An audio data stream compression method based on OFDM modulation

Abstract

The present invention discloses an audio data stream compression method based on OFDM modulation, which relates to the field of signal technology, including step S1: using multi-channel coding to reduce distortion of the original audio signal; step S2: using discrete cosine transform to process the sampled signal frame by frame and output DCT coefficients according to different channels, thereby dividing the original audio signal into a plurality of subcarrier signals; step S3: performing inverse discrete Fourier transform on the subcarrier signal, converting the frequency domain data into time domain OFDM symbols and performing a second multi-channel coding; step S4: presetting a reference audio signal and setting a matching reference crosstalk attenuation ratio, converting the time domain OFDM symbols into a modified audio signal; step S5: calculating the modified crosstalk attenuation ratio of the modified audio signal and comparing it with the reference crosstalk attenuation ratio. The present invention can reduce crosstalk caused by inconsistent coding and has the advantages and beneficial effects of effectively taking into account the control of crosstalk between channels when using multi-channel audio coding.

Description

Technical Field

[0001] The present invention relates to the field of signal technology, and in particular to an audio data stream compression method based on OFDM modulation. Background Art

[0002] In modern audio processing, multi-channel audio coding is widely used for the transmission and storage of high-dynamic-range audio. This coding method decomposes audio signals into multiple channels, providing rich spatial perception and sound quality. However, in high-dynamic-range (HDR) audio processing, multi-channel coding faces the problem of dynamic range compression distortion (DGR). DGR refers to the compression of the signal's dynamic range due to coding limitations when processing audio signals with a wide dynamic range, resulting in a loss of detail and layering in the audio. Currently, multi-channel audio coding is the primary method used to mitigate DGR. Existing multi-channel audio coding methods are prone to inter-channel crosstalk in HDR audio. Signal aliasing and interference between channels significantly impact the spatial positioning and overall sound quality of the audio. Specifically, the audio content of each channel affects each other during the encoding or decoding process, resulting in the mixing of previously independent channel information, thereby impairing the audio's spatial perception and clarity. Existing multi-channel audio coding technologies lack a method to significantly reduce inter-channel crosstalk when processing HDR audio. Summary of the Invention

[0003] The present invention provides an audio data stream compression method based on OFDM modulation, which solves the problem in the prior art that when multi-channel audio coding is used in a high dynamic range to reduce dynamic range compression distortion, more crosstalk between channels is easily caused.

[0004] The present invention is achieved through the following technical solutions:

[0005] An audio data stream compression method based on OFDM modulation, the method comprising:

[0006] Step S1: sampling the high dynamic range portion of the original audio signal to obtain a sampled signal, preprocessing the sampled signal for noise removal and quantization conversion, preliminarily reducing the dynamic range compression distortion of the sampled signal, and using multi-channel coding to divide the sampled signal into multiple channels for further distortion reduction processing;

[0007] Step S2: Divide the sampled signal of each channel into several frames, use discrete cosine transform to process the sampled signal frame by frame and output DCT coefficients according to different channels, use frequency division multiplexing modulation method to divide the original audio signal into several subcarrier signals and place them in the frequency domain, and set a quantization allocation strategy to randomly allocate all DCT coefficients to all subcarrier signals;

[0008] Step S3: performing an inverse discrete Fourier transform on the DCT coefficients on the subcarrier signal to convert the frequency domain data of the original audio signal represented by the DCT coefficients into time domain OFDM symbols, adding a cyclic prefix to each OFDM symbol, and performing a second multi-channel encoding on each OFDM symbol in a manner where each symbol is independently encoded;

[0009] Step S4: Preset a reference audio signal representing a standard and set a matching reference crosstalk attenuation ratio, use a frequency division multiplexing demodulation method to convert the time-domain OFDM symbols into DCT coefficients representing frequency-domain data, then perform an inverse discrete cosine transform to convert the DCT coefficients and label the conversion result as a modified audio signal;

[0010] Step S5: Calculate the corrected crosstalk attenuation ratio of the corrected audio signal and compare it with the reference crosstalk attenuation ratio. If the corrected crosstalk attenuation ratio is less than the reference crosstalk attenuation ratio, it is determined that the signal correction is completed. If the corrected crosstalk attenuation ratio is greater than the reference crosstalk attenuation ratio, re-execute step S2.

