CN103326819A - Method for suppressing common-channel interference - Google Patents

Abstract

The invention provides a method for suppressing common-channel interference. The method includes the steps that S1, a channel matrix from a base station to a user and a channel matrix from a base station in an adjacent cell to the user are obtained, and an inter-cell interference plus noise covariance matrix is calculated; S2, conversion is carried out on the inter-cell interference plus noise covariance matrix, moreover, a receiving matrix of the user is calculated, and the receiving matrix is used for processing received signals before the user receives signals transmitted by the base station; S3, a second preprocessing matrix is calculated according to the receiving matrix. Through the provided method for suppressing the common-channel interference, amplification of weak interference with the adjacent cell by the base station is prevented, and the problem that a system is poor in bit error rate performance is relieved.

Description

A kind of inhibition method of common-channel interference

Technical field

The present invention relates to the cordless communication network technical field, particularly a kind of inhibition method of common-channel interference.

Background technology

In descending MU-MIMO system, each base station and each user can configure many antennas simultaneously, and a plurality of data flow can be transmitted to each user in a base station.Single User MIMO is when channel relevancy is stronger, the spectrum efficiency of system can sharply reduce, the multiuser MIMO technology can different data flow simultaneously, with keeping pouring in to different users, and the correlation between the different users is less, thereby the frequency range efficient of the system that improves of MU-MIMO technology.Because this advantage, the MU-MIMO technology is considered to one of key technology of next generation mobile communication, is subject to paying close attention to of the international standards such as 3GPP, IEEE802.16m.

Because descending MU-MIMO communication, each base station simultaneously, transmit a plurality of data flow with frequently giving a plurality of users, therefore there is common-channel interference (Co-Channel Interference between the different data flow, CCI), each user interference of receiving can be divided three classes specifically, be presence of intercell interference (Inter-Cell Interference, ICI), interference in this residential quarter between the user (Inter-User Interference, IUI) and this user self receive interference (Inter-Stream Interference, ISI) between the different data streams.

In real system, because all can there be certain error in the process of channel estimating, channel quantitative and channel feedback, the resource of up channel feedback also is limited simultaneously, it is incomplete that these factors have caused the channel condition information of system acquisition, and non-to improve that channel condition information quantizes or obtain be an important research direction.

There are some researches show, can adopt dirty paper code (Dirty Paper Coding, the DPC) technology in the nonlinear precoding technology to obtain maximum system capacity, but the system complexity of dirty paper code is very high, is difficult to be applied in the real system.In order to solve higher this problem of non linear system complexity, the scholar proposes the lower Linear Precoding of Various Complex degree, typical algorithm has block diagonalization (Block Diagonalization, BD) algorithm, letter leaks noise ratio (Signal to leakage and noise ratio, SLNR) algorithm, being specifically described as follows of algorithm:

In the MU-MIMO system of descending many residential quarters, simple in order to narrate, suppose total J base station, there is the N strip antenna each base station, and there is K user each base station, and each user unifies to configure M antenna.I base station, k user's reception signal y _{K, i}For:

$y_{k,i}=\sqrt{{\mathrm{\ρ}}_{k,i}}{H}_{k,i}{W}_{k,i}{x}_{k,i}+\underset{l=1,l\≠k}{\overset{K_i-1}{\mathrm{\Σ}}}\sqrt{{\mathrm{\μ}}_{k,i}}{H}_{k,i}{W}_{l,i}{x}_{l,i}+\underset{\underset{j\≠i}{j=0}}{\overset{J}{\mathrm{\Σ}}}\underset{\stackrel{\‾}{k}}{\overset{K_j}{\mathrm{\Σ}}}\sqrt{{\mathrm{\μ}}_{k,j}}{H}_{k,j}{W}_{\stackrel{\‾}{k},j}{x}_{\stackrel{\‾}{k},j}+n_{k,j}---\left(1\right)$

Wherein i ∈ 1,2 ... K}, k ∈ 1 ..., J}, ρ _{K, i}Be the large scale signal fadeout factor of base station i to its service-user k, ρ _{K, i}=P _{K, i}P _Loss, P _{K, i}Be the power that base station i distributes for this base station service-user k, P _LossBe large scale decline and the shadow fading of base station i to user k; Symbol x _{K, i}Represent the signal that base station i sends to user k; μ _{L, i}(l ≠ k) for the user k of base station i, be this area interference factor, user l and user k are in same residential quarter, and therefore base station i can cause the interference between same community user owing to penetrating useful signal to service-user l and user k while, same taking place frequently; P _{L, i}Represent the transmitted power that base station i distributes to the user,

Be path loss and the shadow fading of base station i to user k; For the user k of base station i,

Adjacent cell interference factor for correspondence; Herein, Symbol for mark adjacent cell user;

