CN113691343B - Interference channel network topology interference alignment method based on cache - Google Patents

Interference channel network topology interference alignment method based on cache Download PDF

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CN113691343B
CN113691343B CN202110968275.4A CN202110968275A CN113691343B CN 113691343 B CN113691343 B CN 113691343B CN 202110968275 A CN202110968275 A CN 202110968275A CN 113691343 B CN113691343 B CN 113691343B
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CN113691343A (en
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刘伟
康增鹏
侯林
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Chengdu Yaguang Electronic Co ltd
Xidian University
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Xidian University
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04J—MULTIPLEX COMMUNICATION
    • H04J11/00—Orthogonal multiplex systems, e.g. using WALSH codes
    • H04J11/0023—Interference mitigation or co-ordination
    • 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
    • H04B7/0456—Selection of precoding matrices or codebooks, e.g. using matrices antenna weighting
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
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    • Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks

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Abstract

The invention provides a cache-based interference channel network topology interference alignment method, which comprises the following steps: constructing an interference channel network topology structure; constructing an interference channel network signal intensity matrix; acquiring a cache cancellation signal intensity matrix; establishing a union in a caching elimination signal intensity matrix; acquiring the maximum interference block number of the alliance; and acquiring an interference alignment result of the network topology of the interference channel. According to the invention, by constructing an interference channel network topological structure and an interference channel network signal intensity matrix, part of interference signals in an interference channel are eliminated by utilizing a user cache, the cache eliminated signal intensity matrix is obtained, then a alliance set and the maximum interference block number are constructed by the cache eliminated signal intensity matrix, and a base station precoding matrix and a user decoding matrix are designed, so that the alignment of interference channel topological network topological interference is realized, and the symmetric freedom of the accessible user is improved.

Description

Interference channel network topology interference alignment method based on cache
Technical Field
The invention belongs to the technical field of communication, relates to an interference alignment method, and particularly relates to a cache-based interference channel network topology interference alignment method.
Background
In the sixth generation of wireless networks, the ultra-dense networking can obtain great improvement of frequency reuse efficiency by increasing the distribution density of wireless network base stations, so that the increase of system capacity is realized, but more serious interference is brought by more dense arrangement of micro-cells and overlapping of cell coverage. Without proper interference management strategies, interference in the network becomes more severe as cell density increases and becomes one of the key constraints limiting seamless coverage of wireless networks and low availability of available channel links.
Interference alignment is receiving increasing attention as an efficient interference management method. The main idea of interference alignment is to design a pre-coding matrix at the transmitting end and a decoding matrix at the receiving end, so that interference signals of signals received at the receiving end are overlapped in space, and thus the receiving end can eliminate overlapped interference to obtain interference-free received signals. By adopting the interference alignment technology, higher user symmetry freedom can be obtained, so that the success rate of file transmission is improved.
The main idea of the topological interference alignment is to obtain a topological matrix by obtaining the topological connection relationship between a base station and a user in a network, design a base station precoding matrix and a receiving end precoding matrix through the topological matrix, and eliminate an interference signal received by a user end. And the base station in the topological interference alignment has the characteristic of not needing to acquire the Channel State Information (CSI) of the user terminal.
However, the existing research on the Topological Interference alignment can only perform the Topological Interference alignment on the Interference channel networks of K user K base stations, and in the paper Analysis of maximum strategies and the theory DoFs in the Interference Management published by IEEE Access in 2020, Yoon J Y and No js, a method for the Topological Interference alignment of the Interference channel networks is proposed. Although the method can realize topological interference alignment on all K user K base station interference channel networks, the method has the disadvantages that a large number of interference signals in the interference channel networks can form a large number of interference blocks, and the reachable symmetric freedom of users is low.
Disclosure of Invention
The invention aims to overcome the defects in the prior art, provides a cache-based multi-interference channel network topology interference alignment method, and aims to deploy and configure a part of file cache at a user terminal so that the user terminal can eliminate part of interference signals by using content cache, and improve the reachable symmetric freedom of users in a wireless network.