[0011] Due to the limitations of coding technology, the dynamic range of the signal is compressed, resulting in a loss of audio details and layering. Currently, the existing technology mainly uses multi-channel audio coding to reduce dynamic range compression distortion. When using the existing multi-channel audio coding method, crosstalk between channels is prone to occur in high dynamic range audio. Signal aliasing and interference between channels will significantly affect the spatial positioning and overall sound quality of the audio. Specifically, the audio content of each channel affects each other during the encoding or decoding process, resulting in the original independent channel information being mixed together, thereby destroying the spatial sense and clarity of the audio. Currently, the existing multi-channel audio coding technology lacks a method for reducing dynamic range compression distortion that can significantly reduce crosstalk between channels when processing high dynamic range. Based on this, the present invention provides an audio data stream compression method based on OFDM modulation to solve the problem in the existing technology that more crosstalk between channels is easily caused when using multi-channel audio coding to reduce dynamic range compression distortion in a high dynamic range.

[0012] Furthermore, as a feasible implementation method, the process of the frequency division multiplexing modulation method includes: using a frequency domain window function for the subcarrier signal to smooth the subcarrier spectrum and dynamically adjust the subcarrier spacing; obtaining the channel frequency response of each subcarrier signal based on frequency domain analysis, and identifying the spectrum extension caused by the multipath effect based on the channel frequency response; then using DFT transformation to transfer all subcarrier signals to the frequency domain, and performing frequency domain filtering on each subcarrier signal, and compensating the spectrum data of the filtered subcarrier signal to the spectrum extension caused by the multipath effect.

[0013] Furthermore, as a feasible implementation method, the process of using the frequency domain window function includes: applying the Blackman window function to the frequency domain data of each subcarrier for windowing processing, adjusting the subcarrier spacing based on the characteristics of the Blackman window function, and setting a width critical value for the main lobe width of the Blackman window. When the window function width of each subcarrier is lower than the width critical value, the subcarrier signal is doubled in subcarrier spacing width.

[0014] Further, as a feasible implementation method, the sample index of the window function of the subcarrier is represented as n, the width of the window function is represented as N, the Blackman window function value is represented as ω, the window function value at the nth sample point is represented as ω(n), the constant term is represented as A, the first coefficient is represented as B, and the second coefficient is represented as C.

[0015] Then the calculation formula of the Blackman window function is set as: ,

[0016] The constant term A is used to ensure that the value of the window function is not equal to zero at the beginning and end of the window.

[0017] The first coefficient B and the second coefficient C are both used to adjust the main lobe and side lobe characteristics of the window function.

[0018] Furthermore, the spectrum expansion compensation process further includes setting a compensation filter based on the channel frequency response to adjust the spectrum, wherein the compensation filter is used to adjust the spectrum to reduce distortion.

[0019] Furthermore, the method for setting the width critical value is to construct a linear relationship between the spectrum efficiency and the width critical value, and dynamically adjust the width critical value according to the level of the spectrum efficiency.

[0020] Furthermore, the modified crosstalk attenuation ratio of the modified audio signal is set as the ratio between the crosstalk amplitude of the modified audio signal and the main lobe amplitude of the modified audio signal.

[0021] Furthermore, the reference crosstalk attenuation ratio is calculated based on a spectrum leakage value and a crosstalk component value, wherein the spectrum leakage value represents the size of the component of the desired spectrum component of the original audio signal extended to the non-target frequency, and the crosstalk component value represents the energy size caused by overlapping interference in the original audio signal.

[0022] Furthermore, the spectrum leakage value is set as the ratio of the sidelobe energy of the original audio signal to the mainlobe energy of the reference audio signal; and the crosstalk component value is set as the ratio of the total crosstalk component energy of the original audio signal to the total signal energy of the reference audio signal.

[0023] Furthermore, the length of the cyclic prefix is ​​dynamically adjusted according to the multipath effect and delay spread of the channel.

