CN100423602C - Beam form-endowing and realizing method for co-frequency network - Google Patents

Abstract

The present invention discloses a wave beam shaping method applied to co-frequency network, which comprises: a, a base station receives upstream signals, the channels of the subzone and adjacent subzones are estimated according to the received upstream signals; b, according to the result of the channel estimation of the subzone, a user's spatial correlation matrix is constructed for a user who needs to shape wave beams in the subzone; c, according to the results of the channel estimation of the subzone and the adjacent subzones, an interference noise spatial correlation matrix of the subzone is constructed; d, the user's spatial correlation matrix obtained in the step b and the interference noise spatial correlation matrix obtained in the step c are decomposed by generalized characteristics, an eigenvector which the maximum eigenvalue is corresponding to is used as a weight vector, and downstream wave beams are shaped for the user who needs to shape wave beams in the subzone. Through the present invention, the interference of co-frequency adjacent subzones in the subzone can be effectively suppressed, and the influence of noise in the subzone is sufficiently considered so that a system obtains optimum performance.

Description

Be applied to the wave beam forming implementation method of identical networking

Technical field

The present invention relates to the signal beam figuration technology of digital cellular communication system, particularly a kind of downstream signal wave beam forming implementation method that is applied to identical networking.

Background technology

In TD SDMA (TD-SCDMA) system, the base station adopts array antenna to carry out up reception and down beam shaping.The beamforming algorithm of using in the reality roughly has two kinds at present: a kind of is beam scanning method (GOB, Grid of Beams), and another kind is power features decomposition method (P-EBB, Power Eigenvalue Based Beamforming).These two kinds of methods are consistent on criterion, all be the power maximum that satisfies up received signal, and up received signal power are represented with weight vector and amassing of user's space correlation matrix, promptly is expressed as formula $w^{\left(k\right)}=\arg \max \left(w^{\left(k\right)H}{R}_{\mathrm{xx}}^{\left(k\right)}{w}^{\left(k\right)}\right),$ W wherein ^(k)The figuration weight vector of representing k user, R _Xx ^(k)The spatial correlation matrix of representing k user.The difference of these two kinds of methods is the solution procedure difference, and the GOB method is the form that weight vector is expressed as in advance direction vector, and concentrates from the direction vector that sets in advance and to find out optimum separating; And the P-EBB method is by to R _Xx ^(k)Carry out feature decomposition, eigenvalue of maximum characteristic of correspondence vector is used as optimum separating.

Do not having under the situation of adjacent area interference, above-mentioned power maximal criterion based on the user uplink received signal can obtain preferable performance.Yet when stronger adjacent area interference is arranged, because this method does not have the ability that suppresses adjacent area interference, the existence of the adjacent sub-district of receiving terminal will seriously worsen the performance of system down link.

Summary of the invention

In view of this, main purpose of the present invention is to provide a kind of beam form-endowing method that is applied to identical networking, solves the problem of the caused system down link mis-behave of interference between the existing co-frequency neighbor cell.

The invention provides a kind of beam form-endowing method that is applied to identical networking based on above-mentioned purpose, comprising:

A) base station receives upward signal, according to the upward signal that receives channel estimating is carried out in this sub-district and adjacent sub-district;

B) according to this cell channel results estimated be the spatial correlation matrix of user's structuring user's of this pending wave beam forming in sub-district;

C) construct the interference noise spatial correlation matrix of this sub-district according to this sub-district and adjacent cell channel results estimated;

D) the interference noise spatial correlation matrix that obtains of user's space correlation matrix that step b is obtained and step c carries out generalized character and decomposes, gained eigenvalue of maximum characteristic of correspondence vector as weight vector, is carried out down beam shaping to the user of this described pending wave beam forming in sub-district.

The described structuring user's spatial correlation matrix of this method step b process comprises:

According to this cell channel results estimated is the channel response matrix that the user of described pending wave beam forming constructs this user;

The user's space correlation matrix of constructing this user equals described user's the channel response matrix and the long-pending average of self conjugation.

