprises a memory having a beamforming method of the wireless communication system stored therein and a processor configured to employ the method when performing the beamforming method of the wireless communication system.
In a third aspect:
a storage medium stores a computer program that can be loaded by a processor and that executes the above-described method.
The embodiment of the invention has the following beneficial effects:
iterative parameters are constructed through array parameters of the millimeter wave large-scale array, and then iterative solution is carried out by utilizing the iterative parameters, so that the main lobe gain fluctuation of each code word in the codebook is reduced, and the whole codebook is called as a low-main-lobe gain fluctuation codebook. After the beam direction is obtained, the estimated beam direction. And selecting a corresponding code word in the codebook according to the beam direction, then obtaining the phase of a corresponding phase shifter according to the code word, and generating a beam with a pointing direction corresponding to the beam direction through the phase shifter and the phase to complete beam forming. Because the main lobe gain fluctuation of the code word is low, even if the beam direction is deviated from the actual beam direction, the difference between the obtained beam forming gain and the actual beam forming gain is small, and the robustness of the data link is improved, namely the robustness of the wireless communication system is improved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a graph of beamforming gain for a codeword in the prior art.
Fig. 2 is an overall flow diagram of a beamforming method of a wireless communication system in one embodiment.
Fig. 3 is a diagram illustrating beam directions in a beamforming method of a wireless communication system according to an embodiment.
Fig. 4 is a beamforming gain graph of a beamforming method of a wireless communication system in one embodiment.
Fig. 5 is an overall flowchart of a beamforming method of a wireless communication system in another embodiment.
Fig. 6 is a flow chart of generating a codebook of low mainlobe gain fluctuation in a beamforming method of a wireless communication system in one embodiment.
Fig. 7 is a flow chart of iterative parameter construction in a beamforming method of a wireless communication system in one embodiment.
Fig. 8 is a flow diagram of an iterative solution in a beamforming method of a wireless communication system in one embodiment.
Fig. 9 is a graph comparing the main lobe gain fluctuation of the codeword in the prior art and the main lobe gain fluctuation of the codeword in the present embodiment.
FIG. 10 is a graph comparing the main lobe gain fluctuation of codewords generated after iterative solution of different rounds in one embodiment.
Fig. 11 is a block diagram of a beamforming system of a wireless communication system in one embodiment.
Detailed Description
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.
Referring to fig. 2, in an embodiment, a beamforming method of a wireless communication system includes:
s100, acquiring the beam direction of the communication data.
Communication data refers to data transmitted using electromagnetic waves as carriers. In an application scene, the communication system is a large-scale array communication system, and the electromagnetic waves are millimeter waves; the beam direction refers to an incoming wave direction or a transmitting direction of a beam containing communication data; for easy understanding, referring to fig. 3, in the present application scenario, the communication system includes 256 antennas, each antenna corresponds to one phase shifter, the codebook is a set of codewords, and each codeword corresponds to one phase shifter. The beam direction may be obtained after being estimated by a technician, an estimation device, an estimation algorithm, or a combination thereof.
Referring to fig. 2, based on the beam direction, a codeword having a pointing direction corresponding to the beam direction is retrieved from a codebook having low mainlobe gain fluctuation S200.
The codebook with low main lobe gain fluctuation is obtained by carrying out iterative solution on iterative parameters constructed on the basis of array parameters of the millimeter wave large-scale array.
Each codeword has a main lobe direction and a main lobe range, for example, in an application scenario, the main lobe direction of the codeword is 15 °, and the main lobe range is 7.5 ° to 24.5 °. The pointing direction in step S200 refers to the main lobe range, that is, it is determined whether the pointing direction of the codeword corresponds to the beam direction, and it is sufficient to determine whether the beam direction is located within the main lobe range of the codeword; if the beam direction is within the range of the main lobe of the code word, the corresponding judgment is carried out; otherwise, the judgment is non-corresponding.
Thus, for each codeword in the codebook, the main lobe direction and the main lobe range are fixed. After the beam direction is known, the code word corresponding to the pointing direction can be selected. Even if the beam direction is deviated from the actual beam direction, because the main lobe range is a range value, as long as the actual beam direction is within the main lobe range of the selected codeword, a higher beamforming gain can still be obtained, and the beamforming flexibility is improved.
In addition, because the codebook is based on iterative solution, the amplitude of the main lobe gain fluctuation is reduced. Therefore, when deviation exists between the beam direction and the actual beam direction, the difference between the estimated beam forming gain and the actual beam forming gain is reduced under the influence of low main lobe gain fluctuation, and the robustness of the millimeter wave large-scale array system is improved. Specifically, comparing the main lobe gain curves in fig. 1 and 4, when the actual beam direction is the 1 direction and the estimated beam direction is the 2 direction, since the beamforming gain fluctuation in fig. 4 is small, the difference between the beamforming gain of the estimated beam direction and the beamforming gain of the actual beam direction is smaller, and thus a more stable beamforming gain can be obtained.
Referring to fig. 2, beamforming is performed based on the codeword S300.
Because the corresponding code word is selected, the phase of the corresponding phase shifter is changed according to the code word, and the beam corresponding to the beam direction can be obtained, namely the beam forming is completed.
