CN116962123B - Raised cosine shaping filter bandwidth estimation method and system of software defined framework - Google Patents
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- H—ELECTRICITY
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Abstract
The application relates to a raised cosine shaping filter bandwidth estimation method and a raised cosine shaping filter bandwidth estimation system of a software definition framework. And then carrying out average filtering smoothing treatment on the obtained signal amplitude spectrum so as to smooth the amplitude-frequency response by utilizing the vertical axis value characteristic of the amplitude-frequency response and adding average filtering, further searching a frequency intermediate value point on an amplitude-frequency response curve obtained after the signal amplitude spectrum is subjected to smoothing treatment, and calculating by utilizing the frequency intermediate value point to obtain a relatively accurate bandwidth estimated value of the digital signal to be blindly identified.
Description
Technical Field
The application belongs to the technical field of communication transmission, and relates to a raised cosine shaping filter bandwidth estimation method and system of a software defined framework.
Background
The digital signal modulation recognition technology is a key technology in the field of communication signal reconnaissance, in the case of an unknown signal modulation mode, blind recognition of the signal modulation mode is a key step of blind demodulation of signals, and when the modulation mode is recognized, signals of the same modulation mode, which comprise frequency points and bandwidths, of a known frequency band are transmitted when the two parties are opposed, and saturated blocking interference can be carried out on a designated target, so that the aim of communication countermeasure training is achieved.
In the art, conventional digital signals include ASK (amplitude modulation), FSK (frequency modulation), MSK (minimum shift keying), PSK (phase modulation) and QAM (quadrature amplitude modulation), and the amplitude-frequency response of the signals of the first three systems generally has obvious discrete lines, so that the signals can be identified and classified according to the number of the discrete lines after being processed by FFT (fast fourier transform). The spectrum characteristic of the PSK/QAM signal is flat and has no obvious discrete spectral line, which is similar to the spectrum characteristic of a spread spectrum signal, and the modulation end is used for oversampling the signal and adding a filter for reducing out-of-band interference, so that the receiving end can finish cooperative demodulation by using matched filtering. But blind identification of such signals must be known by an oversampling multiple equal to the sampling rate divided by the signal bandwidth, and bandwidth estimation for such signals is therefore particularly important.
Disclosure of Invention
Aiming at the problems in the traditional method, the application provides a raised cosine shaping filter bandwidth estimation system of a software defined framework and a raised cosine shaping filter bandwidth estimation method of the software defined framework, which can greatly improve the accuracy of bandwidth estimation.
In order to achieve the above object, the embodiment of the present application adopts the following technical scheme:
in one aspect, a method for estimating a raised cosine shaping filter bandwidth of a software defined framework is provided, including the steps of:
acquiring a transmitted digital signal to be blindly identified;
carrying out fast Fourier transform processing on the digital signal to be blind identified, and extracting a signal amplitude spectrum;
smoothing the signal amplitude spectrum by means of average filtering; the size of the filtering window of the mean filtering is equal to the signal length/50 of the fast Fourier transform;
finding out a frequency intermediate value point on an amplitude-frequency response curve obtained by smoothing the signal amplitude spectrum;
and calculating to obtain the bandwidth estimated value of the digital signal to be blindly identified by using the frequency intermediate value point.
In one embodiment, the step of finding a frequency intermediate value point on an amplitude-frequency response curve obtained by smoothing a signal amplitude spectrum includes:
searching an amplitude maximum value point on an amplitude-frequency response curve obtained after the signal amplitude spectrum is subjected to smoothing treatment;
searching from the maximum amplitude point to two sides of the curve to find a first critical point and a second critical point with the amplitude being half of the maximum amplitude;
determining a frequency intermediate value point according to the first critical point and the second critical point; the frequency intermediate value point is half of the sum of the frequencies of the first critical point and the second critical point.
In one embodiment, the frequency intermediate value point is a frequency point corresponding to the amplitude maximum value point on the amplitude-frequency response curve.
