Filter determination method and device, electronic equipment, storage medium and computer program product

Abstract

The invention discloses a filter determination method and device, electronic equipment, a storage medium and a computer program product. The method comprises the following steps: determining first information of data to be filtered, the first information being related to a channel bandwidth, a frequency band range, a subcarrier interval and a duplex multiplexing mode; second information is determined through the first information, and the second information comprises the type of a filter, the type of a window function and the order of the filter; and determining a filter for filtering the to-be-filtered data by using the second information.

Description

Technical Field

[0001] The present application relates to the field of data processing, and in particular to a filter determination method, device, electronic device, storage medium and computer program product. Background Art

[0002] In the related art, a multi-carrier filter can usually be used to filter the data, thereby resisting the interference caused by out-of-band radiation leakage of adjacent spectrums and eliminating channel transmission distortion, thereby achieving high-precision demodulation and analysis of the data.

[0003] However, with the development of mobile communication technology, the signal bandwidth continues to increase. In this case, on the one hand, the increase in bandwidth will require the order of the filter used by the communication equipment in the process of demodulating the data to continue to increase; on the other hand, the increase in bandwidth will make the effect of using the filter to filter the received data (which can also be understood as the data to be filtered) worse, such as the out-of-band radiation attenuation suppression performance deteriorates, the in-band interference fluctuation increases, etc., making it difficult to achieve high-precision demodulation analysis. Summary of the invention

[0004] To solve the related technical problems, the embodiments of the present application provide a filter determination method, device, electronic device, storage medium and computer program product.

[0005] The technical solution of the embodiment of the present application is implemented as follows:

[0006] The present application provides a filter determination method, including:

[0007] Determine first information of the data to be filtered, where the first information is related to the channel bandwidth, frequency band range, subcarrier spacing, and duplex multiplexing mode;

[0008] Determine second information using the first information, where the second information includes a type of filter, a type of window function, and an order of the filter;

[0009] The second information is used to determine a filter for filtering the data to be filtered.

[0010] In the above scheme, the type of the filter includes one of the following:

[0011] Low pass filter;

[0012] High pass filter;

[0013] Bandpass filter;

[0014] Band-stop filter.

[0015] In the above solution, the step of using the first information to determine the second information includes:

[0016] Determine filter requirement information corresponding to the data to be filtered using the first information;

[0017] The second information is determined using the filter requirement information.

[0018] In the above solution, the filter requirement information includes one or more of the following:

[0019] Signal sampling frequency;

[0020] Nyquist frequency;

[0021] Passband cutoff frequency;

[0022] Stopband cutoff frequency;

[0023] Passband ripple;

[0024] Stopband attenuation.

[0025] In the above scheme, the method further comprises:

[0026] The data to be filtered is filtered using the determined filter to obtain filtered data.

[0027] In the above scheme, the method further comprises:

[0028] Using the filtered data, updating the second information;

[0029] The updated second information is used to re-determine the filter used to filter the subsequent data to be filtered.

[0030] In the above scheme, the filtering of the to-be-filtered data by using the determined filter to obtain the filtered data includes:

[0031] Using N delay devices included in the filter, the data to be filtered is delayed to obtain N delayed data, wherein each of the N delayed data has a different delay, and N is the order of the filter;

[0032] Performing fast Fourier transform (FFT) processing on the N delayed data and the data to be filtered to obtain N+1 frequency domain data, wherein the N+1 frequency domain data correspond to the N+1 filter coefficients one by one;

[0033] For each frequency domain data, the product of the frequency domain data and the corresponding filter coefficient is calculated to obtain a calculation result;

[0034] The N+1 calculation results are accumulated to obtain the filtered data.

[0035] In the above scheme, the filtering of the to-be-filtered data by using the determined filter to obtain the filtered data includes:

[0036] Performing FFT processing on the data to be filtered to obtain frequency domain data to be filtered;

[0037] The filter is used to process the frequency domain data to be filtered to obtain the filtered data.

[0038] The embodiment of the present application also provides a filter determination device, including:

[0039] A first determining unit, configured to determine first information of the data to be filtered, wherein the first information is related to a channel bandwidth, a frequency band range, a subcarrier spacing, and a duplex multiplexing mode;

[0040] The second determination unit is used to use the first information to determine second information, where the second information includes a filter type, a window function type, and a filter order; and use the second information to determine a filter for filtering the data to be filtered.

[0041] The present application also provides an electronic device, including: a processor and a memory for storing a computer program that can be run on the processor.

[0042] Wherein, the processor is used to execute the steps of any of the above methods when running the computer program.

[0043] An embodiment of the present application further provides a storage medium having a computer program stored thereon, wherein the computer program implements the steps of any of the above methods when executed by a processor.

[0044] An embodiment of the present application also provides a computer program product, including a computer program, which implements the steps of any of the above methods when executed by a processor.

