Data modulation method, communication node and storage medium

By modulating and Fourier transforming the data sequence and then extracting a portion of the data, the peak-to-average power ratio (PAPR) of the signal is optimized, solving the problem of excessively high PAPR in multi-carrier orthogonal frequency division multiplexing signals, and improving the efficiency of the power amplifier and the coverage capability of the communication system.

WO2026086551A1PCT designated stage Publication Date: 2026-04-30ZTE CORP
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Patent Information

Authority / Receiving Office
WO · WO
Patent Type
Applications
Current Assignee / Owner
ZTE CORP
Filing Date
2025-09-26
Publication Date
2026-04-30

AI Technical Summary

Technical Problem

In existing communication systems, the peak-to-average power ratio (PAPR) of multi-carrier orthogonal frequency division multiplexing signals is too high, which leads to a decrease in the efficiency of power amplifiers and affects the coverage and signal transmission quality of the communication system.

Method used

The first data sequence is modulated to form the second data sequence, and after Fourier transform, R times the data is extracted from the third data sequence to form the fourth data sequence, where R is less than 1. The extraction position is optimized by combining the average power spectral density map to reduce the peak-to-average power ratio.

Benefits of technology

It effectively reduces the peak-to-average power ratio of the signal, reduces the nonlinear distortion of the power amplifier, improves the operating efficiency of the power amplifier, and enhances the coverage and signal transmission quality of the communication system.

✦ Generated by Eureka AI based on patent content.

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Abstract

Provided in the present application are a data modulation method, a communication node, and a storage medium. The data modulation method comprises: modulating a first data sequence to form a second data sequence; performing Fourier transform on the second data sequence to form a third data sequence; and intercepting R times of data from the third data sequence to form a fourth data sequence, wherein R is less than 1.
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Description

Data modulation method, communication node and storage medium Technical Field

[0001] This application relates to the field of wireless communication technology, such as data modulation methods, communication nodes, and storage media. Background Technology

[0002] With the development of wireless communication technology, the capacity and coverage of communication systems are constantly expanding, and the requirements for signal quality are becoming increasingly stringent. The peak-to-average power ratio (PAPR) of a communication signal is a key indicator for measuring signal quality and power amplifier efficiency. An excessively high PAPR can lead to reduced power amplifier efficiency, thereby affecting the coverage capability and signal transmission quality of the communication system.

[0003] In communication systems, multi-carrier Orthogonal Frequency Division Multiplexing (OFDM) signals have a high PAPR (Power Amplitude Reduction). A high PAPR means that the peak power of the signal is much greater than the average power. This not only leads to nonlinear distortion in the power amplifier but also forces the power amplifier to operate at high power, thereby increasing energy consumption and heat loss, and reducing its efficiency. Although single-carrier OFDM (DFT-s-OFDM) signals based on Discrete Fourier Transform have a relatively low PAPR, it is still difficult to meet the low PAPR requirements of future communications. Summary of the Invention

[0004] This application provides a data modulation method, a communication node, and a storage medium.

[0005] This application provides a data modulation method, including: modulating a first data sequence to form a second data sequence; performing a Fourier transform on the second data sequence to form a third data sequence; and extracting R times the data from the third data sequence to form a fourth data sequence, where R is less than 1.

[0006] This application also provides a communication node, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the above-described data modulation method.

[0007] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described data modulation method. Attached Figure Description

[0008] Figure 1 is a flowchart of a data modulation method provided in an embodiment;

[0009] Figure 2 is a schematic diagram of a modulation process of a first data sequence provided in an embodiment;

[0010] Figure 3 is a schematic diagram of another modulation process of a first data sequence provided in one embodiment;

[0011] Figure 4 is a schematic diagram of the power spectral density of a third data sequence obtained by Fourier transform and semi-cyclic shift according to an embodiment.

[0012] Figure 5 is a schematic diagram of a data modulation process provided in one embodiment;

[0013] Figure 6 is a schematic diagram of the power spectral density of a third data sequence provided in one embodiment;

[0014] Figure 7 is a schematic diagram of a data modulation device provided in one embodiment;

[0015] Figure 8 is a schematic diagram of the hardware structure of a communication node according to an embodiment. Detailed Implementation

[0016] The present application will now be described in conjunction with the accompanying drawings and embodiments. The specific embodiments described herein are merely illustrative of the present application. Unless otherwise specified, the embodiments and features described herein can be arbitrarily combined with each other. For ease of description, only the parts relevant to the present application are shown in the accompanying drawings.

[0017] Figure 1 is a flowchart of a data modulation method according to an embodiment. This method can be applied to a data modulation device or a data transmission device. As shown in Figure 1, the method provided in this embodiment includes:

[0018] 110. Modulate the first data sequence to form the second data sequence.