In another embodiment, referring to fig. 5, after S100, step T200 is performed.
And T200, judging whether a codebook with low mainlobe gain fluctuation is stored.
Namely, whether a codebook with low main lobe gain fluctuation is stored in the storage space or under the designated storage path is judged. If yes, executing step S200; if not, go to step T300.
After step T300, steps S200 and S300 are performed in order.
And T300, generating a codebook with low main lobe gain fluctuation.
The codebook with low main lobe gain fluctuation is actively generated, so that the difference between the obtained beamforming gain and the actual beamforming gain is smaller during beamforming, and the robustness of a wireless communication system is improved.
Specifically, referring to fig. 6, in an embodiment, step T300 includes:
and T310, acquiring array parameters of the millimeter wave large-scale array.
In one embodiment, the array parameters include the codeword pointing angle, the main lobe range, the number of antennas for the large scale array, and the resolution of the phase shifters. The code word pointing angle and the main lobe range are preset values, and in an application scene, the space pointing direction of the code word is usually considered within the range of 0-90 degrees, namely the code word pointing angle; and divides this range into a coverage of an integer number of codewords, i.e. the range of the main lobe of the codeword. For ease of understanding, for example, in one codebook, the codeword pointing angles are set to 15 °, 30 °, 45 °, 60 °, and 75 °, respectively, and the main lobe range is 15 °.
Since the wireless communication system has already been constructed, the number of antennas and the resolution of the phase shifters in a large-scale array are known values. For easy understanding, in an application scenario, the number of antennas is 256; the resolution of the phase shifter is 2 to the power of 5.
And T320, constructing an average gain variable, a rotation matrix variable, a first auxiliary variable and a second auxiliary variable based on the array parameters.
That is, in one embodiment, the iteration parameters include an average gain variable, a rotation matrix variable, a first auxiliary variable, and a second auxiliary variable. For ease of understanding and description, in the present embodiment, the average gain variable is denoted by c; the rotation matrix variable is denoted by A; the first auxiliary variable is denoted by v; the second auxiliary variable is denoted by lambda. And the rotation matrix variable A and the second auxiliary variable lambda are vectors.
Specifically, referring to fig. 7, in an embodiment, step T320 includes:
and T321, obtaining an angle control parameter based on the code word pointing angle.
Wherein the angle control parameter is denoted by b. In an application scenario, by psi b ＝sin -1 b obtaining angle control parameterA number b; wherein psi b Pointing the angle for the codeword. At psi b Is larger than {15 degrees, 30 degrees, 45 degrees, 60 degrees and 75 degrees }, the angle control parameter b is larger than {0.259,0.5,0.707,0.866 and 0.966 }.
And T322, obtaining a main lobe width control parameter based on the main lobe range, the number of the antennas and the angle control parameter.
Wherein the main lobe width control parameter is denoted by u. In an application scenario, by
Obtaining a main lobe width control parameter u; wherein, the first and the second end of the pipe are connected with each other,
is the main lobe range; b is an angle control parameter; u is a main lobe width control parameter; nt is the number of antennas. Setting the angle control parameter b to 0.259, main lobe range
The main lobe width control parameter u can be obtained by setting the number of antennas Nt to 256 to 0.131.
And T323, constructing a ZC sequence according to the number of the antennas, the angle control parameters and the main lobe width control parameters.
Wherein, the ZC sequence refers to a Zadoff-Chu sequence. ZC sequences are denoted by p; substituting the antenna number Nt, the angle control parameter b and the main lobe width control parameter u into p to obtain a formula
Where n represents the nth meaning, and the maximum value of n is equal to the number of antennas Nt. In an application scenario, since the number of antennas Nt is 256, the maximum value of n is 256, ranging from 1 to 256; j is an imaginary unit; when the number of antennas Nt is 256, 256 p can be obtained, and a group of ZC sequences is obtained; where p is a vector.
T324, acquiring the number of sampling points.
The number of spots is represented by R. In one embodiment, theThe number of points is calculated by
Calculating to obtain; wherein R is PS The resolution of the phase shifter. With R PS ＝2 5 For example, the number of spots is determined to be 490. It should be noted that the number R of sampling points may also be 500, which is specifically determined according to the calculation amount that can be carried, that is, the larger the value of R is, the higher the calculation accuracy is, but the larger the calculation amount is. Therefore, within the acceptable calculation amount range, rounding and reduction can be carried out on the basis of the calculation result.
In another embodiment, the number R of sampling points is a predetermined value, such as 300, 500, 700. When the number of the sampling points needs to be acquired, the sampling points are called down to a preset storage path.
And T325, obtaining an average gain variable based on the number of antennas, the angle control parameter, the main lobe width control parameter, the ZC sequence and the number of sampling points.
In one embodiment, the average gain variable c is based on the formula
And (6) calculating. Wherein g (p, ψ) is a gain function with respect to p; psi r Is a discretized angle. In particular, the gain function with respect to p
Discretized angle
a (psi) is a guide vector, having
H is matrix conjugate transpose; t is matrix transposition.
And T326, constructing a rotation matrix variable based on the diagonal matrix model.