[0024] Compared with the existing technology, the present invention adopts frequency division multiplexing modulation in multi-channel coding, divides the signal into multiple subcarriers, and uses the DCT coefficients in the frequency domain for further processing. It can independently perform dynamic range compression and optimization on each channel, and perform a second multi-channel independent encoding on each OFDM symbol, which can reduce the crosstalk caused by inconsistent coding. It has the advantages and beneficial effects of effectively controlling crosstalk between channels when using multi-channel audio coding. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] The drawings described herein are used to provide a further understanding of the embodiments of the present invention, constitute a part of this application, and do not constitute a limitation of the embodiments of the present invention. In the drawings:

[0026] Figure 1 It is a flowchart of the present invention. DETAILED DESCRIPTION

[0027] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with examples and drawings. The exemplary embodiments of the present invention and their descriptions are only used to explain the present invention and are not intended to limit the present invention. Example

[0028] like Figure 1 As shown, this embodiment is an audio data stream compression method based on OFDM modulation, which solves the problem in the prior art that when multi-channel audio coding is used in a high dynamic range to reduce dynamic range compression distortion, it easily causes more crosstalk between channels.

[0029] The present invention is achieved through the following technical solutions:

[0030] An audio data stream compression method based on OFDM modulation, the method comprising:

[0031] Step S1: sampling the high dynamic range portion of the original audio signal to obtain a sampled signal, preprocessing the sampled signal for noise removal and quantization conversion, preliminarily reducing the dynamic range compression distortion of the sampled signal, and using multi-channel coding to divide the sampled signal into multiple channels for further distortion reduction processing;

[0032] Step S2: Divide the sampled signal of each channel into several frames, use discrete cosine transform to process the sampled signal frame by frame and output DCT coefficients according to different channels, use frequency division multiplexing modulation method to divide the original audio signal into several subcarrier signals and place them in the frequency domain, and set a quantization allocation strategy to randomly allocate all DCT coefficients to all subcarrier signals;

[0033] Step S3: performing an inverse discrete Fourier transform on the DCT coefficients on the subcarrier signal to convert the frequency domain data of the original audio signal represented by the DCT coefficients into time domain OFDM symbols, adding a cyclic prefix to each OFDM symbol, and performing a second multi-channel encoding on each OFDM symbol in a manner where each symbol is independently encoded;

[0034] Step S4: Preset a reference audio signal representing a standard and set a matching reference crosstalk attenuation ratio, use a frequency division multiplexing demodulation method to convert the time-domain OFDM symbols into DCT coefficients representing frequency-domain data, then perform an inverse discrete cosine transform to convert the DCT coefficients and label the conversion result as a modified audio signal;

[0035] Step S5: Calculate the corrected crosstalk attenuation ratio of the corrected audio signal and compare it with the reference crosstalk attenuation ratio. If the corrected crosstalk attenuation ratio is less than the reference crosstalk attenuation ratio, it is determined that the signal correction is completed. If the corrected crosstalk attenuation ratio is greater than the reference crosstalk attenuation ratio, re-execute step S2.

[0036] The original audio signal is the target audio signal for processing, and the multi-channel encoding process is the primary method used in existing technologies to reduce distortion. Using discrete cosine transform (DCT) to process the sampled signal frame by frame aims to independently process different frequency components within the audio signal. This transform separates the signal's spectral characteristics, helping to reduce crosstalk between different frequency components during the encoding process, thereby reducing crosstalk between channels. Simultaneously, performing DCT processing on the sampled signal frame by frame allows for independent optimization of the data for each frame. This framing allows crosstalk to be addressed individually for each frame, helping to optimize signal separation between channels at the frame level and thus reduce crosstalk. Frequency division multiplexing (FDM) modulation is used to divide the original audio signal into several subcarrier signals and place them in the frequency domain, allowing for simultaneous transmission of multiple signals within the same spectrum, each occupying a different frequency band. This approach improves spectrum efficiency, allowing the system to transmit more information within a limited bandwidth while maintaining the independence of each channel signal. The frequency domain data of the original audio signal represented by the DCT coefficients is converted into time domain OFDM symbols to reduce frequency domain interference. Signal interference and crosstalk in the frequency domain may be alleviated after conversion to the time domain because the processing and transmission characteristics of the time domain signal are different from those in the frequency domain. Inverse OFDM and inverse DCT operations are performed to convert the time domain signal back to the frequency domain and restore the original audio signal. This can effectively correct the interference caused by crosstalk during transmission and further reduce crosstalk between multiple channels through appropriate demodulation and decoding steps. The reference audio signal refers to a standard audio signal used to compare, calibrate or evaluate the quality of other audio signals, that is, an audio signal that represents industry standards.