[0019] 120. Perform a Fourier transform on the second data sequence to form the third data sequence.

[0020] 130. Extract R times the amount of data from the third data sequence to form a fourth data sequence, where R is less than 1.

[0021] The data modulation method in this embodiment involves inserting data into a first data sequence to form a second data sequence, then performing a Fourier transform on the second data sequence to form a third data sequence, and finally extracting R times the amount of data from the third data sequence. Based on the average power spectral density (PSD) plot of the third data sequence, it can be seen that by setting a reasonable factor, the minimum value of the modulus of the third data sequence (e.g., at 3 / 4 of the bandwidth) can be used as a boundary for truncation, achieving lower out-of-band leakage, thereby reducing the peak-to-average power ratio and minimizing performance loss.

[0022] In one embodiment, R takes one of the following values: 3 / 4, 3 / 5, [1 / 2, 3 / 4], [1 / 2, 17 / 20].

[0023] In one embodiment, the first data sequence is a bit sequence consisting of zero data and data with a value of 1.

[0024] In one embodiment, the first data sequence is formed by transforming a sequence of data with a value of 1 and data with a value of -1; the transformation satisfies the following: data with a value of 1 is transformed into zero data, and data with a value of -1 is transformed into 1.

[0025] In one embodiment, modulating the first data sequence to form the second data sequence includes: when k is even, k = 2i. When k is odd, k = 2i + 1. or,

[0026] Where i = 0, 1, 2, ..., I-1, I is the number of elements in the first data sequence, or the number of bits in a data block; k = 0, 1, 2, ..., 2I-1, 2I is the number of elements in the second data sequence; b(i) is an element of the first data sequence; d(k) is an element of the second data sequence; a equals 1 or -1, and θ is a preset constant or 0.

[0027] In one embodiment, modulating a first data sequence to form a second data sequence includes: or Where i = 0, 1, 2, ..., I-1, I is twice the number of elements in the first data sequence, or twice the number of bits in a data block, and I is also the number of elements in the second data sequence; and d(i) is an element of the first data sequence; d(i) is an element of the second data sequence; θ is a preset constant or 0.

[0028] In one embodiment, c is π / 4, π, or 5π / 4; s is -π / 4, π, or 3π / 4.

[0029] In one embodiment, extracting R times the data from the third data sequence includes: extracting R times the data from the third data sequence and discarding the remaining data in the third data sequence other than the extracted R times the data.

[0030] In one embodiment, extracting R times the amount of data from the third data sequence includes: performing a dot product between the third data sequence and the fifth data sequence to obtain a dot product data sequence; discarding zero data obtained by multiplying zero data in the dot product data sequence from the zero data in the fifth data sequence; the number of non-zero data in the fifth data sequence is R times the number of data in the third data sequence, and the number of zero data in the fifth data sequence is 1-R times the number of data in the third data sequence.

[0031] In one embodiment, in the fifth data sequence, the number of data with a value of 1 is R times the number of data in the third data sequence, and the number of zero data is (1-R) ​​times the number of data in the third data sequence.

[0032] In one embodiment, extracting R times the amount of data from the third data sequence includes: filtering the frequency domain third data sequence using a filtering function, wherein the width of the filtering function in the frequency domain is R times the width of the frequency domain of the third data sequence.

[0033] In one embodiment, the filtering function is a root-raised cosine function or a raised cosine function, with a roll-off factor of [0, 0.7].

[0034] In one embodiment, the filtering function is a rectangular function with a roll-off factor of 0.

[0035] In one embodiment, the fifth data sequence is the discrete values ​​of the filtering function.

[0036] In one embodiment, extracting R times the data from the third data sequence to form a fourth data sequence includes: cyclically shifting the third data sequence, and extracting R times the continuous data from the cyclically shifted data sequence to form the fourth data sequence.

[0037] In one embodiment, extracting R times the data from the third data sequence to form a fourth data sequence includes: directly extracting R times the continuous data from the third data sequence to form the fourth data sequence.

[0038] In one embodiment, extracting R times the data from the third data sequence to form a fourth data sequence includes: extracting R times the data from both ends of the third data sequence. Alternatively, extracting R times the data from the middle of the third data sequence.

[0039] In one embodiment, the method further includes: according to The frequency position of R, where R is zero or near zero in the power spectral density, is determined by f, which is equal to 1 or -1; where p is a constant and f is the power factor. The frequency points at or near the zero value in the power spectral density are used as boundaries. The data portion of the third data sequence corresponding to the intermediate frequency domain interval within the two boundaries is extracted to form the fourth data sequence.

[0040] In one embodiment, p takes the value 1, or

[0041] In one embodiment, the first data sequence is a part of a sixth data sequence, the length of which is greater than the length of the first data sequence.