Wherein, the diagonal array model is diag function, and the rotation matrix variable
Need to make sure thatIt is noted that in an application scenario, phi 1 To
Is 0, the initial value of the rotation matrix variable a is also 0.
T327, define the first auxiliary variable.
The first auxiliary variable v represents the current average gain, i.e. the actual average gain. By iteratively calculating the first auxiliary variable, the main lobe gain fluctuation of the codeword is reduced.
And T328, constructing a second auxiliary variable based on the Lagrangian model.
Lagrange model, i.e. lagrange formula, in particular, the second auxiliary variable λ ═ λ 1 ,λ 2 ,…,λ R ] T 。
By constructing the average gain variable c, the first auxiliary variable v and the second auxiliary variable lambda, the average gain variable c, the first auxiliary variable v and the second auxiliary variable lambda can be continuously updated during iterative solution, and main lobe gain fluctuation in a main lobe range is not solved and optimized according to the fixed average gain variable c, so that the main lobe gain fluctuation is reduced conveniently, and the robustness of a data link is improved.
It should be noted that steps T321-T323 need to be executed in sequence, T324 may be executed at any node, and after the execution ends T323 and T324, T325 is executed. T326, T327, and T328 have no order of execution requirements for each other, nor for each step from the others.
Referring to fig. 6, T330, the first auxiliary variable, the rotation matrix variable, the average gain variable, and the second auxiliary variable are iteratively solved in sequence.
Through iterative solution, an optimal result is obtained, instead of optimizing the main lobe gain fluctuation by using a fixed value, and the robustness of the wireless communication system is improved.
Specifically, in an embodiment, step T330 includes:
and T331, constructing an optimization condition by using the first auxiliary variable, the rotation matrix variable, the average gain variable and the second auxiliary variable.
In an application scenario, the optimized condition is a KKT (Karush-Kuhn-Tucker) condition. Specifically, KKT condition
Wherein Re represents a real part; im represents the imaginary part; rho is the step length; gA, ψ r are gain functions relating to A, calculated in a manner corresponding to gain function g (p, ψ r) relating to p r ) The same is true. And (4) obtaining the code word with low main lobe gain fluctuation by iteratively and alternately optimizing the four variables of c, A, v and lambda.
Specifically, the method for constructing the optimization condition is as follows: and obtaining a first optimization condition based on the first upper-wheel auxiliary variable, the upper-wheel rotation matrix variable, the upper-wheel average gain variable and the upper-wheel second auxiliary variable.
Namely, the real part intermediate quantity is obtained according to the upper-wheel second auxiliary variable, the upper-wheel average gain variable and the upper-wheel rotation matrix variable.
Wherein, the middle quantity of the real part is
And obtaining an imaginary part intermediate quantity according to the second auxiliary variable of the upper wheel, the average gain variable of the upper wheel and the rotation matrix variable of the upper wheel.
Wherein the imaginary intermediate quantity refers to
And obtaining a first optimization condition according to the first auxiliary variable, the real part intermediate quantity and the imaginary part intermediate quantity of the upper wheel.
It should be noted that the optimization condition L (c, a, v, λ) is also updated with the updating of the average gain variable c, the rotation matrix variable a, the first auxiliary variable v, and the second auxiliary variable λ. After one round of iterative solution is completed, the obtained iterative solution result is brought into the optimization condition L (c, A, ν, λ) to obtain a first optimization condition for application in the next round of iterative solution. That is, the first optimization condition refers to an optimization condition obtained after a round of iterative solution is completed and an iterative solution result is brought into the optimization condition L (c, a, v, λ). For example, after the first round of iterative solution is completed, the average gain variable c, the rotation matrix variable a, the first auxiliary variable v and the second auxiliary variable λ obtained in the first round are substituted into the optimization condition L (c, a, v, λ) formula to obtain a first optimization condition used in the second round of iterative solution; if the first round of iterative solution does not start, the initial value of the average gain variable c, namely the value obtained in the step T325, is brought into the formula with the optimization condition L (c, A, ν, λ); and (3) bringing the initial value of the rotation matrix variable A, the initial value of the first auxiliary variable v and the initial value of the second auxiliary variable lambda into an optimization condition L (c, A, v, lambda) formula to obtain a first optimization condition. Wherein the initial value of the rotation matrix variable a, the initial value of the first auxiliary variable v and the initial value of the second auxiliary variable λ are all 0. I.e. how many iterations of the solution are performed, how many first optimization conditions are generated.
And T332, sequentially and iteratively solving the first auxiliary variable, the rotation matrix variable, the average gain variable and the second auxiliary variable according to turns based on the optimization conditions.
Specifically, referring to fig. 8, step T332 includes:
and T3321, obtaining the minimum first auxiliary variable meeting the feasible region from the first optimization condition, and assigning the minimum first auxiliary variable to the first auxiliary variable of the current round.
In an application scenario, the updating formula of the first auxiliary variable v (t +1) in the current round is as follows:
wherein the content of the first and second substances,
is a feasible field. That is, the minimum first auxiliary variable is obtained from the first optimization condition, so that the minimum first auxiliary variable satisfies the feasible region.
