Communication transmission method and device based on pseudo-random code

Abstract

The invention discloses a communication transmission method and device based on a pseudo-random code. The method comprises the following steps: acquiring information to be transmitted; randomly generating first seed information and second seed information; performing feedback iterative calculation processing on the first seed information and the second seed information to obtain a pseudo-random code; performing coding processing on the information to be transmitted by using the pseudo-random code to obtain information to be transmitted; and sending the to-be-sent information to a receiving end from a sending end. According to the method, the random seed information is subjected to linear feedback shift and fractal calculation processing, so that the generated pseudo-random code has a chaotic characteristic, the randomness of the pseudo-random code is improved, and the pseudo-random code with excellent randomness and a statistical characteristic close to that of white noise is quickly constructed.

Description

Technical Field

[0001] The present invention relates to the field of communications, and in particular to a communication transmission method and device based on pseudo-random codes. Background Art

[0002] With the rapid development of wireless communication technology, wireless network security is receiving increasing attention. Using pseudorandom numbers to encode transmitted information is one means of enhancing wireless network security. Pseudorandom numbers are random numbers derived from a uniform distribution between [0, 1] calculated using a deterministic algorithm. While not truly random, they possess statistical properties similar to those of random numbers. Pseudorandom sequences are deterministic sequences with certain random properties. Due to their excellent randomness and statistical properties similar to white noise, they are widely used in many fields of science, technology, and engineering.

[0003] How to quickly construct a pseudo-random code with excellent randomness and statistical properties close to white noise, and use it for secure information transmission, is an urgent problem to be solved. Summary of the Invention

[0004] The present invention mainly solves the problem of how to quickly construct a pseudo-random code with excellent randomness and statistical characteristics close to white noise, and use it to transmit information. The present invention discloses a communication transmission method and device of the pseudo-random code.

[0005] In a first aspect of the embodiments of the present application, a communication transmission method based on a pseudo-random code is disclosed, comprising:

[0006] S1, obtain the information to be transmitted;

[0007] S2, randomly generating first seed information and second seed information;

[0008] S3, performing feedback iterative calculation processing on the first seed information and the second seed information to obtain a pseudo-random code;

[0009] S4, using the pseudo-random code to encode the information to be transmitted to obtain information to be sent;

[0010] S5, sending the information to be sent from the sending end to the receiving end.

[0011] The performing feedback iterative calculation processing on the first seed information and the second seed information to obtain a pseudo-random code includes:

[0012] S31, initialize the shift value;

[0013] S32, performing a linear feedback shift process on the first seed information to obtain a first state sequence; and performing a linear cyclic shift process on the second seed information using the shift value to obtain a second state sequence;

[0014] S33, performing fractal calculation processing on the first state sequence to obtain a third state sequence;

[0015] S34, performing an AND operation on the first state sequence and the third state sequence to obtain a fourth state sequence;

[0016] S35, performing a bit-by-bit XOR operation on the fourth state sequence to obtain a pseudo-random code;

[0017] S36, using each numerical value of the pseudo-random code to update the shift value.

[0018] The calculation expression of the linear feedback shift process is:

[0019]

[0020] Among them, f i represents the i-th coefficient of the linear feedback shift process, a i represents the value of the first seed information a at the i-th bit, F t It represents the value of the first state sequence at time t, and is also the output at time t of linear feedback shift processing of the first seed information a. t-1 Represents the value of the first state sequence at time t-1.

[0021] The expression of the fractal calculation process is:

[0022] z i+1 =μz i (1–F i –z i ) w-1 ,

[0023] Among them, z i+1 is the i+1th value of the third state sequence obtained by fractal calculation, F i represents the value of the i-th bit of the first state sequence, z i is the i-th value of the third state sequence obtained by the fractal calculation process, μ and w are the multiplication factor and exponential factor of the preset fractal calculation process respectively;

[0024] When performing fractal calculations, the z i The value is determined by the mean of the first state sequence.

[0025] The step of encoding the information to be transmitted using the pseudo-random code to obtain the information to be sent includes:

[0026] Using the pseudo-random codes obtained at several moments, a pseudo-random code matrix is constructed;

[0027] Performing feature transformation processing on the pseudo-random code matrix to obtain a coding sequence;

[0028] The coded sequence is multiplied by the information to be transmitted to obtain the information to be sent.

