Demodulation methods, demodulation devices, and demodulation equipment for QAM modulation

Abstract

This application provides a demodulation method, demodulation apparatus, and demodulation device for QAM modulation. The method includes: performing soft demodulation on the signal to be demodulated to obtain multiple LLR curves, wherein the signal to be demodulated includes multiple symbols to be demodulated, and each symbol to be demodulated includes multiple bits, with each LLR curve corresponding to a bit; performing linear fitting on each LLR curve to obtain multiple slopes and multiple intercepts, each slope and intercept corresponding to a LLR curve; performing IQ decomposition on each symbol to be demodulated to obtain in-phase components and quadrature components, each quadrature component and in-phase component corresponding to a symbol to be demodulated; and correcting the corresponding LLR curves according to each intercept, noise variance, each in-phase component, each quadrature component, and each correction factor to obtain multiple corrected LLR curves. This method solves the problem of high computational complexity in existing QAM demodulation algorithms.

Description

Technical Field

[0001] This invention relates to the field of digital signal processing, and more specifically, to a demodulation method, demodulation apparatus, computer-readable storage medium, and demodulation device for QAM modulation. Background Technology

[0002] The widespread adoption of mobile internet devices has brought convenience to everyone's lives. With the proliferation of smartphones and a wide variety of applications, the demand for communication services is increasing, leading to a shortage of spectrum resources. To improve spectrum utilization and data transmission rates, high-order digital modulation techniques are widely used in wireless communication systems. Among these, high-order QAM modulation technology has been widely applied in satellite communication, Wi-Fi communication, and smart cars and smart homes.

[0003] Communication systems employing high-order QAM modulation can significantly improve spectral efficiency. To reduce the system error rate and enhance reliability, advanced error-correcting code techniques are typically used. For channel coding methods such as Polar codes, convolutional codes, and LDPC codes, soft-decision decoding with higher reliability is generally employed. Therefore, probabilistic demodulation-based soft demodulation algorithms are commonly used to output the probability information for each bit.

[0004] Traditional soft demodulation algorithm LOG-MAP involves a large number of exponential and logarithmic operations, resulting in high algorithm complexity and making it difficult to implement in hardware. While existing simplified algorithms reduce a significant amount of exponential and logarithmic operations, they still contain a large number of real number operations, and their complexity remains high as the modulation order increases. Summary of the Invention

[0005] The main objective of this application is to provide a demodulation method, demodulation device, computer-readable storage medium, and demodulation equipment for QAM modulation, so as to at least solve the problem of high computational complexity of the demodulation algorithm for QAM modulation in the prior art.

[0006] To achieve the above objectives, according to one aspect of this application, a demodulation method for QAM modulation is provided, comprising: performing soft demodulation on a signal to be demodulated to obtain multiple LLR curves, wherein the soft demodulation is a demodulation method that expresses the modulated signal using the log-likelihood ratio, the signal to be demodulated is a modulated signal received by a receiver, the signal to be demodulated includes multiple symbols to be demodulated, each symbol to be demodulated includes multiple bits, and the LLR curves correspond one-to-one with the bits; performing linear fitting on each of the LLR curves to obtain multiple slopes and multiple intercepts, wherein the slopes correspond one-to-one with the LLR curves. A one-to-one correspondence is established, with each intercept corresponding to a specific LLR curve. IQ decomposition is performed on each of the demodulated symbols to obtain co-directional and quadrature components, with each quadrature component corresponding to a specific demodulated symbol, and each co-directional component corresponding to a specific demodulated symbol. Multiple modified LLR curves are obtained by modifying the corresponding LLR curves based on each intercept, noise variance, co-directional component, quadrature component, and correction factor. The noise variance characterizes the degree of variation in the demodulated signal, and the correction factor corrects the amplitude of the LLR curve.

[0007] Optionally, soft demodulation of the signal to be demodulated to obtain multiple LLR curves includes: determining a set of symbols to be demodulated and a modulation order based on the signal to be demodulated, wherein the set of symbols to be demodulated contains all the symbols to be demodulated in the signal to be demodulated, and the modulation order is the number of bits contained in each symbol to be demodulated; splitting the set of symbols to be demodulated according to the modulation order to obtain multiple bits; and determining multiple LLR curves based on the multiple bits and the noise variance.

[0008] Optionally, linear fitting is performed on each of the LLR curves to obtain multiple slopes and multiple intercepts, including: sampling each of the LLR curves at equal intervals to obtain multiple first sample sets, and calculating the corresponding first mean, where the first mean is the mean of all samples in the first sample set; constructing a first curve based on the noise variance and each of the bits, where the first curve is used to characterize the change in the quotient of the bit and the noise variance; sampling the first curves at equal intervals to obtain multiple second sample sets, and calculating the corresponding second mean, where the second mean is the mean of all samples in the second sample set; calculating multiple intercepts and multiple slopes based on the multiple first sample sets, the multiple second sample sets, the corresponding first mean, and the corresponding second mean, where each intercept and slope corresponds one-to-one with the bit.

[0009] Optionally, before correcting the corresponding LLR curves according to each intercept, noise variance, each in-direction component, each orthogonal component, and each correction factor to obtain multiple corrected LLR curves, the method further includes: a determination step, determining the corresponding peak value according to each slope, wherein the peak value is the peak value of the LLR curve corresponding to the slope, and the peak value corresponds one-to-one with the slope; and a calculation step, calculating each correction factor according to each slope and the peak value, wherein the correction factor corresponds one-to-one with the slope.

[0010] Optionally, the corresponding LLR curves are corrected according to each intercept, noise variance, in-direction component, quadrature component, and correction factor to obtain multiple corrected LLR curves, including: a first correction step, determining multiple first LLR curves for the target symbol to be demodulated according to the in-direction component, noise variance, correction factor, and intercept, wherein the first LLR curves are the LLR curves corresponding to the odd-numbered bits of the target symbol to be demodulated, and the target symbol to be demodulated is one of the symbols to be demodulated; a second correction step, determining multiple second LLR curves for the target symbol to be demodulated according to the quadrature component, noise variance, correction factor, and intercept, wherein the second LLR curves are the LLR curves corresponding to the even-numbered bits of the target symbol to be demodulated; repeating the first correction step and the second correction step at least once until the corrected LLR curves corresponding to all bits of all the symbols to be demodulated are obtained, wherein the multiple corrected LLR curves include multiple first LLR curves and multiple second LLR curves.

[0011] Optionally, before determining the plurality of LLR curves based on the plurality of bits and the noise variance, the method further includes: obtaining the signal-to-noise ratio and signal power of the signal to be demodulated; and calculating the noise variance based on the signal-to-noise ratio and the signal power.

[0012] Optionally, after correcting the corresponding LLR curves according to each intercept, noise variance, in-phase component, quadrature component, and correction factor to obtain multiple corrected LLR curves, the method further includes: constructing a noise variance group based on the noise variance, such that the ratio of any target noise variance in the noise variance group to the noise variance is within a preset range; constructing multiple lookup tables, each lookup table corresponding one-to-one with the target noise variance of the noise variance group, wherein the lookup table is a lookup table for the intercept, slope, and correction factor under the target noise variance; and, upon receiving the signal to be demodulated, determining the corresponding lookup table based on the noise variance of the signal to be demodulated, and performing soft demodulation on the signal to be demodulated based on the lookup table.

