CN119652709B - Feedback decision equalization method, feedback decision equalizer structure and data receiving end - Google Patents
Feedback decision equalization method, feedback decision equalizer structure and data receiving end Download PDFInfo
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Abstract
The invention belongs to the field of communication circuits, and provides a feedback decision equalization method, a feedback decision equalizer structure and a data receiving end, wherein the method comprises the steps of calculating and obtaining an equalization signal according to the difference value between an input signal and a feedback signal, wherein the feedback signal is obtained by modulating a feedback tap coefficient by a delay decision signal, the decision signal is obtained by threshold decision of the equalization signal, the reference signal is obtained by modulating a decision signal according to a reference tap coefficient, the difference value between the equalization signal and the reference signal is calculated, the feedback tap coefficient and the reference tap coefficient are adaptively trained and updated until the difference value converges, the conventional method of additionally training a decision threshold is avoided by adding the reference tap coefficient, and therefore a feedback decision scheme with simple structure and better performance is obtained.
Description
Technical Field
The invention belongs to the field of communication circuits, and particularly relates to a feedback decision equalization method, a feedback decision equalizer structure and a data receiving end.
Background
ISI (Inter-Symbol Interference Inter-symbol interference) occurs when data passes through a high-speed channel. The receiving end generally needs CTLE (Continuous TIME LINEAR Equalizer), FFE (Feed Forward Equalization, feedforward Equalizer), DFE (Decision Feedback Equalizer ) and other modules for recovering data, wherein the DFE module adopts a feedback decision structure, and the DFE coefficient is adaptively trained by a least mean Square (LEAST MEAN Square, LMS) error algorithm.
In the conventional feedback decision equalizer working process, referring to fig. 1, an input signal x in is subtracted from a feedback signal x fb of a feedback modulation unit to obtain an equalized signal y eq, where the feedback signal x fb is a product accumulated value of a DFE coefficient (w 1~wm) with a tap number of m and a delayed decision signal d k-1~dk-m, which represents interference of other symbols to a current symbol. The equalized signal y eq represents the signal after the input signal x in has filtered out the feedback signal x fb representing the disturbance. The equalized signal y eq is decided by a decision device sler to obtain a decision value d k. and (3) recording the gain value of the decision device slicer as G th, wherein the error value input and output by the slicer module is e k, recording the signal threshold V th=1/Gth and the error value expression is e k=yeq-dk/Gth=yeq- dk*Vth. From the equalized signal y eq, And calculating an error value e k by the decision value d k and the V th, and adjusting the DFE coefficient in the self-adaptive training module according to the error value e k so that the error of the feedback decision equalizer is gradually reduced. The feedback decision equalizer depends on the error value, and the error value depends on the signal threshold V th, while the signal threshold V th generally requires additional power consumption and time to stabilize, and has high complexity. Accordingly, there is a need to provide a feedback decision equalization method, a feedback decision equalizer, and a data receiving end to solve the above-mentioned problems in the prior art.
Disclosure of Invention
In order to reduce the dependence of a feedback decision equalizer on a signal threshold and reduce overall complexity, the application provides a feedback decision equalizing method, a feedback decision equalizer and a data receiving end.
The application provides a feedback decision equalizing method, a feedback decision equalizer structure and a data receiving end, which adopt the following technical scheme:
A feedback decision equalization method comprising:
Modulating the delayed decision signal according to the feedback tap coefficient to obtain a feedback signal;
calculating according to the difference between the input signal and the feedback signal to obtain an equalization signal;
Threshold judgment is carried out on the balanced signal to obtain a judgment signal;
modulating the decision signal according to a reference tap coefficient to obtain a reference signal;
Calculating the difference value between the equalization signal and the reference signal, and adaptively training and updating the feedback tap coefficient and the reference tap coefficient according to the decision signal so that the difference value tends to converge;
the feedback signal is generated after the delay decision signal is modulated by the feedback tap coefficient, and is used for representing the interference of the delay symbol to the current symbol.
According to the technical scheme, self-adaptive training is carried out according to the decision signal and the difference value to continuously generate a training tap coefficient sequence so as to update the feedback tap coefficient and the reference tap coefficient, so that the difference value gradually tends to converge, wherein the feedback tap coefficient is used for generating a feedback signal simulating other symbol interference, and the reference tap coefficient is used for generating a reference signal pulling up the gain of the decision device. By adding the reference tap coefficient, the traditional method of additional training decision threshold is avoided, and thus the balanced signal with simple structure and better performance is obtained.
Optionally, modulating the delayed decision signal according to the feedback tap coefficient to obtain a feedback signal includes:
according to a preset feedback tap number m, delaying the decision signal for 1 to m symbol times to obtain a delayed decision signal sequence;
Sequentially modulating the delay decision signal sequences one by adopting the feedback tap coefficients to obtain feedback sub-signal sequences, wherein the feedback tap coefficients have initial values;
And generating the feedback signal according to the aggregation result of the feedback sub-signal sequence.
