Data modulation method, communication node and storage medium

Abstract

The invention provides a data modulation method, a communication node and a storage medium. The method comprises the steps that one piece of data is inserted between every two adjacent pieces of data in a first data sequence to form a second data sequence, the first data sequence comprises two elements which are opposite in number, and the included angle between each piece of inserted data and the adjacent data is 0 or pi / 2, or the included angle between each piece of inserted data and the adjacent data is pi or pi / 2; 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, R being less than 1.

Description

Technical Field

[0001] This application relates to the field of wireless communication technology, such as a data modulation method, a communication node, and a storage medium. 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 existing communication systems, the PAPR (Power Amount Reduction Ratio) of multi-carrier Orthogonal Frequency Division Multiplexing (OFDM) signals is very high. 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, increasing energy consumption and heat loss, and reducing its efficiency. Although the PAPR of single-carrier OFDM (DFT-s-OFDM) signals based on Discrete Fourier Transform is relatively low, it is still difficult to meet the low PAPR requirements of future communications. Therefore, a modulation method that can further reduce PAPR is needed. 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:

[0006] One data point is inserted between every two adjacent data points in the first data sequence to form the second data sequence. The first data sequence contains two elements that are opposites of each other. The angle between each inserted data point and its adjacent data points is 0 or π / 2, or the angle between each inserted data point and its adjacent data points is π or π / 2.

[0007] Perform a Fourier transform on the second data sequence to form a third data sequence;

[0008] R times the data is extracted from the third data sequence to form a fourth data sequence, where R is less than 1.

[0009] 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.

[0010] 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

[0011] Figure 1 A flowchart of a data modulation method provided in one embodiment;

[0012] Figure 2 A schematic diagram of the statistical average power spectral density of a third data sequence provided in one embodiment;

[0013] Figure 3 A schematic diagram of the statistical average power spectral density of another third data sequence provided in one embodiment;

[0014] Figure 4 A schematic diagram of the statistical average power spectral density of another third data sequence provided in one embodiment;

[0015] Figure 5 A schematic diagram of the statistical average power spectral density of a third data sequence obtained by Fourier transform and semi-circular shift, provided as an embodiment;

[0016] Figure 6 A schematic diagram of the statistical average power spectral density of a third data sequence obtained by Fourier transform and semi-cyclic shift as provided in one embodiment;

[0017] Figure 7 A schematic diagram of the statistical average power spectral density of another third data sequence provided in one embodiment;

[0018] Figure 8 A schematic diagram of the statistical average power spectral density of another third data sequence provided in one embodiment;

[0019] Figure 9 A schematic diagram of the statistical average power spectral density of another third data sequence provided in one embodiment;

[0020] Figure 10 A schematic diagram of the statistical average power spectral density of another third data sequence provided in one embodiment;

[0021] Figure 11 A schematic diagram of the statistical average power spectral density of another third data sequence provided in one embodiment;

[0022] Figure 12 A schematic diagram of the statistical average power spectral density of another third data sequence provided in one embodiment;

[0023] Figure 13A schematic diagram of the statistical average power spectral density of a third data sequence repeated once, as provided in one embodiment;

[0024] Figure 14 A schematic diagram of the statistical average power spectral density of another third data sequence repeated once, as provided in one embodiment;

[0025] Figure 15 A schematic diagram illustrating the modulus values ​​of a third data sequence and a fifth data sequence as provided in one embodiment;

[0026] Figure 16 A schematic diagram of a data modulation process provided in one embodiment;

[0027] Figure 17 A schematic diagram of the structure of a data modulation apparatus provided in one embodiment;

[0028] Figure 18 This is a schematic diagram of the hardware structure of a communication node provided in one embodiment. Detailed Implementation

[0029] The present application will now be described in conjunction with the accompanying drawings and embodiments. It is to be understood that the specific embodiments described herein are merely illustrative of the application and not intended to limit it. It should be noted that, unless otherwise specified, the embodiments and features described herein can be arbitrarily combined with each other. Furthermore, it should be noted that, for ease of description, the accompanying drawings show only the parts relevant to the present application, not the entire structure.

[0030] Figure 1 This is a flowchart illustrating a data modulation method as provided in one embodiment. This method can be applied to a data modulation device or a data transmission device. Figure 1 As shown, the method provided in this embodiment includes the following steps:

[0031] Step 110: Insert one data point between every two adjacent data points in the first data sequence to form a second data sequence. The first data sequence contains two elements that are opposites of each other. The angle between each inserted data point and its adjacent data point is 0 or π / 2, or the angle between each inserted data point and its adjacent data point is π or π / 2.

[0032] Step 120: Perform a Fourier transform on the second data sequence to form a third data sequence.

[0033] Step 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.

[0034] 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, or performing a Fourier transform and cyclic shift on the second data sequence to form a third data sequence, and then extracting R times the amount of data from the third data sequence. Based on the average PSD plot of the third data sequence, it can be seen that by setting a reasonable multiple, the extraction can be performed with reference to the position of the minimum average PSD of the third data sequence (e.g., at 3 / 4 of the bandwidth) as the boundary, achieving lower out-of-band leakage, thereby reducing the peak-to-average power ratio and minimizing performance loss.

[0035] In one embodiment, R takes one of the following values: 3 / 4, 3 / 5, [1 / 2, 3 / 4], [1 / 2, 17 / 20].