[0013] According to another aspect of this application, a demodulation apparatus for QAM modulation is provided. The apparatus includes: a demodulation unit configured to perform soft demodulation on a signal to be demodulated to obtain multiple LLR curves, wherein the soft demodulation is a demodulation method that expresses the modulated signal using the log-likelihood ratio; the signal to be demodulated is a modulated signal received by a receiver; the signal to be demodulated includes multiple symbols to be demodulated, each symbol including multiple bits; and the LLR curves correspond one-to-one with the bits. A fitting unit configured to perform linear fitting on each of the LLR curves to obtain multiple slopes and multiple intercepts, wherein the slopes correspond one-to-one with the LLR curves. The intercept corresponds one-to-one with the LLR curve; the decomposition unit is used to perform IQ decomposition on each of the symbols to be demodulated to obtain in-phase components and quadrature components, wherein the quadrature components correspond one-to-one with the symbols to be demodulated, and the in-phase components correspond one-to-one with the symbols to be demodulated; the correction unit is used to correct the corresponding LLR curves according to each intercept, noise variance, each in-phase component, each quadrature component, and each correction factor to obtain multiple corrected LLR curves, wherein the noise variance is used to characterize the degree of variation of the signal to be demodulated, and the correction factor is used to correct the amplitude of the LLR curve.

[0014] According to another aspect of this application, a computer-readable storage medium is provided, the computer-readable storage medium including a stored program, wherein, when the program is executed, it controls the device on which the computer-readable storage medium is located to perform any of the methods described.

[0015] According to another aspect of this application, a demodulation device is provided, comprising: one or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs including methods for performing any of the methods described.

[0016] Applying the technical solution of this application, in the above-mentioned QAM modulation demodulation method, firstly, soft demodulation is performed on the signal to be demodulated to obtain multiple LLR curves. The soft demodulation is a demodulation method that expresses the modulated signal using the log-likelihood ratio. The signal to be demodulated is the modulated signal received by the receiver, which includes multiple demodulated symbols, each of which includes multiple bits. The LLR curves correspond one-to-one with the bits. Then, linear fitting is performed on each of the LLR curves to obtain multiple slopes and multiple intercepts. The slopes correspond one-to-one with the LLR curves, and the intercepts... Each LLR curve corresponds one-to-one with the aforementioned LLR curves. Then, IQ decomposition is performed on each of the aforementioned symbols to be demodulated to obtain in-phase and quadrature components. The quadrature components correspond one-to-one with each of the aforementioned symbols to be demodulated, and the in-phase components correspond one-to-one with each of the aforementioned symbols to be demodulated. Finally, the corresponding LLR curves are corrected according to the aforementioned intercepts, noise variance, in-phase components, quadrature components, and correction factors to obtain multiple corrected LLR curves. The noise variance is used to characterize the degree of variation of the aforementioned signal to be demodulated, and the correction factors are used to correct the amplitude of the aforementioned LLR curves. This application, based on existing theoretical LLR curves, performs linear fitting on the existing theoretical LLR curves to determine the fitting coefficients; calculates the scaling factor corresponding to each fitting coefficient during the fitting process based on the fitting coefficients, and then calculates the correction factor based on the fitting coefficients and the scaling factor. The LLR curve corresponding to each symbol to be demodulated is corrected according to the correction factor. This method performs linear fitting on the LLR curve, unifying discrete points onto a single curve. Compared to existing technologies that simplify the LLR curve before converting it into a piecewise function and then performing piecewise calculations, this method significantly reduces the complex exponential and logarithmic operations and addition, subtraction, multiplication, and division operations in the signal demodulation process, thus solving the problem of high computational complexity in existing QAM modulation demodulation algorithms. Attached Figure Description

[0017] Figure 1 A hardware structure block diagram of a mobile terminal performing a demodulation method of QAM modulation according to an embodiment of this application is shown.

[0018] Figure 2 A schematic flowchart of a QAM modulation demodulation method according to an embodiment of this application is shown;

[0019] Figure 3 A schematic diagram of LLR curves corresponding to different bits provided in embodiments of this application is shown;

[0020] Figure 4 The diagram illustrates the algorithm structure of a specific QAM modulation demodulation method according to an embodiment of this application.

[0021] Figure 5A comparison diagram of the demodulation effects of different demodulation methods for an LDPC format signal according to another embodiment of this application is shown;

[0022] Figure 6 A comparison diagram of the demodulation effects of different demodulation methods for a Polar format signal according to another embodiment of this application is shown;

[0023] Figure 7 A structural block diagram of a QAM modulation demodulation apparatus provided according to an embodiment of this application is shown. Detailed Implementation

[0024] It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other. This application will now be described in detail with reference to the accompanying drawings and embodiments.

[0025] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort should fall within the scope of protection of the present application.

[0026] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate for the embodiments of this application described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0027] As described in the background section, the traditional soft demodulation algorithm LOG-MAP in the prior art involves a large number of exponential and logarithmic operations, resulting in high algorithm complexity and hindering hardware implementation. Although existing classical simplified algorithms reduce a large number of exponential and logarithmic operations, they still contain a large number of real number operations. As the modulation order increases, the complexity of this algorithm remains high. To solve the problem of high computational complexity in existing QAM modulation demodulation algorithms, embodiments of this application provide a QAM modulation demodulation method, demodulation apparatus, computer-readable storage medium, and demodulation device.

[0028] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention.

[0029] The methods and embodiments provided in this application can be executed on a mobile terminal, computer terminal, or similar computing device. Taking running on a mobile terminal as an example, Figure 1 This is a hardware structure block diagram of a mobile terminal for a QAM modulation demodulation method according to an embodiment of the present invention. Figure 1 As shown, a mobile terminal may include one or more ( Figure 1 Only one is shown in the diagram. A processor 102 (which may include, but is not limited to, a microprocessor MCU or a programmable logic device FPGA, etc.) and a memory 104 for storing data are also shown. The mobile terminal may further include a transmission device 106 for communication functions and an input / output device 108. Those skilled in the art will understand that... Figure 1 The structure shown is for illustrative purposes only and does not limit the structure of the mobile terminal described above. For example, the mobile terminal may also include components that are more... Figure 1 The more or fewer components shown, or having the same Figure 1 The different configurations shown.

[0030] The memory 104 can be used to store computer programs, such as application software programs and modules, like the computer program corresponding to the device information display method in this embodiment of the invention. The processor 102 executes various functional applications and data processing by running the computer program stored in the memory 104, thereby implementing the above-described method. The memory 104 may include high-speed random access memory and non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 104 may further include memory remotely located relative to the processor 102, and these remote memories can be connected to the mobile terminal via a network. Examples of the aforementioned networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof. The transmission device 106 is used to receive or send data via a network. Specific examples of the aforementioned networks may include wireless networks provided by the mobile terminal's communication provider. In one example, the transmission device 106 includes a network interface controller (NIC), which can be connected to other network devices via a base station to communicate with the Internet. In one example, the transmission device 106 may be a radio frequency (RF) module, which is used to communicate with the Internet wirelessly.

[0031] This embodiment provides a demodulation method for QAM modulation that runs on a mobile terminal, computer terminal, or similar computing device. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Also, although the logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0032] Figure 2 This is a flowchart of a QAM modulation demodulation method according to an embodiment of this application. Figure 2 As shown, the method includes the following steps:

[0033] Step S201: Soft demodulation is performed on the signal to be demodulated to obtain multiple LLR curves. The soft demodulation is a demodulation method that expresses the modulated signal using the log-likelihood ratio. The signal to be demodulated is the modulated signal received by the receiver. The signal to be demodulated includes multiple symbols to be demodulated. Each symbol to be demodulated includes multiple bits. The LLR curves correspond one-to-one with the bits.

[0034] Specifically, based on the noise variance of the signal to be demodulated, the existing LOG-MAP algorithm is substituted to calculate the theoretical LLR curve for each bit.

[0035] In one embodiment of this application, the LLR curve obtained by the above bit calculation may include the following situations: Figure 3 As shown.

[0036] Step S202: Perform linear fitting on each of the above LLR curves to obtain multiple slopes and multiple intercepts. The slopes correspond one-to-one with the above LLR curves, and the intercepts correspond one-to-one with the above LLR curves.

[0037] Specifically, such as Figure 3 As shown, the LLR curve has obvious symmetry and piecewise linearity. The LLR curve can be linearly fitted by the least squares method to determine the fitting coefficient of each LLR curve, namely the slope and intercept. Since the LLR curve corresponding to each bit is different, the fitting coefficient corresponding to each bit is also different. The fitting coefficient corresponds one-to-one with the curve.

