CN102868434A - MIMO detection method and device - Google Patents

Abstract

The invention discloses an MIMO detection method and device, relating to the field of communication. The MIMO detection method comprises the steps of: carrying out linear detection on receiving signals to obtain a first estimation value; carrying out nonlinear detection on the receiving signals according to a preset iteration time to obtain an estimating value of corresponding partial sending signals; carrying out bit not operation on residual sending signals which do not obtain estimating values in the last step according to the first estimating value and the estimating values of the partial sending signals to obtain estimating values of the corresponding residual sending signals; merging the estimating values of the partial sending signals with the estimating values of the residual sending signals to obtain a second estimating value; and obtaining a vector space according to the first estimating value and the second estimating value, and carrying out maximum likelihood detection on the receiving signals in the vector space to obtain a final estimating value. According to the method and device, the complexity and the detection property can be flexibly regulated according to the actual channel quality and the demand condition of a communication system, and different levels of detection properties are realized by different levels of detection complexities.

Description

A kind of MIMO detection method and device

Technical field

The present invention relates to communication technical field, particularly a kind of MIMO detection method and device.

Background technology

Since middle nineteen nineties in last century, the MIMO signal processing technology becomes the study hotspot of communication theory maximum.The MIMO technology is that communication system is introduced Spatial Dimension, so that people can be in time domain, frequency domain and spatial domain combined optimization communication system, thereby might obtain the performance of convergence and theoretical limit.First practical mimo system is the V-BLAST system, and it has obtained very high spectrum efficiency under quasistatic (Block Fading) fading channel condition.Meanwhile, the MIMO detection technique has obtained the common concern of academia.

The MIMO detection algorithm relate to mimo system performance quality with and complexity whether can carry out practical application.At present, a variety of signal detecting methods are arranged in mimo system, such as linearity test (ZF ZF detector, least mean-square error MMSE detector), non-linear detection (the BLAST detector is divided into ZF-BLAST detector and MMSE-BLAST detector), maximum likelihood (ML) detection etc.

ZF ZF algorithm has been eliminated the interference between each antenna in the linearity test, but to amplify noise as cost, and least mean-square error MMSE algorithm has considered interference between the antenna and the interference of noise, and so that reach mean square error between data estimator and the real data and minimize, its performance is better than ZF and detects.

Non-linear detection is passed through repeatedly serial interference delete iteration, at first rebuilds the highest transmitting antenna data of signal to noise ratio of making a start, and eliminates these data to the impact of reception antenna, and iteration repeatedly can obtain afterwards the data of all transmitting antennas.The nonlinear detector performance is better than linear detector, but need to carry out repeatedly the process of iteration and matrix inversion.

Maximum likelihood (ML) detects to be searched for all possible originating data space at receiving terminal, and draws and the value that receives the signal distance minimum, with this as estimating detected value.Maximum likelihood (ML) detects function admirable, but its complexity is very high, and be exponent increase with order of modulation and antenna configuration, and the improvement algorithm that proposes for maximum likelihood (ML) criterion, decipher such as ball, complexity is still higher, and adopting parameters is difficult to determine, brings certain difficulty for the application in the real system.

Summary of the invention

The technical problem that (one) will solve

The technical problem to be solved in the present invention is: how a kind of MIMO detection method and device are provided, with according to actual channel quality and communication system conditions of demand flexible complexity and detection performance, realize the detection performance of varying level with the detection complexity of different brackets.

(2) technical scheme

For solving the problems of the technologies described above, the invention provides a kind of MIMO detection method, it comprises step:

A: r carries out linearity test to received signal, obtains the first estimated value of corresponding transmitted signal

B: according to predetermined iterations to received signal r carry out non-linear detection, obtain the estimated value of counterpart transmitted signal

C: according to described the first estimated value

Estimated value with described part transmitted signal

The residue transmitted signal that does not obtain estimated value among the described step B is carried out the bit inversion operation, obtain the estimated value of corresponding residue transmitted signal

D: the estimated value that merges described part transmitted signal

Estimated value with described residue transmitted signal Obtain the second estimated value of corresponding transmitted signal

E: according to described the first estimated value

With described the second estimated value

Obtain vector space R, r carries out Maximum Likelihood Detection to received signal in described vector space R, obtains distance and receives the nearest signal vector of signal r as the final estimated value of corresponding transmitted signal

Wherein, in the described steps A, described the first estimated value

Computing formula as follows:

${\hat{r}}_1=g\×r;$

Wherein, g is filtering matrix.

