CN101710884B - Method for identifying QAM mode based on channel estimation and equalization - Google Patents
Method for identifying QAM mode based on channel estimation and equalization Download PDFInfo
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Abstract
The invention relates to a method for identifying a QAM mode based on channel estimation and equalization. The method comprises the following steps of: A, receiving input data in a QAM mode; B, adjusting the energy of the received data with a first convergence step length to make the data signal energy larger than an energy threshold; C, carrying out the equal convergence with a second convergence step length, and carrying the phase position and frequency offset correction on the received data when signal carrier recovery frequency-offset detection is locked; D, carrying out the equal convergence with a third convergence step length, and detecting whether the mean square error of the converged data is less than a threshold, if yes, going to Step E, otherwise, going to Step F; E, carrying out the LMS adaptive equal convergence on the input data by an equalizer, and detecting whether the mean square error of the converged data is less than a threshold, if yes, inputting data by the LMS adaptive equal convergence, otherwise, going to Step F; and F, changing the QAM mode and going to Step B. The invention effectively realizes the data equalization and completes the QAM mode identification in a simple and easily achievable mode.
Description
Technical field
The present invention relates to digital signal transmission field, particularly the channel equalization method under the QAM pattern recognition in the cable digital TV.
Background technology
The digital cable TV system provides and is based upon the broadcast service that cable television network is uploaded elm, converts anolog TV signals to digital signal and handles and transmit with digital mode.
Up to the present, several different digital cable TV standards have been formed in the world.Be example with Europe, from nineteen ninety-five, Europe has been issued Digital Television Terrestrial Broadcasting (DVB-T), digital satellite broadcasting (DVB-S), Digital Television wired broadcasting (DVB-C) standard successively.China has also begun the work of piloting of digital cable TV in calendar year 2001.
In Digital Television wired broadcasting (DVB-C) standard, because the signal of transmitting terminal emission is brought in for reception and is said that all parameters all are unknown, and do not contain any known training sequence in the signal of launching, so receiving terminal must be judged code check, digital modulator (Quadrature Amplitude Modulation, QAM) pattern earlier according to signal.Traditional equalizer need could carry out channel estimating and equilibrium to the input data under known QAM pattern, convergence rate is slower simultaneously, can not adapt to the balanced demand under the different Q AM pattern.
Summary of the invention
The present invention proposes a kind of based on the method for channel estimating with the QAM pattern recognition of equilibrium, effectively realizes data balancing and finishes the QAM pattern recognition in mode simple, that be easy to realize.
The present invention has adopted following technical scheme to realize: a kind of based on the method for channel estimating with the QAM pattern recognition of equilibrium, it comprises step:
A, equalizer receives the input data under an acquiescence QAM pattern;
B, equalizer adopt blind equalization algorithm with the data energy that the first convergence step-length adjustment receives, and make balanced data-signal energy later greater than a certain energy threshold value;
C, equalizer adopt blind equalization algorithm with the second convergence step-length input data to be carried out the equilibrium convergence, start frequency deviation and skew that carrier wave recovers to detect balanced output signal, after carrier wave recovered to detect the frequency deviation locking, data were carried out phase place and correcting frequency deviation is handled to receiving;
D, equalizer adopt blind equalization algorithm with the 3rd convergence step-length the input data to be carried out the equilibrium convergence, detect the mean square error of convergence back data whether less than a certain threshold value, if change step e over to, otherwise change step F over to;
E, equalizer carry out the convergence of LMS adaptive equalization to the input data, and whether the mean square error that detects convergence back data less than a certain threshold value, if then by with LMS adaptive equalization convergence input data, otherwise change step F over to;
F, replacing QAM pattern also change step B over to.
Wherein, in step B, C or D, the account form of error is in the blind equalization algorithm: e (n)=(R
2+ L*T
2The * of)-(L+1) | y (n) |
2
Wherein,
Representing the signal averaging energy radius under a certain QAM pattern, T
2=E (| x (n) |
2) representing each mark signal average energy radius under a certain QAM pattern, L is modifying factor, the balanced output of y (n) expression.
Wherein, in step B, C and D, each is restrained step size mu and satisfies relation:
W (n) is tap coefficient.
Error when wherein, LMS adaptive equalization restrains is:
The balanced output of y (n) expression.
Wherein, in the step e, the convergence step size mu that LMS adaptive equalization adopts satisfies:
W (n) is tap coefficient.
Wherein, the first convergence step-length is greater than the second convergence step-length, and the second convergence step-length is greater than the 3rd convergence step-length.