[0045] The filter determination method, device, electronic device, storage medium and computer program product provided in the embodiment of the present application determine the first information of the data to be filtered, the first information is related to the channel bandwidth, frequency band range, subcarrier spacing and duplex multiplexing mode; using the first information, determine the second information, the second information includes the type of filter, the type of window function and the order of the filter; using the second information, determine the filter used to filter the data to be filtered. The scheme provided in the embodiment of the present application dynamically and flexibly designs the filter according to the channel bandwidth, frequency band range, subcarrier spacing and duplex multiplexing mode of the data to be filtered (which can also be understood as the signal to be filtered). That is to say, for different data to be filtered, the filter most suitable for filtering the data to be filtered is determined from the three dimensions of the type of filter, the type of window function and the order of the filter. On the one hand, it can better meet the filtering requirements and improve the filtering effect; on the other hand, when meeting the same filtering requirements (such as the transition band width requirements, etc.), the filters determined by the above three dimensions are adjusted at the same time. Compared with the filter determined by only adjusting the filter order, the required filter order is small and easier to implement. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 It is a schematic diagram of the structure of a generalized multi-carrier filter bank in the related art;

[0047] Figure 2 It is a structural schematic diagram of a general multi-carrier filter bank in the related art;

[0048] Figure 3 A flowchart of a filter determination method according to an embodiment of the present application;

[0049] Figure 4 This is a schematic diagram of the amplitude response of the filter in the embodiment of the present application;

[0050] Figure 5 This is a schematic diagram of the structure of an electronic device according to an embodiment of the present application;

[0051] Figure 6 This is a schematic diagram of the structure of the filter according to the embodiment of the present application;

[0052] Figure 7 This is a schematic diagram of the signal power spectrum of the filtered data in the embodiment of the present application;

[0053] Figure 8 A schematic diagram of the error vector magnitude (EVM) demodulation result of the filtered data in an embodiment of the present application;

[0054] Fig. 9 This is a schematic diagram of the structure of a filter determination device according to an embodiment of the present application;

[0055] Fig.10 This is a schematic diagram of the structure of an electronic device according to an embodiment of the present application. DETAILED DESCRIPTION

[0056] The present application will be further described in detail below through the accompanying drawings and embodiments.

[0057] With the rapid development of the fifth-generation mobile communication technology (5G) New Radio (NR) wireless communication technology, diversified application scenario requirements have been put forward, and higher requirements have been put forward for communication capacity and signal transmission quality, which may include: higher system capacity, more complex and diverse carrier bandwidth configuration capabilities, and better transmission channel characteristics.

[0058] In order to meet the above technical requirements, it is necessary to increase the carrier bandwidth configured in the communication transmission and improve the clock sampling frequency. However, the above method requires increasing the radiation energy leakage outside the system spectrum band and increasing the mutual interference between different adjacent frequency bands, which in turn leads to low spectrum resource utilization (which can also be understood as waste of spectrum resources), increased power consumption, and increased demodulation analysis errors of the modulated signal, making it difficult to achieve high-precision demodulation analysis.

[0059] In the related technology, the multi-carrier filter is an important component of the modulation and demodulation of 5G NR signals, and the performance of the multi-carrier filter will directly affect the quality of communication services. Specifically, during the signal demodulation process, the multi-carrier filter obtains parameters such as the bandwidth of the system frequency band, the number of FFT points, and the length of the cyclic prefix (CP, Cyclic Prefix), adjusts the parameters of the filter according to the obtained parameters, and filters all subcarrier signals in the system frequency band, thereby resisting the interference caused by the out-of-band radiation leakage of adjacent spectrum, eliminating channel transmission distortion or damage, and then realizing high-precision demodulation analysis of 5G NR signals.

[0060] In the related art, the design method of multi-carrier filter mainly includes the design method of generalized multi-carrier filter group and the design method of universal multi-carrier filter group. Among them, the generalized multi-carrier filter group includes multiple sub-band modulation filters, each sub-band modulation filter corresponds to a sub-band, and the sub-band includes multiple sub-bands with fixed small bandwidth obtained by decomposing the total bandwidth of the system, and the sub-band contains one or more sub-carriers (it can also be understood that one or more sub-carriers are located in a sub-band); the universal multi-carrier filter group includes multiple band-pass filters based on sub-band filtering, after the received signal is processed by the band-pass filter, only the signal on the sub-carrier in the sub-band corresponding to the band-pass filter can pass, and the order of the filter is small (it can also be understood that the filter length is short), and the interval between the sub-carriers in a sub-band (it can also be understood as the sub-carrier interval) is fixed.

[0061] Specifically, in the scenario where a generalized multi-carrier filter bank is applied, such as Figure 1 As shown, after receiving the baseband modulated and added RF signals, the receiving end sequentially performs down-conversion, low-pass root mean square raised cosine filtering, tap delay and extraction processing on the RF signals to obtain the restored signals of each subcarrier (which can also be understood as reconstructed signals). However, in actual applications, there is usually inter-symbol interference, inter-channel interference and additive noise between the multi-channel subcarrier signals reconstructed by the generalized multi-carrier filter group, that is, the use scenarios of the generalized multi-carrier filter group are limited.

[0062] At the same time, in the scenario where a general multi-carrier filter bank is applied, such as Figure 2 As shown, after receiving the baseband signal, the receiving end performs serial-to-parallel conversion on the baseband signal to obtain multiple parallel data (each parallel data contains multiple orthogonal frequency-division multiplexing (OFDM) symbols), and then performs FFT processing on each parallel data, and performs filter coefficient equalization (i.e., the filter coefficient is used to multiply the parallel data after the corresponding FFT processing) to obtain the filtered data corresponding to each parallel data. Among them, the sidelobe attenuation level, main lobe width and other characteristics of the filter can be matched with the filtering requirements (such as the subcarrier spectrum range, etc.) by adjusting the parameters of the filter, so that the filter can filter the corresponding subcarrier spectrum, constrain the out-of-band radiation leakage of the subcarrier, and accelerate the attenuation rate of the subcarrier power out of the band (it can also be understood as accelerating the out-of-band power attenuation). However, in actual application, in the 5G scenario, when a general multi-carrier filter group is used to filter the received 5G NR signal, the interference between the subcarriers in each subband of the 5G NR signal is still large, and it is difficult to achieve high-precision demodulation and analysis of the 5G NR signal.