[0037] The high dynamic range portion of the original audio signal is sampled and pre-processed with noise removal and quantization to reduce dynamic range compression distortion. Multi-channel coding is then used to separate the sampled signal into multiple channels to further reduce distortion. This cleans and optimizes the audio signal for more efficient subsequent processing. Sampling the high dynamic range portion ensures that audio signal details are preserved. Noise removal and quantization help improve signal quality, while multi-channel coding provides greater flexibility for subsequent processing. The sampled signal of each channel is divided into several frames, and the DCT coefficients are applied frame by frame. This is used to convert the audio signal from the time domain to the frequency domain and is commonly used for data compression and removing redundant information. This frame division facilitates the gradual processing of audio data, improving processing accuracy and efficiency.

[0038] Furthermore, the original audio signal is divided into several subcarrier signals, placed in the frequency domain, and the DCT coefficients are randomly allocated to the subcarrier signals using a quantization allocation strategy. Frequency division multiplexing technology allows signals to be transmitted on different subcarriers at the same time, thereby improving bandwidth utilization. The quantization allocation strategy is used to allocate the quantization results of the signal to different subcarriers or frequency ranges. Commonly used quantization allocation strategies may include uniform quantization allocation, linear quantization allocation, and gradient quantization allocation. As a specific application, in a specific implementation, preferably, a quantization allocation strategy can be set based on gradient quantization allocation, and the frequencies of the subcarrier signals and the DCT coefficients are arranged from high to low, and the entire frequency range is equally divided into multiple frequency gradient range intervals, and the subcarrier signals and DCT coefficients within the same gradient range interval are randomly allocated, and at least one DCT coefficient is allocated to each subcarrier signal. The width of the frequency gradient range interval is comprehensively considered based on the sparsity of the DCT coefficients and the subcarrier width. The quantization allocation strategy enables each subcarrier to carry different DCT coefficients, thereby optimizing the utilization of the frequency domain. The DCT coefficients are converted to time-domain OFDM symbols and a cyclic prefix is ​​added to each OFDM symbol to convert the frequency-domain data back to the time domain in preparation for OFDM modulation. The cyclic prefix helps reduce interference between channel symbols and improve the robustness of the system. Each OFDM symbol is then subjected to a second multi-channel encoding for further crosstalk optimization. The DCT coefficients that convert the time-domain OFDM symbols back to the frequency domain are used to convert the time-domain signal back to the frequency domain in preparation for an inverse DCT operation. The inverse discrete cosine transform restores the frequency-domain data to the time domain to obtain the corrected audio signal. The corrected crosstalk attenuation ratio of the corrected audio signal is calculated and compared with the reference crosstalk attenuation ratio. The ratio is used to determine whether the signal has been corrected. If it fails, the process returns to step S2 to evaluate the corrected audio quality. If the correction does not meet the standard, the process will return and reprocess to ensure that the final audio signal meets the expected quality.

[0039] Furthermore, as a feasible implementation method, the process of the frequency division multiplexing modulation method includes: using a frequency domain window function for the subcarrier signal to smooth the subcarrier spectrum and dynamically adjust the subcarrier spacing; obtaining the channel frequency response of each subcarrier signal based on frequency domain analysis, and identifying the spectrum extension caused by the multipath effect based on the channel frequency response; then using DFT transformation to transfer all subcarrier signals to the frequency domain, and performing frequency domain filtering on each subcarrier signal, and compensating the spectrum data of the filtered subcarrier signal to the spectrum extension caused by the multipath effect.

[0040] The frequency domain window function helps smooth the subcarrier spectrum and reduce spectrum leakage. Spectral leakage refers to the leakage of frequency domain signal energy from one frequency component into other frequency components, which can cause signal interference and crosstalk. The use of a window function can also adjust the subcarrier spacing to adapt to different spectral environments. This dynamic adjustment helps optimize spectrum utilization, reduce interference between adjacent subcarriers, and improve overall modulation efficiency. By analyzing the channel frequency response, we can understand the spectrum variations of each subcarrier during actual transmission. The channel frequency response reveals signal attenuation and frequency-selective distortion during transmission. Multipath effects often cause spectrum spread, which refers to signal overlap and interference caused by multiple transmission paths. This effect broadens the spectrum and increases interference between signals. Identifying these effects is a prerequisite for processing and compensating for spectrum spread. Frequency domain filtering of each subcarrier signal can effectively reduce or compensate for spectrum spread caused by multipath effects. In specific implementations, filter design can optimize the signal based on the characteristics of multipath effects, thereby reducing the impact of spectrum spread on signal quality.