Compared with prior art, the present invention has following beneficial effect:
At first, the present invention under the MCMA algorithm, carries out blind equalization by the big step-length of data utilization that reception is come, adjusts the data energy that receives, and makes that receiving the data energy reaches data energy under " target QAM pattern " substantially; Secondly, after indication receives the data energy and reaches data energy " target QAM pattern " under substantially, control equalizer and enter the blind equalization senior state.After equalizer entered this state, equalizer adopted new step parameter to carry out the equilibrium convergence, and the control carrier estimation module starts the estimation of frequency deviation and skew is carried out in the data output of equalizer after a period of time; Again, by the carrier recovery block lock indication signal, control equalizer change step-length enters the blind equalization phase III, after after a while, enters the adaptive tracing state; According to the size of the MSE value under the adaptive tracing state, determine the lock condition of QAM pattern; If " target QAM " pattern is then changed in not locking, convergence is balanced again.Therefore, when the present invention effectively realizes data balancing, finished the QAM pattern recognition again, method is simple and be easy to realize.
Description of drawings
Fig. 1 is system configuration schematic diagram of the present invention;
Fig. 2 is schematic flow sheet of the present invention;
Fig. 3 is QAM16 energy radius schematic diagram.
Embodiment
Because in Digital Television wired broadcasting (DVB-C) system, receiving terminal must use blind equalization algorithm to information data the unknown of transmitting terminal emission, generally adopt constant modulus algorithm (Constant Modulus Algorithm, CMA).The main feature of this algorithm is to restrain to average energy circle (radius) being input to the equalizer data, but he has brought an important disadvantages again, that is exactly that all input data are all restrained on this energy radius, and this phenomenon is particularly outstanding to the high-order QAM modulation.
In order to address this problem, the present invention discloses a kind of CMA algorithm that is easy to realize.Wherein, the formula of traditional blind equalization algorithm is as follows: e (n)=R
2-| y (n) |
2
The present invention revises it, and correction formula is as follows: e (n)=(R
2+ L*T
2The * of)-(L+1) | y (n) |
2
In the following formula:
Representing the signal averaging energy radius under a certain QAM pattern; T
2=E (| x (n) |
2) representing each mark signal average energy radius under a certain QAM pattern; L is modifying factor; The balanced output of y (n) expression.
Realize that core mode of the present invention is: when guaranteeing balanced input data signal energy, by adjusting modifying factor L input data signal is drawn close to the standard symbol point of a certain QAM pattern as far as possible, to guarantee the very fast and correct convergence of equalizer; Utilize scanning that designed equalizer carries out the QAM pattern and set: traditional QAM pattern recognition needs a special circuit, the present invention does not then need to increase any circuit, by to least mean square algorithm (Least Mean Square, LMS) calculating the mean square error extent judges, when mean square error is lower than a certain threshold value, then think this mode locking, pattern recognition is correct, equalizer continues LMS adaptive tracing state, otherwise it is balanced again that " it " font is changed pattern, as searching for according to " QAM64--＞QAM128--＞QAM32--＞QAM256--＞QAM16 " direction.
As shown in Figure 1, it is the structural representation of equilibrium disclosed by the invention and QAM pattern recognition system.This system comprises: the data that contain equalizer are selected module 101, blind equalization circuit 102, error calculating module 103, LMS adaptive balance module 104, coefficient updating module 105, MSE (Mean Square Error, mean square error) computing module 106, state controller 107.
During two stages, what the input data were selected module 101 is not correct skew and and inclined to one side data before blind equalization.At blind equalization during the phase I, data are selected module 101 at first to adopt to give tacit consent to QAM pattern (for example selecting 64QAM), select bigger step-length, with the balancing energy of input signal to the energy band at this QAM pattern place.In blind equalization the last stage and LMS self adaptation stage, these data select module 101 to select the data of correcting frequency offset.Therefore, the main effect of data selection module 101 is to select the flow direction of data path and adopt which kind of QAM type to carry out equilibrium.
A, at the three phases of blind equalization, error is asked for according to following formula.
e(n)＝(R
2+L*T
2)-(L+1)*|y(n)|
2
Under different Q AM pattern, signal averaging energy radius R difference.In order to realize that conveniently L can choose 2
iForm.And each mark signal average energy radius T
2Then be blind equalization circuit 102 output the standard point place radius of data under various QAM patterns square.
B, in the LMS self adaptation stage, error is to ask for according to following formula:
The data of expression LMS adaptation module 105 outputs and the error amount between the determination point.
Under the situation of different balance stages, error calculating module 103 is sent to coefficient updating module 105 and MSE computing module 106 respectively with its result calculated (error).
The function of LMS adaptive balance module 104 is the same with blind equalization circuit 102, and unique different tap coefficient that is to use is inequality, so can share a cover mlultiplying circuit in side circuit.
Among coefficient updating module 105, the coefficient update formula is as follows:
In addition, the main process of its work of state controller 107 is:
A, judge according to the energy to equilibrium output data, start equalizer and enter the blind equalization second stage, and start over time that carrier recovery block is carried out phase place to equilibrium output data and frequency deviation is estimated.After locking, the control equalizer enters the blind equalization phase III.