[0038] Step S203: Perform IQ decomposition on each of the above-mentioned symbols to be demodulated to obtain in-phase components and quadrature components. The quadrature components correspond one-to-one with the above-mentioned symbols to be demodulated, and the in-phase components correspond one-to-one with the above-mentioned symbols to be demodulated.

[0039] Specifically, the received demodulated symbols are decomposed into in-direction components and quadrature components, denoted as the I-path and Q-path, respectively. It can be seen that the fitting coefficients for the I-path and Q-path are the same.

[0040] Step S204: Based on each of the above intercepts, noise variances, in-phase components, quadrature components, and correction factors, the corresponding LLR curves are corrected to obtain multiple corrected LLR curves. The noise variance is used to characterize the degree of variation of the demodulated signal, and the correction factors are used to correct the amplitude of the LLR curves.

[0041] Specifically, because the LLR values ​​of different bits have amplitude differences, a small fitting error for a particular bit will significantly increase when projected onto a smaller LLR amplitude bit scale. Furthermore, during decoding, the LLR demodulation value for each bit is not calculated independently. Therefore, bits with larger error scales will interfere with bits with smaller errors, thus affecting the demodulation result. Therefore, this application uses the aforementioned slope, in-direction component, and quadrature component to calculate the correction factor for each bit. Then, based on the correction factor, in-direction component, quadrature component, and intercept, the corrected soft information for each bit is calculated, i.e., the aforementioned corrected LLR curve.

[0042] In this embodiment, firstly, soft demodulation is performed on the signal to be demodulated to obtain multiple LLR curves. The soft demodulation is a demodulation method that expresses the modulated signal using the log-likelihood ratio. The signal to be demodulated is the modulated signal received by the receiver, and the signal to be demodulated includes multiple symbols to be demodulated, each symbol including multiple bits. The LLR curves correspond one-to-one with the bits. Then, linear fitting is performed on each of the LLR curves to obtain multiple slopes and multiple intercepts. The slopes correspond one-to-one with the LLR curves, and the intercepts correspond one-to-one with the LLR curves. A one-to-one correspondence is established; then, IQ decomposition is performed on each of the above-mentioned symbols to be demodulated to obtain in-phase and quadrature components. The quadrature components correspond one-to-one with the above-mentioned symbols to be demodulated, and the in-phase components correspond one-to-one with the above-mentioned symbols to be demodulated. Finally, the corresponding LLR curves are corrected according to the intercepts, noise variances, in-phase components, quadrature components, and correction factors to obtain multiple corrected LLR curves. The noise variance is used to characterize the degree of variation of the above-mentioned signal to be demodulated, and the correction factors are used to correct the amplitude of the above-mentioned LLR curves. Based on the existing theoretical LLR curves, this application performs linear fitting on the existing theoretical LLR curves to determine the fitting coefficients; the scaling factor corresponding to each fitting coefficient in the fitting process is calculated according to the fitting coefficients, and then the correction factor is calculated according to the fitting coefficients and the scaling factor. The LLR theoretical curve corresponding to each symbol to be demodulated is corrected according to the correction factor. This method performs linear fitting on the LLR curve, unifying discrete points onto a single curve. Compared to existing technologies that simplify the LLR curve before converting it into a piecewise function and then performing piecewise calculations, this method significantly reduces the complex exponential and logarithmic operations and addition, subtraction, multiplication, and division operations in the signal demodulation process, thus solving the problem of high computational complexity in existing QAM modulation demodulation algorithms.

[0043] To obtain the above-mentioned LLR curve, in an optional implementation, step S201 includes:

[0044] Step S2011: Determine the demodulation symbol set and modulation order based on the demodulation signal. The demodulation symbol set includes all the demodulation symbols in the demodulation signal, and the modulation order is the number of bits contained in each demodulation symbol.

[0045] Specifically, the receiving end receives the demodulated signal after transmission through a Gaussian additive white noise channel, and obtains a demodulated symbol set containing multiple modulated symbols based on this signal. Then, the modulation order can be determined based on the number of bits contained in each demodulated signal.

[0046] Step S2012: The above-mentioned set of symbols to be demodulated is split according to the above-mentioned modulation order to obtain multiple bits;

[0047] Specifically, each symbol in the modulation symbol set is differentially divided into multiple bits.

[0048] Step S2013: Determine multiple LLR curves based on the multiple bits and the noise variance.

[0049] Specifically, by setting each bit as the independent variable, and substituting the set of symbols to be demodulated and the noise variance of the signal to be demodulated into the theoretical LLR formula of the LOG-MAP algorithm, the soft information corresponding to each bit, i.e., the LLR curve, can be obtained. The specific formula is as follows:

[0050]

[0051] Where x is a bit, s k For a finite set of symbols, σ 2 For noise variance, and These are sets containing finite symbols whose i-th bit is 0 and whose i-th bit is 1.

[0052] To fit the LLR curve and simplify the computational complexity of the demodulation process, in an optional implementation, step S202 includes:

[0053] Step S2021: Sample each of the above LLR curves at equal intervals to obtain multiple first sample sets, and calculate the corresponding first mean, where the first mean is the mean of all samples in the above first sample set.

[0054] Specifically, let Y be the sample set obtained by sampling the LLR curve at equal intervals, that is, the sample set Y = (y1, y2...y... nThe sample is the y-value collected at equal intervals along the x-axis of the curve. Then, the mean of the samples in the sample set is calculated to obtain the first mean mentioned above.

[0055] Step S2022: Construct a first curve based on the noise variance and each bit, wherein the first curve is used to characterize the change of the ratio of the bit to the noise variance.

[0056] Specifically, construct curves This is the first curve mentioned above.

[0057] Step S2023: Sample the first curve at equal intervals to obtain multiple second sample sets, and calculate the corresponding second mean. The second mean is the mean of all samples in the second sample set.

[0058] Specifically, let X be the sample set obtained by sampling the first curve at equal intervals, that is, the sample set X = (x1, x2, ... x... n The sample is the y-value collected at equal intervals along the x-axis of the first curve. Then, the mean of the samples in the sample set is calculated to obtain the second mean mentioned above.

[0059] Step S2024: Based on the multiple first sample sets, the multiple second sample sets, the corresponding first mean and the corresponding second mean, multiple intercepts and multiple slopes are calculated, and each intercept and slope corresponds one-to-one with the bit.

[0060] Specifically, data X is approximated by a first-order linear expression, i.e. Where α is the slope and β is the intercept. The mean square error of the fit can be expressed as: To ensure the linear approximation most closely approximates the original LLR theoretical curve, the least squares method is used to minimize the mean square error, thus obtaining the intercept and slope mentioned above. The specific formulas are as follows:

[0061]

[0062]

[0063] in, The first mean mentioned above, This is the second mean mentioned above.

[0064] To obtain the aforementioned correction factors, in an optional embodiment, before correcting the corresponding LLR curves according to each of the aforementioned intercepts, noise variances, each of the aforementioned in-direction components, each of the aforementioned quadrature components, and each correction factor to obtain multiple corrected LLR curves, the method further includes:

[0065] Step S301, Determine the step, determine the corresponding peak value according to each of the above slopes, the above peak value is the peak value of the above LLR curve corresponding to the above slope, and the above peak value corresponds one-to-one with the above slope;

[0066] Specifically, since the fitting coefficients for the I-path and Q-path are the same, we can obtain different slopes under the same noise variance, i.e. Let M be the peak value of the LLR curve corresponding to each α during the fitting process, then we have

[0067] Step S302, calculation step: calculate each of the above-mentioned correction factors based on each of the above-mentioned slopes and peak values, wherein each of the above-mentioned correction factors corresponds one-to-one with the above-mentioned slopes.

