CN107579763B - Inter-cluster interference elimination method based on spatial fine high-resolution beams - Google Patents
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Abstract
The invention discloses an inter-cluster interference elimination method based on spatial domain fine-degree high-resolution beams, which mainly solves the problem of poor service quality of cell edge users caused by ARSs (coverage areas) overlapping phenomenon and path loss in the prior art. The method comprises the following implementation steps: 1) selecting a cooperation area and calculating a spatial correlation matrix; 2) calculating a first-stage pre-beamforming matrix according to the spatial correlation matrix, and further calculating equivalent channel dimensions; 3) calculating the optimal spatial degree of freedom; 4) comparing the total degree of freedom with the maximum equivalent channel dimension, judging whether the user cluster is suitable for interference alignment, if so, calculating an interference alignment coding and decoding matrix of the second stage, otherwise, calculating a zero forcing precoding matrix of the second stage; 5) and calculating a two-stage precoding matrix by combining the first-stage coding and the second-stage coding. According to the invention, the intra-cluster interference is eliminated by the edge cluster through interference alignment, and the intra-cluster interference is eliminated by the center cluster through zero-forcing precoding, so that the system throughput is effectively improved, and the method can be used for a large-scale MIMO cellular network.
Description
Technical Field
The invention belongs to the technical field of wireless communication, and particularly relates to an inter-cluster interference elimination method which can be used in a large-scale MIMO cellular network system.
Background
at present, in the fifth generation cellular network 5G, in order to meet the wireless service rate 1000 times higher than that of the long term evolution standard L TE-a, the large-scale MIMO technology has been widely used, and the frequency spectrum of the millimeter wave covers the range of 30GHz to 300GHz, so that the application of the millimeter wave frequency band transmission becomes a feasible method for increasing the network capacity.
In a large-scale MIMO network structure, in order to effectively complete downlink precoding and uplink detection, a base station needs to acquire sufficiently accurate channel state information. For a time division duplex system, the detection of the channel information of the base station end can be completed by the uplink training by fully utilizing the uplink and downlink reciprocity characteristics of a channel link. In this scenario, the required length of the channel training sequence is proportional to the number of antennas at the user end. However, in the frequency division duplex mode, the reciprocity of the uplink and downlink of the link will not hold. The base station can only sense the downlink channel state information through three continuous processes of downlink channel training frame transmission, user side channel estimation and uplink channel feedback. In such a scenario, the length of the downlink training symbols and the amount of information of the uplink feedback channel are in direct proportion to the number of antennas at the base station, and therefore, a large system overhead is generated, especially when the number of antennas at the base station is large. To overcome this bottleneck, several low complexity precoding methods have been proposed in succession, typically the following:
1. The two-stage precoding method, i.e. "joint spatial diversity and multiplexing transmission". The core idea of two-stage precoding can be summarized as: firstly, clustering users according to the covariance characteristics of respective user channels, wherein each user in the same cluster has approximately the same channel covariance characteristics; then, the downlink precoding transmission process is divided into two stages, namely an outer layer precoding stage and an inner layer precoding stage;
2. Three improved two-stage precoding methods:
The first modified type is essentially in low-overhead random user selection and outer layer precoding design with the maximum achievable rate;
The second modified type is characterized in that the outer precoding design which is based on phase rotation and takes the maximum minimum user average speed as the direction;
The improved nature of the third improvement lies in low complexity on-line outer layer precoding tracking.
By the methods, when the electromagnetic scattering angle extension ranges ASR of different user clusters are not overlapped, orthogonal access can be realized. However, in an actual scenario, users are deployed randomly in a limited geographic space, ASR clustered by different users will overlap with a high probability, and interference among user clusters is introduced, which may reduce the performance of the above precoding algorithms. The influence of ASR overlapping on the cell edge user cluster is particularly serious, and the transmission rate of the edge cluster is greatly limited.
Disclosure of Invention
The invention aims to provide a method for eliminating inter-cluster interference based on spatial domain fine high-resolution beams, aiming at overcoming the defects of the prior art, so as to reduce the influence of ASR (access router) overlapping on a cell edge user cluster and improve the transmission rate of the cell edge cluster.