In one embodiment, the step of calculating the bandwidth estimation value of the digital signal to be blindly identified by using the frequency intermediate value point includes:
acquiring an amplitude value of a frequency intermediate value point;
searching a minimum amplitude value in the frequency searching length to the left of the first critical point; the frequency search length is half of the difference between the frequencies of the second critical point and the first critical point;
searching a third critical point and a fourth critical point with amplitude values equal to a specific value from the amplitude maximum value point of the amplitude-frequency response curve to two sides of the curve; the specific value is equal to half of the sum of the amplitude value and the minimum amplitude value of the frequency intermediate value point;
and calculating according to the signal length of the fast Fourier transform, the sampling rate of the mean value filtering, the third critical point and the fourth critical point to obtain the bandwidth estimation value of the digital signal to be blindly identified.
On the other hand, still provide a raised cosine shaping filter bandwidth estimation system of software defined framework, include:
the signal acquisition module is used for acquiring the transmitted digital signal to be blindly identified;
the signal conversion module is used for extracting a signal amplitude spectrum after performing fast Fourier transform processing on the digital signal to be blindly identified;
the average filtering module is used for carrying out average filtering smoothing on the signal amplitude spectrum; the size of the filtering window of the mean filtering is equal to the signal length/50 of the fast Fourier transform;
the median searching module is used for searching a frequency median point on an amplitude-frequency response curve obtained by smoothing the signal amplitude spectrum;
and the bandwidth estimation module is used for calculating and obtaining the bandwidth estimation value of the digital signal to be blindly identified by utilizing the frequency intermediate value point.
In one embodiment, the median lookup module includes:
the maximum value submodule is used for finding out an amplitude maximum value point on an amplitude-frequency response curve obtained by smoothing the signal amplitude spectrum;
the first critical submodule is used for searching the two sides of the curve from the maximum amplitude point to find a first critical point and a second critical point with the amplitude half of the maximum amplitude;
the median value determining submodule is used for determining a frequency median point according to the first critical point and the second critical point; the frequency intermediate value point is half of the sum of the frequencies of the first critical point and the second critical point.
In one embodiment, the frequency intermediate value point is a frequency point corresponding to the amplitude maximum value point on the amplitude-frequency response curve.
In one embodiment, the bandwidth estimation module includes:
the middle amplitude sub-module is used for acquiring the amplitude value of the frequency middle value point;
a minimum amplitude submodule, configured to search a minimum amplitude value in a frequency search length to the left of the first critical point; the frequency search length is half of the difference between the frequencies of the second critical point and the first critical point;
the second critical submodule is used for searching a third critical point and a fourth critical point with amplitude values equal to a specific value from the amplitude maximum value point of the amplitude-frequency response curve to two sides of the curve; the specific value is equal to half of the sum of the amplitude value and the minimum amplitude value of the frequency intermediate value point;
and the bandwidth calculation sub-module is used for calculating and obtaining the bandwidth estimation value of the digital signal to be blindly identified according to the signal length of the fast Fourier transform, the sampling rate of the mean value filtering, the third critical point and the fourth critical point.
One of the above technical solutions has the following advantages and beneficial effects:
according to the raised cosine shaping filter bandwidth estimation method and system of the software defined framework, after the digital signal to be blindly identified transmitted in the external space is obtained, the digital signal is subjected to fast Fourier transform processing and is transferred to a frequency domain, and then the signal amplitude spectrum of the signal is extracted, so that the amplitude-frequency response curve of the signal is obtained. And then, carrying out average filtering smoothing treatment on the obtained signal amplitude spectrum so as to smooth the amplitude-frequency response by utilizing the characteristic of the vertical axis value (amplitude) of the amplitude-frequency response and adding the average filtering, thereby ensuring that the bandwidth can be estimated more accurately. And then searching a frequency intermediate value point on an amplitude-frequency response curve obtained after the signal amplitude spectrum is subjected to smoothing treatment, and calculating by using the frequency intermediate value point to obtain a relatively accurate bandwidth estimated value of the digital signal to be identified blindly.
Compared with the prior art, the technical scheme is based on a raised cosine shaping filtering mode, utilizes the vertical axis value characteristic of the amplitude-frequency response, utilizes the mean value adding filtering to smooth the amplitude-frequency response for the first time, can accurately estimate the bandwidth, has extremely small estimated bandwidth error and is simple and efficient in algorithm implementation.
