CN114142986B - Uplink and downlink channel reciprocity air interface calibration method based on access point grouping - Google Patents
Uplink and downlink channel reciprocity air interface calibration method based on access point grouping Download PDFInfo
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L7/00—Arrangements for synchronising receiver with transmitter
- H04L7/02—Speed or phase control by the received code signals, the signals containing no special synchronisation information
- H04L7/033—Speed or phase control by the received code signals, the signals containing no special synchronisation information using the transitions of the received signal to control the phase of the synchronising-signal-generating means, e.g. using a phase-locked loop
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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
- H04B7/0413—MIMO systems
- H04B7/0452—Multi-user MIMO systems
Abstract
The invention discloses an uplink and downlink channel reciprocity air interface calibration method based on access point grouping. Comprising the following steps: step 1, dividing a plurality of access points into two groups according to the positions of the access points; step 2, mutually receiving and transmitting calibration pilot signals between the two groups, and estimating two channel matrixes according to the received pilot signals; and 3, calculating a calibration matrix according to the channel matrixes estimated by the two groups of access points. The invention utilizes the positions among the access points to ensure that each access point has better reference access point as much as possible, thereby obtaining better calibration performance in the joint calibration.
Description
Technical Field
The invention belongs to the technical field of wireless communication transmission, and particularly relates to an uplink and downlink channel reciprocity air interface calibration method based on access point grouping.
Background
With the large-scale increase of users and antennas in MIMO systems, the acquisition of channel state information becomes a major challenge. The time division duplex (TDD, time Division Duplexing) system can utilize the characteristics of air channel reciprocity to greatly reduce the pilot overhead of the system. But the actual channel upstream and downstream is no longer reciprocal due to the asymmetry of the transmit and receiver Radio Frequency (RF) links. The RF gain is compensated, i.e. reciprocity calibrated, when the downstream precoding technique is employed.
For a large-scale distributed MIMO system of 6G, the time cost of traditional alternate transmission calibration is large and the implementation difficulty is also large because the number of access points is increased in a large scale. To reduce the time overhead of calibration, access points may be grouped into multiple groups for inter-group calibration. In the grouping calibration, the most basic implementation is to divide the two groups. The two groups are mutually referenced, so that the calculation of the calibration coefficients of all access points is realized. However, since there is a certain physical distance between the access points, the channel estimated after the pilot signal is subjected to large-scale fading is not accurate enough, which will seriously affect the accuracy of the calibration algorithm.
Careful design of the grouping algorithm is required to achieve better calibration performance. The complexity of an exhaustive search for optimal packets is not affordable when actually implemented.
Disclosure of Invention
The invention aims to provide an uplink and downlink channel reciprocity air interface calibration method based on access point grouping, which aims to solve the technical problem that the complexity of exhaustive searching of optimal grouping is difficult to bear in actual realization.
In order to solve the technical problems, the specific technical scheme of the invention is as follows:
an uplink and downlink channel reciprocity air interface calibration method based on access point grouping comprises the following steps:
step 1, dividing a plurality of access points into two groups according to the positions of the access points;
step 1.1, finding an access point a farthest from the sum of the distances of other access points 1 And separation a 1 Nearest access point b 1 Access point a 1 Grouping access point b into group A 1 Grouping into group B;
step 1.2, continuously searching p which is farthest from the sum of the distances of other access points in the uncategorized access points and an access point q which is closest to the uncategorized access points, calculating the minimum distance minA from p to the existing access points in the group A, and calculating the minimum distance minB from p to the existing access points in the group B; if MinA is large, p is divided into a group A, and q is divided into a group B; if MinA is large, q is divided into a group A, and p is divided into a group B;
step 1.3, searching by the operation until all access points are grouped;
step 2, mutually receiving and transmitting calibration pilot signals between the two groups, and estimating two channel matrixes according to the received pilot signals;
and 3, calculating a calibration matrix according to the channel matrixes estimated by the two groups of access points.
Further, in the step 1.1, the access point with the farthest sum of the distances from other access points is realized by summing the matrix D according to columns to find the index idx1 of the largest element; and putting the corresponding access point idx1 into the A set, finding out the smallest element index idx2 in the D matrix idx1 row, putting the corresponding access point idx2 into the B set, and enabling the number of the ungrouped access points to be R=N-2.
