Efficient signal sampling rate transformation method and device based on discrete Fourier transform
By using the discrete Fourier transform method, the hardware overhead and time delay problems of high-multiple downsampling in existing technologies are solved, achieving efficient signal sampling rate transformation, reducing errors and improving processing efficiency.
Patent Information
- Application Number
- CN202511461067.X
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-10-14
- Publication Date
- 2026-02-17
AI Technical Summary
Existing technologies suffer from significant hardware overhead and latency issues when performing high-rate downsampling, especially in 6G communication where efficient signal sampling rate conversion methods are needed.
The method based on Discrete Fourier Transform is adopted. The signal is transformed into a spectrum by DFT, the high-frequency part is discarded during downsampling, and zeros are added during upsampling to achieve consistency of the number of spectrum points. Then, IDFT is performed, thus avoiding the use of filters.
It achieves efficient signal sampling rate conversion, reduces errors, improves processing efficiency, and reduces hardware overhead and latency.
Smart Images
Figure CN121547048A_ABST
Abstract
Description
Technical Field
[0001] The embodiments disclosed herein relate to the field of digital signal processing, and more specifically to an efficient signal sampling rate conversion method and apparatus based on discrete Fourier transform. Background Technology
[0002] The upcoming 6G (6th Generation Mobile Communication Technology) requires significantly greater transmission bandwidth than 5G (5th Generation Mobile Communication Technology), which means a higher sampling rate is needed for digital data acquisition. For a frequency-division multiplexed broadband signal, composed of narrowband signals from different terminals, each terminal has a different frequency band of interest. In this case, channelization processing is often required, filtering out the necessary narrowband signals. This reduces the signal bandwidth, necessitating downsampling to save storage resources. However, the downsampling factor can be very large. For example, if the front-end sampling rate is 20 GHz, and a narrowband signal has a bandwidth of 40 kHz, a sampling rate of 100 kHz would be sufficient, requiring a 20,000-fold downsampling. Therefore, an efficient method for sampling rate transformation is needed.
[0003] Currently, the mainstream method for downsampling at high sampling rates mainly employs a cascaded downsampling approach combining a Cascaded Integrator Comb (CIC) filter, a Half-Band Filter (HB), and a Finite Impulse Response (FIR) filter. Specifically, the comb filter first performs high-rate downsampling at the front end. Then, multiple cascaded half-band filters perform power-of-two downsampling. Finally, a Finite Impulse Response (FIR) filter transforms the sample rate to the target rate. However, while the aforementioned methods utilize low-overhead hardware filters, significant overhead remains for high-rate changes, and the multi-stage filtering structure increases overall latency. Summary of the Invention
[0004] The summary portion of this disclosure is intended to provide a brief overview of the concepts, which will be described in detail in the detailed description portion. This summary portion is not intended to identify key or essential features of the claimed technical solutions, nor is it intended to limit the scope of the claimed technical solutions.
[0005] Some embodiments of this disclosure propose an efficient signal sampling rate conversion method and apparatus based on discrete Fourier transform to solve the technical problems mentioned in the background section above.
[0006] In a first aspect, some embodiments of this disclosure provide an efficient signal sampling rate conversion method based on Discrete Fourier Transform (DFT). The method includes: acquiring a target signal, wherein the target signal is a signal to be converted at a sampling rate; performing a DFT on the target signal to obtain a first signal spectrum, wherein the first signal spectrum is the signal spectrum corresponding to the target signal; generating a second signal spectrum based on an interpolation factor, a decimation factor, and the first signal spectrum, wherein the second signal spectrum is the signal spectrum corresponding to the output signal; and performing an inverse DFT on the second signal spectrum to obtain an output signal.