[0042] In one embodiment, the method further includes: performing an oversampled inverse Fourier transform on the fourth data sequence to form time-domain data; and transmitting the time-domain data.

[0043] In one embodiment, the method further includes: performing a filtering operation on the fourth data sequence; performing an oversampled inverse Fourier transform on the filtered data sequence to form time-domain data; and transmitting the time-domain data.

[0044] In one embodiment, the method further includes multiplying the fourth data sequence by a power factor before performing the oversampled inverse Fourier transform.

[0045] The data modulation method of this application is illustrated by some embodiments below.

[0046] Example 1

[0047] This embodiment is an example of modulating a first data sequence to form a second data sequence.

[0048] In this embodiment, the first data sequence is modulated to form the second data sequence.

[0049] Assume the first data sequence is a sequence of bits 0 and 1, containing elements b(i) and number I, expressed as: [b(i) = 0 or 1, i = 0, 1, 2, ..., I-1]; the second data sequence contains elements d[i] and number 2I, expressed as: [d(k), k = 0, 1, 2, ..., 2I-1]; the second data sequence is formed by modulating the first data sequence. The modulation process is as follows: when k is even, k = 2i, ... When k is odd, k = 2i + 1 or, Where, when b(i)=0, [(1-2b(i))+j(1-2b(i))]=1+1j, when b(i)=1, [(1-2b(i))+j(1-2b(i))]=-1-1j; when i=0,1,2,...,I-1, and θ=0, ej(π(i mod 2) / 2)=[1,1j,1,1j,1,1j,...,1,1j]; when k=2i+1=1,3,5,...,2I-1, k-1=0,2,4,...,2I-2, (k+1)mod(2I)=[2,4,6,...,2I-2,0].

[0050] When k is even, k = 0, 2, 4, ..., 2(I-1), the characteristic of element d(k) in the second data sequence is: the first modulation data sequence is formed by [(1-2b(i)) + j(1-2b(i))], and the phase of the even-position elements (i.e., the 2nd element, the 4th element, the 6th element...) in the first modulation data sequence is rotated by π / 2, and all of them are subjected to... Power is normalized to form the element d(k) in the second data sequence.

[0051] For k to be odd, k = 1, 3, 5, ..., 2I-1, the characteristic of element d(k) in the second data sequence is: element d(k-1) and element d(k+1) are added together and then... Power normalization is formed by d(k), which is achieved by adding elements d(0) and d(2) and performing the operation. Power normalization forms element d(1), elements d(2) and d(4) are added and then processed. Power normalization forms d(3), and so on, the elements d(2I-2) and d(0) are added and then... Power normalization forms d(2I-1).

[0052] Alternatively, for odd numbers, k = 1, 3, 5, ..., 2I-1, the characteristics of element d(k) in the second data sequence are: the square root of element d(k-1) and element d(k+1) multiplied by a forms d(k), that is, the square root of element d(0) and element d(2) multiplied by a forms element d(1), the square root of element d(2) and element d(4) multiplied by a forms d(3), and so on, the square root of element d(2I-2) and element d(0) multiplied by a forms d(2I-1).

[0053] Example 2

[0054] This embodiment is an example of modulating a first data sequence to form a second data sequence.

[0055] In this embodiment, the first data sequence [b(i), i = 0, 1, 2, ..., I-1] is modulated using the modulation method of Embodiment 1 to form the second data sequence [d(k), k = 0, 1, 2, ..., 2I-1].

[0056] In this embodiment, the first data sequence is assumed to be: [b(i), i = 0, 1, 2, 3, 4, 5] = [1, 1, 0, 1, 0, 0], and the modulation process is shown in Figure 2.

[0057] When k = 0, 2, 4, 6, 8, 10 is even:

[0058] When k = 1, 3, 5, 7, 9, 11 is odd:

[0059] Or d(1) = a(d(0)d(2)) 1 / 2 =-aj

[0060] Or d(3) = a(d(2)d(4)) 1 / 2 =a

[0061] Or d(5) = a(d(4)d(6)) 1 / 2 =a

[0062] Or d(7) = a(d(6)d(8)) 1 / 2 =a

[0063] Or d(9) = a(d(8)d(10)) 1 / 2 =aj

[0064] Or d(11) = a(d(10)d(0)) 1 / 2 =-a

[0065] Therefore, the second data sequence is: When a equals 1 or -1, the modulus of the data in the second data sequence is 1. When a equals 1, the phase difference between adjacent data is ±π / 4.

[0066] Example 3

[0067] This embodiment is an example of modulating a first data sequence to form a second data sequence.

[0068] In this embodiment, the first data sequence is modulated to form the second data sequence.