In order to achieve the purpose, the technical scheme adopted by the invention comprises the following steps:
(1) constructing an interference channel network topological structure:
constructing K base stations with coverage radii of rB＝{b1,...,bi,...,bKAnd its corresponding K desired users R ═ u1,...,ui,...,uKThe interference channel network structure of each base station biConfiguring N antennas with signal transmitting power of Pi，biCoordinate position of
Figure BDA0003224997260000021
Obeying a random distribution, biDesired user uiConfiguring N antennas with their coordinate positions
Figure BDA0003224997260000022
Compliance
Figure BDA0003224997260000023
Each base station biTo whom user u is expectediThe expected file to be transmitted is wi，biDesired user uiCache divide by biSet of files C transmitted by F other base stationsi＝{w1,...,wp,...,wFB, wherein K is more than or equal to 2, F is less than or equal to K, N is more than or equal to 1iDenotes the ith base station;
(2) constructing an interference channel network signal intensity matrix:
(2a) calculate each base station biWith each user ugThe distance between
Figure BDA0003224997260000024
And pass through
Figure BDA0003224997260000025
And biSignal transmission power PiCalculating each user ugEach base station b receivediSignal strength of
Figure BDA0003224997260000026
Figure BDA0003224997260000027
Wherein g belongs to [1, K ], and alpha represents a path loss parameter with a non-negative real number;
(2b) constructed with biIs a row index, ugFor column index, each element on the main diagonal has a value of 1, and the rest elements have values of
Figure BDA0003224997260000028
And satisfy U in each column
Figure BDA0003224997260000029
Is set to 1, and then the sum of the signal strengths in each column which are not equal to 1 is calculated
Figure BDA00032249972600000210
(2c) Judgment of
Figure BDA0003224997260000031
And average noise power N0Whether or not to satisfy
Figure BDA0003224997260000032
If so, the column is divided into two rows
Figure BDA0003224997260000033
The corresponding signal strength is set to 0, otherwise, it will be
Figure BDA0003224997260000034
Setting the corresponding signal intensity as 1, and obtaining the interference channel network signal intensity matrix with the signal intensity of 0 or 1
Figure BDA0003224997260000035
(3) Obtaining a buffer elimination signal intensity matrix:
network signal strength matrix of interference channel
Figure BDA0003224997260000036
Expected user u of medium-buffer transmission filegReceived signal strength of base station
Figure BDA0003224997260000037
Set to 0, realize the network signal intensity matrix of the interference channel
Figure BDA0003224997260000038
Eliminating partial interference channel network signal to obtain buffer eliminated signal strength matrix
Figure BDA0003224997260000039
(4) Constructing a coalition in a buffer elimination signal strength matrix:
(4a) initializing a buffer to eliminate a signal strength matrix
Figure BDA00032249972600000310
The sub-matrix row index boundary and the column index boundary in (1) are respectively γ and κ, the union set is Ω, γ is equal to 1, κ is equal to 1,
Figure BDA00032249972600000311
(4b) judging buffer memory eliminating signal strength matrix
Figure BDA00032249972600000312
Middle row index range of bd∈[γ,κ+1]Column index range of uz∈[γ,κ+1]Is formed by a sub-matrix of elements
Figure BDA00032249972600000313
If the array is a unit array, executing the step (4c) if the array is the unit array, otherwise executing the step (4 d);
(4c) let κ be κ +1, and perform step (4 b);
(4d) judging whether the kappa-gamma +1 is equal to 1 or not, if so, caching the eliminated signal intensity matrix
Figure BDA00032249972600000314
Line coordinate index of the middle main diagonal element { (b)d,uz)|bd∈[γ,κ]And column coordinate index uz∈[γ,κ]Expressing the set formed by the steps as a union, adding the union into a union set omega, and executing a step (4f), otherwise, executing a step (4 e);
(4e) eliminating the buffer from the signal strength matrix
Figure BDA00032249972600000315
Middle element
Figure BDA00032249972600000316
Formed sub-matrix
Figure BDA00032249972600000317
