CN106685501A - Beamforming method and beamforming device - Google Patents

Beamforming method and beamforming device Download PDF

Info

Publication number
CN106685501A
CN106685501A CN201510746940.XA CN201510746940A CN106685501A CN 106685501 A CN106685501 A CN 106685501A CN 201510746940 A CN201510746940 A CN 201510746940A CN 106685501 A CN106685501 A CN 106685501A
Authority
CN
China
Prior art keywords
feature vector
dimension
vector
feature
eigenvalue
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Granted
Application number
CN201510746940.XA
Other languages
Chinese (zh)
Other versions
CN106685501B (en
Inventor
李传军
苏昕
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
China Academy of Telecommunications Technology CATT
Datang Mobile Communications Equipment Co Ltd
Original Assignee
China Academy of Telecommunications Technology CATT
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by China Academy of Telecommunications Technology CATT filed Critical China Academy of Telecommunications Technology CATT
Priority to CN201510746940.XA priority Critical patent/CN106685501B/en
Priority to PCT/CN2017/070124 priority patent/WO2017076371A1/en
Publication of CN106685501A publication Critical patent/CN106685501A/en
Application granted granted Critical
Publication of CN106685501B publication Critical patent/CN106685501B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Classifications

    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L1/00—Arrangements for detecting or preventing errors in the information received
    • H04L1/02—Arrangements for detecting or preventing errors in the information received by diversity reception
    • H04L1/06—Arrangements for detecting or preventing errors in the information received by diversity reception using space diversity
    • H—ELECTRICITY
    • 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
    • H—ELECTRICITY
    • 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
    • H04B7/08—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the receiving station
    • H04B7/0837—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the receiving station using pre-detection combining
    • H04B7/0842—Weighted combining
    • H04B7/086—Weighted combining using weights depending on external parameters, e.g. direction of arrival [DOA], predetermined weights or beamforming

Landscapes

  • Engineering & Computer Science (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Radio Transmission System (AREA)
  • Mobile Radio Communication Systems (AREA)

Abstract

The invention provides a beamforming method and a beamforming device. The beamforming method comprises the steps of acquiring a channel matrix of an uplink channel of a detecting reference signal which is transmitted from user equipment; respectively acquiring a first-dimensional characteristic vector and a second-dimensional characteristic vector of the channel matrix; determining a three-dimensional characteristic vector according to the first-dimensional characteristic vector and the second-dimensional characteristic vector; and performing beamforming according to the three-dimensional characteristic vector. According to the beamforming method and the beamforming device, through vertical-dimensional characteristic decomposition and horizontal-dimensional characteristic decomposition, a beamforming vector which comprises complete three-dimensional channel information is acquired, thereby realizing more accurate 3D beam transmission and furthermore reducing characteristic decomposition complexity of large-dimension channel related matrixes.