Wherein, the computing formula of described filtering matrix g is as follows:

G=(H ^HH) ^-1H ^HPerhaps,

g=（H ^HH+σ ²I） ^-1H ^H；

Wherein, H represents channel matrix, σ ²The expression noise power.

Wherein, among the described step B, according to predetermined iterations to received signal r to carry out the detailed process of non-linear detection as follows:

Initialization: i=1, G ₁=F (H);

Iterative process:

$s_i=\arg \underset{j\∉\{s_1,s_2,...s_{i-1}\}}{\min }\left|\right|{\left(G_i\right)}_j\left|\right|;$

$W_{s_i}={\left(G_i\right)}_{s_i};$

$y_{s_i}=W_{s_i}{r}_i;$

${\hat{x}}_{s_i}=Q\left(y_{s_i}\right);$

$r_{i+1}=r_i-{\hat{x}}_{s_i}{\left(H\right)}_{s_i}^T;$

$G_{i+1}=F\left(H_{\stackrel{\‾}{s}i}\right);$

i＝i+1；

Wherein, i is less than or equal to predetermined iterations N _Iterr _iReception signal when representing the i time iteration, r ₁Equal initial described reception signal r; G _iThe expression filtering matrix, F (H) and Expression calculation of filtered matrix G _iFunction, H represents channel matrix; (G _i) _jExpression filtering matrix G _iJ capable, s _iRepresent filtering matrix G in the i time iteration _iThe capable subscript of 2-Norm minimum in the row vector;

Expression according to planisphere to detection signal

Carry out hard decision,

S in the expression transmitted signal _iThe estimated value of individual symbol;

The s of expression channel matrix H _iRow turn order;

The s of expression signaling channel matrix H ₁, s ₂..., s _iClassify 0 matrix that obtains as.

Wherein, adopt zero forcing algorithm or least-mean-square error algorithm calculation of filtered matrix G _i

Wherein, described predetermined iterations is according to the signal to noise ratio setting of communication system.

Wherein, described step C specifically comprises step:

C1: determine every kind of probability of happening that variation mode is corresponding according to the signal to noise ratio of communication system;

C2: according to the estimated value of described part transmitted signal

Do not obtained the location index of the residue transmitted signal of estimated value;

C3: according to every kind of probability of happening that variation mode is corresponding, the transmitted signal that described location index is corresponding is carried out the bit inversion operation, obtain the estimated value of corresponding residue transmitted signal

Wherein, in the described step e, the formula of Maximum Likelihood Detection is as follows:

$\hat{r}=\arg \underset{x\∈R}{\min }\left|\right|r-\mathrm{Hx}\left|\right|;$

Wherein, H represents channel matrix; X is all possible vector in the vector space R;

The final estimated value that represents corresponding transmitted signal.

The present invention also provides a kind of MIMO checkout gear, and described device comprises:

The linearity test unit is used for to received signal that r carries out linearity test, obtains the first estimated value of corresponding transmitted signal

Non-linear detection unit, be used for according to predetermined iterations to received signal r carry out non-linear detection, obtain the estimated value of counterpart transmitted signal

Detecting unit is estimated in variation, is used for according to every kind of probability of happening that variation mode is corresponding, according to described the first estimated value Estimated value with described part transmitted signal

The residue transmitted signal that does not obtain estimated value among the described step B is carried out the bit inversion operation, obtain the estimated value of corresponding residue transmitted signal

Merge cells is for the estimated value that merges described part transmitted signal

Estimated value with described residue transmitted signal

Obtain the second estimated value of corresponding transmitted signal

The Maximum Likelihood Detection unit is used for according to described the first estimated value

With described the second estimated value

Obtain vector space R, r carries out Maximum Likelihood Detection to received signal in described vector space R, obtains distance and receives the nearest signal vector of signal r as the final estimated value of corresponding transmitted signal

Wherein, described device also comprises:

The complexity control unit is used for determining predetermined iterations according to the signal to noise ratio of communication system;

The variance control unit is used for determining every kind of probability of happening that variation mode is corresponding according to the signal to noise ratio of communication system.