In order to achieve the purpose, the technical scheme of the invention comprises the following steps:
(1) Selecting a cooperation area consisting of 3 adjacent base stations in the cellular network, and calculating a spatial correlation matrix from the ith base station to the jth cluster in the cooperation area 
Wherein, i ═ {1,2,3}, J ═ 1,2,. and J }, J is the number of clusters;
(2) Computing a pre-beamforming matrix for the first stage:
(2.1) correlating the spatial correlation matrix 
Feature decomposition into 
Wherein the content of the first and second substances, 
Is composed of 
A diagonal matrix of non-zero eigenvalues of, 
Is composed of 
Feature vector corresponding to the non-zero eigenvalue of A matrix of compositions, () HIs a conjugate transpose of the matrix;
(2.2) calculation of 
The column index set of the column in the unit discrete Fourier transform DFT matrix is recorded as 
(2.3) aggregation according to the index 
Computing pre-beamforming matrices for the ith base station to the jth cluster 
(3) The ith base station forms the matrix according to the pre-beam 
Calculate its equivalent channel dimension to the jth cluster 
(4) Calculating the optimal spatial freedom from 3 base stations to the jth cluster 
(5) Comparing the total degree of freedom from all base stations to the jth cluster with the maximum equivalent channel dimension:
If it is 
Executing the step (6), otherwise, executing the step (7);
(6) Selecting 3 users in the jth cluster to perform interference alignment transmission with 3 base stations in a cooperation area, and calculating a second stage interference alignment coding and decoding matrix:
(6.1) each base station sends a downlink channel training frame subjected to pre-beamforming to a user;
(6.2) performing channel estimation on 3 users selected from the jth cluster to obtain the equivalent channel of the kth user performing interference alignment from the ith base station to the jth cluster 
And will be 
Feeding the uplink to a base station end, wherein k is {1,2,3 };
(6.3) the base station end calculates the interference alignment coding matrix from 3 base stations to the jth cluster and the decoding matrix of 3 users performing interference alignment in the jth cluster by using the equivalent channel information, and records the interference alignment coding matrix from the ith base station to the jth cluster as 
The decoding matrix of the k user for interference alignment in the jth cluster is U j,k；
(7) Selecting equivalent channel dimensions 
Maximum ith *Each base station serves the jth cluster, 
And computing a second stage zero-forcing coding matrix:
(7.1) th i *The base station sends a downlink channel training frame which is subjected to pre-beam forming to a user;
(7.2) performing channel estimation on the user in the jth cluster to obtain the ith cluster *Equivalent channel from base station to jth cluster 
And will be 
Uplink feedback to ith *A base station;
(7.3) th i *A base station using equivalent channel information 
Computing a zero forcing coding matrix to the jth cluster 
(8) Computing a two-stage joint precoding matrix 
Compared with the prior art, the invention has the following technical effects:
Several existing two-stage precoding techniques simply process all clusters together, but they do not distinguish between cell edge clusters and center clusters, and the ASRs overlap phenomenon and severe path loss cause low transmission rate of the cell edge clusters. According to the invention, the edge clusters and the center cluster are distinguished, the intra-cluster interference of the edge clusters is eliminated through interference alignment, and the intra-cluster interference of the center cluster is eliminated through zero-forcing precoding, so that the transmission rate of the edge clusters is effectively improved, and the throughput of a network is increased.
Drawings
FIG. 1 is a diagram of an application scenario of the present invention;
FIG. 2 is a diagram of a collaboration zone selected from FIG. 1 in accordance with the present invention;
Fig. 3 is a flow chart of an implementation of the present invention.
Detailed Description
The invention is further described below with reference to the accompanying drawings.