By adopting the technical scheme, the decision signals are delayed according to the delay step length, so that a plurality of delay decision signal sequences with different delay time sequences are obtained. And modulating the decision signal sequences with different delay time sequences by adopting corresponding feedback tap coefficients to obtain feedback sub-signals of the delay time sequences. All feedback sub-signals of the delay time sequence form a feedback sub-signal sequence. And then adding all feedback sub-signals in all feedback sub-signal sequences to obtain feedback signals. Wherein, for the initial feedback signal being the initial value of the feedback tap coefficient, the historical decision signal of the modulation delay is obtained.
Optionally, performing threshold decision on the equalization signal to obtain a decision signal, including:
When the threshold is When the threshold judgment result isThe decision function is:
;
The decision signal is represented as,
;
Wherein, In order to decide the signal(s),In order to equalize the signal,For the reference tap coefficients,Indicating the time sequence number.
Optionally, modulating the decision signal according to a reference tap coefficient to obtain a reference signal includes:
after threshold judgment is carried out on the balanced signal to obtain a judgment signal, the judgment signal is modulated according to a reference tap coefficient to obtain the reference signal, and the reference tap coefficient has an initial value.
Optionally, the calculating a difference between the equalization signal and the reference signal, adaptively training and updating the feedback tap coefficient and the reference tap coefficient according to the decision signal, so that the difference tends to converge, includes:
calculating the difference between the equalization signal and the reference signal to obtain an error signal;
adaptively training the feedback tap coefficient and the reference tap coefficient according to the decision signal, and updating the feedback tap coefficient and the reference tap coefficient;
and when the error signal meets a convergence standard, judging that the error signal converges, wherein the convergence standard is that the sum value of the error signal is smaller than a preset threshold value within a preset duration.
By adopting the technical scheme, when the error signal generated by the difference between the equalization signal and the reference signal reaches the convergence standard, the equalization signal at the moment is judged to be the result of the best interference effect caused by filtering other symbols by the input signal, so that the output equalization signal gradually tends to be optimal.
And setting the convergence standard to be smaller than a preset threshold within the window time of the preset duration. Compared with the instantaneous judgment of error signals when filtering interference, the instantaneous judgment is easy to be inaccurate due to signal fluctuation, the scheme fully ensures the stability of balanced signals during judgment through the sum value of errors in window time, and reduces the influence of signal fluctuation on the overall precision.
Optionally, calculating a difference between the equalization signal and the reference signal to obtain an error signal includes:
The error signal is represented as a signal representing, ,
Wherein, In order to equalize the signal,As a reference signal, a reference signal is provided,Representing the reference tap coefficients of the reference signal,In order to decide the signal(s),Indicating the time sequence number.
Optionally, performing adaptive training on the feedback tap coefficient and the reference tap coefficient according to the decision signal includes:
Calculating the feedback tap coefficient and the reference tap coefficient in the modulated training tap coefficient sequence according to a preset step length, the equalizing signal, the reference signal and an initial training tap coefficient sequence,
,E [0, m ], m is the feedback tap number;
wherein the initial training tap coefficient sequence comprises an initial feedback tap coefficient and an initial reference tap coefficient, The time sequence number is indicated as such,Is thatTap coefficients at the corresponding positions after updating; as an error signal, the signal is a signal, To equalize signalsThe step length is preset;
When i=0, the number of the cells, Representing the reference tap coefficients of the reference signal,Representing initial reference tap coefficients;
when i is greater than 0, the method comprises the steps of, Representing the feedback tap coefficients of the signal,Representing the initial feedback tap coefficients.
By adopting the technical proposal, the utility model has the advantages that,For the ith feedback tap coefficient in the modulated training tap coefficient sequence,Is the ith feedback tap coefficient in the training tap coefficient sequence before modulation, mu is the step length of the training tap coefficient sequence in the initial state,Is an error signal dIn order to decide the signal(s),Is a decision signal that has undergone i delays. And updating according to the initial training tap coefficient sequence to obtain a training tap coefficient sequence after self-adaptive training.