[0068] Specifically, based on the correspondence between slope and peak value, a scaling factor can be calculated for each slope, and then a correction factor can be calculated based on the scaling factor. The specific formula is as follows:

[0069]

[0070] γ=εα,

[0071] Where ε is the scaling factor mentioned above, and γ is the correction factor.

[0072] To reduce the impact of linear fitting on the demodulation results, in an optional implementation, step S204 includes:

[0073] Step S2041, first correction step, determine multiple first LLR curves of the target to be demodulated symbol according to the above-mentioned in-direction component, the above-mentioned noise variance, the above-mentioned correction factor and the above-mentioned intercept, the first LLR curve is the LLR curve corresponding to the odd-numbered bits in the target to be demodulated symbol, and the target to be demodulated symbol is one of the above to be demodulated symbols.

[0074] Specifically, the corrected LLR curve for the first bit can be determined based on the noise variance, the in-direction component, and the correction factor and intercept corresponding to the first bit. The specific formula is as follows:

[0075] Step S2042, the second correction step, determines multiple second LLR curves of the target symbol to be demodulated based on the above-mentioned quadrature components, the above-mentioned noise variance, the above-mentioned correction factor and the above-mentioned intercept, wherein the above-mentioned second LLR curves are the LLR curves corresponding to the even-numbered bits in the target symbol to be demodulated.

[0076] Specifically, the corrected LLR curve for the second bit can be determined based on the noise variance, the quadrature components, the correction factor corresponding to the second bit, and the intercept. The specific formula is as follows:

[0077] Step S2043: Repeat the first correction step and the second correction step at least once in sequence until the corrected LLR curves corresponding to all bits of all the above-mentioned symbols to be demodulated are obtained. The multiple corrected LLR curves include multiple first LLR curves and multiple second LLR curves.

[0078] Specifically, based on the recursive relationship, the coordinate relationship between the third bit and the first bit can be determined as follows: Where A is the amplitude of the LLR curve, and then the formula is used... The in-direction component corresponding to the third bit can then be calculated, and the LLR curve corresponding to the third bit can be corrected based on the correction factor corresponding to the third bit. Repeating the above recursive and calculation process completes the LLR curve correction for odd-numbered bits. According to the recursive relationship, the coordinate relationship between the second and fourth bits is as follows: Then through the formula The orthogonal component corresponding to the fourth bit can then be calculated, and the LLR curve corresponding to the fourth bit can be corrected based on the correction factor corresponding to the fourth bit. Repeating the above recursive and calculation process can complete the LLR curve correction for even-numbered bits.

[0079] To simplify the acquisition of noise variance, in an optional implementation, before determining the multiple LLR curves based on the multiple bits and the noise variance, the method further includes:

[0080] Step S401: Obtain the signal-to-noise ratio and signal power of the signal to be demodulated.

[0081] Specifically, in actual calculations, the noise method is very complex to perform directly. Therefore, this application uses the signal-to-noise ratio to calculate the corresponding noise variance.

[0082] Step S402: Calculate the noise variance based on the signal-to-noise ratio and the signal power.

[0083] Specifically, the noise variance can be calculated based on the signal-to-noise ratio (SNR) and noise variance obtained above, using the relationship between SNR and noise variance. The specific relationship is as follows:

[0084]

[0085] Where SNR is the signal-to-noise ratio and P is the signal power.

[0086] To simplify the acquisition of correction factors, in an optional embodiment, after correcting the corresponding LLR curves according to each of the above-mentioned intercepts, noise variances, each of the above-mentioned in-direction components, each of the above-mentioned quadrature components, and each correction factor to obtain multiple corrected LLR curves, the method further includes:

[0087] Step S501: Construct a noise variance group based on the above noise variance, such that the ratio of any target noise variance in the noise variance group to the above noise variance is within a preset range.

[0088] Specifically, the LLR curve is determined based on the noise variance. The same signal will generate different noise variances during channel transmission. Therefore, this application modifies the noise variance to obtain a noise variance group composed of different noise variances. The noise variance group includes the noise variance that may be generated during signal transmission in the channel.

[0089] Step S502: Construct multiple lookup tables, each of which corresponds one-to-one with the target noise variance of the noise variance group. The lookup tables are reference tables for the intercept, slope, and correction factor under the target noise variance.

[0090] Specifically, based on the slope, intercept, and correction factor for each noise variance in the above noise variance group, a lookup table of multiple intercepts and correction factors is established.

[0091] Step S503: Upon receiving the signal to be demodulated, a corresponding lookup table is determined based on the noise variance of the signal to be demodulated, and the signal to be demodulated is subjected to soft demodulation based on the lookup table.

[0092] Specifically, in the subsequent demodulation process, after receiving the signal to be demodulated, demodulation can be performed by looking up the corresponding table based on the noise variance, thus reducing the computational complexity in the demodulation process.

[0093] To enable those skilled in the art to better understand the technical solution of this application, the implementation process of the QAM modulation demodulation method of this application will be described in detail below with reference to specific embodiments.

[0094] This embodiment relates to a specific QAM modulation demodulation method, such as... Figure 4 As shown, it includes the following steps:

[0095] Step S1: Calculate the theoretical LLR curve for each bit of the signal to be demodulated;

[0096] Step S2: Perform linear fitting based on the LLR curve, and then calculate its fitting coefficient, scaling factor and correction factor;

[0097] Step S3: Calculate the fitting coefficients and correction factors for different noise variances (see table).

[0098] Step S4: When a new signal to be demodulated arrives, calculate the noise variance based on the signal-to-noise ratio and look it up in the table;

[0099] Step S5: Perform soft demodulation on the LLR curve based on the fitting coefficients and correction factors in the target comparison table, and output the soft demodulation results. The formulas used in the demodulation process are as follows:

[0100]

[0101]

[0102] In another embodiment of this application, the demodulation method of this application, the traditional LOG-MAP demodulation algorithm, the traditional MAX-LOG-MAP demodulation algorithm, the simplified LLR-Metrics algorithm, and an existing fitting algorithm are respectively used to perform soft demodulation on signals encoded by LDPC and Polar coding methods. The effects are compared as follows: Figure 5 and Figure 6 As shown. Figure 5 This is a comparison chart of the software demodulation effects of LDPC format. Figure 6 The chart shows a comparison of the soft demodulation performance of the Polar format. The computational complexity of the above demodulation methods is shown in Table 1.

[0103] Table 1

[0104]

[0105] It is evident that this application, while simplifying computational complexity, ensures the accuracy of demodulation, and its performance is significantly superior to the simplified LLR-Metrics algorithm and existing fitting algorithms.

[0106] This application also provides a QAM modulation demodulation apparatus. It should be noted that the QAM modulation demodulation apparatus of this application can be used to execute the QAM modulation demodulation method provided in this application. This apparatus is used to implement the above embodiments and preferred embodiments; details already described will not be repeated. As used below, the term "module" can refer to a combination of software and / or hardware that implements a predetermined function. Although the apparatus described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0107] The following describes the QAM modulation demodulation apparatus provided in the embodiments of this application.

[0108] Figure 7 This is a structural block diagram of a QAM modulation demodulation apparatus according to an embodiment of this application. Figure 7As shown, the device includes:

[0109] The demodulation unit 10 is used to perform soft demodulation on the signal to be demodulated to obtain multiple LLR curves. The soft demodulation is a demodulation method that expresses the modulated signal using the log-likelihood ratio. The signal to be demodulated is the modulated signal received by the receiving end. The signal to be demodulated includes multiple symbols to be demodulated. Each symbol to be demodulated includes multiple bits. The LLR curves correspond one-to-one with the bits.

[0110] Specifically, based on the noise variance of the signal to be demodulated, the existing LOG-MAP algorithm is substituted to calculate the theoretical LLR curve for each bit.

[0111] In one embodiment of this application, the LLR curve obtained by the above bit calculation may include the following situations: Figure 3 As shown.

[0112] Fitting unit 20 is used to perform linear fitting on each of the above LLR curves to obtain multiple slopes and multiple intercepts. The slopes correspond one-to-one with the above LLR curves, and the intercepts correspond one-to-one with the above LLR curves.