[0036] In this embodiment, based on the average PSD plot of the third data sequence, the modulus of the third data sequence is at its minimum at 3 / 4 bandwidth. Truncation at this position will result in lower out-of-band leakage, lower peak-to-average power ratio, and less performance loss.

[0037] In one embodiment, the third data sequence includes a spectral period centered at zero frequency corresponding to the second data sequence;

[0038] A fourth data sequence is formed by extracting R times the amount of data from the third data sequence, including:

[0039] R times the frequency domain data is extracted from the edge of the frequency period to form the fourth data sequence.

[0040] In one embodiment, extracting R times the amount of data from the third data sequence to form a fourth data sequence includes:

[0041] R times the data is extracted from the third data sequence, and the remaining data in the third data sequence other than the extracted R times the data is discarded to form a fourth data sequence.

[0042] In one embodiment, extracting R times the amount of data from the third data sequence to form a fourth data sequence includes:

[0043] The third data sequence is multiplied by the fifth data sequence, and the zero data obtained by multiplying the zero data in the fifth data sequence is discarded to form the fourth data sequence.

[0044] 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.

[0045] In one embodiment, the number of data points with a value of 1 in the fifth data sequence is R times the number of data points in the third data sequence, and the number of data points with a value of zero is 1-R times the number of data points in the third data sequence.

[0046] In one embodiment, R times the data is extracted from the third data sequence to form a fourth data sequence, including:

[0047] The third data sequence is filtered using a filtering function to form the fourth data sequence;

[0048] The width of the filtering function in the frequency domain is R times the width of the third data sequence in the frequency domain.

[0049] 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].

[0050] In one embodiment, the filtering function is a rectangular function with a roll-off factor of 0.

[0051] In one embodiment, the fifth data sequence is the discrete values ​​of the filtering function.

[0052] In one embodiment, extracting R times the amount of data from the third data sequence to form a fourth data sequence includes:

[0053] R times the data is extracted from both ends of the third data sequence, and the remaining data in the middle part of the third data sequence except for the extracted data is discarded. Then, the data is cyclically shifted to form a fourth data sequence.

[0054] In one embodiment, extracting R times the amount of data from the third data sequence to form a fourth data sequence includes:

[0055] The third data sequence is cyclically shifted, and R times the data is extracted from the cyclically shifted data sequence to form the fourth data sequence.

[0056] In one embodiment, extracting R times the amount of data from the third data sequence to form a fourth data sequence includes:

[0057] A fourth data sequence is formed by extracting R times the continuous data from the edge of the third data sequence; where R takes the value (0, 3 / 4).

[0058] In one embodiment, extracting R times the amount of data from the third data sequence to form a fourth data sequence includes:

[0059] A total of R times the data is extracted from both ends of the third data sequence; where R takes the value (3 / 4, 17 / 20).

[0060] In one embodiment, extracting R times the amount of data from the third data sequence to form a fourth data sequence includes:

[0061] The third data sequence is repeated once to obtain the repeated data sequence;

[0062] R times the continuous frequency domain data are extracted from the repeated data sequence to form the fourth data sequence.

[0063] In one embodiment, the method further includes:

[0064] R is determined based on the frequency position of zero or near zero in the power spectral density of p*[a*(1+1j) / 2,1,a*(1-1j) / 2] or p*[a*(1-1j) / 2,1,a*(1+1j) / 2]; where p is a constant, the power factor, and a is equal to 1 or -1. Using the frequency position of zero or near zero in the power spectral density of p*[a*(1+1j) / 2,1,a*(1-1j) / 2] or p*[a*(1-1j) / 2,1,a*(1+1j) / 2] 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.

[0065] In one embodiment, p is set to 1.

[0066] In one embodiment, after inserting one data point between every two adjacent data points in the first data sequence, the method further includes:

[0067] Insert one data point before or after the first data sequence to form a second data sequence.

[0068] 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.

[0069] In one embodiment, for every two adjacent data, the power of the inserted data is equal to the power of the adjacent data.

[0070] In one embodiment, for every two adjacent data,

[0071] When the inserted data is the same as the adjacent data, the angle between the inserted data and the adjacent data is 0.

[0072] When the inserted data is different from the adjacent data, the angle between the inserted data and the adjacent data is π / 2;

[0073] or,

[0074] When the inserted data is the same as the adjacent data, the angle between the inserted data and the adjacent data is π.

[0075] When the inserted data is different from the adjacent data, the angle between the inserted data and the adjacent data is π / 2.

[0076] In one embodiment, the first data sequence is a BPSK data sequence.

[0077] In one embodiment, the method further includes:

[0078] The fourth data sequence is subjected to an oversampled inverse Fourier transform to form time-domain data;

[0079] Transmit the time-domain data.

[0080] In one embodiment, the method further includes:

[0081] The fourth data sequence is then filtered.

[0082] The filtered data sequence is then subjected to an oversampled inverse Fourier transform to form time-domain data;

[0083] Transmit the time-domain data.

[0084] In one embodiment, the method further includes, prior to performing the oversampled inverse Fourier transform:

[0085] Multiply the fourth data sequence by a power factor.

[0086] The data modulation method of this application is illustrated by some embodiments below.