The invention also provides a feedback decision equalizer structure, which comprises a first subtracter, a decision device, a self-adaptive training unit, a feedback modulation unit, a reference modulation unit, a second subtracter, a convergence judging unit and an output unit;
the first subtracter is connected with the feedback modulation unit and is used for calculating a difference value according to an input signal from the outside and a feedback signal from the feedback modulation unit to obtain an equalization signal;
the decision device is connected with the first subtracter and is used for deciding the balanced signal according to a threshold to obtain a decision signal;
The reference modulation unit is connected with the decision device, the self-adaptive training unit and the second subtracter, and is used for modulating the decision signal according to a reference tap coefficient to obtain a reference signal and transmitting the reference signal to the second subtracter;
The second subtracter is connected with the first subtracter, the reference modulation unit and the convergence judging unit and is used for calculating the difference value between the reference signal and the balanced signal, generating an error signal and sending the error signal to the convergence judging unit;
The feedback modulation unit is connected with the decision device, the self-adaptive training unit and the first subtracter, and is used for modulating the decision signal according to a feedback tap coefficient to obtain the feedback signal and transmitting the feedback signal to the first subtracter;
the convergence judging unit is connected with the second subtracter and is used for giving convergence judgment when the error signal meets the convergence standard;
the output unit is connected with the decision device and is used for outputting the decision signal;
The self-adaptive training unit is connected with the decision device and is used for carrying out self-adaptive training according to the decision signal to obtain a training tap coefficient sequence so that the error signal tends to converge, and the training tap coefficient sequence comprises a feedback tap coefficient and a reference tap coefficient.
By adopting the technical scheme, the first subtracter obtains an equalization signal according to the input signal and the feedback signal. The decision device processes the equalization signal to obtain a decision signal, the decision signal is subjected to self-adaptive training unit and then trains a tap coefficient sequence, wherein the feedback tap coefficient is used for generating a feedback signal by combining the decision signal so as to simulate intersymbol interference, and the reference tap coefficient is used for pulling up the gain of the decision device. The scheme introduces a reference modulation unit, modulates the decision signal by adjusting a reference tap coefficient to obtain a reference signal, and avoids the conventional method of additionally training a decision threshold, thereby obtaining an equalization signal with simple structure and better performance.
Optionally, the feedback modulation unit includes a third adder and a plurality of sets of delay multiplication circuits, each set of delay multiplication circuits including a delay and a modulation multiplier;
In each group of delay multiplication circuits, the input end of the delay device is connected with the output end of the decision device, the input end of the modulation multiplier is connected with the output end of the delay device, the delay device is used for carrying out time sequence modulation on the decision signal to obtain a delay decision signal, and the modulation multiplier is used for multiplying a feedback tap coefficient with the delay decision signal to obtain a feedback sub-signal, wherein the delay time length of the time sequence modulation of the delay device in each group of delay multiplication circuits is increased;
the third adder is connected with the modulation multipliers in each group of delay multiplying circuits and is used for adding feedback sub-signals of all delay multiplying circuits to obtain the feedback signal.
By adopting the technical scheme, in the self-adaptive training modulation unit, the delayers of each group of delay multiplication circuits are directly connected with the decision device and used for delaying the decision signals in different time lengths, and then multiplying the delayed decision signals with the corresponding feedback tap coefficients to obtain feedback sub-signals. And adding all feedback sub-signals through a third adder to obtain a feedback signal.
The invention also provides a data receiving end, which comprises a data recovery module, wherein the data recovery module comprises a continuous time linear equalizer, a feedforward equalizer and the feedback decision equalizer structure.
In summary, the present application includes at least one of the following beneficial technical effects:
1. By setting the reference tap coefficient, the scheme has a simple structure, saves the power consumption and time of independent training of the signal threshold, and avoids the coupling of the DFE module and the signal threshold training module.
2. The scheme sets the reference tap coefficient, multiplexes the training method of the traditional DFE feedback coefficient, uses the LMS algorithm to converge along the gradient descent direction, and converges faster than the traditional signal threshold.
3. The scheme sets the reference tap coefficient, multiplexes the training method of the traditional DFE feedback coefficient, and because the LMS algorithm step length is smaller, the training result is more accurate and stable than the result of the traditional signal threshold, and the DFE performance is better.
Drawings
Fig. 1 is a schematic diagram of a feedback decision equalizer in the background art;
fig. 2 is a schematic flow chart of a feedback decision equalization method provided by the present invention;
Fig. 3 is a schematic block diagram of a feedback decision equalizer structure provided by the present invention;
FIG. 4 is a schematic block diagram of the feedback modulation unit of FIG. 3;
Fig. 5 is a schematic diagram of the structure of the feedback modulation unit in fig. 4;
FIG. 6 is another block diagram of the feedback modulation unit of FIG. 3;
fig. 7 is a schematic diagram of the structure of the feedback modulation unit in fig. 6.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the present invention more apparent, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention. Unless otherwise defined, technical or scientific terms used herein should be given the ordinary meaning as understood by one of ordinary skill in the art to which this invention belongs. As used herein, the word "comprising" and the like means that elements or items preceding the word are included in the element or item listed after the word and equivalents thereof without precluding other elements or items.
