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WO2017008307A1 - Procédé et appareil permettant d'effectuer un filtrage spatial - Google Patents

Procédé et appareil permettant d'effectuer un filtrage spatial Download PDF

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Publication number
WO2017008307A1
WO2017008307A1 PCT/CN2015/084246 CN2015084246W WO2017008307A1 WO 2017008307 A1 WO2017008307 A1 WO 2017008307A1 CN 2015084246 W CN2015084246 W CN 2015084246W WO 2017008307 A1 WO2017008307 A1 WO 2017008307A1
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Prior art keywords
horizontal
channel matrix
antenna array
matrix
beamforming
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Inventor
Chuangxin JIANG
Zhennian SUN
Gang Wang
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NEC Corp
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NEC Corp
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    • 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
    • H04B7/06—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
    • H04B7/0619—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 using feedback from receiving side
    • H04B7/0621—Feedback content
    • H04B7/0626—Channel coefficients, e.g. channel state information [CSI]

Definitions

  • Embodiments of the present invention generally relate to communication techniques. More particularly, embodiments of the present invention relate to a method and apparatus for performing beamforming.
  • MIMO Multiple Input Multiple Output
  • LTE Long Term Evolution
  • LTE-A Long Term Evolution-Advanced
  • AAS two dimensional antenna system
  • eigenvector (s) obtained by eigenvalue decomposition have been used as beamforming weight (s) or precoder (s) in transmission/reception of a signal, in order to improve radio characteristics.
  • s beamforming weight
  • precoder precoder
  • the present invention proposes a solution for performing beamforming with low complexity in determination of the precoder, while obtaining an average gain which can get high tolerance of uplink channel estimation.
  • embodiments of the invention provide a method of performing beamforming in a MIMO system, wherein a base station (BS) in the MIMO system includes a first antenna array and a second antenna array, each of the first antenna array and the second antenna array contains a plurality of antennas, and the first antenna array and the second antenna array have the same size and are cross-polarized.
  • BS base station
  • the method comprises: obtaining an initial channel matrix based on reference signals received via the first and second antenna arrays from user equipment (UE) , wherein the initial channel matrix includes channel parameters associated with both the first antenna array and the second antenna array; determining vertical beamforming vectors and horizontal beamforming vectors based on the initial channel matrix; determining a first three-dimensional (3D) beamforming vector and a second 3D beamforming vector based on the vertical beamforming vectors and the horizontal beamforming vectors, wherein the first 3D beamforming vector is associated with the polarization of the first antenna array, and the second 3D beamforming vector is associated with the polarization of the second antenna array; determining, at least in part based on the initial channel matrix, a phase factor matrix for polarizations of the first antenna array and the second antenna array; and determining a beamforming parameter matrix based on the phase factor matrix, the first 3Dbeamforming vector and the second 3D beamforming vector.
  • UE user equipment
  • embodiments of the invention provide an apparatus for performing beamforming in a MIMO system, wherein a BS in the MIMO system includes a first antenna array and a second antenna array, each of the first antenna array and the second antenna array contains a plurality of antennas, and the first antenna array and the second antenna array have the same size and are cross-polarized.
  • the apparatus comprises: an obtaining unit configured to obtain an initial channel matrix based on reference signals received via the first and second antenna arrays from a UE, wherein the initial channel matrix includes channel parameters associated with both the first antenna array and the second antenna array; a first determining unit configured to determine vertical beamforming vectors and horizontal beamforming vectors based on the initial channel matrix; a second determining unit configured to determine a first 3D beamforming vector and a second 3D beamforming vector based on the vertical beamforming vectors and the horizontal beamforming vectors, wherein the first 3D beamforming vector is associated with the polarization of the first antenna array, and the second 3D beamforming vector is associated with the polarization of the second antenna array; a third determining unit configured to determine, at least in part based on the initial channel matrix, a phase factor matrix for polarizations of the first antenna array and the second antenna array; and a fourth determining unit configured to determine a beamforming parameter matrix based on the phase factor matrix, the first 3Dbeamforming vector and the second 3D beamforming vector
  • FIG. 1 illustrates a schematic diagram of a MIMO system according to embodiments of the invention
  • FIG. 2 illustrates a flow chart of a method for performing beamforming in a MIMO system according to embodiments of the invention
  • FIG. 3 illustrates a flow chart of a method for determining vertical beamforming vectors and horizontal beamforming vectors according to embodiments of the invention
  • FIG. 4 illustrates a flow chart of a method for determining vertical beamforming vectors and horizontal beamforming vectors according to further embodiments of the invention
  • FIG. 5 illustrates a flow chart of a method for determining vertical beamforming vectors and horizontal beamforming vectors according to embodiments of the invention
  • FIG. 6 illustrates a flow chart of a method for determining vertical beamforming vectors and horizontal beamforming vectors according to further embodiments of the invention
  • FIG. 7 illustrates a flow chart of a method for determining a phase factor matrix according to embodiments of the invention
  • FIG. 8 illustrates a flow chart of a method for determining a phase factor matrix according to further embodiments of the invention.
  • FIG. 9 illustrates a schematic diagram of an apparatus for performing beamforming in a MIMO system according to embodiments of the invention.
  • FIG. 10A illustrates a diagram of dividing the initial channel matrix into 2N groups according to embodiments of the present invention
  • FIG. 10B illustrates a diagram of determination of the vertical beamforming vectors according to embodiments of the present invention.
  • FIG. 11 illustrates a diagram of obtaining the horizontal composition channel matrix according to embodiments of the present invention.
  • FIG. 12 illustrates a diagram of determination of the first and second horizontal beamforming vectors and the first and second 3D beamforming vectors according to embodiments of the present invention
  • FIG. 13 illustrates a diagram of determination of the vertical beamforming vectors according to embodiments of the present invention.
  • FIG. 14 illustrates a diagram of determination of the vertical beamforming vectors according to embodiments of the present invention.
  • FIG. 15 illustrates a diagram of dividing of the initial channel matrix according to embodiments of the present invention.
  • FIG. 16 illustrates a diagram of obtaining the horizontal beamforming vectors according to embodiments of the present invention.
  • FIG. 17 illustrates a diagram of determination of the horizontal beamforming vectors according to embodiments of the present invention.
  • FIG. 18 illustrates a diagram of determination of the horizontal beamforming vectors according to embodiments of the present invention.
  • FIG. 19 illustrates a diagram of obtaining the composition channel matrix according to embodiments of the present invention.
  • FIG. 20 illustrates a diagram of a process for determining the phase factor matrix and the beamforming parameter matrix according to embodiments of the present invention.
