CN101841302B - Effective order estimator for predistorter - Google Patents

Abstract

The invention discloses an effective order estimator for a predistorter, which comprises a conversion unit, a decomposition unit and an approximation unit, wherein the conversion unit is used for receiving a polynomial of the predistorter, and converting the polynomial into matrix representation to obtain a predistortion matrix consisting of K predistortion functions, wherein K refers to the maximum order of the polynominal; the decomposition unit is used for performing singular value decomposition on the predistortion matrix to obtain a singular value matrix; and the approximation unit is used for acquiring the effective sequence of the predistortion matrix according to the singular value matrix, wherein the effective sequence of the predistortion matrix is the effective order of the polynominal and is the minimal sequence of an approximate predistortion matrix capable of achieving the preset approximation effect of approximating the predistortion matrix, and the approximate predistortion matrix is a matrix for approximating the predistortion matrix. The effective order estimator reduces the complexity of the polynominal-based power amplifier predistorter while ensuring the predistortion performance so as to have better convergence property and stability.

Description

A kind of effective order estimator of predistorter

Technical field

The present invention relates to a kind of effective order estimator of predistorter.

Background technology

Power amplifier (PA) is one of requisite parts in the wireless communication system, and the raising of its effect is for Wireless Telecom Equipment, and especially the energy-saving consumption-reducing to portable mobile terminal is significant.Portable terminals such as the base station that radio communication operator adopted, repeater, radio and television launching tower and the employed mobile phone of user, mobile TV, Miniaturized Communications equipment all relate to the efficacy problems of power amplifier.

The distortion of the transmission signals that nonlinear characteristic caused of power amplifier is to cause one of major reason that the power amplifier effect reduces, and therefore, it is most important for the development of radio communication to improve its effect that power amplifier is carried out linearization process.

The linearization process of power amplifier generally comprises back-off technology, envelope elimination and recovery technology, cartesian loop rear feed technology, feedforward linearized technology, nonlinear device linearization technique and digital pre-distortion technology etc.; Wherein, Digital pre-distortion technology has advantages such as high, the suitable bandwidth of stability is wide, precision is high, the realization cost is lower, is widely used at present.

The power amplifier digital pre-distortion technology has based on look-up table with based on multinomial two class methods.Method based on look-up table needs a large amount of memory cell, and estimation and convergence rate are slow; , for LUT Method, can save a large amount of RAM (Random Access Memory) memory cell, and very fast convergence rate is arranged based on polynomial pre-distortion method.Basic thought based on polynomial pre-distortion method is: through regulating the contrary complex gain curve of multinomial coefficient match PA.

In based on polynomial power amplifier pre-distortion technology; When the used multinomial exponent number of predistorter is higher; System complexity is index to be increased, and correspondingly makes the hardware complexity of power amplifier pre-distortion device and realizes that difficulty increases greatly, and then cause the bad stability of predistorter.In addition, when the design predistorter, order of a polynomial has determined the free transmission range design and the linearisation effect of power amplifier median filter.

Current based on polynomial power amplifier pre-distortion technology in, make the predistortion effect obvious, can cause the computation complexity of higher predistorter usually; And to reduce complexity, must reduce the multinomial exponent number again, thereby reduce the predistortion effect.

Summary of the invention

The effective order estimator that the purpose of this invention is to provide a kind of predistorter; It reduces the complexity based on polynomial power amplifier pre-distortion device when guaranteeing the predistortion performance, and then guarantees based on polynomial power amplifier pre-distortion utensil better convergence and stability are arranged

For this reason, the invention provides a kind of effective order estimator of predistorter, it is characterized in that, comprising: converting unit, be used to receive the multinomial of predistorter, convert said multinomial into matrix notation, obtain the predistortion matrix that constitutes by K predistortion function; K representes said polynomial maximum order; Resolving cell is used for said predistortion matrix is carried out singular value decomposition, obtains singular value matrix; Approximation unit; Be used for according to said singular value matrix; Obtain effective order of said predistortion matrix, effective order of said predistortion matrix is said polynomial effective rank, wherein; Effective order of said predistortion matrix is can reach the predetermined minimum order of approaching predistortion matrix of approaching effect to approaching of said predistortion matrix, and the said predistortion matrix of approaching is the matrix that said predistortion matrix is approached.