[0007] Secondly, some embodiments of this disclosure provide an efficient signal sampling rate conversion device based on Discrete Fourier Transform (DFT). The device includes: an acquisition unit configured to acquire a target signal, wherein the target signal is a signal to be converted at a signal sampling rate; a DFT unit configured to perform a DFT on the target signal to obtain a first signal spectrum, wherein the first signal spectrum is the signal spectrum corresponding to the target signal; a generation unit configured to generate a second signal spectrum based on an interpolation factor, a decimation factor, and the first signal spectrum, wherein the second signal spectrum is the signal spectrum corresponding to an output signal; and an inverse DFT unit configured to perform an inverse DFT on the second signal spectrum to obtain an output signal.
[0008] Thirdly, some embodiments of this disclosure provide an electronic device, including: one or more processors; and a storage device having one or more programs stored thereon, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the method described in any implementation of the first aspect above.
[0009] Fourthly, some embodiments of this disclosure provide a computer-readable medium having a computer program stored thereon, wherein the program, when executed by a processor, implements the method described in any of the implementations of the first aspect above.
[0010] The embodiments disclosed above have the following beneficial effects: By performing a DFT (Discrete Fourier Transform) on the signal to transform it to the spectrum, the high-frequency components of the signal spectrum are discarded during downsampling, and zeros are padded to the high-frequency components during upsampling to make the number of DFT points consistent with the number of points after the sampling rate transformation. Then, an IDFT (Inverse Discrete Fourier Transform) is performed to achieve sampling rate transformation. Since each processing only changes the high-frequency components of the signal, the introduced error is small. At the same time, DFT itself is supported by FFT (Fast Fourier Transform) as a fast algorithm, so within a certain error tolerance range, the present invention can achieve efficient sampling rate transformation. Attached Figure Description
[0011] The above and other features, advantages, and aspects of the embodiments of this disclosure will become more apparent from the accompanying drawings and the following detailed description. Throughout the drawings, the same or similar reference numerals denote the same or similar elements. It should be understood that the drawings are schematic, and elements are not necessarily drawn to scale.
[0012] Figure 1 This is a flowchart of some embodiments of the efficient signal sampling rate transformation method based on discrete Fourier transform according to this disclosure;
[0013] Figure 2 This is a schematic diagram of the spectrum of a discrete-time signal;
[0014] Figure 3 It is a comparison chart of the spectrum before and after interpolation;
[0015] Figure 4 It is a comparison chart of the spectrum before and after extraction;
[0016] Figure 5 This is a schematic diagram of the error results;
[0017] Figure 6 This is a schematic diagram of another error result;
[0018] Figure 7 This is a schematic diagram of the structure of some embodiments of the high-efficiency signal sampling rate conversion device based on the discrete Fourier transform according to the present disclosure;
[0019] Figure 8 This is a schematic diagram of the structure of an electronic device suitable for implementing some embodiments of the present disclosure. Detailed Implementation
[0020] Embodiments of this disclosure will now be described in more detail with reference to the accompanying drawings. While some embodiments of this disclosure are shown in the drawings, it should be understood that this disclosure can be implemented in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided to provide a more thorough and complete understanding of this disclosure. It should be understood that the accompanying drawings and embodiments of this disclosure are for illustrative purposes only and are not intended to limit the scope of protection of this disclosure.
[0021] It should also be noted that, for ease of description, only the parts relevant to the invention are shown in the accompanying drawings. Unless otherwise specified, the embodiments and features described in this disclosure can be combined with each other.
[0022] It should be noted that the concepts of "first" and "second" mentioned in this disclosure are used only to distinguish different devices, modules or units, and are not used to limit the order of functions performed by these devices, modules or units or their interdependencies.
[0023] It should be noted that the terms "a" and "a plurality of" used in this disclosure are illustrative rather than restrictive, and those skilled in the art should understand that, unless otherwise expressly indicated in the context, they should be understood as "one or more".
[0024] The names of messages or information exchanged between multiple devices in the embodiments of this disclosure are for illustrative purposes only and are not intended to limit the scope of such messages or information.
[0025] This disclosure will now be described in detail with reference to the accompanying drawings and embodiments.