Distribute to its service-user for base station j

Power,

For base station j to user k path loss and shadow loss, need to prove that user k is the service-user of base station i, k herein, the service-user that is base station i of mark; H _{K, i}Be the channel matrix of base station i to user k; W _{K, i}Pre-coding matrix when representing base station i and transmitting to user k;

For disturbing in the residential quarter,

Be presence of intercell interference.Convenient for description, we make $z_{k,i}=\underset{j=0j\≠i}{\overset{J}{\mathrm{\Σ}}}\underset{\stackrel{\‾}{k}}{\overset{K_j}{\mathrm{\Σ}}}\sqrt{{\mathrm{\μ}}_{k,j}}{H}_{k,j}{W}_{\stackrel{\‾}{k},j}{x}_{\stackrel{\‾}{k},j}+n_{k,i},$ So (1) formula can be expressed as follows:

$y_{k,i}=\sqrt{{\mathrm{\ρ}}_{k,i}}{H}_{k,i}{W}_{k,i}{x}_{k,i}+\underset{l=1,l\≠k}{\overset{K_i-1}{\mathrm{\Σ}}}\sqrt{{\mathrm{\μ}}_{k,i}}{H}_{k,i}{W}_{l,i}{x}_{l,i}+z_{k,i}---\left(2\right)$

Based on the precoding strategy of joint receiver and transmitter, adopt the line decoder restoring signal at receiver, then (2) the right and left all multiply by and separates pre-coding matrix G _{K, i}Receive signal after treatment, expression formula is:

$r_{k,i}=\sqrt{{\mathrm{\ρ}}_{k,i}}{G}_{k,i}{H}_{k,i}{W}_{k,i}{x}_{k,i}+G_{k,i}\underset{l=1,l\≠k}{\overset{M_1}{\mathrm{\Σ}}}\sqrt{{\mathrm{\μ}}_{k,i}}{H}_{k,i}{W}_{l,i}{x}_{l,i}+G_{k,i}{z}_{k,i}---\left(3\right)$

The basic thought of traditional B D-algorithm is that the design pre-coding matrix is eliminated IUI, namely designs pre-coding matrix W _{K, i}, make it to satisfy following formula:

$H_{k,i}{W}_{l,i}=0,\∀l\≠k---\left(4\right)$

The traditional B D-algorithm, can eliminate the interference in the residential quarter fully, but can not eliminate or suppress the interference of minizone, problem for presence of intercell interference, there is the scholar to propose a kind of based on leakage signal noise ratio (Signal Leakage Noise Ratio, SLNR) the improvement algorithm of maximized BD algorithm has suppressed presence of intercell interference.The pre-coding matrix of design is as follows:

W _k,i=V _k,iC _k,i (5)

V _{K, i}Be positioned at matrix

Kernel in, can satisfy (4) formula, can eliminate the interference between the user in the residential quarter.In order to suppress the base station to adjacent cell user's interference, the concept of a kind of leakage signal noise ratio SLNR is proposed, user's SLNR is,

${\mathrm{SLNR}}_{k,i}=\frac{\left(H_{k,i}{V}_{k,i}{C}_{k,i}\right){\left(H_{k,i}{V}_{k,i}{C}_{k,i}\right)}^H}{E\left\{n_{k,i}{n}_{k,i}^H\right\}+\underset{\stackrel{\‾}{k}}{\overset{{\mathrm{\Ω}}_i}{\mathrm{\Σ}}}\left(H_{\stackrel{\‾}{k},i}{W}_{\stackrel{\‾}{k},i}\right){\left(H_{\stackrel{\‾}{k},i}{W}_{\stackrel{\‾}{k},i}\right)}^H}---\left(6\right)$

N wherein _{K, i}Be the noise signal of the user k of base station i,

Be n _{K, i}Conjugate matrices, Ω _iBe the adjacent cell user's of base station i set,

Base station i arrives adjacent cell user's channel matrix,

The pre-coding matrix that transmits for the adjacent cell user.In the time of (6) formula maximum, the interference of inter-cell user is minimum, therefore designs C _{K, i}Make signal noise reveal noise ratio SLNR _{K, i}Maximum, design as follows:

$\left\{\begin{array}{c}{C}_{k,i}^{\mathrm{opt}}=\arg \underset{C_{k,i}\∈C^{N\×m}}{\max }\frac{\mathrm{Tr}\left(C_{k,i}^H(H_{k,i}{V}_{k,i}{)}^H{H}_{k,i}{V}_{k,i}{C}_{k,i}\right)}{\mathrm{Tr}\left[C_{k,i}^H(M_{k,i}{\mathrm{\σ}}_0^2+{\stackrel{\‾}{H}}_{\stackrel{\‾}{k},i}^H{\stackrel{\‾}{H}}_{\stackrel{\‾}{k},i})C_{k,i}\right]}\\ s.t.C_{k,i}^H{V}_{k.i}^H{H}_{k,i}^H{H}_{k,i}{V}_{k.i}{C}_{k,i}=D_{k,i}=\mathrm{diag}(d_{k,i,l},\·\·\·d_{k,i,M})\end{array}\right.---\left(7\right)$

Wherein,

Ω _iSet for base station i neighbor cell user number.When if the neighbor cell number of users is excessive, need a large amount of channel condition information (Channel state information, the CSI) information of feedback, the scholar proposes Ω _iFor receiving that base station i disturbs larger user's set.But words can not suppress base station i to neighbor cell Ω like this _iThe user's that set is outer interference.According to generalized singular value decomposition theoretical (Generalized Singular Value Decomposition, GSVD), Ck, i can solve the optimization problem of (7) formula when being satisfied with (8) formula.