The interference noise spatial correlation matrix process of this sub-district of the described structure of this method step c comprises:

According to adjacent cell channel results estimated structure interference space correlation matrix;

According to this cell channel results estimated structure spatial noise correlation matrix;

Structure interference noise spatial correlation matrix equal described interference space correlation matrix and spatial noise correlation matrix with.

The described structure interference space of this method correlation matrix process comprises: the combined channel response matrix of estimating to obtain each adjacent sub-district according to adjacent cell channel;

Structure interference space correlation matrix equal adding up of each adjacent sub-district tapping channel response and self conjugation product and.

The described structure interference space of this method correlation matrix is the correlation matrix of the combined channel response matrix of described adjacent sub-district;

Or the correlation matrix of the multiuser channel response matrix of adjacent sub-district;

Or the correlation matrix of many tap response of adjacent sub-district.

Many taps that this method participates in the correlation matrix calculating of described many tap response belong to the strongest L bar tap of power in the described adjacent sub-district, and wherein L is the strong number of taps that sets in advance.

The described structure spatial noise of this method correlation matrix process comprises:

Estimate to obtain this community associated channel response matrix according to this cell channel;

Weak power tap according to this sub-district original channel response is calculated the noise power that receiving terminal is estimated;

Structure spatial noise correlation matrix equal noise power that described receiving terminal estimates square with the product of unit matrix.

The described structure spatial noise of this method correlation matrix process comprises:

Estimate to obtain this community associated channel response matrix according to this cell channel;

According to this community associated channel response matrix structure noise response matrix;

Structure spatial noise correlation matrix equals the product of noise response matrix and self associate matrix.The beam form-endowing method that is applied to identical networking provided by the invention as can be seen from above, principle based on the signal interference ratio maximum, the multi-cell channel estimated result that obtains according to base station receiver at first, make up user's space correlation matrix and interference noise spatial correlation matrix respectively, two matrixes to gained carry out the generalized character decomposition again, it is molecule that feasible downlink forming weight vector to the user is configured to the long-pending of weight vector and user's space correlation matrix, with the long-pending of weight vector and interference noise spatial correlation matrix is the signal interference ratio form of denominator, with gained eigenvalue of maximum characteristic of correspondence vector as weight vector, downstream signal figuration for the user, effectively suppressed in the downstream signal figuration process co-frequency neighbor cell to the interference of this sub-district, and take into full account this sub-district The noise, thereby the system that makes obtains optimal performance.

Description of drawings

Fig. 1 is the realization flow schematic diagram of the wave beam forming of preferred embodiment of the present invention.

Embodiment

The present invention is further described in more detail below in conjunction with drawings and the specific embodiments.

The present invention is based on the signal interference ratio maximal criterion, take into full account desired user and adjacent area interference, pursue the maximum of both signal power ratio.Available equation expression is: $w^{\left(k\right)}=\arg \max \left(\frac{w^{\left(k\right)H}{R}_{\mathrm{xx}}^{\left(k\right)}{w}^{\left(k\right)}}{w^{\left(k\right)H}{R}_{\mathrm{IN}}{w}^{\left(k\right)}}\right).$ Wherein, the expression of molecule and GOB, P-EBB method are basic identical, the expression of denominator and interference noise spatial correlation matrix R _INRelevant.

Referring to shown in Figure 1, be example with the TD-SCDMA system below, the preferable implementation of signal interference ratio beam form-endowing method under the common frequency multi-cell situation is described.

Step 101, the base station receives upward signal.

Comprise the multi-user multi-path upward signal that this sub-district and neighbor cell user terminal are sent in the upward signal that is received.

Step 102, base station utilize the upward signal that receives to comprise the multi-cell channel estimation of this sub-district and adjacent sub-district.

Here, all disturbed stronger neighbor cell around described adjacent sub-district was meant in this sub-district.The multi-cell channel estimation procedure of this step can be according to the method that generally adopts at present, the power of promptly selecting reception reaches the neighbor cell upward signal of certain threshold value, utilize this cell uplink signal and selected neighbor cell upward signal, these sub-districts are carried out channel estimating respectively, obtain the combined channel response matrix of each sub-district.