[0029] The performing feature transformation processing on the pseudo-random code matrix to obtain a coding sequence includes:

[0030] Performing VMD transformation on each row vector of the pseudo-random code matrix to obtain a corresponding transformation vector;

[0031] Using the transformation vector as a row vector, constructing a transformation matrix;

[0032] Multiplying the pseudo-random code matrix by the transformed rank of the transformation matrix to obtain a random transformation matrix;

[0033] Solving the singular values of the random transformation matrix to obtain a singular value set and a singular value vector;

[0034] Performing statistical calculations on the singular value set and the singular value vector to obtain a coding sequence;

[0035] The expression of the statistical calculation is:

[0036]

[0037] Among them, c i is the i-th element of the encoding sequence, ρ i is the i-th element of the singular value set, t ij is the jth element of the i-th singular value vector, t i and vt i are the mean and variance of the i-th singular value vector, and M is the number of elements in the singular value vector.

[0038] In a second aspect of the embodiments of the present application, a communication transmission device based on a pseudo-random code is disclosed, which is used to implement the communication transmission method based on a pseudo-random code, including: a signal source module, a pseudo-random code generation module, an encoding module, a sending module and a receiving module;

[0039] The information source module is used to obtain information to be transmitted;

[0040] The pseudo-random code generation module is used to randomly generate first seed information and second seed information;

[0041] The pseudo-random code generation module is used to perform feedback iterative calculation processing on the randomly generated first seed information and second seed information to obtain a pseudo-random code;

[0042] The encoding module is used to encode the information to be transmitted using a pseudo-random code to obtain the information to be sent;

[0043] The sending module is used to send the information to be sent to the receiving module;

[0044] The receiving module is used to receive the information to be sent.

[0045] The pseudo-random code generation module includes a random number submodule, a linear feedback shift register, a fractal function submodule, a shift register, a sum operation submodule, a register, an exclusive OR operation submodule and an output submodule;

[0046] The random number submodule is connected to the linear feedback shift register and the shift register respectively, and is used to randomly generate the first seed information and the second seed information;

[0047] The linear feedback shift register is connected to the fractal function submodule and is used to perform linear feedback shift processing on the first seed information to obtain a first state sequence;

[0048] The fractal function submodule is used to perform fractal calculation processing on the first state sequence to obtain a third state sequence;

[0049] The shift register is configured to perform a linear cyclic shift process on the second seed information using a shift value to obtain a second state sequence; the shift value is updated according to each value of the pseudo-random code output by the output submodule;

[0050] The sum operation submodule is connected to the fractal function submodule and the shift register respectively, and is used to perform a sum operation on the first state sequence and the third state sequence to obtain a fourth state sequence;

[0051] The register is connected to the AND operator module and the XOR operator module respectively, and is used to perform register processing on the fourth state sequence and send the fourth state sequence bit by bit to the XOR operator module;

[0052] The XOR operation submodule is connected to the shift register, the register and the output submodule respectively, and is used to perform bit-by-bit XOR operation on the fourth state sequence to obtain a pseudo-random code, and send the pseudo-random code to the shift register and the output submodule;

[0053] The output submodule is used to output a pseudo-random code.

[0054] In a third aspect of the embodiments of the present application, a communication transmission device based on a pseudo-random code is disclosed, the device comprising:

[0055] a memory storing executable program code;

[0056] a processor coupled to the memory;

[0057] The processor calls the executable program code stored in the memory to execute the communication transmission method based on the pseudo-random code.

[0058] In a fourth aspect of the embodiments of the present application, a computer-storable medium is disclosed, wherein the computer-storable medium stores computer instructions. When the computer instructions are called by a computer, they are used to execute the communication transmission method based on pseudo-random codes.

[0059] In a fifth aspect of the embodiments of the present application, an information data processing terminal is disclosed, which is used to implement the communication transmission method based on pseudo-random codes.

[0060] The beneficial effects of the present invention are:

[0061] The present invention performs linear feedback shift and fractal calculation processing on random seed information, so that the generated pseudo-random code has chaotic characteristics, improves the randomness of the pseudo-random code, and thus realizes the rapid construction of a pseudo-random code with excellent randomness and statistical characteristics close to white noise.