[0063] In addition to the above two design methods, when designing a multi-carrier signal system, the design of the filter bank can also be optimized based on the time domain window function method. Specifically, the interference caused by the filter bank can be minimized by optimizing the window function weighted value. In practical applications, in order to determine the window function weighted value, a nonlinear optimization algorithm needs to be introduced, and the nonlinear optimization algorithm is extremely time-consuming, and there is limited room for further optimization. Therefore. The optimization scheme based on the time domain window function method is limited in application scenarios.

[0064] In the related art, it is usually necessary to design a multi-carrier filter with a filter order of about 400 (specifically, it may include a channel filter based on pulse shaping design, i.e., a pulse shaping channel filter) for signal demodulation. In the 5G scenario, the signal bandwidth can reach 400MHz. At this time, in order to be able to demodulate the 5G NR signal at the receiving end, on the one hand, it is necessary to further increase the order of the filter at the receiving end; on the other hand, even if the order of the filter is increased, when the original filter used to process small bandwidth signals is used to filter the large bandwidth signal, the filtering performance is poor, such as the out-of-band radiation attenuation suppression becomes worse, the interference fluctuation between the in-band subcarriers becomes larger, etc., making it difficult to achieve high-precision and efficient demodulation of the 5G NR signal.

[0065] Based on this, in various embodiments of the present application, the filter is dynamically and flexibly designed according to the channel bandwidth, frequency band range, subcarrier spacing and duplex multiplexing mode of the data to be filtered (which can also be understood as the signal to be filtered). That is to say, for different data to be filtered, the filter that is most suitable for filtering the data to be filtered is determined from three dimensions: filter type, window function type and filter order. On the one hand, it can better meet the filtering requirements and improve the filtering effect; on the other hand, while meeting the same filtering requirements (such as transition band width requirements, etc.), the filters determined by the above three dimensions are adjusted at the same time. Compared with the filter determined by only adjusting the filter order, the required filter order is small and easier to implement.

[0066] The present application embodiment provides a filter determination method, which is applied to electronic equipment, such as Figure 3 As shown, the method includes:

[0067] Step 301: Determine first information of the data to be filtered, where the first information is related to the channel bandwidth, frequency band range, subcarrier spacing, and duplex multiplexing mode;

[0068] Step 302: Determine second information using the first information, where the second information includes a filter type, a window function type, and a filter order;

[0069] Step 303: using the second information, determine a filter for filtering the data to be filtered.

[0070] Here, in actual application, the electronic device can also be understood as a filtering device (i.e., a device that requires data (which can also be understood as a received signal) to be filtered), such as a terminal, a base station, etc. The embodiment of the present application does not limit the name of the electronic device, as long as its function is realized.

[0071] The data to be filtered may also be referred to as a signal to be filtered, and may specifically include a 5G NR signal, etc. Exemplarily, the data to be filtered may specifically include a parallel code stream obtained by serial-to-parallel conversion of captured baseband in-phase / quadrature (I / Q, In-phase / Quadrature) two-way complex time domain signals (i.e., the real part and the imaginary part of the complex signal).

[0072] In actual application, in step 301, the first information (also referred to as relevant information of the data to be filtered) can be pre-configured on the electronic device; wherein the first information can specifically include the channel bandwidth, frequency band range, subcarrier spacing, and duplex multiplexing mode of the data to be filtered. Here, the first information can also be referred to as a configuration item parameter or an input parameter, and the embodiment of the present application does not limit the name of the first information.

[0073] Exemplarily, the electronic device may specifically include a module for human-computer interaction (specifically referred to as an input parameter configuration module), and the relevant staff may select the parameter value corresponding to the relevant information in a selector (also understood as a drop-down menu) on a display screen included in the module for each relevant information, thereby pre-configuring the relevant information of the data to be filtered. After pre-configuring the relevant information of the data to be filtered on the electronic device, the electronic device may store the relevant information of the data to be filtered in a corresponding storage space, such as storing each relevant information in a corresponding data structure matrix. Among them, the contents of the configuration list of the selector (also understood as the channel bandwidth selector) for selecting the channel bandwidth parameter (i.e., the drop-down menu options) may include: 5MHz, 10MHz, 15MHz, 20MHz, 25MHz, 30MHz, 40MHz, 50MHz, 60MHz, 70MHz, 80MHz, 90MHz, 100MHz, 200MHz and 400MHz; the contents of the configuration list of the selector (also understood as the frequency band selector) for selecting the frequency band parameter may include: frequency range 1 (FR1, Frequency Range 1) and frequency range 2 (FR2); the contents of the configuration list of the selector (also understood as the subcarrier spacing selector) for selecting the subcarrier spacing parameter may include: 15kHz, 30kHz, 60kHz and 120kHz; the contents of the configuration list of the selector (also understood as the duplexing selector) for selecting the duplexing mode parameter may include: frequency division duplex (FDD, Frequency Division Duplex) and time division duplex (TDD, Time Division Duplex).