If the combined channel response matrix H of certain sub-district _n, n=0,1,2 ... represent, this cell channel response of n=0 interval scale matrix wherein, n=1,2 ... the time represent respectively adjacent sub-district 1, adjacent sub-district 2 ... channel response matrix.H _nConcrete structure with formula (1) expression:

$H_n={\left(\begin{array}{ccccccc}{h_n}^{\left(1\right)}& {h_n}^{\left(2\right)}& ...& {h_n}^{\left(k_m\right)}& ...& {h_n}^{\left(K_m\right)}& {h_n}^{(K_m+1)}\end{array}\right)}_{K_a\×P}---\left(1\right)$

Wherein, K _aThe sum of expression antenna, K _mThe sum of expression channel estimation window;

The k that represents n sub-district _mThe channel response of individual channel estimation window correspondence, it specifically represents to see formula (2) with tap:

${h_n}^{\left(k_m\right)}=\left(\begin{array}{cccc}{h_{n,1}}^{(1,k_m)}& {h_{n,2}}^{(1,k_m)}& {h_{n,w}}^{(1,k_m)}& {h_{n,W}}^{(1,k_m)}\\ {h_{n,1}}^{(2,k_m)}& {h_{n,2}}^{(2,k_m)}& {h_{n,w}}^{(2,k_m)}& {h_{n,W}}^{(2,k_m)}\\ {h_{n,1}}^{(k_a,k_m)}& {h_{n,2}}^{(k_a,k_m)}& {h_{n,w}}^{(k_a,k_m)}& {h_{n,W}}^{(k_a,k_m)}\\ {h_{n,1}}^{(K_a,k_m)}& {h_{n,2}}^{(K_a,k_m)}& {h_{n,w}}^{(K_a,k_m)}& {h_{n,W}}^{(K_a,k_m)}\end{array}\right)---\left(2\right)$

n＝0，1，2，...；k _m＝1，2，…，K _m

Wherein, W represents that window is long;

The k that represents n sub-district _mW tap of individual channel estimation window is corresponding to k _aThe channel response of root antenna.Window is long

P=128.At P=K _mDuring W, in the formula (1)

Item is empty, promptly ${h_n}^{(K_m+1)}=\left[\right].$

Step 103, the spatial correlation matrix of this cell channel estimated result structuring user's that utilization obtains from step 102.

Suppose to be k the user's in this sub-district down beam shaping, this k CU k _mIndividual channel estimation window, then this k user's spatial correlation matrix R _Xx ^(k)What can be expressed as the channel response of the channel estimation window correspondence that this user occupies and its conjugation long-pendingly gets average to the time, concrete expression as the formula (3):

$R_{\mathrm{xx}}^{\left(k\right)}=E\{{h_0}^{\left(K_m\right)}\·{h_0}^{\left(K_m\right)H}\}---\left(3\right)$

Step 104, structure interference noise spatial correlation matrix.

Interference noise spatial correlation matrix R among the present invention _INBy interference space correlation matrix R _IWith spatial noise correlation matrix R _nAnd represent i.e. R _IN=R _I+ R _n

For interference space correlation matrix R _I, the combined channel response matrix with each adjacent sub-district among the present invention is expressed, and specifically can be represented by following formula (4):

$R_I=\underset{n\≠0}{\mathrm{\Σ}}\underset{k_m}{\mathrm{\Σ}}\underset{w}{\mathrm{\Σ}}({h_{n,w}}^{\left(k_m\right)}\·{h_{n,w}}^{\left(k_m\right)H})---\left(4\right)$

In this formula, R _IBe expressed as the tapping channel response of adjacent sub-district and be directed to tap w channel estimation window k with its conjugation product _mWith the sub-district number of adjacent sub-district add up and, the adjacent sub-district of mentioning here is described consistent with step 102.