As shown in fig. 1, the present invention is applicable to a multi-cell cellular network scenario, where 1 base station is configured at the center of each cell, and every 3 adjacent base stations form a cooperation area. As shown in fig. 2, a triangular cooperation area commonly served by 3 neighboring base stations is selected, wherein a base station is configured at the center of each cell and is marked as BS iI ═ 1,2,3, and N is installed per base station tAntennas with uniformly distributed roots, N t＞＞1，The antenna element spacing is τ. There are 5 users clustered in the region, denoted as C iJ ═ {1,2,3,4,5}, with 4 mounts N in each cluster rUsers of the root antenna. The jth cluster has a radius of R jThe distance from the ith base station to the jth cluster is 
Referring to fig. 2 and 3, the implementation steps of the invention are as follows:
Step 1, calculating a spatial correlation matrix from a base station to a cluster.
Selecting a cooperation area consisting of 3 adjacent base stations, and calculating a spatial correlation matrix from the ith base station to the jth cluster in the cooperation area 
Wherein the content of the first and second substances, 
Is N t×NtMatrix of N tFor the number of base station antennas, p, q are the row and column indices, respectively, and p ═ 1,2 t}，q＝{1,2,...,Nt}，
For the azimuth from the ith base station to the jth cluster, 
For the angular spread of the ith base station to the jth cluster, 
RjIs the radius of the jth cluster, 
Is the distance from the ith base station to the jth cluster, and tau is the base station antenna unit spacing 。
And 2, calculating a pre-beamforming matrix in the first stage.
(2.1) correlating the spatial correlation matrix 
Feature decomposition into 
Wherein the content of the first and second substances, 
Is composed of 
A diagonal matrix of non-zero eigenvalues of, 
Is composed of 
Is used for generating a matrix of eigenvectors corresponding to the non-zero eigenvalues of (c) () HIs a conjugate transpose of the matrix;
(2.2) calculation of 
Column index set in the unit discrete fourier transform DFT matrix:
Index set of column labels from ith base station to jth cluster 
Is represented as follows:
Wherein λ is a carrier wavelength;
(2.3) aggregation according to the index 
Calculating the ith base station Pre-beamforming matrix to jth cluster 
Wherein f is n∪ is ∪ the ∪ nth ∪ column ∪ of ∪ the ∪ DFT ∪ matrix ∪, ∪ is ∪ the ∪ union ∪ of ∪ the ∪ solved ∪ sets ∪, ∪ 
For the column index set of the ith base station to the jth cluster, j '═ {1,2,3,4,5} and j' ≠ j.
And 3, calculating the equivalent channel dimension from the base station to the cluster.
The ith base station forms the matrix according to the pre-beam 
Calculate its equivalent channel dimension to the jth cluster 
Wherein rank { } is the rank of the matrix, and | is the number of elements in the set.
And 4, calculating the optimal spatial freedom from the base station to the cluster.
Calculating the optimal spatial degrees of freedom from 3 base stations to the jth cluster by solving the following optimization problem 
The objective function of the optimization problem is as follows:
The constraints are as follows:
Wherein the content of the first and second substances, 
Number of data streams sent to jth cluster for ith base station, N rMax (. lamda.) is the maximum value and min (. lamda.) is the minimum value for the number of user antennas.
And 5, judging whether the user cluster is suitable for interference alignment transmission with the base station.
(5.1) adding the degrees of freedom from 3 base stations to the jth cluster to obtain the total degree of freedom, i.e. 
(5.2) take the maximum equivalent channel dimension from 3 base stations to the jth cluster, i.e. 
(5.3) comparing the total degree of freedom from 3 base stations to the jth cluster with the maximum equivalent channel dimension:
If it is 
Step 6 is performed, otherwise step 7 is performed.
And 6, selecting 3 users in the jth cluster to perform interference alignment transmission with 3 base stations in a cooperation area, and calculating a second-stage interference alignment coding and decoding matrix.
(6.1) each base station sends a downlink channel training frame which is subjected to pre-beam forming to a user:
First, a pilot sequence X is generated by the ith base station i(ii) a Then to X iPerforming pre-beamforming coding, i.e. 