According to the present invention,, under the prerequisite of guaranteeing certain good predistortion effect, the predistorted complex degree is reduced greatly, and then guaranteed the stability of predistortion through estimating polynomial effective order.

Description of drawings

Fig. 1 is the schematic flow sheet of the effective rank of multinomial of the present invention method of estimation embodiment.

Fig. 2 describes the part of effective order estimator.

Fig. 3 is first kind of implementation of approximation unit among the present invention.

Fig. 4 is second kind of implementation of approximation unit among the present invention.

Fig. 5 is the schematic flow sheet of radio transmission method embodiment of the present invention.

Fig. 6 has the composition sketch map of the wireless launcher embodiment of predistortion function for the present invention.

Embodiment

For making technical scheme of the present invention and beneficial effect clearer, below in conjunction with accompanying drawing and embodiment the present invention is done further detailed description, so that implementation procedure of the present invention can be made much of and enforcement according to this.

Basic ideas of the present invention are: utilize the singular value decomposition technology that polynomial effective rank are estimated; With the multinomial exponent number of the effective order that estimates as predistorter; Make when the computation complexity that makes predistorter reduces, guarantee the superior function of predistorter.Polynomial predistortion distorter under this effective order can obtain enough good predistortion effect.If do not carry out the estimation on effective rank, then can bring the problem that makes higher order polynomial predistorter implementation complexity height and poor stability.

The multinomial z (n) of predistorter can be expressed as:

$z\left(n\right)=\underset{k=1}{\overset{K}{\mathrm{\Σ}}}{a}_k{\mathrm{\φ}}_k\left(x\left(n\right)\right)---\left(1\right)$

Above-mentioned expression formula (1) is an expression formula based on polynomial predistorter;

Wherein:

K representes the sequence number of multinomial exponent number;

a _kThe expression multinomial coefficient;

φ _k(x (n)) expression is corresponding to the polynomial predistortion function in k rank;

The input data sequence of x (n) expression predistorter;

N representes the sequence number of input data sequence;

K representes polynomial maximum order.

Expression formula (1) matrix-style capable of using is expressed as:

z＝Φ _xa (2)

In the above-mentioned expression formula (2):

Z=[z (0) ..., z (N-1)] ^T, the polynomial matrix of expression predistorter, by N element z (0) ..., z (N-1) constitutes; Wherein, the transposition of subscript T representing matrix.

A=[a ₁..., a _K] ^T, represent K multinomial coefficient a ₁..., a _KThe coefficient matrix that constitutes;

Φ _x=[φ ₁(x) ..., φ _K(x)], the predistortion matrix that constitutes by K predistortion function of expression;

X=[x (0) ..., x (N-1)] ^T, represent N input data sequence x (0) by predistorter ..., the input matrix that x (N-1) constitutes;

φ _k(x)=[φ _k(x (0)) ..., φ _k(x (N-1))] ^T, the predistortion Jacobian matrix that expression is made up of N predistorter input data sequence.Need to prove φ _k(x) matrix that constitutes corresponding to the polynomial predistortion function in k rank of expression, and top Φ _xThen represent the predistortion matrix that constitutes by a plurality of predistortion functions.

Like this, seek the problem on polynomial effective rank of predistorter, can convert into and seek predistortion matrix Φ _xThe problem of effective order.The present invention provides two kinds of execution modes and seeks predistortion matrix Φ _xEffective order.Wherein first kind of execution mode is the predistortion matrix Φ that seeks K * N rank _xBest fit under Fu Luobeiniusi (Frobenius) norm

According to this best fit

Obtain predistortion matrix Φ _xEffective order and final obtain polynomial effective rank; Second kind of execution mode is to utilize the normalization singular value to obtain predistortion matrix Φ _xEffective order and final obtain polynomial effective rank.