[0074] After determining the first information, in step 302, the electronic device can comprehensively consider the relevant information of the data to be filtered, determine the requirement information when designing the filter, that is, determine which requirements the designed filter needs to meet, and then determine the second information (which can also be understood as a filter designed to filter the data to be filtered) according to the requirement information of the filter; here, the second information can also be referred to as relevant information of the filter or filter parameters, etc., and the name of the second information is not limited in the embodiment of the present application; when the electronic device determines the requirement information when designing the filter, it comprehensively considers the values ​​of the four parameters of channel bandwidth, frequency band range, subcarrier spacing and duplex multiplexing mode, which can also be understood as the four parameters being coupled and responded to each other.

[0075] Based on this, in one embodiment, the specific implementation of step 302 may include:

[0076] Determine filter requirement information corresponding to the data to be filtered using the first information;

[0077] The second information is determined using the filter requirement information.

[0078] In one embodiment, the filter requirement information may include one or more of the following:

[0079] The signal sampling frequency refers to the number of times the electronic device samples the filtered data per second;

[0080] Nyquist frequency, which refers to the minimum signal sampling frequency required to avoid aliasing effects;

[0081] A passband cutoff frequency, wherein the passband cutoff frequency refers to a critical frequency of the filter passband;

[0082] Stopband (which can be understood as stopband) cutoff frequency, the stopband cutoff frequency refers to the critical frequency of the filter stopband;

[0083] Passband ripple, wherein the passband ripple refers to the degree of change of the filter gain within the passband range of the filter;

[0084] Stopband attenuation refers to the attenuation degree of signal power of the filter within the stopband range.

[0085] After determining the filter requirement information, the electronic device may design a filter that can meet the corresponding requirement according to the determined filter requirement information.

[0086] Specifically, in order to better meet the filter requirements, when designing the filter, the electronic device can design a finite impulse response (FIR) filter. The FIR filter can effectively suppress out-of-band radiation and reduce in-band interference fluctuations, thereby achieving high-precision and efficient demodulation analysis. The specific reasons include: the FIR filter has a narrow transition band, simple design, small filter order, and low calculation order (specifically the order of FFT points (i.e., number of samples) / 2); at the same time, the FIR filter has a linear phase and adopts the design concept of a window function. Therefore, there is no nonlinear delay distortion when the FIR filter filters the data, and there is only a delay effect of a fixed factor.

[0087] In practical applications, when designing an FIR filter, it is necessary to determine the type of window function to be used. The window function is used to intercept an infinite impulse response and obtain an impulse response sequence of fixed length as an FIR filter parameter; at the same time, the length of the window function is equivalent to the order of the FIR filter.

[0088] Specifically, the types of the window function may include a rectangular window (which can be expressed as RectangleWindow in English), a Hanning window, a Hamming window, a Blackman window, a Kaiser-Basel window, etc., and the characteristics of each type of window function (such as main lobe width and side lobe attenuation characteristics, etc.) are different. That is to say, when designing an FIR filter, the type of window function used by the FIR filter can determine the frequency resolution of the FIR filter and the ability to suppress out-of-band signals.

[0089] The following describes the characteristics of each type of window function:

[0090] (a) Rectangular window:

[0091] The window function of the rectangular window can be expressed by formula (1), and the amplitude function (which can also be understood as amplitude response) can be expressed by formula (2):

[0092] w R (n) = R N (n) (1)

[0093]

[0094] Among them, w R (n) represents the window function of the rectangular window, W R (e jω) represents the amplitude function of the rectangular window, which can be obtained by the window function of the rectangular window through discrete-time Fourier transform (DTFT), N represents the length of the rectangular window, R N (n) represents a rectangular function of length N. The rectangular function takes the value of 1 when n is greater than or equal to 0 and less than or equal to N-1; and takes the value of 0 when n is other than 0.

[0095] From the window function and amplitude function of the rectangular window, it can be determined that the characteristics of the rectangular window include: the main lobe width is 4π / N; the power of the first side lobe is 12dB lower than the main lobe power; the minimum stopband attenuation (also understood as the stopband minimum attenuation) is 20dB.

[0096] (b) Hanning window:

[0097] The window function of the Hanning window can be expressed by formula (3):

[0098]

[0099] Among them, w Hn (n) represents the window function of the Hanning window. When N>>1, the value of the N-1 term in formula (3) can be approximated to N. At this time, the amplitude function of the Hanning window can be expressed by formula (4):

[0100]

[0101] Among them, W Hn (w) represents the amplitude function of the Hanning window, W R (ω) represents the amplitude function of the rectangular window. The amplitude function of the Hanning window consists of three parts, each of which has a different displacement. The three parts can reduce the sidelobe power by canceling each other out, so that the spectrum energy of the Hanning window (which can also be understood as the window spectrum energy) is more concentrated in the main lobe.

[0102] From the window function and amplitude function of the Hanning window, it can be determined that the characteristics of the Hanning window include: the main lobe width is 8π / N, the power of the first side lobe is 30 dB lower than the main lobe power, and the minimum stopband attenuation is 45 dB.

[0103] (c)Hamming window:

[0104] The window function of the Hamming window can be expressed by formula (5):

[0105]

[0106] Among them, wHm (n) represents the window function of the Hamming window. When N>>1, the value of the N-1 term in formula (5) can be approximated to N. At this time, the amplitude function of the Hamming window can be expressed by formula (6):

[0107]

[0108] Among them, W Hm (ω) represents the amplitude function of the Hamming window.

[0109] From the window function and amplitude function of the Hamming window, it can be determined that the characteristics of the Hamming window include: 99.96% of the spectrum energy of the Hamming window is concentrated in the main lobe, the main lobe width is 8π / N, the power of the first side lobe is 40dB lower than the main lobe power, and the minimum stopband attenuation is 55dB.