[0041] Furthermore, as a feasible implementation method, the process of using the frequency domain window function includes: applying the Blackman window function to the frequency domain data of each subcarrier for windowing processing, adjusting the subcarrier spacing based on the characteristics of the Blackman window function, and setting a width critical value for the main lobe width of the Blackman window. When the window function width of each subcarrier is lower than the width critical value, the subcarrier signal is doubled in subcarrier spacing width.

[0042] The Blackman window function is a windowing function used to reduce spectral leakage and improve the accuracy of frequency domain analysis. Its shape typically features a large mainlobe and multiple sidelobes. It effectively reduces spectral leakage and smoothes spectral data. Compared to other window functions, such as the Hanning and Hamming windows, the Blackman window significantly attenuates sidelobes, helping to reduce spectral sidelobe interference. By applying the Blackman window function to subcarrier frequency domain data, frequency domain leakage can be reduced, improving spectral resolution and signal clarity. The Blackman window's mainlobe width directly affects the subcarrier spacing in the frequency domain. To avoid spectral overlap between subcarriers, the subcarrier spacing must be adjusted based on the characteristics of the window function, ensuring that it is sufficiently large to maintain effective frequency domain isolation. The Blackman window's mainlobe width determines the subcarrier resolution in the frequency domain. Setting a width threshold helps adjust the subcarrier spacing based on the actual window function width. When the Blackman window's mainlobe width is below the set width threshold, spectral interference between subcarriers is minimal. To further optimize system performance, the subcarrier spacing needs to be increased to prevent interference caused by spectrum leakage or multipath effects. This dynamic adjustment method can adapt to the actual needs of different frequency domain environments and ensure low interference levels and high signal quality during the frequency domain processing of subcarrier signals.

[0043] Furthermore, let the sample index of the subcarrier window function be n, let the width of the window function be N, let the Blackman window function value be ω, let the window function value at the nth sample point be ω(n), let the constant term be A, let the first coefficient be B, let the second coefficient be C,

[0044] Then the calculation formula of the Blackman window function is set as: ,

[0045] The constant term A is used to ensure that the value of the window function is not equal to zero at the beginning and end of the window.

[0046] The first coefficient B and the second coefficient C are both used to adjust the main lobe and side lobe characteristics of the window function.

[0047] The constant term A is used to ensure that the window function's value at the beginning and end of the window is non-zero. This helps reduce the window function's impact on signal edges, preventing abrupt signal interruptions at the window boundaries, thereby reducing spectral leakage. By keeping the window function's boundary values ​​close to zero, the spectral artifacts generated by the window function at the signal edges can be reduced, improving the accuracy of spectral analysis. The first coefficient B is used to adjust the width and shape of the window function's main lobe. The main lobe width affects the width of the window function's main peak in the frequency domain, thereby affecting the spectral resolution. Increasing the value of B makes the main lobe wider, improving spectral resolution; however, it may increase the amplitude of the sidelobes. Optimizing the value of B can find a balance between mainlobe width and sidelobe attenuation. The second coefficient C is used to adjust the sidelobe characteristics of the window function. By adjusting the value of C, the sidelobe attenuation characteristics can be controlled, further reducing spectral leakage and sidelobe interference. Increasing the value of C helps reduce the amplitude of the sidelobes, making them decay faster, improving the spectral dynamic range of the window function, and further helping to reduce noise and interference in the spectrum. During operation, the window function value ω(n) at each sample point is calculated according to the formula. When applying the Blackman window function in the frequency domain, ensure that the window's endpoints are non-zero to reduce spectral artifacts. Adjust the coefficients B and C to optimize the mainlobe and sidelobe characteristics of the window function. This affects spectral resolution and sidelobe interference. Applying the Blackman window function to frequency domain data, selecting appropriate values ​​for A, B, and C optimizes spectral data smoothing, reduces spectral leakage and interference, and improves system performance.

[0048] Furthermore, as a feasible implementation method, the compensation process of the spectrum expansion also includes setting a compensation filter based on the channel frequency response to adjust the spectrum, and the compensation filter is used to adjust the spectrum to reduce distortion; the method for setting the width critical value is to construct a linear relationship between the spectrum efficiency and the width critical value, and dynamically adjust the width critical value according to the level of the spectrum efficiency; the corrected crosstalk attenuation ratio of the corrected audio signal is set to the ratio between the crosstalk amplitude of the corrected audio signal and the main lobe amplitude of the corrected audio signal.

