CN108900232B - Adaptive beam forming method and device and electronic equipment - Google Patents
Adaptive beam forming method and device and electronic equipment Download PDFInfo
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- H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
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- H04B7/0615—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission of weighted versions of same signal
- H04B7/0617—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission of weighted versions of same signal for beam forming
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Abstract
The embodiment of the invention relates to the field of communication, and discloses a method and a device for self-adaptive beam forming and electronic equipment. The self-adaptive beam forming method comprises the following steps: determining the distribution of all user equipment in the coverage area of the base station on a two-dimensional plane according to the channel matrixes of all the user equipment in the coverage area of the base station; taking the number of the beams as the number of clusters in a K clustering algorithm, clustering the distribution of all user equipment on a two-dimensional plane by adopting the K clustering algorithm, and determining the clustering result of the clusters corresponding to the number of the beams; determining an optimal weight vector matrix and a radius matrix of the wave beam according to the clustering result; and weighting the antenna array according to the optimal weight vector matrix and the radius matrix to form a self-adaptive beam. The adaptive beamforming method in this embodiment improves the beam positioning capability, thereby improving the cell coverage capability of the base station signal.
Description
Technical Field
The embodiment of the invention relates to the field of communication, in particular to a method and a device for adaptive beam forming and electronic equipment.
Background
Beamforming technology and Massive multiple-input multiple-output antenna technology (Massive MIMO) are core technologies of 5G communication. Beamforming is a combination of antenna technology and digital signal processing technology, intended for directional signal transmission or reception.
Currently, in a 5G architecture, a gob (gob of beam) strategy is generally adopted to improve the signal coverage of a base station to a cell, for example, a coarse beam is designed for a broadcast beam, and a fine beam is designed for a Physical Downlink Shared Channel (PDSCH). Whereas in massive MIMO systems, 5G systems require multi-beam coverage server cells (including broadcast and traffic services).
The inventor finds that at least the following problems exist in the prior art: in order to position the beams in a 3D spatial area to maximize and optimize the coverage of the base station, the "equidistant beam" approach as described above is currently used, or a different kind of coarse beam option is used, as shown in fig. 1. Alternatively, a number of different kinds of beam positions are designed for selection, as shown in fig. 2. However, in real life, because human life and work are regular, power consumption of the same base station in different time periods is different, for example, for the same base station (abbreviated as "eNB"), there are few UEs in a cell covered by the base station in the daytime and many UEs in a cell covered by the base station in the evening, and it is seen that power consumption of the base station in the daytime and in the evening is time-varying, and the base station adopting the two fixed beam positioning schemes consumes energy seriously. Secondly, different base stations have different natural environment characteristics, and a base station adopting a fixed beam positioning scheme cannot be applied to various environments, and has a very large limitation, for example, a base station a is applied to hills, a base station B is applied to rivers, and a coarse beam positioning scheme is beneficial to the base station a but may not be applied to the base station B. User Equipments (UEs) in the serving cell may not be uniquely and evenly distributed, and a base station employing a fixed beam positioning scheme will result in coverage of only a portion of the UEs, affecting the cell coverage of the signal.
Disclosure of Invention
The invention aims to provide a method, a device and an electronic device for adaptive beam forming, which improve the positioning capability of beams so as to improve the cell coverage capability of base station signals.
To solve the above technical problem, an embodiment of the present invention provides an adaptive beamforming method, including: determining the distribution of all user equipment in the coverage area of the base station on a two-dimensional plane according to the channel matrixes of all the user equipment in the coverage area of the base station; taking the number of the beams as the number of clusters in a K clustering algorithm, clustering the distribution of all user equipment on a two-dimensional plane by adopting the K clustering algorithm, and determining the clustering result of the clusters corresponding to the number of the beams; determining an optimal weight vector matrix and a radius matrix of the wave beam according to the clustering result; and weighting the antenna array according to the optimal weight vector matrix and the radius matrix to form a self-adaptive beam.
The embodiment of the invention also provides a device for adaptive beam forming, which comprises: the device comprises a distribution determining module, a clustering result determining module, a matrix determining module and a weighting module; the distribution determining module is used for determining the distribution of all user equipment in the coverage area of the base station on a two-dimensional plane according to the channel matrixes of all the user equipment in the coverage area of the base station;
the clustering result determining module is used for taking the number of the beams as the number of clusters in a K clustering algorithm, clustering the distribution of all the user equipment on a two-dimensional plane by adopting the K clustering algorithm and determining the clustering result of the cluster corresponding to the number of the beams; the matrix determining module is used for determining an optimal weight vector matrix and a radius matrix of the wave beam according to the clustering result; and the weighting module is used for weighting the antenna array according to the optimal weight vector matrix and the radius matrix to form a self-adaptive beam.