  • FIG. 21 illustrates a diagram of a process for determining the phase factor matrix and the beamforming parameter matrix according to embodiments of the present invention.
  • BS represents a node B (NodeB or NB), an evolved NodeB (eNodeB or eNB) , a Remote Radio Unit (RRU) , a radio header (RH) , a remote radio head (RRH) , a relay, a low power node such as a femto, a pico, and so forth.
  • NodeB or NB node B
  • eNodeB or eNB evolved NodeB
  • RRU Remote Radio Unit
  • RH radio header
  • RRH remote radio head
  • relay a low power node such as a femto, a pico, and so forth.
  • the term “user equipment” or “UE” refers to any device that is capable of communicating with the BS.
  • the UE may include a terminal, a Mobile Terminal (MT) , a Subscriber Station (SS) , a Portable Subscriber Station, a Mobile Station (MS) , or an Access Terminal (AT) .
  • MT Mobile Terminal
  • SS Subscriber Station
  • MS Mobile Station
  • AT Access Terminal
  • Embodiments of the present invention may be applied in various communication systems, including but not limited to a Long Term Evolution (LTE) system or a Long Term Evolution Advanced (LTE-A) system.
  • LTE Long Term Evolution
  • LTE-A Long Term Evolution Advanced
  • FIG. 1 illustrates a schematic diagram of a MIMO system 100 according to embodiments of the invention.
  • a BS 110 and a UE 120 are exemplarily illustrated.
  • the BS includes a first antenna array and a second antenna array, each of them containing a plurality of antennas.
  • the first antenna array and the second antenna array are cross-polarized and have the same size.
  • either the first antenna array or the second antenna array has M antennas in the vertical direction and N antennas in the horizontal direction, wherein each of M and N is a natural number.
  • the first antenna array includes M ⁇ N antennas
  • the second antenna array includes M ⁇ N antennas as well.
  • N R 2MN antennas in total.
  • the UE 120 there are N T antennas for communication with the BS 110.
  • information about a channel from the UE 120 to the BS 110 may be indicated by H [N R ⁇ N T ] .
  • a beamforming parameter matrix (sometimes called as “precoder” or “beamforming parameters” ) for performing beamforming
  • precoder or “beamforming parameters”
  • beamforming parameters one or more channel covariance matrices need to be decomposed. Since the decomposition complexity with respect to a large-size antenna array is extremely high, embodiments of the present invention propose a solution to solve this problem. In this way, the beamforming parameter matrix may be determined with reduced complexity.
  • FIG. 2 illustrates a flow chart of a method 200 for performing beamforming in a MIMO system according to embodiments of the invention.
  • the MIMO system may be implemented as the MIMO system 100 shown in FIG. 1.
  • the method 200 may be implemented in any other suitable MIMO system within the scope of the subject matter.
  • the method 200 starts in step 210, in which an initial channel matrix is obtained based on reference signals received via the first and second antenna arrays from a UE, wherein the initial channel matrix includes channel parameters associated with both the first antenna array and the second antenna array.
  • the initial channel matrix may represent channel information characterizing the channel from the UE 120 to the BS 110, and may include channel parameters associated with both the first antenna array and the second antenna array.
  • the initial channel matrix may be denoted as H [N R ⁇ N T ] .
  • the initial channel matrix is illustrated in the form of a matrix, but it is just an example rather than limitation. Those skilled in the art will appreciate that the initial channel matrix may have some other suitable forms.
  • the initial channel matrix may be a set including multiple groups (for example M groups) of channel parameters, and each group comprises a certain number of channel parameters (for example, N channel parameters) .
  • the initial channel matrix may be obtained in several ways.
  • the UE may send reference signals such as sounding reference signals (SRSs) to the BS.
  • the BS may measure the reference signals and determine the initial channel matrix based thereon. It is to be noted that this embodiment is illustrated for purpose of example, rather than limitation. Those skilled in the art can obtain the initial channel matrix by means of some other conventional techniques, and relevant descriptions are not detailed here.
  • step 220 vertical beamforming vectors and horizontal beamforming vectors are determined based on the initial channel matrix.
  • the vertical beamforming vectors and horizontal beamforming vectors may be determined in several ways.
  • the vertical beamforming vectors may be calculated based on the initial channel matrix.
  • a first horizontal beamforming vector and a second horizontal beamforming vector may be calculated based on the vertical beamforming vectors as well as the initial channel matrix. Details of these embodiments will be described with respect to FIG. 3.
  • the vertical beamforming vectors may be calculated based on the initial channel matrix.
  • the horizontal beamforming vectors may be calculated based on the initial channel matrix.
  • the horizontal beamforming vectors may be calculated independent of the vertical beamforming vectors.
  • the calculation of the vertical beamforming vectors may occur either before or after the calculation of the horizontal beamforming vectors, or both of the calculations be executed concurrently. Details of these embodiments will be described with respect to FIG. 5.
  • a first three-dimensional (3D) beamforming vector and a second 3D beamforming vector are determined based on the vertical beamforming vectors and the horizontal beamforming vectors, wherein the first 3D beamforming vector is associated with the polarization of the first antenna array, and the second 3D beamforming vector is associated with the polarization of the second antenna array.
  • the first 3D beamforming vector and the second 3D beamforming vector may be determined in several ways.
  • the vertical beamforming vectors may be divided into two parts, wherein the first part of the vertical beamforming vectors may be associated with the polarization of the first antenna array, and the second part of the vertical beamforming vectors may be associated with the polarization of the second antenna array.
  • the first 3D beamforming vector may be calculated based on a first part of the vertical beamforming vectors and the first horizontal beamforming vector
  • the second 3D beamforming vector may be calculated based on a second part of the vertical beamforming vectors and the second horizontal beamforming vector. It is to be noted that the calculation of the first 3D beamforming vector and the calculation of the second 3D beamforming vector may execute in sequence, concurrently or in the reverse order.
  • the first 3D beamforming vector may be calculated based on a first part of the vertical beamforming vectors and a first part of the horizontal beamforming vectors
  • the second 3D beamforming vector may be calculated based on a second part of the vertical beamforming vectors and a second part of the horizontal beamforming vectors.
  • the first part of the vertical beamforming vectors and the first part of the horizontal beamforming vectors may be associated with the polarization of the first antenna array respectively
  • the second part of the vertical beamforming vectors and the second part of the horizontal beamforming vectors may be associated with the polarization of the second antenna array respectively.
  • a phase factor matrix for polarizations of the first antenna array and the second antenna array is determined at least in part based on the initial channel matrix.
  • the phase factor matrix is associated with the different polarizations of the first antenna array and the second antenna array.
