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 following steps: 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, 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] The first data sequence is modulated to form the second data sequence;

[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 a modulation process for a first data sequence provided in one embodiment;

[0013] Figure 3 A schematic diagram of another modulation process for a first data sequence provided in one embodiment;

[0014] Figure 4 A schematic diagram of the power spectral density of a third data sequence obtained by Fourier transform and semi-cyclic shift, as provided in one embodiment;

[0015] Figure 5 A schematic diagram of a data modulation process provided in one embodiment;

[0016] Figure 6 A schematic diagram of the power spectral density of a third data sequence provided in one embodiment;

[0017] Figure 7 A schematic diagram of the structure of a data modulation apparatus provided in one embodiment;

[0018] Figure 8 This is a schematic diagram of the hardware structure of a communication node provided in one embodiment. Detailed Implementation

[0019] 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.

[0020] 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:

[0021] Step 110: Modulate the first data sequence to form the second data sequence.

[0022] Step 120: Perform a Fourier transform on the second data sequence to form a third data sequence.

[0023] 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.

[0024] 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.

[0025] In one embodiment, R takes one of the following values: 3 / 4, 3 / 5, [1 / 2, 3 / 4], [1 / 2, 17 / 20].

[0026] In one embodiment, the first data sequence is a bit sequence consisting of zero data and data with a value of 1.

[0027] 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.

[0028] In one embodiment, modulating a first data sequence to form a second data sequence includes:

[0029] When k is even, k = 2i.

[0030]

[0031] When k is odd, k = 2i + 1.

[0032] Alternatively, d(k) = a(d(k-1)d((k+1)mod(2I)) 1 2.

[0033] 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;

[0034] k = 0, 1, 2, ..., 2I-1, where 2I is the number of elements in the second data sequence;

[0035] b(i) represents the element of the first data sequence; d(k) represents the element of the second data sequence;

[0036] a equals 1 or -1, and θ is a preset constant or 0.

[0037] In one embodiment, modulating a first data sequence to form a second data sequence includes:

[0038]

[0039] or

[0040]

[0041] 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;

[0042] and d(i) represents the elements of the first data sequence; d(i) represents the elements of the second data sequence.

[0043] θ is a preset constant or 0.

[0044] In one embodiment, c is π / 4, π, or 5π / 4; s is -π / 4, π, or 3π / 4.

[0045] In one embodiment, extracting R times the amount of data from the third data sequence includes:

[0046] 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.

[0047] In one embodiment, extracting R times the amount of data from the third data sequence includes:

[0048] The third data sequence and the fifth data sequence are multiplied by a dot product to obtain the multiplied data sequence.

[0049] Discard the zero data obtained by multiplying the zero data in the fifth data sequence into the dot product data sequence.

[0050] 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.

[0051] 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.

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

[0053] 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.

[0054] 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].

[0055] In one embodiment, the filtering function is a rectangular function with a roll-off factor of 0.

[0056] In one embodiment, the fifth data sequence is the discrete values ​​of the filtering function.

[0057] In one embodiment, extracting R times the amount of data from the third data sequence to form a fourth data sequence includes:

[0058] 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.

[0059] In one embodiment, extracting R times the amount of data from the third data sequence to form a fourth data sequence includes:

[0060] R times the continuous data are directly extracted from the third data sequence to form the fourth data sequence.

[0061] In one embodiment, extracting R times the amount of data from the third data sequence to form a fourth data sequence includes:

[0062] R times the data are extracted from both ends of the third data sequence. Alternatively, R times the data are extracted from the middle of the third data sequence.

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

[0064] 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.

[0065] In one embodiment, p takes the value 1, or

[0066] 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.

[0067] In one embodiment, the method further includes:

[0068] The fourth data sequence is subjected to an oversampled inverse Fourier transform to form time-domain data;

[0069] Transmit the time-domain data.

[0070] In one embodiment, the method further includes:

[0071] The fourth data sequence is then filtered.

[0072] The filtered data sequence is subjected to an oversampled inverse Fourier transform to form time-domain data;

[0073] Transmit the time-domain data.

[0074] In one embodiment, the method further includes, prior to performing the oversampled inverse Fourier transform:

[0075] Multiply the fourth data sequence by a power factor.

[0076] The data modulation method of this application is illustrated by some embodiments below.

[0077] Example 1

[0078] This embodiment is an example of modulating a first data sequence to form a second data sequence.

[0079] In this embodiment, the first data sequence is modulated to form the second data sequence.

[0080] Assume the first data sequence is a sequence of bits 0 and 1, containing elements b(i) and having a number of elements I. The first data sequence can be expressed by the formula: [b(i) = 0 or 1, i = 0, 1, 2, ..., I-1]; the second data sequence contains elements d[i] and has a number of elements 2I. The second data sequence can be expressed by the formula: [d(k), k = 0, 1, 2, ..., 2I-1];

[0081] The first data sequence is modulated to form the second data sequence. The modulation process is as follows:

[0082] When k is even, k = 2i

[0083]

[0084] When k is odd, k = 2i + 1

[0085]

[0086] or,

[0087] in,

[0088] 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.