The first embodiment of the invention provides a feedback decision equalization method, which is shown by referring to fig. 2, and comprises the steps of obtaining a feedback signal according to a decision signal of a feedback tap coefficient modulation delay, obtaining an equalization signal according to a difference value between an input signal and the feedback signal, carrying out threshold decision on the equalization signal to obtain the decision signal, modulating the decision signal according to a reference tap coefficient to obtain a reference signal, calculating the difference value between the equalization signal and the reference signal, carrying out self-adaptive training according to the decision signal, updating the feedback tap coefficient and the reference tap coefficient to enable the difference value to trend to converge, wherein the feedback signal is generated after the feedback tap coefficient modulation of the delay decision signal and is used for representing interference of a delay symbol to a current symbol.
In the method, self-adaptive training is carried out according to the decision signal and the difference value to continuously generate a training tap coefficient sequence so as to update the feedback tap coefficient and the reference tap coefficient, so that the difference value gradually tends to be converged. The feedback tap coefficient is used for generating feedback signals simulating other symbol interference, and the reference tap coefficient is used for generating reference signals of the gain of the pull-up decision device. By adding the reference tap coefficient, the reference tap coefficient gradually approaches the gain of the pull-in decision device along with the gradual convergence of the difference value, and avoids the traditional method of additional training decision threshold, thereby obtaining the balanced signal with simple structure and better performance.
The implementation details of a feedback decision equalizing method of the present invention are specifically described below, and the following details are provided only for facilitating understanding, and a specific flow of this embodiment is shown in fig. 2, and includes the following steps:
Step 101, modulating the delayed decision signal according to the feedback tap coefficient to obtain a feedback signal.
Specifically, the feedback tap coefficient(I > 0) has an initial value,Representing the initial feedback tap coefficients. The specific implementation of step 101 includes:
S1-1, according to the preset feedback tap number m, judging a signal Performing delay of 1 to m symbol times, wherein the delay step length of each symbol time is t, and obtaining a delay decision signal sequence {、、......}。
Wherein, Representing time sequence number, the decision signalPerforming first delay to obtain delay decision signal sequenceBy combining decision signalsPerforming a second delay to obtain a delayed decision signal sequenceBy combining decision signalsPerforming a third delay to obtain a delayed decision signal sequenceBy combining decision signalsPerforming the mth delay to obtain a delay decision signal sequence。
S1-2, training tap coefficient sequence { is adopted in sequence、、、......Feedback tap coefficients { in }、、......{ For a delayed decision signal sequence }、、......One-to-one modulation is performed to obtain a feedback sub-signal sequence,Indicating the time sequence number.
Specifically, a training tap coefficient sequence { is adopted、、......{ For delay judgment sequence }、、......One-to-one modulation, specifically:
delay determination signal obtained for first delay Using feedback tap coefficientsModulating to obtain feedback sub-signals*A delay judgment signal obtained by the second delayUsing feedback tap coefficientsModulating to obtain feedback sub-signals*A delay judgment signal obtained by the third delayUsing feedback tap coefficientsModulating to obtain feedback sub-signals*And so on, for the delay judgment signal obtained by the mth delayUsing feedback tap coefficientsModulating to obtain feedback sub-signals*。
Where k=0, the tap coefficient sequence { is trained、、、......The initial feedback tap coefficient { in the initial training tap coefficient sequence is set to {、、......Using the initial feedback tap coefficient to make { a historical delay decision signal sequence input by the system、、......And performing one-to-one modulation, wherein k is larger than or equal to m, and obtaining a feedback sub-signal.
Under the continuous updating of step 105, according to the decision signalFrom the initial training tap coefficient sequence {、、、......Self-adaptive training is started to obtain an updated training tap coefficient sequence {、、、......The updated training tap coefficient sequence {、、、......Comprises reference tap coefficientsAnd by a plurality of feedback tap coefficientsConstructed training tap coefficient sequence {、、......}. Using training tap coefficient sequences {、、......Feedback tap coefficients(0<I.ltoreq.m) { for delay judgment sequence、、......And performing one-to-one modulation to obtain a feedback sub-signal.
S1-3, generating a feedback signal according to the aggregation result of the feedback sub-signal sequence. Specifically, the initial training tap coefficient sequence {、、、......Comprises initial feedback tap coefficientsAnd initial reference tap coefficients。
Based on all feedback tap coefficients in a training tap coefficient sequence (i.e., a DFE sequence)(I > 0) for delayed decision signalModulating to obtain feedback signal. Will decide the signalDifferent delays are performed and decision signals for each delay are determinedAnd corresponding feedback tap coefficients(I > 0) to obtain feedback sub-signals, and then adding all the feedback sub-signals to obtain a feedback signal.
The sum of these feedback sub-signals is then used as the feedback signal,*+*+*+......+*. Realizing the feedback tap coefficient(0<I.ltoreq.m) vs. decision signalTo obtain feedback signalThe expression is:,。
step 102, according to the difference between the input signal and the feedback signal, an equalization signal is obtained by calculation.