  • the phase factor matrix may be determined in multiple ways.
  • the initial channel matrix may be divided into a first channel matrix and a second channel matrix, wherein the first channel matrix is associated with the first antenna array and the second channel matrix is associated with the second antenna array.
  • a composition channel matrix then may be obtained based on the first 3D beamforming vector, the second 3D beamforming vector, the first channel matrix and the second channel matrix.
  • a composition covariance matrix of the composition channel matrix may be calculated and then averaged in a third predetermined period of time or a third predetermined frequency band.
  • the phase factor matrix may be determined by performing decomposition (for example EVD) based on the averaging results. Details of the embodiments will be described with respect to FIG. 7.
  • the phase factor matrix may be directly determined from the initial channel matrix, without using the first 3D beamforming vector or the second 3D beamforming vector. More specifically, a simplified channel matrix may be determined from the initial channel matrix. The simplified channel matrix may include channel parameters associated with a pair of antennas that have different polarizations, wherein one of the pair of antennas belongs to the first antenna array and the other of the pair of antennas belongs to the second antenna array. Next, a simplified covariance matrix of the simplified channel matrix may be calculated and averaged in a third predetermined period of time or a third predetermined frequency band. Then, the phase factor matrix may be determined by performing decomposition based on the averaging results. Details of the embodiments will be described with respect to FIG. 8.
  • a beamforming parameter matrix is determined based on the phase factor matrix, the first 3D beamforming vector and the second 3D beamforming vector.
  • the beamforming parameter matrix may be obtained by applying the phase factor matrix to the first 3D beamforming vector and the second 3D beamforming vector.
  • the first 3D beamforming vector and the second 3D beamforming vector obtained in step 230 are denoted as and respectively, and the phase factor matrix obtained in step 240 is denoted as
  • the beamforming parameter matrix V F may be determined based on the phase factor matrix, the first 3D beamforming vector and the second 3D beamforming vector as follows:
  • the complexity of determining the beamforming parameter matrix can be reduced, and the beamforming parameter matrix can be obtained in a fast and efficient manner.
  • FIG. 3 illustrates a flow chart of a method 300 for determining vertical beamforming vectors and horizontal beamforming vectors according to embodiments of the invention.
  • the method 300 may be considered as a specific implementation of step 220 of method 200 described above with reference to Fig. 2. However, it is noted that this is only for the purpose of illustrating the principles of the present invention, rather than limiting the scope thereof.
  • step 310 the vertical beamforming vectors are calculated based on the initial channel matrix.
  • the vertical beamforming vectors may be obtained in several ways.
  • elements of the initial channel matrix may be divided into 2N groups, wherein N indicates the number of antennas in a horizontal direction of the first antenna array or the second antenna array.
  • 2N vertical covariance matrices of the 2N groups may be calculated respectively, and averaged in a first predetermined period of time or a first predetermined frequency band respectively.
  • 2N eigenvectors may be calculated based on the averaging results as the vertical beamforming vectors.
  • the calculation of the 2N eigenvectors as discussed above may be simplified as calculating one eigenvector. More specifically, elements of the initial channel matrix may be divided into 2N groups, wherein N indicates the number of antennas in a horizontal direction of the first antenna array or the second antenna array. Next, 2N vertical covariance matrices of the 2N groups may be calculated. Each of the 2N vertical covariance matrices may be then averaged in a first predetermined period of time or a first predetermined frequency band. Next, a sum or a mean value of the averaging results may be calculated. Then, an eigenvector which is calculated based on the sum or the mean value may be determined as ach of the vertical beamforming vectors. In this way, all of the vertical beamforming vectors are identical.
  • elements of the initial channel matrix may be divided into 2N groups, wherein N indicates the number of antennas in a horizontal direction of the first antenna array or the second antenna array.
  • a vertical covariance matrix of one of the 2N groups may be calculated and averaged in a first predetermined period of time or a first predetermined frequency band.
  • an eigenvector calculated based on the averaging result may be determined as each of the vertical beamforming vectors.
  • a first horizontal beamforming vector and a second horizontal beamforming vector are calculated based on the initial channel matrix and the vertical beamforming vectors.
  • FIG. 4 illustrates a flow chart of a method 400 for determining vertical beamforming vectors and horizontal beamforming vectors according to further embodiments of the invention.
  • the method 400 may be considered as a specific implementation of method 300 described above with reference to Fig. 3. More specifically, steps 410-440 corresponds to an implementation of step 310, and steps 450-490 corresponds to an implementation of step 320. However, it is noted that this is only for the purpose of illustrating the principles of the present invention, rather than limiting the scope thereof.
  • step 410 elements of the initial channel matrix are divided into 2N groups, wherein N indicates the number of antennas in a horizontal direction of the first antenna array or the second antenna array.
  • the method 400 may be applicable in the MIMO system 100.
  • the initial channel matrix H [2MN ⁇ N T ] may be divided into 2N groups, that is H 0 , ... , H N-1 and H N , ... , H 2N-1 , wherein each of H 0 , ... , H N-1 and H N , ... , H 2N-1 is a M ⁇ N T matrix.
  • FIG. 10A illustrates a diagram of dividing the initial channel matrix into 2N groups according to embodiments of the present invention.
  • step 420 2N vertical covariance matrices of the 2N groups are calculated.
  • a corresponding vertical covariance matrix, R i may be calculated as follows:
  • each of the 2N vertical covariance matrices is averaged in a first predetermined period of time or a first predetermined frequency band.
  • each of the 2N vertical covariance matrices, R i may be averaged in a first predetermined period of time or a first predetermined frequency band.
  • the first predetermined period of time or the first predetermined frequency band may be referred to as the first range and may be preset according to system conditions, certain requirements or the like.
  • the R i may be averaged on a certain number of resource blocks (RBs) .
  • the averaged R i may be denoted as In this way, can be obtained.
  • step 440 2N eigenvectors calculated based on the averaging results are determined as the vertical beamforming vectors.
  • a decomposition operation such as M ⁇ M Eigen Value Decomposition (EVD)
  • ELD Eigen Value Decomposition
  • an eigenvector may be obtained therefrom.
  • an eigenvector V i may be calculated from the following:
  • D i is an eigenvalue matrix
  • V i is the eigenvector corresponding to the maximum eigenvalue.
  • 2N eigenvectors V 0 , V 1 , ... V 2N-1 may be calculated from equation (4) and may be determined as 2N vertical beamforming vectors.
  • the size of each of the 2N vertical beamforming vectors V 0 , V 1 , ... V 2N-1 is M ⁇ 1.
  • FIG. 10B illustrates a diagram 1000 of determination of the vertical beamforming vectors according to embodiments of the present invention.