[0062] When encoding the information to be processed, the present application constructs a matrix by constructing pseudo-random codes obtained at multiple moments, performs feature extraction processing on the matrix, and obtains the final coding sequence, which effectively improves the stability and security of the coding process and realizes efficient and secure information transmission. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] Figure 1 Flow chart for the implementation of the method of the present invention;

[0064] Figure 2 Schematic diagram of the composition of the pseudo-random code generation module of the present invention. DETAILED DESCRIPTION

[0065] In order to better understand the content of the present invention, an embodiment is given here.

[0066] Figure 1 Flow chart for the implementation of the method of the present invention; Figure 2 Schematic diagram of the composition of the pseudo-random code generation module of the present invention.

[0067] In a first aspect of the embodiments of the present application, a communication transmission method based on a pseudo-random code is disclosed, comprising:

[0068] S1, obtain the information to be transmitted;

[0069] S2, randomly generating first seed information and second seed information;

[0070] S3, performing feedback iterative calculation processing on the first seed information and the second seed information to obtain a pseudo-random code;

[0071] S4, using a pseudo-random code to encode the information to be transmitted to obtain the information to be sent;

[0072] S5, sending the information to be sent from the sending end to the receiving end, completing the communication transmission based on the pseudo-random code.

[0073] The performing feedback iterative calculation processing on the first seed information and the second seed information to obtain a pseudo-random code includes:

[0074] S31, initialize the shift value;

[0075] S32, performing a linear feedback shift process on the first seed information to obtain a first state sequence; and performing a linear cyclic shift process on the second seed information using the shift value to obtain a second state sequence;

[0076] S33, performing fractal calculation processing on the first state sequence to obtain a third state sequence;

[0077] S34, performing an AND operation on the first state sequence and the third state sequence to obtain a fourth state sequence;

[0078] S35, performing a bit-by-bit XOR operation on the fourth state sequence to obtain a pseudo-random code;

[0079] S36, using each numerical value of the pseudo-random code to update the shift value.

[0080] The calculation expression of the linear feedback shift process is:

[0081]

[0082] Among them, f i represents the i-th coefficient of the linear feedback shift process, a i represents the value of the first seed information a at the i-th bit, F t It represents the value of the first state sequence at time t, and is also the output at time t of linear feedback shift processing of the first seed information a. t-1 Represents the value of the first state sequence at time t-1. For the first state sequence at time t=0, it is represented by the first seed information;

[0083] The expression of the fractal calculation process is:

[0084] z i+1 =μz i (1–F i –z i ) w-1 ,

[0085] Among them, z i+1 is the i+1th value of the third state sequence obtained by fractal calculation, F i represents the value of the i-th bit of the first state sequence, z i is the i-th value of the third state sequence obtained by fractal calculation, μ and w are the multiplication factor and exponential factor of the preset fractal calculation respectively; when performing fractal calculation, z in the first calculation is i The value is determined by the mean of the first state sequence.

[0086] The method of encoding the information to be transmitted using a pseudo-random code to obtain the information to be sent includes:

[0087] Using the pseudo-random codes obtained at a number of moments, a pseudo-random code matrix is constructed; the row vector of the pseudo-random code matrix is the pseudo-random code at each moment;

[0088] Performing feature transformation processing on the pseudo-random code matrix to obtain a coding sequence;

[0089] The coded sequence is multiplied by the information to be transmitted to obtain the information to be sent.

[0090] The performing feature transformation processing on the pseudo-random code matrix to obtain a coding sequence includes:

[0091] Decomposing the pseudo-random code matrix to obtain a left decomposition matrix, a characteristic matrix, and a right decomposition matrix;

[0092] The calculation expression of the decomposition process is:

[0093] Y=UAV,

[0094] Among them, U is the left decomposition matrix, Y is the pseudo-random code matrix, A is the characteristic matrix, V is the right decomposition matrix, U and V are both orthogonal matrices, and A is a diagonal matrix;

[0095] Extracting the diagonal elements of the characteristic matrix to obtain a characteristic vector;