[0087] Example 1

[0088] This embodiment describes an example of forming a second data sequence from a first data sequence, and forming a third data sequence from the second data sequence.

[0089] In this embodiment, a second data sequence is formed from a first data sequence. One data element is inserted between each adjacent data element in the first data sequence to form the second data sequence. The first data sequence contains two elements that are opposites of each other, and the angle between the inserted data element and its adjacent data element is 0 or π / 2. Then, a Fourier transform and cyclic shift are performed on the second data sequence to form a third data sequence.

[0090] Assume the first data sequence is a BPSK data sequence, including two elements {+1, -1}. When the adjacent data is {1, 1}, the inserted data is 1; when the adjacent data is {-1, -1}, the inserted data is -1; when the adjacent data is {1, -1}, the inserted data is 1j; when the adjacent data is {-1, 1}, the inserted data is -1j. Alternatively, suppose the first data sequence is a BPSK data sequence, including two elements {(1+1j) / √2, (-1-1j) / √2}. When the adjacent data is {(1+1j) / √2, (1+1j) / √2}, the inserted data is (1+1j) / √2; when the adjacent data is {(-1-1j) / √2, (-1-1j) / √2}, the inserted data is (-1-1j) / √2; when the adjacent data is {(1+1j) / √2, (-1-1j) / √2}, the inserted data is (-1+1j) / √2; when the adjacent data is {(-1-1j) / √2, (1+1j) / √2}, the inserted data is (1-1j) / √2. Alternatively, suppose the first data sequence is a BPSK data sequence, including two elements {(-1+1j) / √2, (1-1j) / √2}. When the adjacent data is {(-1+1j) / √2, (-1+1j) / √2}, the inserted data is (-1+1j) / √2; when the adjacent data is {(1-1j) / √2, (1-1j) / √2}, the inserted data is (1-1j) / √2; when the adjacent data is {(-1+1j) / √2, (1-1j) / √2}, the inserted data is (-1-1j) / √2; when the adjacent data is {(1-1j) / √2, (-1+1j) / √2}, the inserted data is (1+1j) / √2.

[0091] In this case, a second data sequence is formed from the first data sequence, and then a Fourier transform and semi-circular shift are performed on the second data sequence to form a third data sequence. The statistical average power spectral density of the third data sequence is as follows: Figure 2 As shown. Figure 2 The horizontal axis represents the relative frequency (Hz), arranged in the order of [negative frequency, 0, positive frequency], while the vertical axis represents the statistical average power spectral density (dB).

[0092] Example 2

[0093] This embodiment describes an example of forming a second data sequence from a first data sequence, and then forming a third data sequence from the second data sequence.

[0094] In this embodiment, a second data sequence is formed from a first data sequence. One data element is inserted between each adjacent data element in the first data sequence to form the second data sequence. The first data sequence contains two elements that are opposites of each other, and the angle between the inserted data element and its adjacent data element is π or π / 2. Then, a Fourier transform is performed on the second data sequence to form a third data sequence.

[0095] Suppose the first data sequence is a BPSK data sequence, including two elements {+1, -1}. When the adjacent data is {1, 1}, the inserted data is -1; when the adjacent data is {-1, -1}, the inserted data is 1; when the adjacent data is {1, -1}, the inserted data is -1j; when the adjacent data is {-1, 1}, the inserted data is 1j. Alternatively, suppose the first data sequence is a BPSK data sequence, including two elements {(1+1j) / √2, (-1-1j) / √2}. When the adjacent data is {(1+1j) / √2, (1+1j) / √2}, the inserted data is (-1-1j) / √2; when the adjacent data is {(-1-1j) / √2, (-1-1j) / √2}, the inserted data is (1+1j) / √2; when the adjacent data is {(1+1j) / √2, (-1-1j) / √2}, the inserted data is (1-1j) / √2; when the adjacent data is {(-1-1j) / √2, (1+1j) / √2}, the inserted data is (-1+1j) / √2. Alternatively, suppose the first data sequence is a BPSK data sequence, including two elements {(-1+1j) / √2, (1-1j) / √2}. When the adjacent data is {(-1+1j) / √2, (-1+1j) / √2}, the inserted data is (1-1j) / √2; when the adjacent data is {(1-1j) / √2, (1-1j) / √2}, the inserted data is (-1+1j) / √2; when the adjacent data is {(-1+1j) / √2, (1-1j) / √2}, the inserted data is (1+1j) / √2; when the adjacent data is {(1-1j) / √2, (-1+1j) / √2}, the inserted data is (-1-1j) / √2.

[0096] In this case, a second data sequence is formed from the first data sequence, and then a Fourier transform is performed on the second data sequence to form a third data sequence. The statistical average power spectral density of the third data sequence is as follows: Figure 3 As shown. Figure 3 The horizontal axis represents the relative frequency (Hz), arranged in the order of [0:1], and the vertical axis represents the statistical average power spectral density (dB).

[0097] Example 3

[0098] This embodiment describes an example of forming a second data sequence from a first data sequence, and then forming a third data sequence from the second data sequence.

[0099] In this embodiment, a second data sequence is formed from a first data sequence. One data element is inserted between each adjacent data element in the first data sequence to form the second data sequence. The first data sequence contains two elements that are opposites of each other, and the angle between the inserted data element and its adjacent data element is 0° or π / 2. Then, a Fourier transform is performed on the second data sequence to form a third data sequence.