  • 2N vertical beamforming vectors V 0 [M ⁇ 1] , V 1 [M ⁇ 1] , ... V 2N-1 [M ⁇ 1] are obtained from the initial channel matrix H [N R ⁇ N T ] after calculating covariance matrices, averaging, and performing EVD.
  • step 450 a horizontal composition channel matrix is obtained based on the initial channel matrix and the vertical beamforming vectors.
  • the horizontal composition channel matrix may be obtained by applying the 2N vertical beamforming vectors V 0 , V 1 , ... V 2N-1 to conjugation of H 0 , ... , H N-1 and H N , ... , H 2N-1 , respectively. More specifically, the horizontal composition channel matrix (denoted as ) may be obtained as follows:
  • equation (5) can be calculated by:
  • step 450 a diagram 1100 of obtaining the horizontal composition channel matrix is illustrated.
  • the horizontal composition channel matrix comprises 2N sub-matrices and each of them is calculated by equation (6) .
  • step 460 the horizontal composition channel matrix is divided into a first horizontal channel matrix and a second horizontal channel matrix, wherein the first horizontal channel matrix is associated with the first antenna array and the second horizontal channel matrix is associated with the second antenna array.
  • the horizontal composition channel matrix may be divided into the first horizontal channel matrix (sometimes referred to as ) and the second horizontal channel matrix (sometimes referred to as ) .
  • the first horizontal channel matrix includes a half of the 2N sub-matrices, namely, which are associated with the first antenna array.
  • the second horizontal channel matrix includes the remaining of the 2N sub-matrices, namely which are associated with the second antenna array.
  • step 470 a first horizontal covariance matrix of the first horizontal channel matrix and a second horizontal covariance matrix of the second horizontal channel matrix are calculated.
  • R A For the first horizontal channel matrix the corresponding covariance matrix, R A ,may be calculated as follows:
  • R B the corresponding covariance matrix
  • the first horizontal covariance matrix R A and the second horizontal covariance matrix R B may be obtained based on equations (7) and (8) .
  • each of the first horizontal covariance matrix and the second horizontal covariance matrix is averaged in a second predetermined period of time or a second predetermined frequency band.
  • the second predetermined period of time or the second predetermined frequency band may be referred to as the second range and may be preset according to system conditions, certain requirements or the like.
  • the first horizontal covariance matrix R A and the second horizontal covariance matrix R B may be averaged on a certain number of RBs.
  • the first and second horizontal covariance matrices may be denoted as and
  • the first range may be larger than or equal to the second range.
  • the first predetermined period of time may be larger than or equal to the second predetermined period of time
  • the first predetermined frequency band may be larger than or equal to the second predetermined frequency band.
  • step 490 an eigenvector calculated based on the averaging of the first horizontal covariance matrix is determined as the first horizontal beamforming vector, and another eigenvector calculated based on the averaging of the second horizontal covariance matrix is determiined as the second horizontal beamforming vector.
  • the first and horizontal beamforming vectors may be obtained by performing EVD on and respectively.
  • an eigenvector V A may be calculated from:
  • V B may be calculated from:
  • V A is N ⁇ 1
  • V B is N ⁇ 1.
  • the first and second 3D beamforming vectors may be calculated accordingly.
  • the vertical beamforming vectors obtained at step 440 may be divided into two parts, wherein the first part is associated with the polarization of the first antenna array, and the second part is associated with the polarization of the second antenna array. Then, the first 3D beamforming vector may be calculated based on the first part of the vertical beamforming vectors and the first horizontal beamforming vector. The second 3D beamforming vector may be calculated based on the second part of the vertical beamforming vectors and the second horizontal beamforming vector.
  • the first 3D beamforming vector (denoted as ) may be obtained by:
  • V 0 , ... V N-1 represent the first part of the vertical beamforming vectors.
  • the second 3D beamforming vector (denoted as ) may be obtained by:
  • V N , ... V 2N-1 represent the second part of the vertical beamforming vectors.
  • FIG. 12 illustrates a diagram 1200 of determination of the first and second horizontal beamforming vectors and the first and second 3D beamforming vectors.
  • steps 410-440 of the method 400 illustrate an exemplary embodiment of step 310, which is an example rather than limitation to the present invention.
  • step 310 may be implemented in any other suitable embodiments.
  • the calculation of the 2N eigenvectors as discussed above may be simplified as calculating one eigenvector. More specifically, elements of the initial channel matrix may be divided into 2N groups, wherein N indicates the number of antennas in a horizontal direction of the first antenna array or the second antenna array. Next, 2N vertical covariance matrices of the 2N groups may be calculated.
  • Each of the 2N vertical covariance matrices may be then averaged in a first predetermined period of time or a first predetermined frequency band. Next, a sum or a mean value of the averaging results may be calculated. Then, an eigenvector which is calculated based on the sum or the mean value may be determined as ach of the vertical beamforming vectors. In this way, all of the vertical beamforming vectors are identical.
  • FIG. 13 illustrates a diagram 1300 of determination of the vertical beamforming vectors according to the aforesaid embodiments of the present invention.
  • elements of the initial channel matrix may be divided into 2N groups, wherein N indicates the number of antennas in a horizontal direction of the first antenna array or the second antenna array.
  • a vertical covariance matrix of one of the 2N groups may be calculated and averaged in a first predetermined period of time or a first predetermined frequency band.
  • an eigenvector calculated based on the averaging result may be determined as each of the vertical beamforming vectors.
  • FIG. 14 illustrates a diagram 1400 of determination of the vertical beamforming vectors according to the aforesaid embodiments of the present invention.
  • step 220 may be implemented in several other ways.
  • FIG. 5 illustrates a flow chart of a method 500 for determining vertical beamforming vectors and horizontal beamforming vectors according to embodiments of the invention.
  • both the vertical beamforming vectors and the horizontal beamforming vectors are determined from the initial channel matrix.
  • this is only for the purpose of illustrating the principles of the present invention, rather than limiting the scope thereof.
  • Method 500 starts from step 510, in which the vertical beamforming vectors are calculated based on the initial channel matrix. This step is similar to step 310, thus its descriptions are not detailed here. It is to be noted that the embodiments described with respect to step 310 of method 300 and steps 410-440 of method 400 also applicable to step 510.
  • step 520 the horizontal beamforming vectors are calculated based on the initial channel matrix.
  • the horizontal beamforming vectors may be obtained in several ways.
  • the initial channel matrix may be divided into 2M groups, wherein M indicates the number of antennas in a vertical direction of the first antenna array or the second antenna array.
  • 2M horizontal covariance matrices of the 2M groups may be calculated and averaged in a second predetermined period of time or a second predetermined frequency band.