[0069] Assume the first data sequence is a sequence of bits 0 and 1, containing elements b(i) and having a number of elements I / 2. The first data sequence can be expressed as: [b(i) = 0 or 1, i = 0, 1, 2, ..., I / 2-1]; the second data sequence contains elements d[i] and has a number of elements I. The second data sequence can be expressed as: [d(i), k = 0, 1, 2, ..., I-1]; the first data sequence is modulated to form the second data sequence. The modulation process is as follows: or Where, when i = 0, 1, 2, ..., I-1, When b(i) = 0 or 1, Or -1, Or -1j; when i = 0, 1, 2, ..., I-1, θ equals 0, c equals π / 4, π, 5π / 4, and s equals -π / 4, π, 3π / 4.

[0070] The characteristics of element d(i) in the second data sequence are as follows: element b(i) in the first data sequence is repeated once to form the first modulation data sequence; all elements except the first element in element b(i) in the first data sequence are repeated once, and a second first element is placed at the end to form the second modulation data sequence; the first and second modulation data sequences are used as the real and imaginary parts, respectively, to form the third modulation data sequence; then the phase of the third modulation data sequence is rotated ci sequentially, and all of them are subjected to... Power normalization is performed to form the elements d(i) in the second data sequence; or the first and second modulation data sequences are used as the imaginary and real parts, respectively, to form the third modulation data sequence, and then the phase of the third modulation data sequence is rotated si in sequence, and all of them are subjected to... Power is normalized and used to form the elements d(i) in the second data sequence.

[0071] Example 4

[0072] This embodiment is an example of modulating a first data sequence to form a second data sequence.

[0073] In this embodiment, the first data sequence [b(i), i = 0, 1, 2, ..., I / 2-1] is modulated using the modulation method of Embodiment 3 to form the second data sequence [d(i), i = 0, 1, 2, ..., I-1], where c equals π / 4.

[0074] In this embodiment, the first data sequence is assumed to be: [b(i), i = 0, 1, 2, 3, 4, 5] = [1, 1, 0, 1, 0, 0], and the modulation process is shown in Figure 3.

[0075] Therefore, the second data sequence is: The modulus of the data in the second data sequence is 1, and the phase difference between adjacent data is ±π / 4.

[0076] Example 5

[0077] This embodiment is an example of modulating a first data sequence to form a second data sequence.

[0078] In this embodiment, the first data sequence [b(i), i = 0, 1, 2, ..., I / 2-1] is modulated using the modulation method of Embodiment 3 to form the second data sequence [d(i), i = 0, 1, 2, ..., I-1], where c equals π.

[0079] In this embodiment, it is assumed that the first data sequence is: [b(i), i = 0, 1, 2, 3, 4, 5] = [1, 1, 0, 1, 0, 0]. Therefore...

[0080] Therefore, the second data sequence is: In the second data sequence, the modulus of the data is 1, and the phase difference between adjacent data is ±π or ±π / 2.

[0081] Example 6

[0082] This embodiment is based on R. This is an example of determining the location of a frequency point near or at zero in the power spectral density.

[0083] In this embodiment, for The power spectral density of the sequence is obtained by performing a Fourier transform and a semi-circular shift. As shown in Figure 4. In Figure 4, the horizontal axis represents the relative frequency (Hz), and the vertical axis represents the magnitude. The zero value of the power spectral density is located at [-3 / 8] and [3 / 8] on the horizontal axis. Therefore, the value of R in the data extracted from the third data sequence is determined based on the position of the zero value or the frequency point near the zero value in the power spectral density of the sequence.

[0084] R can take the value 3 / 4, or 3 / 5, or [1 / 2, 3 / 4], or [1 / 2, 17 / 20].

[0085] when sequence When the length of the sequence is the same as that of the third data sequence, the power spectral density of the sequence is the same as that of the statistical average power spectral density of the third data sequence. Extracting R times the data from the third data sequence to form the fourth data sequence can minimize the modulus of the fourth data sequence. When R is 3 / 4, the modulus of the fourth data sequence is minimized.

[0086] In other embodiments, R is based on The location of the frequency point at or near the zero value in the power spectral density is determined, and the frequency point at or near the zero value is determined. The power spectral density of the sequence obtained by performing a Fourier transform has the same shape as that in Figure 3.

[0087] or The power spectral density plot contains a large peak and a small peak. The position of the large peak is used to determine the position of the data extracted from the third data sequence and the R value.

[0088] according to The frequency points at or near the zero value in the power spectral density are used as boundaries. The data portion of the third data sequence corresponding to the intermediate frequency domain interval within the two boundaries is extracted to form the fourth data sequence.

[0089] Example 7

[0090] This embodiment is an example of forming a fourth data sequence from a first data sequence.