An embodiment of the present invention also provides an electronic device, including: at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the above-described method of adaptive beamforming.
Compared with the prior art, the method and the device have the advantages that the distribution of all the user equipment in the coverage area of the base station on the two-dimensional plane is clustered according to the number of the beams in the base station as the number of clusters, the position of the user equipment which can be covered by each beam can be determined through clustering, the optimal weight vector matrix of the beam in the base station can be further determined according to the distribution condition of the user equipment in each cluster, the radius matrix of the beam can be determined according to the radius of each cluster, and the self-adaptive beam is obtained through the optimal vector matrix and the radius matrix, so that the beams in the base station can be ensured to cover all the user equipment under the condition that the user equipment is in time varying, the gain of the beam is improved, and the cell coverage area of the signal is improved.
In addition, the abscissa of the two-dimensional plane indicates the angular range covered by the base station in the horizontal direction, and the ordinate of the two-dimensional plane indicates the angular range covered by the base station in the vertical direction. In the embodiment, the two-dimensional plane can intuitively reflect the position of the user equipment, and meanwhile, the two-dimensional plane is easy to establish a mapping relation with the beam in the base station, so that the position of the user equipment is conveniently clustered.
In addition, determining the distribution of all user equipments in the coverage area of the base station on the two-dimensional plane according to the channel matrices of all user equipments in the coverage area of the base station specifically includes: the channel matrix of each user equipment is processed as follows: searching the position of the user equipment meeting a first preset condition on the two-dimensional plane, wherein the first preset condition is that the distance between a weight vector matrix corresponding to the searched position on the two-dimensional plane and a channel matrix of the user equipment is minimum, and the weight vector matrix comprises a weight vector of a beam pair searched position corresponding to each array element in the base station. In this embodiment, the position of the user meeting the first preset condition is searched on the whole two-dimensional plane through the channel matrix of the user equipment, so that the searched position is the accurate position where the actual position of the user equipment is mapped onto the two-dimensional plane, and the accuracy of the subsequent clustering result is ensured.
In addition, the method for determining the cluster result of the cluster corresponding to the beam number by using the number of the beams as the number of the clusters in the K clustering algorithm and clustering the distribution of all the user equipment on the two-dimensional plane by using the K clustering algorithm specifically comprises the following steps: taking the number of the beams as the number of clusters in a K clustering algorithm, and selecting a first centroid of each cluster from the distribution of all user equipment on a two-dimensional plane; and determining a second centroid of each cluster in the clustering result according to the first centroid of each cluster and the distribution of the user equipment on the two-dimensional plane. In this embodiment, the number of beams is used as the number of clusters in the K clustering algorithm, so that the user equipment finally obtains clusters with the same number as the beams, and each cluster corresponds to a beam, and thus, the weight vector of the cluster adapted to the beam can be determined, and the generated adaptive beam is ensured to be adapted to the distribution situation of various user equipments within the coverage area of the base station.
In addition, determining a second centroid of each cluster in the clustering result according to the first centroid of each cluster and the distribution of the user equipment on the two-dimensional plane specifically includes: step S1: calculating the position of the user equipment contained in each cluster on the two-dimensional plane according to the distribution of all the user equipment on the two-dimensional plane and the first centroid of each cluster; step S2: determining a third centroid of each cluster according to the position of the user equipment contained in each cluster; step S3: and judging whether the currently determined third centroid of each cluster is the same as the first centroid of each cluster, if so, taking the third centroid of each cluster as the second centroid of each cluster in the clustering result, otherwise, taking the third centroid of each cluster as the first centroid of each cluster and returning to execute the step S1. This embodiment provides a specific way of performing clustering.
In addition, according to the clustering result, determining an optimal weight vector matrix and a radius matrix of the beam specifically comprises: acquiring a second centroid of each cluster in the clustering result and a position of user equipment contained in each cluster; respectively calculating the weight vector of a second centroid of the beam pair cluster corresponding to each cluster, and taking a matrix formed by all the calculated weight vectors as an optimal weight vector matrix of the beams; and respectively calculating the radius of each cluster, and taking a matrix formed by the calculated radius of each cluster as a radius matrix of the beam, wherein the radius of each cluster is the maximum distance between the position of the user equipment in the cluster and the second centroid in the cluster. In this embodiment, the weight vector of the beam is calculated according to the position of the centroid of the cluster corresponding to the beam, and the weight vector of the beam corresponding to the centroid of each cluster is calculated and the radius of each cluster is used as the radius of the corresponding beam, so that it is ensured that the subsequently generated beam can uniformly cover the user equipment included in the corresponding cluster, and the situation that some user equipment is covered and some user equipment cannot be covered is avoided.