Specifically, data is transmitted to a data receiving end through a high-speed channel. In order to recover the original data, the data receiving end generally needs to use a decision feedback equalizer to filter the interference of other symbols to the current symbol. Input signal in this caseData received by the data receiving end and feedback signalsQuantized signal, equalized signal, for other symbols interfering with current symbolThen represents the output signal of the filtered feedback signal. Wherein the feedback signalThe generation of (c) depends on step 102 and step 103, k representing a time sequence number.
And, step 102 continuously outputs the equalized signal. Equalizing signals in this caseWith feedback tap coefficientsThe adaptive training update of (i > 0) gradually tends to stabilize.
Step 103, threshold decision is performed on the equalization signal to obtain a decision signal.
This patent includes, but is not limited to, a function, e.g., a decision maker sler threshold ofThe results of the corresponding decision signals are ordered according to the values,
The decision function SlicerJudge is:
。
Based on this case, the signal is traditionally decided It is indicated that the number of the elements is,
Wherein, the method comprises the steps of,In order to decide the signal(s),As a function of the decision,For equalizing the signal, the decision-maker has a gain of,Indicating the time sequence number.
In the present application,For measuring the size of the Slicer gain, deciding the signalIt is indicated that the number of the elements is,
Wherein, the method comprises the steps of,The time sequence number is indicated as such,In order to decide the signal(s),In order to equalize the signal,Is the reference tap coefficient. Therefore, the scheme is implemented by setting the reference tap coefficientSaving signal thresholdThe power consumption and time of the independent training avoid the coupling of the DFE module and the signal threshold training module.
Step 104, modulating the decision signal according to the reference tap coefficient to obtain a reference signal.
In particular, reference tap coefficients are usedFor decision signalModulating to obtain reference signal,。
Wherein, when the reference signal is generated for the first timeUsing initial reference tap coefficientsFor decision signalModulating, then step 105 calculates a training tap coefficient sequence using the updated reference tap coefficients therein。
Step 105, calculating the difference between the equalization signal and the reference signal, adaptively training according to the decision signal, and updating the feedback tap coefficient and the reference tap coefficient so that the difference tends to converge.
Specifically, the staff sets an initial training tap coefficient sequence according to the judgment signalAnd carrying out self-adaptive training on the initial training tap coefficient sequence to obtain a continuously updated training tap coefficient sequence. Each training tap coefficient sequence includes reference tap coefficientsAnd feedback tap coefficients(I > 0), wherein the tap coefficients are referencedFor deciding signalsModulating to obtain reference signalFeedback tap coefficient(I > 0) for deciding signalModulating to obtain a feedback signal applied to step 101From equalised signalsReference signalError signal generated by difference between themWhether or not convergence is the reference, the training tap coefficient sequence is continuously updated to enable the error signal corresponding to the difference valueTending to converge.
The implementation of this step 105 includes:
S5-1, calculating an equalization signal With reference signalsThe difference between them to obtain an error signal,。
S5-2, according to the decision signalAdaptive training and updating feedback tap coefficients(I > 0) and reference tap coefficientsSo that the error signalWhich tends to converge.
S5-3, judging error signalWhether convergence criterion is met, in error signalDetermining an error signal when the convergence criterion is satisfiedConverging and feeding back.
In step S5-2, adaptive training is performed according to the decision signal to obtain a training tap coefficient sequence, including according to a preset step lengthEqualizing a signalReference signalInitial training tap coefficient sequence {、、、......Calculating a training tap coefficient sequence { after modulation }、、、......},
,
,
Wherein the initial training tap coefficient sequence comprises initial feedback tap coefficientsAnd initial reference tap coefficients,Is thatTap coefficients at the corresponding positions after updating; as an error signal, the signal is a signal, In order to equalize the signal,As a reference signal, a reference signal is provided,For a preset step size, k represents a time sequence number, and when i=0,Representing the reference tap coefficients of the reference signal,Representing the initial reference tap coefficient, when 0<i is less than or equal to m,Representing the feedback tap coefficients of the signal,And representing initial feedback tap coefficients, wherein m is the number of feedback taps.
In the error signalWhen the convergence criterion is met, i.e. when the input signal filters other symbols resulting in the best interference effect,This is true, wherein,For the modulated training tap coefficient sequence,Is a training tap coefficient sequence before modulation,To train the step size of the tap coefficient sequence,As an error signal, the signal is a signal,In order to decide the signal(s),Is a decision signal that has undergone i delays. And updating according to the initial training tap coefficient sequence to obtain a training tap coefficient sequence after self-adaptive training.
In step S5-3, an error signal is determinedWhen the convergence criterion is satisfied, the convergence criterion is within a preset time length, and the error signalThe sum of which is less than a preset threshold value. This example takes into account the error signalInstability in transmission, for error signalsAnd judging the time period, wherein the convergence standard is set to be in window time with preset duration, and the sum value of errors is smaller than a preset threshold. Phase error signalThe scheme fully ensures the balanced signal during the judging period through the sum value of errors in window time under the condition that the instantaneous judgment of (a) is easy to be inaccurateThe influence of signal fluctuation on the overall accuracy is reduced. Equalizing signals upon convergenceAbout equal toSo that the signal is equalizedSubstantially no inter-symbol interference ISI is contained.