[0091] Figure 5 is a schematic diagram of a data modulation process provided in one embodiment. As shown in Figure 5, in this embodiment, a fourth data sequence is formed from a first data sequence; the first data sequence is modulated to form a second data sequence; then, a Fourier transform is performed on the second data sequence to form a third data sequence; then, R times the data is truncated to form a fourth data sequence; then, subcarrier mapping and oversampling inverse Fourier transform are performed on the fourth data sequence to form time-domain data, which is then transmitted. Alternatively, a Fourier transform and cyclic shift are performed on the second data sequence to form a third data sequence; then, R times the data is truncated to form a fourth data sequence; then, subcarrier mapping and oversampling inverse Fourier transform are performed on the fourth data sequence to form time-domain data, which is then transmitted. Where R < 1.

[0092] Extracting R times the data can be done by directly taking R times the data of the third data sequence, discarding the remaining (1-R) ​​times the data of the third data sequence, and forming the fourth data sequence.

[0093] Alternatively, extracting R times the data can be done by multiplying the third data sequence with the fifth data sequence to obtain the multiplied data sequence, discarding the zero data obtained by multiplying the zero data in the fifth data sequence to form the fourth data sequence, where the number of non-zero data in the fifth data sequence is R times the number of data in the third data sequence, and the number of zero data is (1-R) ​​times the number of data in the third data sequence.

[0094] Alternatively, extracting R times the data can be done by using a filtering function to filter the third data sequence to form the fourth data sequence. The width (non-zero width) of the filtering function in the frequency domain is R times the width of the third data sequence in the frequency domain.

[0095] Example 8

[0096] This embodiment is an example of the average PSD shape of the third data sequence and the value of R in the data truncation of R times.

[0097] In this embodiment, a fourth data sequence is formed from a first data sequence. The first data sequence is modulated to form a second data sequence, in which the magnitude of the data is 1 and the phase difference between adjacent data is ±π / 4. Then, a Fourier transform and a semi-circular shift are performed on the second data sequence to form a third data sequence. Then, R times the data is truncated to form a fourth data sequence, which is then transmitted.

[0098] The power spectral density of the third data sequence is shown in Figure 6. The horizontal axis represents the relative frequency (Hz), and the vertical axis represents the power spectral density (PSD) (dB). The length of the horizontal axis is equal to the data bandwidth of the third data sequence. In Figure 6, nine scales are evenly marked. The horizontal axis [0] represents the center frequency or the 0th subcarrier. The negative values ​​of the horizontal axis [-1 / 2, -3 / 8, -1 / 4, -1 / 8] represent negative frequencies, and the positive values ​​of the horizontal axis [1 / 8, 1 / 4, 3 / 8, 1 / 2] represent positive frequencies. The power spectral density of the third data sequence is the smallest at the position of the horizontal axis [-3 / 8, 3 / 8]. The length of the horizontal axis range [-3 / 8, 3 / 8] is exactly 3 / 4 times the length of the third data sequence.

[0099] The value of R in the fourth data sequence is 3 / 4. The fourth data sequence is formed by truncating R times the data, which means truncating the data sequence within the range of the horizontal coordinate [-3 / 8, 3 / 8] of the third data sequence.

[0100] The minimum value of R in the fourth data sequence formed by truncating R times the data is 1 / 2. This means that the fourth data sequence is formed by truncating R times the data from the third data sequence within the x-coordinate range of [-1 / 4, 1 / 4]. The maximum value of R in the fourth data sequence formed by truncating R times the data is 17 / 20. This means that the fourth data sequence is formed by truncating R times the data from the third data sequence within the x-coordinate range of [-17 / 40, 17 / 40].

[0101] This application also provides a data modulation device. Figure 7 is a schematic diagram of the structure of a data modulation device according to an embodiment. As shown in Figure 7, the data modulation device includes: a modulation module 210, configured to modulate a first data sequence to form a second data sequence; a transformation module 220, configured to perform a Fourier transform on the second data sequence to form a third data sequence; and a truncation module 230, configured to truncate R times the data from the third data sequence to form a fourth data sequence, where R is less than 1.

[0102] In one embodiment, R takes one of the following values: 3 / 4, 3 / 5, [1 / 2, 3 / 4], [1 / 2, 17 / 20].

[0103] In one embodiment, the first data sequence is a bit sequence consisting of zero data and data with a value of 1.

[0104] In one embodiment, the first data sequence is formed by transforming a sequence of data with a value of 1 and data with a value of -1; the transformation satisfies the following: data with a value of 1 is transformed into zero data, and data with a value of -1 is transformed into 1.

[0105] In one embodiment, modulating the first data sequence to form the second data sequence includes: when k is even, k = 2i. When k is odd, k = 2i + 1. or,

[0106] Where i = 0, 1, 2, ..., I-1, I is the number of elements in the first data sequence, or the number of bits in a data block; k = 0, 1, 2, ..., 2I-1, 2I is the number of elements in the second data sequence; b(i) is an element of the first data sequence; d(k) is an element of the second data sequence; a equals 1 or -1, and θ is a preset constant or 0.