[0100] Assume the first data sequence is a BPSK data sequence, including two elements {+1, -1}. When the adjacent data is {1,1}, the inserted data is 1; when the adjacent data is {-1,-1}, the inserted data is -1; when the adjacent data is {1,-1}, the inserted data is -1j; when the adjacent data is {-1,1}, the inserted data is 1j. Alternatively, suppose the first data sequence is a BPSK data sequence, including two elements {(1+1j) / √2, (-1-1j) / √2}. When the adjacent data is {(1+1j) / √2, (1+1j) / √2}, the inserted data is (1+1j) / √2; when the adjacent data is {(-1-1j) / √2, (-1-1j) / √2}, the inserted data is (-1-1j) / √2; when the adjacent data is {(1+1j) / √2, (-1-1j) / √2}, the inserted data is (1-1j) / √2; when the adjacent data is {(-1-1j) / √2, (1+1j) / √2}, the inserted data is (-1+1j) / √2. Alternatively, suppose the first data sequence is a BPSK data sequence, including two elements {(-1+1j) / √2, (1-1j) / √2}. When the adjacent data is {(-1+1j) / √2, (-1+1j) / √2}, the inserted data is (-1+1j) / √2; when the adjacent data is {(1-1j) / √2, (1-1j) / √2}, the inserted data is (1-1j) / √2; when the adjacent data is {(-1+1j) / √2, (1-1j) / √2}, the inserted data is (1+1j) / √2; when the adjacent data is {(1-1j) / √2, (-1+1j) / √2}, the inserted data is (-1-1j) / √2.

[0101] At this point, a second data sequence is formed from the first data sequence. Then, a Fourier transform and a semi-circular shift are performed on the second data sequence to form a third data sequence. The average power spectral density of the third data sequence is as follows: Figure 4 As shown, Figure 4 The horizontal axis represents the relative frequency (Hz), arranged in the order of [negative frequency, 0, positive frequency], and the vertical axis represents the power spectral density (dB).

[0102] Example 4

[0103] This embodiment describes an example of determining the position of R based on the zero value or a frequency point near the zero value in the power spectral density of [(1+1j) / 2,1,(1-1j) / 2] or [(1-1j) / 2,1,(1+1j) / 2].

[0104] In this embodiment, the power spectral density of the sequence [1,(1-1j) / 2,0...0,(1+1j) / 2] is obtained by performing a Fourier transform and a semi-cyclic shift, as shown below. Figure 5 As shown, the power spectral density is zero at the horizontal coordinates [-1 / 2] and [1 / 4]. 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.

[0105] Alternatively, the power spectral density of the sequence [1,(1+1j) / 2,0...0,(1-1j) / 2] can be obtained by performing a Fourier transform and a semi-cyclic shift, such as... Figure 6 As shown, the power spectral density is zero at the horizontal coordinates [-1 / 4] and [1 / 2]. 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.

[0106] R can take the value 3 / 4, 3 / 5, or [1 / 2, 17 / 20].

[0107] Using the zero value or the frequency point near the zero value in the power spectral density of [(1+1j) / 2,1,(1-1j) / 2] or [(1-1j) / 2,1,(1+1j) / 2] 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. The length of the sequence [1,(1-1j) / 2,0...0,(1+1j) / 2] or [1,(1+1j) / 2,0...0,(1-1j) / 2] is the same as the length of the third data sequence, and the power spectral density of the sequence is the same as 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 magnitude of the fourth data sequence. When R is 3 / 4, the magnitude of the fourth data sequence is minimized.

[0108] Example 5

[0109] This embodiment is an example of extracting R times the data from a third data sequence to form a fourth data sequence.

[0110] In this embodiment, the statistical average power spectral density of the third data sequence is as follows: Figure 7-9 As shown, Figure 7-9The horizontal axis represents relative frequency (Hz), and the vertical axis represents power spectral density (dB). The width of the horizontal axis is exactly the width of the spectrum of the third data sequence. R times the data is extracted from the third data sequence to form the fourth data sequence.

[0111] When R is 1 / 2, data in the range [-1 / 8, 3 / 8] is extracted from the third data sequence to form the fourth data sequence, such as... Figure 7 As shown;

[0112] When R takes the value 3 / 4, data in the range [-1 / 4, 1 / 2] is extracted from the third data sequence to form the fourth data sequence, such as... Figure 8 As shown;

[0113] When R is 17 / 20, data within the ranges [-6 / 20, 1 / 2] and [-1 / 2, -9 / 20] are extracted from the third data sequence to form the fourth data sequence, such as... Figure 9 As shown.

[0114] Example 6

[0115] This embodiment is an example of extracting R times the data from a third data sequence to form a fourth data sequence.

[0116] In this embodiment, the statistical average power spectral density of the third data sequence is as follows: Figure 10-12 As shown, Figure 10-12 The horizontal axis represents relative frequency (Hz), and the vertical axis represents power spectral density (dB). The width of the horizontal axis is exactly the width of the spectrum of the third data sequence. R times the data is extracted from the third data sequence to form the fourth data sequence.