Finally, encoding 
Sending the information to the users in the jth cluster;
(6.2) performing channel estimation on 3 users selected from the jth cluster to obtain the equivalent channel of the kth user performing interference alignment from the ith base station to the jth cluster 
And will be 
Feeding back to the base station end, wherein, 
For the channel from the ith base station to the kth user in the jth cluster, k is {1,2,3 };
(6.3) the base station uses the equivalent channel information 
Calculating interference alignment coding matrixes from 3 base stations to the jth cluster and decoding matrixes of 3 users performing interference alignment in the jth cluster, wherein:
Interference alignment coding matrix from 1 st base station to j th cluster 
Is represented as follows:
2 nd base station Interference aligned coding matrix to jth cluster 
Is represented as follows:
Interference alignment coding matrix from 3 rd base station to j th cluster 
Is represented as follows:
Decoding matrix U of 1 st user for interference alignment in jth cluster j,1Expressed as follows:
Decoding matrix U of 2 nd user for interference alignment in jth cluster j,2Expressed as follows:
Decoding matrix U of 3 rd user for interference alignment in jth cluster j,3Expressed as follows:
wherein vig { } is the eigenvector of the matrix, and NU LL { } is the null space of the matrix.
Step 7, selecting equivalent channel dimension 
Maximum ith *Each base station serves the jth cluster, 
And computes a second stage zero-forcing coding matrix.
(7.1) th i *The base station sends a downlink channel training frame which is subjected to pre-beam forming to a user;
(7.2) performing channel estimation on the user in the jth cluster to obtain the ith cluster *Equivalent channel from base station to jth cluster 
And will be 
Is fed back to the ith *A base station, wherein, 
Is the ith *Channels from base station to jth cluster;
(7.3) th i *A base station using equivalent channel information 
Computing a zero forcing coding matrix to the jth cluster 
Wherein the content of the first and second substances, 
In order to normalize the factors, the method comprises the steps of, 
tr () is trace of matrix
Step 8, according to the first order from the ith base station to the jth cluster Segment pre-beamforming matrix 
And a second stage encoding matrix 
Calculating a two-stage precoding matrix from the ith base station to the jth cluster: 
And completing the two-stage joint coding.
The above is a detailed description of an example of the invention and is not to be construed as limiting the invention in any way, it being obvious that various changes may be made within the spirit and scope of the invention, which is encompassed by the protection of the present invention.
Claims (10)
1. A method for eliminating inter-cluster interference based on spatial fine high-resolution beams comprises the following steps:
(1) Selecting a cooperation area consisting of 3 adjacent base stations in the cellular network, and calculating a spatial correlation matrix from the ith base station to the jth cluster in the cooperation area 
Wherein, i ═ {1,2,3}, J ═ 1,2,. and J }, J is the number of clusters;
(2) Computing a pre-beamforming matrix for the first stage:
(2.1) correlating the spatial correlation matrix 
Feature decomposition into 
Wherein the content of the first and second substances, 
Is composed of 
A diagonal matrix of non-zero eigenvalues of, 
Is composed of 
Is used for generating a matrix of eigenvectors corresponding to the non-zero eigenvalues of (c) () HIs a conjugate transpose of the matrix;
(2.2) calculation of 
The column index set of the column in the unit discrete Fourier transform DFT matrix is recorded as 
(2.3) aggregation according to the index 
Computing pre-beamforming matrices for the ith base station to the jth cluster 
(3) The ith base station forms the matrix according to the pre-beam 
Calculate its equivalent channel dimension to the jth cluster 
(4) Calculating the optimal spatial freedom from 3 base stations to the jth cluster 
(5) Comparing the total degree of freedom from all base stations to the jth cluster with the maximum equivalent channel dimension:
If it is 
Executing the step (6), otherwise, executing the step (7);
(6) Selecting 3 users in the jth cluster to perform interference alignment transmission with 3 base stations in a cooperation area, and calculating a second stage interference alignment coding and decoding matrix:
(6.1) each base station sends a downlink channel training frame subjected to pre-beamforming to a user;
(6.2) performing channel estimation on 3 users selected from the jth cluster to obtain the equivalent channel of the kth user performing interference alignment from the ith base station to the jth cluster 
And will be 