Description

A kind of method and device of wave beam forming
Technical field
The present invention relates to communication technical field, more particularly to a kind of method and device of wave beam forming.
Background technology
In view of Multiple Input Multiple Output (MIMO technology) is for raising peak rate and system spectrum utilization rate Important function, LTE (Long Term Evolution, Long Term Evolution)/LTE-A (LTE-Advanced, LTE Evolution) etc. wireless access technology standard be all with MIMO+OFDM (Orthogonal Frequency Division Multiplexing, OFDM) construct based on technology.MIMO technology Performance gain can be obtained spatial degrees of freedom from multiaerial system, and the utilization space free degree obtains bigger Data transfer.Therefore a most important evolution tendency of the MIMO technology in standardisation process is dimension The extension of degree.
In order to further lift MIMO technology, extensive antenna technology is introduced in GSM.For The extensive antenna of total digitalization has up to 128,256,512 antenna oscillators, and up to 128,256, 512 transceivers, each antenna oscillator connects a transceiver, with up to 128,256,512 Digital antenna port.Up to 128 are made full use of, the spatial degrees of freedom of 256,512 digital antenna ports. Base station is caused to make full use of up to 128 in wave beam forming, corresponding to 256,512 digital antenna ports Spatial channel information.For TDD pattern, then need to be measured up to using uplink SRS signal Spatial channel information corresponding to 128,256,512 digital antenna ports, and Eigenvalues Decomposition is carried out, with Obtain the figuration vector of wave beam forming.But it is up to 128x128, the association side of 256x256,512x512 dimension The complexity of the feature decomposition of difference matrix is high.
At present for extensive antenna, in the method for the utilization feature decomposition of base station side wave beam forming is calculated Method, the method for generally carrying out feature decomposition using overall three dimensions channel, the method can obtain Whole channel eigenvectors, this complete channel eigenvectors not only include the possible multithread of vertical direction, Include the possible multithread of horizontal direction, but the complexity of eigendecomposition that the method is brought is excessive, Base station is difficult to complete when code is realized.
The content of the invention
It is an object of the invention to provide a kind of method and device of wave beam forming, solves profit in prior art The complexity for calculating the eigendecomposition that wave beam forming brings with the method for feature decomposition is excessive, and base station is in generation Code is difficult to the problem for completing when realizing.
In order to achieve the above object, the embodiment of the present invention provides a kind of method of wave beam forming, including：
Obtain the channel matrix of the up channel of user equipment emission detection reference signal；
First dimensional feature vector and the second dimensional feature vector of the channel matrix are obtained respectively；
According to first dimensional feature vector and the second dimensional feature vector, three-dimensional feature vector is determined；
Wave beam forming is carried out according to the three-dimensional feature vector.
Wherein, the step of channel matrix of the up channel for obtaining user equipment emission detection reference signal Including：
The detection reference signal that receive user equipment is sent by the up channel：
According to the detection reference signal, the channel matrix of the up channel is obtained.
Wherein, first dimensional feature vector that the channel matrix is obtained respectively and the second dimensional feature vector Step includes：
Obtain the first eigenvector and second feature vector of the first dimension of the channel matrix；
It is vectorial according to the first eigenvector and the second feature, the third feature vector of the dimension of acquisition second, Fourth feature vector, fifth feature vector and sixth feature vector.
Wherein, it is described according to first dimensional feature vector and the second dimensional feature vector, determine three-dimensional feature to The step of amount, includes：
The corresponding third feature value of the comparison third feature vector, the corresponding fourth feature of fourth feature vector Value, the corresponding fifth feature value of fifth feature vector and the corresponding sixth feature value of sixth feature vector, really The eigenvalue of maximum of fixed second dimension and the secondary eigenvalue of maximum of the second dimension；
According to described second dimension eigenvalue of maximum and it is described second dimension secondary eigenvalue of maximum, it is determined that with it is described The first object characteristic vector of corresponding first dimension of eigenvalue of maximum of the second dimension, with the described second dimension time most The second target feature vector that big characteristic value corresponding first is tieed up is corresponding with the eigenvalue of maximum of the described second dimension Second dimension the 3rd target feature vector and with described second dimension secondary eigenvalue of maximum it is corresponding second tie up The 4th target feature vector；
According to the 3rd target feature vector and the first object characteristic vector, the first three-dimensional feature is determined Vector；
According to the 4th target feature vector and second target feature vector, the second three-dimensional feature is determined Vector.
Wherein, it is described to include the step of carry out wave beam forming according to the three-dimensional feature vector：
According to first three-dimensional feature vector, single current wave beam forming is carried out；Or
The second three-dimensional feature vector, carries out dual-stream beamforming according to the first three-dimensional feature vector sum.
Wherein, the first eigenvector of first dimension for obtaining the channel matrix and second feature vector Step includes：
Obtain the first dimension correlation matrix of the channel matrix；
To described first dimension correlation matrix carry out Eigenvalues Decomposition, obtain first eigenvector and second feature to Amount, and the First Eigenvalue corresponding with the first eigenvector and corresponding with the second feature vector Second Eigenvalue；Wherein, the First Eigenvalue is the eigenvalue of maximum of the first dimension, the Second Eigenvalue For the secondary eigenvalue of maximum of the first dimension.
Wherein, it is described according to the first eigenvector and second feature vector, obtain the of the second dimension The step of three characteristic vectors, fourth feature vector, fifth feature vector and sixth feature vector includes：
According to the first eigenvector, the first equivalent channel matrix of the second dimension is built；
According to second feature vector, the second equivalent channel matrix of the second dimension is built；
Obtain the first correlation matrix of the first equivalent channel matrix of second dimension and the of second dimension Second correlation matrix of two equivalent channel matrix；
Eigenvalues Decomposition is carried out to first correlation matrix, third feature vector sum fourth feature vector is obtained, And with the third feature corresponding third feature value of vector and with fourth feature vector the corresponding 4th Characteristic value；Wherein, the third feature value is the eigenvalue of maximum of the first equivalent channel matrix of the second dimension, The fourth feature value is the secondary eigenvalue of maximum of the first equivalent channel matrix of the second dimension；
Eigenvalues Decomposition is carried out to second correlation matrix, fifth feature vector sum sixth feature vector is obtained, And with the fifth feature corresponding fifth feature value of vector and with sixth feature vector the corresponding 6th Characteristic value；Wherein, the fifth feature value is the eigenvalue of maximum of the second equivalent channel matrix of the second dimension, The sixth feature value is the secondary eigenvalue of maximum of the second equivalent channel matrix of the second dimension.
The embodiment of the present invention also provides a kind of device of wave beam forming, it is characterised in that include：
Matrix acquisition module, for obtaining the channel square of the up channel of user equipment emission detection reference signal Battle array；
Vectorial acquisition module, for obtaining first dimensional feature vector and the second Wei Te of the channel matrix respectively Levy vector；
Determining module, for according to first dimensional feature vector and the second dimensional feature vector, it is determined that three-dimensional special Levy vector；
Figuration module, for carrying out wave beam forming according to the three-dimensional feature vector.
Wherein, the matrix acquisition module includes：
First matrix acquisition submodule, is joined for receive user equipment by the detection that the up channel sends Examine signal：
Second matrix acquisition submodule, for according to the detection reference signal, obtaining the up channel Channel matrix.
Wherein, the vectorial acquisition module includes：
Primary vector acquisition submodule, for obtain the channel matrix first dimension first eigenvector and Second feature vector；
Secondary vector acquisition submodule, for according to the first eigenvector and the second feature vector, Obtain third feature vector, fourth feature vector, fifth feature vector and the sixth feature vector of the second dimension.
Wherein, the determining module includes：