[0049] The compensation filter is designed to adjust the spectrum based on the channel frequency response. This filter corrects for spectral spread caused by multipath or other channel characteristics, ensuring that the signal's spectrum returns to its intended shape. The primary purpose of the compensation filter is to reduce distortion caused by spectral spread. Appropriate filtering can adjust the signal spectrum to a form closer to its ideal state, thereby reducing interference and distortion caused by spectral spread. In specific implementations, the filter design should preferably consider the specific frequency response of the channel to accurately compensate for signal spectral shift and spread. An effective compensation filter can improve signal quality and overall system performance. The width threshold is used to determine whether the Blackman window function's mainlobe width is sufficient. When spectral efficiency is high, subcarrier spectral overlap is minimal, requiring a smaller width threshold. When spectral efficiency is low, subcarrier spectral overlap is significant, requiring a larger width threshold. The corrected crosstalk attenuation ratio is used to assess the crosstalk effect of the corrected audio signal. By calculating the ratio of the crosstalk amplitude to the mainlobe amplitude, the degree of crosstalk in the corrected signal can be quantified. A smaller corrected crosstalk attenuation ratio indicates a better correction effect and less crosstalk impact. This ratio is used to determine the effectiveness of the correction process and whether further adjustments are needed. By setting this ratio and comparing it with a reference value, the success of the correction process can be evaluated. If the ratio does not meet expectations, it indicates that the correction process needs to be optimized or re-executed. This implementation can effectively reduce the distortion caused by spectrum expansion and improve the quality of the audio signal. The compensation filter corrects spectral distortion, dynamically adjusts the width threshold to optimize spectral efficiency, and the corrected crosstalk attenuation ratio is used to evaluate the correction effect.

[0050] Furthermore, as a feasible implementation method, the reference crosstalk attenuation ratio is calculated based on the spectrum leakage value and the crosstalk component value, wherein the spectrum leakage value represents the size of the component of the desired spectrum component of the original audio signal extended to the non-target frequency, and the crosstalk component value represents the energy size caused by overlapping interference in the original audio signal; the spectrum leakage value is set to the ratio of the sidelobe energy of the original audio signal to the mainlobe energy of the reference audio signal; the crosstalk component value is set to the ratio of the total energy of the crosstalk component of the original audio signal to the total signal energy of the reference audio signal; and the cyclic prefix dynamically adjusts its length according to the multipath effect and delay spread of the channel.

[0051] The spectral leakage value represents the amount of components extending from the desired spectral components of the original audio signal to non-target frequencies. It is calculated as the ratio of the sidelobe energy of the original audio signal to the mainlobe energy of the reference audio signal. By calculating the ratio of the original signal's sidelobe energy to the reference signal's mainlobe energy, the degree of signal leakage in the frequency domain is assessed. Sidelobe energy refers to the signal's energy within the frequency range outside the mainlobe. Lower leakage values ​​indicate less spectral leakage. The crosstalk component value quantifies the energy caused by overlapping interference by calculating the ratio of the total crosstalk component energy to the total signal energy. Lower crosstalk component values ​​indicate less interference. The cyclic prefix length should be dynamically adjusted based on the channel's multipath effect and delay spread. Multipath refers to the time domain expansion of a signal caused by multiple paths it travels to reach the receiver during propagation. Delay spread refers to the time delay incurred by the signal at the receiving end. In specific implementations, the reference crosstalk attenuation ratio can be set as a weighted average of the spectral leakage value and the crosstalk component value, or other comprehensive indicator, to evaluate the overall effectiveness of crosstalk processing.