[0107] In one embodiment, modulating a first data sequence to form a second data sequence includes: or Where i = 0, 1, 2, ..., I-1, I is twice the number of elements in the first data sequence, or twice the number of bits in a data block, and I is also the number of elements in the second data sequence; and d(i) is an element of the first data sequence; d(i) is an element of the second data sequence; θ is a preset constant or 0.

[0108] In one embodiment, c is π / 4, π, or 5π / 4; s is -π / 4, π, or 3π / 4.

[0109] In one embodiment, extracting R times the data from the third data sequence includes: extracting R times the data from the third data sequence and discarding the remaining data in the third data sequence other than the extracted R times the data.

[0110] In one embodiment, extracting R times the amount of data from the third data sequence includes: performing a dot product between the third data sequence and the fifth data sequence to obtain a dot product data sequence; discarding zero data obtained by multiplying zero data in the dot product data sequence from the zero data in the fifth data sequence; the number of non-zero data in the fifth data sequence is R times the number of data in the third data sequence, and the number of zero data in the fifth data sequence is 1-R times the number of data in the third data sequence.

[0111] In one embodiment, in the fifth data sequence, the number of data with a value of 1 is R times the number of data in the third data sequence, and the number of zero data is (1-R) ​​times the number of data in the third data sequence.

[0112] In one embodiment, extracting R times the amount of data from the third data sequence includes: filtering the frequency domain third data sequence using a filtering function, wherein the width of the filtering function in the frequency domain is R times the width of the frequency domain of the third data sequence.

[0113] In one embodiment, the filtering function is a root-raised cosine function or a raised cosine function, with a roll-off factor of [0, 0.7].

[0114] In one embodiment, the filtering function is a rectangular function with a roll-off factor of 0.

[0115] In one embodiment, the fifth data sequence is the discrete values ​​of the filtering function.

[0116] In one embodiment, extracting R times the data from the third data sequence to form a fourth data sequence includes: cyclically shifting the third data sequence, and extracting R times the continuous data from the cyclically shifted data sequence to form the fourth data sequence.

[0117] In one embodiment, extracting R times the data from the third data sequence to form a fourth data sequence includes: directly extracting R times the continuous data from the third data sequence to form the fourth data sequence.

[0118] In one embodiment, extracting R times the data from the third data sequence to form a fourth data sequence includes: extracting R times the data from both ends of the third data sequence. Alternatively, extracting R times the data from the middle of the third data sequence.

[0119] In one embodiment, the device further includes: a multiple determination module, configured to determine based on... The frequency position of R, where R is zero or near zero in the power spectral density, is determined by f, which is equal to 1 or -1; where p is a constant and f is the power factor. The frequency points at or near the zero value in the power spectral density are used as boundaries. The data portion of the third data sequence corresponding to the intermediate frequency domain interval within the two boundaries is extracted to form the fourth data sequence.

[0120] In one embodiment, p takes the value 1, or

[0121] In one embodiment, the first data sequence is a part of a sixth data sequence, the length of which is greater than the length of the first data sequence.

[0122] In one embodiment, the device further includes: a first inverse transform module configured to perform an oversampled inverse Fourier transform on the fourth data sequence to form time-domain data; and a transmission module configured to transmit the time-domain data.

[0123] In one embodiment, the device further includes: a filtering module configured to perform a filtering operation on the fourth data sequence; a second inverse transform module configured to perform an oversampled inverse Fourier transform on the filtered data sequence to form time-domain data; and a transmission module configured to transmit the time-domain data.

[0124] In one embodiment, the apparatus further includes multiplying the fourth data sequence by a power factor before performing the oversampled inverse Fourier transform.

[0125] The data modulation device proposed in this embodiment belongs to the same concept as the data modulation method proposed in the above embodiments. Technical details not described in detail in this embodiment can be found in any of the above embodiments. Furthermore, this embodiment has the same effect as performing the data modulation method.

[0126] This application also provides a communication node. Figure 8 is a schematic diagram of the hardware structure of a communication node provided in an embodiment. As shown in Figure 8, the communication node provided in this application includes a processor 310 and a memory 320. The processor 310 in the communication node can be one or more, and Figure 8 takes one processor 310 as an example. The memory 320 is configured to store one or more programs. The one or more programs are executed by the one or more processors 310, so that the one or more processors 310 implement the data modulation method as described in the embodiment of this application.

[0127] The communication node also includes: a communication device 330, an input device 340, and an output device 350.