$\left\{\begin{array}{c}{C}_{k,i}^H{V}_{k.i}^H{H}_{k,i}^H{H}_{k,i}{V}_{k.i}{C}_{k,i}=D_{k,i}=\mathrm{diag}(d_{k,i,l},\·\·\·d_{k,i,M})\\ C_{k,i}^H(M_{k,i}{\mathrm{\σ}}_0^2+{\stackrel{\‾}{H}}_{\stackrel{\‾}{k},i}^H{\stackrel{\‾}{H}}_{\stackrel{\‾}{k},i})C_{k,i}=I\end{array}\right.---\left(8\right)$

Maximized BD improves algorithm based on the leakage signal noise ratio, eliminated the interference between the user in the residential quarter, and by making the leakage signal noise ratio maximum, reduced the interference to the neighbor cell user, but it is to be noted, when the design pre-coding matrix is conciliate pre-coding matrix, concern be the throughput of system, ignored the error performance of system.

Summary of the invention

(1) technical problem that solves

The BD improvement project that the technical problem that the present invention solves is based on SLNR is ignored the error performance of system.

(2) technical scheme

The invention provides a kind of inhibition method of common-channel interference, described method comprises:

S1: obtain the channel matrix of base station to user's channel matrix and neighbor cell base station to the user, and the covariance matrix of interference plus noise between calculation plot;

S2: the covariance matrix to inter-cell interference plus noise carries out conversion, and calculates user's receiving matrix, and described receiving matrix is used for processing to received signal before the signal of reception base station transmission as the user;

S3: calculate the second preconditioning matrix according to described receiving matrix, described the second preconditioning matrix satisfies following formula,

$\left\{\begin{array}{c}{C}_{k,i}^H{\left(A_{k,i}{H}_{k,i}{V}_{k,i}\right)}^H{A}_{k,i}{H}_{k,i}{V}_{k,i}{C}_{k,i}=\mathrm{diag}({\mathrm{\α}}_1^2,\·\·\·,{\mathrm{\α}}_m^2)\\ C_{k,i}^H(M_{k,i}{\mathrm{\σ}}_0^2+{\stackrel{\‾}{H}}_{\stackrel{\‾}{k},i}^H{{\stackrel{\‾}{H}}_{\stackrel{\‾}{k},i}}_{})C_{k,i}=\mathrm{diag}({\mathrm{\β}}_1^2,\·\·\·,{\mathrm{\β}}_m^2)\end{array}\right.,$

And the restriction relation of α and β is $\left\{\begin{array}{c}1>{\mathrm{\&alpha;}}_1\&GreaterEqual;\&CenterDot;\&CenterDot;\&CenterDot;\&GreaterEqual;{\mathrm{\&alpha;}}_m>0\\ 0<{\mathrm{\&beta;}}_1\&le;\&CenterDot;\&CenterDot;\&CenterDot;\&le;{\mathrm{\&beta;}}_m<1\\ {\mathrm{\&alpha;}}_i^2+{\mathrm{\&beta;}}_i^2=1,i=1,\&CenterDot;\&CenterDot;\&CenterDot;,m\end{array}\right.,$

Wherein, k receives the user for this residential quarter, and i is this cell base station, C _{K, i}Be second preconditioning matrix of base station i to user k,

Be C _{K, i}Conjugate transpose, A _{K, i}Be the receiving matrix of base station i to user k, H _{K, i}Be the channel matrix of base station i to user k, V _{K, i}Be first preconditioning matrix of base station i to user k, α _mAnd β _mBe generalized singular value pair, M _{K, i}Be the number of user antenna, Hk, i are user's equivalence cascade matrix,

Ω _iSet for base station i neighbor cell user number; M is that base station i is to the number of the data flow of user k.

Preferably, after user's channel matrix, also comprise obtaining channel matrix and the neighbor cell base station of base station to the user among the step S1: calculate described the first preconditioning matrix V _{K, i}, described the first preconditioning matrix V _{K, i}Satisfy

Then

Wherein, H _{L, i}Be the channel matrix of base station i to user l, user l is the user except user k in the residential quarter, user k place,

Be zero right singular value vector corresponding to singular value.