(3) beneficial effect

The described MIMO detection method of the embodiment of the invention and device, can and detect performance according to actual channel quality and communication system conditions of demand flexible complexity, realize the detection performance of varying level with the detection complexity of different brackets, be with a wide range of applications.

Description of drawings

Fig. 1 is the structural representation of MIMO communication system;

Fig. 2 is the described MIMO detection method of embodiment of the invention flow chart;

Fig. 3 is the modular structure schematic diagram of the described MIMO checkout gear of the embodiment of the invention.

Embodiment

Below in conjunction with drawings and Examples, the specific embodiment of the present invention is described in further detail.Following examples are used for explanation the present invention, but are not used for limiting the scope of the invention.

For the MIMO(multiple-input and multiple-output) communication system, need to carry out the transmission data that MIMO detects to obtain transmitting terminal at receiving terminal.The invention provides method and the device of the adjustable realization MIMO input of a kind of complexity, can and detect performance according to actual channel quality and system requirements situation flexible complexity, and in conjunction with linear MIMO detect, non-linear partial MIMO detects, linear MIMO testing result carried out meristic variation, realizes the detection performance of varying level with the detection complexity of different brackets.

Fig. 1 is the structural representation of MIMO communication system, and as shown in Figure 1, described MIMO communication system has N at transmitting terminal _tThe root antenna, receiving terminal has N _rThe root antenna; Then receive signal and transmitted signal and satisfy following relation:

r=H×x+n；

Wherein, r is for receiving signal, and its dimension is N _r* 1, N _rBe the reception antenna number. $r=[r_1^{\′},$ $r_2^{\′}...r_{N_r}^{\′}],$ R ' ₁, r ' ₂ Be respectively the reception signal of every reception antenna; X is transmitted signal, and its dimension is N _t* 1, N _tBe the transmitting antenna number.

x ₁, x ₂

Be respectively the transmitted signal of every transmitting antenna; H represents channel matrix, and its dimension is N _r* N _tN represents noise jamming, and its dimension is N _r* 1.

Fig. 2 is the described MIMO detection method of embodiment of the invention flow chart, and as shown in Figure 2, described method comprises step:

A: r carries out linearity test to received signal, obtains the first estimated value of corresponding transmitted signal

In steps A, receiving terminal to received signal r carries out linearity test, obtains the first estimated value to transmitted signal

Concrete formula is as follows:

${\hat{r}}_1=g\×r;$

Wherein,

Be N _t* 1 dimension, N _tBe the transmitting antenna number, g is filtering matrix;

Wherein, can adopt in the present embodiment but be not limited to ZF (ZF) algorithm or least mean-square error (MMSE) algorithm calculates described filtering matrix g.

When adopting zero forcing algorithm, g=(H ^HH) ^-1H ^H

When adopting least-mean-square error algorithm, g=(H ^HH+ σ ²I) ^-1H ^H

Wherein, H is channel matrix, can be obtained by channel estimating σ ²Be noise power.

B: according to predetermined iterations to received signal r carry out non-linear detection, obtain the estimated value of counterpart transmitted signal

In step B, the predetermined iterations according to the indication of complexity control unit carries out non-linear detection to received signal, obtains the estimated value to the part transmitted signal

Concrete grammar is as follows:

The complexity control unit determines the iterations N of non-linear detection _Iter, and N _Iter＜N _t, N wherein _tBe the transmitting antenna number.The complexity control unit is regulated iterations N automatically according to the communication system signal to noise ratio snr _Iter

Table one is N _t=N _r=4, when adopting the 16QAM modulation, the iterations N of complexity control unit output _IterRule change relation table with signal to noise ratio snr.

Table 1 iterations N _IterRule change relation table with signal to noise ratio snr

Need to prove, in actual applications, iterations N _IterBe not limited to shown in the table one with the relation of signal to noise ratio snr, those skilled in the art can be according to flexible adjustment form one data such as actual conditions and system configuration, to average out between detection complexity and detection performance.

