CN115801518B - Frequency offset estimation method and device based on probability distribution statistics and computer equipment - Google Patents
Frequency offset estimation method and device based on probability distribution statistics and computer equipment Download PDFInfo
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Abstract
The application relates to a frequency offset estimation method, a device and computer equipment based on probability distribution statistics. The method comprises the following steps: receiving a communication signal, and obtaining the frequency phase difference of each sampling point in the communication signal by carrying out sliding autocorrelation calculation on the communication signal; selecting a frequency phase difference of a preset sampling point from the communication signal, and performing cyclic mean square error calculation to obtain root mean square values of all cyclic calculation moments; the method comprises the steps of visually displaying sampling curves corresponding to root mean square values at each cycle calculation moment, and confirming abnormal sampling points in the sampling curves; the confidence coefficient of the sampling curve is adjusted so that the abnormal sampling points are outside the confidence coefficient interval, and the abnormal sampling points are removed; and carrying out sliding autocorrelation calculation on the communication signals with abnormal sampling points removed, and outputting a frequency offset value. By adopting the method, the frequency offset estimation in the severe environment can be realized.
Description
Technical Field
The present disclosure relates to the field of wireless communications technologies, and in particular, to a method and an apparatus for estimating frequency offset based on probability distribution statistics, and a computer device.
Background
In wireless communication, the most classical frequency error estimation method is to obtain the phase difference of all samples of the training sequence based on the autocorrelation of the repeated training sequence or the correlation operation with the local sequence, and finally to average the phase difference to eliminate noise and obtain the frequency error of the signal.
However, in actual wireless communication, the frequency is unstable due to the problems of radio station heating, unstable crystal oscillator and the like, so that the frequency offset of a receiving end of a wireless communication system to a channel is inaccurate.
Disclosure of Invention
Based on the foregoing, it is necessary to provide a method, an apparatus and a computer device for estimating frequency offset based on probability distribution statistics.
A method of frequency offset estimation based on probability distribution statistics, the method comprising:
receiving a communication signal, and obtaining a frequency phase difference of each sampling point in the communication signal by carrying out sliding autocorrelation calculation on the communication signal;
selecting a frequency phase difference of a preset sampling point from the communication signal, and performing cyclic mean square error calculation to obtain root mean square values of all cyclic calculation moments;
visually displaying a sampling curve corresponding to the root mean square value at each cycle calculation moment, and confirming abnormal sampling points in the sampling curve;
the confidence coefficient of the sampling curve is adjusted so that the abnormal sampling points are outside the confidence coefficient interval, and abnormal sampling points are removed;
and carrying out sliding autocorrelation calculation on the communication signals with abnormal sampling points removed, and outputting a frequency offset value.
In one embodiment, sliding autocorrelation calculation is performed on the communication signal with the abnormal sampling points removed, average value calculation is performed to obtain a frequency phase difference average value, and the frequency phase difference average value is output as a frequency offset value.
A probability distribution statistics-based frequency offset estimation device, comprising:
the phase difference calculation module is used for receiving a communication signal and obtaining the frequency phase difference of each sampling point in the communication signal by carrying out sliding autocorrelation calculation on the communication signal;
the root mean square calculation module is used for selecting a frequency phase difference of a preset sampling point from the communication signal, and carrying out cyclic mean square error calculation to obtain root mean square values of all cyclic calculation moments;
the abnormal point removing module is used for visually displaying sampling curves corresponding to root mean square values at each cycle calculation moment and confirming abnormal sampling points in the sampling curves; the confidence coefficient of the sampling curve is adjusted so that the abnormal sampling points are outside the confidence coefficient interval, and abnormal sampling points are removed;
and the frequency offset estimation module is used for carrying out sliding autocorrelation calculation on the communication signals with the abnormal sampling points removed and outputting frequency offset values.
In one embodiment, the frequency offset estimation module is further configured to perform sliding autocorrelation calculation on the communication signal with the abnormal sampling points removed, perform average calculation, obtain a frequency phase difference average value, and output the frequency phase difference average value as a frequency offset value.