[0026] refer to Figure 1 The flowchart 100 illustrates some embodiments of the efficient signal sampling rate conversion method based on Discrete Fourier Transform according to this disclosure. This efficient signal sampling rate conversion method based on Discrete Fourier Transform includes the following steps:
[0027] Step 101: Obtain the target signal.
[0028] In some embodiments, the execution subject (e.g., a computing device) of the efficient signal sampling rate transformation method based on discrete Fourier transform can acquire the target signal via a wired or wireless connection.
[0029] The target signal can be the signal whose sampling rate needs to be transformed.
[0030] It should be noted that the aforementioned wireless connection methods may include, but are not limited to, 3G / 4G / 5G connections, WiFi connections, Bluetooth connections, WiMAX connections, Zigbee connections, UWB (Ultra Wide Band) connections, and other currently known or future wireless connection methods.
[0031] It should be noted that the aforementioned computing devices can be either hardware or software. When the computing device is hardware, it can be implemented as a distributed cluster consisting of multiple servers or terminal devices, or as a single server or a single terminal device. When the computing device is software, it can be installed on the hardware devices listed above. It can be implemented as, for example, multiple software programs or software modules used to provide distributed services, or as a single software program or software module. No specific limitations are made here.
[0032] Optionally, the target signal is obtained by segmentation using either the overlap-preservation method or the overlap-addition method.
[0033] In practice, signal processing often doesn't wait for all data to be received before changing the sampling rate, firstly because it's inefficient in terms of time, and secondly because it involves a large amount of computation. Therefore, for long sequences of signals, it's often necessary to segment them (change the sampling rate) and then concatenate them in time sequence after processing.
[0034] As an example, taking the overlap-preserving method, for the case of... The signal at each signal point (sampling point) is divided into... Each signal segment consists of segmented signals. It consists of 1 signal point. For each Each signal segment is taken forward from the previous signal segment. Each signal point is concatenated with a signal segment to obtain a concatenated signal segment. A DFT sampling rate transform is then performed on this concatenated signal segment to obtain a transformed signal segment. At this point, the sampling rate of the transformed signal segment is reduced to the original value. Times. Among them, This indicates the interpolation factor. This indicates the decimation factor. Then, the first part of the transformed signal segment is discarded. By taking a number of signal points and reassembling them in time sequence, a complete DFT sampling rate transformation for long signal sequences can be achieved.
[0035] Step 102: Perform a discrete Fourier transform on the target signal to obtain the spectrum of the first signal.
[0036] In some embodiments, the aforementioned execution entity may perform a discrete Fourier transform on the target signal to obtain a first signal spectrum.
[0037] Wherein, the first signal spectrum is the signal spectrum corresponding to the target signal.
[0038] In some optional implementations of certain embodiments, the aforementioned execution entity may perform a discrete Fourier transform on the target signal to obtain a first signal spectrum, including:
[0039] Step S1: Calculate the number of samples for the target signal using the following formula. The discrete Fourier transform yields the spectrum of the first signal:
[0040] ,
[0041] in, Indicates the signal value index. Indicates the number of samples. Represents the imaginary unit. Indicates the signal value index in the target signal The corresponding signal value, Indicates frequency index, Indicates the frequency index in the spectrum of the first signal. The corresponding frequency components.
[0042] Step 103: Generate the second signal spectrum based on the interpolation ratio, decimation ratio, and the first signal spectrum.
[0043] In some embodiments, the above execution can generate a second signal spectrum based on the interpolation rate, the decimation rate, and the first signal spectrum.
[0044] The second signal spectrum is the signal spectrum corresponding to the output signal.
[0045] In some optional implementations of some embodiments, the execution entity generates a second signal spectrum based on the interpolation rate, the decimation rate, and the first signal spectrum, including:
[0046] Step S1: In response to the interpolation rate being greater than the decimation rate, the second signal spectrum is generated based on the first signal spectrum using the following formula:
[0047] .