Note that t represents the number of rounds of iterative solution, and the initial value of t is 0. That is, when t is 0, it represents the first round of iterative solution, when t is 2, it represents the second round of iterative solution, and so on. When t is 0, c (0) represents the initial value of c, and other variables are the same, and are not described again.
T3322, when the first auxiliary variable satisfying the feasible region is not obtained from the first optimization condition, assigning the first auxiliary variable of the previous round to the first auxiliary variable of the present round.
In an application scene, after the steps of T3321 and T3322 are integrated, the following relation is obtained:
wherein the content of the first and second substances,
the result is calculated when the feasible domain is satisfied; if the feasible region is not satisfied, v (t +1) v (t) is given. For convenience of understanding, for example, in the first round of iterative solution, if none of the minimum first auxiliary variables found in the first optimization condition satisfies the feasible region, the first auxiliary variable of this round is made equal to the initial value of the first auxiliary variable.
And T3323, replacing the first auxiliary variable of the previous round in the first optimization condition with the first auxiliary variable of the current round to obtain a second optimization condition.
And the first auxiliary variable v of the current round, the rotation matrix variable of the upper round, the average gain variable of the upper round and the second auxiliary variable of the upper round are brought into an optimization condition L (c, A, v, lambda) formula to obtain a second optimization condition. Namely, the other three variables are unchanged, so that the first auxiliary variable of the current round replaces the first auxiliary variable of the previous round. The formula of the optimization condition L (c, a, v, λ) refers to an optimization condition obtained by calculation using initial values of four variables, and may be the same as or different from the first optimization condition. And when the first optimization conditions are the same, the first optimization conditions are the same only when the first round of iteration starts, and the first optimization conditions obtained by the second round of iteration solution and the later round of iteration solution are possibly different.
Specifically, the second optimization condition is L (c (t), a (t), v (t +1), λ (t)); namely that
And T3324, obtaining the rotation matrix variable of the current round based on the second optimization condition.
In an application scenario, step T3324 includes:
and obtaining the minimum rotation matrix variable from the second optimization condition, and endowing the minimum rotation matrix variable to the current initial rotation matrix variable.
That is, the smallest rotation matrix variable a is found from the second optimization condition, and the value is assigned to the current initial rotation matrix variable. Specifically, by A (t +1) ═ argmin A L (c (t), A (t), v (t +1) and lambda (t)) obtain the minimum rotation matrix variable, and then the current initial rotation matrix variable is obtained.
And alternately solving a minimum sequence value and a minimum double product value according to the current initial rotation matrix variable.
In an application scenario, the minimum sequence value is according to formula X:
solving, the minimum double product value is according to formula Y:
and (6) obtaining. Wherein, B ═ a (psi) 1 ),…,a(ψ R )]；
p A pA; denotes conjugation; as indicates a Hadamard product (Hadamard product);
represents Kronecker Product (Kronecker Product); the initial value of Z is zero.
The alternative solution means that the current initial rotation matrix variable is brought into the formula X to obtain a first value of A; substituting the first value of A into formula Y to obtain a second value of A; then the second value of A is brought into the formula X to obtain a third value of A; the value of a is continuously updated between formula X and formula Y with this rule. Since both formula X and formula Y belong to the convex problem, the solution can be directly solved.
And obtaining the rotation matrix variable of the current wheel after meeting the preset alternation condition.
In an application scenario, the alternation condition is that the number of alternations is not more than 5. That is, after the equations X and Y are calculated five times, it is determined that the alternation condition is satisfied, and the rotation matrix variable a (t +1) of the present round is obtained.
On one hand, the rotation matrix variable A is subjected to alternate solution in each iteration solution process, so that the calculation precision of the rotation matrix variable A in each iteration solution process is improved, and the main lobe gain fluctuation is reduced conveniently; on the other hand, in the alternative solving process, the used formula X and the formula Y are both convex problems and can be directly solved, so that the rotation matrix variable does not need to be optimized and calculated through relaxing constraint, and the stability of the codeword main lobe forming gain is improved.
Referring to fig. 8, T3325, the upper round rotation matrix variable in the second optimization condition is replaced by the present round rotation matrix variable to obtain a third optimization condition.
Specifically, the third optimization condition is L (c (t), a (t +1), v (t +1), λ (t)); namely, it is
And T3326, obtaining the minimum average gain variable from the third optimization condition, and endowing the minimum average gain variable to the average gain variable of the current round.
I.e. find the smallest average gain variable c from the third optimization conditions and assign this value to the current round of average gain variables. Specifically, c (t +1) ═ argmin c And L (c (t), A (t +1), v (t +1) and lambda (t)) obtain the minimum average gain variable, namely the average gain variable of the current round.
And T3327, obtaining a second auxiliary variable of the current round based on the second auxiliary variable of the previous round, the average gain variable of the current round and the rotation matrix variable of the current round, and finishing the iteration of the current round.
In particular, by real part formula
Obtaining a real part of a second auxiliary variable of the current round; by imaginary part formula
Obtaining an imaginary part of a second auxiliary variable of the current round; and then integrating to obtain a second auxiliary variable of the round.