A computer device comprising a memory storing a computer program and a processor which when executing the computer program performs the steps of:
receiving a communication signal, and obtaining a frequency phase difference of each sampling point in the communication signal by carrying out sliding autocorrelation calculation on the communication signal;
selecting a frequency phase difference of a preset sampling point from the communication signal, and performing cyclic mean square error calculation to obtain root mean square values of all cyclic calculation moments;
visually displaying a sampling curve corresponding to the root mean square value at each cycle calculation moment, and confirming abnormal sampling points in the sampling curve;
the confidence coefficient of the sampling curve is adjusted so that the abnormal sampling points are outside the confidence coefficient interval, and abnormal sampling points are removed;
and carrying out sliding autocorrelation calculation on the communication signals with abnormal sampling points removed, and outputting a frequency offset value.
A computer readable storage medium having stored thereon a computer program which when executed by a processor performs the steps of:
receiving a communication signal, and obtaining a frequency phase difference of each sampling point in the communication signal by carrying out sliding autocorrelation calculation on the communication signal;
selecting a frequency phase difference of a preset sampling point from the communication signal, and performing cyclic mean square error calculation to obtain root mean square values of all cyclic calculation moments;
visually displaying a sampling curve corresponding to the root mean square value at each cycle calculation moment, and confirming abnormal sampling points in the sampling curve;
the confidence coefficient of the sampling curve is adjusted so that the abnormal sampling points are outside the confidence coefficient interval, and abnormal sampling points are removed;
and carrying out sliding autocorrelation calculation on the communication signals with abnormal sampling points removed, and outputting a frequency offset value.
In order to solve the unstable condition of a system, after the frequency phase difference is calculated, the root mean square value of the frequency phase difference is calculated, abnormal points can be confirmed from probability distribution through visual display of a sampling curve corresponding to the root mean square value, so that the abnormal points are removed, and the accurate frequency offset value is calculated again. The method is suitable for an unstable system and realizes frequency offset value estimation in a severe environment.
Drawings
FIG. 1 is a diagram showing a correlation calculation in the prior art;
fig. 2 is a flow chart of a method for estimating frequency offset based on probability distribution statistics in one embodiment;
FIG. 3 is a schematic diagram of a stabilization system in one embodiment;
FIG. 4 is a schematic illustration of an ongoing distribution curve in one embodiment;
FIG. 5 is a schematic diagram of an unstable system in one embodiment;
FIG. 6 is a block diagram of an apparatus for estimating frequency offset based on probability distribution statistics in one embodiment;
fig. 7 is an internal structural diagram of a computer device in one embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application will be further described in detail with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the present application.
In the conventional art, such as Error-! Reference source not the training sequence is a 16-point cycle (only 4 points are schematically shown in fig. 1), the frequency estimation is performed by a point a and a point a after 16 points are delayed, and when the system transmission has a frequency offset, the correlation between the point a and the point a after 16 points is delayed, and there is a phase difference.
The phase difference calculated by the correlation value between each point and the repetition point after 16 points is recorded as delta F, and the existing frequency estimation algorithm averages the correlation values of a plurality of repeated sequences to finally obtain a relatively stable frequency error. Namely:
the method for estimating the frequency and the phase difference based on the average value algorithm probably has little problem when the system frequency deviation is stable, but when the system frequency deviation is unstable, the average can introduce larger error.
In the system with stable frequency offset, the phase difference of continuous repeated points is a stable arithmetic series, so that the phase difference of continuous sample points can be averaged to obtain the real average frequency phase difference of the whole sequence.
When the error frequency is unstable, the frequency error of the samples will not be a more concentrated and stable arithmetic series, but some samples will have a severe calculated frequency error offset. This results in a significant problem with the frequency error eventually calculated by averaging, which results in too large a deviation of the frequency error estimate.
In one embodiment, as shown in fig. 1, a frequency offset estimation method based on probability distribution statistics is provided, which includes the following steps:
step 102, receiving the communication signal, and obtaining the frequency phase difference of each sampling point in the communication signal by performing sliding autocorrelation calculation on the communication signal.
Step 104, selecting the frequency phase difference of the preset sampling point from the communication signal, and performing the cyclic mean square error calculation to obtain the root mean square value of each cyclic calculation moment.
