CN114374587B - Channel time domain equalization method based on frame - Google Patents
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- CN114374587B CN114374587B CN202210053371.0A CN202210053371A CN114374587B CN 114374587 B CN114374587 B CN 114374587B CN 202210053371 A CN202210053371 A CN 202210053371A CN 114374587 B CN114374587 B CN 114374587B
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L25/00—Baseband systems
- H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
- H04L25/03—Shaping networks in transmitter or receiver, e.g. adaptive shaping networks
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- H04L25/03012—Arrangements for removing intersymbol interference operating in the time domain
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L25/00—Baseband systems
- H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
- H04L25/03—Shaping networks in transmitter or receiver, e.g. adaptive shaping networks
- H04L25/03006—Arrangements for removing intersymbol interference
- H04L25/03178—Arrangements involving sequence estimation techniques
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L25/00—Baseband systems
- H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
- H04L25/03—Shaping networks in transmitter or receiver, e.g. adaptive shaping networks
- H04L25/03006—Arrangements for removing intersymbol interference
- H04L2025/03592—Adaptation methods
- H04L2025/03598—Algorithms
- H04L2025/03611—Iterative algorithms
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Abstract
The invention belongs to the technical field of communication, and particularly relates to a channel time domain equalization method based on a frame. A method for time domain equalization of a frame-based channel, comprising: and performing error calculation on the output signal obtained by the equalizer, respectively obtaining a first error and a second error in a preset period, and performing error iterative updating on the equalizer alternately in the period of the first error and the second error. The invention utilizes all effective information to realize the uninterrupted tracking of the equalizer and greatly improve the capture rate.
Description
Technical Field
The invention belongs to the technical field of communication, and particularly relates to a channel time domain equalization method based on a frame.
Background
Theoretically, the best transmission can be achieved if the transmission system of the communication system meets the Nequist criterion and the "conjugate match" criterion. However, in an actual system, due to the irrational characteristics of the channel, various noises, interferences, frequency selective fading, band-limited transmission, etc., cause the receiving end to generate inter-symbol interference (ISI) or inter-symbol interference (ISI), which hinders high-speed communication, and therefore, a corresponding measure needs to be taken in the receiver to eliminate or mitigate the interference. Equalization is a method of removing intersymbol interference, which removes intersymbol interference by compensating for distortion of a channel.
Equalization can be divided into frequency domain equalization and time domain equalization. Frequency domain equalization usually needs to correct amplitude-frequency characteristics and group delay characteristics respectively, has weak capability of compensating group delay distortion, and especially cannot compensate non-minimum phase fading generally, so that frequency domain equalization is not adopted in a digital transmission system, and time domain equalization is adopted. The time domain equalization is a condition that, in consideration of the time domain impulse response, the impulse response of the entire system including the equalizer satisfies the condition of no intersymbol interference. The time domain equalizer compensates the distorted signal waveform by using the response generated by the time domain equalizer, and finally, the time domain equalizer can effectively eliminate the interference between symbol symbols, thereby being widely applied to many fields of digital communication.
In order to track channel variation quickly, an adaptive time domain equalization method is generally used, and whether a training sequence is used can be divided into adaptive equalization and adaptive blind equalization. Self-adaptive equalization, using training sequence, in the course of channel propagation, the delay of transmission can be caused by its insertion, reducing transmission rate of effective data in communication and increasing complexity of system; adaptive blind equalization does not use a training sequence and does not affect the transmission rate of effective data, but for high-order QAM modulation, misjudgment of symbol symbols can be more serious when an equalizer is not locked.
In the prior art, a decision feedback equalizer, a feedforward equalizer, a feedback equalizer, and a feedback equalizer are usually adopted, and are locked quickly, and the feedback equalizer is maintained accurately, for example, in patents CN101567863 and CN1647425. However, in patent CN101567863, since the frame header PN sequence is used for channel estimation and decision feedback equalizer, it has the disadvantages of long equalizer locking time, complex structure and large resource consumption. Patent CN1647425 adopts automatic mode switching and decision feedback equalizer, which has the disadvantages of slow convergence speed of equalizer, weak capability of tracking channel variation, complex implementation process and large resource consumption.