First determination sub-module, for the corresponding third feature value of relatively more described third feature vector, the 4th special Levy vectorial corresponding fourth feature value, the corresponding fifth feature value of fifth feature vector and sixth feature vector Corresponding sixth feature value, determines the eigenvalue of maximum of the second dimension and the secondary eigenvalue of maximum of the second dimension；
Second determination sub-module, for according to the eigenvalue of maximum of the described second dimension and second dimension time most Big characteristic value, it is determined that the first object characteristic vector of the first dimension corresponding with the eigenvalue of maximum of the described second dimension, Second target feature vector and described second of the first dimension corresponding with the secondary eigenvalue of maximum of the described second dimension 3rd target feature vector and time maximum with the described second dimension of corresponding second dimension of eigenvalue of maximum of dimension 4th target feature vector of corresponding second dimension of characteristic value；
3rd determination sub-module, for according to the 3rd target feature vector and the first object feature to Amount, determines the first three-dimensional feature vector；
4th determination sub-module, for according to the 4th target feature vector and second target signature to Amount, determines the second three-dimensional feature vector.
Wherein, the figuration module includes：
First figuration submodule, for according to first three-dimensional feature vector, carrying out single current wave beam forming； Or
Second figuration submodule, for the second three-dimensional feature according to the first three-dimensional feature vector sum to Amount, carries out dual-stream beamforming.
Wherein, the primary vector acquisition submodule includes：
First acquisition unit, for obtaining the first dimension correlation matrix of the channel matrix；
First resolving cell, for carrying out Eigenvalues Decomposition to the described first dimension correlation matrix, obtains first special Levy vector sum second feature vector, and the First Eigenvalue corresponding with the first eigenvector and with it is described The corresponding Second Eigenvalue of second feature vector；Wherein, the First Eigenvalue is the maximum feature of the first dimension Value, the Second Eigenvalue is the secondary eigenvalue of maximum of the first dimension.
Wherein, the secondary vector acquisition submodule includes：
First construction unit, for according to the first eigenvector, building the first equivalent channel of the second dimension Matrix；
Second construction unit, for according to second feature vector, building the second equivalent channel of the second dimension Matrix；
Second acquisition unit, for obtaining the first correlation matrix of the first equivalent channel matrix of second dimension And the second correlation matrix of the second equivalent channel matrix of second dimension；
Second resolving cell, for carrying out Eigenvalues Decomposition to first correlation matrix, obtains third feature Vector sum fourth feature vector, and with the third feature corresponding third feature value of vector and with described the The corresponding fourth feature value of four characteristic vectors；Wherein, the third feature value is the first equivalent letter of the second dimension The eigenvalue of maximum of road matrix, the fourth feature value is time maximum of the first equivalent channel matrix of the second dimension Characteristic value；
3rd resolving cell, for carrying out Eigenvalues Decomposition to second correlation matrix, obtains fifth feature Vector sum sixth feature vector, and with the fifth feature corresponding fifth feature value of vector and with described the The corresponding sixth feature value of six characteristic vectors；Wherein, the fifth feature value is the second equivalent letter of the second dimension The eigenvalue of maximum of road matrix, the sixth feature value is time maximum of the second equivalent channel matrix of the second dimension Characteristic value.
The embodiment of the present invention also provides a kind of device of wave beam forming, including：Processor；And by bus The memory that interface is connected with the processor, the memory is performing behaviour for storing the processor The program used when making and data, when processor call and perform the program that stored in the memory and During data, following functional module is realized：
Matrix acquisition module, for obtaining the channel square of the up channel of user equipment emission detection reference signal Battle array；
Vectorial acquisition module, for obtaining first dimensional feature vector and the second Wei Te of the channel matrix respectively Levy vector；
Determining module, for according to first dimensional feature vector and the second dimensional feature vector, it is determined that three-dimensional special Levy vector；
Figuration module, for carrying out wave beam forming according to the three-dimensional feature vector.
The above-mentioned technical proposal of the present invention at least has the advantages that：
In the method and device of the wave beam forming of the embodiment of the present invention, the two-stage tieed up by vertical dimension and level is special Decomposition is levied, acquisition includes the wave beam forming vector of Complete three-dimensional channel information, realizes that more accurate 3D wave beams are passed It is defeated；The complexity of the feature decomposition of big dimensional channel correlation matrix is solved simultaneously.
Description of the drawings
Fig. 1 represents the basic flow sheet of the method for the wave beam forming that the first embodiment of the present invention is provided；
Fig. 2 represents the structural representation of the device of the wave beam forming that the second embodiment of the present invention is provided.
Specific embodiment
To make the technical problem to be solved in the present invention, technical scheme and advantage clearer, below in conjunction with attached Figure and specific embodiment are described in detail.
First embodiment
As shown in figure 1, the first embodiment of the present invention provides a kind of method of wave beam forming, including：
Step 11, obtains the channel matrix of the up channel of user equipment emission detection reference signal；
Step 12, obtains respectively first dimensional feature vector and the second dimensional feature vector of the channel matrix；
Step 13, according to first dimensional feature vector and the second dimensional feature vector, determines three-dimensional feature vector；
Step 14, according to the three-dimensional feature vector wave beam forming is carried out.
In the above embodiment of the present invention, above-mentioned up channel is user equipment (UE) emission detection reference signal The channel of (SRS signal), then can be calculated the channel square of the up channel by above-mentioned SRS signal Battle array.The complexity for directly carrying out feature decomposition to the channel matrix is larger, is difficult to realize, therefore the of the present invention In one embodiment channel matrix is analyzed from two dimensions, obtains the first dimensional feature vector and the second Wei Te Vector is levied, so as to the first dimensional feature vector and the second dimensional feature vector carry out feature decomposition respectively, two is realized Level feature decomposition, reduces the difficulty of feature decomposition；And then three-dimensional feature vector is obtained, this three is characterized vector It is to include ensureing the wave beam forming vector of three dimensional channel information, carries out finally according to the three-dimensional feature vector for obtaining Wave beam forming, realizes more accurate 3D multi-beam transmissions.
It should be noted that in the embodiment of the present invention, the first dimension is that vertical dimension or level are tieed up, accordingly, the Two dimension is level dimension or vertical dimension.It is below vertical with the first dimension for clearer description present context Straight dimension, the second dimension is specifically described for level dimension.But for the first dimension is level dimension, the second dimension is The scene of vertical dimension still falls within the protection domain of the application.
Simultaneously because being analyzed to channel matrix in terms of horizontal peacekeeping vertical dimension two so that the wave beam forming Method not only tie up angle spread using level, be possible with vertical dimension angle spread, flexible self adaptation, Further solve the not enough complete 3D figurations transmission of angle of coverage scope of all antenna ports of vertical direction Problem.
Specifically, step 11 includes in the first embodiment of the present invention：
Step 111, the detection reference signal that receive user equipment is sent by the up channel：
Step 112, according to the detection reference signal, obtains the channel matrix of the up channel.
User equipment (UE) transmitting SRS signal (detection reference signal), base station sends according to the SRS signal The channel matrix of the up channel of the SRS signal.Assume that base station receives KSRSThe P of individual userSRSIndividual antenna end The SRS signal that mouth is launched, by SRS signal K is calculatedSRS(kSRS=0 ..., KSRS- 1) individual user PSRS(pSRS=0 ..., PSRS- 1) the of individual SRS portsBase on individual subcarrier Station antenna up channelIt is a NV×NHMatrix.Wherein, NVThe extensive antenna of correspondence is hanging down Nogata to NVOK, NHThe extensive antenna of correspondence N in the horizontal directionHRow, NRBIt is the RB in system bandwidth (resource block, Resource Block) number,It is the sub-carrier number in a Resource Block RB.