At first kind of execution mode, promptly seek the predistortion matrix Φ on K * N rank _xBest fit under Fu Luobeiniusi (Frobenius) norm

Problem in, K representes polynomial maximum order, N representes the number of predistorter input data sequence.

Predistortion matrix is carried out singular value decomposition, Φ _x=U ∑ V ^H, obtaining the singular value matrix ∑, it comes down to a matrix that comprises singular value information.Wherein, U is the matrix of a K * K, and V is the matrix of a N * N, and ∑ then is the matrix of a K * N, diagonal entry diag (∑)=(σ of matrix ∑ ₁₁, σ ₂₂... .., σ _Kk), singular value σ _KkBe the diagonal entry that the capable k of k through the matrix ∑ that obtains after the singular value decomposition lists, the span of k be (1, min (K, N)), K, N represent predistortion matrix Φ respectively _xLine number and columns.Singular value σ _KkComprised predistortion matrix Φ _xThe useful information of characteristic of order.

Constant and through preceding k the singular value that keeps the matrix ∑ with other singular value zero setting, the matrix ∑ that obtains _k, ∑ _kThe order k that is called ∑ approaches matrix.Obtain expression formula as follows (3).

${\mathrm{\Φ}}_x^{\left(k\right)}={\mathrm{U\Σ}}_k{V}^H---\left(3\right)$

Wherein, Φ _x ^(k)Expression predistortion matrix Φ _xOrder k approach predistortion matrix; U is the K rank (unitary matrice of K * K); V is the N rank (unitary matrice of N * N).

Above-mentioned effect of approaching can be used the matrix difference Φ shown in following expression formula (4) _x-Φ _x ^(k)The Frobenius norm of (also can be referred to as the approximate error vector) || Φ _x-Φ _x ^(k)|| _FWeigh.|| Φ _x-Φ _x ^(k)|| _FMore little, the effect of then approaching is good more.

${|{|\mathrm{\Φ}}_x-{\mathrm{\Φ}}_x^{\left(k\right)}||}_F={\left|\right|{\mathrm{U\ΣV}}^H-{\mathrm{U\Σ}}_k{V}^H\left|\right|}_F---\left(4\right)$

For K rank unitary matrice U and N rank unitary matrice V, its norm is respectively:

${\left|\right|U\left|\right|}_F=\sqrt{K}---\left(5\right)$

${\left|\right|V\left|\right|}_F=\sqrt{N}---\left(6\right)$

Therefore, above-mentioned expression formula (4) can be reduced to:

${\left|\right|{\mathrm{\Φ}}_x-{\mathrm{\Φ}}_x^{\left(k\right)}\left|\right|}_F={\left|\right|U\left|\right|}_F\·{\left|\right|\mathrm{\Σ}-{\mathrm{\Σ}}_k\left|\right|}_F\·{\left|\right|V^H\left|\right|}_F=\sqrt{\mathrm{KN}}{\left|\right|\mathrm{\Σ}-{\mathrm{\Σ}}_k\left|\right|}_F=\sqrt{\mathrm{KN}}{\left[\begin{array}{cc}\underset{i=k+1}{\overset{\min (K,N)}{\mathrm{\Σ}}}& {\mathrm{\σ}}_{\mathrm{ii}}^2\end{array}\right]}^{1/2}---\left(7\right)$

Visible by expression formula (7), order k approaches predistortion matrix Φ _x ^(k)For predistortion matrix Φ _xApproach accuracy, depend on by those square of singular values of zero setting with.

Obvious according to expression formula (7), if k is big more, then || Φ _x-Φ _x ^(k)|| _FMore little, and || Φ _x-Φ _x ^(k)|| _F(K trends towards zero in the time of N) at k=min.Can reach the predetermined integer p that approaches the minimum of effect and be called predistortion matrix Φ _xEffective order.For example, when k value p, approximate error vector Φ _x-Φ _x ^(k)The Frobenius norm less than predetermined threshold, show to reach the predetermined effect of approaching, and when k＞p, approach effect and do not have obvious raising, then can p be confirmed as predistortion matrix Φ _xEffective order.