[0117] When R takes the value 1 / 2, data in the range [-3 / 8, 1 / 8] is extracted from the third data sequence to form the fourth data sequence, such as... Figure 10 As shown;

[0118] When R takes the value 3 / 4, data in the range [-1 / 2, 1 / 4] is extracted from the third data sequence to form the fourth data sequence, such as... Figure 11 As shown;

[0119] When R is 17 / 20, data within the ranges [-1 / 2, 6 / 20] and [9 / 20, 1 / 2] are extracted from the third data sequence to form the fourth data sequence, such as... Figure 12 As shown.

[0120] Example 7

[0121] This embodiment is an example of extracting R times the data from a third data sequence to form a fourth data sequence.

[0122] In this embodiment, the statistical average power spectral density of the third data sequence is repeated once, as follows: Figure 13 As shown, Figure 13 The horizontal axis represents relative frequency (Hz), and the vertical axis represents power spectral density (dB). The width of the horizontal axis is exactly twice the spectrum of the third data sequence. R times the data is extracted from the third data sequence to form the fourth data sequence, as shown below. Figure 13 As shown:

[0123] When R takes the value of 1 / 2, data in the range [-1 / 8, 3 / 8] is extracted from the third data sequence to form the fourth data sequence;

[0124] When R takes the value 3 / 4, data in the range [-1 / 4, 1 / 2] is extracted from the third data sequence to form the fourth data sequence;

[0125] When R is 17 / 20, data in the range [-6 / 20, 11 / 20] is extracted from the third data sequence to form the fourth data sequence.

[0126] Example 8

[0127] This embodiment is an example of extracting R times the data from a third data sequence to form a fourth data sequence.

[0128] In this embodiment, the statistical average power spectral density of the third data sequence is repeated once, as follows: Figure 14 As shown, Figure 14 The horizontal axis represents relative frequency (Hz), and the vertical axis represents power spectral density (dB). The width of the horizontal axis is exactly twice the spectrum of the third data sequence. R times the data is extracted from the third data sequence to form the fourth data sequence, as shown below. Figure 14 As shown:

[0129] When R takes the value of 1 / 2, data in the range [-3 / 8, 1 / 8] is extracted from the third data sequence to form the fourth data sequence;

[0130] When R takes the value 3 / 4, data in the range [-1 / 2, 1 / 4] is extracted from the third data sequence to form the fourth data sequence;

[0131] When R is 17 / 20, data in the range [-11 / 20, 6 / 20] is extracted from the third data sequence to form the fourth data sequence.

[0132] The power spectral density of [a*(1+1j) / 2,1,a*(1-1j) / 2] or [a*(1-1j) / 2,1,a*(1+1j) / 2] is related to... Figure 13 or Figure 14The average power spectral density shape of the third data sequence is the same. R is determined based on the position of the zero value or the frequency point near the zero value in the power spectral density of [a*(1+1j) / 2,1,a*(1-1j) / 2] or [a*(1-1j) / 2,1,a*(1+1j) / 2]. The power spectral density plot of [a*(1+1j) / 2,1,a*(1-1j) / 2] or [a*(1-1j) / 2,1,a*(1+1j) / 2] contains a large peak and a small peak. The position of the truncated data in the third data sequence and the R value are determined based on the position of the large peak. Based on the zero value or the frequency point near the zero value in the power spectral density of [a*(1+1j) / 2,1,a*(1-1j) / 2] or [a*(1-1j) / 2,1,a*(1+1j) / 2], 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. When R<=3 / 4, it is the data portion of the third data sequence corresponding to the frequency domain interval of the large peak, forming the fourth data sequence; when R>3 / 4, it is the data portion of the third data sequence corresponding to the frequency domain interval of the large peak and the adjacent small peak, forming the fourth data sequence.

[0133] Example 9

[0134] This embodiment illustrates the process of performing a dot product between the third and fifth data sequences, and provides an example of the characteristics of the fifth data sequence.

[0135] In this embodiment, a fourth data sequence is formed from a first data sequence. The first data sequence is a BPSK data sequence. In the first data sequence, one new data point is inserted between every two adjacent BPSK data points to form a second data sequence. The angle between the new data point and the adjacent data points is 0° or π / 2°. Then, a Fourier transform and semi-circular shift are performed on the second data sequence to form a third data sequence. The third data sequence is then multiplied by the fifth data sequence to obtain a dot-multiplied data sequence. Zero data points obtained by multiplying zero data points from the fifth data sequence in the dot-multiplied data sequence are discarded, forming the fourth data sequence. Alternatively, the angle between the new data point and the adjacent data points is π or π / 2°. Then, a Fourier transform is performed on the second data sequence to form a third data sequence. The third data sequence is then multiplied by the fifth data sequence to obtain a dot-multiplied data sequence. Zero data points obtained by multiplying zero data points from the fifth data sequence in the dot-multiplied data sequence are discarded, forming the fourth data sequence.

[0136] In the fifth data sequence, the number of non-zero data 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.

[0137] In this embodiment, the modulus values ​​of the third data sequence and the fifth data sequence are as follows: Figure 15As shown, the modulus of the third data sequence is obtained by averaging multiple third data sequences, with R taking a value of 3 / 4. The fifth data sequence is... Figure 15 The sequence represented by the dashed line is the fifth data sequence, which is the discrete value of the root-raised cosine filter function with a roll-off factor of 1. The width of the non-zero value of the fifth data sequence is 3 / 4 of that of the third data sequence.