[0113] Specifically, such as Figure 3 As shown, the LLR curve has obvious symmetry and piecewise linearity. The LLR curve can be linearly fitted by the least squares method to determine the fitting coefficient of each LLR curve, namely the slope and intercept. Since the LLR curve corresponding to each bit is different, the fitting coefficient corresponding to each bit is also different. The fitting coefficient corresponds one-to-one with the curve.

[0114] The decomposition unit 30 is used to perform IQ decomposition on each of the above-mentioned symbols to be demodulated to obtain a co-directional component and a quadrature component. The quadrature component corresponds one-to-one with the above-mentioned symbols to be demodulated, and the co-directional component corresponds one-to-one with the above-mentioned symbols to be demodulated.

[0115] Specifically, the received demodulated symbols are decomposed into in-direction components and quadrature components, denoted as the I-path and Q-path, respectively. It can be seen that the fitting coefficients for the I-path and Q-path are the same.

[0116] The correction unit 40 is used to correct the corresponding LLR curves according to each intercept, noise variance, each of the same-direction components, each of the quadrature components and each correction factor to obtain multiple corrected LLR curves. The noise variance is used to characterize the degree of variation of the demodulated signal and the correction factor is used to correct the amplitude of the LLR curve.

[0117] Specifically, because the LLR values ​​of different bits have amplitude differences, a small fitting error for a particular bit will significantly increase when scaled to bits with smaller LLR amplitudes. Furthermore, during decoding, the LLR demodulation value of each bit is not calculated independently. Therefore, bits with larger error scales will interfere with bits with smaller errors, thus affecting the demodulation result. Therefore, this application uses the aforementioned slope, in-direction component, and quadrature component to calculate the correction factor for each bit, and then calculates the correction soft information for each bit based on the correction factor, in-direction component, quadrature component, and intercept.

[0118] In this embodiment, the demodulation unit is used to perform soft demodulation on the signal to be demodulated to obtain multiple LLR curves. The soft demodulation is a demodulation method that expresses the modulated signal using the log-likelihood ratio. The signal to be demodulated is the modulated signal received by the receiver, and the signal to be demodulated includes multiple symbols to be demodulated, each symbol including multiple bits. The LLR curves correspond one-to-one with the bits. The fitting unit is used to perform linear fitting on each of the LLR curves to obtain multiple slopes and multiple intercepts. The slopes correspond one-to-one with the LLR curves, and the intercepts correspond one-to-one with the LLR curves. The system includes a one-to-one correspondence unit; a decomposition unit for performing IQ decomposition on each of the aforementioned symbols to be demodulated to obtain in-phase and quadrature components, with each quadrature component corresponding one-to-one with the aforementioned symbols to be demodulated; and a correction unit for correcting the corresponding LLR curves based on each intercept, noise variance, each in-phase component, each quadrature component, and each correction factor to obtain multiple corrected LLR curves. The noise variance characterizes the degree of variation of the signal to be demodulated, and the correction factor corrects the amplitude of the LLR curves. Based on existing theoretical LLR curves, this application performs linear fitting on the existing theoretical LLR curves to determine the fitting coefficients; calculates the scaling factor corresponding to each fitting coefficient during the fitting process based on the fitting coefficients; and then calculates the correction factor based on the fitting coefficients and the scaling factor. The LLR curve corresponding to each symbol to be demodulated is then corrected based on the correction factor. This device performs linear fitting on the LLR curve, unifying discrete points onto a single curve. Compared to existing technologies that simplify the LLR curve before converting it into a piecewise function and then performing piecewise calculations, this significantly reduces the complex exponential and logarithmic operations and addition, subtraction, multiplication, and division operations in the signal demodulation process, thus solving the problem of high computational complexity in existing QAM modulation demodulation algorithms.

[0119] To obtain the aforementioned LLR curve, in one optional implementation, the demodulation unit includes:

[0120] The first determining module is used to determine the demodulated symbol set and the modulation order based on the demodulated signal. The demodulated symbol set includes all the demodulated symbols in the demodulated signal, and the modulation order is the number of bits contained in each demodulated symbol.

[0121] Specifically, the receiving end receives the demodulated signal after transmission through a Gaussian additive white noise channel, and obtains a demodulated symbol set containing multiple modulated symbols based on this signal. Then, the modulation order can be determined based on the number of bits contained in each demodulated signal.

[0122] The splitting module is used to split the above-mentioned demodulated symbol set into multiple bits according to the above-mentioned modulation order;

[0123] Specifically, each symbol in the modulation symbol set is differentially divided into multiple bits.

[0124] The second determining module is used to determine multiple LLR curves based on the multiple bits and the noise variance.

[0125] Specifically, by setting each bit as the independent variable, and substituting the set of symbols to be demodulated and the noise variance of the signal to be demodulated into the theoretical LLR formula of the LOG-MAP algorithm, the soft information corresponding to each bit, i.e., the LLR curve, can be obtained. The specific formula is as follows:

[0126]

[0127] Where x is a bit, s k For a finite set of symbols, σ 2 For noise variance, and These are sets containing finite symbols, where the i-th bit is 0 and the i-th bit is 1.

[0128] To fit the LLR curve and simplify the computational complexity of the demodulation process, in one optional implementation, the fitting unit includes:

[0129] The first sampling module is used to sample each of the above-mentioned LLR curves at equal intervals to obtain multiple first sample sets, and calculate the corresponding first mean, wherein the first mean is the mean of all samples in the above-mentioned first sample set.

[0130] Specifically, let Y be the sample set obtained by sampling the LLR curve at equal intervals, that is, the sample set Y = (y1, y2...y... n The sample is the y-value collected at equal intervals along the x-axis of the curve. Then, the mean of the samples in the sample set is calculated to obtain the first mean mentioned above.

[0131] A construction module is used to construct a first curve based on the noise variance and each of the bits, wherein the first curve is used to characterize the change of the quotient of the bits and the noise variance.

[0132] Specifically, construct curves This is the first curve mentioned above.

[0133] The second sampling module is used to sample the first curve at equal intervals to obtain multiple second sample sets, and to calculate the corresponding second mean, wherein the second mean is the mean of all samples in the second sample set.

[0134] Specifically, let X be the sample set obtained by sampling the first curve at equal intervals, that is, the sample set X = (x1, x2, ... x... n The sample is the y-value collected at equal intervals along the x-axis of the first curve. Then, the mean of the samples in the sample set is calculated to obtain the second mean mentioned above.

[0135] The calculation module is used to calculate multiple intercepts and multiple slopes based on multiple first sample sets, multiple second sample sets, corresponding first means and corresponding second means, wherein each intercept and slope corresponds one-to-one with the bit.

[0136] Specifically, data X is approximated by a first-order linear expression, i.e. Where α is the slope and β is the intercept. The mean square error of the fit can be expressed as: To ensure the linear approximation most closely approximates the original LLR theoretical curve, the least squares method is used to minimize the mean square error, thus obtaining the intercept and slope mentioned above. The specific formulas are as follows:

[0137]

[0138]

[0139] in, The first mean mentioned above, This is the second mean mentioned above.

[0140] To obtain the aforementioned correction factor, in one optional embodiment, the apparatus further includes:

[0141] The first determining unit is used to perform a determining step before correcting the corresponding LLR curves according to each intercept, noise variance, each in-direction component, each orthogonal component and each correction factor to obtain multiple corrected LLR curves. The determining unit is used to determine the corresponding peak value according to each slope. The peak value is the peak value of the LLR curve corresponding to the slope. The peak value corresponds one-to-one with the slope.

[0142] Specifically, since the fitting coefficients for the I-path and Q-path are the same, we can obtain different slopes under the same noise variance, i.e. Let M be the peak value of the LLR curve corresponding to each α during the fitting process, then we have

[0143] The first calculation unit is used to perform calculation steps, calculate each of the above-mentioned correction factors based on each of the above-mentioned slopes and peak values, and the above-mentioned correction factors correspond one-to-one with the above-mentioned slopes.