[0110] (d) Blackman window:

[0111] The window function of the Blackman window can be expressed by formula (7), and the amplitude function can be expressed by formula (8):

[0112]

[0113] Among them, w Bl (n) represents the window function of the Blackman window, W Bl (ω) represents the amplitude function of the Blackman window. The amplitude function of the Blackman window consists of five parts, each of which has a different displacement, and the five parts can reduce the sidelobe power and increase the stopband attenuation by canceling each other.

[0114] From the window function and amplitude function of the Blackman window, it can be determined that the characteristics of the Blackman window include: the main lobe width is 12π / N, the power of the first side lobe is 59 dB lower than the main lobe power, and the minimum stopband attenuation is 74 dB.

[0115] (e)Kaiser-Basel window:

[0116] The window function of the Kaiser-Basel window can be expressed by formula (9):

[0117]

[0118] Among them, w k (n) represents the window function of the Kaiser-Basel window, I0() represents the zero-order first-kind modified Bessel function, α and β represent non-negative real numbers used to adjust the shape of the window (i.e., to select the exchange relationship between the main lobe width and the side lobe attenuation), and Here, the larger β is, the wider the transition band is, the smaller the stop band is, and the greater the stop band attenuation is.

[0119] From the window function of the Kaiser-Basel window, it can be determined that the characteristics of the Kaiser-Basel window are related to the value of the parameter β, and window functions with different characteristics can be obtained by adjusting the value of β.

[0120] It can be seen from the above description that in step 302, the electronic device can design a FIR filter according to the filter requirement information. The specific implementation of designing the FIR filter may include: determining which type of FIR filter (such as low-pass, high-pass, etc.) is needed to process the data to be filtered, determining which window function is used in the FIR filter, and determining the order of the FIR filter; that is, determining the FIR filter from three dimensions: the type of filter, the type of window function, and the order of the filter, so that the determined FIR filter can meet the filter requirement information (such as meeting the stopband attenuation requirements, etc.). In one embodiment, the type of the filter includes one of the following:

[0121] A low-pass filter is a filter that allows low-frequency signals to pass through while attenuating (also understood as shielding or blocking) high-frequency signals;

[0122] A high-pass filter is a filter that allows high-frequency signals to pass through while attenuating low-frequency signals;

[0123] Bandpass filter, that is, a filter that only allows signals within a specific frequency band to pass through, while attenuating signals outside the frequency band;

[0124] A band-stop filter is a filter that only attenuates signals within a specific frequency band while allowing signals outside the frequency band to pass.

[0125] In actual application, after the electronic device determines the type of FIR filter, it can select the window function type used by the FIR filter based on the filter demand information, the properties of the data to be filtered (such as bandwidth information) and processing requirements (such as the requirement to filter out signal interference, reduce spectrum energy leakage, etc.).

[0126] Specifically, the electronic device can select a window function with the narrowest possible main lobe width from the above five window functions according to a preset algorithm, while ensuring that the out-of-band radiation attenuation suppression (which can also be understood as out-of-band suppression) meets the requirements. In this way, since the selected window function has the largest possible stopband attenuation and the smallest possible transition band, by using the FIR filter of the window function to filter the data to be filtered, the out-of-band radiation can be effectively suppressed to meet the corresponding index requirements. Exemplarily, assuming that the out-of-band radiation attenuation suppression requirement is 80dB, the electronic device can select a suitable window function when designing the FIR filter, so as to use the designed FIR filter to filter the data to be filtered. In this way, Figure 4 As shown, the obtained filtered data can meet the requirements of out-of-band radiation attenuation suppression.

[0127] Exemplarily, assuming that the filter requirement information indicates that the filter needs to have a higher stopband attenuation, the electronic device may determine that it is necessary to select a window function with better sidelobe attenuation, such as a Blackman window; or, assuming that the data to be filtered includes a 5G NR signal, the 5G NR signal is a narrowband signal and there is strong interference noise, the electronic device may determine that it is necessary to select a window function with a small sidelobe amplitude, such as a Hanning window, a Hamming window, etc.

[0128] After the electronic device selects the window function type used by the FIR filter, the order of the FIR filter (i.e., the length of the window function) can be determined according to the selected window function type and the filter requirement information. Specifically, the order of the filter can be calculated by formula (10):

[0129]

[0130] Among them, N represents the order of the filter, the value of A is a constant, and the value of A is related to the window function type (for example, when the window function is a rectangular window, A=4π; when the window function is a Hanning window, A=8π), and B represents the transition bandwidth (that is, the difference between the passband frequency and the stopband frequency).

[0131] For example, assuming that the filter requirement information indicates that 80 dB of out-of-band radiation attenuation suppression needs to be met, the electronic device may determine that the FIR filter order is 127.

[0132] In actual application, after determining the second information, in step 303, the electronic device can set the parameters of the FIR filter according to the second information, that is, determine the filter used for filtering.

[0133] After the filter is determined, the electronic device may obtain the data to be filtered, and filter the data to be filtered using the determined filter. That is, in one embodiment, the method may further include:

[0134] The data to be filtered is filtered using the determined filter to obtain filtered data.

[0135] In actual application, when filtering the data to be filtered, the electronic device needs to perform FFT processing on the time domain data to be filtered to obtain frequency domain data.

[0136] Specifically, the electronic device may first perform FFT processing on the time domain data to be filtered, and then use the determined filter to filter the data after the FFT processing.