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In order to more clearly illustrate the technical solutions of the embodiments or the conventional techniques of the present application, the drawings required for the descriptions of the embodiments or the conventional techniques will be briefly described below, and it is apparent that the drawings in the following description are only some embodiments of the present application, and other drawings may be obtained according to the drawings without inventive effort for those skilled in the art.
FIG. 1 is a flowchart of a method for estimating a raised cosine shaping filter bandwidth of a software defined framework according to an embodiment;
FIG. 2 is a schematic diagram illustrating a characteristic principle of a raised cosine shaping filter according to an embodiment;
FIG. 3 is a flow chart illustrating the acquisition of frequency intermediate value points in one embodiment;
FIG. 4 is a graph of the amplitude-frequency response before mean filtering in one embodiment;
FIG. 5 is a graph of the amplitude-frequency response after mean filtering in one embodiment;
FIG. 6 is a flow diagram of a bandwidth estimation process in one embodiment;
FIG. 7 is a graph showing the relative error of bandwidth estimation with FFT size for different signal-to-noise ratios in one embodiment;
fig. 8 is a schematic block diagram of a raised cosine shaping filter bandwidth estimation system of a software defined framework in one embodiment.
Detailed Description
The present application will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present application more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the application.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used in the description of the application herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the application.
It is noted that reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment may be included in at least one embodiment of the application. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments.
Those skilled in the art will appreciate that the embodiments described herein may be combined with other embodiments. The term "and/or" as used in the present specification and the appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes such combinations.
Aiming at the technical problem of low accuracy of bandwidth estimation in the traditional signal blind identification technology, the design concept of the application is as follows: based on raised cosine shaping filtering mode, the amplitude-frequency response is smoothed by utilizing the vertical axis value characteristic of the amplitude-frequency response and adding average filtering, so that the bandwidth size can be estimated more accurately.
Embodiments of the present application will be described in detail below with reference to the attached drawings in the drawings of the embodiments of the present application.
Referring to fig. 1, in one embodiment, a method for estimating a raised cosine shaping filter bandwidth of a software defined framework is provided, which may include the following processing steps S12 to S20:
s12, acquiring the transmitted digital signal to be identified blindly.
S14, extracting a signal amplitude spectrum after performing fast Fourier transform processing on the digital signal to be blind identified.
S16, carrying out mean value filtering smoothing on the signal amplitude spectrum; the filter window size of the mean filter is equal to the signal length/50 of the fast fourier transform.
S18, finding out a frequency intermediate value point on an amplitude-frequency response curve obtained by smoothing the signal amplitude spectrum.
S20, calculating to obtain the bandwidth estimated value of the digital signal to be blindly identified by using the frequency intermediate value point.
It can be understood that the digital signal to be blindly identified refers to a signal to be identified, which is transmitted in the space of the current application scene and needs to be blindly identified by the signal modulation mode, and the oversampling multiple of the signal can be determined by estimating the bandwidth of the signal, so that the modulation mode of the signal can be obtained, and the identification and classification of the signal are realized.
As shown in fig. 2, which is a schematic illustration of the characteristic principle of the raised cosine shaping filter, it can be seen from fig. 2 that, for the raised cosine shaping filter with 4 times of oversampling, it is assumed that the sampling rate fs=160 MHz,40MHz is the bandwidth, and the frequency band range between 61 MHz and 101MHz is the effective bandwidth. While the bandwidth edge threshold 1.076dB is exactly half the size of 2.094dB of the frequency intermediate point 80MHz and is approximately equal to (61-54)/20 since the roll-off coefficient is equal to 0.35. The roll-off coefficient ranges from 0 to 1, and when the roll-off coefficient is equal to 0, the raised cosine shaping filter is equivalent to a rectangular filter (without filtering); when the roll-off coefficient is equal to 1, the tail length of the raised cosine shaping filter is just equal to half the bandwidth, i.e. 20MHz. With this feature, the present embodiment performs efficient accurate bandwidth estimation through the foregoing steps.