Row coordinate index of main diagonal element of (a { (b))n,un)|bn∈[γ,κ]And column coordinate index un∈[γ,κ]Expressing the set formed by the method as a union, and adding the union into a union set omega;
(4f) determination of kappa +1>If K is true, obtaining M alliances omega ═ Λ if K is true1,...,Λf,...,ΛMElse, let γ ═ κ +1, and perform step (4 c);
(5) acquiring the maximum number of interference blocks of the alliance:
(5a) initializing the set of interference blocks of the alliance set omega as phi ═ G1,...,Gf,...,GMV. each federation ΛfSet of interference blocks of
Figure BDA0003224997260000041
(5b) Obtaining alliance ΛfMiddle column index set mu ═ uf|uf∈ΛfΛ, and each of the other M-1 federationsjLine index set Lf＝{β1,...,βj,...,βM-1Is traversed to the set LfWill matrix
Figure BDA0003224997260000042
Middle row index and column index set Πf,j＝{(x,y)|x∈βjY ∈ μ }
Figure BDA0003224997260000043
The set with element value 1 is marked as alliance LambdafTo the interference block set GfPerforming the following steps; wherein beta isj＝{br|br∈Λj}，j∈[1,M]，f≠j；
(5c) Traverse each federation ΛfCorresponding set of interference blocks GfNumber of medium interference blocks ΨfTo obtain a cache matrix
Figure BDA00032249972600000417
The number of medium-largest interfering blocks EM, where:
Figure BDA0003224997260000044
(6) obtaining an interference alignment result of an interference channel network topology:
(6a) design of Each AssociationfAll base stations b inf,iOf dimension (EM +1) of a precoding vector vfAnd obtaining a precoding vector set V ═ V { V } which corresponds to the union set omega and in which any EM +1 precoding vectors are linearly independent1,...,vf,...vM}；
(6b) Through each alliance ΛfAll base stations b inf,iOf the precoding vector vfAnd bf,iSent to the expected user uf,iDocument w ofiComputing base station bf,iTo the desired user uf,iTransmitting coded signals
Figure BDA0003224997260000045
(6c) By encoding the signal
Figure BDA0003224997260000046
Obtaining a desired user uf,iReceived signal of
Figure BDA0003224997260000047
And calculate
Figure BDA0003224997260000048
Middle interference signal
Figure BDA0003224997260000049
To obtain uf,iDecoding matrix of
Figure BDA00032249972600000410
Figure BDA00032249972600000411
Figure BDA00032249972600000412
Figure BDA00032249972600000413
Figure BDA00032249972600000414
Wherein,
Figure BDA00032249972600000415
and
Figure BDA00032249972600000416
respectively representing desired users uf,iA received desired signal, an undesired signal, and white gaussian noise.
(6c) Will expect user uf,iDecoding matrix of
Figure BDA0003224997260000051
And
Figure BDA0003224997260000052
interference signal in
Figure BDA0003224997260000053
Multiplying to obtain user uf,iReceived signal of
Figure BDA0003224997260000054
In
Figure BDA0003224997260000055
Is 0, i.e.
Figure BDA0003224997260000056
Contains only the desired signal
Figure BDA0003224997260000057
And white gaussian noise
Figure BDA0003224997260000058
And realizing the network topology interference alignment of the interference channel.
Compared with the prior art, the invention has the following advantages:
according to the invention, by constructing the interference channel network signal intensity matrix, utilizing the user cache to eliminate partial interference channel network signals, then constructing the alliance in the signal intensity matrix for eliminating partial interference channel network signals, obtaining the maximum interference block number of the alliance, finally designing the base station precoding matrix according to the maximum interference block number, designing the user decoding matrix in a combined manner, carrying out topological interference alignment, fully utilizing the advantage that the user cache is placed to eliminate the interference signals of partial interference channels, and improving the reachable symmetric freedom degree of wireless network users.
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FIG. 1 is a flow chart of an implementation of the present invention.
FIG. 2 is a comparison of simulation results for the user achievable symmetric degrees of freedom of the present invention and the prior art.
Detailed Description
The present invention is described in further detail below with reference to the figures and specific examples.