[0096] Performing linear fitting processing on the elements and element sequence numbers of the characteristic vector to obtain a characteristic approximation polynomial;

[0097] For each row vector of the pseudo-random code matrix, calculating an average value u0 of the row vector;

[0098] For each element in the row vector, calculate the absolute value of the difference between the element and the average value u0, and determine the absolute value of the difference as the offset of the element;

[0099] For each row vector, find the element with the minimum offset, and determine the sequence number of the element in the row vector, which is the offset sequence number of the row vector;

[0100] Using the characteristic estimation polynomial, the deviation sequence value of each row vector is calculated and processed to obtain the eigenvalue corresponding to each row vector;

[0101] Using the eigenvalues corresponding to all row vectors, the coding sequence is constructed;

[0102] The decomposition process can be implemented by using a matrix singular value decomposition algorithm.

[0103] The linear fitting process is to use the characteristic vector element serial number value Ix as a known independent variable and the characteristic vector element value as a known dependent variable, and to construct a curve to be approximated using the known independent variable and the known dependent variable, and to perform curve fitting on the curve to be approximated using the function approximation method to obtain a characteristic approximation polynomial.

[0104] The curve fitting for the curve to be approximated by using a function approximation method may be performed using an optimal consistent linear approximation method.

[0105] The performing feature transformation processing on the pseudo-random code matrix to obtain a coding sequence includes:

[0106] Performing VMD transformation on each row vector of the pseudo-random code matrix to obtain a corresponding transformation vector;

[0107] Using all transformation vectors as row vectors, the transformation matrix is constructed;

[0108] Multiplying the pseudo-random code matrix by the transformed rank of the transformation matrix to obtain a random transformation matrix;

[0109] Solving the singular values of the random transformation matrix to obtain a singular value set and a singular value vector;

[0110] Performing statistical calculations on the singular value set and the singular value vector to obtain a coding sequence;

[0111] The expression of the statistical calculation is:

[0112]

[0113] Among them, c iis the i-th element of the encoding sequence, ρ i is the i-th element of the singular value set, t ij is the jth element of the i-th singular value vector, t i and υt i are the mean and variance of the i-th singular value vector, and M is the number of elements in the singular value vector;

[0114] The first half of the statistical calculation expression uses the inverse sine function to calculate the ratio of the difference and the sum of the two values, which can fully explore the complex relationship between the singular value set and the singular value vector. Therefore, the generation of the coding sequence is no longer a simple linear relationship, but incorporates richer nonlinear factors, thereby enhancing the randomness of the coding sequence, making it more in line with the requirements of excellent randomness of pseudo-random codes, and helping to improve the security of information transmission.

[0115] The second half of the statistical calculation expression utilizes the mean and variance of the i-th singular value vector. By calculating the norm of the difference between the elements of the singular value set and the mean of the singular value vector and performing an exponential operation based on the variance, the statistical properties of the singular value vector are incorporated into the generation of the code sequence. This statistically-based calculation method makes the generated code sequence more similar to the statistical properties of white noise. Because white noise has specific statistical regularities, calculations using the mean and variance of the singular value vector can better simulate these statistical properties, thereby increasing the complexity of interference in information transmission and improving the security and reliability of information transmission.

[0116] The entire statistical calculation expression integrates multiple aspects of information, including the elements of the singular value set, the elements of the singular value vector, the mean, and the variance. By using nonlinear operations such as exponential and inverse sine functions, this not only increases computational complexity, making it difficult for attackers to crack the coding sequence through simple analysis, but also effectively utilizes various information obtained through the transformation of the pseudo-random code matrix characteristics. This further optimizes the coding sequence generation process, making it more suitable for secure information transmission and better meeting the current demand for improving wireless network security.

[0117] The VMD transformation is variational mode decomposition.