Further, the two channel matrices in the step 2 are:
where H is the air channel when group A transmits group B, H T Is the aerial signal when B group sends A group, H and H T The method has reciprocity and is a transposed relation; c (C) A,t Is a transmit RF gain diagonal matrix for group A antennas, C B,t Is a transmit RF gain diagonal matrix for group B antennas, C A,r Is a diagonal matrix of the received RF gain for the A group antenna, C B,r Is a diagonal matrix of receive RF gain for the B group antenna.
Further, the step 3 specifically includes the following steps:
step 3.1, after obtaining the estimation of two channel matrixes between A and B, constructing the following objective function:
where vec is the vectorization operator, G B,A Is the channel when group A sends group B, G A,B Is the channel when B group sends A group, C A Is the calibration matrix of the A group antenna, C B Is the calibration matrix for the group B antennas;
step 3.2, constructing a matrix of psi:
wherein:
i.e. for G B,A The modules of the elements are squared and summed in columns, and then the junctionFruit transformation of the matrix, N 1 The number of the antennas of the group B;
i.e. for G A,B The modules of the elements are squared and summed in columns, and the result is then converted into a pair of angular arrays, N 2 The number of the antennas of the group A;
refers to the pair [ G ] B,A ] v,u Conjugation is taken;
is to be t 12 Performing conjugate transposition;
step 3.3, decomposing eigenvalues of the psi matrix:
Ψ＝UΛU H ；
in the U matrix, a feature vector corresponding to the minimum feature value is used as a final calibration vector ccal; the calibration vectors are divided into two groups,final calibration matrix C A And C B Denoted as C A ＝diag(c A )，C B ＝diag(c B ) Wherein diag () represents the vector generation diagonal matrix.
The uplink and downlink channel reciprocity air interface calibration method based on the access point grouping has the following advantages:
1. the invention makes the geometric distance between the two groups of antennas of receiving and transmitting minimum grouping mode, the geometric distance between the two groups of antennas of receiving and transmitting minimum causes the large-scale fading that the calibration signal experiences to reduce, the calibration coefficient will estimate more accurately too, the downlink transmission capacity is promoted greatly;
2. the invention is simpler and easier to implement than the exhaustive algorithm.
Drawings
FIG. 1 is a schematic diagram of a packet alignment procedure according to the present invention;
FIG. 2 is a schematic diagram of the calibration performance of the present invention.
Detailed Description
In order to better understand the purpose, structure and function of the present invention, the following describes in further detail an uplink and downlink channel reciprocity air interface calibration method based on access point grouping with reference to the accompanying drawings.
Step 1, dividing a plurality of access points into two groups according to the positions of the access points;
FIG. 1 shows a schematic flow chart of the execution of the group calibration of the present invention, comprising the following steps:
step 1.1, initializing: calculating a distance matrix D from N access point positions, wherein the dimension of the matrix is N multiplied by N, and the element D ij The Euclidean distance from the access point i to the access point j;
step 1.2, finding the access point with the farthest sum of the distances from other access points, and the implementation method comprises the following steps: the matrix D sums by column to find the index idx1 of the largest element. The corresponding access point idx1 is put into the A set, the minimum element index idx2 in the D matrix idx1 row is found, and the corresponding access point idx2 is put into the B set. Let the number of non-grouped access points be r=n-2;
step 1.3, performing the following operations on the access points which are not grouped yet:
step 1.3.1, recalculating a distance matrix D, wherein the dimension of the matrix is R multiplied by R, and the distance matrix is obtained by removing the grouped access points;
step 1.3.2, summing the matrix D according to columns to find the index idx1 of the largest element, and finding the index idx2 of the smallest element in the row of the matrix idx1 of the matrix D;
step 1.3.3, finding out the distance between the access point idx1 and the existing access point in the A set, finding out the minimum distance minA, finding out the minimum distance minB from the B set, if minA > minB, putting the access point idx1 into the A set, and putting the idx2 into the B set, and the same is the same.
Step 1.3.4, r=r-2. Returning to step 1.3.1 until r=0.