Referring to fig. 1, the present invention includes the steps of:
step 1) constructing an interference channel network topological structure:
constructing K base stations B (B) with coverage radius r (200 m)1,...,bi,...,bKAnd its corresponding K desired users R ═ u1,...,ui,...,uKThe interference channel network structure of each base station biConfiguring N antennas with signal transmitting power of Pi，biCoordinate position of
Figure BDA0003224997260000059
Obeying a random distribution, biDesired user uiConfiguring N antennas with their coordinate positions
Figure BDA00032249972600000510
Compliance
Figure BDA00032249972600000511
Each base station biTo whom user u is expectediThe expected file to be transmitted is wi，biDesired user uiCache divide by biSet of files C transmitted by F other base stationsi＝{w1,...,wp,...,wFWhere K is 6, F is 2, biDenotes the ith base station;
step 2), constructing an interference channel network signal intensity matrix:
(2a) calculate each base station biWith each user ugThe distance between
Figure BDA0003224997260000061
And pass through
Figure BDA0003224997260000062
And biSignal transmission power PiCalculating each user ugEach base station b receivediSignal strength of
Figure BDA0003224997260000063
Figure BDA0003224997260000064
Wherein g is [1, K ]]Where α ═ 2 denotes a path loss parameter with a value that is not a negative real number, PiRandomly taking 10-20 mW;
(2b) construction with biIs a row index, ugFor column index, each element on the main diagonal has a value of 1, and the rest elements have values of
Figure BDA0003224997260000065
And satisfy U in each column
Figure BDA0003224997260000066
Is set to 1, and then the sum of the signal strengths in each column which are not equal to 1 is calculated
Figure BDA0003224997260000067
(2c) Judgment of
Figure BDA0003224997260000068
And average noise power N0Whether or not to satisfy
Figure BDA0003224997260000069
If so, the column is divided into two rows
Figure BDA00032249972600000610
The corresponding signal strength is set to 0, otherwise, it will be
Figure BDA00032249972600000611
Setting the corresponding signal intensity as 1, and obtaining the interference channel network signal intensity matrix with the signal intensity of 0 or 1
Figure BDA00032249972600000612
Step 3) eliminating partial interference channel network signals through user buffer:
since the files transmitted by the base station are pre-codedThe formed signal can be decoded and restored to be the original file at the user terminal, so that after the user terminal caches the file transmitted by the base station, the user can eliminate the file formed by the interference signal transmitted by the base station by using the local cache file of the user after receiving the file transmitted by the base station, the interference signal received by the user is reduced, and the channel utilization rate in the network is improved; so each user u is acquired firstgCached transmission file set C of base stationgThrough CgIn-cache file index wpFinding out the corresponding base station index p, and then, forming the interference channel network signal intensity matrix
Figure BDA00032249972600000613
The middle row index is p and the column index is uiOf (2) element(s)
Figure BDA00032249972600000614
Element value of 1
Figure BDA00032249972600000615
Setting to 0, obtaining the signal intensity matrix of the network signal for eliminating partial interference channel
Figure BDA00032249972600000616
Step 4), establishing a coalition of the caching elimination signal intensity matrix:
(4a) representing the diagonal element row index and column index pair set of the unit array on the main diagonal in the signal intensity matrix of the partial interference channel network signals as a union, and initializing the signal intensity matrix for eliminating the partial interference channel network signals
Figure BDA0003224997260000071
The sub-matrix row index boundary and the column index boundary in (1) are respectively γ and κ, the union set is Ω, γ is equal to 1, κ is equal to 1,
Figure BDA0003224997260000072
(4b) judgment of
Figure BDA0003224997260000073
Middle row index range of bd∈[γ,κ+1]Column index range of uz∈[γ,κ+1]Is formed by a sub-matrix of elements
Figure BDA0003224997260000074
If the array is a unit array, executing the step (4c) if the array is the unit array, otherwise executing the step (4 d);
(4c) let κ be κ +1, and perform step (4 b);
(4d) judging whether kappa-gamma +1 is true or not, if yes, eliminating the signal intensity matrix from the buffer memory
Figure BDA0003224997260000075
Line coordinate index of the middle main diagonal element { (b)d,uz)|bd∈[γ,κ]And column coordinate index uz∈[γ,κ]Expressing the set formed by the step (4) as a union, adding the union into a union set omega, and executing the step (4f), otherwise, executing the step (4 e);
