CN116260692A - Algorithm, system and processor readable medium for blind capture of data frames based on OFDM signals - Google Patents
Algorithm, system and processor readable medium for blind capture of data frames based on OFDM signals Download PDFInfo
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- H—ELECTRICITY
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- H04L27/00—Modulated-carrier systems
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- H—ELECTRICITY
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Abstract
The invention discloses an algorithm, a system and a processor readable medium for blind capturing of data frames based on OFDM signals. The algorithm obtains approximate components of the signal time domain power envelope by wavelet transformation, then calculates differential values of the approximate components of the signal power envelope, and finds out the maximum value and the minimum value of the differential values to serve as a frame starting position and a frame ending position. Compared with the traditional frame detection algorithm, the algorithm does not depend on a specific frame synchronization structure, and can achieve satisfactory effect in signal detection of non-cooperative communication. In addition, compared with a frame detection algorithm based on a power sliding window, the detection success rate of the proposed algorithm is obviously improved. Simulations show that the algorithm can accurately estimate the start and end positions of an OFDM signal frame at low signal-to-noise ratios.
Description
Technical Field
The present invention relates to the field of signal processing technologies, and in particular, to an algorithm, a system, and a processor readable medium for frame capture in an OFDM signal parameter blind estimation process.
Background
Currently in the field of frame synchronization algorithms, many researchers have proposed correlation algorithms based on OFDM (Orthogonal Frequency Division Multiplexing ) systems. Classical SC algorithms were proposed by Schmidl and Cox in 1997 as precursors for frame detection using autocorrelation. Researchers such as Park do various forms of preamble improvement on the SC algorithm, and meanwhile, other forms are adopted for correlation, and the greatest disadvantage of the correlation algorithm is that the influence of frequency offset is larger, and the frame detection difficulty is large for uncooperative communication.
The frame detection algorithm of the signal energy of the sliding window is also utilized, the algorithm utilizes the characteristic of larger energy value of the packet data, the information received by the receiver is subjected to autocorrelation operation, the signal energy value is obtained, the correlation of the noise signal is poorer, the energy value is smaller, and the energy value of the packet data is larger, so that the detection can be carried out according to the change of the energy value of the received signal. In this way, the decision threshold is difficult to select, and depends on the magnitude of the signal energy, which is related to the power of the transmitter, and the uncertainty factor affecting the energy change is more, and if the packet data energy is smaller, the frame detection effect is worse.
Disclosure of Invention
In order to solve the problems, the application provides an algorithm based on the blind capturing of the OFDM signal data frames aiming at the defects of a classical frame synchronization correlation algorithm and an energy detection algorithm based on a sliding window. The algorithm obtains approximate components of the signal time domain power envelope by wavelet transformation, and finds the maximum value and the minimum value of the differential values by calculating the differential values of the approximate components of the signal power envelope, and takes the maximum value and the minimum value as the initial position and the final position of the frame. The algorithm improves the accuracy of the detection.
The technical scheme adopted in the application for achieving the purpose is as follows:
a system for wavelet decomposition based OFDM frame detection, comprising:
the signal acquisition module is used for acquiring a data signal to be detected;
the filtering module is used for performing smoothing filtering processing on the acquired detection data;
a data processing module for calculating a differential value of an approximate component of the signal power envelope and outputting a maximum value and a minimum value of the differential value,
and the marking module is used for taking the maximum value and the minimum value as the frame starting position and the frame ending position.
Preferably, the data processing module obtains an approximate component of the signal time domain power envelope using wavelet transformation, then calculates a differential value of the approximate component of the signal power envelope based on the approximate component, and outputs a maximum value and a minimum value of the differential value.
An algorithm for blind capturing of data frames based on OFDM signals comprises the following steps:
calculating the power spectrum of the signal x (n) received by the receiver, selecting the appropriate smoothing coefficient τ smooth The signal is smoothed in order to reduce noise effects.