Preferably, calculate

Specifically comprise:

S11: structuring user's cascade matrix ${\stackrel{\&OverBar;}{H}}_{k,i}={[H_{1,i}^H,H_{2,i}^H,H_{k-1,i}^H\&CenterDot;\&CenterDot;\&CenterDot;H_{k+1,i}^H,H_{K_i,i}^H]}^H;$

S12: with H _{L, i}

Carry out conversion, become

S13: with singular value Be decomposed into ${\stackrel{\&OverBar;}{H}}_{k,i}=U_{k,i}\left[{\mathrm{\&Lambda;}}_{k,i}0\right]{\left[V_{k.i}^{\left(1\right)}{V}_{k.i}^{\left(0\right)}\right]}^H,$ By calculating

Wherein, U _{K, i}Be left singular value vector, Λ _{K, i}Be singular value matrix,

Be right singular value vector corresponding to non-zero singular value.

Preferably, described the first preconditioning matrix V _{K, i}With described the second preconditioning matrix C _{K, i}Product be pre-coding matrix, described pre-coding matrix is used for transmitted signal being carried out preliminary treatment when the base station during to user's transmitted signal.

Preferably, among the step S2 covariance matrix of inter-cell interference plus noise being carried out conversion specifically comprises:

The covariance matrix of inter-cell interference plus noise is:

$E\left\{z_{k,i}{z}_{k,i}^H\right\}=(\underset{j=0j\&NotEqual;i}{\overset{J}{\mathrm{\&Sigma;}}}\underset{\stackrel{\&OverBar;}{k}=0}{\overset{K}{\mathrm{\&Sigma;}}}{H}_{k,j}{W}_{\stackrel{\&OverBar;}{k},j}(H_{k,j}{W}_{\stackrel{\&OverBar;}{k},j}{)}^H+{\mathrm{\&sigma;}}_0^{2}I),$

Covariance matrix to inter-cell interference plus noise is transformed to:

${(\underset{j=0j\&NotEqual;i}{\overset{J}{\mathrm{\&Sigma;}}}\underset{\stackrel{\&OverBar;}{k}=0}{\overset{K}{\mathrm{\&Sigma;}}}{\mathrm{\&mu;}}_{\stackrel{\&OverBar;}{k},j}{H}_{k,j}{W}_{\stackrel{\&OverBar;}{k},j}{\left(H_{k,j}{W}_{\stackrel{\&OverBar;}{k},j}\right)}^H+{\mathrm{\&sigma;}}_0^{2}I)}^{-1}=A_{k,i}^H{A}_{k,i},$

${\mathrm{\&mu;}}_{\stackrel{\&OverBar;}{k},j}=P_{\stackrel{\&OverBar;}{k},j}{P}_{k,j}^{\mathrm{loss}}$

Then described user's receiving matrix is A _{K, i}

Wherein, z _{K, i}Be presence of intercell interference and noise sum,

Be z _{K, i}Conjugate transpose, H _{K, j}Be the channel matrix of base station j to user k, For base station j to the user

Pre-coding matrix, the user

Be the user in the adjacent cell j of residential quarter, user k place,

Noise variance, for the user k of base station i,

Be the adjacent cell interference factor of residential quarter, user k place,

For base station j to the user

Power,

For base station j to user k path loss and shadow loss.

Preferably, step S3 also comprises and working as

The time, described the second preconditioning matrix satisfies following formula:

$\left\{\begin{array}{c}{C}_{k,i}^H(A_{k,i}{H}_{k,i}{V}_{k,i}{)}^H{A}_{k,i}{H}_{k,i}{V}_{k,i}{C}_{k,i}=I\\ C_{k,i}^H(M_{k,i}{\mathrm{\&sigma;}}_0^2+{\stackrel{\&OverBar;}{H}}_{\stackrel{\&OverBar;}{k},i}^H{\stackrel{\&OverBar;}{H}}_{\stackrel{\&OverBar;}{k},i})C_{k,i}=\mathrm{diag}({\mathrm{\&lambda;}}_1^2,\&CenterDot;\&CenterDot;\&CenterDot;{\mathrm{\&lambda;}}_i^2,\&CenterDot;\&CenterDot;\&CenterDot;,{\mathrm{\&lambda;}}_m^2)\end{array}\right.,$

Wherein, I and λ _iBe generalized singular value pair.

Preferably, when the base station to user's transmitted signal x _{K, i}The time transmitted signal carried out preliminary treatment, then obtaining described reception signal is V _{K, i}C _{K, i}x _{K, i}

Preferably, described reception signal is processed, the reception signal after obtaining processing is V _{K, i}C _{K, i}x _{K, i}A _{K, i}

(3) beneficial effect

The present invention has prevented the amplification of base station to neighbor cell user weak jamming by a kind of inhibition method of common-channel interference is provided, and has alleviated the poor problem of system's error performance.

Description of drawings

The method flow diagram that Fig. 1 provides.

Embodiment

Below in conjunction with the accompanying drawing in the embodiment of the invention, the technical scheme in the embodiment of the invention is clearly and completely described.