[0137] Based on this, in one embodiment, filtering the to-be-filtered data using the determined filter to obtain filtered data includes:

[0138] Performing FFT processing on the data to be filtered to obtain frequency domain data to be filtered;

[0139] The filter is used to process the frequency domain data to be filtered to obtain the filtered data.

[0140] Here, illustratively, Figure 5 As shown, the electronic device may include an input parameter configuration module, an FFT module, a FIR filter module and a data output module. Wherein, after the electronic device obtains the first information through the input parameter configuration module, it determines the filter. Afterwards, the electronic device may first use the FFT module to perform FFT processing on the data to be filtered, and input the obtained frequency domain data to be filtered into the FIR filter module. The electronic device may use the N-1 delay devices (N represents the order of the filter) contained in the FIR filter module to delay the frequency domain data to be filtered, and use the parameters of the determined filter to perform weighted accumulation on the delayed data to obtain the filtered data (which can also be understood as output data). The FIR filter module can send the obtained filtered data to the data output module, and the data output module performs parallel-to-serial conversion on the filtered data and outputs it to the subsequent device to facilitate subsequent measurement data processing.

[0141] Of course, for example, Figure 6 As shown, the electronic device may also first utilize the N-1 delay devices (N represents the order of the filter) included in the filter to perform delay processing on the time domain data to be filtered, perform FFT processing on the delayed data, and use the determined filter parameters to perform weighted accumulation on the FFT processed data to obtain the filtered data.

[0142] Based on this, in one embodiment, filtering the to-be-filtered data using the determined filter to obtain filtered data includes:

[0143] Using N delay devices included in the filter, the data to be filtered is delayed to obtain N delayed data, wherein each of the N delayed data has a different delay, and N is the order of the filter;

[0144] Performing FFT processing on the N delayed data and the data to be filtered to obtain N+1 frequency domain data, wherein the N+1 frequency domain data correspond to the N+1 filter coefficients one by one;

[0145] For each frequency domain data, the product of the frequency domain data and the corresponding filter coefficient is calculated to obtain a calculation result;

[0146] The N+1 calculation results are accumulated to obtain the filtered data.

[0147] Here, the above process can also be understood as the electronic device calculating the amplitude-frequency response and phase response characteristics of the baseband time-domain complex signal at each moment, and then performing iterative circular convolution, multiplication and accumulation covering processing on the input data based on the time-fixed delay effect to obtain the filtered data. Specifically, the data after the filter can be expressed by formula (11):

[0148]

[0149] Among them, y(n) represents the filtered time domain data, x(n) represents the time domain data to be filtered, h(n) represents the unit impulse response function of the filter, h(k) represents the filter coefficient corresponding to the time delay k, and x(Nk) represents the data of the time domain data to be filtered after delay processing and FFT processing. Specifically, the delayed data can be expressed by formula (12):

[0150] x′(n)=x(n+D -N ) (12)

[0151] Among them, x′(n) represents the time domain data after delay processing, D -N Represents the time delay matrix factor, which can be set according to actual needs.

[0152] In actual application, the electronic device can analyze the filtered data to obtain analysis results. Figure 7 As shown, the electronic device can analyze and obtain the filtered data power spectrum; at the same time, Figure 8As shown, the electronic device can demodulate 5G NR signals of multiple different bandwidths (which can also be understood as multi-band modulation) to determine the EVM corresponding to data of different bandwidths. The smaller the EVM corresponding to the filtered data, the more accurate the demodulation result.

[0153] In actual application, the electronic device can adjust the window function type and order of the filter according to the analysis results corresponding to the filtered data, and redesign the filter with better performance (such as better out-of-band suppression performance), and then use the redesigned filter to filter subsequent data.

[0154] Based on this, in one embodiment, the method may further include:

[0155] Using the filtered data, updating the second information;

[0156] The updated second information is used to re-determine the filter used to filter the subsequent data to be filtered.

[0157] Exemplarily, it is assumed that the electronic device analyzes the filtered data to obtain the corresponding EVM. When the EVM is greater than the preset threshold, the electronic device can determine that the filtering performance needs to be improved, and adjust the filter requirement information, such as increasing the out-of-band suppression requirement, etc., so as to determine the window function type and filter order that meet the adjusted filter requirement information according to the preset strategy, and determine the updated filter. In this way, the electronic device can use the updated filter to filter the subsequent data to be filtered, which can effectively reduce the EVM corresponding to the filtered data, that is, improve the filtering performance.

[0158] The filter determination method provided in the embodiment of the present application determines the first information of the data to be filtered, the first information is related to the channel bandwidth, frequency band range, subcarrier spacing and duplex multiplexing mode; using the first information, the second information is determined, the second information includes the type of filter, the type of window function and the order of the filter; using the second information, the filter used to filter the data to be filtered is determined. The scheme provided in the embodiment of the present application dynamically designs the type of filter, the type of window function and the order of the filter according to the channel bandwidth, frequency band range, subcarrier spacing and duplex multiplexing mode of the data to be filtered (which can also be understood as the signal to be filtered). The design method is flexible and simple, and the filter order is small and the transition band is narrow, which can realize high-precision demodulation analysis.

[0159] In order to implement the method of the embodiment of the present application, the embodiment of the present application also provides a filter determination device, which is arranged on an electronic device, such as Fig. 9 As shown, the device comprises:

[0160] A first determining unit 901 is used to determine first information of the data to be filtered, where the first information is related to the channel bandwidth, frequency band range, subcarrier spacing, and duplex multiplexing mode;

[0161] The second determination unit 902 is used to determine second information using the first information, where the second information includes the type of filter, the type of window function and the order of the filter; and to determine a filter for filtering the data to be filtered using the second information.