Continuous wavelet transformation of signal by using OFDM power spectrum of signal after noise reduction treatment
And reconstruct the OFDM signal with the approximation coefficients. />
Wherein a, tau e R, a is a telescopic variable, tau is a translational variable,
the wavelet mother function selects haar wavelet, which is defined as: />
Calculating differential values r (k, k+1) =d (k+1) -d (k) (k=1, 2,..once., N-1) among points of the signal by using the obtained signal time domain power envelope, normalizing the obtained differential values, calculating a differential mean value at the same time, differentiating each differential value from the mean value to obtain a maximum value and a minimum value, and if the difference between the maximum value and the minimum value and the mean value is greater than a certain threshold value, considering that frame data is detected, and taking the maximum value and the minimum value as a starting position and an ending position of a data frame respectively. The algorithm does not need to rely on a specific frame synchronization head, so that the algorithm can still obtain higher precision on the premise of not knowing the frame structure of the signal.
Advantageous effects
Relative to the scheme in the prior art, the advantage of this application: the method for blind detection of the signal data frames by utilizing wavelet transformation is provided. The algorithm has the advantages that the algorithm does not need to rely on a specific frame synchronization head, is insensitive to frequency deviation, and can still obtain a satisfactory effect on the premise of not knowing the signal frame structure. Secondly, compared with a frame detection algorithm utilizing the signal energy of the sliding window, the detection success rate of the algorithm under the condition of low signal-to-noise ratio under the action of wavelet transformation is obviously higher than that of a detection algorithm based on the power sliding window.
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For a clearer description of embodiments of the present description or of solutions in the prior art, the drawings that are required to be used in the description of the embodiments or of the prior art will be briefly described, it being apparent that the drawings in the description below are only some of the embodiments described in the description, from which, without inventive faculty, other drawings can also be obtained for a person skilled in the art:
fig. 1 is a flowchart of an OFDM signal data frame blind acquisition algorithm according to an embodiment of the present invention;
fig. 2 is a graph showing the frame recognition success rate of the OFDM signal data frame blind capturing algorithm and the frame capturing algorithm based on signal energy under different signal to noise ratios according to the embodiment of the present invention.
Fig. 3 is a graph of mean square error comparison between an OFDM signal data frame blind capture algorithm and a signal energy based frame capture algorithm under different signal to noise ratios according to an embodiment of the present invention.
Detailed Description
The above-described aspects are further described below in conjunction with specific embodiments. It should be understood that these examples are illustrative of the present application and are not limiting the scope of the present application. The implementation conditions used in the examples may be further adjusted according to the conditions of the specific manufacturer, and the implementation conditions not specified are generally those in routine experiments. Numerous specific details are set forth in the following detailed description in order to provide a better understanding of the present disclosure. It will be understood by those skilled in the art that the present disclosure may be practiced without some of these specific details.
The application provides a system for OFDM frame detection based on wavelet decomposition. The system comprises:
a signal acquisition module for acquiring a data signal (signal x (n)) to be detected;
a filtering module for smoothing the acquired detection data (i.e. filtering the signal),
the data processing module obtains the approximate component of the signal time domain power envelope by utilizing wavelet transformation, then calculates the differential value of the approximate component of the signal power envelope according to the approximate component of the signal time domain power envelope, and outputs the maximum value and the minimum value of the differential value,
and the marking module is used for taking the maximum value and the minimum value as the frame starting position and the frame ending position. The system does not depend on a specific frame synchronization structure, and can obtain satisfactory effect in signal detection of non-cooperative communication.