[0048] in, Indicates the interpolation factor. Indicates the extraction multiplier. Indicates the frequency index in the spectrum of the second signal. The corresponding frequency components, This indicates rounding down to the nearest integer.
[0049] Step S2: In response to the interpolation rate being less than the decimation rate, the second signal spectrum is generated based on the first signal spectrum using the following formula:
[0050] .
[0051] Step 104: Perform an inverse discrete Fourier transform on the spectrum of the second signal to obtain the output signal.
[0052] In some embodiments, the aforementioned execution entity may perform an inverse discrete Fourier transform on the spectrum of the second signal to obtain an output signal.
[0053] In some optional implementations of some embodiments, the aforementioned execution entity performs an inverse discrete Fourier transform on the spectrum of the second signal to obtain an output signal, including:
[0054] The output signal is obtained by performing an inverse discrete Fourier transform on the spectrum of the second signal using the following formula:
[0055] .
[0056] in, Indicates the signal value index. Indicates the signal value index in the output signal. The corresponding signal value.
[0057] In practice, for a discrete-time signal, its corresponding spectrum must be infinitely wide. Therefore, we can assume that the digital spectral bandwidth of the signal is fully occupied. For example, see Figure 2 The diagram shown illustrates the spectrum of a discrete-time signal. The discrete-time signal consists of a positive spectrum and a negative spectrum, with its corresponding digital spectral bandwidth fully occupied. Assuming that for the sampling rate transformation of a discrete-time signal, the first step is to perform... Interpolation by a factor of 1, followed by filtering, and finally... The decimation is multiplied by a factor of two. Interpolation causes the period of the analog spectrum of a discrete-time signal to increase; for example, see [reference needed]. Figure 3 The spectrum comparison before and after interpolation shown is equivalent to "both the positive and negative spectra narrowing" in the digital spectrum. The high-frequency components (high-frequency parts) missing between the narrowed positive and negative spectra are the image spectrum caused by interpolation. The conventional method is to eliminate the influence of the image spectrum using an image filter. Ideally, the image spectrum component should be zero; therefore, the process of "interpolation + image filtering" is equivalent to... The input signal to the point DFT is padded with zeros in the high-frequency components. Complete the points to Then, performing IDFT completes the interpolation process. Furthermore, decimation reduces the period of the analog spectrum of the discrete-time signal, potentially causing aliasing of the periodic spectral components. For example, see... Figure 4The spectrum comparison diagram before and after decimation shows that, in the digital spectrum, both positive and negative frequencies become wider, while high-frequency components become aliased. The traditional method is to filter out the high-frequency components of the signal using an anti-aliasing filter before decimation to ensure that the decimated spectrum does not alias. Ideally, the high-frequency components of the signal should be completely filtered out; therefore, the process of "anti-aliasing filtering + decimation" is equivalent to decimating the signal in the frequency domain. The input signal of a point DFT discards high-frequency components and retains only the high-frequency components. By performing IDFT on a low-frequency point, the decimation process can be completed. Therefore, based on the spectral characteristics during sampling rate transformation, this disclosure designs a signal sampling rate transformation algorithm based on Discrete Fourier Transform (DFT). Since it eliminates the need to set up a filter for sampling rate transformation, it directly increases or decreases the number of points in the signal spectrum by analyzing the impact of sampling rate transformation on the signal spectrum, thereby achieving efficient sampling rate transformation.
[0058] Experimental simulation
[0059] Simulation was performed using MATLAB software. The simulation conditions were: single-tone signal, carrier frequency of 900 kHz, and input sampling rate of 5 MHz. A total of [number] signals were generated. 1000 data points per segment. Downsampled to 4 MHz, 1000 data points per segment, with 20 data points retained forward. See also Figure 5 The diagram showing the error results illustrates the error at various (data) points in the time domain between the single-tone spectrum under rate variation and the ideal single-tone spectrum obtained using the algorithm disclosed herein. Then, upsampling is performed to 7 MHz, with 1000 data points per segment, and 20 data points are retained forward. See [link to documentation]. Figure 6 Another error result diagram is shown, illustrating the error results at various (data) points in the time domain between the single-tone spectrum under rate variation and the single-tone spectrum under ideal conditions using the algorithm disclosed herein. Through simulations of downsampling and upsampling at rational multiples, analysis reveals that the error before and after the sampling rate transformation is small, indicating that the algorithm disclosed herein can achieve efficient arbitrary rate transformation at rational multiples.