It should be noted that the signals are equalizedError signalAccording to LMS algorithm, along the gradientIn the direction of (i.e., DFE training) the adaptive training (i.e., DFE training) converges most rapidly, where i=0, 1. The number of the first group is m, m is a positive integer; Training tap coefficient sequences ~A preset step length betweenThen toTraining step length for DFE according toDirectional update of (2)When the time, then,
,
Wherein, Is thatAnd updating the tap coefficient of the corresponding position. When i is more than or equal to 0 and less than or equal to m,
;
。
Therefore, the training method of the traditional DFE feedback coefficient is multiplexed, the LMS algorithm is used for converging along the gradient descent direction, and compared with the traditional scheme, the training method has the advantages that the result of obtaining the signal threshold through additional training is faster and more stable, and the DFE performance is better.
The above steps of the various methods are divided, for clarity of description, and may be combined into one step or split into multiple steps when implemented, so long as they include the same logic relationship, and all the steps are within the scope of protection of this patent, and adding insignificant modifications or introducing insignificant designs to the algorithm or the process, but not changing the core designs of the algorithm and the process are within the scope of protection of this patent.
A second embodiment of the present invention provides a feedback decision equalizer structure, as shown in fig. 3, comprising:
a first subtracter 301 connected to the feedback modulation unit 304 for calculating an input signal And feedback signalGenerates an equalized signal;
A decision device 302 connected to the first subtractor 301 for equalizing the signalMaking a decision to obtain a decision signal;
A reference modulation unit 305 connected to the decision device 302, the adaptive training unit 303 and the second subtracter 306 for generating reference tap coefficientsFor decision signalModulating to obtain reference signalAnd sent to a second subtractor 306;
A second subtracter 306 connected to the first subtracter 301, the reference modulation unit 305, and the convergence judgment unit 307, for calculating a reference signal And equalizing signalsGenerates an error signal;
A feedback modulation unit 304 connected to the decision device 302, the adaptive training unit 303, and the first subtractor 301 for generating a feedback tap coefficient(0<I.ltoreq.m, m is the number of taps), for the decision signalModulating to obtain feedback signalAnd sent to the first subtractor 301;
Convergence judging unit 307 connected to the second subtracter 306 for generating an error signal When the convergence criterion is met, giving convergence judgment;
An output unit 308 connected to the decision device 302 for outputting a decision signal ;
An adaptive training unit 303 connected to the decision device 302, the reference modulation unit 305, and the feedback modulation unit 304 for determining a signal according to the decision signalPerforming adaptive training to obtain a training tap coefficient sequence so as to enable an error signalTowards convergence, the training tap coefficient sequence includes feedback tap coefficientsAnd reference tap coefficientsWherein 0<i is less than or equal to m, and m is the number of taps.
In this case, the first subtractor 301 is based on the input signalAnd feedback signals for simulating interference caused by other symbolsObtaining an equalized signal. Decision device 302 equalizes the signalModulating to obtain decision signalThe decision signalGenerates a feedback signal after passing through the feedback modulation unit 304. Wherein the adaptive training unit 303 gradually adjusts its own training tap coefficient sequence to update the feedback tap coefficients(0<I.ltoreq.m, m is the number of taps) and reference tap coefficients。
Reference modulation unit 305 is introduced by adjusting the reference tap coefficientsFor decision signalModulating to obtain reference signal. Subsequently calculate a reference signalAnd equalizing the signalError signal formed by differenceFurther adjusting the training tap sequence to equalize the signalTends to be optimally performing. In some examples, as shown in fig. 4 and 5, the feedback modulation unit 304 includes a third adder 3041 and multiple sets of delay multiplication circuits, each set of delay multiplication circuits including a delay 3042 and a modulation multiplier 3043;
in each group of delay multiplying circuits, an input terminal of a delay 3042 is connected to an output terminal of a decision device 302, an input terminal of a modulation multiplier 3043 is connected to an output terminal of the delay 3032, and the delay 3042 is used for outputting a decision signal Performing time sequence modulation to obtain delay decision signal(0<I. Ltoreq.m, m is the number of taps), the modulation multiplier 3043 is used to feed back the tap coefficientsAnd delay decision signalMultiplying to obtain feedback sub-signalWherein the delay duration of the timing modulation of the delays in each set of delay multiplier circuits is incremented, the tap coefficients are fed backTraining tap coefficient sequence { belonging to preset step length、、、......A third adder 3041 connected with the modulation multiplier 3042 in each group of delay multiplying circuits for adding the feedback sub-signals of all delay multiplying circuits to obtain a feedback signal。
In the feedback modulation unit 304 of the present example, the delay 3042 of each set of delay multiplying circuits is directly connected to the decision device 302 for determining the signalDelay with different time lengths is carried out, and then the delay is multiplied by corresponding feedback tap coefficients to obtain feedback sub-signals, and all the feedback sub-signals are added by a third adder 3041 to obtain feedback signals。