Embodiment 1:

The invention provides a kind of inhibition method of common-channel interference, as shown in Figure 1, described method comprises:

S1: obtain the channel matrix of base station to user's channel matrix and neighbor cell base station to the user, and the covariance matrix of interference plus noise between calculation plot;

S2: the covariance matrix to inter-cell interference plus noise carries out conversion, and calculates user's receiving matrix, and described receiving matrix is used for processing to received signal before the signal of reception base station transmission as the user;

S3: calculate the second preconditioning matrix according to described receiving matrix, described the second preconditioning matrix satisfies following formula,

$\left\{\begin{array}{c}{C}_{k,i}^H(A_{k,i}{H}_{k,i}{V}_{k,i}{)}^H{A}_{k,i}{H}_{k,i}{V}_{k,i}{C}_{k,i}=\mathrm{diag}({\mathrm{\&alpha;}}_1^2,\&CenterDot;\&CenterDot;\&CenterDot;,{\mathrm{\&alpha;}}_m^2)\\ C_{k,i}^H(M_{k,i}{\mathrm{\&sigma;}}_0^2+{\stackrel{\&OverBar;}{H}}_{\stackrel{\&OverBar;}{k},i}^H{\stackrel{\&OverBar;}{H}}_{\stackrel{\&OverBar;}{k},i})C_{k,i}=\mathrm{diag}({\mathrm{\&beta;}}_1^2,\&CenterDot;\&CenterDot;\&CenterDot;,{\mathrm{\&beta;}}_m^2)\end{array}\right.---\left(9\right)$

And the restriction relation of α and β is $\left\{\begin{array}{c}1>{\mathrm{\&alpha;}}_1\&GreaterEqual;\&CenterDot;\&CenterDot;\&CenterDot;\&GreaterEqual;{\mathrm{\&alpha;}}_m>0\\ 0<{\mathrm{\&beta;}}_1\&le;\&CenterDot;\&CenterDot;\&CenterDot;\&le;{\mathrm{\&beta;}}_m<1\\ {\mathrm{\&alpha;}}_i^2+{\mathrm{\&beta;}}_i^2=1,i=1,\&CenterDot;\&CenterDot;\&CenterDot;,m\end{array}\right.,$

Wherein, k receives the user for this residential quarter, and i is this cell base station, C _{K, i}Be second preconditioning matrix of base station i to user k,

Be C _{K, i}Conjugate transpose, A _{K, i}Be the receiving matrix of base station i to user k, H _{K, i}Be the channel matrix of base station i to user k, V _{K, i}Be first preconditioning matrix of base station i to user k, α _mAnd β _mBe generalized singular value pair, M _{K, i}Be the number of user antenna,

Be user's equivalence cascade matrix,

Ω _iSet for base station i neighbor cell user number; M is that base station i is to the number of the data flow of user k.

Under the multiuser MIMO network configuration of a plurality of residential quarters, user's reception signal (signal before receiving terminal is processed) is:

Formula (10) is identical with formula (1), omits the implication of formula internal symbol herein.

Process to received signal,

$r_{k,i}=\sqrt{{\mathrm{\&rho;}}_{k,i}}{G}_{k,i}{H}_{k,i}{W}_{k,i}{x}_{k,i}+G_{k,i}\underset{l=1,l\&NotEqual;k}{\overset{K_i-1}{\mathrm{\&Sigma;}}}\sqrt{{\mathrm{\&mu;}}_{k,i}}{H}_{k,i}{W}_{l,i}{x}_{l,i}+G_{k,i}\underset{\underset{j\&NotEqual;i}{j=0}}{\overset{J}{\mathrm{\&Sigma;}}}\underset{\stackrel{\&OverBar;}{k}}{\overset{K_j}{\mathrm{\&Sigma;}}}\sqrt{{\mathrm{\&mu;}}_{k,j}}{H}_{k,j}{W}_{\stackrel{\&OverBar;}{k},j}{x}_{\stackrel{\&OverBar;}{k},j}+G_{k,i}{n}_{k,j}---\left(11\right)$

In the formula, G _{K, i}It is the signal receiving matrix of the service-user k of base station i.