[0118] A second aspect of an embodiment of the present invention discloses a communication transmission method based on a pseudo-random code, comprising: a signal source module, a pseudo-random code generation module, an encoding module, a sending module, and a receiving module;

[0119] The information source module is used to obtain information to be transmitted; the pseudo-random code generation module is used to randomly generate first seed information and second seed information;

[0120] The pseudo-random code generation module is used to perform feedback iterative calculation processing on the randomly generated first seed information and second seed information to obtain a pseudo-random code;

[0121] The encoding module is used to encode the information to be transmitted using a pseudo-random code to obtain the information to be sent;

[0122] The sending module is used to send the information to be sent to the receiving module;

[0123] The receiving module is used to receive the information to be sent;

[0124] The pseudo-random code generation module includes a random number submodule, a linear feedback shift register, a fractal function submodule, a shift register, a sum operation submodule, a register, an exclusive OR operation submodule and an output submodule;

[0125] The random number submodule is connected to the linear feedback shift register and the shift register respectively, and is used to randomly generate the first seed information and the second seed information;

[0126] The linear feedback shift register is connected to the fractal function submodule and is used to perform linear feedback shift processing on the first seed information to obtain a first state sequence;

[0127] The fractal function submodule is used to perform fractal calculation processing on the first state sequence to obtain a third state sequence;

[0128] The shift register is configured to perform a linear cyclic shift process on the second seed information using a shift value to obtain a second state sequence; the shift value is updated according to each value of the pseudo-random code output by the output submodule;

[0129] The sum operation submodule is connected to the fractal function submodule and the shift register respectively, and is used to perform a sum operation on the first state sequence and the third state sequence to obtain a fourth state sequence;

[0130] The register is connected to the AND operator module and the XOR operator module respectively, and is used to perform register processing on the fourth state sequence and send the fourth state sequence bit by bit to the XOR operator module;

[0131] The XOR operation submodule is connected to the shift register, the register and the output submodule respectively, and is used to perform bit-by-bit XOR operation on the fourth state sequence to obtain a pseudo-random code, and send the pseudo-random code to the shift register and the output submodule;

[0132] The output submodule is used to output a pseudo-random code.

[0133] Figure 2This is a schematic diagram of the pseudo-random code generation module. Figure 2 In the figure, mLFSR represents the pseudo-random code generation module, lamdafractal function represents the fractal function submodule, Shift Register represents the shift register module, XOR represents the exclusive OR operation submodule, Register represents the register module, Output represents the output submodule, Seed2 and Seed1 represent the first seed information and the second seed information, respectively.

[0134] The calculation expression of the linear feedback shift process is:

[0135]

[0136] Among them, f i represents the i-th coefficient of the linear feedback shift process, a i represents the value of the first seed information a at the i-th bit, F t It represents the value of the first state sequence at time t, and is also the output at time t of linear feedback shift processing of the first seed information a. t-1 Represents the value of the first state sequence at time t-1. For the first state sequence at time t=0, it is represented by the first seed information;

[0137] The expression of the fractal calculation process is:

[0138] z i+1 =μz i (1–F i –z i ) w-1 ,

[0139] Among them, z i+1 is the i+1th value of the third state sequence obtained by fractal calculation, F i represents the value of the i-th bit of the first state sequence, z i is the i-th value of the third state sequence obtained by fractal calculation, μ and w are the multiplication factor and exponential factor of the preset fractal calculation respectively; when performing fractal calculation, z in the first calculation is i The value is determined by the mean of the first state sequence.

[0140] The encoding module is used to construct a pseudo-random code matrix using pseudo-random codes obtained at several moments; the row vector of the pseudo-random code matrix is the pseudo-random code at each moment; the pseudo-random code matrix is subjected to feature transformation processing to obtain a coding sequence; and the coding sequence is multiplied by the information to be transmitted to obtain the information to be sent.

[0141] The performing feature transformation processing on the pseudo-random code matrix to obtain a coding sequence includes:

[0142] Decomposing the pseudo-random code matrix to obtain a left decomposition matrix, a characteristic matrix, and a right decomposition matrix;

[0143] The calculation expression of the decomposition process is:

[0144] Y=UAV,

[0145] Among them, U is the left decomposition matrix, Y is the pseudo-random code matrix, A is the characteristic matrix, V is the right decomposition matrix, U and V are both orthogonal matrices, and A is a diagonal matrix;

[0146] Extracting the diagonal elements of the characteristic matrix to obtain a characteristic vector;

[0147] Performing linear fitting processing on the elements and element sequence numbers of the characteristic vector to obtain a characteristic approximation polynomial;

[0148] For each row vector of the pseudo-random code matrix, calculating an average value u0 of the row vector;