And T3328, performing the next iteration solving step when the iteration condition is met.
I.e. when the iteration condition is not met, the steps T3321-T3327 are repeated again. It is noted that the value of T is incremented by one before repeating steps T3321-T3327.
Through iterative solution, the average gain variable c and the first auxiliary variable v are continuously solved, so that the actual average gain is closer to the calculated large average gain, the stable main lobe gain fluctuation is conveniently obtained, and the robustness of the wireless communication system is improved.
In another embodiment, after the step T3326, before ending the current iteration, the method further includes:
k3001, obtaining the first step length intermediate quantity according to the average gain variable of the current round and the rotation matrix variable of the current round.
In particular, in an application scenario, the first step is in the middleAmount ═ c (t +1) -g (A (t +1), ψ r )。
K3001, obtaining the second step length intermediate quantity according to the upper wheel average gain variable and the upper wheel rotation matrix variable.
In an application scenario, the second step length intermediate amount is c (t) -g (a (t), ψ r )。
K3003, obtaining the step length of the current round by subtracting the intermediate quantity of the first step length from the intermediate quantity of the second step length.
Namely, in each iteration solving process, the step length is updated and solved simultaneously. The optimization condition comprises the characteristic of step length, the step length is updated, the quality of updating the optimization condition more times is improved conveniently, therefore, the code word with lower main lobe gain fluctuation is obtained, and the robustness of a wireless system is improved.
Referring to fig. 6, T340, after a preset iteration condition is satisfied, generating a codeword according to an iteration result and forming a codebook with low main lobe gain fluctuation.
After each round of iterative solution is completed, judging whether an iterative condition is met, if so, generating a code word and forming a codebook with low main lobe gain fluctuation; otherwise, continuing the next round of iterative solution.
In an embodiment, the iteration condition includes whether the iteration number is equal to a preset iteration threshold and whether the current round step size is smaller than a preset step size threshold.
If the iteration times are equal to the iteration threshold, or the step length of the current round is smaller than the step length threshold, judging that the iteration condition is met; otherwise, it is determined to be not satisfied. The iteration times are the iteration rounds, and when each iteration is completed, the iteration times are increased by one. The iteration threshold is established according to the bearing capacity of the calculated amount, and in the embodiment, the iteration threshold is set to be 5, that is, five rounds of iteration solution are performed for more. In other embodiments, the iteration threshold may be 10, 20, or 100.
Step size threshold is set to
I.e. in step size
And judging that the step length of the current round is smaller than a step length threshold value. For example, when the number of antennas Nt is 256, the step threshold is
After the iterative solution is finished, calling the result of the rotation matrix variable A obtained in the last round, and obtaining a code word from f (b) p (T) A (T); wherein, f (b) is a code word, b is an angle control parameter, p is a ZC sequence, A is a rotation matrix variable obtained in the last round, and T is the number of rounds of iterative solution.
It should be noted that, in an embodiment, after the obtained codeword is learned by d, a codeword f (b + d) pointing to the b + d direction can be obtained. For example, when b is 0, a codeword pointing to 0 ° is obtained, and d ∈ {0.5,0.707,0.866,0.966}, a codeword pointing to {30 °, 45 °, 60 °, 75 ° } can be obtained.
In addition, by using the code words of which the iteration times do not reach the iteration threshold, the generated beam broadening can be counteracted when part of the antennas cannot work due to faults, so that the beam forming is closer to the expected value. Specifically, for example, in a large-scale array with 256 antennas, if a general antenna is turned off due to a breakdown, the main lobe range is widened from a design value of 15 ° to 30 °. If a codeword of T-3 is used, the main lobe range can be narrowed to about 22 °, canceling out the partial beam broadening, and bringing the main lobe range closer to the design value.
The implementation principle of the beam forming method of the wireless communication system in this embodiment is as follows: when the codebook with low mainlobe gain fluctuation is stored, the corresponding code word is directly called from the codebook with low mainlobe gain fluctuation according to the beam direction, and then the phase of the corresponding phase shifter in the wireless communication system is changed according to the called code word, thereby forming the beam and completing the analog beam forming. The low main lobe gain fluctuation is obtained by iterative solution of iterative parameters constructed based on array parameters of the millimeter wave large-scale array, and the iterative parameters are continuously updated through the iterative solution, so that parameter values closer to actual iterative parameters can be obtained when each iteration is finished, the main lobe gain fluctuation is reduced, the robustness of a data link is improved, and the robustness of a wireless communication system is improved. For ease of understanding, referring to fig. 9, the stability of the beam gain obtained without using the iterative solution is inferior to the beam gain obtained using the iterative solution; referring to fig. 10, the beam gain subjected to the multiple iterative solutions is more stable than the beam gain subjected to the relatively fewer iterative solutions.
Referring to fig. 11, an embodiment of the present application further discloses a beam forming system of a wireless communication system, including an obtaining module 1, configured to obtain a beam direction of communication data; the code word module 2 is configured to, based on the beam direction, retrieve a code word whose pointing direction corresponds to the beam direction from a codebook with low main lobe gain fluctuation, where the codebook with low main lobe gain fluctuation is obtained by performing iterative solution based on an iterative parameter constructed by an array parameter of a millimeter wave large-scale array; and a beamforming module 3, configured to perform beamforming based on the codeword.