[0128] The processor 310, memory 320, communication device 330, input device 340 and output device 350 in the communication node can be connected by a bus or other means. Figure 8 shows an example of connection by bus.

[0129] Input device 340 can be used to receive input digital or character information, and to generate key signal inputs related to user settings and function control of the communication node. Output device 350 may include display devices such as a display screen.

[0130] The communication device 330 may include a receiver and a transmitter. The communication device 330 is configured to perform information transmission and reception communication under the control of the processor 310.

[0131] The memory 320, as a computer-readable storage medium, can be configured to store software programs, computer-executable programs, and modules, such as program instructions / modules corresponding to the data modulation method described in the embodiments of this application (e.g., modulation module 210, conversion module 220, and interception module 230 in a data modulation apparatus). The memory 320 may include a program storage area and a data storage area, wherein the program storage area may store an operating system and an application program required for at least one function; the data storage area may store data created based on the use of the communication node, etc. Furthermore, the memory 320 may include high-speed random access memory and may also include non-volatile memory, such as at least one disk storage device, flash memory device, or other non-volatile solid-state storage device. In some instances, the memory 320 may further include memory remotely located relative to the processor 310, and these remote memories can be connected to the communication node via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0132] This application also provides a storage medium storing a computer program, which, when executed by a processor, implements any of the data modulation methods described in this application. The data modulation method includes: modulating a first data sequence to form a second data sequence; performing a Fourier transform on the second data sequence to form a third data sequence; and extracting R times the amount of data from the third data sequence to form a fourth data sequence, where R is less than 1.

[0133] This application also provides a computer program product, including a computer program / instructions, which, when executed by a processor, implement any of the data modulation methods described in this application. The data modulation method includes: modulating a first data sequence to form a second data sequence; performing a Fourier transform on the second data sequence to form a third data sequence; and extracting R times the amount of data from the third data sequence to form a fourth data sequence, where R is less than 1.

[0134] The computer storage medium in this application embodiment can be any combination of one or more computer-readable media. The computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium. For example, a computer-readable storage medium can be, but is not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of computer-readable storage media (a non-exhaustive list) include: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), flash memory, optical fiber, portable CD-ROM, optical storage device, magnetic storage device, or any suitable combination thereof. The computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0135] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. Computer-readable signal media may also be any computer-readable medium other than computer-readable storage media, which can send, propagate, or transmit programs for use by or in connection with an instruction execution system, apparatus, or device.

[0136] Program code contained on a computer-readable medium may be transmitted using any suitable medium, including but not limited to: wireless, wire, optical fiber, radio frequency (RF), etc., or any suitable combination thereof.

[0137] Computer program code for performing the operations of this application can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, as well as conventional procedural programming languages ​​such as "C" or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0138] This application also provides a computer program product, including a computer program / instructions, which, when executed by a processor, implement the data modulation method as described in any of the above embodiments.

[0139] The above description is merely an exemplary embodiment of this application and is not intended to limit the scope of protection of this application.

[0140] Those skilled in the art will understand that the term user terminal encompasses any suitable type of wireless user equipment, such as mobile phones, portable data processing portable web browsers, or vehicle-mounted mobile stations.

[0141] Generally, the various embodiments of this application can be implemented in hardware or dedicated circuitry, software, logic, or any combination thereof. For example, some aspects can be implemented in hardware, while others can be implemented in firmware or software that can be executed by a controller, microprocessor, or other computing device, although this application is not limited thereto.

[0142] Embodiments of this application can be implemented by executing computer program instructions through the data processor of a mobile device, for example, in a processor entity, or through hardware, or through a combination of software and hardware. The computer program instructions can be assembly instructions, Instruction Set Architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, status setting data, or source code or object code written in any combination of one or more programming languages.

[0143] Any block diagram of logical flow in the accompanying drawings of this application may represent program operations, or may represent interconnected logic circuits, modules, and functions, or may represent a combination of program operations and logic circuits, modules, and functions. Computer programs may be stored in memory. Memory may be of any type suitable to the local technical environment and may be implemented using any suitable data storage technology, such as, but not limited to, read-only memory (ROM), random access memory (RAM), optical storage devices and systems (Digital Video Disc (DVD) or Compact Disk (CD), etc.). Computer-readable media may include non-transitory storage media. Data processors may be of any type suitable to the local technical environment, such as, but not limited to, general-purpose computers, special-purpose computers, microprocessors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), and processors based on multi-core processor architectures.

Claims

1. A data modulation method, comprising: The first data sequence is modulated to form the second data sequence; Perform a Fourier transform on the second data sequence to form a third data sequence; R times the data is extracted from the third data sequence to form a fourth data sequence, where R is less than 1.

2. The method according to claim 1, wherein, R can take one of the following values: 3 / 4,3 / 5,[1 / 2,3 / 4],[1 / 2,17 / 20]。 3. The method according to claim 1, wherein, The first data sequence is a bit sequence consisting of zero data and data with a value of 1.