(4e) eliminating the buffer from the signal strength matrix
Figure BDA0003224997260000076
Middle element
Figure BDA0003224997260000077
Formed sub-matrix
Figure BDA0003224997260000078
Row coordinate index of main diagonal element of (a { (b))n,un)|bn∈[γ,κ]And column coordinate index un∈[γ,κ]Expressing the set formed by the method as a union, and adding the union into a union set omega;
(4f) determination of kappa +1>If K is true, obtaining M alliances omega ═ Λ if K is true1,...,Λf,...,ΛMElse, let γ ═ κ +1, and perform step (4 c);
step 5), acquiring the maximum interference block number of the alliance:
(5a) get one federation in every two federationsAllium LambdaδAnd another federation ΛγJudging whether the signal intensity of the element of the submatrix corresponding to the row index and the column index in the cache elimination signal intensity matrix is 1, if so, the row index and the column index of the submatrix form the alliance lambdaδThe interference block of (2); initializing the set of interference blocks of the alliance set omega as phi ═ G1,...,Gf,...,GMV. each federation ΛfSet of interference blocks of
Figure BDA0003224997260000079
(5b) Obtaining alliance ΛfMiddle column index set mu ═ uf|uf∈ΛfΛ, and each of the other M-1 federationsjLine index set Lf＝{β1,...,βj,...,βM-1Is traversed to the set LfWill matrix
Figure BDA00032249972600000710
Middle row index and column index set pif,j＝{(x,y)|x∈βjY ∈ μ }
Figure BDA00032249972600000711
The set with element value 1 is marked as alliance LambdafTo the interference block set GfPerforming the following steps; wherein beta isj＝{br|br∈Λj}，j∈[1,M]，f≠j；
(5c) Traverse each federation ΛfCorresponding set of interference blocks GfNumber of medium interference blocks ΨfTo obtain a cache matrix
Figure BDA0003224997260000081
The number of medium-largest interfering blocks EM, where:
Figure BDA0003224997260000082
step 6), obtaining an interference alignment result of the interference channel network topology:
(6a) designing each alliance Lambda by alliance set omega and maximum interference block number EMfAll base stations b inf,iDimension of (EM +1) as a precoding vector vf，vfThe element values in (1) are randomly generated, and a precoding vector set V ═ V { V } which corresponds to the union set omega and in which any EM +1 precoding vectors are linearly independent is obtained1,...,vf,...vM}；
(6b) Through each alliance ΛfAll base stations b inf,iOf the precoding vector vfAnd bf,iSent to the expected user uf,iDocument w ofiComputing base station bf,iTo the desired user uf,iTransmitting coded signals
Figure BDA0003224997260000083
(6c) Through each alliance ΛfAll base stations b inf,iTransmitted coded signal
Figure BDA0003224997260000084
The expected user u can be obtainedf,iReceived signal of
Figure BDA0003224997260000085
And calculate
Figure BDA0003224997260000086
Middle interference signal
Figure BDA0003224997260000087
To obtain uf,iDecoding matrix of
Figure BDA0003224997260000088
Figure BDA0003224997260000089
Figure BDA00032249972600000810
Figure BDA00032249972600000811
Figure BDA00032249972600000812
Wherein,
Figure BDA00032249972600000813
is a base station bf,iAnd user uf,iThe channel coefficient between the two channels is determined,
Figure BDA00032249972600000814
and
Figure BDA00032249972600000815
respectively representing desired users uf,iA received desired signal, an undesired signal, and white gaussian noise.
(6c) Will expect user uf,iDecoding matrix of
Figure BDA00032249972600000816
And
Figure BDA00032249972600000817
interference signal in
Figure BDA00032249972600000818
Multiplying to obtain user uf,iReceived signal of
Figure BDA00032249972600000819
In
Figure BDA00032249972600000820
Is 0, i.e.
Figure BDA00032249972600000821
Contains only the desired signal
Figure BDA00032249972600000822
And white gaussian noise
Figure BDA00032249972600000823
And realizing the network topology interference alignment of the interference channel.
The technical effects of the invention are further explained by combining simulation experiments as follows:
1. simulation experiment conditions are as follows:
the hardware platform of the simulation experiment is as follows: the processor is an InterXeon Silver 4208CPU, the main frequency is 2.1GHz, and the memory is 128G.
The software platform of the simulation experiment is as follows: the Windows10 operating system MATLAB R2016 a. The number of the antennas of the base station and the user is configured to be 1,2,3,4 and 5 in each simulation experiment.
2. Simulation content and result analysis thereof:
the user reachable degrees of freedom of the method for aligning the network topology interference of the interference channel are compared and simulated, and the result is shown in figure 2.