Disclosure of Invention
The invention aims to solve the technical problems that self-adaptive equalization and self-adaptive blind equalization have defects in the using process and provides a channel time domain equalization method based on a frame.
A method for time domain equalization of a frame-based channel, comprising:
and performing error calculation on the output signal obtained by the equalizer, respectively obtaining a first error and a second error in a preset period, and alternately performing error iterative update on the equalizer by using the first error and the second error in the period.
Preferably, the output signal includes a plurality of data frame structures, and the data frame structure of each frame includes:
a frame header part, which is known sequence information and is used for frame synchronization;
a payload part located after the frame header part;
the first error is obtained by calculating a frame header part in the output signal through a preset adaptive equalization algorithm;
and the second error is obtained by calculating a load part in the output signal through a preset adaptive blind equalization algorithm.
Preferably, the known sequence information is a special sequence with autocorrelation.
Preferably, the known sequence information is one of a barker code sequence, an m-sequence or a gold-sequence.
Preferably, the output signal is initially obtained in the following manner:
constructing an Nf-order equalizer, wherein the number of the equalizer coefficients W is Nf +1, and initializing the equalizer;
the input signal x is processed by the equalizer to obtain an output signal
Namely that
Wherein (·) H The conjugate transpose process is shown.
Preferably, when the first error and the second error are alternately updated with the error iteration in the period, the method comprises the following steps:
selecting the first error or the second error by a timing switch that switches at the cycle;
and updating the coefficients of the equalizer in real time through a coefficient iterative updater.
Preferably, the adaptive equalization algorithm preferably uses an LMS (least mean square error) algorithm.
Preferably, the first error is calculated by:
let the output signal be
Wherein l 1 If the preset known sequence information is x _ knock for the length of the known sequence information in the output signal, obtaining the corresponding error
The error iteration updating mode of the equalizer is as follows:
W′＝W-μ*e 1 T *x
wherein W' is the equalizer coefficient after error iteration update, W is the equalizer coefficient before update, μ is convergence step length, (-) T Representing the transposition process and x the input signal.
Preferably, the adaptive blind equalization algorithm preferably uses DDLMS (decision-oriented minimum mean square error) algorithm.
Preferably, the second error is calculated by:
let the output signal be
Judging the output signal to obtain x _ d, and obtaining corresponding error
The error iteration updating mode of the equalizer is as follows:
W′＝W-μ*e 2 T *x
wherein W' is the equalizer coefficient after error iteration update, W is the equalizer coefficient before update, μ is the convergence step length, (·) T Representing the transposition process and x is the input signal.
The positive progress effects of the invention are as follows: compared with the traditional equalization method, the invention adopts the channel time domain equalization method based on the frame, and has the following remarkable advantages:
1. all effective information is utilized, the uninterrupted tracking of the equalizer is realized, and the capture rate is greatly improved;
2. the adaptive equalization method based on the frame header known sequence is combined with the adaptive blind equalization method based on the rest information of the frame, so that the time domain equalization of the channel is realized, the convergence speed of the equalizer is high, the channel change can be tracked quickly, and the equalization effect is good;
3. the adaptive process is supervised by using the standard information of the known sequence of the frame header;
4. only one equalizer is needed, so that the design complexity of the equalizer is greatly reduced, and the resource consumption of engineering implementation is reduced;
5. the design of the data frame structure and the equalizer order is suitable for the balance of any QAM modulated load signal, so that the method is suitable for high-order QAM modulated signals, and the equalizer has a good convergence effect.