The k that represents n sub-district _mThe channel response of w tap correspondence of individual channel estimation window, its expression are seen shown in the formula (5):

${h_{n,w}}^{\left(k_m\right)}={\left(\begin{array}{cccc}{h_{n,w}}^{(1,k_m)}& {h_{n,w}}^{(2,k_m)}& {h_{n,w}}^{(k_a,k_m)}& {h_{n,w}}^{(K_a,k_m)}\end{array}\right)}^T---\left(5\right)$

As can be seen, for its interference space correlation matrix of all users in this sub-district R _IAll be identical.

In formula (4), R _IBe expressed as the correlation matrix of many tap response of many sub-districts, the tap number of participate in calculating can be one or more in described all adjacent sub-district all taps of all users, and even all, can determine that concrete principle is chosen and participate in the tap of calculating according to the demand of reality.

If the tap that participates in calculating is the part in all adjacent sub-district all taps of all users, then available formula (4) calculates.

If all taps of described all adjacent community users are all sampled, then formula (4) can be reduced to as the described form of formula (6):

$R_I=\underset{n\≠0}{\mathrm{\Σ}}\underset{k_m}{\mathrm{\Σ}}({h_n}^{\left(k_m\right)}\·{h_n}^{\left(k_m\right)H})---\left(6\right)$

In this formula, R _IBe expressed as the correlation matrix of the multiuser channel response matrix of many sub-districts, the number of users that participates in calculating can be one or more among all users of adjacent sub-district.

Certainly, if all users of described all adjacent sub-districts are sampled, then can further be reduced to form as shown in Equation (7):

$R_I=\underset{n\≠0}{\mathrm{\Σ}}(H_n\·{H_n}^H)---\left(7\right)$

Here, R _IDirectly be expressed as the correlation matrix of the combined channel response matrix of many sub-districts.Wherein, the sub-district number of participation calculating can be one or more in all adjacent sub-districts.

For example, if prepare to suppress the strongest multipath of L bar of all adjacent sub-districts, then the interference space correlation matrix R of this sub-district _IDirectly utilize the strong footpath of this L bar to express, its expression-form is by formula (4), that is:

$R_I=\underset{n\≠0;k_m;w}{\mathrm{\Σ}}({h_{n,w}}^{\left(k_m\right)}\·{h_{n,w}}^{\left(k_m\right)H}),$ Make

Wherein, described strong footpath is meant the highest footpath of detected power in described each adjacent sub-district.

For spatial noise correlation matrix R _n, it utilizes the combined channel response matrix of this sub-district to calculate, and its computational methods roughly have two kinds:

(1) at first estimates to obtain this community associated channel response matrix according to this cell channel; Utilize the weak power tap of this sub-district original channel response to calculate the noise power that receiving terminal is estimated again; Construct the spatial noise correlation matrix at last $R_n={\mathrm{\σ}}_n^{2}I,$ Wherein I is a unit matrix, σ _n ²The noise power that the expression receiving terminal is estimated, it utilizes the weak power tap of this sub-district original channel response to calculate.This scheme specifically can be 03149766.7 Chinese invention patent application " slot CDMA system interference power method of measurement " referring to the applicant in the patent No. of first to file;

(2) at first estimate to obtain this community associated channel response matrix according to this cell channel; Again according to this community associated channel response matrix structure noise response matrix; Construct spatial noise correlation matrix R at last _nBe expressed as the product of noise response matrix and its associate matrix.This scheme specifically is 03114763.1 Chinese invention patent application " slot CDMA system spatial noise correlation properties method of estimation " in the patent No. of first to file referring to the applicant.