Therefore, seeking the effective rank of multinomial is converted into and seeks predistortion matrix Φ _xEffective order.Approach predistortion matrix Φ through order k _x ^(k)To predistortion matrix Φ _xApproach effect, confirm predistortion matrix Φ _xEffective order.That is to say that effective order of the predistortion matrix is here represented can reach the predetermined minimum order of approaching predistortion matrix of approaching effect to approaching of said predistortion matrix.Specify the effective order that how to obtain predistortion matrix below.

For example, first threshold ε is set ₁, make and work as || Φ _x-Φ _x ^(k)|| _FLess than first threshold ε ₁The time, can reach the predetermined effect of approaching.Calculate || Φ _x-Φ _x ^(k)|| _F, judge || Φ _x-Φ _x ^(k)|| _FWhether less than first threshold ε ₁, will make || Φ _x-Φ _x ^(k)|| _FLess than first threshold ε ₁Smallest positive integral k confirm as matrix Φ _xEffective order p (being polynomial effective rank of predistorter).

After obtaining the singular value matrix ∑, the present invention also can utilize the normalization singular value to judge and approach effect, therefore, also can utilize the method for normalization singular value to confirm predistortion matrix Φ _xEffective order.Specifically, can adopt expression formula as follows (8) to obtain normalization singular value

${\stackrel{\‾}{\mathrm{\σ}}}_{\mathrm{kk}}\stackrel{\mathrm{def}}{=}{\mathrm{\σ}}_{\mathrm{kk}}/{\mathrm{\σ}}_{11},$ 1≤k≤min(K，N) (8)

Obviously

Be provided with one and approach zero positive number ε ₂As second threshold value, make and confirm matrix Φ as follows _xEffective order the time, can reach the predetermined effect of approaching: calculate the normalization singular value

Judge the normalization singular value

Whether greater than second threshold epsilon ₂, will make the normalization singular value

Greater than second threshold epsilon ₂Maximum integer k be taken as matrix Φ _xEffective order p (being polynomial effective rank of predistorter).

Adopt approximate error vector Φ _x-Φ _x ^(k)The Frobenius norm to approach and adopt the normalization singular value to approach be the method on two kinds of parallel definite effective rank.

Fig. 1 is the schematic flow sheet of the effective rank of multinomial of the present invention method of estimation embodiment, and this method embodiment illustrates with above-mentioned first kind of mode of approaching.As shown in Figure 1, this method of estimation mainly comprises the steps:

Step S110, the multinomial of reception predistorter

Convert the multinomial z (n) of predistorter into matrix z=Φ _xA obtains predistortion matrix Φ _x=[φ ₁(x) ..., φ _K(x)], predistortion matrix Φ _xConstitute by K predistortion function, wherein, φ _k(x) expression is corresponding to the matrix of the polynomial predistortion function formation in k rank;

Step S120 is to predistortion matrix Φ _xCarry out singular value decomposition Φ _x=U ∑ V ^H, obtain the singular value matrix ∑.Diagonal entry diag (∑)=(σ of singular value matrix ∑ ₁₁, σ ₂₂... .., σ _Kk), singular value σ _KkIt is the diagonal entry that the capable k of k through the singular value matrix ∑ that obtains after the singular value decomposition lists;

Step S130, the order k that obtains ∑ according to this ∑ approaches the matrix ∑ _k, and approach ∑ according to this order k _kObtain predistortion matrix Φ _xOrder k approach predistortion matrix Φ _x ^(k), wherein, preceding k the singular value that keeps ∑ is constant, and simultaneously with other singular value zero setting, the order k that obtains the singular value ∑ in view of the above approaches the matrix ∑ _k, this Φ _x ^(k)Obtain and see also above-mentioned expression formula (3);

Step S140 judges and approaches effect, can adopt matrix difference Φ _x-Φ _x ^(k)The Frobenius norm || Φ _x-Φ _x ^(k)|| _FSize weigh the above-mentioned effect of approaching, wherein || Φ _x-Φ _x ^(k)|| _FSee also above-mentioned expression formula (4) to expression formula (7);

Step S150 approaches effect according to this and obtains predistortion matrix Φ _xEffective order p, effectively order p is polynomial effective rank.