  • 2M eigenvectors calculated based on the averaging results may be determined as the horizontal beamforming vectors.
  • the initial channel matrix may be divided into 2M groups, wherein M indicates the number of antennas in a vertical direction of the first antenna array or the second antenna array.
  • 2M horizontal covariance matrices of the 2M groups may be calculated and averaged in a second predetermined period of time or a second predetermined frequency band.
  • a sum or a mean value of the averaging results may be calculated.
  • an eigenvector calculated based on the sum or the mean value may be determined as each of the horizontal beamforming vectors. In this way, all of the horizontal beamforming vectors are identical.
  • the initial channel matrix may be divided into 2M groups, wherein M indicates the number of antennas in a vertical direction of the first antenna array or the second antenna array.
  • a horizontal covariance matrix of one of the 2M groups may be calculated and averaged in a second predetermined period of time or a second predetermined frequency band.
  • an eigenvector calculated based on the averaging result may be determined as each of the horizontal beamforming vectors.
  • FIG. 6 illustrates a flow chart of a method 600 for determining vertical beamforming vectors and horizontal beamforming vectors according to further embodiments of the invention.
  • the method 600 may be considered as a specific implementation of method 500 described above with reference to Fig. 5. More specifically, steps 610 corresponds to an implementation of step 510, and steps 620-650 correspond to an implementation of step 520. However, it is noted that this is only for the purpose of illustrating the principles of the present invention, rather than limiting the scope thereof.
  • Method 600 starts from step 610, in which the vertical beamforming vectors are calculated based on the initial channel matrix. This step is similar to steps 310 and 510, thus its descriptions are not detailed here.
  • step 620 calculates the horizontal beamforming vectors independent of the vertical beamforming vectors.
  • the initial channel matrix is divided into 2M groups, wherein M indicates the number of antennas in a vertical direction of the first antenna array or the second antenna array.
  • FIG. 15 illustrates a diagram 1500 of dividing of the initial channel matrix according to embodiments of the present invention.
  • the size of the initial channel matrix H [N R ⁇ N T ] is 2MN ⁇ N T .
  • the initial channel matrix may be divided, according to 2M rows of antennas, into 2M groups, H 0 , ... H M-1 , ... H 2M-1 .
  • Each of the H 0 , ... H M-1 , ... H 2M-1 corresponds to a row of antennas in the first antenna array or the second antenna array.
  • step 630 2M horizontal covariance matrices of the 2M groups are calculated.
  • a corresponding horizontal covariance matrix, R j may be calculated as follows:
  • each of the 2M horizontal covariance matrices is averaged in a second predetermined period of time or a second predetermined frequency band.
  • each of the 2M horizontal covariance matrices, R j may be averaged in the second predetermined period of time or the second predetermined frequency band.
  • the second predetermined period of time or the second predetermined frequency band may be referred to as the second range in context of the disclosure.
  • step 650 2M eigenvectors calculated based on the averaging results are determined as the horizontal beamforming vectors.
  • an eigenvector P j may be calculated from the following:
  • 2M eigenvectors P 0 , P 1 , ... P 2M-1 may be calculated from equation (14) and may be determined as 2M horizontal beamforming vectors.
  • the size of each of the 2M horizontal beamforming vectors P 0 , P 1 , ... P 2M-1 is N ⁇ l.
  • FIG. 16 a diagram 1600 of obtaining the horizontal beamforming vectors is illustrated.
  • the 2M horizontal beamforming vectors P 0 , P 1 , ... P 2M-1 (shown as P 0 [N ⁇ 1] , P 1 [N ⁇ 1] ... P 2M-1 [N ⁇ 1] ) are obtained from 2M groups, H 2M-1 , ... H M-1 , ... H 0 ofthe initial channel matrix H [N R ⁇ N T ] after calculating covariance matrices (denoted as “Covar. ” ) , averaging (denoted as “Av. ” ) and EVD.
  • Covar. represents an operation of calculating a covariance matrix
  • Av. represents an operation of averaging.
  • steps 620-650 of the method 600 illustrate an exemplary embodiment of step 520, which is an example rather than limitation to the present invention.
  • the initial channel matrix may be divided into 2M groups, wherein M indicates the number of antennas in a vertical direction of the first antenna array or the second antenna array.
  • 2M horizontal covariance matrices of the 2M groups may be calculated and averaged in a second predetermined period of time or a second predetermined frequency band. Next, a sum or a mean value of the averaging results may be calculated.
  • FIG. 17 illustrates a diagram 1700 of determination of the horizontal beamforming vectors according to the aforesaid embodiments of the present invention.
  • the initial channel matrix may be divided into 2M groups, wherein M indicates the number of antennas in a vertical direction of the first antenna array or the second antenna array.
  • a horizontal covariance matrix of one of the 2M groups may be calculated and averaged in a second predetermined period of time or a second predetermined frequency band.
  • an eigenvector calculated based on the averaging result may be determined as each of the horizontal beamforming vectors.
  • FIG. 18 illustrates a diagram 1800 of determination of the horizontal beamforming vectors according to the aforesaid embodiments of the present invention.
  • the first and second 3D beamforming vectors may be calculated accordingly.
  • the vertical beamforming vectors obtained at step 610 may be divided into two parts, wherein the first part is associated with the polarization of the first antenna array, and the second part is associated with the polarization of the second antenna array.
  • the horizontal beamforming vectors obtained at step 650 may be divided into two parts, wherein the first part is associated with the polarization of the first antenna array, and the second part is associated with the polarization of the second antenna array.
  • the first 3D beamforming vector may be calculated based on the first part of the vertical beamforming vectors and the first part of the horizontal beamforming vectors.
  • the second 3D beamforming vector may be calculated based on the second part of the vertical beamforming vectors and the second part of horizontal beamforming vectors.
  • the first 3D beamforming vector (denoted as )associated with the polarization of the first antenna array may be obtained by:
  • V 0 (0) ⁇ P 0 (0) corresponds to antenna location (0, 0) shown in FIG. 1;
  • V 0 (1) ⁇ P 1 (0) corresponds to antenna location (1, 0) shown in FIG. 1;
  • V 0 (M-1) ⁇ P M-1 (0) corresponds to antenna location (M-1, 0) shown in FIG. 1;
  • V 1 (0) .P 0 (1) corresponds to antenna location (0, 1) shown in FIG. 1;
  • V 1 (1) ⁇ P 1 (1) corresponds to antenna location (1, 1) shown in FIG. 1;
  • V 1 (M-1) ⁇ P M-1 (1) corresponds to antenna location (M-1, 1) shown in FIG. 1;
  • V N-1 (0) ⁇ P 0 (N -1) corresponds to antenna location (0, N-1) shown in FIG. 1;
  • V N-1 (1) ⁇ P 1 (N-1) corresponds to antenna location (1, N-1) shown in FIG. 1;
  • V N-1 (M-1) ⁇ P M-1 (N-1) corresponds to antenna location (M-1, N-1) shown in FIG. 1.