Base station i processes transmitted signal before the user k transmitted signal, and it is W to the pre-coding matrix of user k that base station i is set _{K, i}=V _{K, i}C _{K, i}

Wherein, preconditioning matrix V is set _{K, i}Step as follows:

In order to eliminate inter-user interference in the residential quarter, need to make V satisfy following formula,

$H_{k,i}{V}_{l,i}=0,\&ForAll;l\&NotEqual;k---\left(12\right)$

Wherein, H _{K, i}For the channel matrix of base station i to user k, obtained V by the base station _{L, i}Be first pre-coding matrix of base station i to its service-user l, up channel can be passed through in the base station, measures the channel condition information of all users in this base station, and is used for the downstream signal precoding processing.The cascade matrix of our structuring user's,

${\stackrel{\&OverBar;}{H}}_{k,i}={[H_{1,i}^H\&CenterDot;\&CenterDot;\&CenterDot;H_{k-1,i}^H{H}_{k+1,i}^H\&CenterDot;\&CenterDot;\&CenterDot;H_{K,i}^H]}^H---\left(13\right)$

(13) formula is rewritten as following form:

${\stackrel{\&OverBar;}{H}}_{k,i}{V}_{l,i}=0---\left(14\right)$

We are right

Carry out singular value decomposition, obtain after the decomposition

U wherein _{K, i}And Λ _{K, i}Be respectively

Left singular matrix and singular value matrix;

With

Respectively expression

Right singular matrix in the vector of corresponding 0 singular value of vector sum of corresponding non-zero singular value, and satisfy The first preconditioning matrix is set is

User's receiving matrix G _{K, i}With the second preconditioning matrix C _{K, i}Co-design as follows:

Order

z _{K, i}Its covariance matrix can be expressed as:

$E\left\{z_{k,i}{z}_{k,i}^H\right\}=(\underset{j=0j\&NotEqual;i}{\overset{J}{\mathrm{\&Sigma;}}}\underset{\stackrel{\&OverBar;}{k}=0}{\overset{K}{\mathrm{\&Sigma;}}}{H}_{k,j}{W}_{\stackrel{\&OverBar;}{k},j}(H_{k,j}{W}_{\stackrel{\&OverBar;}{k},j}{)}^H+{\mathrm{\&sigma;}}_0^{2}I).$

Covariance matrix is done such as down conversion:

${(\underset{j=0j\&NotEqual;i}{\overset{J}{\mathrm{\&Sigma;}}}\underset{\stackrel{\&OverBar;}{k}=0}{\overset{K}{\mathrm{\&Sigma;}}}{\mathrm{\&mu;}}_{k,j}{H}_{k,j}{W}_{\stackrel{\&OverBar;}{k},j}{\left(H_{k,j}{W}_{\stackrel{\&OverBar;}{k},j}\right)}^H+{\mathrm{\&sigma;}}_0^{2}I)}^{-1}=A_{k,i}^H{A}_{k,i}---\left(15\right)$

Then user's receiving matrix is G _{K, i}=A _{K, i}

Then described user's receiving matrix is A _{K, i}

Wherein, z _{K, i}Be presence of intercell interference and noise sum, Be z _{K, i}Conjugate transpose, H _{K, j}Be the channel matrix of base station j to user k,

For base station j to the user

Pre-coding matrix, utilize existing BD to improve algorithm and try to achieve, such as the improvement algorithm based on BD.The user

Be the user in the adjacent cell j of residential quarter, user k place,

Noise variance, for the user k of base station i,

Be the adjacent cell interference factor of residential quarter, user k place,

For base station j to the user

Power,

For base station j to user k path loss and shadow loss.

C _{K, i}The theory analysis process as follows:

Theoretical according to generalized singular value decomposition, for nonsingular value matrix M ∈ C ^{P * m}With N ∈ C ^{P * m}Exist unitary matrice U, V and nonsingular value matrix Q to satisfy

$\left\{\begin{array}{c}{\left(\mathrm{UMQ}\right)}^H\mathrm{UMQ}=Q^H{M}^H\mathrm{MQ}=\mathrm{diag}({\mathrm{\&alpha;}}_1^2,\&CenterDot;\&CenterDot;\&CenterDot;,{\mathrm{\&alpha;}}_m^2)\\ {\left(\mathrm{VNQ}\right)}^H\mathrm{VNQ}=Q^H{N}^H\mathrm{NQ}=\mathrm{diag}({\mathrm{\&beta;}}_1^2,\&CenterDot;\&CenterDot;\&CenterDot;,{\mathrm{\&beta;}}_m^2)\end{array}\right.---\left(16\right)$

Wherein α and β restriction relation are $\left\{\begin{array}{c}1>{\mathrm{\&alpha;}}_1\&GreaterEqual;\&CenterDot;\&CenterDot;\&CenterDot;\&GreaterEqual;{\mathrm{\&alpha;}}_m>0\\ 0<{\mathrm{\&beta;}}_1\&le;\&CenterDot;\&CenterDot;\&CenterDot;\&le;{\mathrm{\&beta;}}_m<1\\ {\mathrm{\&alpha;}}_i^2+{\mathrm{\&beta;}}_i^2=1,i=1,\&CenterDot;\&CenterDot;\&CenterDot;,m\end{array}\right..$

Theoretical according to generalized singular value decomposition, when

The time, C _{K, i}Satisfy (9) formula, otherwise, C calculated according to (17) formula _{K, i}, wherein, generalized singular value is