[0162] In one embodiment, the second determining unit 902 is specifically configured to:

[0163] Determine filter requirement information corresponding to the data to be filtered using the first information;

[0164] The second information is determined using the filter requirement information.

[0165] In one embodiment, the device may further include:

[0166] The filtering unit is used to filter the data to be filtered using a determined filter to obtain filtered data.

[0167] In one embodiment, the second determining unit 902 is further configured to:

[0168] Using the filtered data, updating the second information;

[0169] The updated second information is used to re-determine the filter used to filter the subsequent data to be filtered.

[0170] In one embodiment, the filtering unit is specifically used for:

[0171] Using N delay devices included in the filter, the data to be filtered is delayed to obtain N delayed data, wherein each of the N delayed data has a different delay, and N is the order of the filter;

[0172] Performing FFT processing on the N delayed data and the data to be filtered to obtain N+1 frequency domain data, wherein the N+1 frequency domain data correspond to the N+1 filter coefficients one by one;

[0173] For each frequency domain data, the product of the frequency domain data and the corresponding filter coefficient is calculated to obtain a calculation result;

[0174] The N+1 calculation results are accumulated to obtain the filtered data.

[0175] In one embodiment, the filtering unit is specifically used for:

[0176] Performing FFT processing on the data to be filtered to obtain frequency domain data to be filtered;

[0177] The filter is used to process the frequency domain data to be filtered to obtain the filtered data.

[0178] In actual application, the first determination unit 901 and the second determination unit 902 may be implemented by a processor in the filter determination device, and the filtering unit may be implemented by the processor in the filter determination device in combination with a communication interface.

[0179] It should be noted that: the filter determination device provided in the above embodiment only uses the division of the above program units as an example when performing filter determination. In practical applications, the above processing can be assigned to different program units as needed, that is, the internal structure of the device is divided into different program units to complete all or part of the processing described above. In addition, the filter determination device provided in the above embodiment and the filter determination method embodiment belong to the same concept, and the specific implementation process is detailed in the method embodiment, which will not be repeated here.

[0180] Based on the hardware implementation of the above program modules, and in order to implement the method of the embodiment of the present application, the embodiment of the present application also provides an electronic device, such as Fig.10 As shown, the electronic device 1000 includes:

[0181] Communication interface 1001, capable of exchanging information with other devices;

[0182] The processor 1002 is connected to the communication interface 1001 to implement information interaction with other devices, and is used to execute the method provided by one or more of the above technical solutions when running the computer program;

[0183] The computer program is stored in the memory 1003 .

[0184] Specifically, the processor 1002 is configured to:

[0185] Determine first information of the data to be filtered, wherein the first information is related to the channel bandwidth, frequency band range, subcarrier spacing and duplex multiplexing mode; use the first information to determine second information, wherein the second information includes the type of filter, the type of window function and the order of the filter; and use the second information to determine the filter used to filter the data to be filtered.

[0186] In one embodiment, the processor 1002 is specifically configured to:

[0187] Determine filter requirement information corresponding to the data to be filtered using the first information;

[0188] The second information is determined using the filter requirement information.

[0189] In one embodiment, the processor 1002 is further configured to:

[0190] The communication interface 1001 is used to filter the data to be filtered using a determined filter to obtain filtered data.

[0191] In one embodiment, the processor 1002 is further configured to:

[0192] The updated second information is used to re-determine the filter used to filter the subsequent data to be filtered.

[0193] In one embodiment, the processor 1002 is specifically configured to:

[0194] Using N delay devices included in the filter, the data to be filtered is delayed to obtain N delayed data, wherein each of the N delayed data has a different delay, and N is the order of the filter;

[0195] Performing FFT processing on the N delayed data and the data to be filtered to obtain N+1 frequency domain data, wherein the N+1 frequency domain data correspond to the N+1 filter coefficients one by one;

[0196] For each frequency domain data, the product of the frequency domain data and the corresponding filter coefficient is calculated to obtain a calculation result;

[0197] The N+1 calculation results are accumulated to obtain the filtered data.

[0198] In one embodiment, the processor 1002 is specifically configured to:

[0199] Performing FFT processing on the data to be filtered to obtain frequency domain data to be filtered;

[0200] The filter is used to process the frequency domain data to be filtered to obtain the filtered data.

[0201] It should be noted that the specific processing process of the processor 1002 and the communication interface 1001 can be understood by referring to the above method.

[0202] Of course, in actual application, the various components in the electronic device 1000 are coupled together through the bus system 1004. It can be understood that the bus system 1004 is used to realize the connection and communication between these components. In addition to the data bus, the bus system 1004 also includes a power bus, a control bus, and a status signal bus. However, for the sake of clarity, Fig.10 Various buses are labeled as bus system 1004 .

[0203] The memory 1003 in the embodiment of the present application is used to store various types of data to support the operation of the electronic device 1000. Examples of such data include: any computer program used to operate on the electronic device 1000.