[0060] Further reference Figure 7 As an implementation of the methods shown in the above figures, this disclosure provides some embodiments of an efficient signal sampling rate conversion device based on discrete Fourier transform. These device embodiments are similar to... Figure 1 Corresponding to the method embodiments shown, this efficient signal sampling rate conversion device based on discrete Fourier transform can be specifically applied to various electronic devices.
[0061] like Figure 7As shown, a high-efficiency signal sampling rate conversion device 700 based on discrete Fourier transform in some embodiments includes: an acquisition unit 701, a discrete Fourier transform unit 702, a generation unit 703, and an inverse discrete Fourier transform unit 704. The acquisition unit 701 is configured to acquire a target signal, wherein the target signal is the signal to be converted at the signal sampling rate. The discrete Fourier transform unit 702 is configured to perform a discrete Fourier transform on the target signal to obtain a first signal spectrum, wherein the first signal spectrum is the signal spectrum corresponding to the target signal. The generation unit 703 is configured to generate a second signal spectrum based on an interpolation factor, a decimation factor, and the first signal spectrum, wherein the second signal spectrum is the signal spectrum corresponding to the output signal. The inverse discrete Fourier transform unit 704 is configured to perform an inverse discrete Fourier transform on the second signal spectrum to obtain the output signal.
[0062] It is understandable that the units and references described in this high-efficiency signal sampling rate conversion device 700 based on discrete Fourier transform are related. Figure 1 The steps in the described method correspond to each other. Therefore, the operations, features, and beneficial effects described above for the method also apply to the high-efficiency signal sampling rate conversion device 700 based on discrete Fourier transform and the units contained therein, and will not be repeated here.
[0063] The following is for reference. Figure 8 It illustrates a schematic diagram of the structure of an electronic device (e.g., a computing device) suitable for implementing some embodiments of the present disclosure. Figure 8 The electronic device shown is merely an example and should not be construed as limiting the functionality or scope of the embodiments of this disclosure. Figure 8 As shown, the computer device includes a processor, memory, and a network interface connected via a system bus. The memory may include a non-volatile storage medium and internal memory. The non-volatile storage medium may store an operating system and a computer program. The computer program includes program instructions that, when executed, cause the processor to perform any of the methods described above. The processor provides computational and control capabilities to support the operation of the entire computer device. The internal memory provides an environment for the execution of the computer program in the non-volatile storage medium; when executed by the processor, the computer program causes the processor to perform any of the methods described above. The network interface is used for network communication, such as sending assigned tasks. Those skilled in the art will understand that... Figure 8 The structure shown is merely a block diagram of a portion of the structure related to the present disclosure and does not constitute a limitation on the computer device to which the present disclosure is applied. A specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.
[0064] It should be understood that the processor can be a Central Processing Unit (CPU), but it can also be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. Among these, a general-purpose processor can be a microprocessor or any conventional processor.
[0065] In one embodiment, the processor is configured to run a computer program stored in a memory to perform the following steps: acquiring a target signal, wherein the target signal is a signal to be subjected to signal sampling rate transformation; performing a discrete Fourier transform on the target signal to obtain a first signal spectrum, wherein the first signal spectrum is the signal spectrum corresponding to the target signal; generating a second signal spectrum based on the interpolation rate, the decimation rate, and the first signal spectrum, wherein the second signal spectrum is the signal spectrum corresponding to the output signal; and performing an inverse discrete Fourier transform on the second signal spectrum to obtain the output signal.