Specifically, after the digital signal to be blindly identified transmitted in the space is acquired, the digital signal is transformed into a frequency domain through Fast Fourier Transform (FFT) processing, so as to obtain a signal amplitude spectrum of the signal, that is, an amplitude-frequency response curve of the signal is acquired. In order to enable the amplitude-frequency response curve to be accurately bandwidth estimated by using the characteristics of the raised cosine shaping filter described in the previous paragraph, it is necessary to ensure that the amplitude-frequency response curve is smooth, and thus the amplitude-frequency response curve is subjected to mean filtering to become a smooth amplitude-frequency response curve. And then the frequency intermediate value point can be found out on the amplitude-frequency response curve, and finally the bandwidth estimated value of the digital signal to be blindly identified can be obtained from the found frequency intermediate value point, so that the bandwidth estimated value can be used for reversely pushing to obtain the modulation mode of the signal, and the blind identification of the digital signal to be blindly identified is realized.
According to the raised cosine shaping filter bandwidth estimation method of the software defined framework, after the digital signal to be blindly identified transmitted in the external space is obtained, the digital signal is subjected to fast Fourier transform processing and is transferred to a frequency domain, and then the signal amplitude spectrum of the signal is extracted, so that the amplitude-frequency response curve of the signal is obtained. And then, carrying out average filtering smoothing treatment on the obtained signal amplitude spectrum so as to smooth the amplitude-frequency response by utilizing the characteristic of the vertical axis value (amplitude) of the amplitude-frequency response and adding the average filtering, thereby ensuring that the bandwidth can be estimated more accurately. And then searching a frequency intermediate value point on an amplitude-frequency response curve obtained after the signal amplitude spectrum is subjected to smoothing treatment, and calculating by using the frequency intermediate value point to obtain a relatively accurate bandwidth estimated value of the digital signal to be identified blindly.
Compared with the prior art, the technical scheme is based on a raised cosine shaping filtering mode, utilizes the vertical axis value characteristic of the amplitude-frequency response, utilizes the mean value adding filtering to smooth the amplitude-frequency response for the first time, can accurately estimate the bandwidth, has extremely small estimated bandwidth error and is simple and efficient in algorithm implementation.
It should be noted that, each step of the above method may be respectively packaged into components with corresponding functions in a software defined manner, for example, a communication system of a software radio device is adopted in the field, and the corresponding components are installed in general communication signal transmission processing equipment hardware and communication connection between the components is established according to a flow sequence executed by the method, so that the corresponding functions of each step of the above method can be implemented by running the software defined components, and online setting of different processing parameters, such as but not limited to setting a filtering window, changing signal length of a fast fourier transform, etc., can be supported in a software defined manner, so that the above method can be suitable for different signal blind recognition scenarios.
In one embodiment, the frequency intermediate value point is a frequency point corresponding to the amplitude maximum value point on the amplitude-frequency response curve.
It can be understood that in this embodiment, for the amplitude-frequency response curve after the mean filtering, there is also a case that the frequency intermediate value point is a frequency point corresponding to the amplitude maximum value point on the amplitude-frequency response curve, and at this time, after the mean filtering, the frequency intermediate value point may be directly found on the amplitude-frequency response curve after the mean filtering, so that the frequency intermediate value point may be quickly obtained, so as to be used for quickly calculating to obtain the bandwidth estimation value of the digital signal to be blindly identified, for example, half of the frequency value of the frequency intermediate value point is the bandwidth estimation value.
In one embodiment, as shown in fig. 3, regarding the above-mentioned step S18, the following processing steps S182 to S186 may be specifically included:
s182, finding out the maximum value point of the amplitude on the amplitude-frequency response curve obtained by smoothing the signal amplitude spectrum.
S184, searching the two sides of the curve from the maximum amplitude point to find a first critical point and a second critical point with the amplitude half of the maximum amplitude.
S186, determining a frequency intermediate value point according to the first critical point and the second critical point; the frequency intermediate value point is half of the sum of the frequencies of the first critical point and the second critical point.