[0149] For each element in the row vector, calculate the absolute value of the difference between the element and the average value u0, and determine the absolute value of the difference as the offset of the element;

[0150] For each row vector, find the element with the minimum offset, and determine the sequence number of the element in the row vector, which is the offset sequence number of the row vector;

[0151] Using the characteristic estimation polynomial, the deviation sequence value of each row vector is calculated and processed to obtain the eigenvalue corresponding to each row vector;

[0152] Using the eigenvalues corresponding to all row vectors, the coding sequence is constructed;

[0153] The decomposition process can be implemented by using a matrix singular value decomposition algorithm.

[0154] The linear fitting process is to use the characteristic vector element serial number value Ix as a known independent variable and the characteristic vector element value as a known dependent variable, and to construct a curve to be approximated using the known independent variable and the known dependent variable, and to perform curve fitting on the curve to be approximated using the function approximation method to obtain a characteristic approximation polynomial.

[0155] The curve fitting for the curve to be approximated by using a function approximation method may be performed using an optimal consistent linear approximation method.

[0156] The sending module, after obtaining the coding sequence and before starting to send the information to be sent, sends the coding sequence to the receiving module; after receiving the coding sequence, the receiving module performs an inverse process on the coding sequence to obtain a decoding sequence; after receiving the information to be sent, the decoding sequence is used to decode the information to be sent to obtain received information;

[0157] The inverse process is to solve the sequence obtained by multiplying the encoded sequence to obtain the unit sequence, and determine the sequence as the decoding sequence.

[0158] In a third aspect of the embodiments of the present application, a communication transmission device based on a pseudo-random code is disclosed, the device comprising:

[0159] a memory storing executable program code;

[0160] a processor coupled to the memory;

[0161] The processor calls the executable program code stored in the memory to execute the communication transmission method based on the pseudo-random code.

[0162] In a fourth aspect of the embodiments of the present application, a computer-storable medium is disclosed, wherein the computer-storable medium stores computer instructions. When the computer instructions are called by a computer, they are used to execute the communication transmission method based on pseudo-random codes.

[0163] In a fifth aspect of the embodiments of the present application, an information data processing terminal is disclosed, which is used to implement the communication transmission method based on pseudo-random codes.

[0164] The foregoing is merely an embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present application should all be included within the scope of the claims of the present application.

Claims

1. A communication transmission method based on pseudo-random code, characterized in that: include: S1, obtain the information to be transmitted; S2, randomly generating first seed information and second seed information; S3, performing feedback iterative calculation processing on the first seed information and the second seed information to obtain a pseudo-random code; S4, using the pseudo-random code to encode the information to be transmitted to obtain information to be sent; S5, sending the information to be sent from the sending end to the receiving end.

2. The communication transmission method based on pseudo-random code according to claim 1, characterized in that: The performing feedback iterative calculation processing on the first seed information and the second seed information to obtain a pseudo-random code includes: S31, initialize the shift value; S32, performing a linear feedback shift process on the first seed information to obtain a first state sequence; and performing a linear cyclic shift process on the second seed information using the shift value to obtain a second state sequence; S33, performing fractal calculation processing on the first state sequence to obtain a third state sequence; S34, performing an AND operation on the first state sequence and the third state sequence to obtain a fourth state sequence; S35, performing a bit-by-bit XOR operation on the fourth state sequence to obtain a pseudo-random code; S36, using each numerical value of the pseudo-random code to update the shift value.

3. The communication transmission method based on pseudo-random code according to claim 2, characterized in that: The calculation expression of the linear feedback shift process is: Among them, f i represents the i-th coefficient of the linear feedback shift process, a i represents the value of the first seed information a at the i-th bit, F t It represents the value of the first state sequence at time t, and is also the output at time t of linear feedback shift processing of the first seed information a. i-1 Represents the value of the first state sequence at time t-1.

4. The communication transmission method based on pseudo-random code according to claim 2, characterized in that: The expression of the fractal calculation process is: z i+1 =μz i (1–F i –z i ) w-1 , Among them, z i+1 is the i+1th value of the third state sequence obtained by fractal calculation, F i represents the value of the i-th bit of the first state sequence, z i is the i-th value of the third state sequence obtained by the fractal calculation process, μ and w are the multiplication factor and exponential factor of the preset fractal calculation process respectively; When performing fractal calculations, the z i The value is determined by the mean of the first state sequence.