[0144] Specifically, based on the correspondence between slope and peak value, a scaling factor can be calculated for each slope, and then a correction factor can be calculated based on the scaling factor. The specific formula is as follows:

[0145]

[0146] γ=εα,

[0147] Where ε is the scaling factor mentioned above, and γ is the scaling factor.

[0148] To reduce the impact of linear fitting on the demodulation results, in one optional implementation, the correction unit includes:

[0149] The first correction module is used to perform a first correction step, which determines multiple first LLR curves of the target symbol to be demodulated based on the above-mentioned in-direction component, the above-mentioned noise variance, the above-mentioned correction factor and the above-mentioned intercept. The first LLR curve is the LLR curve corresponding to the odd-numbered bits in the target symbol to be demodulated, and the target symbol to be demodulated is one of the symbols to be demodulated.

[0150] Specifically, the corrected LLR curve for the first bit can be determined based on the noise variance, the in-direction component, and the correction factor and intercept corresponding to the first bit. The specific formula is as follows:

[0151] The second correction module is used to perform a second correction step, which determines multiple second LLR curves of the target symbol to be demodulated based on the above-mentioned quadrature components, the above-mentioned noise variance, the above-mentioned correction factor and the above-mentioned intercept, wherein the above-mentioned second LLR curves are the LLR curves corresponding to the even-numbered bits in the target symbol to be demodulated.

[0152] Specifically, the corrected LLR curve for the second bit can be determined based on the noise variance, the quadrature components, the correction factor corresponding to the second bit, and the intercept. The specific formula is as follows:

[0153] The repeating module is used to repeat the first correction step and the second correction step at least once in sequence until the corrected LLR curves corresponding to all bits of all the above-mentioned symbols to be demodulated are obtained, and the multiple corrected LLR curves include multiple first LLR curves and multiple second LLR curves.

[0154] Specifically, based on the recursive relationship, the coordinate relationship between the third bit and the first bit can be determined as follows: Where A is the amplitude of the LLR curve, and then the formula is used... The in-direction component corresponding to the third bit can then be calculated, and the LLR curve corresponding to the third bit can be corrected based on the correction factor corresponding to the third bit. Repeating the above recursive and calculation process completes the LLR curve correction for odd-numbered bits. According to the recursive relationship, the coordinate relationship between the second and fourth bits is as follows: Then through the formula The orthogonal component corresponding to the fourth bit can then be calculated, and the LLR curve corresponding to the fourth bit can be corrected based on the correction factor corresponding to the fourth bit. Repeating the above recursive and calculation process can complete the LLR curve correction for even-numbered bits.

[0155] To simplify the acquisition of noise variance, in an optional implementation, before determining the multiple LLR curves based on the multiple bits and the noise variance, the apparatus further includes:

[0156] The acquisition unit is used to acquire the signal-to-noise ratio and signal power of the signal to be demodulated.

[0157] Specifically, in actual calculations, the noise method is very complex to perform directly. Therefore, this application uses the signal-to-noise ratio to calculate the corresponding noise variance.

[0158] The second calculation unit is used to calculate the noise variance based on the signal-to-noise ratio and the signal power.

[0159] Specifically, the noise variance can be calculated based on the signal-to-noise ratio (SNR) and noise variance obtained above, using the relationship between SNR and noise variance. The specific relationship is as follows:

[0160]

[0161] Where SNR is the signal-to-noise ratio and P is the signal power.

[0162] To simplify the acquisition of correction factors, in an optional embodiment, after correcting the corresponding LLR curves according to each of the above-mentioned intercepts, noise variances, each of the above-mentioned in-direction components, each of the above-mentioned quadrature components, and each correction factor to obtain multiple corrected LLR curves, the apparatus further includes:

[0163] The first construction unit is used to construct a noise variance set based on the noise variance mentioned above, such that the ratio of any target noise variance in the noise variance set to the noise variance is within a preset range.

[0164] Specifically, the LLR curve is determined based on the noise variance. The same signal will generate different noise variances during channel transmission. Therefore, this application modifies the noise variance to obtain a noise variance group composed of different noise variances. The noise variance group includes the noise variance that may be generated during signal transmission in the channel.

[0165] The second construction unit is used to construct multiple lookup tables, which correspond one-to-one with the target noise variance of the noise variance group. The lookup tables are reference tables for the intercept, slope and correction factor under the target noise variance.

[0166] Specifically, based on the slope, intercept, and correction factor for each noise variance in the above noise variance group, a lookup table of multiple intercepts and correction factors is established.

[0167] The retrieval unit is configured to, upon receiving the signal to be demodulated, determine the corresponding lookup table based on the noise variance of the signal to be demodulated, and perform soft demodulation on the signal to be demodulated based on the lookup table.

[0168] Specifically, in the subsequent demodulation process, after receiving the signal to be demodulated, demodulation can be performed by looking up the corresponding table based on the noise variance, thus reducing the computational complexity in the demodulation process.

[0169] The aforementioned QAM modulation demodulation device includes a processor and a memory. The demodulation unit, fitting unit, decomposition unit, and correction unit are all stored as program units in the memory, and the processor executes these program units to achieve their respective functions. All of the above modules are located in the same processor; alternatively, the modules may be located in different processors in any combination.

[0170] The processor contains a kernel, which retrieves the corresponding program unit from memory. One or more kernels can be configured, and adjusting kernel parameters can reduce the computational complexity of QAM demodulation.

[0171] The memory may include non-permanent memory in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM, and the memory includes at least one memory chip.

[0172] This invention provides a computer-readable storage medium including a stored program, wherein, when the program is executed, it controls the device where the computer-readable storage medium is located to perform the QAM modulation demodulation method.

[0173] Specifically, the demodulation methods for QAM modulation include:

[0174] Step S201: Soft demodulation is performed on the signal to be demodulated to obtain multiple LLR curves. The soft demodulation is a demodulation method that expresses the modulated signal using the log-likelihood ratio. The signal to be demodulated is the modulated signal received by the receiver. The signal to be demodulated includes multiple symbols to be demodulated. Each symbol to be demodulated includes multiple bits. The LLR curves correspond one-to-one with the bits.

[0175] Step S202: Perform linear fitting on each of the above LLR curves to obtain multiple slopes and multiple intercepts. The slopes correspond one-to-one with the above LLR curves, and the intercepts correspond one-to-one with the above LLR curves.

[0176] Step S203: Perform IQ decomposition on each of the above-mentioned symbols to be demodulated to obtain in-phase components and quadrature components. The quadrature components correspond one-to-one with the above-mentioned symbols to be demodulated, and the in-phase components correspond one-to-one with the above-mentioned symbols to be demodulated.

[0177] Step S204: Based on each of the above intercepts, noise variances, in-phase components, quadrature components, and correction factors, the corresponding LLR curves are corrected to obtain multiple corrected LLR curves. The noise variance is used to characterize the degree of variation of the demodulated signal, and the correction factors are used to correct the amplitude of the LLR curves.

[0178] This invention provides a processor for running a program, wherein the program executes the QAM modulation demodulation method.

[0179] Specifically, the demodulation methods for QAM modulation include:

[0180] Step S201: Soft demodulation is performed on the signal to be demodulated to obtain multiple LLR curves. The soft demodulation is a demodulation method that expresses the modulated signal using the log-likelihood ratio. The signal to be demodulated is the modulated signal received by the receiver. The signal to be demodulated includes multiple symbols to be demodulated. Each symbol to be demodulated includes multiple bits. The LLR curves correspond one-to-one with the bits.

[0181] Step S202: Perform linear fitting on each of the above LLR curves to obtain multiple slopes and multiple intercepts. The slopes correspond one-to-one with the above LLR curves, and the intercepts correspond one-to-one with the above LLR curves.