  • the second 3D beamforming vector (denoted as ) associated with the polarization of the second antenna array may be obtained by:
  • V N (0) ⁇ P M (0) corresponds to antenna location (0, 0) shown in FIG. 1;
  • V N (1) ⁇ P M+1 (0) corresponds to antenna location (1, 0) shown in FIG. 1;
  • V N (M-1) ⁇ P 2M-1 (0) corresponds to antenna location (M-1, 0) shown in FIG. 1;
  • V N+1 (0) ⁇ P M (1) corresponds to antenna location (0, 1) shown in FIG. 1;
  • V N+1 (1) ⁇ P M+1 (1) corresponds to antenna location (1, 1) shown in FIG. 1;
  • V N+1 (M-1) ⁇ P 2M-1 (1) corresponds to antenna location (M-1, 1) shown in FIG. 1;
  • V 2N-1 (0) ⁇ P M (N-1) corresponds to antenna location (0, N-1) shown in FIG. 1;
  • V 2N-1 (1) ⁇ P M+1 (N-1) corresponds to antenna location (1, N-1) shown in FIG. 1;
  • V 2N-1 (M-1) ⁇ P 2M-1 (N-1) corresponds to antenna location (M-1, N-1) shown in FIG.1.
  • the phase factor matrix may be determined based on the first 3D beamforming vector, the second 3D beamforming vector as well as the initial channel matrix.
  • FIG. 7 illustrates a flow chart of a method 700 for determining a phase factor matrix according to such embodiments.
  • the method 700 may be considered as a specific implementation of step 240 of method 200 described above with reference to Fig. 2. However, it is noted that this is only for the purpose of illustrating the principles of the present invention, rather than limiting the scope thereof.
  • Method 700 starts from step 710, in which the initial channel matrix is divided into a first channel matrix and a second channel matrix, wherein the first channel matrix is associated with the first antenna array and the second channel matrix is associated with the second antenna array.
  • the initial channel matrixH [N R ⁇ N T ] may be divided as below:
  • first channel matrix H A is a MN ⁇ N T matrix and associated with the polarization of the first antenna array
  • the second channel matrix H B is a MN ⁇ N T matrix and associated with the polarization of the second antenna array.
  • a composition channel matrix is obtained based on the first 3D beamforming vector, the second 3D beamforming vector, the first channel matrix and the second channel matrix.
  • composition channel matrix may be obtained as follows:
  • FIG. 19 illustrates a diagram 1900 of obtaining the composition channel matrix according to embodiments of the present invention.
  • step 730 a composition covariance matrix of the composition channel matrix is calculated.
  • composition covariance matrix R H of the composition channel matrix may be calculated as follows:
  • composition channel matrix where represents the composition channel matrix, and represents conjugation of the composition channel matrix
  • the composition covariance matrix is averaged in a third predetermined period of time or a third predetermined frequency band.
  • the third predetermined period of time or the third predetermined frequency band may be referred to as the third range.
  • the first range may be larger than or equal to the second range, and the second range may be larger than or equal to the third range.
  • the first predetermined period of time may be larger than or equal to the second predetermined period of time, and the second predetermined period of time may be larger than or equal to the third predetermined period of time.
  • the first predetermined frequency band may be larger than or equal to the second predetermined frequency band, and the second predetermined frequency band may be larger than or equal to the third predetermined frequency band.
  • the averaged composition covariance matrix may be denoted as
  • step 750 the phase factor matrix is determined by performing decomposition based on the averaging results.
  • the phase factor matrix V p may be obtained by performing EVD (for example, 2 ⁇ 2 EVD) on EVD (for example, 2 ⁇ 2 EVD) on
  • phase factor matrix V p may be determined as:
  • FIG. 20 illustrates a diagram 2000 of a process for determining the phase factor matrix and the beamforming parameter matrix according to the aforesaid embodiments of the present invention.
  • the phase factor matrix may be determined only based on the initial channel matrix, independent of the first 3D beamforming vector and the second 3D beamforming vector.
  • FIG. 8 illustrates a flow chart of a method 800 for determining a phase factor matrix according to such embodiments.
  • the method 800 may be considered as a specific implementation of step 240 of method 200 described above with reference to Fig. 2. However, it is noted that this is only for the purpose of illustrating the principles of the present invention, rather than limiting the scope thereof.
  • Method 800 starts from step 810, in which a simplified channel matrix is determined from the initial channel matrix, wherein the simplified channel matrix includes channel parameters associated with a pair of antennas that have different polarizations, wherein one of the pair of antennas belongs to the first antenna array and the other of the pair of antennas belongs to the second antenna array.
  • FIG. 21 illustrates a diagram 2100 of a process for determining the phase factor matrix and the beamforming parameter matrix according to the aforesaid embodiments of the present invention.
  • the pair of antennas includes a first antenna which belongs to the first antenna array and a second antenna which belongs to the second antenna array, and both the first antenna and the second antenna have the same location (M-1, 0) .
  • a simplified channel matrix is a channel matrix associated with the pair of antennas.
  • the simplified channel matrix which is denoted as may be obtained from the initial channel matrix, for example, by extracting related channel information about the pair of antennas from the initial channel matrix.
  • step 820 a simplified covariance matrix of the simplified channel matrix is calculated.
  • step 830 the simplified covariance matrix is averaged in a third predetermined period of time or a third predetermined frequency band.
  • step 840 the phase factor matrix is determined by performing decomposition based on the averaging results.
  • Steps 820 to 840 are similar to steps 730 to 750, and the phase factor matrix may be obtained in a similar way as equations (19) - (21) . Thus, related descriptions are not detailed here.
  • the beamforming parameter matrix V F may be determined according to equation (2) . In this way, the precoder may be obtained with reduced complexity.
  • FIG. 9 illustrates a schematic diagram of an apparatus 900 for performing beamforming in a MIMO system according to embodiments of the invention.
  • the apparatus 900 may be implemented at a BS or other suitable node in a MIMO system, and the BS or other suitable node may comprise a first antenna array and a second antenna array.
  • Each of the first antenna array and the second antenna array contains a plurality of antennas, and the first antenna array and the second antenna array have the same size and are cross-polarized.