5. The communication transmission method based on pseudo-random code according to claim 1, characterized in that: The step of encoding the information to be transmitted using the pseudo-random code to obtain the information to be sent includes: Using the pseudo-random codes obtained at several moments, a pseudo-random code matrix is constructed; Performing feature transformation processing on the pseudo-random code matrix to obtain a coding sequence; The coded sequence is multiplied by the information to be transmitted to obtain the information to be sent. The performing feature transformation processing on the pseudo-random code matrix to obtain a coding sequence includes: Performing VMD transformation on each row vector of the pseudo-random code matrix to obtain a corresponding transformation vector; Using the transformation vector as a row vector, constructing a transformation matrix; Multiplying the pseudo-random code matrix by the transformed rank of the transformation matrix to obtain a random transformation matrix; Solving the singular values of the random transformation matrix to obtain a singular value set and a singular value vector; Performing statistical calculations on the singular value set and the singular value vector to obtain a coding sequence; The expression of the statistical calculation is: Among them, c i is the i-th element of the encoding sequence, ρ i is the i-th element of the singular value set, t ij is the jth element of the i-th singular value vector, t i and υt i are the mean and variance of the i-th singular value vector, and M is the number of elements in the singular value vector.

6. A communication transmission device based on pseudo-random code, characterized in that: Used to implement the communication transmission method based on pseudo-random code according to any one of claims 1 to 5, comprising: a source module, a pseudo-random code generation module, an encoding module, a sending module and a receiving module; The information source module is used to obtain information to be transmitted; The pseudo-random code generation module is used to randomly generate first seed information and second seed information; The pseudo-random code generation module is used to perform feedback iterative calculation processing on the randomly generated first seed information and second seed information to obtain a pseudo-random code; The encoding module is used to encode the information to be transmitted using a pseudo-random code to obtain the information to be sent; The sending module is used to send the information to be sent to the receiving module; The receiving module is used to receive the information to be sent.

7. The communication transmission device based on pseudo-random code according to claim 6, characterized in that: The pseudo-random code generation module includes a random number submodule, a linear feedback shift register, a fractal function submodule, a shift register, a sum operation submodule, a register, an exclusive OR operation submodule and an output submodule; The random number submodule is connected to the linear feedback shift register and the shift register respectively, and is used to randomly generate the first seed information and the second seed information; The linear feedback shift register is connected to the fractal function submodule and is used to perform linear feedback shift processing on the first seed information to obtain a first state sequence; The fractal function submodule is used to perform fractal calculation processing on the first state sequence to obtain a third state sequence; The shift register is configured to perform a linear cyclic shift process on the second seed information using a shift value to obtain a second state sequence; the shift value is updated according to each value of the pseudo-random code output by the output submodule; The sum operation submodule is connected to the fractal function submodule and the shift register respectively, and is used to perform a sum operation on the first state sequence and the third state sequence to obtain a fourth state sequence; The register is connected to the AND operator module and the XOR operator module respectively, and is used to perform register processing on the fourth state sequence and send the fourth state sequence bit by bit to the XOR operator module; The XOR operation submodule is connected to the shift register, the register and the output submodule respectively, and is used to perform bit-by-bit XOR operation on the fourth state sequence to obtain a pseudo-random code, and send the pseudo-random code to the shift register and the output submodule; The output submodule is used to output a pseudo-random code.

8. A communication transmission device based on pseudo-random code, characterized in that: The device comprises: a memory storing executable program code; a processor coupled to the memory; The processor calls the executable program code stored in the memory to execute the communication transmission method based on pseudo-random codes according to any one of claims 1 to 5.

9. A computer storable medium, characterized in that The computer storable medium stores computer instructions, and when the computer instructions are called by a computer, they are used to execute the communication transmission method based on pseudo-random codes according to any one of claims 1 to 5.

10. An information data processing terminal, characterized in that: The information data processing terminal is used to implement the communication transmission method based on pseudo-random codes as described in any one of claims 1 to 5.

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