The invention provides an OFDM frame detection algorithm based on wavelet decomposition. The algorithm obtains approximate components of the signal time domain power envelope by wavelet transformation, calculates differential values of the approximate components of the signal power envelope according to the approximate components, and finds the maximum value and the minimum value of the differential values to serve as a frame starting position and a frame ending position. Compared with the traditional frame detection algorithm, the algorithm does not depend on a specific frame synchronization structure, and can achieve satisfactory effect in signal detection of non-cooperative communication. In addition, compared with a signal frame detection algorithm based on a power sliding window, the detection success rate of the algorithm is obviously improved. Simulations show that the algorithm can accurately estimate the start and end positions of an OFDM signal frame at low signal-to-noise ratios,
the algorithm based on the blind capture of the OFDM signal data frame proposed in the present application is described next with reference to the accompanying drawings.
The flow of this algorithm is shown in figure 1.
The flow of the algorithm comprises the following steps:
smoothing, obtaining and smoothing the detected data (signal x (n)), the process comprising calculating the power spectrum of the signal x (n) received by the receiver, selecting the appropriate smoothing coefficient τ smooth The signal is smoothed. This stepIs aimed at reducing noise effects.
The reconstruction of the signal power waveform, namely, the OFDM power spectrum of the signal after noise reduction treatment is used for continuous wavelet transformation of the signal,
and reconstruct the OFDM signal with the approximation coefficients.
Wherein a, τ e R, a is a telescoping variable, τ is a translation variable, and R is a real number.
The wavelet mother function selects the haar wavelet,
the definition formula is:
calculating a power waveform difference, calculating a difference value r (k, k+1) =d (k+1) -d (k) (k=1, 2..the., N-1) between each point of the signal by using the reconstructed signal power waveform, and normalizing the obtained difference value.
Obtaining the maximum value and the minimum value of the difference result, wherein the step comprises the steps of calculating a difference average value, and obtaining the maximum value and the minimum value by making difference between each difference value and the average value. If the difference between the maximum value and the minimum value and the average value is greater than a certain threshold value, the frame data is considered to be detected, and the maximum value and the minimum value are respectively used as the starting position and the ending position of the data frame. The algorithm does not depend on a specific frame synchronization structure, and can achieve satisfactory effect in signal detection of non-cooperative communication.
The algorithm based on the blind capture of the OFDM signal data frames, which is proposed by the application, is verified through simulation.
Experimental conditions: the success rate of the frame capturing algorithm based on wavelet transformation provided by the application and the success rate of the OFDM signal frame capturing under different signal-to-noise ratio conditions of other schemes are compared through a computer experiment (such as MATLAB based method).
In the simulation, the number of subcarriers is 1024, the cyclic prefix length is 32, the number of OFDM symbols is 100, the sampling rate is 60e6, the modulation mode adopts 16QAM, the signal-to-noise ratio SNR is in the range of-16 dB to 16dB, the signal delay of 1 microsecond is added on the signal, 100 Monte Carlo simulation is adopted, the delay point number of the signal is set as the threshold value of frame detection, and the frame identification is judged to be successful in the range of the delay point number which is larger than the threshold value and 20 microseconds. From the above conditions, a comparison graph of success rates of the wavelet transform-based frame capture and the signal energy-based frame capture algorithms is shown in fig. 2, and a comparison graph of mean square errors of the two frame capture algorithms is shown in fig. 3.
As can be seen from fig. 2, the present algorithm can also maintain a higher frame recognition success rate under a low signal-to-noise ratio, and is particularly shown in that the present algorithm can achieve a frame capture success rate of more than 80% when the signal-to-noise ratio is about-5 dB, and the frame capture success rate of the frame capture algorithm based on signal energy is almost 0% at this time, which proves that the frame recognition performance of the present algorithm is higher than that of the frame capture algorithm based on signal energy.
As can be seen from fig. 3, the mean square error of the present algorithm at a low signal-to-noise ratio is significantly smaller than that of the frame capturing algorithm based on signal energy, and is particularly shown in comparison with the frame capturing algorithm based on signal energy, the mean square error of the present algorithm is kept in a low order of magnitude when the signal-to-noise ratio is about-6 dB, which proves that the present algorithm also has higher frame capturing accuracy.
The invention also provides a processor readable medium comprising a computer program running the algorithm described above.
