A method for optimizing encryption parameters of low peak-to-average ratio in OFDM modulation system

Abstract

The application discloses a low peak-to-average ratio encryption parameter optimization method in an OFDM modulation system, wherein first, input OFDM communication data is subjected to serial-parallel conversion and QAM constellation point mapping; then, an initial key generated by using preset parameters is subjected to one-dimensional SINE chaotic mapping modeling to generate a pseudo-random sequence, which is used as an iteration rule to disturb and encrypt constellation point coordinate data by using a cellular automaton; after that, ciphertext data is subjected to inverse Fourier transform, peak-to-average ratio calculation is performed, and then the key is optimized by using a random multi-neighborhood synchronous search optimization model to generate an optimized key and update the key; the pseudo-random sequence generation, constellation point data encryption, inverse Fourier transform, peak-to-average ratio calculation operations are repeated until the output data is less than a minimum peak-to-average ratio expectation value; finally, an insertion cyclic prefix is performed, serial-parallel conversion is performed, digital-analog conversion data is obtained, and data transmission is completed through electro-optical conversion.

Description

Technical Field

[0001] This invention belongs to the field of optical communication security technology, and more specifically, relates to a method for optimizing encryption parameters for low peak-to-average power ratio in OFDM modulation systems. Background Technology

[0002] In recent years, with the accelerated pace of digital transformation and upgrading across various industries, the cloud era has brought more threats and challenges to information optical transmission and access security, as well as network penetration. Communication transmission is also susceptible to eavesdropping and interference. Ensuring the security of access network communication data transmission and enhancing information confidentiality are crucial for addressing information security issues. Therefore, research on physical layer security enhancement technologies, such as information transmission confidentiality, has become one of the most pressing problems for broadband access networks. Improving the confidentiality of information transmission in broadband access networks has become a hot topic of common concern in the international academic and industrial communities. Common application-layer encryption typically adds authentication and encryption standards to the five layers above the application layer in the Open Systems Interconnection (OSI) seven-layer model. This technology is currently very mature and is already used in PON standards, particularly facilitating secure communication within computer operating systems. Common national-level and commercial encryption algorithms are application-layer encryption algorithms. However, this encryption method suffers from limited key space and complex management, cannot provide security protection for control information and headers, and relies on the computational complexity of algorithm cracking to provide network security protection. It also suffers from high costs, high latency, and complex configuration, and is currently unable to meet the demands of high-speed communication. Digital chaotic encryption utilizes the nonlinearity, randomness, and initial value sensitivity of chaos to generate pseudo-random sequences to encrypt data. It does not require the introduction of additional equipment and has good compatibility with existing communication networks. However, the generation of chaotic pseudo-random sequences requires the introduction of additional DSP latency, resulting in low real-time communication performance. The key space of standalone digital chaotic encryption methods is also limited and subject to floating-point precision limitations, making them prone to chaotic dynamic degradation.

[0003] On the other hand, existing peak-to-average ratio (PAR) suppression algorithms mainly include selective mapping and partial transmission sequence. Selective mapping generates multiple candidate OFDM signals by introducing different phase rotation factors, and then selects the signal with the smallest PAR for transmission. Unlike selective mapping, partial transmission sequence divides the OFDM signal into several sub-blocks, applies a different phase rotation factor to each sub-block, and then performs phase weighting and merging processing on the sub-blocks, selecting the set of symbols with the smallest PAR for transmission to reduce the PAR of the OFDM signal. Both of these PAR suppression algorithms have high computational complexity, requiring the generation and calculation of the PAR of multiple candidate signals. In addition, there is a certain bandwidth overhead due to the need to transmit sideband information such as the selected phase rotation factor. In recent years, researchers have invented many algorithms for suppressing peak-to-average power ratio (PAPR). Among them, the "Scrambling Method and Device for Suppressing PAPR in OFDM / OQAM Systems" first uses frequency domain sequence scrambling, requiring FFT followed by IFFT. The "A System and Method for Suppressing High Peak-to-Average Power Ratio in OFDM Systems" requires a third serial-to-parallel conversion, cyclic prefix removal, fast Fourier transform, decoding, demodulation, and a fourth serial-to-parallel conversion on the basis of the original OFDM modulation. The "PAPR Suppression Method and System for OFDM Encrypted Signals Based on Autoencoders" requires the introduction of chaotic neural networks. These methods require the introduction of additional Fourier transform operations or neural network models, resulting in high computational complexity, which cannot meet the requirements of high-speed communication. Summary of the Invention

[0004] The purpose of this invention is to overcome the shortcomings of the prior art and provide an optimization method for encryption parameters of low peak-to-average power ratio in OFDM modulation systems. This method addresses constellation diagram scrambling encryption and peak-to-average power ratio suppression in OFDM modulation systems, thereby reducing the peak-to-average power ratio of the system while ensuring the security of system transmission and achieving data transmission.