Drawings
FIG. 1 is a diagram of a frame structure according to the present invention;
FIG. 2 is a diagram of another frame structure according to the present invention;
FIG. 3 is a block diagram of one implementation of time domain equalization of the present invention;
FIG. 4 is a constellation diagram before equalization obtained by multi-path equal channel simulation under 1024QAM modulation;
FIG. 5 is a graph of error convergence after adaptive equalization algorithm under 1024QAM modulation;
FIG. 6 is a constellation diagram after adaptive equalization algorithm under 1024QAM modulation;
FIG. 7 is a diagram of error convergence after 1024QAM modulation by the channel time domain equalization method of the present invention;
fig. 8 is a constellation diagram after the channel time domain equalization method of the present invention under 1024QAM modulation.
Detailed Description
In order to make the technical means, the creation characteristics, the achievement purposes and the effects of the invention easy to understand, the invention is further described with the specific drawings.
A channel time domain equalization method based on frame includes the following steps:
s1, performing error calculation on the output signal obtained by the equalizer, and respectively obtaining a first error and a second error in a preset period.
In one embodiment, the equalizer of the present invention preferably employs an FIR filter, the output signal is obtained by the equalizer from the input signal, and the output signal is initially obtained by:
an Nf-order equalizer is constructed, the number of equalizer coefficients W is Nf +1, the equalizer is initialized, and the equalizer coefficients W = [1,0, \ 8230;, 0, can be set initially]The initial input signal is x, and the output signal is obtained after the equalizer
Namely that
Wherein (·) H The conjugate transpose process is shown.
And after the equalizer is subjected to error iterative updating alternately according to the first error and the second error, the input signal is equalized by the updated equalizer in real time to obtain an output signal, and the new output signal is subjected to error calculation to update the equalizer so as to realize uninterrupted tracking of the equalizer.
In one embodiment, referring to fig. 1 and 2, the output signal of the present invention comprises a plurality of consecutive data frame structures, each comprising a frame header part SOF and a Payload part Payload. The frame header part SOF is known sequence information used for frame synchronization. Sequence information is known as a special sequence with autocorrelation. The known sequence information may be one of a barker sequence, an m-sequence, or a gold sequence. If the data of the preset known sequence information is assumed to be x _ knock, the known sequence information in the output signal may be the same as x _ knock or different from x _ knock due to interference during transmission, and an error e may be generated at this time 1 Error e of the 1 Can be used for updating the equalizer coefficient, and the x _ knock can be used as standard information for supervision of the adaptive process.
The Payload portion Payload comprises fixed symbols, the length of which varies with the QAM modulation order. Referring to fig. 2, code modulation information ACM may be further included between the frame header part SOF and the Payload part Payload, and the code modulation information ACM stores coding rate information or modulation information.
The frame header section SOF and the Payload section exhibit a periodic overlapping characteristic in time, which can be confirmed by slot segmentation. The SOF of the frame header part and the Payload part can also rapidly determine the position of the frame header part according to the autocorrelation of the known sequence information of the frame header part, so that the known sequence information is determined, and the rest data are other parts, and the specific mode is as follows:
in one embodiment, in a current data frame structure of the output signal, the position of known sequence information in the output signal is determined using autocorrelation of the known sequence information, the data symbol positions in the current data frame structure are labeled, and the length l of the known sequence information in the output signal is determined 1 (ii) a Mark number less than 1 The corresponding data in +1 is the frame head part; the reference number is greater than 1 The corresponding data is the other part including the payload part.
Specifically, each part of a frame structure may be labeled one by one, and the lengths of the three parts are respectively set to be l in fig. 2 1 ，l 2 And l 3 The symbol positions of a frame of data are labeled, i.e. 1, 2, 3, \ 8230;, l 1 、l 1 +1、…l 1 +l 2 、l 1 +l 2 +1、…、l 1 +l 2 +l 3 . Because the position of the known sequence information can be determined, and the length of the known sequence information can also be determined, the frame header part and other parts corresponding to the known sequence information can be distinguished according to the size of the label. I.e. when the index is less than l 1 +1, the corresponding data is the frame header part. When the index is greater than l 1 The corresponding data is the other part, such as the coded modulation information and payload part.