In addition, after the antenna array is weighted according to the optimal weight vector matrix and the radius matrix to form the adaptive beam, the method further comprises the following steps: checking the coverage range of the generated self-adaptive wave beam according to the radius of each cluster;
and adjusting the coverage range of each self-adaptive beam according to the verification result. In this embodiment, the generated beam is verified by the radius of each cluster, which further ensures the coverage of the generated adaptive beam.
In addition, the weight vector of the second centroid of the beam pair cluster corresponding to each array element is determined according to the position of the second centroid, the distance of the adjacent array element in the horizontal direction, the distance of the adjacent array element in the vertical direction, the position of the array element in the array antenna, and the wavelength of the beam generated by the array element correspondingly.
Drawings
One or more embodiments are illustrated by way of example in the accompanying drawings, which correspond to the figures in which like reference numerals refer to similar elements and which are not to scale unless otherwise specified.
Fig. 1 is a detailed flowchart of a method of adaptive beamforming according to a first embodiment of the present invention;
fig. 2 is a schematic diagram of a two-dimensional plane in the method of adaptive beamforming according to the first embodiment of the present invention;
fig. 3 is a schematic diagram of an antenna array in a method of adaptive beamforming according to a first embodiment of the present invention;
fig. 4 is a detailed flowchart for determining the second centroid of each cluster in the adaptive beamforming method according to the first embodiment of the present invention;
fig. 5 is a diagram illustrating data transmission when the method for adaptive beamforming according to the first embodiment of the present invention is applied to a base station;
FIG. 6 is a schematic diagram of the distribution of user equipment on a two-dimensional plane according to the first embodiment of the present invention;
fig. 7 is a schematic diagram illustrating the effect of the adaptive beamforming method according to the first embodiment of the present invention on a two-dimensional plane;
fig. 8 is a schematic diagram of the effect of the fixed beam forming method on a two-dimensional plane according to the first embodiment of the present invention;
fig. 9 is a schematic diagram for comparing the gain effects of adaptive beamforming and fixed beamforming according to the first embodiment of the present invention;
fig. 10 is a detailed flowchart of a method of adaptive beamforming according to a second embodiment of the present invention;
fig. 11 is a schematic structural diagram of an apparatus for adaptive beamforming according to a third embodiment of the present invention;
fig. 12 is a schematic structural diagram of an electronic device according to a fourth embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention more apparent, embodiments of the present invention will be described in detail below with reference to the accompanying drawings. However, it will be appreciated by those of ordinary skill in the art that numerous technical details are set forth in order to provide a better understanding of the present application in various embodiments of the present invention. However, the technical solution claimed in the present application can be implemented without these technical details and various changes and modifications based on the following embodiments.
A first embodiment of the invention relates to a method of adaptive beamforming. The method of adaptive beamforming applies to base stations employing array antennas. The specific flow is shown in figure 1.
Step 101: and determining the distribution of all user equipment in the coverage area of the base station on a two-dimensional plane according to the channel matrixes of all the user equipment in the coverage area of the base station.
Specifically, the base station may obtain channel matrices of all user equipments in the current coverage area, and it can be understood that the channel matrices are obtained by estimating channels, and assuming that the number of all user equipments in the coverage area of the current base station is N, and N is an integer greater than 1, the channel matrices of all user equipments may be represented as H ═ H1,h2,…hNIn which hiExpressed as a channel matrix for a user equipment, 1 ≦ i ≦ N.
In a specific implementation, the abscissa of the two-dimensional plane represents the angular range covered by the base station in the horizontal direction, and the ordinate of the two-dimensional plane represents the angular range covered by the base station in the vertical direction.
Specifically, in order to reflect the position of the ue relative to the base station, a two-dimensional plane is constructed, and the position of the ue in the rectangular coordinate system is mapped onto the two-dimensional plane, which is shown in fig. 2, wherein fig. 2 illustrates the position of the ue in the rectangular coordinate system
The horizontal axis is represented, the vertical axis is represented by theta, the horizontal axis is represented by the angular range of the coverage of the base station in the horizontal direction,
is in the range of-60 degrees to +60 degrees, theta is in the range of 0 degrees to 180 degrees, and the black dots in fig. 2 represent the position of any one of the two-dimensional planes.
The following describes in detail a process of determining a location of a user equipment on a constructed two-dimensional plane according to a channel matrix of the user equipment.
In a specific implementation, the location of the ue meeting a first preset condition is searched on the two-dimensional plane, where the first preset condition is that a distance between a weight vector matrix corresponding to the searched location on the two-dimensional plane and a channel matrix of the ue is minimum, and the weight vector matrix includes a weight vector of a beam pair corresponding to each array element in the base station to the searched location.