[0089] When i = 0, 1, 2, ..., I-1, and θ equals 0, e j(π(i mod 2) / 2) =[1,1j,1,1j,1,1j,...,1,1j];

[0090] 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];

[0091] 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.

[0092] 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... 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).

[0093] 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).

[0094] Example 2

[0095] This embodiment is an example of modulating a first data sequence to form a second data sequence.

[0096] 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].

[0097] 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], and the modulation process is as follows: Figure 2 As shown:

[0098] When k = 0, 2, 4, 6, 8, 10 is even:

[0099]

[0100] When k = 1, 3, 5, 7, 9, 11 is odd:

[0101] Or d(1) = a(d(0)d(2)) 1 / 2 =-aj

[0102] Or d(3) = a(d(2)d(4)) 1 / 2 =a

[0103] Or d(5) = a(d(4)d(6)) 1 / 2 =a

[0104] Or d(7) = a(d(6)d(8)) 1 / 2 =a

[0105] Or d(9) = a(d(8)d(10)) 1 / 2 =aj

[0106] Or d(11) = a(d(10)d(0)) 1 / 2 =-a

[0107] 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.

[0108] Example 3

[0109] This embodiment is an example of modulating a first data sequence to form a second data sequence.

[0110] In this embodiment, the first data sequence is modulated to form the second data sequence.

[0111] 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 by the formula: [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 by the formula: [d(i), k = 0, 1, 2, ..., I-1];

[0112] The first data sequence is modulated to form the second data sequence. The modulation process is as follows:

[0113]

[0114] or

[0115]

[0116] in,

[0117] When i=0,1,2,...,I-1,

[0118] When b(i) = 0 or 1, Or -1, Or -1j;

[0119] 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.

[0120] 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.

[0121] Example 4

[0122] This embodiment is an example of modulating a first data sequence to form a second data sequence.

[0123] 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.

[0124] 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], and the modulation process is as follows: Figure 3 As shown:

[0125]

[0126] 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.

[0127] Example 5

[0128] This embodiment is an example of modulating a first data sequence to form a second data sequence.

[0129] 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.

[0130] 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...

[0131]

[0132]

[0133] 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.

[0134] Example 6

[0135] 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.

[0136] In this embodiment, for The power spectral density of the sequence is obtained by performing a Fourier transform and a semi-circular shift. like Figure 4 As shown. 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.

[0137] R can take the value 3 / 4, or 3 / 5, or [1 / 2, 3 / 4], or [1 / 2, 17 / 20].

[0138] 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 amount of 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.

[0139] 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 is obtained by performing a Fourier transform on the sequence. Figure 3 They have the same shape.

[0140] 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.

[0141] 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.

[0142] Example 7

[0143] This embodiment is an example of forming a fourth data sequence from a first data sequence.

[0144] Figure 5 This is a schematic diagram illustrating a data modulation process according to one embodiment. Figure 5As shown, 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.

[0145] 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.

[0146] 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.

[0147] 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.

[0148] Example 8

[0149] 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.

[0150] 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.

[0151] The power spectral density of the third data sequence is as follows: Figure 6 As shown, the horizontal axis represents relative frequency (Hz), and the vertical axis represents power spectral density (PSD) (dB). The length of the horizontal axis is equal to the data bandwidth of the third data sequence. Figure 6Nine scales are evenly marked in the middle. The horizontal axis [0] is the center frequency or the 0th subcarrier. The negative values ​​of the horizontal axis [-1 / 2, -3 / 8, -1 / 4, -1 / 8] are negative frequencies, and the positive values ​​of the horizontal axis [1 / 8, 1 / 4, 3 / 8, 1 / 2] are 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.

[0152] 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.

[0153] In the fourth data sequence, the minimum value of R for truncating R times the data is 1 / 2. This means that truncating R times the data to form the fourth data sequence is equivalent to truncating the data from the third data sequence within the x-coordinate range of [-1 / 4, 1 / 4]. The maximum value of R for truncating R times the data to form the fourth data sequence is 17 / 20. This means that truncating R times the data to form the fourth data sequence is equivalent to truncating the data from the third data sequence within the x-coordinate range of [-17 / 40, 17 / 40].

[0154] This application also provides a data modulation apparatus. Figure 7 This is a schematic diagram of a data modulation apparatus provided in one embodiment. Figure 7 As shown, the data modulation device includes:

[0155] The modulation module 210 is configured to modulate the first data sequence to form a second data sequence;

[0156] Transformation module 220 is configured to perform a Fourier transform on the second data sequence to form a third data sequence;

[0157] 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.

[0158] In one embodiment, R takes one of the following values: 3 / 4, 3 / 5, [1 / 2, 3 / 4], [1 / 2, 17 / 20].

[0159] In one embodiment, the first data sequence is a bit sequence consisting of zero data and data with a value of 1.

[0160] 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.

[0161] In one embodiment, modulating a first data sequence to form a second data sequence includes:

[0162] When k is even, k = 2i.

[0163]

[0164] When k is odd, k = 2i + 1.