[0138] In other embodiments, the fifth data sequence may also be a root raised cosine function or a discrete value of a raised cosine function, wherein the roll-off factor is [0, 0.7], and when the roll-off factor is 0, it is a rectangular function.

[0139] Example 10

[0140] This embodiment is an example of forming a fourth data sequence from a first data sequence.

[0141] Figure 16 This is a schematic diagram illustrating a data modulation process according to one embodiment. Figure 16 As shown, in this embodiment, a fourth data sequence is formed from a first data sequence. In the first data sequence, one data element is inserted between each adjacent data element to form a second data sequence. The first data sequence contains two elements that are opposites of each other, and the angle between the inserted data element and the adjacent data element is 0 or π / 2. Then, a Fourier transform and 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. Finally, subcarrier mapping and oversampling inverse Fourier transform are performed on the fourth data sequence to form time-domain data, which is then transmitted. Here, R < 1.

[0142] Alternatively, the angle between the inserted data and the adjacent data is π or π / 2; then, a Fourier transform is performed on the second data sequence to form the third data sequence, and then R times the data is truncated to form the fourth data sequence. Finally, subcarrier mapping and oversampling inverse Fourier transform are performed on the fourth data sequence to form time-domain data, which is then transmitted. Here, R < 1.

[0143] One way to extract R times the data is to directly extract R times the data of the third data sequence, discard the remaining (1-R) ​​times the data of the third data sequence, and form the fourth data sequence.

[0144] 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.

[0145] 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.

[0146] Example 11

[0147] This embodiment is an example of forming a fourth data sequence from a first data sequence.

[0148] In this embodiment, a fourth data sequence is formed by a first data sequence. The first data sequence is a BPSK data sequence. One data point is inserted between every two adjacent BPSK data points in the first data sequence to form a second data sequence. The power of the data point is equal to the power of the adjacent data point. The angle between the data point and the adjacent data point is 0 or π / 2, or the angle between the data point and the adjacent data point is π or π / 2. 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 the fourth data sequence.

[0149] The second data sequence is subjected to a Fourier transform to form a third data sequence. The third data sequence may be sorted according to [0th subcarrier, positive frequency, negative frequency]. Therefore, the third data sequence is cyclically shifted and sorted according to [negative frequency, 0th subcarrier, positive frequency]. Then, R times the data is extracted to form a fourth data sequence.

[0150] Alternatively, a Fourier transform can be performed on the second data sequence to form a third data sequence. The third data sequence is sorted according to [0th subcarrier, positive frequency]. Therefore, the third data sequence can be directly truncated to form a fourth data sequence.

[0151] This application also provides a data modulation apparatus. Figure 17 This is a schematic diagram of a data modulation apparatus provided in one embodiment. Figure 17 As shown, the data modulation device includes:

[0152] The insertion module 210 is configured to insert one data between every two adjacent data in the first data sequence to form a second data sequence. The first data sequence contains two elements that are opposites of each other. The angle between each inserted data and the adjacent data is 0 or π / 2, or the angle between each inserted data and the adjacent data is π or π / 2.

[0153] Transformation module 220 is configured to perform a Fourier transform on the second data sequence to form a third data sequence;

[0154] The interception module 230 is configured to intercept R times the data from the third data sequence to form a fourth data sequence, where R is less than 1.

[0155] In one embodiment, R takes one of the following values: 3 / 4, 3 / 5, [1 / 2, 3 / 4], [1 / 2, 17 / 20].

[0156] In one embodiment, the third data sequence includes a spectral period centered at zero frequency corresponding to the second data sequence;

[0157] A fourth data sequence is formed by extracting R times the amount of data from the third data sequence, including:

[0158] R times the frequency domain data is extracted from the edge of the frequency period to form the fourth data sequence.

[0159] In one embodiment, extracting R times the amount of data from the third data sequence to form a fourth data sequence includes:

[0160] R times the data is extracted from the third data sequence, and the remaining data in the third data sequence other than the extracted R times the data is discarded to form a fourth data sequence.

[0161] In one embodiment, extracting R times the amount of data from the third data sequence to form a fourth data sequence includes:

[0162] The third data sequence is multiplied by the fifth data sequence, and the zero data obtained by multiplying the zero data in the fifth data sequence is discarded to form the fourth data sequence.

[0163] 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.

[0164] In one embodiment, the number of data points with a value of 1 in the fifth data sequence is R times the number of data points in the third data sequence, and the number of data points with a value of zero is 1-R times the number of data points in the third data sequence.

[0165] In one embodiment, R times the data is extracted from the third data sequence to form a fourth data sequence, including:

[0166] The third data sequence is filtered using a filtering function to form the fourth data sequence;

[0167] The width of the filtering function in the frequency domain is R times the width of the third data sequence in the frequency domain.

[0168] 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].

[0169] In one embodiment, the filtering function is a rectangular function with a roll-off factor of 0.

[0170] In one embodiment, the fifth data sequence is the discrete values ​​of the filtering function.

[0171] In one embodiment, extracting R times the amount of data from the third data sequence to form a fourth data sequence includes:

[0172] R times the data is extracted from both ends of the third data sequence, and the remaining data in the middle part of the third data sequence except for the extracted data is discarded. Then, the data is cyclically shifted to form a fourth data sequence.