[0182] Step S203: Perform IQ decomposition on each of the above-mentioned symbols to be demodulated to obtain in-phase components and quadrature components. The quadrature components correspond one-to-one with the above-mentioned symbols to be demodulated, and the in-phase components correspond one-to-one with the above-mentioned symbols to be demodulated.

[0183] Step S204: Based on each of the above intercepts, noise variances, in-phase components, quadrature components, and correction factors, the corresponding LLR curves are corrected to obtain multiple corrected LLR curves. The noise variance is used to characterize the degree of variation of the demodulated signal, and the correction factors are used to correct the amplitude of the LLR curves.

[0184] This invention provides a demodulation device, which includes a processor, a memory, and a program stored in the memory and executable on the processor. When the processor executes the program, it performs at least the following steps:

[0185] Step S201: Soft demodulation is performed on the signal to be demodulated to obtain multiple LLR curves. The soft demodulation is a demodulation method that expresses the modulated signal using the log-likelihood ratio. The signal to be demodulated is the modulated signal received by the receiver. The signal to be demodulated includes multiple symbols to be demodulated. Each symbol to be demodulated includes multiple bits. The LLR curves correspond one-to-one with the bits.

[0186] Step S202: Perform linear fitting on each of the above LLR curves to obtain multiple slopes and multiple intercepts. The slopes correspond one-to-one with the above LLR curves, and the intercepts correspond one-to-one with the above LLR curves.

[0187] Step S203: Perform IQ decomposition on each of the above-mentioned symbols to be demodulated to obtain in-phase components and quadrature components. The quadrature components correspond one-to-one with the above-mentioned symbols to be demodulated, and the in-phase components correspond one-to-one with the above-mentioned symbols to be demodulated.

[0188] Step S204: Based on each of the above intercepts, noise variances, in-phase components, quadrature components, and correction factors, the corresponding LLR curves are corrected to obtain multiple corrected LLR curves. The noise variance is used to characterize the degree of variation of the demodulated signal, and the correction factors are used to correct the amplitude of the LLR curves.

[0189] This application also provides a computer program product, which, when executed on a data processing device, is suitable for executing an initialization program having at least the following method steps:

[0190] Step S201: Soft demodulation is performed on the signal to be demodulated to obtain multiple LLR curves. The soft demodulation is a demodulation method that expresses the modulated signal using the log-likelihood ratio. The signal to be demodulated is the modulated signal received by the receiver. The signal to be demodulated includes multiple symbols to be demodulated. Each symbol to be demodulated includes multiple bits. The LLR curves correspond one-to-one with the bits.

[0191] Step S202: Perform linear fitting on each of the above LLR curves to obtain multiple slopes and multiple intercepts. The slopes correspond one-to-one with the above LLR curves, and the intercepts correspond one-to-one with the above LLR curves.

[0192] Step S203: Perform IQ decomposition on each of the above-mentioned symbols to be demodulated to obtain in-phase components and quadrature components. The quadrature components correspond one-to-one with the above-mentioned symbols to be demodulated, and the in-phase components correspond one-to-one with the above-mentioned symbols to be demodulated.

[0193] Step S204: Based on each of the above intercepts, noise variances, in-phase components, quadrature components, and correction factors, the corresponding LLR curves are corrected to obtain multiple corrected LLR curves. The noise variance is used to characterize the degree of variation of the demodulated signal, and the correction factors are used to correct the amplitude of the LLR curves.

[0194] It is obvious to those skilled in the art that the modules or steps of the present invention described above can be implemented using general-purpose computing devices. They can be centralized on a single computing device or distributed across a network of multiple computing devices. They can be implemented using computer-executable program code, and thus can be stored in a storage device for execution by a computing device. In some cases, the steps shown or described can be performed in a different order than those described herein, or they can be fabricated as separate integrated circuit modules, or multiple modules or steps can be fabricated as a single integrated circuit module. Thus, the present invention is not limited to any particular combination of hardware and software.

[0195] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0196] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0197] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0198] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0199] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0200] Memory may include non-persistent memory in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0201] Computer-readable media includes both permanent and non-permanent, removable and non-removable media that can store information using any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic magnetic disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.

[0202] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus. 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 apparatus that includes that element.

[0203] As can be seen from the above description, the embodiments of this application achieve the following technical effects:

[0204] 1) The QAM modulation demodulation method of this application firstly performs soft demodulation on the signal to be demodulated to obtain multiple LLR curves. The soft demodulation is a demodulation method that expresses the modulated signal using the log-likelihood ratio. The signal to be demodulated is the modulated signal received by the receiver, which includes multiple demodulated symbols, each of which includes multiple bits. The LLR curves correspond one-to-one with the bits. Then, linear fitting is performed on each LLR curve to obtain multiple slopes and multiple intercepts. The slopes correspond one-to-one with the LLR curves, and the intercepts correspond one-to-one with the LLR curves. The LLR curves are one-to-one correspondences. Then, IQ decomposition is performed on each of the aforementioned symbols to be demodulated to obtain in-phase and quadrature components. The quadrature components and in-phase components each correspond one-to-one with the aforementioned symbols to be demodulated. Finally, the corresponding LLR curves are corrected according to the intercepts, noise variance, in-phase components, quadrature components, and correction factors to obtain multiple corrected LLR curves. The noise variance characterizes the degree of variation of the demodulated signal, and the correction factors correct the amplitude of the LLR curves. This application, based on existing theoretical LLR curves, performs linear fitting on the existing theoretical LLR curves to determine the fitting coefficients; calculates the scaling factor corresponding to each fitting coefficient during the fitting process based on the fitting coefficients, and then calculates the correction factor based on the fitting coefficients and scaling factors. The LLR curve corresponding to each symbol to be demodulated is corrected according to the correction factor. This method performs linear fitting on the LLR curve, unifying discrete points onto a single curve. Compared to existing technologies that simplify the LLR curve before converting it into a piecewise function and then performing piecewise calculations, this method significantly reduces the complex exponential and logarithmic operations and addition, subtraction, multiplication, and division operations in the signal demodulation process, thus solving the problem of high computational complexity in existing QAM modulation demodulation algorithms.

[0205] 2) The QAM modulation demodulation apparatus of this application includes a demodulation unit for soft demodulating the signal to be demodulated to obtain multiple LLR curves. The soft demodulation is a demodulation method that expresses the modulated signal using the log-likelihood ratio. The signal to be demodulated is the modulated signal received by the receiver. The signal to be demodulated includes multiple symbols to be demodulated, each symbol including multiple bits. The LLR curves correspond one-to-one with the bits. A fitting unit is used to perform linear fitting on each of the LLR curves to obtain multiple slopes and multiple intercepts. The slopes correspond one-to-one with the LLR curves, and the intercepts correspond one-to-one with the LLR curves. The LLR curves are one-to-one; the decomposition unit is used to perform IQ decomposition on each of the above-mentioned symbols to be demodulated to obtain in-phase components and quadrature components, the quadrature components and the in-phase components are one-to-one corresponding to the above-mentioned symbols to be demodulated; the correction unit is used to correct the corresponding LLR curves according to each intercept, noise variance, in-phase component, quadrature component and correction factor to obtain multiple corrected LLR curves, the noise variance is used to characterize the degree of variation of the above-mentioned signal to be demodulated, and the correction factor is used to correct the amplitude of the above-mentioned LLR curves. This application, based on the existing theoretical LLR curves, performs linear fitting on the existing theoretical LLR curves to determine the fitting coefficients; calculates the scaling factor corresponding to each fitting coefficient in the fitting process according to the fitting coefficients, and then calculates the correction factor according to the fitting coefficients and the scaling factor. The LLR theoretical curve corresponding to each symbol to be demodulated is corrected according to the correction factor. This device performs linear fitting on the LLR curve, unifying discrete points onto a single curve. Compared to existing technologies that simplify the LLR curve before converting it into a piecewise function and then performing piecewise calculations, this significantly reduces the complex exponential and logarithmic operations and addition, subtraction, multiplication, and division operations in the signal demodulation process, thus solving the problem of high computational complexity in existing QAM modulation demodulation algorithms.