Further, step 12 includes in the first embodiment of the present invention：
Step 121, obtains the first eigenvector and second feature vector of the first dimension of the channel matrix；
Step 122, according to the first eigenvector and second feature vector, obtains the 3rd of the second dimension the Characteristic vector, fourth feature vector, fifth feature vector and sixth feature vector.
And step 121 includes：
Step 1211, obtains the first dimension correlation matrix of the channel matrix；
Step 1212, to described first dimension correlation matrix carry out Eigenvalues Decomposition, obtain first eigenvector and Second feature vector, and the First Eigenvalue corresponding with the first eigenvector and with the second feature The corresponding Second Eigenvalue of vector；Wherein, the First Eigenvalue is the eigenvalue of maximum of the first dimension, described Second Eigenvalue is the secondary eigenvalue of maximum of the first dimension.
It should be noted that in the embodiment of the present invention, the first dimension is that vertical dimension or level are tieed up, accordingly, the Two dimension is level dimension or vertical dimension.It is below vertical with the first dimension for clearer description present context Straight dimension, the second dimension is specifically described for level dimension.But for the first dimension is level dimension, the second dimension is The scene of vertical dimension still falls within the protection domain of the application, and repeat specification is no longer carried out below.
Specifically, in step 1211, the tool of the first dimension (the such as first dimension is vertical dimension) correlation matrix is obtained Body step is：
Vertical dimension correlation matrix is calculated, is qBfB(qBfB=0,1 ..., QBfB- 1) figuration block calculates vertical dimension phase Close matrix.Wherein, by system bandwidthIndividual subcarrier is divided into QBfBIndividual figuration block (BfB), each tax Have in shape blockIndividual subcarrier, each figuration block subcarrier is adoptedIndividual sampling subcarrier calculates vertical Dimension correlation matrix, then sample at intervals ofAt this moment subcarrier number n and qBfB (qBfB=0,1 ..., QBfB- 1) in individual figuration blockRelation table between individual sampling subcarrier It is shown as：
So as to calculate kthSRSIndividual user qBfBThe vertical dimension correlation matrix of figuration block：
Wherein,
It is NV× 1 dimension matrix
qBfB=0,1 ..., QBfB-1
Preferably, carry out Eigenvalues Decomposition to vertical dimension correlation matrix in step 1212 concretely comprising the following steps：
Calculate vertical dimensional feature vector：Carry out EVD decompositionObtain calculating kthSRSThe of individual user qBfBThe main characteristic vector of two vertical dimensions of individual figuration block, i.e. first eigenvectorWith second feature vectorAnd corresponding two characteristic values, i.e. the First EigenvalueAnd Second EigenvalueWherein One characteristic valueAnd Second EigenvalueMaximum and time maximum two characteristic values are corresponded to respectively；Then first Characteristic vectorWith second feature vectorIt is maximum and time maximum two characteristic valuesWith Corresponding characteristic vector.Wherein,WithIt is respectively NV× 1 matrix.
On the basis of step 121 obtains first eigenvector and second feature vector, the first of the present invention is real Applying step 122 in example includes：
Step 1221, according to the first eigenvector, builds the first equivalent channel matrix of the second dimension；
Step 1222, according to second feature vector, builds the second equivalent channel matrix of the second dimension；
Form 2 levels and tie up equivalent channel, calculate kthSRSIndividual user qBfBIn figuration blockIndividual sampling The level dimension equivalent channel of subcarrierWithWherein,WithIt is respectively a 1 × NHSquare Battle array.
And first equivalent channel matrix：
Second equivalent channel matrix：
Wherein,
qBfB=0,1 ..., QBfB-1
Step 1223, obtains first correlation matrix of the first equivalent channel matrix of second dimension and described Second correlation matrix of the second equivalent channel matrix of the second dimension；
The correlation matrix that two levels tie up equivalent channel is calculated respectively.Calculate kthSRSIndividual user qBfBFiguration block First level equivalent channel and the second horizontal equivalent channel correlation matrix：
Then the first correlation matrix：
Second correlation matrix：
Wherein,
It is 1 × NHDimension matrix
It is 1 × NHDimension matrix
qBfB=0,1 ..., QBfB-1
Step 1224, to first correlation matrix Eigenvalues Decomposition is carried out, and obtains third feature vector sum Four characteristic vectors, and with the third feature corresponding third feature value of vector and with the fourth feature to Measure corresponding fourth feature value；Wherein, the third feature value is the first equivalent channel matrix of the second dimension Eigenvalue of maximum, the fourth feature value is the secondary eigenvalue of maximum of the first equivalent channel matrix of the second dimension；
Step 1225, to second correlation matrix Eigenvalues Decomposition is carried out, and obtains fifth feature vector sum Six characteristic vectors, and with the fifth feature corresponding fifth feature value of vector and with the sixth feature to Measure corresponding sixth feature value；Wherein, the fifth feature value is the second equivalent channel matrix of the second dimension Eigenvalue of maximum, the sixth feature value is the secondary eigenvalue of maximum of the second equivalent channel matrix of the second dimension.
That is calculated level dimensional feature vector：Carry out EVD point to the first correlation matrix and the second correlation matrix respectively Solution, carries out EVD decompositionWith
It is rightFeature decomposition is carried out, obtains calculating kthSRSThe q of individual userBfBTwo of individual figuration block The main characteristic vector of vertical dimension is third feature vectorWith fourth feature vectorAnd corresponding two Characteristic value, third feature valueWith fourth feature valueWherein third feature valueIt is special with the 4th Value indicativeMaximum and time maximum two characteristic values are corresponded to respectively.Then third feature is vectorialWith the 4th Characteristic vectorIt is maximum and time maximum two characteristic valuesWithCorresponding characteristic vector. Wherein, third feature vectorWith fourth feature vectorIt is respectively NH× 1 matrix.
It is rightFeature decomposition is carried out, obtains calculating kthSRSThe q of individual userBfBTwo of individual figuration block The main characteristic vector of vertical dimension is fifth feature vectorWith sixth feature vectorAnd corresponding two Individual characteristic value, fifth feature valueWith sixth feature valueWherein fifth feature valueWith the 6th Characteristic valueMaximum and time maximum two characteristic values are corresponded to respectively.Fifth feature vectorWith the 6th Characteristic vectorIt is maximum and time maximum two characteristic valuesWithCorresponding characteristic vector. Wherein, fifth feature vectorWith sixth feature vectorIt is respectively NH× 1 matrix.
Further, in the first embodiment of the present invention determine first eigenvector to sixth feature vector after, Step 13 includes：
Step 131, the corresponding third feature value of the comparison third feature vector, fourth feature vector are corresponding Fourth feature value, the fifth feature corresponding fifth feature value of vector and sixth feature vector are corresponding 6th special Value indicative, determines the eigenvalue of maximum of the second dimension and the secondary eigenvalue of maximum of the second dimension；
Step 132, according to described second dimension eigenvalue of maximum and it is described second dimension secondary eigenvalue of maximum, really The first object characteristic vector of fixed the first dimension corresponding with the eigenvalue of maximum of the described second dimension, with described second Second target feature vector of corresponding first dimension of secondary eigenvalue of maximum of dimension and the maximum of second dimension are special Value indicative it is corresponding second dimension the 3rd target feature vector and with described second dimension secondary eigenvalue of maximum it is corresponding Second dimension the 4th target feature vector；
Step 133, according to the 3rd target feature vector and the first object characteristic vector, determines first Three-dimensional feature vector；
Step 134, according to the 4th target feature vector and second target feature vector, determines second Three-dimensional feature vector.
That is the purpose of step 13 is maximum and time maximum the two figuration characteristic vectors of search, so that it is determined that three-dimensional Characteristic vector.Specifically, compareWithFind wherein maximum and secondary big The numbering of two characteristic values of maximum and time maximum corresponding to characteristic valueWithWherein,WithAccording to the numbering of maximum and time maximum two characteristic valuesWithCan obtain calculating kthSRSIndividual user qBfBTwo levels of figuration block tie up main feature Vector is first object characteristic vectorWith the second target feature vectorAnd pass throughWithFind its target feature vector of vertical dimensional feature vector the 3rdWith the 4th target feature vector Two levels are tieed up into main characteristic vector dimensional feature vector synthesis three-dimensional feature vector vertical with two respectively.
Wherein(Kronecker product) is accumulated for Kronecker,WithIt is respectively NV×NHSquare Battle array.