In addition, when the codebook with low main lobe gain fluctuation is not stored, the system further comprises a codebook module for generating the codebook with low main lobe gain fluctuation.
Specifically, the codebook module includes a parameter unit, configured to obtain the array parameter of the millimeter wave large-scale array; the array parameters comprise a code word pointing angle, a main lobe range, the number of antennas of the large-scale array and the resolution of the phase shifter; a construction unit for constructing the average gain variable, the rotation matrix variable, the first auxiliary variable and the second auxiliary variable based on the array parameters; the iteration unit is used for sequentially iterating and solving the first auxiliary variable, the rotation matrix variable, the average gain variable and the second auxiliary variable; and the output unit is used for generating a code word according to an iteration result and forming the low-mainlobe gain fluctuation codebook after a preset iteration condition is met.
In an embodiment, the constructing unit includes an obtaining subunit, configured to obtain an angle control parameter based on the codeword pointing angle; further configured to obtain a main lobe width control parameter based on the main lobe range, the number of antennas, and the angle control parameter; and is also used for acquiring the number of sampling points. A construction subunit, configured to construct a ZC sequence according to the number of antennas, the angle control parameter, and the main lobe width control parameter; the number of antennas, the angle control parameter, the main lobe width control parameter, the ZC sequence and the number of sampling points are used for obtaining the average gain variable; and is further configured to construct the rotation matrix variable based on a diagonal matrix model, define the first auxiliary variable, and construct the second auxiliary variable based on a lagrangian model.
In an embodiment, the iteration unit comprises an optimization condition subunit for constructing an optimization condition using the first auxiliary variable, the rotation matrix variable, the average gain variable and the second auxiliary variable; and the iteration subunit is used for sequentially iterating and solving the first auxiliary variable, the rotation matrix variable, the average gain variable and the second auxiliary variable according to turns based on the optimization condition.
And the optimization condition subunit is used for constructing an optimization condition by using the first auxiliary variable, the rotation matrix variable, the average gain variable and the second auxiliary variable, and is realized by adopting a mode of obtaining the first optimization condition based on the first auxiliary variable of the previous round, the rotation matrix variable of the previous round, the average gain variable of the previous round and the second auxiliary variable of the previous round. Specifically, the optimization condition subunit includes a real part intermediate quantum unit, and is configured to obtain a real part intermediate quantity according to the second auxiliary variable of the upper wheel, the average gain variable of the upper wheel, and the rotation matrix variable of the upper wheel; the imaginary part intermediate quantum unit is used for obtaining an imaginary part intermediate quantity according to the upper wheel second auxiliary variable, the upper wheel average gain variable and the upper wheel rotation matrix variable; and the integration subunit is used for obtaining the first optimization condition according to the first auxiliary variable of the upper round, the real part intermediate quantity and the imaginary part intermediate quantity.
In an embodiment, the iteration subunit includes a first subunit, configured to obtain a minimum first auxiliary variable that satisfies a feasible domain from the first optimization condition, and assign the minimum first auxiliary variable to the current round of first auxiliary variables; a second subunit, configured to assign the first auxiliary variable of the previous round to the first auxiliary variable of the current round when the first auxiliary variable satisfying the feasible region is not obtained from the first optimization condition; the third subunit is configured to replace the first auxiliary variable in the first optimization condition with the first auxiliary variable in the current round to obtain a second optimization condition; the fourth subunit is used for obtaining a rotation matrix variable of the current round based on the second optimization condition; a fifth subunit, configured to replace the upper-wheel rotation matrix variable in the second optimization condition with the current-wheel rotation matrix variable to obtain a third optimization condition; a sixth subunit, configured to obtain a minimum average gain variable from the third optimization condition, and assign the minimum average gain variable to the current round of average gain variables; a seventh subunit, configured to obtain a second auxiliary variable of the current round based on the second auxiliary variable of the previous round, the average gain variable of the current round, and the rotation matrix variable of the current round, and complete iteration of the current round; and an eighth subunit, configured to start a next round of iterative solution step when the iteration condition is not satisfied.
The fourth subunit comprises an initial value subunit, configured to obtain a minimum rotation matrix variable from the second optimization condition, and assign the minimum rotation matrix variable to the current initial rotation matrix variable; the alternating subunit is used for alternately solving a minimum sequence value and a minimum double product value according to the current initial rotation matrix variable; and the terminator unit is used for obtaining the rotation matrix variable of the current round after meeting the preset alternation condition.
The iteration subunit further comprises a ninth subunit, configured to, after the sixth subunit operates, obtain a first step length intermediate quantity according to the current round average gain variable and the current round rotation matrix variable, obtain a second step length intermediate quantity according to an upper round average gain variable and the upper round rotation matrix variable, and finally obtain a current round step length by subtracting the first step length intermediate quantity from the second step length intermediate quantity.
In an embodiment, the output unit includes a judging subunit, and when the iteration number is equal to a preset iteration threshold or the current round step length is smaller than a preset step length threshold; and if so, judging that the iteration condition is met.