[0005] To achieve the above-mentioned objective, the present invention provides a method for optimizing encryption parameters for low peak-to-average power ratio in an OFDM modulation system, characterized by comprising the following steps:

[0006] (1) Obtain constellation coordinate data;

[0007] (2) Obtain the key sequence and generate A sequence of consecutive key parameters;

[0008] (3) Optimize encryption parameters by using random multi-neighbor synchronous search optimization;

[0009] (4) Output encrypted data;

[0010] The objective of this invention is achieved as follows:

[0011] This invention discloses a method for optimizing encryption parameters for low peak-to-average power ratio (PAPR) in an OFDM modulation system. First, the input OFDM communication data undergoes serial-to-parallel conversion and QAM constellation point mapping. Then, an initial key generated using preset parameters is used to generate a pseudo-random sequence via a one-dimensional SINE chaotic mapping model. This sequence serves as an iterative rule for scrambling and encrypting the constellation point coordinate data using a cellular automaton. Next, the ciphertext data undergoes an inverse Fourier transform, followed by PAPR calculation. The key is then optimized using a random multi-neighbor synchronous search optimization model, generating an optimized key and updating it. This process of generating a pseudo-random sequence, encrypting constellation point data, performing an inverse Fourier transform, and calculating PAPR is repeated until the output data is less than the minimum PAPR expectation value. Finally, a cyclic prefix is ​​inserted, and the parallel-to-serial conversion is performed to convert the data into digital-to-analog conversion data, completing the electro-optical conversion for data transmission.

[0012] Meanwhile, the encryption parameter optimization method for low peak-to-average power ratio in an OFDM modulation system of the present invention also has the following beneficial effects:

[0013] (1) To address the problem of insufficient chaos intensity and weak sequence randomness caused by dynamic degradation in low-dimensional chaotic models, this invention introduces a cellular automata mathematical model. By using a one-dimensional SINE chaotic sequence as the iteration rule, the input constellation map coordinate data is dynamically iterated and encrypted, thereby enhancing the dynamic intensity of the model and improving the complexity, pseudo-randomness and disorder of the low-dimensional chaotic system. It also has good data confusion and diffusion effects.

[0014] (2) When the peak-to-average power ratio signal passes through nonlinear devices such as power amplifiers and mixers, it is easy to generate nonlinear distortion. This invention calculates encryption parameters with high peak-to-average power by iteratively optimizing the encryption parameters, thereby reducing the power consumption of the power amplifier devices, increasing the efficiency of the power amplifier, reducing the transmission power, avoiding signal distortion or nonlinear distortion, and reducing the bit error rate.

[0015] (3) In view of the problems of large computational load, slow convergence speed and easy getting trapped in local optima in ordinary optimization algorithms, this invention introduces the idea of ​​random multi-neighbor synchronous search and proposes a random multi-neighbor synchronous search optimization model. The algorithm of this model is simple, does not require complex derivative calculation of the objective function, has strong global search capability, can effectively avoid getting trapped in local optima, can handle complex and nonlinear optimization problems, especially for discrete optimization problems; at the same time, it can also be processed synchronously, which is suitable for large-scale high-speed computing.

[0016] (4) To address the problem of insufficient low-dimensional chaotic parameter space and key space, this invention integrates a one-dimensional SINE chaotic mapping model with a cellular automata mathematical model, thereby improving the ability to resist statistical analysis attacks and possessing high complexity and security. Attached Figure Description

[0017] Figure 1 This is a flowchart of an encryption parameter optimization method for low peak-to-average power ratio in an OFDM modulation system according to the present invention;

[0018] Figure 2 This is a schematic diagram of random multi-neighbor synchronous search optimization;

[0019] Figure 3 This is a schematic diagram of a random multi-neighbor synchronous search location. Detailed Implementation

[0020] The specific embodiments of the present invention will now be described with reference to the accompanying drawings to enable those skilled in the art to better understand the invention. It should be particularly noted that in the following description, detailed descriptions of known functions and designs that might obscure the main content of the invention will be omitted here.