Referring to fig. 2, the abscissa represents the number of antennas configured by each base station and user in the interference channel network, and the ordinate represents the symmetric degrees of freedom that can be achieved by the users in the network. Wherein, the curve marked by the curve with asterisk represents the curve of the simulation result of the invention, and the curve marked by the curve with triangle represents the curve of the simulation result of the prior art.
As can be seen from fig. 2, when the files of the base stations cached by the users can eliminate part of interference signals transmitted by the base stations corresponding to the cached files, the degree of symmetry freedom of the users in the network is effectively improved.
The simulation experiment results show that the method for aligning the topological interference of the interference channel network based on the cache solves the problem of poor channel utilization rate caused by singly performing interference management from the direction of the interference alignment in the prior art, utilizes the advantage that interference signals of partial interference channels can be eliminated by cache placement of a user side, and improves the reachable symmetrical degree of freedom of a wireless network user by combining the topological interference alignment technology.

Claims (2)

1. A buffer-based interference channel network topology interference alignment method is characterized by comprising the following steps:
(1) constructing an interference channel network topological structure:
constructing K base stations B ═ B including coverage radii r1,...,bi,...,bKAnd its corresponding K desired users R ═ u1,...,ui,...,uKThe interference channel network structure of each base station biConfiguring N antennas with signal transmitting power of Pi，biCoordinate position of
Figure FDA0003224997250000011
Obeying a random distribution, biDesired user uiConfiguring N antennas with their coordinate positions
Figure FDA0003224997250000012
Compliance
Figure FDA0003224997250000013
Each base station biTo whom user u is expectediThe expected file to be transmitted is wi，biDesired user uiCache divide by biSet of files C transmitted by F other base stationsi＝{w1,...,wp,...,wFB, wherein K is more than or equal to 2, F is less than or equal to K, N is more than or equal to 1iDenotes the ith base station;
(2) constructing an interference channel network signal intensity matrix:
(2a) calculate each base station biWith each user ugThe distance between
Figure FDA0003224997250000014
And pass through
Figure FDA0003224997250000015
And biSignal transmission power PiCalculating each user ugEach base station b receivediSignal strength of
Figure FDA0003224997250000016
Figure FDA0003224997250000017
Wherein g belongs to [1, K ], and alpha represents a path loss parameter with a non-negative real number;
(2b) construction with biIs a row index, ugFor column index, each element on the main diagonal has a value of 1, and the rest elements have values of
Figure FDA0003224997250000018
And satisfy U in each column
Figure FDA0003224997250000019
Is set to 1, and then the sum of the signal strengths in each column which are not equal to 1 is calculated
Figure FDA00032249972500000110
(2c) Judgment of
Figure FDA0003224997250000021
And average noise power N0Whether or not to satisfy
Figure FDA0003224997250000022
If so, the column is divided into two rows
Figure FDA0003224997250000023
The corresponding signal strength is set to 0, otherwise, it will be
Figure FDA0003224997250000024
Setting the corresponding signal intensity as 1, and obtaining the interference channel network signal intensity matrix with the signal intensity of 0 or 1
Figure FDA0003224997250000025
(3) Obtaining a buffer elimination signal intensity matrix:
network signal strength matrix of interference channel
Figure FDA0003224997250000026
Expected user u of medium-buffer transmission filegReceived signal strength of base station
Figure FDA0003224997250000027
Set to 0, realize the network signal intensity matrix of the interference channel
Figure FDA0003224997250000028
Eliminating partial interference channel network signal to obtain buffer eliminated signal strength matrix
Figure FDA0003224997250000029
(4) Constructing a coalition in a buffer elimination signal strength matrix:
(4a) initializing a buffer to eliminate a signal strength matrix
Figure FDA00032249972500000210
The sub-matrix row index boundary and the column index boundary in (1) are respectively γ and κ, the union set is Ω, γ is equal to 1, κ is equal to 1,