Those of ordinary skill in the art will appreciate that: all or part of the steps for implementing the method embodiments described above may be performed by hardware associated with program instructions. The foregoing program may be stored in a computer (processor) readable storage medium. The program, when executed, performs steps including the method embodiments described above; and the aforementioned storage medium includes: various media that can store program code, such as ROM, RAM, magnetic or optical disks.
The foregoing embodiments are provided to illustrate the technical concept and algorithm steps of the present application and are intended to enable those skilled in the art to understand the contents of the present application and implement the same according to the contents, and are not intended to limit the scope of the present application. All changes and modifications that come within the meaning and range of equivalency of the claims are to be embraced within their scope.
Claims (9)
1. A system for wavelet decomposition based OFDM frame detection comprising:
the signal acquisition module is used for acquiring a data signal to be detected;
the filtering module is used for performing smoothing filtering processing on the acquired detection data;
a data processing module for calculating a differential value of an approximate component of the signal power envelope and outputting a maximum value and a minimum value of the differential value,
and the marking module is used for taking the maximum value and the minimum value as the frame starting position and the frame ending position.
2. The system for wavelet decomposition-based OFDM frame detection of claim 1,
the data processing module obtains approximate components of the signal time domain power envelope by wavelet transformation, calculates differential values of the approximate components of the signal power envelope according to the approximate components, and outputs maximum values and minimum values of the differential values.
3. An algorithm for blind acquisition of data frames based on an OFDM signal, comprising:
reconstructing the signal power waveform by wavelet transformation to obtain an approximate component of the signal time domain power envelope,
a differential value of the time domain power approximation component of the signal is calculated,
and finding out the maximum value and the minimum value of the differential value, and taking the maximum value and the minimum value as a frame starting position and a frame ending position.
4. An OFDM signal data frame based blind acquisition algorithm as claimed in claim 3, wherein,
continuous wavelet transformation of signal by using OFDM power spectrum of signal after noise reduction treatment
And reconstruct the OFDM signal with the approximation coefficients,
wherein a, tau e R, a is a telescopic variable, tau is a translational variable,
5. the algorithm for blind acquisition of data frames based on an OFDM signal as claimed in claim 4, wherein,
the mother function of the wavelet transform is chosen as the haar wavelet, which is defined as:
6. the algorithm for blind acquisition of data frames based on an OFDM signal according to claim 4, further comprising:
calculating a difference value r (k, k+1) =d (k+1) -d (k) (k=1, 2,..,
and carrying out normalization processing on the obtained differential values, calculating a differential average value at the same time, and carrying out difference between each differential value and the average value to obtain a maximum value and a minimum value.
7. The algorithm for blind acquisition of data frames based on an OFDM signal as claimed in claim 6, wherein,
if the difference between the maximum value and the minimum value and the average value is larger than a preset threshold value, the frame data is considered to be detected, and the maximum value and the minimum value are respectively used as the starting position and the ending position of the data frame.
8. An OFDM signal data frame based blind acquisition algorithm according to claim 3, further comprising:
calculating the power spectrum of the received signal x (n) and selecting the smoothing coefficient tau corresponding to the match smooth The signal is smoothed.
9. A processor readable medium having stored thereon a computer program, characterized in that the computer storage medium comprises a computer program running an algorithm according to any of claims 3-8.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117411757A (en) * | 2023-12-13 | 2024-01-16 | 成都国恒空间技术工程股份有限公司 | Frame header capturing method of OFDM (orthogonal frequency division multiplexing) system |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117411757A (en) * | 2023-12-13 | 2024-01-16 | 成都国恒空间技术工程股份有限公司 | Frame header capturing method of OFDM (orthogonal frequency division multiplexing) system |
| CN117411757B (en) * | 2023-12-13 | 2024-02-23 | 成都国恒空间技术工程股份有限公司 | Frame header capturing method of OFDM (orthogonal frequency division multiplexing) system |
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