[0021] Example

[0022] For ease of description, the relevant technical terms appearing in the specific implementation method will be explained first:

[0023] OFDM (Orthogonal Frequency Division Multiplexing): Orthogonal frequency division multiplexing;

[0024] In this embodiment, as Figure 1 As shown, the present invention provides a method for optimizing encryption parameters for low peak-to-average power ratio in an OFDM modulation system, comprising the following steps:

[0025] (1) Obtain constellation coordinate data;

[0026] Obtain OFDM communication data from the OFDM modulation system, perform serial-to-parallel conversion and QAM mapping on the OFDM communication data, and obtain constellation coordinate data;

[0027] (2) Obtain the key sequence and generate A sequence of consecutive key parameters;

[0028] In this embodiment, the transmitter and receiver generate the key parameters based on the key seed; alternatively, a third-party security module or a preset mechanism can distribute the same set of initial parameters to both communicating parties before communication begins, and then generate the key parameter sequence.

[0029] (3) Optimize encryption parameters by using random multi-neighbor synchronous search optimization;

[0030] (3.1) Set the maximum number of iterations Initialize the current iteration count Set the initial search speed for each element. ;

[0031] (3.2) From Randomly selected from the group key parameter sequence Each key parameter sequence is considered as an element, thus forming a vector. , , ;

[0032] (3.3) Using elements As an index, the selected The key parameter sequence is used as input parameters for the chaotic mapping model to generate... Group of pseudo-random sequences ;

[0033] One-dimensional Sine chaotic mapping, also known as sinusoidal chaotic mapping, is a discrete-time dynamical system based on sine functions. It has rich dynamic behaviors and can effectively generate sequences with chaotic characteristics through iteration. Due to its simplicity and rich chaotic behavior, it is widely used in chaotic encryption, random number generation and other complex system research.

[0034] (3.4) Output the optimal solution through iterative optimization;

[0035] (3.4.1) in the first In this iteration, a pseudo-random sequence is used. As a perturbation rule, the input constellation map coordinate data is iteratively encrypted using a cellular automaton to generate ciphertext data. ;

[0036] In this embodiment, a cellular automaton is a discrete mathematical model composed of a large number of simple and regularly arranged cells. Each cell updates its state according to its current state and the states of its neighboring cells, following predefined rules. Cellular automata have wide applications in computer science, physics, biology, and many other fields, and are particularly effective in simulating the dynamic behavior of complex systems. A cellular automaton mainly consists of cells, cell space, cell neighbors, iteration rules, and boundary conditions. A one-dimensional cellular automaton, also known as an elementary cellular automaton, has only two adjacent cells as its cell neighbors. Each cell has two states: "0" and "1". Its mathematical expression is defined as follows:

[0037]

[0038] in, It is a time index value. It is a location index value. It is the cell value at position t after the i-th iteration. These are cell iteration rules. There are a total of 256 rules, for example, rule 105 is shown in the table below:

[0039] <![CDATA[S i (t)]]> 0 0 1 1 0 0 1 1 <![CDATA[S i (t+1)]]> 0 1 0 1 0 1 0 1 <![CDATA[S i+1 (t)]]> 1 0 0 1 0 1 1 0

[0040] The boundary conditions are chosen to be periodic, meaning that the Lth cell is the left neighbor of the 1st cell, and the 1st cell is the right neighbor of the Lth cell, where L is the length of the encrypted data group. The periodic boundary constraints are shown in the following formula:

[0041]

[0042] Before encryption, the input constellation diagram IQ modulation coordinate data is merged. This system uses QAM16 modulation, with each I and Q component data being 4 bits. First, the I component is shifted left by 4 bits, then ORed with the Q component to merge into 8 bits of plaintext data. A pseudo-random sequence is used. As a cell iteration rule, the input constellation map coordinate data is iteratively encrypted using a cellular automaton to generate ciphertext data. For example, using the pseudo-random sequence "0x69", i.e., choosing rule 105 to encrypt the data "127" (assuming the left neighbor cell is 1 and the right neighbor cell is 1), "127" corresponds to the binary value "01111111", and after one iteration, the result is "10000001", so the encryption result is 129.

[0043] (3.4.2) Regarding encrypted data Perform an inverse fast Fourier transform to convert the frequency domain signal into a time domain signal. ;

[0044] (3.4.3) Calculate the time-domain signal for each channel. peak average Select the minimum peak-to-average ratio Then determine the minimum peak-to-average ratio Is it less than the expected value? If it is less than the expected value, then Corresponding ciphertext data If the solution is optimal, output the ciphertext data and then proceed to step (4); otherwise, proceed to step (3.4.4).

[0045] In this embodiment, the peak-to-average power ratio (PAPR) is the ratio of the peak power to the average power of the signal. It reflects the degree of fluctuation in signal power, that is, the proportion of peak power to average power in the signal. The specific expression is shown in the following formula:

[0046] ;

[0047] in, It is a discrete time series, max is to find the maximum value of the series, n is the index of the series, and N is the total length of the series.