4. The method according to claim 1, wherein, The first data sequence is formed by transforming a sequence of data with a value of 1 and data with a value of -1. The transformation satisfies the following: data with a value of 1 is transformed into zero data, and data with a value of -1 is transformed into 1.

5. The method according to claim 1, wherein, Modulating the first data sequence to form the second data sequence includes: When k is even, k = 2i. When k is odd, k = 2i + 1. or, Where i = 0, 1, 2, ..., I-1, I is the number of elements contained in the first data sequence, or the number of bits contained in a data block; k = 0, 1, 2, ..., 2I-1, where 2I is the number of elements contained in the second data sequence; b(i) is an element of the first data sequence; d(k) is an element of the second data sequence; a equals 1 or -1, and θ is a preset constant or 0.

6. The method according to claim 1, wherein, Modulating the first data sequence to form the second data sequence includes: or Where i = 0, 1, 2, ..., I-1, I is twice the number of elements in the first data sequence, or twice the number of bits in a data block, and I is also the number of elements in the second data sequence; and d(i) represents the element of the first data sequence; d(i) represents the element of the second data sequence. θ is a preset constant or 0.

7. The method according to claim 6, wherein, c is π / 4, π or 5π / 4; s is -π / 4, π or 3π / 4.

8. The method according to claim 1, wherein, Extracting R times the amount of data from the third data sequence includes: Extract R times the amount of data from the third data sequence, and discard the remaining data in the third data sequence other than the extracted R times the amount of data.

9. The method according to claim 1, wherein, Extracting R times the amount of data from the third data sequence includes: The third data sequence and the fifth data sequence are multiplied by a dot product to obtain the multiplied data sequence. Discard the zero data obtained by multiplying the zero data in the fifth data sequence into the dot product data sequence. The number of non-zero data in the fifth data sequence is R times the number of data in the third data sequence, and the number of zero data in the fifth data sequence is 1-R times the number of data in the third data sequence.

10. The method according to claim 9, wherein, In the fifth data sequence, the number of data with a value of 1 is R times the number of data in the third data sequence, and the number of zero data is (1-R) ​​times the number of data in the third data sequence.

11. The method according to claim 1, wherein, Extracting R times the amount of data from the third data sequence includes: The third data sequence in the frequency domain is filtered using a filtering function whose width in the frequency domain is R times the width of the third data sequence.

12. The method according to claim 11, wherein, The filtering function is a root-raised cosine function or a raised cosine function, with a roll-off factor of [0, 0.7].

13. The method according to claim 11, wherein, The filtering function is a rectangular function with a roll-off factor of 0.

14. The method according to claim 9, wherein, The fifth data sequence is the discrete value of the filter function.

15. The method according to claim 1, wherein, The fourth data sequence is formed by extracting R times the amount of data from the third data sequence, including: The third data sequence is cyclically shifted, and R times the continuous data is extracted from the cyclically shifted data sequence to form the fourth data sequence.

16. The method according to claim 1, wherein, The fourth data sequence is formed by extracting R times the amount of data from the third data sequence, including: The fourth data sequence is formed by directly extracting R times the continuous data from the third data sequence.

17. The method according to claim 1, wherein, The fourth data sequence is formed by extracting R times the amount of data from the third data sequence, including: The fourth data sequence is formed by extracting R times the data from both ends of the third data sequence, or by extracting R times the data from the middle of the third data sequence.

18. The method according to claim 1, further comprising: according to The position of the frequency point where the power spectral density is zero or near zero determines R, where f is equal to 1 or -1; Where p is a constant and is the power factor.

19. The method according to claim 18, wherein, p takes the value 1, or 20. The method according to claim 1, wherein, The first data sequence is a part of the sixth data sequence, and the length of the sixth data sequence is greater than the length of the first data sequence.

21. The method according to claim 1, further comprising: The fourth data sequence is subjected to an oversampled inverse Fourier transform to form time-domain data; Transmit the time-domain data.

22. The method according to claim 1, further comprising: The fourth data sequence is then filtered. The filtered data sequence is subjected to an oversampled inverse Fourier transform to form time-domain data; Transmit the time-domain data.

23. The method according to claim 21 or 22, further comprising, before performing the oversampled inverse Fourier transform: Multiply the fourth data sequence by a power factor.

24. A communication node, comprising: Memory, and at least one processor; The memory is configured to store at least one program; When the at least one program is executed by the at least one processor, the at least one processor implements the data modulation method as described in any one of claims 1-23.

25. A computer-readable storage medium storing a computer program, wherein, When the program is executed by the processor, it implements the data modulation method as described in any one of claims 1-23.

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