In other examples, as shown in fig. 6 and 7, the feedback modulation unit 304 includes a third adder 3041 and a plurality of sets of delay multiplication circuits, each set of delay multiplication circuits including a delay 3042 and a modulation multiplier 3043;
An input end of a delay 3042 in the first group of delay multiplication circuits is connected with an output end of the decision device 302, and an input end of a modulation multiplier 3043 is connected with an output end of the delay 3042;
The input end of the delay 3042 in the latter bit delay multiplication circuit is connected with the output end of the delay 3042 in the former bit delay multiplication circuit, the input end of the modulation multiplier 3043 is connected with the output end of the delay 3042, and the delay 3042 at the first bit is used for judging the signal Performing time sequence modulation to obtain delay decision signalThe latter bit delay 3042 is used for carrying out time sequence modulation on the delay decision signal input by the former delay 3042 to obtain a new delay decision signal and updating, and the modulation multiplier 3043 is used for feeding back tap coefficientsAnd delay decision signalMultiplying to obtain feedback sub-signals, wherein the time sequence modulation of the delay 3042 in each group of delay multiplying circuits is the same, and the feedback tap coefficients(I >0 and i.ltoreq.m) training tap coefficient sequences { belonging to a preset step size,、、......A third adder 3041 connected to the modulation multiplier 3032 in each group of delay multiplying circuits for adding the feedback sub-signals of all delay multiplying circuits to obtain a feedback signal。
In the adaptive training modulation unit 303 of the present example, a delay 3042 of a delay multiplying circuit located at the first position is connected to a decision device 302, and decides a signalThe delay device 3042 of the delay multiplication circuit of the next bit is connected with the delay device 3042 of the delay multiplication circuit of the previous bit, and the delay is performed again on the basis of the delay device 3042 of the previous bit, and then the delay device is multiplied with the corresponding feedback tap coefficient to obtain a feedback sub-signal. All feedback sub-signals are added by a third adder 3041 to obtain a feedback signal。
In addition, other implementation details and operation manners of the feedback decision equalizer structure disclosed in the present application are the same as or similar to those of the feedback decision equalizing method described above, and are not described herein in detail.
The third embodiment of the invention also discloses a data receiving end. The data receiving end comprises a data recovery module, and the data recovery module comprises a continuous time linear equalizer, a feedforward equalizer and the feedback decision equalizer structure.
While embodiments of the present invention have been described in detail hereinabove, it will be apparent to those skilled in the art that various modifications and variations can be made to these embodiments. It is to be understood that such modifications and variations are within the scope and spirit of the present invention as set forth in the following claims. Moreover, the invention described herein is capable of other embodiments and of being practiced or of being carried out in various ways.
Claims (10)
1. A feedback decision equalization method, comprising:
Modulating the delayed decision signal according to the feedback tap coefficient to obtain a feedback signal;
calculating according to the difference between the input signal and the feedback signal to obtain an equalization signal;
Threshold judgment is carried out on the balanced signal to obtain a judgment signal;
modulating the decision signal according to a reference tap coefficient to obtain a reference signal;
Calculating the difference value between the equalization signal and the reference signal, and adaptively training and updating the feedback tap coefficient and the reference tap coefficient according to the decision signal so that the difference value tends to converge;
the feedback signal is generated after the delay decision signal is modulated by the feedback tap coefficient, and is used for representing the interference of the delay symbol to the current symbol.
2. The feedback decision equalization method of claim 1, wherein the modulating the delayed decision signal based on the feedback tap coefficients results in a feedback signal comprising:
according to a preset feedback tap number m, delaying the decision signal for 1 to m symbol times to obtain a delayed decision signal sequence;
Sequentially modulating the delay decision signal sequences one by adopting the feedback tap coefficients to obtain feedback sub-signal sequences, wherein the feedback tap coefficients have initial values;
And generating the feedback signal according to the aggregation result of the feedback sub-signal sequence.
3. The feedback decision equalization method of claim 1, wherein said performing a threshold decision on said equalized signal results in a decision signal comprising:
When the threshold is When the threshold judgment result isThe decision function is:
;
The decision signal is represented as,
;
Wherein, In order to decide the signal(s),In order to equalize the signal,For the reference tap coefficients,Indicating the time sequence number.
4. The feedback decision equalization method of claim 1, wherein modulating the decision signal based on the reference tap coefficients results in a reference signal, comprising:
after threshold judgment is carried out on the balanced signal to obtain a judgment signal, the judgment signal is modulated according to a reference tap coefficient to obtain the reference signal, and the reference tap coefficient has an initial value.