[0204] The method disclosed in the above embodiment of the present application can be applied to the processor 1002, or implemented by the processor 1002. The processor 1002 may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method can be completed by an integrated logic circuit of the hardware in the processor 1002 or an instruction in the form of software. The above-mentioned processor 1002 may be a general-purpose processor, a digital signal processor (DSP, DigitalSignal Processor), or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. The processor 1002 can implement or execute the methods, steps and logic block diagrams disclosed in the embodiments of the present application. A general-purpose processor may be a microprocessor or any conventional processor, etc. In combination with the steps of the method disclosed in the embodiment of the present application, it can be directly embodied as a hardware decoding processor to execute, or it can be executed by a combination of hardware and software modules in the decoding processor. The software module may be located in a storage medium, which is located in the memory 1003, and the processor 1002 reads the information in the memory 1003 and completes the steps of the above method in combination with its hardware.

[0205] In an exemplary embodiment, the electronic device 1000 can be implemented by one or more application specific integrated circuits (ASIC), DSP, programmable logic device (PLD), complex programmable logic device (CPLD), field programmable gate array (FPGA), general processor, controller, microcontroller (MCU), microprocessor, or other electronic components to execute the aforementioned method.

[0206] It can be understood that the memory (memory 1003) of the embodiment of the present application can be a volatile memory or a non-volatile memory, and can also include both volatile and non-volatile memories. Among them, the non-volatile memory can be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), a magnetic random access memory (FRAM), a ferromagnetic random access memory, a flash memory, a magnetic surface memory, an optical disc, or a compact disc read-only memory (CD-ROM); the magnetic surface memory can be a disk memory or a tape memory. The volatile memory can be a random access memory (RAM), which is used as an external cache. By way of example and not limitation, many forms of RAM are available, such as static random access memory (SRAM), synchronous static random access memory (SSRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDRSDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link dynamic random access memory (SLDRAM, SyncLink Dynamic Random Access Memory), and direct RAMbus random access memory (DRRAM, Direct Rambus Random Access Memory).The memories described in the embodiments of the present application are intended to include, but are not limited to, these and any other suitable types of memories.

[0207] In an exemplary embodiment, the present application also provides a storage medium, namely a computer storage medium, specifically a computer-readable storage medium, for example, including a memory 1003 storing a computer program, and the computer program can be executed by a processor 1002 of an electronic device 1000 to complete the steps of the aforementioned method. The computer-readable storage medium can be a memory such as FRAM, ROM, PROM, EPROM, EEPROM, Flash Memory, magnetic surface storage, optical disk, or CD-ROM.

[0208] In an exemplary embodiment, the embodiment of the present application further provides a computer program product, including a computer program, and the above-mentioned computer program can be executed by the processor 1002 of the electronic device 1000 to complete the steps of the above-mentioned method.

[0209] It should be noted that: "first", "second", etc. are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence.

[0210] In addition, the technical solutions described in the embodiments of the present application can be combined arbitrarily without conflict.

[0211] The above description is only a preferred embodiment of the present application and is not intended to limit the protection scope of the present application.

Claims

1. A filter determination method, characterized in that: include: Determine first information of the data to be filtered, where the first information is related to the channel bandwidth, frequency band range, subcarrier spacing, and duplex multiplexing mode; Determine second information using the first information, where the second information includes a type of filter, a type of window function, and an order of the filter; The second information is used to determine a filter for filtering the data to be filtered.

2. The method according to claim 1, characterized in that: The filter type includes one of the following: Low pass filter; High pass filter; Bandpass filter; Band-stop filter.

3. The method according to claim 1, characterized in that: The using the first information to determine the second information includes: Determine filter requirement information corresponding to the data to be filtered using the first information; The second information is determined using the filter requirement information.

4. The method according to claim 3, characterized in that The filter requirement information includes one or more of the following: Signal sampling frequency; Nyquist frequency; Passband cutoff frequency; Stopband cutoff frequency; Passband ripple; Stopband attenuation.

5. The method according to any one of claims 1 to 4, characterized in that: The method further comprises: The data to be filtered is filtered using the determined filter to obtain filtered data.

6. The method according to claim 5, characterized in that The method further comprises: Using the filtered data, updating the second information; The updated second information is used to re-determine the filter used to filter the subsequent data to be filtered.

7. The method according to claim 5, characterized in that The step of filtering the data to be filtered by using the determined filter to obtain filtered data includes: Using N delay devices included in the filter, the data to be filtered is delayed to obtain N delayed data, wherein each of the N delayed data has a different delay, and N is the order of the filter; Performing fast Fourier transform (FFT) processing on the N delayed data and the data to be filtered to obtain N+1 frequency domain data, wherein the N+1 frequency domain data correspond to the N+1 filter coefficients one by one; For each frequency domain data, the product of the frequency domain data and the corresponding filter coefficient is calculated to obtain a calculation result; The N+1 calculation results are accumulated to obtain the filtered data.

8. The method according to claim 5, characterized in that The step of filtering the data to be filtered by using the determined filter to obtain filtered data includes: Performing FFT processing on the data to be filtered to obtain frequency domain data to be filtered; The filter is used to process the frequency domain data to be filtered to obtain the filtered data.

9. A filter determination device, characterized in that: include: A first determining unit, configured to determine first information of the data to be filtered, wherein the first information is related to a channel bandwidth, a frequency band range, a subcarrier spacing, and a duplex multiplexing mode; A second determining unit, configured to determine second information using the first information, wherein the second information includes a type of filter, a type of window function, and an order of the filter; And using the second information, determining a filter for filtering the data to be filtered.

10. An electronic device, characterized in that: include: a processor and a memory for storing a computer program capable of being executed on the processor, Wherein, when the processor is used to run the computer program, it executes the steps of the method described in any one of claims 1 to 8.

11. A storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 8 are implemented.

12. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 8 are implemented.

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