[0052] The specific implementation methods described above further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above description is only a specific implementation method of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for compressing audio data stream based on OFDM modulation, characterized in that: The method includes: Step S1: sampling the high dynamic range portion of the original audio signal to obtain a sampled signal, preprocessing the sampled signal for noise removal and quantization conversion, preliminarily reducing the dynamic range compression distortion of the sampled signal, and using multi-channel coding to divide the sampled signal into multiple channels for further distortion reduction processing; Step S2: Divide the sampled signal of each channel into several frames, use discrete cosine transform to process the sampled signal frame by frame and output DCT coefficients according to different channels, use frequency division multiplexing modulation method to divide the original audio signal into several subcarrier signals and place them in the frequency domain, and set a quantization allocation strategy to randomly allocate all DCT coefficients to all subcarrier signals; Step S3: performing an inverse discrete Fourier transform on the DCT coefficients on the subcarrier signal to convert the frequency domain data of the original audio signal represented by the DCT coefficients into time domain OFDM symbols, adding a cyclic prefix to each OFDM symbol, and performing a second multi-channel encoding on each OFDM symbol in a manner where each symbol is independently encoded; Step S4: Preset a reference audio signal representing a standard and set a matching reference crosstalk attenuation ratio, use a frequency division multiplexing demodulation method to convert the time-domain OFDM symbols into DCT coefficients representing frequency-domain data, then perform an inverse discrete cosine transform to convert the DCT coefficients and label the conversion result as a modified audio signal; Step S5: Calculate the corrected crosstalk attenuation ratio of the corrected audio signal and compare it with the reference crosstalk attenuation ratio. If the corrected crosstalk attenuation ratio is less than the reference crosstalk attenuation ratio, it is determined that the signal correction is completed. If the corrected crosstalk attenuation ratio is greater than the reference crosstalk attenuation ratio, re-execute step S2.

2. The audio data stream compression method based on OFDM modulation according to claim 1, characterized in that: The process of the frequency division multiplexing modulation method includes: using a frequency domain window function for the subcarrier signal to smooth the subcarrier spectrum and dynamically adjust the subcarrier spacing; obtaining the channel frequency response of each subcarrier signal based on frequency domain analysis, and identifying the spectrum expansion caused by the multipath effect based on the channel frequency response; then using DFT transformation to convert all subcarrier signals to the frequency domain, and performing frequency domain filtering on each subcarrier signal, and compensating the spectrum data of the filtered subcarrier signal to the spectrum expansion caused by the multipath effect.

3. The audio data stream compression method based on OFDM modulation according to claim 2, characterized in that: The process of using the frequency domain window function includes: applying the Blackman window function to the frequency domain data of each subcarrier for windowing processing, adjusting the subcarrier spacing based on the characteristics of the Blackman window function, setting a width critical value for the main lobe width of the Blackman window, and when the window function width of each subcarrier is lower than the width critical value, the subcarrier signal is doubled in subcarrier spacing width.

4. The audio data stream compression method based on OFDM modulation according to claim 3, characterized in that: Let the sample index of the subcarrier window function be n, let the width of the window function be N, let the Blackman window function value be ω, let the window function value at the nth sample point be ω(n), let the constant term be A, let the first coefficient be B, let the second coefficient be C, Then the calculation formula of the Blackman window function is set as: , The constant term A is used to ensure that the value of the window function is not equal to zero at the beginning and end of the window. The first coefficient B and the second coefficient C are both used to adjust the main lobe and side lobe characteristics of the window function.

5. The audio data stream compression method based on OFDM modulation according to claim 2, characterized in that: The spectrum expansion compensation process further includes setting a compensation filter based on the channel frequency response to adjust the spectrum, wherein the compensation filter is used to adjust the spectrum to reduce distortion.

6. The audio data stream compression method based on OFDM modulation according to claim 3, characterized in that: The method for setting the width critical value is to construct a linear relationship between the spectrum efficiency and the width critical value, and dynamically adjust the width critical value according to the level of the spectrum efficiency.

7. The audio data stream compression method based on OFDM modulation according to claim 1, characterized in that: The modified crosstalk attenuation ratio of the modified audio signal is set as the ratio between the crosstalk amplitude of the modified audio signal and the main lobe amplitude of the modified audio signal.

8. The audio data stream compression method based on OFDM modulation according to claim 1, characterized in that: The reference crosstalk attenuation ratio is calculated based on a spectrum leakage value and a crosstalk component value, wherein the spectrum leakage value indicates the size of the component of the desired spectrum component of the original audio signal extending to the non-target frequency, and the crosstalk component value indicates the energy size caused by overlapping interference in the original audio signal.

9. The audio data stream compression method based on OFDM modulation according to claim 8, characterized in that: The spectrum leakage value is set as the ratio of the sidelobe energy of the original audio signal to the mainlobe energy of the reference audio signal; the crosstalk component value is set as the ratio of the total crosstalk component energy of the original audio signal to the total signal energy of the reference audio signal.

10. The audio data stream compression method based on OFDM modulation according to claim 1, characterized in that: The length of the cyclic prefix is ​​dynamically adjusted according to the multipath effect and delay spread of the channel.

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