5. The feedback decision equalization method of claim 1, wherein said calculating a difference between an equalized signal and a reference signal, adaptively training and updating said feedback tap coefficients and said reference tap coefficients based on said decision signal such that said difference tends to converge comprises:
calculating the difference between the equalization signal and the reference signal to obtain an error signal;
adaptively training the feedback tap coefficient and the reference tap coefficient according to the decision signal, and updating the feedback tap coefficient and the reference tap coefficient;
and when the error signal meets a convergence standard, judging that the error signal converges, wherein the convergence standard is that the sum value of the error signal is smaller than a preset threshold value within a preset duration.
6. The feedback decision equalization method of claim 5, wherein calculating the difference between the equalized signal and the reference signal results in an error signal, comprising:
The error signal is represented as a signal representing, ,
Wherein, In order to equalize the signal,As a reference signal, a reference signal is provided,Representing the reference tap coefficients of the reference signal,In order to decide the signal(s),Indicating the time sequence number.
7. The feedback decision equalization method of claim 5, wherein adaptively training the feedback tap coefficients and the reference tap coefficients based on the decision signal comprises:
Calculating the feedback tap coefficient and the reference tap coefficient in the training tap coefficient sequence according to a preset step length, the equalizing signal, the reference signal and an initial training tap coefficient sequence,
,E [0, m ], m is the feedback tap number;
wherein the initial training tap coefficient sequence comprises an initial feedback tap coefficient and an initial reference tap coefficient, The time sequence number is indicated as such,Is thatTap coefficients at the corresponding positions after updating; as an error signal, the signal is a signal, The step length is preset;
When i=0, the number of the cells, Representing the reference tap coefficients of the reference signal,Representing the initial reference tap coefficients of the signal,For deciding the signal;
When i is greater than 0, the method comprises the steps of,Representing the feedback tap coefficients of the signal,Representing the initial feedback tap coefficients of the signal,Representing a delayed decision signal, meaning a decision signalCarry out the first stepThe resulting signal is sub-delayed.
8. The feedback decision equalizer is characterized by comprising a first subtracter, a decision device, an adaptive training unit, a feedback modulation unit, a reference modulation unit, a second subtracter, a convergence judging unit and an output unit;
the first subtracter is connected with the feedback modulation unit and is used for calculating a difference value according to an input signal from the outside and a feedback signal from the feedback modulation unit to obtain an equalization signal;
the decision device is connected with the first subtracter and is used for deciding the balanced signal according to a threshold to obtain a decision signal;
The reference modulation unit is connected with the decision device, the self-adaptive training unit and the second subtracter, and is used for modulating the decision signal according to a reference tap coefficient to obtain a reference signal and transmitting the reference signal to the second subtracter;
The second subtracter is connected with the first subtracter, the reference modulation unit and the convergence judging unit and is used for calculating the difference value between the reference signal and the balanced signal, generating an error signal and sending the error signal to the convergence judging unit;
The feedback modulation unit is connected with the decision device, the self-adaptive training unit and the first subtracter, and is used for modulating the decision signal according to a feedback tap coefficient to obtain the feedback signal and transmitting the feedback signal to the first subtracter;
the convergence judging unit is connected with the second subtracter and is used for giving convergence judgment when the error signal meets the convergence standard;
the output unit is connected with the decision device and is used for outputting the decision signal;
the self-adaptive training unit is connected with the decision device, the reference modulation unit and the feedback modulation unit and is used for carrying out self-adaptive training according to the decision signal to obtain a training tap coefficient sequence so that the error signal tends to converge, and the training tap coefficient sequence comprises a feedback tap coefficient and a reference tap coefficient.
9. The feedback decision equalizer structure of claim 8, wherein the feedback modulation unit comprises a third adder and a plurality of sets of delay multiplier circuits, each set of delay multiplier circuits comprising a delay and a modulation multiplier;
In each group of delay multiplication circuits, the input end of the delay device is connected with the output end of the decision device, the input end of the modulation multiplier is connected with the output end of the delay device, the delay device is used for carrying out time sequence modulation on the decision signal to obtain a delay decision signal, and the modulation multiplier is used for multiplying a feedback tap coefficient with the delay decision signal to obtain a feedback sub-signal, wherein the delay time length of the time sequence modulation of the delay device in each group of delay multiplication circuits is increased;
the third adder is connected with the modulation multipliers in each group of delay multiplying circuits and is used for adding feedback sub-signals of all delay multiplying circuits to obtain the feedback signal.
10. A data receiving end, comprising a data recovery module, wherein the data recovery module comprises a continuous time linear equalizer, a feedforward equalizer and the feedback decision equalizer structure of claim 8.
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| CN115865583A (en) * | 2015-10-15 | 2023-03-28 | 拉姆伯斯公司 | PAM-4DFE architecture with symbol-conversion dependent DFE tap values |
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