Further, its step 14 after three-dimensional feature vector is obtained in the first embodiment of the present invention to be included：
Step 141, according to first three-dimensional feature vector, carries out single current wave beam forming；Or
Step 142, the second three-dimensional feature vector, carries out double fluid according to the first three-dimensional feature vector sum Wave beam forming.
By kthSRSIndividual user qBfBTwo three-dimensional feature vectors of figuration blockWithFor wave beam tax Shape, if single current is then usedIf double fluid is then usedWithInclude altogether SU-MIMO (Single User MIMO) and MU-MIMO (multiuser MIMO).
If SU-MIMO single currents, then useWave beam forming is carried out, is made if single user double fluid WithWithCarry out wave beam forming,
If MU-MIMO, then adoptWithFluxion pairing is carried out, is chosen and successfully match institute Corresponding characteristic vector carries out MU-MIMO wave beam formings.Fluxion matching method can adopt ZF methods.
To sum up, in the method for wave beam forming provided in an embodiment of the present invention, by two-stage feature decomposition, solve The complexity of the feature decomposition of big dimensional channel correlation matrix, obtains including Complete three-dimensional channel information Wave beam forming vector；Simultaneously because being analyzed to channel matrix in terms of horizontal peacekeeping vertical dimension two so that The method of the wave beam forming not only ties up angle spread using level, is possible with vertical dimension angle spread, spirit Self adaptation living, the not enough complete 3D of angle of coverage scope for further solving all antenna ports of vertical direction is assigned The problem of shape transmission, realizes more accurate 3D multi-beam transmissions.
In order to preferably realize above-mentioned purpose, as shown in Fig. 2 the second embodiment of the present invention provides a kind of ripple The device of beam figuration, including：
Matrix acquisition module 21, for obtaining the channel of the up channel of user equipment emission detection reference signal Matrix；
Vectorial acquisition module 22, for obtaining first dimensional feature vector and the second dimension of the channel matrix respectively Characteristic vector；
Determining module 23, for according to first dimensional feature vector and the second dimensional feature vector, it is determined that three-dimensional Characteristic vector；
Figuration module 24, for carrying out wave beam forming according to the three-dimensional feature vector.
Specifically, in the second embodiment of the present invention, the matrix acquisition module 21 includes：
First matrix acquisition submodule, is joined for receive user equipment by the detection that the up channel sends Examine signal：
Second matrix acquisition submodule, for according to the detection reference signal, obtaining the up channel Channel matrix.
Specifically, in the second embodiment of the present invention, the vectorial acquisition module 22 includes：
Primary vector acquisition submodule, for obtain the channel matrix titanizing tie up first eigenvector and Second feature vector；
Secondary vector acquisition submodule, for according to the first eigenvector and the second feature vector, Obtain third feature vector, fourth feature vector, fifth feature vector and the sixth feature vector of the second dimension.
Specifically, in the second embodiment of the present invention, the determining module 23 includes：
First determination sub-module, for the corresponding third feature value of relatively more described third feature vector, the 4th special Levy vectorial corresponding fourth feature value, the corresponding fifth feature value of fifth feature vector and sixth feature vector Corresponding sixth feature value, determines the eigenvalue of maximum of the second dimension and the secondary eigenvalue of maximum of the second dimension；
Second determination sub-module, for according to the eigenvalue of maximum of the described second dimension and second dimension time most Big characteristic value, it is determined that the first object characteristic vector of the first dimension corresponding with the eigenvalue of maximum of the described second dimension, Second target feature vector and described second of the first dimension corresponding with the secondary eigenvalue of maximum of the described second dimension 3rd target feature vector and time maximum with the described second dimension of corresponding second dimension of eigenvalue of maximum of dimension 4th target feature vector of corresponding second dimension of characteristic value；
3rd determination sub-module, for according to the 3rd target feature vector and the first object feature to Amount, determines the first three-dimensional feature vector；
4th determination sub-module, for according to the 4th target feature vector and second target signature to Amount, determines the second three-dimensional feature vector.
Specifically, in the second embodiment of the present invention, the figuration module 24 includes：
First figuration submodule, for according to first three-dimensional feature vector, carrying out single current wave beam forming； Or
Second figuration submodule, for the second three-dimensional feature according to the first three-dimensional feature vector sum to Amount, carries out dual-stream beamforming.
Specifically, in the second embodiment of the present invention, the primary vector acquisition submodule includes：
First acquisition unit, for obtaining the first dimension correlation matrix of the channel matrix；
First resolving cell, for carrying out Eigenvalues Decomposition to the described first dimension correlation matrix, obtains first special Levy vector sum second feature vector, and the First Eigenvalue corresponding with the first eigenvector and with it is described The corresponding Second Eigenvalue of second feature vector；Wherein, the First Eigenvalue is the maximum feature of the first dimension Value, the Second Eigenvalue is the secondary eigenvalue of maximum of the first dimension.
Specifically, in the second embodiment of the present invention, the secondary vector acquisition submodule includes：
First construction unit, for according to the first eigenvector, building the first equivalent channel of the second dimension Matrix；
Second construction unit, for according to second feature vector, building the second equivalent channel of the second dimension Matrix；
Second acquisition unit, for obtaining the first correlation matrix of the first equivalent channel matrix of second dimension And the second correlation matrix of the second equivalent channel matrix of second dimension；
Second resolving cell, for carrying out Eigenvalues Decomposition to first correlation matrix, obtains third feature Vector sum fourth feature vector, and with the third feature corresponding third feature value of vector and with described the The corresponding fourth feature value of four characteristic vectors；Wherein, the third feature value is the first equivalent letter of the second dimension The eigenvalue of maximum of road matrix, the fourth feature value is time maximum of the first equivalent channel matrix of the second dimension Characteristic value；
3rd resolving cell, for carrying out Eigenvalues Decomposition to second correlation matrix, obtains fifth feature Vector sum sixth feature vector, and with the fifth feature corresponding fifth feature value of vector and with described the The corresponding sixth feature value of six characteristic vectors；Wherein, the fifth feature value is the second equivalent letter of the second dimension The eigenvalue of maximum of road matrix, the sixth feature value is time maximum of the second equivalent channel matrix of the second dimension Characteristic value.
It should be noted that the device of the wave beam forming of second embodiment of the invention offer is using above-mentioned wave beam The device of the method for figuration, then all embodiments of the method for above-mentioned wave beam forming be applied to the device, and Same or analogous beneficial effect can be reached.
In order to preferably realize above-mentioned purpose, the third embodiment of the present invention also provides a kind of dress of wave beam forming Put, it is characterised in that include：Processor；And by EBI and depositing that the processor is connected Reservoir, the memory is used to store program and the data that the processor is used when operation is performed, when When processor is called and performs the program and data that are stored in the memory, following functional module is realized：
Matrix acquisition module, for obtaining the channel square of the up channel of user equipment emission detection reference signal Battle array；
Vectorial acquisition module, for obtaining first dimensional feature vector and the second Wei Te of the channel matrix respectively Levy vector；
Determining module, for according to first dimensional feature vector and the second dimensional feature vector, it is determined that three-dimensional special Levy vector；
Figuration module, for carrying out wave beam forming according to the three-dimensional feature vector.
It should be noted that the device of the wave beam forming of third embodiment of the invention offer is using above-mentioned wave beam The device of the method for figuration, then all embodiments of the method for above-mentioned wave beam forming be applied to the device, and Same or analogous beneficial effect can be reached.
The above is the preferred embodiment of the present invention, it is noted that for the common skill of the art For art personnel, on the premise of without departing from principle of the present invention, some improvements and modifications can also be made, These improvements and modifications also should be regarded as protection scope of the present invention.