And 106, visually displaying the sampling curve corresponding to the root mean square value at each cycle calculation time, and confirming abnormal sampling points in the sampling curve.
And step 108, adjusting the confidence coefficient of the sampling curve to enable the abnormal sampling points to be outside the confidence coefficient interval so as to eliminate the abnormal sampling points.
And 110, performing sliding autocorrelation calculation on the communication signals with abnormal sampling points removed, and outputting a frequency offset value.
According to the frequency offset estimation method based on probability distribution statistics, in order to solve the unstable condition of the system, after the frequency phase difference is calculated, the root mean square value of the frequency phase difference is calculated, through the visual display of the root mean square value corresponding to the sampling curve, abnormal points can be confirmed from probability distribution, so that the abnormal points are removed, and the accurate frequency offset value is calculated again. The method is suitable for an unstable system and realizes frequency offset value estimation in a severe environment.
It should be noted that the present invention can solve the above problem, because when the system frequency offset is unstable, the distribution of the frequency offset values of the multiple points is greatly different from the normal distribution under the condition of standard gaussian noise, that is, the deviation of the individual points is particularly serious, so that the calculation deviation of the average value is caused.
In one embodiment, the sliding autocorrelation calculation is performed on the communication signal with the abnormal sampling points removed, the average value calculation is performed, the frequency phase difference average value is obtained, and the frequency phase difference average value is output as the frequency offset value.
Specifically, as shown in fig. 3, in the stable system, the root mean square value of the phase difference is relatively stable and hardly changed, and in the normal distribution analysis, the root mean distribution of the phase difference is concentrated near the mean value, and as shown in fig. 4, the normal mean value is concentrated in the middle part of the probability distribution curve.
As shown in fig. 5, in the unstable system, the root mean square distribution of the phase difference deviates from the central probability region of the mean, and as shown in fig. 4, the confidence interval can be adjusted to 80%, 70% or the like by adjusting the probability confidence interval of the normal distribution (for example, the confidence interval is generally 95%), and the points outside the confidence interval are removed.
It should be understood that, although the steps in the flowchart of fig. 2 are shown in sequence as indicated by the arrows, the steps are not necessarily performed in sequence as indicated by the arrows. The steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders. Moreover, at least some of the steps in fig. 2 may include multiple sub-steps or stages that are not necessarily performed at the same time, but may be performed at different times, nor do the order in which the sub-steps or stages are performed necessarily performed in sequence, but may be performed alternately or alternately with at least a portion of the sub-steps or stages of other steps or other steps.
In one embodiment, as shown in fig. 6, there is provided a frequency offset estimation device based on probability distribution statistics, including: a phase difference calculation module 602, a root mean square calculation module 604, an outlier rejection module 606, and a frequency offset estimation module 608, wherein:
the phase difference calculation module 602 is configured to receive a communication signal, and obtain a frequency phase difference of each sampling point in the communication signal by performing sliding autocorrelation calculation on the communication signal;
the root mean square calculation module 604 is configured to select a frequency phase difference of a predetermined sampling point from the communication signal, perform a cyclic mean square error calculation, and obtain a root mean square value at each cyclic calculation time;
the abnormal point removing module 606 is configured to visually display a sampling curve corresponding to a root mean square value at each cycle calculation time, and confirm an abnormal sampling point in the sampling curve; the confidence coefficient of the sampling curve is adjusted so that the abnormal sampling points are outside the confidence coefficient interval, and abnormal sampling points are removed;
the frequency offset estimation module 608 is configured to perform sliding autocorrelation calculation on the communication signal from which the abnormal sampling point is removed, and output a frequency offset value.
In one embodiment, the frequency offset estimation module 608 is further configured to perform sliding autocorrelation calculation on the communication signal with the abnormal sampling points removed, perform average calculation, obtain a frequency phase difference average value, and output the frequency phase difference average value as a frequency offset value.
For specific limitations of the frequency offset estimation device based on probability distribution statistics, reference may be made to the above limitation of the frequency offset estimation method based on probability distribution statistics, which is not described herein. All or part of the modules in the frequency offset estimation device based on the probability distribution statistics can be realized by software, hardware and a combination thereof. The above modules may be embedded in hardware or may be independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above modules.