  • the apparatus 900 comprises an obtaining unit 910 configured to obtain an initial channel matrix based on reference signals received via the first and second antenna arrays from a UE, wherein the initial channel matrix includes channel parameters associated with both the first antenna array and the second antenna array; a first determining unit 920 configured to determine vertical beamforming vectors and horizontal beamforming vectors based on the initial channel matrix; a second determining unit 930 configured to determine a first three-dimensional (3D) beamforming vector and a second 3D beamforming vector based on the vertical beamforming vectors and the horizontal beamforming vectors, wherein the first 3D beamforming vector is associated with the polarization of the first antenna array, and the second 3D beamforming vector is associated with the polarization of the second antenna array; a third determining unit 940 configured to determine, at least in part based on the initial channel matrix, a phase factor matrix for polarizations of the first antenna array and the second antenna array; and a fourth determining unit 950 configured to determine a beamforming parameter matrix based on the
  • the first determining unit 620 may comprises: a vertical beamforming vector calculating unit configured to calculate the vertical beamforming vectors based on the initial channel matrix; and a horizontal beamforming vector calculating unit configured to calculate a first horizontal beamforming vector and a second horizontal beamforming vector based on the initial channel matrix and the vertical beamforming vectors.
  • the horizontal beamforming vector calculating unit may comprise: a horizontal composition channel matrix obtaining unit configured to obtain a horizontal composition channel matrix based on the initial channel matrix and the vertical beamforming vectors; a horizontal composition channel matrix dividing unit configured to divide the horizontal composition channel matrix into a first horizontal channel matrix and a second horizontal channel matrix, wherein the first horizontal channel matrix is associated with the first antenna array and the second horizontal channel matrix is associated with the second antenna array; a first horizontal covariance matrix calculating unit configured to calculate a first horizontal covariance matrix of the first horizontal channel matrix and a second horizontal covariance matrix of the second horizontal channel matrix; a first averaging unit configured to average each of the first horizontal covariance matrix and the second horizontal covariance matrix in a second predeterrnined period of time or a second predetermined frequency band; and a first horizontal beamforming vector determining unit configured to determine an eigenvector calculated based on the averaging of the first horizontal covariance matrix as the first horizontal beamforming vector, and another e
  • the second determining unit 630 may comprise: a first 3D beamforming vector calculating unit configured to calculate the first 3D beamforming vector based on a first part of the vertical beamforming vectors and the first horizontal beamforming vector; and a second 3D beamforming vector calculating unit configured to calculate the second 3D beamforming vector based on a second part of the vertical beamforming vectors and the second horizontal beamforming vector, wherein the first part of the vertical beamforming vectors is associated with the polarization of the first antenna array, and the second part of the vertical beamforming vectors is associated with the polarization of the second antenna array.
  • the first determining unit 610 may comprise: a vertical beamforming vector calculating unit configured to calculate the vertical beamforming vectors based on the initial channel matrix; and a horizontal beamforming vector calculating unit configured to calculate the horizontal beamforming vectors based on the initial channel matrix.
  • the horizontal beamforming vector calculating unit may comprise: a first initial channel matrix dividing unit configured to divide the initial channel matrix into 2M groups, wherein M indicates the number of antennas in a vertical direction of the first antenna array or the second antenna array; a second horizontal covariance matrix calculating unit configured to calculate 2M horizontal covariance matrices of the 2M groups; a second averaging unit configured to average each of the 2M horizontal covariance matrices in a second predetermined period of time or a second predetermined frequency band; and a second horizontal beamforming vector determining unit configured to determine 2M eigenvectors calculated based on the averaging results as the horizontal beamforming vectors.
  • the horizontal beamforming vector calculating unit may comprise: a first initial channel matrix dividing unit configured to divide the initial channel matrix into 2M groups, wherein M indicates the number of antennas in a vertical direction of the first antenna array or the second antenna array; a second horizontal covariance matrix calculating unit configured to calculate 2M horizontal covariance matrices of the 2M groups; a second averaging unit configured to average each of the 2M horizontal covariance matrices in a second predetermined period of time or a second predetermined frequency band; a first computing unit configured to calculate a sum or a mean value of the averaging results; and a second horizontal beamforming vector determining unit configured to determine an eigenvector calculated based on the sum or the mean value as each of the horizontal beamforming vectors.
  • the horizontal beamforming vector calculating unit may comprise: a first initial channel matrix dividing unit configured to divide the initial channel matrix into 2M groups, wherein M indicates the number of antennas in a vertical direction of the first antenna array or the second antenna array; a second horizontal covariance matrix calculating unit configured to calculate a horizontal covariance matrix of one of the 2M groups; a second averaging unit configured to average the horizontal covariance matrix in a second predetermined period of time or a second predetermined frequency band; and a second horizontal beamforming vector determining unit configured to determine an eigenvector calculated based on the averaging result as each of the horizontal beamforming vectors.
  • the second determining unit may comprise: a first 3D beamforming vector calculating unit configured to calculate the first 3D beamforming vector based on a first part of the vertical beamforming vectors and a first part of the horizontal beamforming vectors; and a second 3D beamforming vector calculating unit configured to calculate the second 3D beamforming vector based on a second part of the vertical beamforming vectors and a second part of the horizontal beamforming vectors, wherein the first part of the vertical beamforming vectors and the first part of the horizontal beamforming vectors are associated with the polarization of the first antenna array, and the second part of the vertical beamforming vectors and the second part of the horizontal beamforming vectors are associated with the polarization of the second antenna array.
  • the vertical beamforming vector calculating unit may comprise: a second initial channel matrix dividing unit configured to divide elements of the initial channel matrix into 2N groups, wherein N indicates the number of antennas in a horizontal direction of the first antenna array or the second antenna array; a third horizontal covariance matrix calculating unit configured to calculate 2N vertical covariance matrices of the 2N groups; a third averaging unit configured to average each of the 2N vertical covariance matrices in a first predetermined period of time or a first predetermined frequency band; and a vertical beamforming vector determining unit configured to determine 2N eigenvectors calculated based on the averaging results as the vertical beamforming vectors.
  • the vertical beamforming vector calculating unit may comprise: a second initial channel matrix dividing unit configured to divide elements of the initial channel matrix into 2N groups, wherein N indicates the number of antennas in a horizontal direction of the first antenna array or the second antenna array; a third horizontal covariance matrix calculating unit configured to calculate 2N vertical covariance matrices of the 2N groups; a third averaging unit configured to average each of the 2N vertical covariance matrices in a first predetermined period of time or a first predetermined frequency band; a second computing unit configured to calculating a sum or a mean value of the averaging results; and a vertical beamforming vector determining unit configured to determine an eigenvector calculated based on the sum or the mean value as each of the vertical beamforming vectors.