Fig. 2 is the composition sketch map of multinomial effective order estimator embodiment of the present invention.In conjunction with method embodiment shown in Figure 1, this estimation module shown in Figure 2 mainly comprises converting unit 210, resolving cell 220 and approximation unit 230, wherein:

Converting unit 210 is used to receive the multinomial z (n) of predistorter, wherein

And according to this multinomial z (n) acquisition one predistortion matrix Φ _xConvert above-mentioned multinomial z (n) into matrix z=Φ _xA obtains above-mentioned matrix Φ _x

Resolving cell 220 is used for predistortion matrix is carried out singular value decomposition, Φ _x=U ∑ V ^H, obtain the singular value matrix ∑; Wherein, U is the matrix of a K * K, and V is the matrix of a N * N, and ∑ then is the matrix of a K * N, and K, N represent predistortion matrix Φ respectively _xLine number and columns;

Approximation unit 230 is used for obtaining predistortion matrix Φ according to singular value matrix ∑ and the preset threshold value of approaching _xEffective order, predistortion matrix Φ _xEffective order be effective rank of multinomial z (n).

Fig. 3 is for first kind of implementation of approximation unit 230 among the present invention, and is as shown in Figure 3, and the approximation unit 230 in this first kind of implementation mainly comprises the first operator unit 310, the second operator unit 320 and the 3rd operator unit 330, wherein:

The first operator unit 310 be used to keep preceding k singular value of singular value matrix, and with all the other singular value zero setting, the order k that obtains singular value matrix approaches matrix;

The second operator unit 320 is used for approaching the order k that matrix obtains predistortion matrix according to order k and approaches predistortion matrix;

The 3rd operator unit 330 calculates the size of Fu Luobeiniusi norm that predistortion matrix and order k approach the difference of predistortion matrix;

Confirm subelement 340, be used for approaching approach the effective order that effect confirm predistortion matrix of predistortion matrix predistortion matrix according to order k; Wherein first threshold is for approaching threshold value; The size of Fu Luobeiniusi norm that adopts predistortion matrix and order k to approach the difference of predistortion matrix is weighed and is approached effect; Suppose that the Fu Luobeiniusi norm of difference of approaching predistortion matrix as predistortion matrix and order k is during less than first threshold; Reach and approach effect; The Fu Luobeiniusi norm of difference of then approaching predistortion matrix as predistortion matrix and order p is smaller or equal to first threshold, and predistortion matrix and order k (the Fu Luobeiniusi norm of difference that k＜p) approaches predistortion matrix is confirmed as predistortion matrix Φ with p during all greater than first threshold _xEffective order, promptly polynomial effective rank.Predistortion matrix and order k are approached the Fu Luobeiniusi norm calculation of the difference of predistortion matrix, see also above-mentioned expression formula (4) to expression formula (7).

Fig. 4 is second kind of implementation of approximation unit 230 among the present invention, and as shown in Figure 4, the approximation unit 230 in this second kind of implementation mainly comprises normalization subelement 410 and definite subelement 420, wherein:

Normalized value computation subunit 410, the element that is used for being listed as according to singular value matrix first row first is to the singular value σ in the singular value matrix _KkCarry out normalization, obtain singular value σ _KkNormalized value

Confirm subelement 420, adopt normalized value

Judge and approach effect, suppose when the normalization singular value

Greater than second threshold epsilon ₂The time, can not reach and approach effect, then according to second threshold value and normalized value, obtain effective order of predistortion matrix, particularly, based on the element of first row, first row in the said singular value matrix to singular value σ in the said singular value matrix _KkCarry out normalization and handle, obtain singular value σ _PpNormalized value

If normalization singular value

More than or equal to second threshold epsilon ₂, and

(p＜k≤K) all less than second threshold epsilon ₂, then can integer p be taken as matrix Φ _xEffective order, wherein second threshold value is for approaching threshold value.