$\left\{\begin{array}{c}{C}_{k,i}^H(A_{k,i}{H}_{k,i}{V}_{k,i}{)}^H{A}_{k,i}{H}_{k,i}{V}_{k,i}{C}_{k,i}=I\\ C_{k,i}^H(M_{k,i}{\mathrm{\&sigma;}}_0^2+{\stackrel{\&OverBar;}{H}}_{\stackrel{\&OverBar;}{k},i}^H{\stackrel{\&OverBar;}{H}}_{\stackrel{\&OverBar;}{k},i})C_{k,i}=\mathrm{diag}({\mathrm{\&lambda;}}_1^2,\&CenterDot;\&CenterDot;\&CenterDot;{\mathrm{\&lambda;}}_i^2,\&CenterDot;\&CenterDot;\&CenterDot;,{\mathrm{\&lambda;}}_m^2)\end{array}\right.---\left(17\right)$

The present invention has eliminated the interference between the user in the residential quarter fully by the design pre-coding matrix, and has suppressed the strong jamming of base station to the neighbor cell user, and design receiving terminal matrix has solved the scale-up problem of base station to neighbor cell user weak jamming.Loosened the maximized condition restriction of SLNR, exchanged the raising of system's error performance with the loss than the mini system capacity for, balance the channel gain between user's different data streams, guaranteed user's service quality.

Above execution mode only is used for explanation the present invention; and be not limitation of the present invention; the those of ordinary skill in relevant technologies field; in the situation that do not break away from the spirit and scope of the present invention; can also make a variety of changes and modification; therefore all technical schemes that are equal to also belong to category of the present invention, and scope of patent protection of the present invention should be defined by the claims.

Claims (8)

1. the inhibition method of a common-channel interference is characterized in that, described method comprises:

S1: obtain the channel matrix of base station to user's channel matrix and neighbor cell base station to the user, and the covariance matrix of interference plus noise between calculation plot;

S2: the covariance matrix to inter-cell interference plus noise carries out conversion, and calculates user's receiving matrix, and described receiving matrix is used for the user to be processed before the signal that receives the base station transmission to received signal;

S3: calculate the second preconditioning matrix according to described receiving matrix, described the second preconditioning matrix satisfies following formula,

$\left\{\begin{array}{c}{C}_{k,i}^H(A_{k,i}{H}_{k,i}{V}_{k,i}{)}^H{A}_{k,i}{H}_{k,i}{V}_{k,i}{C}_{k,i}=\mathrm{diag}({\mathrm{\&alpha;}}_1^2,\&CenterDot;\&CenterDot;\&CenterDot;,{\mathrm{\&alpha;}}_m^2)\\ C_{k,i}^H(M_{k,i}{\mathrm{\&sigma;}}_0^2+{\stackrel{\&OverBar;}{H}}_{\stackrel{\&OverBar;}{k},i}^H{\stackrel{\&OverBar;}{H}}_{\stackrel{\&OverBar;}{k},i})C_{k,i}=\mathrm{diag}({\mathrm{\&beta;}}_1^2,\&CenterDot;\&CenterDot;\&CenterDot;,{\mathrm{\&beta;}}_m^2)\end{array}\right.,$

And the restriction relation of α and β is $\left\{\begin{array}{c}1>{\mathrm{\&alpha;}}_1\&GreaterEqual;\&CenterDot;\&CenterDot;\&CenterDot;\&GreaterEqual;{\mathrm{\&alpha;}}_m>0\\ 0<{\mathrm{\&beta;}}_1\&le;\&CenterDot;\&CenterDot;\&CenterDot;\&le;{\mathrm{\&beta;}}_m<1\\ {\mathrm{\&alpha;}}_i^2+{\mathrm{\&beta;}}_i^2=1,i=1,\&CenterDot;\&CenterDot;\&CenterDot;,m\end{array}\right.,$

Wherein, k receives the user for this residential quarter, and i is this cell base station, C _{K, i}Be second preconditioning matrix of base station i to user k,

Be C _{K, i}Conjugate transpose, A _{K, i}Be the receiving matrix of base station i to user k, H _{K, i}Be the channel matrix of base station i to user k, V _{K, i}Be first preconditioning matrix of base station i to user k, α _mAnd β _mBe generalized singular value pair, M _{K, i}Be the number of user antenna,

Be user's equivalence cascade matrix,

Ω _iSet for base station i neighbor cell user number; M is that base station i is to the number of the data flow of user k.

2. method according to claim 1 is characterized in that, also comprises after user's channel matrix obtaining channel matrix and the neighbor cell base station of base station to the user among the step S1: calculate described the first preconditioning matrix V _{K, i}, described the first preconditioning matrix V _{K, i}Satisfy $H_{l,i}{V}_{k,i}^{\left(0\right)}=0\&ForAll;k\&NotEqual;l,$ Then $V_{k,i}=V_{k,i}^{\left(0\right)};$

Wherein, H _{L, i}Be the channel matrix of base station i to user l, user l is the user except user k in the residential quarter, user k place,

Be zero right singular value vector corresponding to singular value.