[0165] or,

[0166] 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;

[0167] k = 0, 1, 2, ..., 2I-1, where 2I is the number of elements in the second data sequence;

[0168] b(i) represents the element of the first data sequence; d(k) represents the element of the second data sequence;

[0169] a equals 1 or -1, and θ is a preset constant or 0.

[0170] In one embodiment, modulating a first data sequence to form a second data sequence includes:

[0171]

[0172] or

[0173]

[0174] 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;

[0175] and d(i) represents the elements of the first data sequence; d(i) represents the elements of the second data sequence.

[0176] θ is a preset constant or 0.

[0177] In one embodiment, c is π / 4, π, or 5π / 4; s is -π / 4, π, or 3π / 4.

[0178] In one embodiment, extracting R times the amount of data from the third data sequence includes:

[0179] 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.

[0180] In one embodiment, extracting R times the amount of data from the third data sequence includes:

[0181] The third data sequence and the fifth data sequence are multiplied by a dot product to obtain the multiplied data sequence.

[0182] Discard the zero data obtained by multiplying the zero data in the fifth data sequence into the dot product data sequence.

[0183] 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.

[0184] 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.

[0185] In one embodiment, extracting R times the amount of data from the third data sequence includes:

[0186] 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.

[0187] 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].

[0188] In one embodiment, the filtering function is a rectangular function with a roll-off factor of 0.

[0189] In one embodiment, the fifth data sequence is the discrete values ​​of the filtering function.

[0190] In one embodiment, extracting R times the amount of data from the third data sequence to form a fourth data sequence includes:

[0191] 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.

[0192] In one embodiment, extracting R times the amount of data from the third data sequence to form a fourth data sequence includes:

[0193] R times the continuous data are directly extracted from the third data sequence to form the fourth data sequence.

[0194] In one embodiment, extracting R times the amount of data from the third data sequence to form a fourth data sequence includes:

[0195] R times the data are extracted from both ends of the third data sequence. Alternatively, R times the data are extracted from the middle of the third data sequence.

[0196] In one embodiment, the device further includes:

[0197] The multiple determination module is configured to determine R based on the frequency position of zero or near zero in the power spectral density of p*[f / √2, 1, f / √2], where f equals 1 or -1; and p is a constant, representing the power factor. Using the frequency position of zero or near zero in the power spectral density of p*[f / √2, 1, f / √2] as boundaries, the module extracts the data portion of the third data sequence corresponding to the intermediate frequency intervals within the two boundaries to form the fourth data sequence.

[0198] In one embodiment, p takes the value 1, or 1 / √2.

[0199] 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.

[0200] In one embodiment, the device further includes:

[0201] The first inverse transform module is configured to perform an oversampled inverse Fourier transform on the fourth data sequence to form time-domain data;

[0202] The transmission module is configured to transmit the time-domain data.

[0203] In one embodiment, the device further includes:

[0204] The filtering module is configured to perform filtering operations on the fourth data sequence.

[0205] The second inverse transform module is configured to perform an oversampled inverse Fourier transform on the filtered data sequence to form time-domain data;

[0206] The transmission module is configured to transmit the time-domain data.

[0207] In one embodiment, the device further includes, prior to performing the oversampled inverse Fourier transform:

[0208] Multiply the fourth data sequence by a power factor.

[0209] 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.

[0210] This application also provides a communication node. Figure 8 This is a schematic diagram of the hardware structure of a communication node provided in one embodiment, such as... Figure 8 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 8 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.

[0211] The communication node also includes: a communication device 330, an input device 340, and an output device 350.

[0212] 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 8 Taking the example of a connection between China and Israel via a bus.

[0213] 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.

[0214] 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.

[0215] 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.

[0216] 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.

[0217] 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.

[0218] 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.

[0219] 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.

[0220] 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.

[0221] 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).

[0222] 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.

[0223] The above description is merely an exemplary embodiment of this application and is not intended to limit the scope of protection of this application.

[0224] 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.

[0225] 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.

[0226] 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.

[0227] 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 in memory. The 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.

[0228] 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: 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, 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 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, characterized in that, 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, characterized in that, 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. 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, where 2I is the number of elements in the second data sequence; b(i) represents the element of the first data sequence; d(k) represents the 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, characterized in that, 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 elements of the first data sequence; d(i) represents the elements of the second data sequence. θ is a preset constant or 0.

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

8. The method according to claim 1, characterized in that, 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, characterized in that, 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, characterized in that, 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, characterized in that, 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, 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].

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

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

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 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, 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 continuous data are directly extracted from the third data sequence to form the fourth data sequence.

17. 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 are extracted from both ends of the third data sequence, or R times the data are extracted from the middle of the third data sequence.

18. 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*[f / √2, 1, f / √2], 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, characterized in that, p takes the value 1, or 1 / √2.

20. 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.

21. 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.

22. The method according to claim 1, characterized in that, Also includes: 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, characterized in that, Before performing the oversampled inverse Fourier transform, the following is also included: Multiply the fourth data sequence by a power factor.

24. 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 1-23.

25. A computer-readable storage medium having a computer program stored thereon, characterized in that, 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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