In one embodiment, the first error and the second error can be obtained in a form of periodic alternation when the error calculation is performed on the output type. The first error is calculated by a preset adaptive equalization algorithm on the frame header part in the output signal. And the second error is obtained by calculating the load part in the output signal through a preset adaptive blind equalization algorithm.
In one embodiment, the adaptive equalization algorithm preferably employs an LMS (least mean square error) algorithm. The first error is calculated as:
setting the output signal as
Wherein l 1 If the preset known sequence information is x _ knock, the corresponding error is obtained for the length of the known sequence information in the output signal
In one embodiment, the adaptive blind equalization algorithm preferably employs a DDLMS (decision-directed minimum mean square error) algorithm. The second error is calculated as:
let the output signal be
DD decision is performed on the output signal to obtain x _ d, and then corresponding error is obtained
And S2, alternately carrying out error iterative updating on the equalizer by the first error and the second error in a period.
In one embodiment, the first error or the second error is selected by a timing switch that is switched in cycles; the coefficients of the equalizer are updated in real time by a coefficient iteration updater.
In one embodiment, the manner of updating when iteratively updating the equalizer for errors is as follows.
And corresponding to the first error, performing error iteration updating on the equalizer in the following mode:
W′＝W-μ*e 1 T *x
wherein W' is the equalizer coefficient after the error iteration update, W is the equalizer coefficient before the update, mu is the convergence step length, (-) T Representing the transposition process, x being the input signal;
for the second error, the error iteration updating mode of the equalizer is as follows:
W′＝W-μ*e 2 T *x
wherein W' is the equalizer coefficient after the error iteration update, W is the equalizer coefficient before the update, mu is the convergence step length, (-) T Representing the transposition process, x being the input signal;
and the subsequent input signals adopt the updated equalizer coefficient W' to carry out adaptive equalization to obtain new output signals.
Embodiment one, refer to fig. 3:
the input signal is processed by the equalizer to obtain an output signal, the frame header part and the load part time slot are used for periodically switching to calculate a first error and a second error, the first error or the second error is selected through a time sequence switch which is periodically switched, the time sequence switch transmits the selected first error or the selected second error to a coefficient iteration updater, and the coefficient iteration updater carries out real-time error iteration updating on the equalizer. Wherein the first error is obtained by an adaptive equalization algorithm and the second error is obtained by an adaptive blind equalization algorithm. And the updated equalizer equalizes the input signal in real time to obtain a new output signal, and the new output signal continuously calculates a first error and a second error periodically and alternately to perform a new error iterative update.
The invention combines the self-adaptive equalization of the frame header part and the self-adaptive blind equalization of other parts including the load part by switching two equalization algorithms, can realize the training of the equalizer by utilizing the known sequence information to carry out the self-adaptive equalization, and then carries out the self-adaptive blind equalization by combining other information, thereby effectively improving the equalization convergence speed, being capable of quickly tracking the channel change, obtaining better equalization effect and being suitable for the equalization of load information modulated by any QAM. Therefore, the equalizing method of the invention effectively expands the application range and can be applied to high-order QAM modulation.
Example two, with reference to fig. 2:
under 1024QAM modulation, a constellation diagram before equalization obtained through multipath equal channel simulation is shown in fig. 4.
Under the same external conditions, if only the equalization method of the adaptive equalization (LMS) algorithm is applied, the error convergence diagram shown in fig. 5 and the constellation diagram after adaptive equalization (LMS) shown in fig. 6 are obtained under the condition of no switching. By adopting the switching condition of the invention, the adaptive equalization (LMS) of the frame header part and the adaptive blind equalization (DDLMS) of other parts including the load part are combined to obtain an error convergence diagram as shown in figure 7 and a constellation diagram after the adaptive equalization (LMS) and the adaptive blind equalization (DDLMS) as shown in figure 8.