[0066] This disclosure also provides a computer-readable storage medium storing a computer program, the computer program including program instructions, and the method implemented when the program instructions are executed can be referred to the various embodiments of the methods described above.
[0067] The aforementioned computer-readable storage medium may be an internal storage unit of the computer device described in the foregoing embodiments, such as the hard disk or memory of the computer device. Alternatively, the aforementioned computer-readable storage medium may be an external storage device of the computer device, such as a plug-in hard disk, SmartMedia Card (SMC), Secure Digital (SD) card, or Flash Card equipped on the computer device.
[0068] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or system. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or system that includes that element.
[0069] The above description is merely a selection of preferred embodiments of this disclosure and an explanation of the technical principles employed. Those skilled in the art should understand that the scope of the invention involved in the embodiments of this disclosure is not limited to technical solutions formed by specific combinations of the above-described technical features, but should also cover other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the above-described inventive concept. For example, technical solutions formed by substituting the above-described features with (but not limited to) technical features with similar functions disclosed in the embodiments of this disclosure.
Claims
1. A high-efficiency signal sampling rate conversion method based on discrete Fourier transform, characterized by, The method comprises: obtaining a target signal, wherein the target signal is a signal to be subjected to signal sampling rate conversion; performing discrete Fourier transform on the target signal to obtain a first signal spectrum, wherein the first signal spectrum is a signal spectrum corresponding to the target signal; generating a second signal spectrum according to an interpolation factor, an extraction factor and the first signal spectrum, wherein the second signal spectrum is a signal spectrum corresponding to an output signal; performing inverse discrete Fourier transform on the second signal spectrum to obtain the output signal.
2. The method of claim 1, wherein, The method comprises: The target signal is subjected to a discrete Fourier transform of a number of samples to obtain a first signal spectrum by the following equation: ， wherein denotes a signal value index, denotes a number of samples, denotes an imaginary unit, denotes a signal value index in a target signal a corresponding signal value, denotes a frequency index, denotes a frequency index in a first signal spectrum a corresponding frequency component.
3. The method of claim 2, wherein, The method comprises: In response to the interpolation factor being greater than the extraction factor, the second signal spectrum is generated according to the first signal spectrum by the following formula: ， wherein, denotes an interpolation factor, denotes an extraction factor, denotes a frequency index in the second signal spectrum corresponding frequency component, denotes a floor function.
4. The method of claim 3, wherein, The method comprises: In response to the interpolation factor being less than the extraction factor, the second signal spectrum is generated according to the first signal spectrum by the following formula: 。 5. The method of claim 4, wherein, The method comprises: The output signal is obtained by performing inverse discrete Fourier transform on the second signal spectrum by the following formula: ， wherein, represents a signal value index, represents a signal value index in the output signal the corresponding signal value.
6. The method of claim 5, wherein, The target signal is obtained by segmenting the target signal by the overlap-save method or the overlap-add method.
7. A high-efficiency signal sampling rate conversion apparatus based on a discrete Fourier transform, characterized by comprising: The method comprises: obtaining a target signal, wherein the target signal is a signal to be subjected to signal sampling rate conversion; performing discrete Fourier transform on the target signal to obtain a first signal spectrum, wherein the first signal spectrum is a signal spectrum corresponding to the target signal; generating a second signal spectrum according to an interpolation factor, an extraction factor and the first signal spectrum, wherein the second signal spectrum is a signal spectrum corresponding to an output signal; performing inverse discrete Fourier transform on the second signal spectrum to obtain the output signal.
8. An electronic device, comprising: The method comprises: one or more processors; a storage device having one or more programs stored thereon; when the one or more programs are executed by the one or more processors, the one or more processors implement the method according to any one of claims 1 to 6.
9. A computer readable medium characterized by a computer program stored thereon, wherein the computer program is executed by a processor to implement the method according to any one of claims 1 to 6.