Determine iterations N at the complexity control unit according to signal to noise ratio snr _IterAfterwards, non-linear detection unit is carried out N _IterInferior iterative detection.MIMO iterative detection process is specific as follows:

Initialization: i=1, G ₁=F (H);

Iterative process:

$s_i=\arg \underset{j\∉\{s_1,s_2,...s_{i-1}\}}{\min }\left|\right|{\left(G_i\right)}_j\left|\right|;$

$W_{s_i}={\left(G_i\right)}_{s_i};$

$y_{s_i}=W_{s_i}{r}_i;$

${\hat{x}}_{s_i}=Q\left(y_{s_i}\right);$

$r_{i+1}=r_i-{\hat{x}}_{s_i}{\left(H\right)}_{s_i}^T;$

$G_{i+1}=F\left(H_{\stackrel{\‾}{s}i}\right);$

i＝i+1；

Wherein, i is less than or equal to predetermined iterations N _Iterr _iReception signal when representing the i time iteration, r ₁Equal initial described reception signal r; G _iThe expression filtering matrix, F (H) and

Expression calculation of filtered matrix G _iFunction, H represents channel matrix; (G _i) _jExpression filtering matrix G _iJ capable, s _iRepresent filtering matrix G in the i time iteration _iThe capable subscript of 2-Norm minimum in the row vector;

Expression according to planisphere to detection signal

Carry out hard decision,

S in the expression transmitted signal _iThe estimated value of individual symbol;

The s of expression channel matrix H _iRow turn order;

The s of expression signaling channel matrix H ₁, s ₂..., s _iClassify 0 matrix that obtains as.Need to prove, the interference elimination in the above-mentioned algorithm sequentially is that the energy of the generalized inverse matrix reception column vector signal of the each iteration of basis sorts, and guarantees like this N under the control of complexity control unit _IterThe detected value of inferior iteration is local optimum.

Wherein, can adopt in the present embodiment but be not limited to ZF ordering interference cancellation algorithm or least mean-square error ordering interference cancellation algorithm is come calculation of filtered matrix G _i

Therefore in step B, non-linear detection unit will be according to the iterations N of complexity control unit decision _IterExport the estimated value to the part transmitted signal

Dimension be N _t* 1, but owing to not carrying out completely iterative detection, wherein only have N _IterIndividual symbol has value, and all the other the unknowns are 0.

C: according to described the first estimated value

Estimated value with described part transmitted signal

The residue transmitted signal that does not obtain estimated value among the described step B is carried out the bit inversion operation, obtain the estimated value of corresponding residue transmitted signal

In step C, iterative detection among the step B do not estimated the transmitted signal that obtains, by the variance control unit controls, detect according to the steps A neutral line and to obtain

Respective symbol is carried out the bit variation, thereby produce the estimated value of corresponding receiving symbol

Concrete grammar is as follows:

For the signal that uses M contrast system, its each constellation symbol has log ₂M bit number, possible variation kind has log ₂The M kind.For example modulate for 16QAM, each constellation symbol is made of 4 bit binary code, then have the possibility of 4 kinds of variations: 1 bit makes a variation ... 4 bits make a variation, the bit that variation is corresponding position in this bit group carries out negate (0 change 1,1 becomes 0), the variance control unit is used for determining the probability of happening of every kind of variation when generating estimate symbol.The purpose of variance control unit is to make this sign estimation value to have may equal actual value greatlyr, is a kind of local best practice.The variance control unit can be regulated automatically according to the communication system signal to noise ratio snr.

Table two is N _t=N _rDuring=4,16QAM modulation, the probability of happening of every kind of variation mode of variance control unit output and the relation of SNR.

The relation table of table 2 variation mode, probability of happening and SNR

Need to prove, in actual applications, the probability of happening of every kind of variation mode of variance control unit output and the relation of SNR are not limited to shown in the table one, and those skilled in the art can be according to flexible adjustment form two data such as actual conditions and system configuration.

The estimated value of the part transmitted signal that obtains among the step B

Dimension be N _t* 1, owing to not carrying out completely iterative detection, wherein only have N _IterIndividual symbol has value, and all the other positions are 0, and obtaining the position is the location index index=[index of 0 signal ₁, index ₂Index _n], n=N wherein _t-N _IterSteps A is carried out linearity test to received signal, obtains the first estimated value to whole transmitted signals

Dimension be N _t* 1.According to the indication of index vector index and variance control unit, right

In the symbol corresponding with index vector index carry out the bit inversion operation, generate new Vector Groups

Dimension be N _t* 1, wherein only have n=N _t-N _IterIndividual symbol has value, and all the other are 0.