[0173] In one embodiment, extracting R times the amount of data from the third data sequence to form a fourth data sequence includes:

[0174] The third data sequence is cyclically shifted, and R times the data is extracted from the cyclically shifted data sequence to form the fourth data sequence.

[0175] In one embodiment, extracting R times the amount of data from the third data sequence to form a fourth data sequence includes:

[0176] A fourth data sequence is formed by extracting R times the continuous data from the edge of the third data sequence; where R takes the value (0, 3 / 4).

[0177] In one embodiment, extracting R times the amount of data from the third data sequence to form a fourth data sequence includes:

[0178] A total of R times the data is extracted from both ends of the third data sequence; where R takes the value (3 / 4, 17 / 20).

[0179] In one embodiment, extracting R times the amount of data from the third data sequence to form a fourth data sequence includes:

[0180] The third data sequence is repeated once to obtain the repeated data sequence;

[0181] R times the continuous frequency domain data are extracted from the repeated data sequence to form the fourth data sequence.

[0182] In one embodiment, the device further includes:

[0183] The multiple determination module is set to determine R based on the position of the zero value or the frequency point near the zero value in the power spectral density of p*[a*(1+1j) / 2,1,a*(1-1j) / 2] or p*[a*(1-1j) / 2,1,a*(1+1j) / 2]; where p is the power factor and a is equal to 1 or -1.

[0184] In one embodiment, p is set to 1.

[0185] In one embodiment, after inserting one data point between every two adjacent data points in the first data sequence, the insertion module 210 is further configured to:

[0186] Insert one data point before or after the first data sequence to form a second data sequence.

[0187] 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.

[0188] In one embodiment, for every two adjacent data, the power of the inserted data is equal to the power of the adjacent data.

[0189] In one embodiment, for every two adjacent data,

[0190] When the inserted data is the same as the adjacent data, the angle between the inserted data and the adjacent data is 0.

[0191] When the inserted data is different from the adjacent data, the angle between the inserted data and the adjacent data is π / 2;

[0192] or,

[0193] When the inserted data is the same as the adjacent data, the angle between the inserted data and the adjacent data is π.

[0194] When the inserted data is different from the adjacent data, the angle between the inserted data and the adjacent data is π / 2.

[0195] In one embodiment, the first data sequence is a BPSK data sequence.

[0196] In one embodiment, the device further includes: an inverse transform module configured to perform an oversampled Fourier inverse transform on the fourth data sequence to form time-domain data;

[0197] The transmission module is configured to transmit the time-domain data.

[0198] In one embodiment, the device further includes:

[0199] The filtering module is configured to perform filtering operations on the fourth data sequence.

[0200] The inverse transform module is configured to perform an oversampled inverse Fourier transform on the filtered data sequence to form time-domain data;

[0201] The transmission module is configured to transmit the time-domain data.

[0202] In one embodiment, the device further includes, prior to performing the oversampled inverse Fourier transform:

[0203] The power control module is configured to multiply the fourth data sequence by a power factor.

[0204] The data modulation device proposed in this embodiment belongs to the same inventive 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 beneficial effects as performing the data modulation method.

[0205] This application also provides a communication node. Figure 18 This is a schematic diagram of the hardware structure of a communication node provided in one embodiment, such as... Figure 18 As shown, 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. Figure 18 Taking a 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, causing the one or more processors 310 to implement the data modulation method as described in the embodiments of this application.

[0206] The communication node also includes: a communication device 330, an input device 340, and an output device 350.

[0207] The processor 310, memory 320, communication device 330, input device 340, and output device 350 in the communication node can be connected via a bus or other means. Figure 18 Taking the example of a connection between China and Israel via a bus.

[0208] 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.

[0209] 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.

[0210] 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., the insertion module 210, transformation module 220, and interception module 230 in the data modulation apparatus). The memory 320 may include a program storage area and a data storage area, wherein the program storage area may store the operating system and at least one application program required for a 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.

[0211] 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: inserting one data element between every two adjacent data elements in a first data sequence to form a second data sequence, wherein the first data sequence contains two elements that are opposites of each other, and the angle between each inserted data element and its adjacent data element is 0 or π / 2, or the angle between each inserted data element and its adjacent data element is π or π / 2; 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.

[0212] 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: inserting one data element between every two adjacent data elements in a first data sequence to form a second data sequence, wherein the first data sequence contains two elements that are opposites of each other, and the angle between each inserted data element and its adjacent data element is 0 or π / 2, or the angle between each inserted data element and its adjacent data element is π or π / 2; 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.

[0213] 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.

[0214] 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.

[0215] 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.

[0216] 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).

[0217] 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.

[0218] The above description is merely an exemplary embodiment of this application and is not intended to limit the scope of protection of this application.

[0219] 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.

[0220] 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.

[0221] 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.

[0222] Any block diagram of logical flow in the accompanying drawings of this application may represent program steps, or may represent interconnected logic circuits, modules, and functions, or may represent a combination of program steps and logic circuits, modules, and functions. The computer program may be stored on 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. The data processor 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.

[0223] A detailed description of exemplary embodiments of this application has been provided above through exemplary and non-limiting examples. However, various modifications and adjustments to the above embodiments will be apparent to those skilled in the art when considered in conjunction with the accompanying drawings and claims, without departing from the scope of this application. Therefore, the proper scope of this application will be determined by the claims.