Specifically, there are countless positions on the two-dimensional plane, and the searching process is to traverse all the positions on the two-dimensional plane, in this embodiment, for the convenience of searching, 1 degree on the horizontal axis is taken as 1 interval, and 1 degree on the vertical axis is also taken as 1 interval, so that there are 120 × 180 positions on the two-dimensional plane, and it is determined whether the coordinates of each position satisfy the first preset condition, if not, the traversal is continued, otherwise, the position satisfying the first preset condition is taken as the searched position. The first preset condition may be expressed as formula (1):
wherein p (phi, theta) represents that an objective function meeting a first preset condition is searched, and hiA channel matrix, w, representing any user equipment within the coverage area of the base stationφ,θA weight vector matrix, w, representing the base stationφ,θEach element in (a) is represented as w (n)v,nh)，w(nv,nh) Is as formula (2)
In the formula (2), λ represents the wavelength of the beam, nhAnd nvThe number of antennas in the vertical direction and the number of antennas in the horizontal direction in the antenna array are respectively represented by nhAnd nvThe position of each antenna in the antenna array can be shown, e.g. as shown in fig. 3, then (n)h＝5，nv＝4) That is, the position where the number of antennas (array elements) of the array antenna in the horizontal direction is 5 and the position where the number of antennas in the vertical direction is 4 are shown. dhRepresenting the distance between two adjacent array elements in the vertical direction, dvIndicating the distance between two adjacent array elements in the horizontal direction.
The search process is described below in a specific example:
for example, the channel matrix of one user equipment A is h2And searching the corresponding position of the user equipment A on a two-dimensional plane. Traversing all the positions on the two-dimensional plane and judging the traversed point Xi(phi, theta) and the channel matrix h2If the distance between the user equipment and the user equipment is the minimum, the process of determining the user equipment on the two-dimensional plane is as follows: substituting any point belonging to the two-dimensional plane into formula (2) to calculate the weight vector matrix w corresponding to the antenna arrayφ,θW to be calculatedφ,θCarry in | | wφ,θ-h2||2To obtain the point and h2The minimum value of the calculated distances is selected as the searched position.
And regarding the channel matrix of each user equipment, taking the searched position meeting the first preset condition as the position of each user equipment on the two-dimensional plane, and obtaining the distribution of the user equipment on the two-dimensional plane.
Step 102: and taking the number of the beams as the number of clusters in a K clustering algorithm, clustering the distribution of all the user equipment on a two-dimensional plane by adopting the K clustering algorithm, and determining the clustering result of the clusters corresponding to the number of the beams.
In a specific implementation, the number of beams is used as the number of clusters in a K-clustering algorithm, and a first centroid of each cluster is selected from the distribution of all user equipments on a two-dimensional plane; and determining a second centroid of each cluster in the clustering result according to the first centroid of each cluster and the distribution of the user equipment on the two-dimensional plane.
Specifically, the K clustering algorithm needs to set the number of clusters, and in this embodiment, the number of clusters is set as the number of beams generated by the base station. The distribution of the user equipment on the two-dimensional plane can be clustered by a clustering algorithm. Because the number of the clusters is the same as the number of the beams, one cluster can be regarded as a beam coverage range, and then the weight vector adaptive to the beams can be determined according to the distribution of the user equipment in each cluster, so that the generated adaptive beams are ensured to be adaptive to the distribution condition of the user equipment in the base station coverage range.
Before the K clustering algorithm starts, a first centroid may be set for each cluster, and the setting may be performed by randomly selecting the first centroid of each cluster from a distribution of all user equipments on a two-dimensional plane, for example, the distribution of all user equipments on the two-dimensional plane is represented as X ═ X1,x2,…xNEach element in X represents the position of user equipment on the two-dimensional plane, and if the number of beams is K, K X elements are randomly selected from XiAs the centroid of each cluster. Of course, the first centroid may also be selected from the distribution of all the user equipments on the two-dimensional plane according to a certain rule, for example, the area where all the user equipments are distributed on the two-dimensional plane is divided into N sub-areas, and the central point of each sub-area is selected as the first centroid of each cluster, where N is the same as the number of beams (the number of clusters).
It is to be understood that the skilled person may select the first centroid of each cluster from the distribution of all the user equipments on the two-dimensional plane in other ways, which is not limited by the present embodiment.
The process of determining the second centroid of each cluster in the clustering result according to the first centroid of each cluster and the distribution of the user equipment on the two-dimensional plane will be described in detail below. The specific flow of the process of determining the second centroid for each cluster is shown in fig. 4.
Step 1021: and calculating the position of the user equipment contained in each cluster on the two-dimensional plane according to the distribution of all the user equipment on the two-dimensional plane and the first centroid of each cluster.