Referring to fig. 5 and 6, when only adaptive equalization (LMS) is used, the known sequence information of the frame header part is used as a training sequence for equalization, and the equalizer can converge, but the equalization convergence effect is poor in the case that the channel time variation is severe.
Referring to fig. 7 and 8, the present invention combines adaptive mean square (LMS) and adaptive blind mean square (DDLMS) for channel equalization, and has a fast convergence rate, fast tracking of channel variation, and a good equalization convergence effect.
The foregoing shows and describes the general principles, essential features, and advantages of the invention. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, which are given by way of illustration of the principles of the present invention, but that various changes and modifications may be made without departing from the spirit and scope of the invention, and such changes and modifications are within the scope of the invention as claimed. The scope of the invention is defined by the appended claims and equivalents thereof.
Claims (9)
1. A method for time domain equalization of a channel based on a frame, comprising:
performing error calculation on an output signal obtained by an equalizer, respectively obtaining a first error and a second error in a preset period, and alternately performing error iterative update on the equalizer in the period by using the first error and the second error;
the output signal comprises a number of data frame structures, the data frame structure of each frame comprising:
a frame header part, which is known sequence information, for frame synchronization;
a payload part located after the frame header part;
the first error is obtained by calculating a frame header part in the output signal through a preset adaptive equalization algorithm;
and the second error is obtained by calculating a load part in the output signal through a preset adaptive blind equalization algorithm.
2. The method for time-domain equalization of a frame-based channel of claim 1 wherein the known sequence information is a special sequence with autocorrelation.
3. The method for time-domain equalization of a frame-based channel of claim 2 wherein said known sequence information employs one of a barker sequence, an m-sequence or a gold-sequence.
4. A method for time-domain equalization of a frame-based channel as defined in claim 1 wherein said output signal is initially obtained by:
constructing an Nf-order equalizer, initializing the equalizer if the number of the equalizer coefficients W is Nf + 1;
the input signal x is processed by the equalizer to obtain an output signal
Namely, it is
Wherein (·) H The conjugate transpose process is shown.
5. A frame-based channel time-domain equalization method according to any of claims 1-4, characterized in that when the equalizer is iteratively updated with errors alternating with said period using said first error and said second error:
selecting the first error or the second error by a timing switch that switches at the cycle;
and updating the coefficients of the equalizer in real time through a coefficient iterative updater.
6. A frame-based channel time-domain equalization method as claimed in claim 1 characterized in that said adaptive equalization algorithm employs the LMS algorithm.
7. The frame-based channel time-domain equalization method of claim 6 wherein said first error is calculated by:
let the output signal be
Wherein l 1 If the preset known sequence information is x _ knock for the length of the frame header part in the output signal, the corresponding error is obtained
The error iteration updating mode of the equalizer is as follows:
W′＝W-μ*e 1 T *x
wherein W' is the equalizer coefficient after error iteration update, W is the equalizer coefficient before update, μ is convergence step length, (-) T Representing the transposition process and x is the input signal.
8. The method for time domain equalization of a frame based channel as claimed in claim 1 wherein said adaptive blind equalization algorithm employs DDLMS algorithm.
9. The frame-based channel time-domain equalization method of claim 8 wherein said second error is calculated by:
let the output signal be
For the output messageThe number is judged to obtain x _ d, and then the corresponding error is obtained
The error iteration updating mode of the equalizer is as follows:
W′＝W-μ*e 2 T *x
wherein W' is the equalizer coefficient after error iteration update, W is the equalizer coefficient before update, μ is convergence step length, (-) T Representing the transposition process and x is the input signal.
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| JP2012070348A (en) * | 2010-09-21 | 2012-04-05 | Asano David | Information communication system having adaptive error prediction filter |
| CN102111360A (en) * | 2011-03-14 | 2011-06-29 | 中国人民解放军海军航空工程学院 | Algorithm for dynamically switching channel equalization based on real-time signal-to-noise ratio estimation |
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