It is to be noted here that: the above description of the beam forming system embodiment applied to the wireless communication system is similar to the above description of the method, and has the same advantageous effects as the method embodiment. For technical details not disclosed in the beamforming system embodiment of the wireless communication system of the present invention, those skilled in the art should understand with reference to the description of the method embodiment of the present invention.
It should be noted that, in the embodiment of the present invention, if the method is implemented in the form of a software functional module and sold or used as a standalone product, it may also be stored in a computer readable storage medium. Based on such understanding, the technical solutions of the embodiments of the present invention may be essentially implemented or a part contributing to the prior art may be embodied in the form of a software product, which is stored in a storage medium and includes several 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 methods described in the embodiments of the present invention. And the aforementioned storage medium includes: various media capable of storing program codes, such as a usb disk, a removable hard disk, a Read Only Memory (ROM), a magnetic disk, or an optical disk. Thus, embodiments of the invention are not limited to any specific combination of hardware and software.
Correspondingly, the embodiment of the application also discloses a storage medium which stores a computer program capable of being loaded by a processor and executing the method.
The embodiment of the application also discloses a beam forming device of the wireless communication system, which comprises a memory and a processor, wherein the memory stores the beam forming method of the wireless communication system; the processor is configured to employ the above-described method in performing a beamforming method of a wireless communication system.
The above description of the beam forming apparatus and storage medium embodiments applied to the wireless communication system is similar to the description of the above method embodiments, with similar advantageous effects as the method embodiments. For technical details not disclosed in the embodiments of the beam forming apparatus and the storage medium of the wireless communication system of the present invention, reference is made to the description of the embodiments of the method of the present invention for understanding.
It should be appreciated that reference throughout this specification to "one embodiment" or "an embodiment" means that a particular feature, structure or characteristic described in connection with the embodiment is included in at least one embodiment of the present invention. Thus, the appearances of the phrases "in one embodiment" or "in an embodiment" in various places throughout this specification are not necessarily all referring to the same embodiment. Furthermore, the particular features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. It should be understood that, in various embodiments of the present invention, the sequence numbers of the above-mentioned processes do not mean the execution sequence, and the execution sequence of each process should be determined by its function and inherent logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention. The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments.
In the embodiments provided in the present invention, it should be understood that the disclosed apparatus and method may be implemented in other ways. The above-described device embodiments are merely illustrative, for example, the division of the unit is only a logical functional division, and there may be other division ways in actual implementation, such as: multiple units or components may be combined, or may be integrated into another system, or some features may be omitted, or not implemented. In addition, the coupling, direct coupling or communication connection between the components shown or discussed may be through some interfaces, and the indirect coupling or communication connection between the devices or units may be electrical, mechanical or other forms.
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; can be located in one place or 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, all functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may be separately used as one unit, or two or more units may be integrated into one unit; the integrated unit can be realized in a form of hardware, or in a form of hardware plus a software functional unit.
Those of ordinary skill in the art will understand that: all or part of the steps for realizing the method embodiments can be completed by hardware related to program instructions, the program can be stored in a computer readable storage medium, and the program executes the steps comprising the method embodiments when executed; and the aforementioned storage medium includes: a removable storage device, a ROM, a magnetic or optical disk, or other various media that can store program code.
Alternatively, the integrated unit of the present invention may be stored in a computer-readable storage medium if it is implemented in the form of a software functional module and sold or used as a separate product. Based on such understanding, the technical solutions of the embodiments 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 device to perform all or part of the methods according to the embodiments of the present invention. And the aforementioned storage medium includes: a removable storage device, a ROM, a magnetic or optical disk, or other various media that can store program code.
The above disclosure is only for the purpose of illustrating the preferred embodiments of the present invention, and it is therefore to be understood that the invention is not limited by the scope of the appended claims.
Claims (10)
1. A method of beamforming in a wireless communication system, comprising:
acquiring the beam direction of communication data;
based on the beam direction, a code word of which the pointing direction corresponds to the beam direction is called from a codebook with low main lobe gain fluctuation, and the codebook with low main lobe gain fluctuation is obtained by carrying out iterative solution on iterative parameters constructed based on array parameters of a millimeter wave large-scale array;
beamforming based on the codeword.
2. The beamforming method of a wireless communication system according to claim 1, further comprising, after acquiring the beam direction of the communication data:
generating a codebook with low main lobe gain fluctuation when the codebook with low main lobe gain fluctuation is not stored; the iteration parameters comprise an average gain variable, a rotation matrix variable, a first auxiliary variable and a second auxiliary variable;
the step of generating the codebook of the low mainlobe gain fluctuation includes:
acquiring the array parameters of the millimeter wave large-scale array; the array parameters comprise a code word pointing angle, a main lobe range, the number of antennas of the large-scale array and the resolution of the phase shifter;
constructing the average gain variable, the rotation matrix variable, the first auxiliary variable, and the second auxiliary variable based on the array parameters;
sequentially and iteratively solving the first auxiliary variable, the rotation matrix variable, the average gain variable and the second auxiliary variable;
and after a preset iteration condition is met, generating a code word according to an iteration result and forming the codebook with low main lobe gain fluctuation.