In one embodiment, a computer device is provided, which may be a terminal, and the internal structure of which may be as shown in fig. 7. The computer device includes a processor, a memory, a network interface, a display screen, and an input device connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program, when executed by a processor, implements a method for estimating frequency offset based on probability distribution statistics. The display screen of the computer equipment can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer equipment can be a touch layer covered on the display screen, can also be keys, a track ball or a touch pad arranged on the shell of the computer equipment, and can also be an external keyboard, a touch pad or a mouse and the like.
It will be appreciated by those skilled in the art that the structure shown in fig. 7 is merely a block diagram of some of the structures associated with the present application and is not limiting of the computer device to which the present application may be applied, and that a particular computer device may include more or fewer components than shown, or may combine certain components, or have a different arrangement of components.
In an embodiment a computer device is provided comprising a memory storing a computer program and a processor implementing the steps of the method of the above embodiments when the computer program is executed.
In one embodiment, a computer readable storage medium is provided, on which a computer program is stored which, when executed by a processor, implements the steps of the method of the above embodiments.
Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in the various embodiments provided herein may include non-volatile and/or volatile memory. The nonvolatile memory can include Read Only Memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double Data Rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous Link DRAM (SLDRAM), memory bus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), among others.
The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.
The above examples merely represent a few embodiments of the present application, which are described in more detail and are not to be construed as limiting the scope of the invention. It should be noted that it would be apparent to those skilled in the art that various modifications and improvements could be made without departing from the spirit of the present application, which would be within the scope of the present application. Accordingly, the scope of protection of the present application is to be determined by the claims appended hereto.
Claims (6)
1. A method for estimating frequency offset based on probability distribution statistics, the method comprising:
receiving a communication signal, and obtaining a frequency phase difference of each sampling point in the communication signal by carrying out sliding autocorrelation calculation on the communication signal;
selecting a frequency phase difference of a preset sampling point from the communication signal, and performing cyclic mean square error calculation to obtain root mean square values of all cyclic calculation moments;
visually displaying a sampling curve corresponding to the root mean square value at each cycle calculation moment, and confirming abnormal sampling points in the sampling curve;
the confidence coefficient of the sampling curve is adjusted so that the abnormal sampling points are outside the confidence coefficient interval, and abnormal sampling points are removed;
and carrying out sliding autocorrelation calculation on the communication signals with abnormal sampling points removed, and outputting a frequency offset value.
2. The method for estimating frequency offset based on probability distribution statistics according to claim 1, wherein the sliding autocorrelation calculation is performed on the communication signal from which the abnormal sampling points are removed, and the output frequency offset value comprises:
and carrying out sliding autocorrelation calculation on the communication signals with abnormal sampling points removed, carrying out average value calculation to obtain a frequency phase difference average value, and outputting the frequency phase difference average value as a frequency offset value.
3. A probability distribution statistics-based frequency offset estimation device, comprising:
the phase difference calculation module is used for receiving a communication signal and obtaining the frequency phase difference of each sampling point in the communication signal by carrying out sliding autocorrelation calculation on the communication signal;
the root mean square calculation module is used for selecting a frequency phase difference of a preset sampling point from the communication signal, and carrying out cyclic mean square error calculation to obtain root mean square values of all cyclic calculation moments;
the abnormal point removing module is used for visually displaying sampling curves corresponding to root mean square values at each cycle calculation moment and confirming abnormal sampling points in the sampling curves; the confidence coefficient of the sampling curve is adjusted so that the abnormal sampling points are outside the confidence coefficient interval, and abnormal sampling points are removed;
and the frequency offset estimation module is used for carrying out sliding autocorrelation calculation on the communication signals with the abnormal sampling points removed and outputting frequency offset values.
4. The apparatus of claim 3 wherein the frequency offset estimation module is further configured to perform sliding autocorrelation calculation on the communication signal with the abnormal sampling points removed, perform average calculation to obtain a frequency phase difference average value, and output the frequency phase difference average value as a frequency offset value.
5. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor implements the steps of the method of claim 1 or 2 when executing the computer program.
6. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method of claim 1 or 2.
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