Claims (15)

1. a kind of method of wave beam forming, it is characterised in that include：
Obtain the channel matrix of the up channel of user equipment emission detection reference signal；
First dimensional feature vector and the second dimensional feature vector of the channel matrix are obtained respectively；
According to first dimensional feature vector and the second dimensional feature vector, three-dimensional feature vector is determined；
Wave beam forming is carried out according to the three-dimensional feature vector.
2. the method for wave beam forming according to claim 1, it is characterised in that the acquisition user sets The step of preparation penetrates the channel matrix of the up channel of detection reference signal includes：
The detection reference signal that receive user equipment is sent by the up channel：
According to the detection reference signal, the channel matrix of the up channel is obtained.
3. the method for wave beam forming according to claim 1, it is characterised in that described to obtain institute respectively The step of the first dimensional feature vector and the second dimensional feature vector for stating channel matrix, includes：
Obtain the first eigenvector and second feature vector of the first dimension of the channel matrix；
It is vectorial according to the first eigenvector and the second feature, the third feature vector of the dimension of acquisition second, Fourth feature vector, fifth feature vector and sixth feature vector.
4. the method for wave beam forming according to claim 3, it is characterised in that described according to described The dimensional feature vector of one-dimensional characteristic vector sum second, determining the step of three-dimensional feature vector includes：
The corresponding third feature value of the comparison third feature vector, the corresponding fourth feature of fourth feature vector Value, the corresponding fifth feature value of fifth feature vector and the corresponding sixth feature value of sixth feature vector, really The eigenvalue of maximum of fixed second dimension and the secondary eigenvalue of maximum of the second dimension；
According to described second dimension eigenvalue of maximum and it is described second dimension secondary eigenvalue of maximum, it is determined that with it is described The first object characteristic vector of corresponding first dimension of eigenvalue of maximum of the second dimension, with the described second dimension time most The second target feature vector that big characteristic value corresponding first is tieed up is corresponding with the eigenvalue of maximum of the described second dimension Second dimension the 3rd target feature vector and with described second dimension secondary eigenvalue of maximum it is corresponding second tie up The 4th target feature vector；
According to the 3rd target feature vector and the first object characteristic vector, the first three-dimensional feature is determined Vector；
According to the 4th target feature vector and second target feature vector, the second three-dimensional feature is determined Vector.
5. the method for wave beam forming according to claim 4, it is characterised in that described according to described three The step of dimensional feature vector carries out wave beam forming includes：
According to first three-dimensional feature vector, single current wave beam forming is carried out；Or
The second three-dimensional feature vector, carries out dual-stream beamforming according to the first three-dimensional feature vector sum.
6. the method for the wave beam forming according to claim 3 or 5, it is characterised in that the acquisition institute The step of the first eigenvector and second feature vector of stating the first dimension of channel matrix includes：
Obtain the first dimension correlation matrix of the channel matrix；
To described first dimension correlation matrix carry out Eigenvalues Decomposition, obtain first eigenvector and second feature to Amount, and the First Eigenvalue corresponding with the first eigenvector and corresponding with the second feature vector Second Eigenvalue；Wherein, the First Eigenvalue is the eigenvalue of maximum of the first dimension, the Second Eigenvalue For the secondary eigenvalue of maximum of the first dimension.
7. the method for wave beam forming according to claim 6, it is characterised in that described according to described One characteristic vector and second feature vector, the third feature that acquisition second is tieed up is vectorial, fourth feature is vectorial, The step of fifth feature vector and sixth feature vector includes：
According to the first eigenvector, the first equivalent channel matrix of the second dimension is built；
According to second feature vector, the second equivalent channel matrix of the second dimension is built；
Obtain the first correlation matrix of the first equivalent channel matrix of second dimension and the of second dimension Second correlation matrix of two equivalent channel matrix；
Eigenvalues Decomposition is carried out to first correlation matrix, third feature vector sum fourth feature vector is obtained, And with the third feature corresponding third feature value of vector and with fourth feature vector the corresponding 4th Characteristic value；Wherein, the third feature value is the eigenvalue of maximum of the first equivalent channel matrix of the second dimension, The fourth feature value is the secondary eigenvalue of maximum of the first equivalent channel matrix of the second dimension；
Eigenvalues Decomposition is carried out to second correlation matrix, fifth feature vector sum sixth feature vector is obtained, And with the fifth feature corresponding fifth feature value of vector and with sixth feature vector the corresponding 6th Characteristic value；Wherein, the fifth feature value is the eigenvalue of maximum of the second equivalent channel matrix of the second dimension, The sixth feature value is the secondary eigenvalue of maximum of the second equivalent channel matrix of the second dimension.
8. a kind of device of wave beam forming, it is characterised in that include：
Matrix acquisition module, for obtaining the channel square of the up channel of user equipment emission detection reference signal Battle array；
Vectorial acquisition module, for obtaining first dimensional feature vector and the second Wei Te of the channel matrix respectively Levy vector；
Determining module, for according to first dimensional feature vector and the second dimensional feature vector, it is determined that three-dimensional special Levy vector；
Figuration module, for carrying out wave beam forming according to the three-dimensional feature vector.
9. the device of wave beam forming according to claim 8, it is characterised in that the matrix obtains mould Block includes：
First matrix acquisition submodule, is joined for receive user equipment by the detection that the up channel sends Examine signal：
Second matrix acquisition submodule, for according to the detection reference signal, obtaining the up channel Channel matrix.
10. the device of wave beam forming according to claim 8, it is characterised in that the vector obtains mould Block includes：
Primary vector acquisition submodule, for obtain the channel matrix first dimension first eigenvector and Second feature vector；
Secondary vector acquisition submodule, for according to the first eigenvector and the second feature vector, Obtain third feature vector, fourth feature vector, fifth feature vector and the sixth feature vector of the second dimension.
The device of 11. wave beam formings according to claim 10, it is characterised in that the determining module Including：
First determination sub-module, for the corresponding third feature value of relatively more described third feature vector, the 4th special Levy vectorial corresponding fourth feature value, the corresponding fifth feature value of fifth feature vector and sixth feature vector Corresponding sixth feature value, determines the eigenvalue of maximum of the second dimension and the secondary eigenvalue of maximum of the second dimension；
Second determination sub-module, for according to the eigenvalue of maximum of the described second dimension and second dimension time most Big characteristic value, it is determined that the first object characteristic vector of the first dimension corresponding with the eigenvalue of maximum of the described second dimension, Second target feature vector and described second of the first dimension corresponding with the secondary eigenvalue of maximum of the described second dimension 3rd target feature vector and time maximum with the described second dimension of corresponding second dimension of eigenvalue of maximum of dimension 4th target feature vector of corresponding second dimension of characteristic value；
3rd determination sub-module, for according to the 3rd target feature vector and the first object feature to Amount, determines the first three-dimensional feature vector；
4th determination sub-module, for according to the 4th target feature vector and second target signature to Amount, determines the second three-dimensional feature vector.
The device of 12. wave beam formings according to claim 11, it is characterised in that the figuration module Including：
First figuration submodule, for according to first three-dimensional feature vector, carrying out single current wave beam forming； Or
Second figuration submodule, for the second three-dimensional feature according to the first three-dimensional feature vector sum to Amount, carries out dual-stream beamforming.
The device of 13. wave beam formings according to claim 10 or 12, it is characterised in that described first Vectorial acquisition submodule includes：
First acquisition unit, for obtaining the first dimension correlation matrix of the channel matrix；
First resolving cell, for carrying out Eigenvalues Decomposition to the described first dimension correlation matrix, obtains first special Levy vector sum second feature vector, and the First Eigenvalue corresponding with the first eigenvector and with it is described The corresponding Second Eigenvalue of second feature vector；Wherein, the First Eigenvalue is the maximum feature of the first dimension Value, the Second Eigenvalue is the secondary eigenvalue of maximum of the first dimension.
The device of 14. wave beam formings according to claim 13, it is characterised in that the secondary vector Acquisition submodule includes：
First construction unit, for according to the first eigenvector, building the first equivalent channel of the second dimension Matrix；
Second construction unit, for according to second feature vector, building the second equivalent channel of the second dimension Matrix；
Second acquisition unit, for obtaining the first correlation matrix of the first equivalent channel matrix of second dimension And the second correlation matrix of the second equivalent channel matrix of second dimension；
Second resolving cell, for carrying out Eigenvalues Decomposition to first correlation matrix, obtains third feature Vector sum fourth feature vector, and with the third feature corresponding third feature value of vector and with described the The corresponding fourth feature value of four characteristic vectors；Wherein, the third feature value is the first equivalent letter of the second dimension The eigenvalue of maximum of road matrix, the fourth feature value is time maximum of the first equivalent channel matrix of the second dimension Characteristic value；
3rd resolving cell, for carrying out Eigenvalues Decomposition to second correlation matrix, obtains fifth feature Vector sum sixth feature vector, and with the fifth feature corresponding fifth feature value of vector and with described the The corresponding sixth feature value of six characteristic vectors；Wherein, the fifth feature value is the second equivalent letter of the second dimension The eigenvalue of maximum of road matrix, the sixth feature value is time maximum of the second equivalent channel matrix of the second dimension Characteristic value.
15. a kind of devices of wave beam forming, it is characterised in that include：Processor；And by EBI The memory being connected with the processor, the memory is used to store the processor when operation is performed The program for being used and data, when processor calls and perform the program and data that are stored in the memory When, realize following functional module：
Matrix acquisition module, for obtaining the channel square of the up channel of user equipment emission detection reference signal Battle array；
Vectorial acquisition module, for obtaining first dimensional feature vector and the second Wei Te of the channel matrix respectively Levy vector；
Determining module, for according to first dimensional feature vector and the second dimensional feature vector, it is determined that three-dimensional special Levy vector；
Figuration module, for carrying out wave beam forming according to the three-dimensional feature vector.
CN201510746940.XA 2015-11-05 2015-11-05 Beam forming method and device Active CN106685501B (en)