If N is an odd number, the minimum distance minA and minB between the last access point to be allocated and the existing access points in the A group and the B group can be obtained, and if the minA is more than or equal to the minB, the access points are separated into the A group; otherwise, the group B is divided.
Step 2, mutually receiving and transmitting calibration pilot signals between the two groups, and estimating two channel matrixes according to the received pilot signals;
in the distributed massive MIMO scenario, since each access point is located in a different geographic location, the effect of mutually transceiving calibration signals for reciprocity calibration in the calibration stage is mainly affected by large-scale fading, where the large-scale fading mainly refers to path loss, so that the signal power after the fading is:
SNR f is the signal-to-noise ratio after large-scale fading, d is the Euclidean distance between antennas, d 0 Is the reference point and α is the path loss index, it can be seen that the larger d is, the more severe the large-scale fading between the antennas will affect the transmission of the calibration signal, and the channel gain between the two antennas can be expressed as follows:
where v-N (0, 1) are complex random variables subject to a normal distribution with a mean of 0 and a variance of 1.
The actual channel is thus modeled as:
G B,A ＝C B,r H C A,t
G A,B ＝C A,r H T C B,t
where H is the air channel when group A transmits group B, H T The air signal in the A group is transmitted by the B group, and the two channels have reciprocity according to reciprocity and are transposed. C (C) A,t Is a transmit RF gain diagonal matrix for group A antennas, C B,t Is a transmit RF gain diagonal matrix for group B antennas, C A,r Is a diagonal matrix of the received RF gain for the A group antenna, C B,r Is a diagonal matrix of receive RF gain for the B group antenna.
And 3, calculating a calibration matrix according to the channel matrixes estimated by the two groups of access points.
And 3.1, obtaining two channel matrixes between A and B, and then obtaining a calibration vector by using the following algorithm. The objective function is constructed as:where vec is the vectorization operator.
The following unconstrained model can be rewritten:
wherein,c A denoted as c A ＝diag(C A )，c B Denoted as c B ＝diag(C B )。
Since ψ is a Hermitian matrixWherein the calibration vector lambda min Is the minimum eigenvalue of ψ, λ max Is the maximum eigenvalue of ψ. And c to be solved cal And the feature vector corresponding to the minimum feature value of the psi is obtained.
Step 3.2, constructing a matrix of psi:
wherein:
i.e. for G B,A The modules of the elements are squared and summed in columns, and the result is then converted into a pair of angular arrays, N 1 The number of the antennas of the group B;
i.e. for G A,B The modules of the elements are squared and summed in columns, and the result is then converted into a pair of angular arrays, N 2 The number of the antennas of the group A;
refers to the pair [ G ] B,A ] v,u Conjugation is taken;
is to be t 12 Performing conjugate transposition;
step 3.3, decomposing eigenvalues of the psi matrix:
Ψ＝UΛU H
in the U matrix, a feature vector corresponding to the minimum feature value is taken as a final calibration vector c cal The method comprises the steps of carrying out a first treatment on the surface of the Note that the calibration vectors are divided into two groups, i.eFinal calibration matrix C A And C B Denoted as C A ＝diag(c A )，C B ＝diag(c B ) Wherein diag () represents the vector generation diagonal matrix.
Step 4, verifying the system capacity through precoding;
with ZF precoding, the received signal is:
wherein the method comprises the steps ofIs a signal sent out by the base station side after being precoded, G UL Is an uplink channel, G DL Is the downlink channel () * Representing the conjugation of matrix elements () T Representing the transpose of the matrix, x is the data to be transmitted before precoding, c=diag (C cal ) N is noise and β is a power normalization factor:
the calibration matrix estimated using the calibration algorithm described above is a pair ofIs similar to C BS,r Is a diagonal array of the receive RF gain of the BS-side antenna, < >>Is the inverse of the transmit RF gain diagonal. And substituting:
G UL ＝C BS,r H T C UE,t
G DL ＝C UE,r H C BS,t
wherein C is UE,r Is the received RF increase of the UE-side antennaThe beneficial effect of the diagonal array is that,the antenna at the UE side transmits RF gain diagonal array;
the method comprises the following steps:
it can be seen that the RF gain matrix of the BS side antenna is eliminated, achieving the purpose of partial calibration.