The following describes a process of specifically calculating the location of the user equipment included in each cluster:
the distribution of all user equipments on the two-dimensional plane is denoted X ═ X1,x2,…xNThe first centroid of each cluster is denoted as { c }1,c2,…cK}, if x is now determined1The clusters to which x belongs can be calculated respectively1To the first centroid c of each cluster j1 ≦ j ≦ K, e.g., calculating x1And c1A distance d between1,1Calculating x1To the first centroid c of each clusterjAfter a distance of (d), obtain { d1,1，d1,2……d1,kIn which d is1,3Is the smallest value of (b), then x1Belong to c3I.e. x1Belong to { d1,1，d1,2……d1,kThe first centroid corresponding to the minimum value in the central region. And other elements in the X can determine the position of the user equipment contained in each cluster according to the steps.
Step 1022: determining a third centroid for each cluster based on the location of the user equipment contained in each cluster.
Specifically, a mean value of the location of the user equipment to which each cluster belongs may be calculated as the third centroid of each cluster, for example, the mean value of the location of the user equipment to which each cluster belongs may be calculated using formula (3).
Wherein S isjIndicated as the location of the user equipment comprised by one cluster.
Step 1023: and judging whether the currently determined third mass center of each cluster is the same as the first mass center of each cluster, if so, executing the step 1024, otherwise, executing the step 1025.
Specifically, if the third centroid of a cluster is the same as the second centroid of the cluster, it indicates that the current cluster has completed clustering and the centroid of the cluster does not change. And if the third centroid of one cluster is not the same as the second centroid of the cluster, indicating that the current cluster is not clustered.
Step 1024: and taking the third centroid of each cluster as the second centroid of each cluster in the clustering result.
Step 1025: the third centroid of each cluster is taken as the first centroid of each cluster and the process returns to step 1021.
Specifically, if the third centroid of a cluster is different from the first centroid of the cluster, the third centroid of the cluster is taken as the first centroid of the cluster, and the process continues to step 1021.
Step 103: and determining an optimal weight vector matrix and a radius matrix of the beam according to the clustering result.
In a specific implementation, a second centroid of each cluster and a location of a user equipment included in each cluster in a clustering result are obtained; and respectively calculating the weight vector of the second centroid of the beam pair cluster corresponding to each cluster, and taking a matrix formed by all the calculated weight vectors as the optimal weight vector matrix of the beam. And (3) determining a weight vector of the beam corresponding to each array element to the second centroid of the cluster according to the position of the second centroid, the distance of the adjacent array elements in the horizontal direction, the distance of the adjacent array elements in the vertical direction, the position of the array element in the array antenna and the wavelength of the beam generated by the array element correspondingly, as shown in formula (2).
Respectively calculating a weight vector of the second centroid of the beam corresponding to each cluster, which can be obtained by calculating using formula (2), for example, cluster SjHas a center of mass of Cj(
θj) Then, the weight vector calculation of the jth beam is calculated using equation (2). Wherein n in the formula (2)hAnd nvCan be given a value ofjAnd (4) learning. And taking a matrix formed by all the calculated weight vectors as an optimal weight vector matrix of the beam.
And respectively calculating the radius of each cluster, and taking a matrix formed by all the calculated radii as a radius matrix of the beam, wherein the radius of each cluster is the maximum distance between the position of the user equipment in the cluster and a second centroid in the cluster. Specifically, the process of calculating the radius of each cluster is as follows: and respectively calculating the distance from the position of each user equipment contained in the cluster to the centroid of the cluster, and selecting the value with the maximum distance as the radius of the cluster. Such as: cluster SjHas a center of mass of CjThen cluster SjRadius of (2)
Wherein i represents a cluster SjSubscript of the belonging user equipment.
Step 104: and weighting the antenna array according to the optimal weight vector matrix and the radius matrix to form a self-adaptive beam.
Specifically, the solved optimal weight vector matrix and radius matrix are weighted with the array antenna of the base station, and then the adaptive beam can be formed.
It should be noted that the method for adaptive beamforming in this embodiment is applied to a base station employing an array antenna, where steps 101 to 102 in the above steps may be applied to a base band processing unit (BBU) of the base station, the BBU sends a matrix formed by a second centroid of each cluster and a radius matrix formed by a radius of each cluster, which are obtained by calculation, to a Radio Remote Unit (RRU), and the RRU executes steps 103 to 104, that is, the RRU calculates a weight vector matrix and a radius matrix, and weights the antenna array with the calculated weight vector matrix and radius matrix to form an adaptive beam, fig. 5 is a schematic diagram of data transmission between the BBU and the RRU, and fig. 5 can be seen from fig. 5Out, the BBU acquires a channel matrix for each user equipment (i.e., "H ═ H)1……hN} ") and calculates a second centroid of each cluster and a radius of each cluster, and a matrix of the second centroids and a matrix of the radii of each cluster are formed (in this embodiment," [ C ] is usedj，Dj]The form sending weight vector matrix and the radius matrix) to the BBU, and the BBU forms the self-adaptive wave beam.