Priority Applications (2)

Application Number Priority Date Filing Date Title
CN201510746940.XA CN106685501B (en) 2015-11-05 2015-11-05 Beam forming method and device
PCT/CN2017/070124 WO2017076371A1 (en) 2015-11-05 2017-01-04 Beamforming method and apparatus

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201510746940.XA CN106685501B (en) 2015-11-05 2015-11-05 Beam forming method and device

Publications (2)

Publication Number Publication Date
CN106685501A true CN106685501A (en) 2017-05-17
CN106685501B CN106685501B (en) 2020-09-25

Family

ID=58662561

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201510746940.XA Active CN106685501B (en) 2015-11-05 2015-11-05 Beam forming method and device

Country Status (2)

Country Link
CN (1) CN106685501B (en)
WO (1) WO2017076371A1 (en)

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110708098A (en) * 2018-07-09 2020-01-17 上海华为技术有限公司 Antenna connection detection method and device
CN111181613A (en) * 2018-11-13 2020-05-19 中国移动通信集团设计院有限公司 Three-dimensional beam forming method and device
CN111294104A (en) * 2020-02-27 2020-06-16 杭州电子科技大学 Beam forming optimization method based on eigenvalue decomposition
CN114499606A (en) * 2020-11-11 2022-05-13 大唐移动通信设备有限公司 Interference suppression method and device in multi-user multi-input multi-output system

Families Citing this family (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115987346B (en) * 2022-12-15 2024-02-02 华工未来通信(江苏)有限公司 Intelligent reflecting surface passive beam forming method, system and storage medium