Claims

1. A data modulation method, characterized in that, include: One data point is inserted between every two adjacent data points in the first data sequence to form the second data sequence. The first data sequence contains two elements that are opposites of each other. The angle between each inserted data point and its adjacent data points is 0 or π / 2, or the angle between each inserted data point and its adjacent data points is π or π / 2. 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, characterized in that, 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, characterized in that, The third data sequence includes a spectral period centered at zero frequency corresponding to the second data sequence; A fourth data sequence is formed by extracting R times the amount of data from the third data sequence, including: R times the frequency domain data is extracted from the edge of the frequency period to form the fourth data sequence.

4. The method according to claim 1, characterized in that, A fourth data sequence is formed by extracting R times the amount of data from the third data sequence, including: R times the data is extracted from the third data sequence, and the remaining data in the third data sequence other than the extracted R times the data is discarded to form a fourth data sequence.

5. The method according to claim 1, characterized in that, A fourth data sequence is formed by extracting R times the amount of data from the third data sequence, including: The third data sequence is multiplied by the fifth data sequence, and the zero data obtained by multiplying the zero data in the fifth data sequence is discarded to form the fourth 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.

6. The method according to claim 5, characterized in that, The number of data points with a value of 1 in the fifth data sequence is R times the number of data points in the third data sequence, and the number of data points with a value of zero is 1-R times the number of data points in the third data sequence.

7. The method according to claim 1, characterized in that, A fourth data sequence is formed by extracting R times the amount of data from the third data sequence, including: The third data sequence is filtered using a filtering function to form the fourth data sequence; The width of the filtering function in the frequency domain is R times the width of the third data sequence in the frequency domain.

8. The method according to claim 7, characterized in that, The filtering function is a root-raised cosine function or a raised cosine function, with a roll-off factor of [0, 0.7].

9. The method according to claim 7, characterized in that, The filtering function is a rectangular function with a roll-off factor of 0.

10. The method according to claim 5, characterized in that, The fifth data sequence is the discrete value of the filter function.

11. The method according to claim 1, characterized in that, A fourth data sequence is formed by extracting R times the amount of data from the third data sequence, including: R times the data is extracted from both ends of the third data sequence, and the remaining data in the middle part of the third data sequence except for the extracted data is discarded. Then, the data is cyclically shifted to form a fourth data sequence.

12. The method according to claim 1, characterized in that, A 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 data is extracted from the cyclically shifted data sequence to form the fourth data sequence.

13. The method according to claim 1, characterized in that, A fourth data sequence is formed by extracting R times the amount of data from the third data sequence, including: A fourth data sequence is formed by extracting R times the continuous data from the edge of the third data sequence; where R takes the value (0, 3 / 4).

14. The method according to claim 1, characterized in that, A fourth data sequence is formed by extracting R times the amount of data from the third data sequence, including: A total of R times the data is extracted from both ends of the third data sequence; where R takes the value (3 / 4, 17 / 20).

15. The method according to claim 1, characterized in that, A fourth data sequence is formed by extracting R times the amount of data from the third data sequence, including: The third data sequence is repeated once to obtain the repeated data sequence; R times the continuous frequency domain data are extracted from the repeated data sequence to form the fourth data sequence.

16. The method according to claim 1, characterized in that, Also includes: R is determined based on the position of the zero value or the frequency point near the zero value in the power spectral density of p*[a*(1+1j) / 2,1,a*(1-1j) / 2] or p*[a*(1-1j) / 2,1,a*(1+1j) / 2]; where p is a constant, is the power factor, and a is equal to 1 or -1.

17. The method according to claim 16, characterized in that, p takes the value 1.

18. The method according to claim 1, characterized in that, After inserting one data point between every two adjacent data points in the first data sequence, it also includes: Insert one data point before or after the first data sequence to form a second data sequence.

19. The method according to claim 1, characterized in that, 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.

20. The method according to claim 1, characterized in that, For every two adjacent data points, the power of the inserted data is equal to the power of the adjacent data.

21. The method according to claim 1, characterized in that, For every two adjacent data points When the inserted data is the same as the adjacent data, the angle between the inserted data and the adjacent data is 0. When the inserted data is different from the adjacent data, the angle between the inserted data and the adjacent data is π / 2; or, When the inserted data is the same as the adjacent data, the angle between the inserted data and the adjacent data is π. When the inserted data is different from the adjacent data, the angle between the inserted data and the adjacent data is π / 2.

22. The method according to claim 1, characterized in that, The first data sequence is a BPSK data sequence.

23. The method according to claim 1, characterized in that, Also includes: The fourth data sequence is subjected to an oversampled inverse Fourier transform to form time-domain data; Transmit the time-domain data.

24. The method according to claim 1, characterized in that, Also includes: The fourth data sequence is then filtered. The filtered data sequence is then subjected to an oversampled inverse Fourier transform to form time-domain data; Transmit the time-domain data.

25. The method according to claim 23 or 24, characterized in that, Before performing the oversampled inverse Fourier transform, the following is also included: Multiply the fourth data sequence by a power factor.

26. A communication node, characterized in that, include: Memory, and one or more processors; The memory is configured to store one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the data modulation method as described in any one of claims 1-25.

27. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the program implements the data modulation method as described in any one of claims 1-25.

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