The following is a diagram illustrating the effect of the adaptive beamforming method in the present embodiment when the number of user equipments in the coverage area of the base station is 100.
It will be appreciated that in order to simulate the randomness of the distribution of user equipment within the coverage area of a base station in real life, 100 user equipment are randomly generated in this example. The base station acquires the channel matrixes of 100 pieces of user equipment, and then 100 channel matrixes are expressed as H ═ H1……h100In which hiRepresenting the channel matrix of the ith user equipment, wherein i is more than or equal to 1 and less than or equal to 100; and after step 101, the distribution of 100 pieces of user equipment on a two-dimensional plane is obtained, as shown in fig. 6. Based on the determined distribution of 100 ues on the two-dimensional plane and the number of beams of the base station (the number of beams is 8), the adaptive beams generated through steps 102 to 104 are as shown in fig. 7. Fig. 8 shows a fixed beam generated by a base station, and it can be seen from fig. 7 and 8 that the adaptive beam generated in the present embodiment can completely cover all user equipments. Fig. 9 is a graph showing a comparison between the gain effect of the fixed beam and the beam generated in the present embodiment (in fig. 9, the fixed beam is a broken line, and the adaptive beam is a solid line). As can be seen from fig. 9, the gain of the generated adaptive beam in the present embodiment is higher than that of the fixed beam.
Compared with the prior art, the method and the device have the advantages that the distribution of all the user equipment in the coverage area of the base station on the two-dimensional plane is clustered according to the number of the beams in the base station as the number of clusters, the position of the user equipment which can be covered by each beam can be located through clustering, the optimal weight vector matrix of the beam in the base station can be further determined according to the distribution condition of the user equipment in each cluster, the radius matrix of the beam can be determined according to the radius of each cluster, and the self-adaptive beam is obtained through the optimal vector matrix and the radius matrix, so that the beams in the base station can be ensured to cover all the user equipment under the condition that the user equipment is in time varying, the gain of the beam is improved, and the cell coverage area of the signal is improved.
A second embodiment of the invention relates to a method of adaptive beamforming. The second embodiment is a further improvement of the first embodiment, and the main improvements are as follows: in the second embodiment of the present invention, after the antenna array is weighted according to the optimal weight vector matrix and the radius matrix to form the adaptive beam, the method further includes checking a coverage area of the generated adaptive beam according to a radius of each cluster. The specific flow of the adaptive beamforming method is shown in fig. 10.
Step 201: and determining the distribution of all user equipment in the coverage area of the base station on a two-dimensional plane according to the channel matrixes of all the user equipment in the coverage area of the base station.
Step 202: and taking the number of the beams as the number of clusters in a K clustering algorithm, clustering the distribution of all the user equipment on a two-dimensional plane by adopting the K clustering algorithm, and determining the clustering result of the clusters corresponding to the number of the beams.
Step 203: and determining the optimal weight vector matrix of the wave beam according to the clustering result.
Step 204: and weighting the antenna array according to the optimal weight vector matrix to form a self-adaptive beam.
Step 205: the range covered by the generated adaptive beam is checked according to the radius of each cluster.
Specifically, the radius of the beam corresponding to each cluster is obtained and compared with the radius of the cluster corresponding to each beam, if the radius of the beam is smaller than the radius of the cluster, it is indicated that the beam cannot cover the cluster, and if the radius of the beam is larger than or equal to the radius of the cluster, it is indicated that the beam can cover the cluster.
Step 206: and adjusting the coverage range of each self-adaptive beam according to the verification result.
Specifically, if the radius of the beam is smaller than the radius of the cluster, the radius of the beam is increased, otherwise, the radius of the beam may be adjusted smaller or not.
It should be noted that step 201, step 203 to step 204 in this embodiment are substantially the same as step 101, step 103 to step 104 in the first embodiment, and are not described again here.
In the method for adaptive beamforming provided in this embodiment, the generated beam is verified by the radius of each cluster, and the generated adaptive beam is adjusted according to the verification result, so that the coverage of the generated adaptive beam is further ensured.
The steps of the above methods are divided for clarity, and the implementation may be combined into one step or split some steps, and the steps are divided into multiple steps, so long as the same logical relationship is included, which are all within the protection scope of the present patent; it is within the scope of the patent to add insignificant modifications to the algorithms or processes or to introduce insignificant design changes to the core design without changing the algorithms or processes.
The third embodiment of the present invention relates to an adaptive beamforming apparatus 30, which includes: a distribution determination module 301, a clustering result determination module 302, a matrix determination module 303, and a weighting module 304. The specific structure is shown in fig. 11.