Citations (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102412885A (en) * 2011-11-25 2012-04-11 西安电子科技大学 Three-dimensional wave beam forming method in long term evolution (LET)
CN103152085A (en) * 2011-12-06 2013-06-12 中兴通讯股份有限公司 Weight obtaining method and weight obtaining device of three-dimensional beam forming
US20140098689A1 (en) * 2012-09-28 2014-04-10 Interdigital Patent Holdings, Inc. Wireless communication using multi-dimensional antenna configuration
GB2507782A (en) * 2012-11-09 2014-05-14 Broadcom Corp Three dimensional beamforming in mobile networks
CN103825678A (en) * 2014-03-06 2014-05-28 重庆邮电大学 Three-dimensional multi-user multi-input and multi-output (3D MU-MIMO) precoding method based on Khatri-Rao product
WO2014182002A1 (en) * 2013-05-07 2014-11-13 엘지전자 주식회사 Method for reporting channel state information for three dimensional beamforming in wireless communication system and apparatus for same
CN104184690A (en) * 2014-09-03 2014-12-03 西安电子科技大学 Double-layer pre-coding method applicable to 3D MIMO system
CN104283631A (en) * 2013-07-05 2015-01-14 株式会社Ntt都科摩 Method and device for generating precoding matrix used in three-dimensional MIMO system and transmitter
US20150030092A1 (en) * 2013-07-26 2015-01-29 Motorola Mobility Llc Methods and a device for multi-resolution precoding matrix indicator feedback

Family Cites Families (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2006270730A (en) * 2005-03-25 2006-10-05 Kyocera Corp Radio communication method, radio communication system, and radio communication apparatus
CN101640583B (en) * 2008-07-31 2013-03-13 鼎桥通信技术有限公司 Method for transmitting preprocessing

Patent Citations (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102412885A (en) * 2011-11-25 2012-04-11 西安电子科技大学 Three-dimensional wave beam forming method in long term evolution (LET)
CN103152085A (en) * 2011-12-06 2013-06-12 中兴通讯股份有限公司 Weight obtaining method and weight obtaining device of three-dimensional beam forming
US20140098689A1 (en) * 2012-09-28 2014-04-10 Interdigital Patent Holdings, Inc. Wireless communication using multi-dimensional antenna configuration
GB2507782A (en) * 2012-11-09 2014-05-14 Broadcom Corp Three dimensional beamforming in mobile networks
WO2014182002A1 (en) * 2013-05-07 2014-11-13 엘지전자 주식회사 Method for reporting channel state information for three dimensional beamforming in wireless communication system and apparatus for same
CN104283631A (en) * 2013-07-05 2015-01-14 株式会社Ntt都科摩 Method and device for generating precoding matrix used in three-dimensional MIMO system and transmitter
US20150030092A1 (en) * 2013-07-26 2015-01-29 Motorola Mobility Llc Methods and a device for multi-resolution precoding matrix indicator feedback
CN103825678A (en) * 2014-03-06 2014-05-28 重庆邮电大学 Three-dimensional multi-user multi-input and multi-output (3D MU-MIMO) precoding method based on Khatri-Rao product
CN104184690A (en) * 2014-09-03 2014-12-03 西安电子科技大学 Double-layer pre-coding method applicable to 3D MIMO system

Cited By (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110708098A (en) * 2018-07-09 2020-01-17 上海华为技术有限公司 Antenna connection detection method and device
US11245448B2 (en) 2018-07-09 2022-02-08 Huawei Technologies Co., Ltd. Antenna connection detection method and apparatus
CN111181613A (en) * 2018-11-13 2020-05-19 中国移动通信集团设计院有限公司 Three-dimensional beam forming method and device
CN111181613B (en) * 2018-11-13 2023-01-13 中国移动通信集团设计院有限公司 Three-dimensional beam forming method and device
CN111294104A (en) * 2020-02-27 2020-06-16 杭州电子科技大学 Beam forming optimization method based on eigenvalue decomposition
CN111294104B (en) * 2020-02-27 2022-10-21 杭州电子科技大学 Beam forming optimization method based on eigenvalue decomposition
CN114499606A (en) * 2020-11-11 2022-05-13 大唐移动通信设备有限公司 Interference suppression method and device in multi-user multi-input multi-output system
CN114499606B (en) * 2020-11-11 2023-04-07 大唐移动通信设备有限公司 Interference suppression method and device in multi-user multi-input multi-output system

Also Published As

Publication number Publication date
WO2017076371A1 (en) 2017-05-11
CN106685501B (en) 2020-09-25

Similar Documents

Publication Publication Date Title
CN106685501A (en) Beamforming method and beamforming device
CN106658751B (en) Channel access method and device for multi-antenna equipment
CN104254946B (en) Method and apparatus for three-dimensional wave beam shaping
CN104704872B (en) A kind of method and apparatus of measurement of communication quality
CN105794123A (en) Channel state information acquisition and feedback for full dimension multiple input multiple output
CN103475401B (en) Down-going wave beam forming method and device
US8494073B2 (en) Beamforming weight estimation using wideband multipath direction of arrival analysis
CN106105292A (en) Mobile communication system, base station and user's set
CN106850009A (en) A kind of method and corresponding intrument for determining communication beams
CN114144977B (en) Beam forming method, device, wireless access network equipment and readable storage medium
RU2019123285A (en) INTERFERENCE SUPPRESSION METHOD AND BASE STATION
CN107888259A (en) A kind of antenna beam management method and relevant device
US11190265B2 (en) Specular component estimation in a wireless communication network
CN105322994B (en) A kind of methods, devices and systems carrying out 3D beam forming
CN105227281B (en) Pilot distribution method and device based on MIMO
CN110266353A (en) Terminal, base station, sending method and pre-coding matrix determination method
CN105812073A (en) Horizontal and vertical combined calibration method and device for active antenna array
CN106161322A (en) A kind of signal processing method, uplink resource allocating method and device thereof
CN105992265B (en) A kind of cell measuring method and terminal
CN105637970B (en) Cut-in method and equipment
CN112640324B (en) Antenna array codebook with beamforming coefficients adapted to arbitrary antenna response
US11005541B2 (en) Method for transmitting feedback information and terminal therefor
US12019143B2 (en) Using high-efficiency PHY frames for motion detection
CN106936484A (en) A kind of uplink information feedback and downlink data transmission method and equipment
EP4115202A1 (en) Using high-efficiency phy frames for motion detection

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant
CP01 Change in the name or title of a patent holder
CP01 Change in the name or title of a patent holder

Address after: 100191 No. 40, Haidian District, Beijing, Xueyuan Road

Patentee after: CHINA ACADEMY OF TELECOMMUNICATIONS TECHNOLOGY

Address before: 100191 No. 40, Haidian District, Beijing, Xueyuan Road

Patentee before: CHINA ACADEMY OF TELECOMMUNICATIONS TECHNOLOGY

TR01 Transfer of patent right
TR01 Transfer of patent right

Effective date of registration: 20210602

Address after: 100085 1st floor, building 1, yard 5, Shangdi East Road, Haidian District, Beijing

Patentee after: DATANG MOBILE COMMUNICATIONS EQUIPMENT Co.,Ltd.

Address before: 100191 No. 40, Haidian District, Beijing, Xueyuan Road

Patentee before: CHINA ACADEMY OF TELECOMMUNICATIONS TECHNOLOGY