D: the estimated value that merges described part transmitted signal

Estimated value with described residue transmitted signal

Obtain the second estimated value of corresponding transmitted signal

In step D, to step B and step C testing result

And

Merge.

With

Be N _t* 1 dimensional vector, and

In N is arranged _IterIndividual symbol has value, In n=N is arranged _t-N _IterIndividual symbol has value, and

With

It is complementary relationship that middle symbol has the location index of value.Then right With

Merge, obtain the second estimated value to transmitted signal

Dimension be N _t* 1.

E: according to described the first estimated value With described the second estimated value

Obtain vector space R, r carries out Maximum Likelihood Detection to received signal in described vector space R, obtains distance and receives the nearest signal vector of signal r as the final estimated value of corresponding transmitted signal

In step e, by the steps A testing result

With step D testing result

Consist of new vector space R, the dimension of new vector space R is N _t* 2.

The search signal vector nearest with receiving signal r carries out the maximum likelihood input in vector space R, obtains final estimated value

Concrete formula is as follows:

$\hat{r}=\arg \underset{x\∈R}{\min }\left|\right|r-\mathrm{Hx}\left|\right|$

Wherein, H is channel matrix, and r is for receiving signal, and x is all possible vector in vector space R, and in the present embodiment, the size of vector space R is

N _tBe the transmitting antenna number.

Be the final estimated value to transmitted signal.

Fig. 3 is the modular structure schematic diagram of the described MIMO checkout gear of the embodiment of the invention, and as shown in Figure 3, this MIMO checkout gear comprises:

Linearity test unit 100 is used for to received signal that r carries out linearity test, obtains the first estimated value of corresponding transmitted signal

Non-linear detection unit 200, be used for according to predetermined iterations to received signal r carry out non-linear detection, obtain the estimated value of counterpart transmitted signal

Detecting unit 300 is estimated in variation, is used for according to every kind of probability of happening that variation mode is corresponding, according to described the first estimated value

Estimated value with described part transmitted signal

The residue transmitted signal that does not obtain estimated value among the described step B is carried out the bit inversion operation, obtain the estimated value of corresponding residue transmitted signal

Merge cells 400 is for the estimated value that merges described part transmitted signal

Estimated value with described residue transmitted signal

Obtain the second estimated value of corresponding transmitted signal

Maximum Likelihood Detection unit 500 is used for according to described the first estimated value With described the second estimated value

Obtain vector space R, r carries out Maximum Likelihood Detection to received signal in described vector space R, obtains distance and receives the nearest signal vector of signal r as the final estimated value of corresponding transmitted signal

Complexity control unit 600 is used for determining predetermined iterations according to the signal to noise ratio of communication system;

Variance control unit 700 is used for determining every kind of probability of happening that variation mode is corresponding according to the signal to noise ratio of communication system.

The described MIMO detection method of the embodiment of the invention and device, can and detect performance according to actual channel quality and communication system conditions of demand flexible complexity, realize the detection performance of varying level with the detection complexity of different brackets, be with a wide range of applications.

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 (10)

1. a MIMO detection method is characterized in that, comprises step:

A: r carries out linearity test to received signal, obtains the first estimated value of corresponding transmitted signal

B: according to predetermined iterations to received signal r carry out non-linear detection, obtain the estimated value of counterpart transmitted signal

C: according to described the first estimated value

Estimated value with described part transmitted signal

The residue transmitted signal that does not obtain estimated value among the described step B is carried out the bit inversion operation, obtain the estimated value of corresponding residue transmitted signal

D: the estimated value that merges described part transmitted signal Estimated value with described residue transmitted signal

Obtain the second estimated value of corresponding transmitted signal

E: according to described the first estimated value

With described the second estimated value

Obtain vector space R, r carries out Maximum Likelihood Detection to received signal in described vector space R, obtains distance and receives the nearest signal vector of signal r as the final estimated value of corresponding transmitted signal

2. the method for claim 1 is characterized in that, in the described steps A, and described the first estimated value Computing formula as follows:

${\hat{r}}_1=g\×r;$

Wherein, g is filtering matrix.