A distribution determining module 301, configured to determine, according to channel matrices of all user equipments in a coverage area of a base station, distribution of all user equipments in the coverage area of the base station on a two-dimensional plane; a clustering result determining module 302, configured to use the number of beams as the number of clusters in a K clustering algorithm, and cluster the distribution of all user equipments on a two-dimensional plane by using the K clustering algorithm, so as to determine a clustering result of a cluster corresponding to the number of beams; a matrix determining module 303, configured to determine an optimal weight vector matrix and a radius matrix of the beam according to the clustering result; and the weighting module 304 is configured to weight the antenna array according to the optimal weight vector matrix and the radius matrix to form a self-adaptive beam.
Compared with the prior art, the method and the device have the advantages that the distribution of all the user equipment in the coverage area of the base station on the two-dimensional plane is clustered according to the number of the beams in the base station as the number of the clusters, the user equipment which can be covered by each beam can be determined through clustering, the optimal weight vector matrix of the beam in the base station can be further determined according to the distribution condition of the user equipment in each cluster, the radius matrix of the beam can be determined according to the radius of each cluster, and the self-adaptive beam is obtained through the optimal vector matrix and the radius matrix, so that the beams in the base station can be ensured to cover all the user equipment under the condition that the user equipment is in time varying, and the coverage area of a signal cell is improved.
It should be understood that this embodiment is an example of the apparatus corresponding to the first embodiment, and may be implemented in cooperation with the first embodiment. The related technical details mentioned in the first embodiment are still valid in this embodiment, and are not described herein again in order to reduce repetition. Accordingly, the related-art details mentioned in the present embodiment can also be applied to the first embodiment.
It should be noted that each module referred to in this embodiment is a logical module, and in practical applications, one logical unit may be one physical unit, may be a part of one physical unit, and may be implemented by a combination of multiple physical units. In addition, in order to highlight the innovative part of the present invention, elements that are not so closely related to solving the technical problems proposed by the present invention are not introduced in the present embodiment, but this does not indicate that other elements are not present in the present embodiment.
A fourth embodiment of the present invention relates to an electronic apparatus 40 including: at least one processor 401; and a memory 402 communicatively coupled to the at least one processor 401; the memory 402 stores instructions executable by the at least one processor 401, and the instructions are executable by the at least one processor 401 to enable the at least one processor 401 to perform the above-described adaptive beamforming method. The specific structure is shown in fig. 12.
The memory 402 and the processor 401 are connected by a bus, which may include any number of interconnected buses and bridges that link one or more of the various circuits of the processor 401 and the memory 402. The bus may also link various other circuits such as peripherals, voltage regulators, power management circuits, and the like, which are well known in the art, and therefore, will not be described any further herein. A bus interface provides an interface between the bus and the transceiver. The transceiver may be one element or a plurality of elements, such as a plurality of receivers and transmitters, providing a means for communicating with various other apparatus over a transmission medium. The data processed by the processor 401 may be transmitted over a wireless medium via an antenna, which may receive the data and transmit the data to the processor 401.
The processor 401 is responsible for managing the bus and general processing and may provide various functions including timing, peripheral interfaces, voltage regulation, power management, and other control functions. And memory 402 may be used to store data used by processor 401 in performing operations.
Those skilled in the art can understand that all or part of the steps in the method of the foregoing embodiments may be implemented by a program to instruct related hardware, where the program is stored in a storage medium and includes several instructions to enable a device (which may be a single chip, a chip, etc.) or a processor (processor) to execute all or part of the steps of the method described in the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
It will be understood by those of ordinary skill in the art that the foregoing embodiments are specific examples for carrying out the invention, and that various changes in form and details may be made therein without departing from the spirit and scope of the invention in practice.
Claims (10)
1. A method for adaptive beamforming, applied to a base station, comprising:
determining the distribution of all user equipment in the coverage area of a base station on a two-dimensional plane according to the channel matrixes of all the user equipment in the coverage area of the base station;
taking the number of the beams as the number of clusters in a K clustering algorithm, clustering the distribution of all the user equipment on a two-dimensional plane by adopting the K clustering algorithm, and determining the clustering result of the clusters corresponding to the number of the beams;
determining an optimal weight vector matrix and a radius matrix of the wave beam according to the clustering result;
and weighting the antenna array according to the optimal weight vector matrix and the radius matrix to form a self-adaptive beam.
2. The method of adaptive beamforming according to claim 1, wherein the abscissa of the two-dimensional plane represents the angular range covered by the base station in the horizontal direction, and the ordinate of the two-dimensional plane represents the angular range covered by the base station in the vertical direction.