[0206] The above description is merely a preferred embodiment of this application and is not intended to limit this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A demodulation method for QAM modulation, characterized in that, include: Multiple LLR curves are obtained by performing soft demodulation on the signal to be demodulated. The soft demodulation is a demodulation method that expresses the modulated signal using the log-likelihood ratio. The signal to be demodulated is the modulated signal received by the receiving end. The signal to be demodulated includes multiple symbols to be demodulated. Each symbol to be demodulated includes multiple bits. The LLR curves correspond one-to-one with each bit. Linear fitting is performed on each of the LLR curves to obtain multiple slopes and multiple intercepts, wherein the slopes correspond one-to-one with the LLR curves and the intercepts correspond one-to-one with the LLR curves; IQ decomposition is performed on each of the demodulated symbols to obtain in-phase components and quadrature components. The quadrature components correspond one-to-one with the demodulated symbols, and the in-phase components correspond one-to-one with the demodulated symbols. Multiple modified LLR curves are obtained by modifying the corresponding LLR curves according to each intercept, noise variance, in-phase component, quadrature component and correction factor. The noise variance is used to characterize the degree of variation of the signal to be demodulated, and the correction factor is used to modify the amplitude of the LLR curve. The LLR curves are modified according to the intercepts, noise variances, in-phase components, quadrature components, and correction factors to obtain multiple modified LLR curves. The modification includes: a first modification step, determining multiple first LLR curves for the target symbol to be demodulated based on the in-phase components, noise variances, correction factors, and intercepts, where the first LLR curves are the LLR curves corresponding to the odd-numbered bits of the target symbol to be demodulated, and the target symbol to be demodulated is one of the symbols to be demodulated; a second modification step, determining multiple second LLR curves for the target symbol to be demodulated based on the quadrature components, noise variances, correction factors, and intercepts, where the second LLR curves are the LLR curves corresponding to the even-numbered bits of the target symbol to be demodulated; repeating the first and second modification steps at least once until all the modified LLR curves corresponding to all the bits of all the symbols to be demodulated are obtained, where the multiple modified LLR curves include multiple first LLR curves and multiple second LLR curves. After obtaining multiple modified LLR curves by modifying the corresponding LLR curves according to each intercept, noise variance, in-phase component, quadrature component, and correction factor, the method further includes: constructing a noise variance group based on the noise variance, such that the ratio of any target noise variance in the noise variance group to the noise variance is within a preset range; constructing multiple lookup tables, each lookup table corresponding one-to-one with the target noise variance of the noise variance group, wherein the lookup table is a lookup table for the intercept, slope, and correction factor under the target noise variance; and, upon receiving the signal to be demodulated, determining the corresponding lookup table based on the noise variance of the signal to be demodulated, and performing soft demodulation on the signal to be demodulated based on the lookup table.

2. The method according to claim 1, characterized in that, Soft demodulation of the signal to be demodulated yields multiple LLR curves, including: The demodulated symbol set and modulation order are determined based on the demodulated signal. The demodulated symbol set contains all the demodulated symbols in the demodulated signal, and the modulation order is the number of bits contained in each demodulated symbol. The set of symbols to be demodulated is split into multiple bits according to the modulation order; Multiple LLR curves are determined based on the multiple bits and the noise variance.

3. The method according to claim 2, characterized in that, Linear fitting was performed on each of the LLR curves to obtain multiple slopes and multiple intercepts, including: Multiple first sample sets are obtained by sampling each LLR curve at equal intervals, and the corresponding first mean is calculated. The first mean is the mean of all samples in the first sample set. A first curve is constructed based on the noise variance and each bit, and the first curve is used to characterize the change of the quotient of the bit and the noise variance; Multiple second sample sets are obtained by sampling the first curve at equal intervals, and the corresponding second mean is calculated. The second mean is the mean of all samples in the second sample set. Multiple intercepts and multiple slopes are calculated based on multiple first sample sets, multiple second sample sets, corresponding first means and corresponding second means, and each intercept and slope corresponds one-to-one with a bit.

4. The method according to claim 3, characterized in that, Before correcting the corresponding LLR curves according to each intercept, noise variance, in-phase component, quadrature component, and correction factor to obtain multiple corrected LLR curves, the method further includes: The determination step involves identifying the corresponding peak value based on each slope, where the peak value is the peak value of the LLR curve corresponding to the slope, and the peak value corresponds one-to-one with the slope. The calculation steps involve calculating each correction factor based on the slope and the peak value, with each correction factor corresponding to a slope.

5. The method according to claim 2, characterized in that, Before determining the multiple LLR curves based on the multiple bits and the noise variance, the method further includes: Obtain the signal-to-noise ratio and signal power of the signal to be demodulated; The noise variance is calculated based on the signal-to-noise ratio and the signal power.

6. A QAM-modulated demodulation device, characterized in that, The device includes: The demodulation unit is used to perform soft demodulation on the signal to be demodulated to obtain multiple LLR curves. The soft demodulation is a demodulation method that expresses the modulated signal using the log-likelihood ratio. The signal to be demodulated is the modulated signal received by the receiving end. The signal to be demodulated includes multiple symbols to be demodulated. Each symbol to be demodulated includes multiple bits. The LLR curves correspond one-to-one with the bits. The fitting unit is used to perform linear fitting on each of the LLR curves to obtain multiple slopes and multiple intercepts, wherein the slopes correspond one-to-one with the LLR curves and the intercepts correspond one-to-one with the LLR curves. The decomposition unit is used to perform IQ decomposition on each of the symbols to be demodulated to obtain in-phase components and quadrature components, wherein the quadrature components correspond one-to-one with the symbols to be demodulated, and the in-phase components correspond one-to-one with the symbols to be demodulated. The correction unit is used to correct the corresponding LLR curves according to each intercept, noise variance, in-phase component, quadrature component and correction factor to obtain multiple corrected LLR curves. The noise variance is used to characterize the degree of variation of the signal to be demodulated, and the correction factor is used to correct the amplitude of the LLR curve. The correction unit includes: a first correction module, configured to perform a first correction step, determining multiple first LLR curves for the target symbol to be demodulated based on the in-phase component, the noise variance, the correction factor, and the intercept, wherein the first LLR curves are LLR curves corresponding to the odd-numbered bits of the target symbol to be demodulated, and the target symbol to be demodulated is one of the symbols to be demodulated; a second correction module, configured to perform a second correction step, determining multiple second LLR curves for the target symbol to be demodulated based on the quadrature component, the noise variance, the correction factor, and the intercept, wherein the second LLR curves are LLR curves corresponding to the even-numbered bits of the target symbol to be demodulated; and a repetition module, configured to repeat the first correction step and the second correction step at least once in sequence until the corrected LLR curves corresponding to all bits of all the symbols to be demodulated are obtained, wherein the multiple corrected LLR curves include multiple first LLR curves and multiple second LLR curves; The apparatus further includes: a first construction unit, configured to, after correcting the corresponding LLR curves according to each intercept, the noise variance, each in-phase component, each quadrature component, and each correction factor to obtain multiple corrected LLR curves, construct a noise variance group based on the noise variance, such that the ratio of any target noise variance in the noise variance group to the noise variance is within a preset range; a second construction unit, configured to construct multiple lookup tables, each lookup table corresponding one-to-one with the target noise variance of the noise variance group, wherein the lookup table is a lookup table for the intercept, the slope, and the correction factor under the target noise variance; and a retrieval unit, configured to, upon receiving the signal to be demodulated, determine the corresponding lookup table based on the noise variance of the signal to be demodulated, and perform soft demodulation on the signal to be demodulated based on the lookup table.

7. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored program, wherein, when the program is executed, it controls the device on which the computer-readable storage medium is located to perform the method according to any one of claims 1 to 5.

8. A demodulation device, characterized in that, include: One or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs including methods for performing any one of claims 1 to 5.

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