Figure FDA00032249972500000211
(4b) judging buffer memory eliminating signal strength matrix
Figure FDA00032249972500000212
Middle row index range of bd∈[γ,κ+1]Column index range of uz∈[γ,κ+1]Is formed by a sub-matrix of elements
Figure FDA00032249972500000213
If the array is a unit array, executing the step (4c) if the array is the unit array, otherwise executing the step (4 d);
(4c) let κ be κ +1, and perform step (4 b);
(4d) judging whether the kappa-gamma +1 is equal to 1 or not, if so, caching the eliminated signal intensity matrix
Figure FDA00032249972500000214
Line coordinate index of the middle main diagonal element { (b)d,uz)|bd∈[γ,κ]And column coordinate index uz∈[γ,κ]Expressing the set formed by the steps as a union, adding the union into a union set omega, and executing a step (4f), otherwise, executing a step (4 e);
(4e) eliminating the buffer from the signal strength matrix
Figure FDA00032249972500000215
Middle element
Figure FDA00032249972500000216
Formed sub-matrix
Figure FDA00032249972500000217
Row coordinate index of main diagonal element of (a { (b))n,un)|bn∈[γ,κ]And column coordinate index un∈[γ,κ]Expressing the set formed by the method as a union, and adding the union into a union set omega;
(4f) determination of kappa +1>If K is true, obtaining M alliances omega ═ Λ if K is true1,...,Λf,...,ΛMElse, let γ ═ κ +1, and perform step (4 c);
(5) acquiring the maximum number of interference blocks of the alliance:
(5a) initializing the set of interference blocks of the alliance set omega as phi ═ G1,...,Gf,...,GMV. each federation ΛfSet of interference blocks of
Figure FDA0003224997250000031
(5b) Obtaining alliance lambdafMiddle column index set mu ═ uf|uf∈ΛfΛ, and each of the other M-1 federationsjLine index set Lf＝{β1,...,βj,...,βM-1Is traversed to the set LfWill matrix
Figure FDA0003224997250000032
Middle row index and column index set Πf,j＝{(x,y)|x∈βjY ∈ μ }
Figure FDA0003224997250000033
The set of element values of 1 is denoted as Federation ΛfTo the interference block set GfPerforming the following steps; wherein beta isj＝{br|br∈Λj}，j∈[1,M]，f≠j；
(5c) Traverse each federation ΛfCorresponding set of interference blocks GfNumber of medium interference blocks ΨfTo obtain a cache matrix
Figure FDA00032249972500000315
The number of medium-largest interfering blocks EM, where:
Figure FDA0003224997250000034
(6) obtaining an interference alignment result of an interference channel network topology:
(6a) design of Each AssociationfAll base stations b inf,iOf dimension (EM +1) of a precoding vector vfAnd obtaining a precoding vector set V ═ V { V } which corresponds to the union set omega and in which any EM +1 precoding vectors are linearly independent1,...,vf,...vM}；
(6b) Through each alliance ΛfAll base stations b inf,iOf the precoding vector vfAnd bf,iSent to the expected user uf,iDocument w ofiComputing base station bf,iTo the desired user uf,iTransmitting coded signals
Figure FDA0003224997250000035
(6c) By encoding the signal
Figure FDA0003224997250000036
Obtaining a desired user uf,iReceived signal of
Figure FDA0003224997250000037
And calculate
Figure FDA0003224997250000038
Middle interference signal
Figure FDA0003224997250000039
To obtain uf,iDecoding matrix of
Figure FDA00032249972500000310
Figure FDA00032249972500000311
Figure FDA00032249972500000312
Figure FDA00032249972500000313
Figure FDA00032249972500000314
Wherein,
Figure FDA0003224997250000041
is a base station bf,iAnd user uf,iThe channel coefficients of the channel between the two channels,
Figure FDA0003224997250000042
and
Figure FDA0003224997250000043
respectively representing desired users uf,iThe received desired signal, undesired signal and white gaussian noise;
(6c) will expect user uf,iDecoding matrix of
Figure FDA0003224997250000044
And
Figure FDA0003224997250000045
interference signal in
Figure FDA0003224997250000046
Multiplying to obtain user uf,iReceived signal of
Figure FDA0003224997250000047
In
Figure FDA0003224997250000048
Is 0, i.e.
Figure FDA0003224997250000049
Contains only the desired signal
Figure FDA00032249972500000410
And white gaussian noise
Figure FDA00032249972500000411
And realizing the network topology interference alignment of the interference channel.
2. The method according to claim 1, wherein the step (2a) of calculating the interference alignment of each base station biWith each user uiThe distance between
Figure FDA00032249972500000412
The calculation formula is as follows:
Figure FDA00032249972500000413
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