It can be understood that in this embodiment, for the amplitude-frequency response curve after the mean value filtering, there are also some cases where the frequency intermediate value point is not necessarily the frequency point corresponding to the amplitude maximum value point (for convenience of description, the amplitude maximum value point may be denoted as index 0), and only the frequency intermediate value point is found to accurately estimate the bandwidth, so that it is first required to find the amplitude maximum value M on the curve, and its corresponding curve point is the amplitude maximum value point index0. Since the trailing point of the curve is monotonically decreasing, searching from the maximum amplitude point index0 to both sides of the curve finds the first critical point index1 and the second critical point index2 with the vertical axis (representing amplitude) equal to M/2 (wherein index1< index2 on the horizontal axis (frequency)). Because of symmetry on the curve, the frequency intermediate value point is (index 1+index 2)/2, so that the required frequency intermediate value point can be obtained rapidly and accurately, and the efficiency and accuracy for calculating and obtaining the frequency intermediate value point are higher.
As shown in fig. 4, which is a graph of the amplitude-frequency response before the mean filtering in one example, and as shown in fig. 5, which is a graph of the amplitude-frequency response after the mean filtering at 2000 points in the example, it is apparent from the two graphs that the graph after the mean filtering becomes much smoother. Here, if the FFT size (signal length) is set to 100000Hz, the number of mean filtering points is set to 2000 frequency points, it can be inferred from the filtering principle of the raised cosine shaping filter that the frequency intermediate value point after mean filtering is shifted forward by 1000 frequency points relative to the filtering front, which needs to be correspondingly compensated when calculating the frequency offset estimation. In particular, assuming the FFT size is noted as L, the mean filter window size is designed to be equal to L/50.
In one embodiment, as shown in fig. 6, regarding the above-described step S20, the following processing steps S202 to S208 may be specifically included:
s202, acquiring an amplitude value of a frequency intermediate value point;
s204, searching the minimum amplitude value in the frequency searching length to the left of the first critical point; the frequency search length is half of the difference between the frequencies of the second critical point and the first critical point;
s206, searching a third critical point and a fourth critical point with amplitude values equal to a specific value from the amplitude maximum value point of the amplitude-frequency response curve to two sides of the curve; the specific value is equal to half of the sum of the amplitude value and the minimum amplitude value of the frequency intermediate value point;
and S208, calculating to obtain the bandwidth estimation value of the digital signal to be blindly identified according to the signal length of the fast Fourier transform, the sampling rate of the mean value filtering, the third critical point and the fourth critical point.
It can be appreciated that, after the frequency intermediate value point is taken on the smooth foregoing curve, more accurate bandwidth estimation can be implemented by the calculation method of this embodiment. Specifically, the vertical axis value M0 of the frequency intermediate value point is taken for the smooth curve, and then the frequency search length w= (index 2-index 1)/2 is taken leftwards from the first critical point index1, so as to find the minimum vertical axis point value N0 (i.e. the minimum amplitude value) in the range. This is done in consideration of the fact that the tail length is exactly equal to the bandwidth when the roll-off coefficient is at most equal to 1. Taking a specific value m1= (m0+n0)/2, searching from the amplitude maximum value point index0 to two sides to find a third critical point index3 and a fourth critical point index4 with vertical axis values equal to M1 (wherein index3< index4 on the horizontal axis). The bandwidth estimation value is bw= (index 4-index 3) fs/L.
Therefore, through the ingenious and simplified design thought, the average filtering is utilized for the first time to obtain the frequency intermediate value point, meanwhile, noise is added at the trailing part of the filter, accurate estimation of bandwidth is realized, modulation and identification can be carried out only by extracting the oversampling multiple of the received signal, and communication transmission countermeasure processing can be carried out without matched filtering. The accuracy of the bandwidth estimation, as a function of the signal-to-noise ratio and FFT size, is illustrated below by way of example with verification of the embodiments using a simulation result graph. When the bandwidth is estimated accurately, the oversampling ratio n=fs/Bw can also be estimated accurately.
In one experimental example, the sampling rate fs may be set equal to 2MHz, the symbol rate, that is, the bandwidth is equal to 500KHz, that is, 4 times of oversampling, a BPSK (binary phase shift keying) signal is adopted to add gaussian noise of 15dB, 30dB and 50dB, respectively, and the relative error of bandwidth estimation when different FFT sizes are changed from 10000 ～ 1000000Hz is set, where the relative error calculation formula is abs (b_esti-500 KHz)/500 KHz, where b_esti is an actual value.