Feeding the uplink to a base station end, wherein k is {1,2,3 };
(6.3) the base station end calculates the interference alignment coding matrix from 3 base stations to the jth cluster and the decoding matrix of 3 users performing interference alignment in the jth cluster by using the equivalent channel information, and records the interference alignment coding matrix from the ith base station to the jth cluster as 
The decoding matrix of the k user for interference alignment in the jth cluster is U j,k；
(7) Selecting equivalent channel dimensions 
Maximum ith *Each base station serves the jth cluster, 
And computing a second stage zero-forcing coding matrix:
(7.1) th i *A base station Sending a downlink channel training frame subjected to pre-beamforming to a user;
(7.2) performing channel estimation on the user in the jth cluster to obtain the ith cluster *Equivalent channel from base station to jth cluster 
And will be 
Uplink feedback to ith *A base station;
(7.3) th i *A base station using equivalent channel information 
Computing a zero forcing coding matrix to the jth cluster 
(8) Computing a two-stage joint precoding matrix 
2. The method of claim 1, wherein the spatial correlation matrix in step (1) 
Calculated according to the following formula:
Wherein the content of the first and second substances, 
Is N t×NtMatrix of N tFor the number of base station antennas, p, q are the row and column indices, respectively, and p ═ 1,2 t}，q＝{1,2,...,Nt}，
For the azimuth from the ith base station to the jth cluster, 
For the angular spread of the ith base station to the jth cluster, 
RjIs the radius of the jth cluster, 
And tau is the distance from the ith base station to the jth cluster, and tau is the base station antenna unit distance.
3. The method of claim 1, wherein the set of column index indices from the ith base station to the jth cluster in step (2.2) 
Calculated according to the following formula:
Wherein N is tIs the number of base station antennas, lambda is the carrier wavelength, 
For the azimuth from the ith base station to the jth cluster, 
For the angular spread of the ith base station to the jth cluster, 
RjIs the radius of the jth cluster, 
And tau is the distance from the ith base station to the jth cluster, and tau is the base station antenna unit distance.
4. The method of claim 1, wherein the pre-beamforming matrix in step (2.3) 
Calculated according to the following formula:
Wherein f is n∪ is ∪ the ∪ nth ∪ column ∪ of ∪ the ∪ DFT ∪ matrix ∪, ∪ is ∪ the ∪ union ∪ of ∪ the ∪ solved ∪ sets ∪, ∪ 
Index sets are labeled for the columns from the ith base station to the jth cluster.
5. The method of claim 1, wherein the equivalent channel dimension from the ith base station to the jth cluster in step (3) 
Calculated according to the following formula:
wherein rank { } is the rank of the solution matrix, | - | is the number of elements in the solution, and U is the union of the solutions, 
Index sets are labeled for the columns from the ith base station to the jth cluster.
6. The method of claim 1, wherein 3 base stations in step (4) Optimal spatial degree of freedom to jth cluster 
Obtained by solving the following optimization problem:
The objective function of the optimization problem is as follows:
The constraints are as follows:
Wherein the content of the first and second substances, 
Number of data streams sent to jth cluster for ith base station, N rMax (. lamda.) is the maximum value and min (. lamda.) is the minimum value for the number of user antennas.
7. The method of claim 1, wherein the step (6.1) of sending the downlink channel training frame first requires the ith base station to generate the pilot sequence X i(ii) a Then to X iPerforming pre-beamforming coding, i.e. 
Finally will be 
And sending to the user of the jth cluster.
8. The method of claim 1, wherein the step (6.2) comprises estimating an equivalent channel for the interference-aligned kth user in the jth cluster 
Is represented as follows:
Wherein the content of the first and second substances, 
The channel from the ith base station to the kth user in the jth cluster.
9. The method of claim 1, wherein the interference alignment coding matrix of 3 base stations to the jth cluster in step (6.3) 
And decoding matrix U of 3 users making interference alignment in jth cluster j,kCalculated according to the following formula:
vig { } is an eigenvector of the matrix, and NU LL { } is a null space of the matrix.
10. The method of claim 1, wherein step (7.3) comprises base station i *Coding matrix to cluster j 
Calculated according to the following formula:
Wherein the content of the first and second substances, 
In order to normalize the factors, the method comprises the steps of, 
tr () is the trace of the matrix.
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