Step 105 is to the matrix R that obtains _Xx ^(k)And R _INCarrying out generalized character decomposes.Generalized character decomposes:

$\mathrm{\λ}=\frac{w^{\left(k\right)H}{R}_{\mathrm{xx}}^{\left(k\right)}{w}^{\left(k\right)}}{w^{\left(k\right)H}{R}_{\mathrm{IN}}{w}^{\left(k\right)}}\⇒R_{\mathrm{xx}}^{\left(k\right)}{w}^{\left(k\right)}={\mathrm{\λR}}_{\mathrm{IN}}{w}^{\left(k\right)}\⇒{R_{\mathrm{IN}}}^{-1}{R}_{\mathrm{xx}}^{\left(k\right)}{w}^{\left(k\right)}={\mathrm{\λw}}^{\left(k\right)}---\left(9\right)$

Be that the generalized character decomposition in fact just is similar to matrix $R={R_{\mathrm{IN}}}^{-1}\·R_{\mathrm{xx}}^{\left(k\right)}$ Carry out feature decomposition, λ representation feature value.

Step 106 is with the eigenvalue of maximum λ of formula (9) _MaxIt is weight vector w that the characteristic of correspondence vector is used as ^(k)

Step 107 is utilized weight vector w ^(k)Go each antenna is weighted, promptly carry out k the user's in this sub-district down beam shaping.

The present invention is applicable to the digital cellular communication system that all adopt identical networking.

The above only is preferred embodiment of the present invention, in order to restriction the present invention, all any modifications of being done within the spirit and principles in the present invention, is not equal to replacement, improvement etc., all should be included within protection scope of the present invention.

Claims (8)

1. a beam form-endowing method that is applied to identical networking is characterized in that, comprising:

A) base station receives upward signal, according to the upward signal that receives channel estimating is carried out in this sub-district and adjacent sub-district;

B) according to this cell channel results estimated be the spatial correlation matrix of user's structuring user's of this pending wave beam forming in sub-district;

C) construct the interference noise spatial correlation matrix of this sub-district according to this sub-district and adjacent cell channel results estimated;

D) the interference noise spatial correlation matrix that obtains of user's space correlation matrix that step b is obtained and step c carries out generalized character and decomposes, gained eigenvalue of maximum characteristic of correspondence vector as weight vector, is carried out down beam shaping to the user of this described pending wave beam forming in sub-district.

2. method according to claim 1 is characterized in that, the described structuring user's spatial correlation matrix of step b process comprises:

According to this cell channel results estimated is the channel response matrix that the user of described pending wave beam forming constructs this user;

The user's space correlation matrix of constructing this user equals described user's the channel response matrix and the long-pending average of self conjugation.

3. method according to claim 1 is characterized in that, the interference noise spatial correlation matrix process of this sub-district of the described structure of step c comprises:

According to adjacent cell channel results estimated structure interference space correlation matrix;

According to this cell channel results estimated structure spatial noise correlation matrix;

Structure interference noise spatial correlation matrix equal described interference space correlation matrix and spatial noise correlation matrix with.

4. method according to claim 3 is characterized in that, described structure interference space correlation matrix process comprises: the combined channel response matrix of estimating to obtain each adjacent sub-district according to adjacent cell channel;

Structure interference space correlation matrix equal adding up of each adjacent sub-district tapping channel response and self conjugation product and.

5. method according to claim 4 is characterized in that, described structure interference space correlation matrix is the correlation matrix of the combined channel response matrix of described adjacent sub-district;

Or the correlation matrix of the multiuser channel response matrix of adjacent sub-district;

Or the correlation matrix of many tap response of adjacent sub-district.

6. method according to claim 5 is characterized in that, the many taps that participate in the correlation matrix calculating of described many tap response belong to the strongest L bar tap of power in the described adjacent sub-district, and wherein L is the strong number of taps that sets in advance.

7. method according to claim 3 is characterized in that, described structure spatial noise correlation matrix process comprises:

Estimate to obtain this community associated channel response matrix according to this cell channel;

Weak power tap according to this sub-district original channel response is calculated the noise power that receiving terminal is estimated;

Structure spatial noise correlation matrix equal noise power that described receiving terminal estimates square with the product of unit matrix.

8. method according to claim 3 is characterized in that, described structure spatial noise correlation matrix process comprises:

Estimate to obtain this community associated channel response matrix according to this cell channel;

According to this community associated channel response matrix structure noise response matrix;

Structure spatial noise correlation matrix equals the product of noise response matrix and self associate matrix.

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