Adopted aforesaid effective rank to estimate the power amplifier technology of handling, can guarantee the superior function of predistorter under low complex degree, thereby can effectively improve the power efficiency of power amplifier.

Fig. 5 is the schematic flow sheet of radio transmission method embodiment of the present invention.In conjunction with effective rank method of estimation embodiment and effective order estimator embodiment shown in Figure 2 shown in Figure 1, power-magnifying method embodiment shown in Figure 5 mainly comprises the steps:

Step S510 receives coupling data based on polynomial predistorter, obtains the multinomial of predistorter;

Step S520 carries out effective rank to this multinomial and estimates, obtains this polynomial effective rank;

Step S530, filter receives the polynomial predistorting data based on effective rank, and this predistorting data is carried out certain conversion, changes signal spectrum, make it more appropriate to Channel Transmission;

Step 540, up-conversion and D/A module are carried out upconversion process with baseband signal, make it to become radiofrequency signal;

Step S550 is that radiofrequency signal is amplified to the frequency-conversion processing result, obtains amplified result and output.

Among the above-mentioned steps S520 this multinomial is carried out effective rank and estimate, and obtain the process on these effective rank, please understand, repeat no more here with reference to effective rank method of estimation embodiment as shown in Figure 1.

Fig. 6 is the composition sketch map with wireless launcher embodiment of predistortion function.In conjunction with effective rank method of estimation embodiment shown in Figure 1, effective order estimator embodiment shown in Figure 2 and the radio communication launching technique embodiment with predistortion function shown in Figure 5, the wireless launcher with predistortion function shown in Figure 6 mainly comprises:

Predistorter 610; Be used to receive the data of coupling and process base band demodulating; Obtain multinomial and send to effective order estimator 620, receive polynomial effective rank of effective order estimator 620 feedbacks, and effective rank are sent to filter 630 as the multinomial exponent number;

Effective order estimator 620 links to each other with predistorter 610, is used for that multinomial is carried out effective rank and estimates, obtains polynomial effective rank;

Filter 630 links to each other with predistorter 610, is used for receiving based on the polynomial predistorting data in effective rank, and predistorting data is carried out filtering, and filtered result is imported D/A and up-conversion module 650;

D/A and up-conversion module 650 are carried out digital-to-analogue conversion and upconversion process to the output result of filter 630, obtain the frequency-conversion processing result, i.e. rf data;

Power amplifier 640 links to each other with D/A and up-conversion module 650, and this rf data is amplified, and obtains amplified result and output;

Down-conversion and A/D module 660 are carried out down-conversion and analog-to-digital conversion to the data sequence that is coupled back, and export transformation result to delay estimation module 670;

Postpone estimation module 670; To through the former input data sequence that delay be coupled back and compare through the data sequence of the base band of demodulation; Analyze and to be coupled back and through the data sequence of the base band of demodulation and the difference of former data (being ideal data), so that predistorter 610 is adjusted.

620 pairs of these multinomials of above-mentioned effective order estimator carry out effective rank to be estimated, and obtains the process on these effective rank, please understands with reference to effective rank method of estimation embodiment as shown in Figure 1 and effective rank estimation module shown in Figure 2, repeats no more here.

Among Fig. 6, " postponing to estimate " module is positioned at " left side " end, carries out the data contrast.

Effective rank estimation technique among the present invention makes predistorter under the prerequisite of guaranteeing the predistortion effect, reduces overhead and implementation complexity greatly, and owing to reduced the multinomial exponent number, makes the convergence of predistorter and stability improve.

The predistorter that the present invention realizes has the advantage of low, stable height of complexity and fast convergence rate, goes for the portable mobile termianls such as communication network device such as base station, repeater, broadcasting television tower and mobile phone, mobile TV of large-scale communication equipment.