3. method as claimed in claim 2 is characterized in that, the computing formula of described filtering matrix g is as follows:

G=(H ^HH) ^-1H ^HPerhaps,

g=（H ^HH+σ ²I） ^-1H ^H；

Wherein, H represents channel matrix, σ ²The expression noise power.

4. the method for claim 1 is characterized in that, among the described step B, according to predetermined iterations to received signal r to carry out the detailed process of non-linear detection as follows:

Initialization: i=1, G ₁=F (H);

Iterative process:

$s_i=\arg \underset{j\∉\{s_1,s_2,...s_{i-1}\}}{\min }\left|\right|{\left(G_i\right)}_j\left|\right|;$

$W_{s_i}={\left(G_i\right)}_{s_i};$

$y_{s_i}=W_{s_i}{r}_i;$

${\hat{x}}_{s_i}=Q\left(y_{s_i}\right);$

$r_{i+1}=r_i-{\hat{x}}_{s_i}{\left(H\right)}_{s_i}^T;$

$G_{i+1}=F\left(H_{\stackrel{\‾}{s}i}\right);$

i＝i+1；

Wherein, i is less than or equal to predetermined iterations N _Iterr _iCorresponding reception signal when representing the i time iteration, r ₁Equal initial described reception signal r; G _iThe expression filtering matrix, F (H) and

The function of expression calculation of filtered matrix, H represents channel matrix; (G _i) _jExpression filtering matrix G _iJ capable, s _iRepresent filtering matrix G in the i time iteration _iThe capable subscript of 2-Norm minimum in the row vector; Expression according to planisphere to detection signal

Carry out hard decision, S in the expression transmitted signal _iThe estimated value of individual symbol; The s of expression channel matrix H _iRow turn order;

The s of expression signaling channel matrix H ₁, s ₂..., s _iClassify 0 matrix that obtains as.

5. method as claimed in claim 4 is characterized in that, adopts zero forcing algorithm or least-mean-square error algorithm calculation of filtered matrix G _i

6. method as claimed in claim 4 is characterized in that, described predetermined iterations is according to the signal to noise ratio setting of communication system.

7. the method for claim 1 is characterized in that, described step C specifically comprises step:

C1: determine every kind of probability of happening that variation mode is corresponding according to the signal to noise ratio of communication system;

C2: according to the estimated value of described part transmitted signal

Do not obtained the location index of the residue transmitted signal of estimated value;

C3: according to every kind of probability of happening that variation mode is corresponding, the transmitted signal that described location index is corresponding is carried out the bit inversion operation, obtain the estimated value of corresponding residue transmitted signal

8. the method for claim 1 is characterized in that, in the described step e, the formula of Maximum Likelihood Detection is as follows:

$\hat{r}=\arg \underset{x\∈R}{\min }\left|\right|r-\mathrm{Hx}\left|\right|;$

Wherein, H represents channel matrix; X is all possible vector in the vector space R;

The final estimated value that represents corresponding transmitted signal.

9. a MIMO checkout gear is characterized in that, described device comprises:

The linearity test unit is used for to received signal that r carries out linearity test, obtains the first estimated value of corresponding transmitted signal

Non-linear detection unit, be used for according to predetermined iterations to received signal r carry out non-linear detection, obtain the estimated value of counterpart transmitted signal

Detecting unit is estimated in variation, is used for according to every kind of probability of happening that variation mode is corresponding, according to described the first estimated value

Estimated value with described part transmitted signal The residue transmitted signal that does not obtain estimated value among the described step B is carried out the bit inversion operation, obtain the estimated value of corresponding residue transmitted signal

Merge cells is for the estimated value that merges described part transmitted signal

Estimated value with described residue transmitted signal

Obtain the second estimated value of corresponding transmitted signal

The Maximum Likelihood Detection unit is used for according to described the first estimated value With described the second estimated value

Obtain vector space R, r carries out Maximum Likelihood Detection to received signal in described vector space R, obtains distance and receives the nearest signal vector of signal r as the final estimated value of corresponding transmitted signal

10. device as claimed in claim 9 is characterized in that, described device also comprises:

The complexity control unit is used for determining predetermined iterations according to the signal to noise ratio of communication system;

The variance control unit is used for determining every kind of probability of happening that variation mode is corresponding according to the signal to noise ratio of communication system.

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