3. method according to claim 2 is characterized in that, calculates

Specifically comprise:

S11: structuring user's cascade matrix ${\stackrel{\&OverBar;}{H}}_{k,i}={[H_{1,i}^H,H_{2,i}^H,H_{k-1,i}^H\&CenterDot;\&CenterDot;\&CenterDot;H_{k+1,i}^H,H_{K_i,i}^H]}^H;$

S12: will

Carry out conversion, become

S13: with singular value

Be decomposed into ${\stackrel{\&OverBar;}{H}}_{k,i}=U_{k,i}\left[{\mathrm{\&Lambda;}}_{k,i}0\right]{\left[V_{k.i}^{\left(1\right)}{V}_{k.i}^{\left(0\right)}\right]}^H,$ By calculating

Wherein, U _{K, i}Be left singular value vector, Λ _{K, i}Be singular value matrix,

Be right singular value vector corresponding to non-zero singular value.

4. each described method according to claim 1 and 2 is characterized in that described the first preconditioning matrix V _{K, i}With described the second preconditioning matrix C _{K, i}Product be pre-coding matrix, described pre-coding matrix is used for transmitted signal being carried out preliminary treatment when the base station during to user's transmitted signal.

5. method according to claim 1 is characterized in that, among the step S2 covariance matrix of inter-cell interference plus noise is carried out conversion and specifically comprises:

The covariance matrix of inter-cell interference plus noise is:

$E\left\{z_{k,i}{z}_{k,i}^H\right\}=(\underset{j=0j\&NotEqual;i}{\overset{J}{\mathrm{\&Sigma;}}}\underset{\stackrel{\&OverBar;}{k}=0}{\overset{K}{\mathrm{\&Sigma;}}}{H}_{k,j}{W}_{\stackrel{\&OverBar;}{k},j}(H_{k,j}{W}_{\stackrel{\&OverBar;}{k},j}{)}^H+{\mathrm{\&sigma;}}_0^{2}I),$

Covariance matrix to inter-cell interference plus noise is transformed to:

${(\underset{j=0j\&NotEqual;i}{\overset{J}{\mathrm{\&Sigma;}}}\underset{\stackrel{\&OverBar;}{k}=0}{\overset{K}{\mathrm{\&Sigma;}}}{\mathrm{\&mu;}}_{\stackrel{\&OverBar;}{k},j}{H}_{k,j}{W}_{\stackrel{\&OverBar;}{k},j}{\left(H_{k,j}{W}_{\stackrel{\&OverBar;}{k},j}\right)}^H+{\mathrm{\&sigma;}}_0^{2}I)}^{-1}=A_{k,i}^H{A}_{k,i},$

${\mathrm{\&mu;}}_{\stackrel{\&OverBar;}{k},j}=P_{\stackrel{\&OverBar;}{k},j}{P}_{k,j}^{\mathrm{loss}}$

Then described user's receiving matrix is A _{K, i}

Wherein, z _{K, i}Be presence of intercell interference and noise sum, Be z _{K, i}Conjugate transpose, H _{K, j}Be the channel matrix of base station j to user k,

For base station j to the user

Pre-coding matrix, the user

Be the user in the adjacent cell j of residential quarter, user k place,

Noise variance, for the user k of base station i,

Be the adjacent cell interference factor of residential quarter, user k place,

For base station j to the user Power,

For base station j to user k path loss and shadow loss.

6. method according to claim 1 is characterized in that, step S3 also comprises and working as The time, described the second preconditioning matrix satisfies following formula:

$\left\{\begin{array}{c}{C}_{k,i}^H(A_{k,i}{H}_{k,i}{V}_{k,i}{)}^H{A}_{k,i}{H}_{k,i}{V}_{k,i}{C}_{k,i}=I\\ C_{k,i}^H(M_{k,i}{\mathrm{\&sigma;}}_0^2+{\stackrel{\&OverBar;}{H}}_{\stackrel{\&OverBar;}{k},i}^H{\stackrel{\&OverBar;}{H}}_{\stackrel{\&OverBar;}{k},i})C_{k,i}=\mathrm{diag}({\mathrm{\&lambda;}}_1^2,\&CenterDot;\&CenterDot;\&CenterDot;{\mathrm{\&lambda;}}_i^2,\&CenterDot;\&CenterDot;\&CenterDot;,{\mathrm{\&lambda;}}_m^2)\end{array}\right.,$

Wherein, I and λ _iBe generalized singular value pair.

7. each described method is characterized in that according to claim 1～6, when the base station to user's transmitted signal x _{K, i}The time transmitted signal carried out preliminary treatment, then obtaining described reception signal is V _{K, i}C _{K, i}x _{K, i}

8. method according to claim 7 is characterized in that, described reception signal is processed, and the reception signal after obtaining processing is V _{K, i}C _{K, i}x _{K, i}A _{K, i}