  • the vertical beamforming vector calculating unit may comprises: a second initial channel matrix dividing unit configured to divide elements of the initial channel matrix into 2N groups, wherein N indicates the number of antennas in a horizontal direction of the first antenna array or the second antenna array; a third horizontal covariance matrix calculating unit configured to calculate a vertical covariance matrix of one of the 2N groups; a third averaging unit configured to average the vertical covariance matrix in a first predetermined period of time or a first predetermined frequency band; and a vertical beamforming vector determining unit configured to determine an eigenvector calculated based on the averaging result as each of the vertical beamforming vectors.
  • the third determining unit 640 may comprise: a third initial channel matrix dividing unit configured to divide the initial channel matrix into a first channel matrix and a second channel matrix, wherein the first channel matrix is associated with the first antenna array and the second channel matrix is associated with the second antenna array; a composition channel matrix obtaining unit configured to obtain a composition channel matrix based on the first 3D beamforming vector, the second 3D beamforming vector, the first channel matrix and the second channel matrix; a composition covariance matrix calculating unit configured to calculate a composition covariance matrix of the composition channel matrix; a fourth averaging unit configured to average the composition covariance matrix in a third predetermined period of time or a third predetermined frequency band; and a first phase factor matrix determining unit configured to determine the phase factor matrix by performing decomposition based on the averaging results.
  • the third determining unit 640 may comprise: a simplified channel matrix determining unit configured to determine a simplified channel matrix from the initial channel matrix, wherein the simplified channel matrix includes channel parameters associated with a pair of antennas that have different polarizations, wherein one of the pair of antennas belongs to the first antenna array and the other of the pair of antennas belongs to the second antenna array; a simplified covariance matrix calculating unit configured to calculate a simplified covariance matrix of the simplified channel matrix; a fifth averaging unit configured to average the simplified covariance matrix in a third predetermined period of time or a third predetermined frequency band; and a second phase factor matrix determining unit configured to determine the phase factor matrix by performing decomposition based on the averaging results.
  • a simplified channel matrix determining unit configured to determine a simplified channel matrix from the initial channel matrix, wherein the simplified channel matrix includes channel parameters associated with a pair of antennas that have different polarizations, wherein one of the pair of antennas belongs to the first antenna array and the other of the pair of antennas belongs to
  • apparatus 900 may be respectively implemented by any suitable technique either known at present or developed in the future. Further, a single device shown in FIG. 9 may be alternatively implemented in multiple devices separately, and multiple separated devices may be implemented in a single device. The scope of the present invention is not limited in these regards.
  • the apparatus 900 may be configured to implement functionalities as described with reference to FIGs. 2-8. Therefore, the features discussed with respect to the methods 200-800 may apply to the corresponding components of the apparatus 900. It is further noted that the components of the apparatus 900 may be embodied in hardware, software, firmware, and/or any combination thereof. For example, the components of the apparatus 900 may be respectively implemented by a circuit, a processor or any other appropriate device. Those skilled in the art will appreciate that the aforesaid examples are only for illustration not limitation.
  • the apparatus 900 may comprise at least one processor.
  • the at least one processor suitable for use with embodiments of the present disclosure may include, by way of example, both general and special purpose processors already known or developed in the future.
  • the apparatus 900 may further comprise at least one memory.
  • the at least one memory may include, for example, semiconductor memory devices, e.g. , RAM, ROM, EPROM, EEPROM, and flash memory devices.
  • the at least one memory may be used to store program of computer executable instructions.
  • the program can be written in any high-level and/or low-level compliable or interpretable programming languages.
  • the computer executable instructions may be configured, with the at least one processor, to cause the apparatus 900 to at least perform according to any of the method 200 -800 as discussed above.
  • the present disclosure may be embodied in an apparatus, a method, or a computer program product.
  • the various exemplary embodiments may be implemented in hardware or special purpose circuits, software, logic or any combination thereof.
  • some aspects may be implemented in hardware, while other aspects may be implemented in firmware or software which may be executed by a controller, microprocessor or other computing device, although the disclosure is not limited thereto.
  • FIGs. 2-8 may be viewed as method steps, and/or as operations that result from operation of computer program code, and/or as a plurality of coupled logic circuit elements constructed to carry out the associated function (s) .
  • At least some aspects of the exemplary embodiments of the disclosures may be practiced in various components such as integrated circuit chips and modules, and that the exemplary embodiments of this disclosure may be realized in an apparatus that is embodied as an integrated circuit, FPGA or ASIC that is configurable to operate in accordance with the exemplary embodiments of the present disclosure.

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Abstract

Des modes de réalisation de l'invention concernent un procédé et un appareil permettant d'effectuer un filtrage spatial dans un système MIMO. Le procédé peut comprendre les étapes consistant à : obtenir une matrice de canaux initiale sur la base de signaux de référence reçus via les premier et second réseaux d'antennes d'un équipement utilisateur (UE), la matrice de canaux initiale comprenant des paramètres de canal associés à la fois au premier réseau d'antennes et au second réseau d'antennes ; déterminer les vecteurs de filtrage spatial vertical et les vecteurs de filtrage spatial horizontal sur la base de la matrice de canaux initiale ; déterminer un premier vecteur de filtrage spatial en 3D et un second vecteur de filtrage spatial en 3D sur la base des vecteurs de filtrage spatial vertical et des vecteurs de filtrage spatial horizontal, le premier vecteur de filtrage spatial en 3D étant associé à la polarisation du premier réseau d'antennes et le second vecteur de filtrage spatial en 3D étant associé à la polarisation du second réseau d'antennes ; déterminer, au moins en partie sur la base de la matrice de canaux initiale, une matrice de facteurs de phase pour les polarisations du premier réseau d'antennes et du second réseau d'antennes ; et déterminer une matrice de paramètres de filtrage spatial sur la base de la matrice de facteurs de phase, du premier vecteur de filtrage spatial en 3D et du second vecteur de filtrage spatial en 3D.
PCT/CN2015/084246 2015-07-16 2015-07-16 Procédé et appareil permettant d'effectuer un filtrage spatial Ceased WO2017008307A1 (fr)

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CN109120322A (zh) * 2018-06-06 2019-01-01 西安科技大学 多小区多用户3d-mimo波束赋形方法
CN110837075A (zh) * 2019-11-13 2020-02-25 杭州电子科技大学 一种低复杂度的极化参数估计跟踪装置及方法
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WO2024007254A1 (fr) * 2022-07-07 2024-01-11 Nokia Shanghai Bell Co., Ltd. Formation de faisceaux

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