Though execution mode of the present invention as above, described content is not in order to limit the present invention just for the ease of understanding the present invention.Technical staff under the present invention in the technical field; Under the prerequisite of spirit that does not break away from the present invention and disclosed and scope; Can on concrete form of implementing and details, do any modification and variation, but these are revised and variation all should be included within the scope of patent protection of the present invention.

Claims (5)

1. the effective order estimator of a predistorter is characterized in that, comprising:

Converting unit is used to receive the multinomial of predistorter, converts said multinomial into matrix notation, obtains the predistortion matrix that is made up of K predistortion function; K representes said polynomial maximum order;

Resolving cell is used for said predistortion matrix is carried out singular value decomposition, obtains singular value matrix;

Approximation unit is used for according to said singular value matrix, obtains effective order of said predistortion matrix, and effective order of said predistortion matrix is said polynomial effective rank, wherein,

Effective order of said predistortion matrix is can reach the predetermined minimum order of approaching predistortion matrix of approaching effect to approaching of said predistortion matrix, and the said predistortion matrix of approaching is the matrix that said predistortion matrix is approached.

2. effective order estimator according to claim 1 is characterized in that, said converting unit comprises:

Receive subelement, be used to receive said multinomial

The conversion subelement, being used for converting said multinomial z (n) into matrix notation is z=Φ _xA;

The output subelement is used to export said predistortion matrix Φ _x

Wherein:

K representes the sequence number of said multinomial exponent number;

a _kRepresent said polynomial coefficient;

φ _k(x (n)) expression is corresponding to the said polynomial predistortion function in k rank;

The input data sequence of the said predistorter of x (n) expression;

N representes the sequence number of said input data sequence;

Z=[z (0) ..., z (N-1)] ^TThe polynomial matrix of representing said predistorter, by N element z (0) ..., z (N-1) constitutes;

A=[a ₁..., a _K] ^TRepresent K multinomial coefficient a ₁..., a _KThe coefficient matrix that constitutes;

Φ _x=[φ ₁(x) ..., φ _K(x)] the said predistortion matrix that constitutes by K predistortion Jacobian matrix of expression;

X=[x (0) ..., x (N-1)] ^TExpression is by N predistorter input data sequence x (0) ..., the input matrix that x (N-1) constitutes;

φ _k(x)=[φ _k(x (0)) ..., φ _k(x (N-1))] ^TThe said predistortion Jacobian matrix that expression is made up of N input data sequence.

3. effective order estimator according to claim 1 is characterized in that, said approximation unit is also carried out following operation:

Preceding k the singular value that keeps said singular value matrix, and with all the other singular value zero setting, the order k that obtains said singular value matrix approaches singular value matrix;

Approach the said predistortion matrix of approaching that singular value matrix obtains said predistortion matrix according to said order k;

The Fu Luobeiniusi norm of difference of approaching predistortion matrix when said predistortion matrix and said is judged as the said predistortion matrix of approaching and can reaches the predetermined effect of approaching during smaller or equal to first threshold.

4. effective order estimator according to claim 1 is characterized in that, said approximation unit is carried out following operation:

Based on the element of first row first row in the said singular value matrix to singular value σ in the said singular value matrix _KkCarry out normalization and handle, obtain singular value σ _PpNormalized value And

If said normalized value

is more than or equal to second threshold value; The said predistortion matrix of approaching that then is judged as order and is p can reach the predetermined effect of approaching; Wherein, 1＜p＜K

Wherein, singular value σ _KkBe the diagonal entry that the capable k of k through the matrix ∑ that obtains after the singular value decomposition lists, the span of k is that (1, (K, N), K, N represent predistortion matrix Φ respectively to min _xLine number and columns;

Singular value σ _KkComprised predistortion matrix Φ _xThe information of characteristic of order.

5. effect order estimator according to claim 4; It is characterized in that; If for arbitrary k value that satisfies p＜k≤K;

all less than said second threshold value, then p can reach the predetermined minimum order of approaching predistortion matrix of approaching effect to approaching of said predistortion matrix.

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