As shown in FIG. 7, it can be seen from the graph that the bandwidth estimation is accurate when the signal to noise ratio is high, and the FFT size is more than 100000Hz, the bandwidth estimation is accurate, and the minimum relative error is equal to 2.469e -5 And multiplying the signal by 500KHz to calculate the bandwidth estimation error equal to 10Hz. When the bandwidth is estimated accurately, the oversampling multiple n=fs/Bw ensures a large redundancy, as this example can be estimated above 1024, which is a very accurate indicator in communication probing. Meanwhile, the frequency offset estimation can be very accurate due to mean filtering smoothing, and the roll-off coefficient can also be reversely deduced according to the existing principle.
It should be understood that, although the steps in the flowcharts 1, 3, and 6 described above are shown in order as indicated by the arrows, these steps are not necessarily performed in order 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 of the flowcharts 1, 3, and 6 described above may include a plurality of sub-steps or stages that are not necessarily performed at the same time, but may be performed at different times, and the order of execution of the sub-steps or stages is not necessarily sequential, but may be performed in turn or alternately with at least some of the other steps or sub-steps of other steps.
In one embodiment, as shown in fig. 8, a raised cosine shaped filter bandwidth estimation system 100 of a software defined framework is provided, which includes a signal acquisition module 11, a signal transformation module 13, a mean filtering module 15, a median lookup module 17, and a bandwidth estimation module 19. The signal acquisition module 11 is configured to acquire the transmitted digital signal to be blind identified. The signal transformation module 13 is used for extracting a signal amplitude spectrum after performing fast fourier transformation processing on the digital signal to be blind identified. The average filtering module 15 is used for performing average filtering smoothing on the signal amplitude spectrum; the filter window size of the mean filter is equal to the signal length/50 of the fast fourier transform. The median searching module 17 is used for searching a frequency median point on an amplitude-frequency response curve obtained by smoothing the signal amplitude spectrum. The bandwidth estimation module 19 is configured to calculate a bandwidth estimation value of the digital signal to be blindly identified by using the frequency intermediate value point.
It can be understood that, regarding the explanation of each feature in this embodiment, the explanation of the corresponding feature of the raised cosine shaping filter bandwidth estimation method of the software defined framework can be understood in the same way, and will not be repeated here.
The raised cosine shaping filter bandwidth estimation system 100 of the software defined framework obtains the amplitude-frequency response curve of the signal by acquiring the digital signal to be blindly identified transmitted in the external space, performing fast fourier transform processing on the digital signal to convert the digital signal to the frequency domain, and extracting the signal amplitude spectrum of the signal. And then, carrying out average filtering smoothing treatment on the obtained signal amplitude spectrum so as to smooth the amplitude-frequency response by utilizing the characteristic of the vertical axis value (amplitude) of the amplitude-frequency response and adding the average filtering, thereby ensuring that the bandwidth can be estimated more accurately. And then searching a frequency intermediate value point on an amplitude-frequency response curve obtained after the signal amplitude spectrum is subjected to smoothing treatment, and calculating by using the frequency intermediate value point to obtain a relatively accurate bandwidth estimated value of the digital signal to be identified blindly.
Compared with the prior art, the technical scheme is based on a raised cosine shaping filtering mode, utilizes the vertical axis value characteristic of the amplitude-frequency response, utilizes the mean value adding filtering to smooth the amplitude-frequency response for the first time, can accurately estimate the bandwidth, has extremely small estimated bandwidth error and is simple and efficient in algorithm implementation.
In one embodiment, the median lookup module 17 may further include the following sub-modules: and the maximum value sub-module is used for finding out an amplitude maximum value point on an amplitude-frequency response curve obtained by smoothing the signal amplitude spectrum. And the first critical sub-module is used for searching the two sides of the curve from the maximum amplitude point to find a first critical point and a second critical point with the amplitude half of the maximum amplitude. The median value determining submodule is used for determining a frequency median point according to the first critical point and the second critical point; the frequency intermediate value point is half of the sum of the frequencies of the first critical point and the second critical point.
In one embodiment, the frequency intermediate value point is a frequency point corresponding to the amplitude maximum value point on the amplitude-frequency response curve.
