CN113691343A - Cache-based interference channel network topology interference alignment method - Google Patents
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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 topological structure; constructing an interference channel network signal intensity matrix; acquiring a cache cancellation signal intensity matrix; establishing a coalition 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
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 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 ofObeying a random distribution, biDesired user uiConfiguring N antennas with their coordinate positionsComplianceEach base station biTo whom user u is expectediThe expected file to be transmitted is wi,biDesired user uiCache divide by biSets of files transmitted by other than F base stationsAnd Ci={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 betweenAnd pass throughAnd biSignal transmission power PiCalculating each user ugEach base station b receivediSignal strength of
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 ofAnd satisfy U in each columnIs set to 1, and then the sum of the signal strengths in each column which are not equal to 1 is calculated
(2c) Judgment ofAnd average noise power N0Whether or not to satisfyIf so, the column is divided into two rowsThe corresponding signal strength is set to 0, otherwise, it will beSetting the corresponding signal intensity as 1, and obtaining the interference channel network signal intensity matrix with the signal intensity of 0 or 1
(3) Obtaining a buffer elimination signal intensity matrix:
network signal strength matrix of interference channelExpected user u of medium-buffer transmission filegReceived signal strength of base stationSet to 0, realize the network signal intensity matrix of the interference channelEliminating partial interference channel network signal to obtain buffer eliminated signal strength matrix
(4) Constructing a coalition in a buffer elimination signal strength matrix:
(4a) initializing a buffer to eliminate a signal strength matrixThe 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,
(4b) judging buffer memory eliminating signal strength matrixMiddle row index range of bd∈[γ,κ+1]Column index range of uz∈[γ,κ+1]Is formed by a sub-matrix of elementsIf 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 matrixLine 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 matrixMiddle elementFormed sub-matrixRow 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
(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 matrixMiddle row index and column index set Πf,j={(x,y)|x∈βjY ∈ μ }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 matrixThe number of medium-largest interfering blocks EM, where:
(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
(6c) By encoding the signalObtaining a desired user uf,iReceived signal ofAnd calculateMiddle interference signalTo obtain uf,iDecoding matrix of
Wherein,andrespectively representing desired users uf,iA received desired signal, an undesired signal, and white gaussian noise.
(6c) Will expect user uf,iDecoding matrix ofAndinterference signal inMultiplying to obtain user uf,iReceived signal ofInIs 0, i.e.Contains only the desired signalAnd white gaussian noiseAnd 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 ofObeying a random distribution, biDesired user uiConfiguring N antennas with their coordinate positionsComplianceEach base station biTo whom user u is expectediExpected file of transmissionIs 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 betweenAnd pass throughAnd biSignal transmission power PiCalculating each user ugEach base station b receivediSignal strength of
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) 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 ofAnd satisfy U in each columnIs set to 1, and then the sum of the signal strengths in each column which are not equal to 1 is calculated
(2c) Judgment ofAnd average noise power N0Whether or not to satisfyIf so, the column is divided into two rowsThe corresponding signal strength is set to 0, otherwise, it will beSetting the corresponding signal intensity as 1, and obtaining the interference channel network signal intensity matrix with the signal intensity of 0 or 1
Step 3) eliminating partial interference channel network signals through user buffer:
because the signal formed by precoding the file transmitted by the base station can be decoded and restored to the original file at the user terminal, 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, thereby reducing the interference signal received by the user and improving the channel utilization rate in the network; 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 matrixThe middle row index is p and the column index is uiOf (2) element(s)Element value of 1Setting to 0, obtaining the signal intensity matrix of the network signal for eliminating partial interference channel
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 signalsThe 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,
(4b) judgment ofMiddle row index range of bd∈[γ,κ+1]Column index range of uz∈[γ,κ+1]Is formed by a sub-matrix of elementsIf 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 matrixLine coordinate index of the middle main diagonal element { (b)d,uz)|bd∈[γ,κ]And column coordinate index uz∈[γ,κ]Expressing the formed set as a union, adding the union set omega, and executing the step (4f)Otherwise, executing step (4 e);
(4e) eliminating the buffer from the signal strength matrixMiddle elementFormed sub-matrixRow 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) obtaining one alliance Lambda in every two alliancesδAnd 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
(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 matrixMiddle row index and column index set Πf,j={(x,y)|x∈βjY ∈ μ }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 matrixThe number of medium-largest interfering blocks EM, where:
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,iOf dimension (EM +1) of 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
(6c) Through each alliance ΛfAll base stations b inf,iTransmitted coded signalThe expected user u can be obtainedf,iReceived signal ofAnd calculateMiddle interference signalTo obtain uf,iDecoding matrix of
Wherein,is a base station bf,iAnd user uf,iThe channel coefficients of the channel between the two channels,andrespectively representing desired users uf,iA received desired signal, an undesired signal, and white gaussian noise.
(6c) Will expect user uf,iDecoding matrix ofAndinterference signal inMultiplying to obtain user uf,iReceived signal ofInIs 0, i.e.Contains only the desired signalAnd white gaussian noiseAnd 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 user caches the file of the base station, part of the interference signals transmitted by the base station corresponding to the cache can be eliminated, and the degree of symmetry freedom of the user 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 ofObeying a random distribution, biDesired user uiConfiguring N antennas with their coordinate positionsComplianceEach 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 betweenAnd pass throughAnd biSignal transmission power PiCalculating each user ugEach base station b receivediSignal strength of
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 ofAnd a K x K dimensional signal strength matrix U, and dividing U perIn one column satisfiesIs set to 1, and then the sum of the signal strengths in each column which are not equal to 1 is calculated
(2c) Judgment ofAnd average noise power N0Whether or not to satisfyIf so, the column is divided into two rowsThe corresponding signal strength is set to 0, otherwise, it will beSetting the corresponding signal intensity as 1, and obtaining the interference channel network signal intensity matrix with the signal intensity of 0 or 1
(3) Obtaining a buffer elimination signal intensity matrix:
network signal strength matrix of interference channelExpected user u of medium-buffer transmission filegReceived signal strength of base stationSet to 0, realize the network signal intensity matrix of the interference channelEliminating partial interference channel network signal to obtain buffer eliminated signal strength matrix
(4) Constructing a coalition in a buffer elimination signal strength matrix:
(4a) initializing a buffer to eliminate a signal strength matrixThe 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,
(4b) judging buffer memory eliminating signal strength matrixMiddle row index range of bd∈[γ,κ+1]Column index range of uz∈[γ,κ+1]Is formed by a sub-matrix of elementsIf 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 matrixLine 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 matrixMiddle elementFormed sub-matrixRow 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
(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 matrixMiddle row index and column index set Πf,j={(x,y)|x∈βjY ∈ μ }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 matrixThe number of medium-largest interfering blocks EM, where:
(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
(6c) By encoding the signalObtaining a desired user uf,iReceived signal ofAnd calculateMiddle interference signalNumber (C)To obtain uf,iDecoding matrix of
Wherein,is a base station bf,iAnd user uf,iThe channel coefficients of the channel between the two channels,andrespectively representing desired users uf,iA received desired signal, an undesired signal, and white gaussian noise.
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