3. The method according to claim 2, wherein the determining, according to the channel matrix of all the ues in the coverage area of the base station, the distribution of all the ues in the coverage area of the base station on the two-dimensional plane comprises:
the channel matrix of each user equipment is processed as follows:
searching the position of the user equipment meeting a first preset condition on the two-dimensional plane, wherein the first preset condition is that the distance between a weight vector matrix corresponding to the searched position on the two-dimensional plane and a channel matrix of the user equipment is minimum, and the weight vector matrix comprises weight vectors of beams corresponding to each array element in the base station to the searched position;
wherein the first preset condition is represented as:
p (phi, theta) represents the objective function which is searched to meet the first preset condition, hiA channel matrix, w, representing any user equipment within the coverage area of the base stationφ,θRepresenting the weight vector matrix of the base station.
4. The method according to any one of claims 1 to 3, wherein the number of beams is taken as the number of clusters in a K-clustering algorithm, and the K-clustering algorithm is used to cluster the distribution of all the user equipments on a two-dimensional plane, and the clustering result of the cluster corresponding to the number of beams is determined, specifically comprising:
taking the number of the beams as the number of clusters in a K clustering algorithm, and selecting a first centroid of each cluster from the distribution of all user equipment on a two-dimensional plane;
and determining a second centroid of each cluster in the clustering result according to the first centroid of each cluster and the distribution of the user equipment on the two-dimensional plane.
5. The method of adaptive beamforming according to claim 4, wherein determining the second centroid of each cluster in the clustering result according to the first centroid of each cluster and the distribution of the user equipment on the two-dimensional plane comprises:
step S1: calculating the position of the user equipment contained in each cluster on the two-dimensional plane according to the distribution of all the user equipment on the two-dimensional plane and the first centroid of each cluster;
step S2: determining a third centroid of each cluster according to the position of the user equipment contained in each cluster;
step S3: and judging whether the currently determined third centroid of each cluster is the same as the first centroid of each cluster, if so, taking the third centroid of each cluster as the second centroid of each cluster in the clustering result, otherwise, taking the third centroid of each cluster as the first centroid of each cluster and returning to execute the step S1.
6. The method according to claim 5, wherein determining an optimal weight vector matrix and a radius matrix of the beam according to the clustering result specifically comprises:
acquiring a second centroid of each cluster in the clustering result and a position of user equipment contained in each cluster;
respectively calculating weight vectors of the wave beams corresponding to each cluster to a second centroid of the cluster, and taking a matrix formed by all the calculated weight vectors as an optimal weight vector matrix of the wave beams;
and respectively calculating the radius of each cluster, and taking a matrix formed by the calculated radius of each cluster as a radius matrix of the beam, wherein the radius of each cluster is the maximum distance between the position of the user equipment of the cluster and the second centroid of the cluster.
7. The method of adaptive beamforming according to claim 6, wherein the weighting the antenna array according to the optimal weight vector matrix and the radius matrix further comprises:
checking the coverage range of the generated self-adaptive wave beam according to the radius of each cluster;
and adjusting the coverage range of each self-adaptive beam according to the verification result.
8. The method of adaptive beamforming according to claim 6 or 7, wherein the weight vector of the beam corresponding to each array element to the second centroid of the cluster is determined according to the position of the second centroid, the distance between adjacent array elements in the horizontal direction, the distance between adjacent array elements in the vertical direction, the position of an array element in the array antenna, and the wavelength of the beam generated by the array element.
9. An apparatus for adaptive beamforming, comprising: the device comprises a distribution determining module, a clustering result determining module, a matrix determining module and a weighting module;
the distribution determining module is used for determining the distribution of all user equipment in the coverage area of the base station on a two-dimensional plane according to the channel matrixes of all the user equipment in the coverage area of the base station;
the clustering result determining module is used for taking the number of the beams as the number of clusters in a K clustering algorithm, clustering the distribution of all the user equipment on a two-dimensional plane by adopting the K clustering algorithm, and determining the clustering result of the cluster corresponding to the number of the beams;
the matrix determination module is used for determining an optimal weight vector matrix and a radius matrix of the wave beam according to the clustering result;
and the weighting module is used for weighting the antenna array according to the optimal weight vector matrix and the radius matrix to form a self-adaptive beam.
10. An electronic device, comprising:
at least one processor; and the number of the first and second groups,
a memory communicatively coupled to the at least one processor; wherein,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of adaptive beamforming according to any of claims 1-8.
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| CN112689329A (en) * | 2019-10-17 | 2021-04-20 | 北京三星通信技术研究有限公司 | Beam configuration method and device, electronic equipment and computer storage medium |
| CN113258971B (en) * | 2020-02-11 | 2024-03-01 | 上海华为技术有限公司 | Multi-frequency combined beam forming method, device, base station and storage medium |
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