In one embodiment, the bandwidth estimation module 19 may further include the following sub-modules: and the middle amplitude sub-module is used for acquiring the amplitude value of the frequency middle value point. A minimum amplitude submodule, configured to search a minimum amplitude value in a frequency search length to the left of the first critical point; the frequency search length is half the difference between the frequencies of the second critical point and the first critical point. The second critical submodule is used for searching a third critical point and a fourth critical point with amplitude values equal to a specific value from the amplitude maximum value point of the amplitude-frequency response curve to two sides of the curve; the specific value is equal to half of the sum of the amplitude value and the minimum amplitude value of the frequency intermediate value point. And the bandwidth calculation sub-module is used for calculating and obtaining the bandwidth estimation value of the digital signal to be blindly identified according to the signal length of the fast Fourier transform, the sampling rate of the mean value filtering, the third critical point and the fourth critical point.
For specific limitations of the system 100 for estimating the bandwidth of the raised cosine shaping filter of the software defined framework, reference may be made to the corresponding limitations of the method for estimating the bandwidth of the raised cosine shaping filter of the software defined framework hereinabove, and the description thereof will not be repeated here. The various modules in the raised cosine shaped filter bandwidth estimation system 100 of the software defined framework described above may be implemented in whole or in part by software, hardware, and combinations thereof. The above modules may be embedded in hardware or may be independent from a device having a communication transmission signal processing function, or may be stored in a memory of the device in software, so that the processor may call and execute operations corresponding to the above modules, where the device may be, but is not limited to, various communication transmission signal processing devices existing in the art.
In one embodiment, there is also provided a computer device including a memory and a processor, the memory storing a computer program, the processor implementing the following processing steps when executing the computer program: acquiring a transmitted digital signal to be blindly identified; carrying out fast Fourier transform processing on the digital signal to be blind identified, and extracting a signal amplitude spectrum; smoothing the signal amplitude spectrum by means of average filtering; the size of the filtering window of the mean filtering is equal to the signal length/50 of the fast Fourier transform; finding out a frequency intermediate value point on an amplitude-frequency response curve obtained by smoothing the signal amplitude spectrum; and calculating to obtain the bandwidth estimated value of the digital signal to be blindly identified by using the frequency intermediate value point.
It will be appreciated that the above-mentioned computer device may include other software and hardware components not listed in the specification besides the above-mentioned memory and processor, and may be specifically determined according to the model of the specific computer device in different application scenarios, and the detailed description will not be listed in any way.
In one embodiment, the processor may further implement the steps or sub-steps added in the embodiments of the raised cosine shaping filter bandwidth estimation method of the software defined framework when executing the computer program.
In one embodiment, there is also provided a computer readable storage medium having stored thereon a computer program which when executed by a processor performs the following processing steps: acquiring a transmitted digital signal to be blindly identified; carrying out fast Fourier transform processing on the digital signal to be blind identified, and extracting a signal amplitude spectrum; smoothing the signal amplitude spectrum by means of average filtering; the size of the filtering window of the mean filtering is equal to the signal length/50 of the fast Fourier transform; finding out a frequency intermediate value point on an amplitude-frequency response curve obtained by smoothing the signal amplitude spectrum; and calculating to obtain the bandwidth estimated value of the digital signal to be blindly identified by using the frequency intermediate value point.
In one embodiment, the computer program may further implement the steps or sub-steps added in the embodiments of the raised cosine shaping filter bandwidth estimation method of the software defined framework.
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, which may be stored on a non-transitory computer readable storage medium and which, when executed, may comprise the steps of the above-described embodiments of the methods. Any reference to memory, storage, database, or other medium used in 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 dynamic random access memory (Rambus DRAM, RDRAM for short), and interface dynamic random access memory (DRDRAM), 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 foregoing examples illustrate only a few embodiments of the application, which are described in detail and are not to be construed as limiting the scope of the application. It should be noted that it is possible for those skilled in the art to make several variations and modifications without departing from the spirit of the present application, which fall within the protection scope of the present application. The scope of the application is therefore intended to be covered by the appended claims.