3. The beamforming method of claim 2, wherein the step of iteratively solving for the first auxiliary variable, the rotation matrix variable, the average gain variable, and the second auxiliary variable in sequence comprises:
constructing an optimization condition using the first auxiliary variable, the rotation matrix variable, the average gain variable, and the second auxiliary variable;
and sequentially and iteratively solving the first auxiliary variable, the rotation matrix variable, the average gain variable and the second auxiliary variable in turn based on the optimization condition.
4. The beamforming method of claim 3, wherein the step of constructing an optimization condition using the first auxiliary variable, the rotation matrix variable, the average gain variable, and the second auxiliary variable comprises:
obtaining a first optimization condition based on the first upper wheel auxiliary variable, the upper wheel rotation matrix variable, the upper wheel average gain variable and the upper wheel second auxiliary variable;
the step of sequentially and iteratively solving the first auxiliary variable, the rotation matrix variable, the average gain variable and the second auxiliary variable in turn based on the optimization condition comprises:
obtaining a minimum first auxiliary variable meeting a feasible domain from the first optimization condition, and assigning the minimum first auxiliary variable to the current round of first auxiliary variables;
assigning the first auxiliary variable of the upper round to the first auxiliary variable of the present round when the first auxiliary variable satisfying the feasible region is not obtained from the first optimization condition;
replacing the first auxiliary variable of the previous round in the first optimization condition with the first auxiliary variable of the current round to obtain a second optimization condition;
obtaining a rotation matrix variable of the current round based on the second optimization condition;
replacing the upper wheel rotation matrix variable in the second optimization condition with the current wheel rotation matrix variable to obtain a third optimization condition;
obtaining a minimum average gain variable from the third optimization condition, and assigning the minimum average gain variable to the current round of average gain variables;
obtaining a second auxiliary variable of the current round based on the second auxiliary variable of the upper round, the average gain variable of the current round and the rotation matrix variable of the current round, and completing iteration of the current round;
and carrying out the next round of iterative solution step when the iterative condition is not met.
5. The beamforming method of claim 4, wherein the step of obtaining the rotation matrix variable of the current round based on the second optimization condition comprises:
obtaining a minimum rotation matrix variable from the second optimization condition, and endowing the minimum rotation matrix variable to the current initial rotation matrix variable;
alternately solving a minimum sequence value and a minimum double product value according to the current initial rotation matrix variable;
and obtaining the rotation matrix variable of the current wheel after meeting the preset alternation condition.
6. The method for beamforming in a wireless communication system according to claim 4, wherein the step of deriving the first optimization condition based on an upper-round first auxiliary variable, an upper-round rotation matrix variable, an upper-round average gain variable, and an upper-round second auxiliary variable comprises:
obtaining a real part intermediate quantity according to the upper wheel second auxiliary variable, the upper wheel average gain variable and the upper wheel rotation matrix variable;
obtaining an imaginary part intermediate quantity according to the upper wheel second auxiliary variable, the upper wheel average gain variable and the upper wheel rotation matrix variable;
and obtaining the first optimization condition according to the first auxiliary variable of the upper wheel, the real part intermediate quantity and the imaginary part intermediate quantity.
7. The beamforming method for a wireless communication system according to claim 4, wherein the optimization condition comprises a step size;
after the obtaining a minimum average gain variable from the third optimization condition and assigning the minimum average gain variable to the current round of average gain variables, the method further includes:
obtaining a first step length intermediate quantity according to the current round average gain variable and the current round rotation matrix variable;
obtaining a second step length intermediate quantity according to the upper wheel average gain variable and the upper wheel rotation matrix variable;
obtaining the step length of the current round after the difference is made between the first step length intermediate quantity and the second step length intermediate quantity;
the step of judging whether the iteration condition is satisfied comprises the following steps:
and when the iteration times are equal to a preset iteration threshold or the step length of the current round is smaller than a preset step length threshold, judging that the iteration condition is met.
8. The method of beamforming in a wireless communication system according to claim 2 wherein the step of constructing an average gain variable, a rotation matrix variable, a first auxiliary variable and a second auxiliary variable based on the array parameters comprises:
obtaining an angle control parameter based on the codeword pointing angle;
obtaining a main lobe width control parameter based on the main lobe range, the number of antennas, and the angle control parameter;
constructing a ZC sequence according to the number of the antennas, the angle control parameters and the main lobe width control parameters;
acquiring the number of sampling points;
obtaining the average gain variable based on the number of antennas, the angle control parameter, the main lobe width control parameter, the ZC sequence and the number of sampling points;
constructing the rotation matrix variable based on a diagonal matrix model;
defining the first auxiliary variable;
and constructing the second auxiliary variable based on a Lagrangian model.
9. A beamforming apparatus of a wireless communication system, comprising a memory and a processor, wherein the memory stores a beamforming method of the wireless communication system, and the processor is configured to employ any of the methods of claims 1-8 when executing the beamforming method of the wireless communication system.
10. A storage medium, characterized in that a computer program is stored which can be loaded by a processor and which executes the method according to any of claims 1-8.
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