Fig. 2 shows a comparison of the packet calibration method proposed in this patent with the capacity of a conventional packet calibration channel. Compared with the traditional grouping calibration, the grouping strategy of the patent has the advantages that the channel capacity is greatly improved, the system capacity is improved by about 20% when the signal-to-noise ratio is 20dB, and the system capacity is more approximate to the ideal calibration (the ideal calibration requires known RF gain and cannot be realized in practice).
It will be understood that the invention has been described in terms of several embodiments, and that various changes and equivalents may be made to these features and embodiments by those skilled in the art without departing from the spirit and scope of the invention. In addition, many modifications may be made to adapt a particular situation or material to the teachings of the invention without departing from the essential scope thereof. Therefore, it is intended that the invention not be limited to the particular embodiment disclosed, but that the invention will include all embodiments falling within the scope of the appended claims.
Claims (1)
1. The uplink and downlink channel reciprocity air interface calibration method based on the access point grouping is characterized by comprising the following steps:
step 1, dividing the access points into two groups according to the positions of N access points;
the step 1 comprises the following steps:
step 1.1, calculating a distance matrix D according to N access point positions, wherein the dimension of the matrix is N multiplied by N, and the element D ij For access point i to access pointThe Euclidean distance of j;
step 1.2, finding an access point with the farthest sum of the distances from other access points, and realizing the method as follows: the matrix D sums up according to the columns to find the index idx1 of the largest element, then finds the access point idx2 nearest to the access point idx1, divides the access point idx1 into the A group, and divides the access point idx2 into the B group;
let the number of non-grouped access points be r=n-2;
step 1.3, performing the following operations on the access points which are not grouped yet:
step 1.3.1, recalculating a distance matrix D between R ungrouped access points, wherein the dimension of the matrix is R multiplied by R;
step 1.3.2, summing each row of the matrix D, finding the index idx1 of the largest element, and finding the index idx2 of the smallest element in the row of the matrix D idx1;
step 1.3.3, finding out the distance between the access point idx1 and the existing access point in the A set, finding out the minimum distance minA, finding out the minimum distance minB from the B set, if minA > minB, putting the access point idx1 into the A set, putting the idx2 into the B set, otherwise putting the idx1 into the B set, and putting the idx2 into the A set;
step 1.3.4, r=r-2; returning to step 1.3.1 until r=0;
if N is an odd number, the minimum distances minA and minB between the last access point to be allocated and the access points existing in the A group and the B group are obtained, and if minA is more than or equal to minB, the access points are separated into the A group; otherwise, dividing into B groups;
step 2, mutually receiving and transmitting calibration pilot signals between the two groups, and estimating two channel matrixes according to the received pilot signals:
where H is the air channel when group A transmits group B, H T Is the air channel when group B sends group A; c (C) A,t ，C A,r Is a transmit and receive RF gain diagonal matrix for group A antennas, C B,t ，C B,r Is a transmit and receive RF gain diagonal matrix for group B antennas;
step 3, calculating a calibration matrix according to the channel matrixes estimated by the two groups of access points;
the step 3 comprises the following steps:
step 3.1, after obtaining the estimation of two channel matrixes between A and B, constructing the following objective function:
where vec is the vectorization operator, C A Is the calibration matrix of the A group antenna, C B Is the calibration matrix for the group B antennas;
rewriting the optimization target as:
wherein,c A ＝diag(C A )，c B ＝diag(C B )；
step 3.3, constructing a matrix of psi:
wherein:
N 1 the number of the antennas of the group B;
N 2 the number of the antennas of the group A;
refers to the pair [ G ] B,A ] v,u Conjugation is taken;
is to be t 12 Performing conjugate transposition;
step 3.4, decomposing eigenvalues of the psi matrix:
Ψ＝UΛU H ；
in the U matrix, a feature vector corresponding to the minimum feature value of the psi matrix is used as a final calibration vector c cal And (2) andfinal calibration matrix C A And C B Denoted as C A ＝diag(c A )，C B ＝diag(c B ) Wherein diag () represents the generation of a diagonal matrix from a vector.
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| US7206354B2 (en) * | 2004-02-19 | 2007-04-17 | Qualcomm Incorporated | Calibration of downlink and uplink channel responses in a wireless MIMO communication system |
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