B, the result who sends out according to MSE computing module 106 judge the convergence situation of equalization data, think then that when the MSE value is lower than a certain threshold value signal restrains under this given pattern, and the convergence of QAM pattern is correct.Otherwise change QAM pattern, equilibrium treatment again.
In conjunction with shown in Figure 2, workflow of the present invention is as follows:
Step S201: when selecting module 101 input signals to data, state controller 107 designation datas select module 101 to receive the data of not recovering correction through carrier wave.
Step S202: under acquiescence QAM pattern (such as 64QAM) control, the data that receive are sent into blind equalization circuit 102.State controller 107 is provided at the relevant parameter (as average energy radius and step-length) of blind equalization phase I under this pattern this moment, and detects the average energy situation behind the blind equalization data balancing of phase I at any time.
Step S203: when state controller 107 detects blind equalization first (initially) stage equilibrium data-signal energy later greater than a certain energy threshold value, enter blind equalization second (senior) stage.Otherwise continue the blind equalization of phase I, till equilibrium signal energy later reaches requirement.
Step S204: when equalizer enters the blind equalization second stage, state controller 107 provides relevant convergence step-length and the current sign energy radius information in this stage, begin to add up the symbolic number of input signal, after reaching preset value, start frequency deviation and skew that carrier wave recovers to detect balanced output signal.
Step S205: after carrier wave recovers to detect the frequency deviation locking, state controller 107 enters the blind equalization phase III, and utilize detected frequency deviation and skew to select to carry out derotation (being phase place and correcting frequency deviation) processing to receiving data in the module 101 in data, then the data after the derotation are sent into blind equalization module 102.
Step S206: when equalizer enters blind equalization during the phase III, state controller 107 provides the relevant information (as average energy radius and step-length) in this stage, restart to add up the symbolic number of input signal, after symbol counter reaches a certain counting thresholding, judge the output valve of MSE computing module 106.
Step S207: after state controller 107 detection MSE mean square errors were less than a certain threshold value, indication is balanced to enter the LMS adaptive equalization of step S208 and relevant convergence step-length and current sign energy radius information is provided; Select module 101 to change the QAM pattern otherwise enter the direct designation data of step S210, restart equilibrium.
Step S208: when equalizer enters LMS adaptive equalization during the stage, state controller 107 designation datas select module 101 to receive through carrier recovery block derotations data later, and detect the output valve of MSE computing module 106 again.
Step S209: after state controller 107 detection MSE mean square errors were less than a certain threshold value, the data after indication QAM mode locking and output equilibrium are adjudicated were given FEC; Otherwise enter step S210 and change the equilibrium again of QAM pattern.
In the different conditions of above-mentioned equalizer work, state controller 107 is index error computing module 103 error of calculation value and updating of tap coefficients simultaneously, provided by coefficient updating module 106 then data are carried out equilibrium.
In conjunction with shown in Figure 3, it is to be example with 16QAM, and energy radius dividing condition is described.4 the QAM points of first quartile of in Fig. 3, simply having painted, and can go out energy radius (the symbol energy radius T at these four QAM point places
2With the average energy radius R
2).In the equilibrium of DVB-C system, can determine symbol energy radius T according to the QAM pattern of maximum
2With the average energy radius R
2
Behind the signal input equalizer, equalizer at first converges to data the average energy radius R
2Near, and determine symbol energy radius T according to each symbolic point position
2Thereby, input signal is progressively converged under the required QAM pattern.Like this, system can arrive data balancing under the needed QAM pattern easily, thereby reaches the purpose of very fast and accurate blind equalization phase I convergence.
From formula e (n)=(R
2+ L*T
2The * of)-(L+1) | y (n) |
2As can be seen, in the CMA algorithm of correction, according to the different demands to the input data balancing in each stage, can be to restrain to the convergence of energy radius or to the symbol energy radius by selecting modifying factor L size to control equalizer.For example, during the phase I, equalizer more needs input signal to the energy radius R at blind equalization
2Last convergence can be selected less L value; And at blind equalization during the phase III, because coefficient is comparatively stable, and signal energy has been passed through the convergence of preceding two stage blind equalization, signal energy is stable, more need this moment signal is restrained to the standard point under a certain QAM pattern, then select bigger L, to obtain better to restrain effect, guarantee the correctness of convergence and less MSE mean square error.
In sum, equalization methods is to carry out blind equalization by revising the CMA algorithm in a kind of Digital Television disclosed by the invention, at first make the energy basis equalization of input signal to the required energy of QAM of a certain setting in the starting stage, further blind equalization again, entangle frequency deviation and skew in the input data then, advance blind equalization after a while again, necessarily require the laggard LMS of going into adaptive equalization when reaching, and judgement mean square error, judge the QAM pattern that draws, like this can be so that circuit be realized and control is relatively simple.