Claims (4)
1. A raised cosine shaping filter bandwidth estimation method of a software defined framework is characterized by comprising the following steps:
acquiring a transmitted digital signal to be blindly identified;
performing fast Fourier transform processing on the digital signal to be blindly identified, and extracting a signal amplitude spectrum;
carrying out mean filtering smoothing treatment on the signal amplitude spectrum; the size of the filtering window of the mean filtering is equal to the signal length/50 of the fast Fourier transform;
finding out a frequency intermediate value point on an amplitude-frequency response curve obtained by smoothing the signal amplitude spectrum; the amplitude maximum value point is found out on an amplitude-frequency response curve obtained after the signal amplitude spectrum is subjected to smoothing treatment;
searching the two sides of the curve from the maximum amplitude point to find a first critical point and a second critical point with the amplitude half of the maximum amplitude;
determining the frequency intermediate value point according to the first critical point and the second critical point; the frequency intermediate value point is half of the sum of the frequencies of the first critical point and the second critical point;
calculating to obtain a bandwidth estimated value of the digital signal to be blindly identified by utilizing the frequency intermediate value point; the amplitude value of the frequency intermediate value point is obtained;
searching a minimum amplitude value in the frequency searching length to the left of the first critical point; the frequency search length is half of the difference between the frequencies of the second critical point and the first critical point;
searching a third critical point and a fourth critical point with amplitude values equal to a specific value from the amplitude maximum value point of the amplitude-frequency response curve to two sides of the curve; the specific value is equal to half of the sum of the amplitude value of the frequency intermediate value point and the minimum amplitude value;
and calculating to obtain the bandwidth estimation value of the digital signal to be blindly identified according to the signal length of the fast Fourier transform, the sampling rate of the mean value filtering, the third critical point and the fourth critical point.
2. The method for estimating a raised cosine shaping filter bandwidth of a software defined framework according to claim 1, wherein the frequency intermediate value point is a frequency point corresponding to an amplitude maximum value point on the amplitude-frequency response curve.
3. A system for raised cosine shaped filter bandwidth estimation of a software defined framework, comprising:
the signal acquisition module is used for acquiring the transmitted digital signal to be blindly identified;
the signal conversion module is used for extracting a signal amplitude spectrum after performing fast Fourier transform processing on the digital signal to be blindly identified;
the average filtering module is used for carrying out average filtering smoothing on the signal amplitude spectrum; the size of the filtering window of the mean filtering is equal to the signal length/50 of the fast Fourier transform;
the median searching module is used for searching a frequency intermediate value point on an amplitude-frequency response curve obtained by smoothing the signal amplitude spectrum;
the bandwidth estimation module is used for calculating and obtaining the bandwidth estimation value of the digital signal to be blindly identified by utilizing the frequency intermediate value point; wherein the bandwidth estimation module comprises:
a middle amplitude sub-module, configured to obtain an amplitude value of the frequency middle value point;
a minimum amplitude submodule, configured to search a minimum amplitude value in a frequency search length to the left of the first critical point; the frequency search length is half of the difference between the frequencies of the second critical point and the first critical point;
the second critical submodule is used for searching a third critical point and a fourth critical point with amplitude values equal to a specific value from the amplitude maximum value point of the amplitude-frequency response curve to two sides of the curve; the specific value is equal to half of the sum of the amplitude value of the frequency intermediate value point and the minimum amplitude value;
the bandwidth calculation sub-module is used for calculating to obtain the bandwidth estimation value of the digital signal to be blindly identified according to the signal length of the fast Fourier transform, the sampling rate of the mean value filtering, the third critical point and the fourth critical point; wherein, the median lookup module includes:
the maximum value submodule is used for finding out an amplitude maximum value point on an amplitude-frequency response curve obtained by smoothing the signal amplitude spectrum;
the first critical sub-module is used for searching the two sides of the curve from the maximum amplitude point to find a first critical point and a second critical point with the amplitude half of the maximum amplitude;
a median determining sub-module for determining the frequency median point according to the first critical point and the second critical point; the frequency intermediate value point is half of the sum of the frequencies of the first critical point and the second critical point.
4. The system for estimating a bandwidth of a raised cosine shaping filter of a software defined framework according to claim 3 wherein the frequency intermediate value point is a frequency point corresponding to a maximum amplitude point on the amplitude-frequency response curve.
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