Claims (6)
1. the method based on the QAM pattern recognition of channel estimating and equilibrium is characterized in that, comprises step:
A, equalizer receives the input data under an acquiescence QAM pattern;
B, equalizer adopt blind equalization algorithm with the data energy that the first convergence step-length adjustment receives, and make balanced data-signal energy later greater than a certain energy threshold value;
C, equalizer adopt blind equalization algorithm with the second convergence step-length described input data to be carried out the equilibrium convergence, start frequency deviation and skew that carrier wave recovers to detect balanced output signal, after carrier wave recovered to detect the frequency deviation locking, data were carried out phase place and correcting frequency deviation is handled to receiving;
D, equalizer adopt blind equalization algorithm with the 3rd convergence step-length described input data to be carried out the equilibrium convergence, detect the mean square error of convergence back data whether less than a certain threshold value, if change step e over to, otherwise change step F over to;
E, equalizer carry out the convergence of LMS adaptive equalization to the input data, and whether the mean square error that detects convergence back data less than a certain threshold value, if then by with LMS adaptive equalization convergence input data, otherwise change step F over to;
F, replacing QAM pattern also change step B over to.
2. described based on the method for channel estimating with the QAM pattern recognition of equilibrium according to claim 1, it is characterized in that in step B, C or D, the account form of mean square error is in the blind equalization algorithm: e (n)=(R
2+ L*T
2The * of)-(L+1) | y (n) |
2Wherein,
Representing the signal averaging energy radius under a certain QAM pattern, T
2=E (| x (n) |
2) representing each mark signal average energy radius under a certain QAM pattern, L is modifying factor, the balanced output of y (n) expression.
3. it is characterized in that based on the method for channel estimating with the QAM pattern recognition of equilibrium that according to claim 2 is described in step B, C and D, each is restrained step size mu and satisfies relation:
W (n) is tap coefficient.
4. it is characterized in that based on the method for channel estimating with the QAM pattern recognition of equilibrium that according to claim 1 is described mean square error the during convergence of LMS adaptive equalization is:
The balanced output of y (n) expression.
5. it is characterized in that based on the method for channel estimating with the QAM pattern recognition of equilibrium that according to claim 4 is described in the step e, the convergence step size mu that LMS adaptive equalization adopts satisfies:
W (n) is tap coefficient.
6. it is characterized in that based on the method for channel estimating with the QAM pattern recognition of equilibrium according to claim 1 is described that the first convergence step-length is greater than the second convergence step-length, the second convergence step-length restrains step-length greater than the 3rd.
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| CN101931595B (en) * | 2010-08-06 | 2013-03-27 | 北京国科环宇空间技术有限公司 | Blind equalization method and blind equalization system |
| CN101931596A (en) * | 2010-08-06 | 2010-12-29 | 北京国科环宇空间技术有限公司 | Blind equalization method and blind equalization device |
| CN102891825B (en) * | 2012-10-08 | 2015-02-04 | 安徽省菲特科技股份有限公司 | Carrier recovery method and device of high-order QAM (quadrature amplitude modulation) system |
| CN102946368B (en) * | 2012-12-11 | 2016-03-23 | 西安电子科技大学 | The digital modulation signal recognizing method of frequency deviation and skew is contained under multidiameter fading channel |
| CN105933265B (en) * | 2016-03-31 | 2019-04-23 | 泉州装备制造研究所 | A kind of pair of QAM signal carries out the phase noise blind estimating method of unbound nucleus |
| CN106788771B (en) * | 2016-12-02 | 2019-05-07 | 武汉邮电科学研究院 | A kind of implementation method of the adaptive equalizer for coherent optical communication system |
| CN107396174B (en) * | 2017-05-31 | 2022-04-12 | 海信视像科技股份有限公司 | Code stream demodulation method and television |
| CN108900447A (en) * | 2018-06-27 | 2018-11-27 | 重庆湃芯入微科技有限公司 | A kind of linear equalizer with good gain compensation effect |
| CN109450831B (en) * | 2018-10-19 | 2021-10-22 | 中国人民解放军国防科技大学 | Convex combination-based parallel soft-switching blind equalization method for MQAM (multiple amplitude modulation) signals |
Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101478349A (en) * | 2009-01-20 | 2009-07-08 | 南京信息工程大学 | Dual mode variant step blind balance method based on orthogonal wavelet packet transform |
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Non-Patent Citations (2)
| Title |
|---|
| 基于盲均衡的高阶QAM信号调制识别算法;王彬等;《电子与信息学报》;20070831;第29卷(第8期);第1882-1886页 * |
| 王彬等.基于盲均衡的高阶QAM信号调制识别算法.《电子与信息学报》.2007,第29卷(第8期),第1882-1886页. |
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