[0048] Before calculating the peak-to-average power ratio (PAPR), the 8-bit encrypted data packet output by the cellular automata is split. The high 4 bits are shifted to the right as the I component, and the low 4 bits are used as the Q component. After splitting each data group into I and Q data, an inverse fast Fourier transform is performed to convert the frequency domain signal into a time domain signal. Then, the PAPR of the output time domain signal data is calculated.

[0049] (3.4.4) Update With corresponding speed ;

[0050]

[0051]

[0052] in, It is an element exist Search speed at any given moment For the updated search speed; It is an element exist Index position at time, This is the updated index position; For elements exist Peak-to-average power ratio at any given time; It is a coefficient that controls the degree of influence of the current global optimal position on the search speed; It is the index position of the lowest peak-to-average ratio parameter that has been found globally; This is the default search speed coefficient, controlling the default search speed. It's typically started with a large value and gradually decreased to balance overall search capability. Specific location searches are as follows... Figure 3 As shown, the horizontal axis represents the parameter index value, and the vertical axis represents the peak-to-average power ratio. It is the lowest peak-to-average ratio found globally. It is the peak-to-average ratio at time t. It is the peak-to-average ratio at time t-1. and The slope of a straight line between two points That is, the search speed at the current moment is... and The distance value is related to the index position of the lowest peak-to-average ratio found in the current global search, and the confidence level of the distance value is related to the slope.

[0053] In this embodiment, the present invention introduces the concept of random multi-neighbor synchronous search and proposes a random multi-neighbor synchronous search optimization model for parameter optimization, such as... Figure 2 As shown, this model starts with multiple random parameters to find the optimal solution with the lowest peak-to-average ratio (PAR), determines the index position of the current optimal solution, and then uses other parameters to approach the index position of the optimal solution, completing the next iteration and updating the position of the optimal solution, until the lowest PAR that meets the conditions is found. Compared with other optimization algorithms, this method does not require complex derivative calculations of the objective function and has strong global search capabilities.

[0054] (3.4.5) Order Then return to step (3.4.1);

[0055] (4) Output encrypted data;

[0056] A cyclic prefix is ​​inserted into the encrypted data, and parallel-to-serial conversion and digital-to-analog conversion are performed to complete the electro-optical conversion, which is then transmitted through optical fiber.

[0057] Although the illustrative specific embodiments of the present invention have been described above to enable those skilled in the art to understand the invention, it should be understood that the invention is not limited to the scope of the specific embodiments. For those skilled in the art, various changes are obvious as long as they are within the spirit and scope of the invention as defined and determined by the appended claims, and all inventions utilizing the concept of the present invention are protected.

Claims

1. A method for optimizing encryption parameters in an OFDM modulation system with low peak-to-average power ratio, characterized in that, Includes the following steps: (1) Obtain constellation coordinate data; Obtain OFDM communication data from the OFDM modulation system, perform serial-to-parallel conversion and QAM mapping on the OFDM communication data, and obtain constellation coordinate data; (2) Obtain the key sequence and generate A sequence of consecutive key parameters; (3) Optimize encryption parameters by using random multi-neighbor synchronous search optimization; (3.1) Set the maximum number of iterations Initialize the current iteration count Set the initial search speed for each element. ; (3.2) From Randomly selected from the group key parameter sequence Each key parameter sequence is considered as an element, thus forming a vector. , , ; (3.3) Using elements As an index, the selected The key parameter sequence is used as input parameters for the chaotic mapping model to generate... Group of pseudo-random sequences ; (3.4) Output the optimal solution through iterative optimization; (3.4.1) in the first In this iteration, a pseudo-random sequence is used. As a perturbation rule, the input constellation map coordinate data is iteratively encrypted using a cellular automaton to generate ciphertext data. ; (3.4.2) Regarding encrypted data Perform an inverse fast Fourier transform to convert the frequency domain signal into a time domain signal. ; (3.4.3) Calculate the time-domain signal for each channel. peak average Select the minimum peak-to-average ratio Then determine the minimum peak-to-average ratio Is it less than the expected value? If it is less than the expected value, then Corresponding encrypted data If the solution is optimal, output the ciphertext data and then proceed to step (4); otherwise, proceed to step (3.4.4). (3.4.4) Update With corresponding speed ; ； ； in, It is an element exist Search speed at any given moment For the updated search speed; It is an element exist Index position at time, This is the updated index position; For elements exist Peak-to-average power ratio at any given time; It is a coefficient that controls the degree of influence of the current global optimal position on the search speed; It is the index position of the lowest peak-to-average ratio parameter that has been found globally; This is the default search speed factor; (3.4.5) Order Then return to step (3.4.1); (4) Output encrypted data; A cyclic prefix is ​​inserted into the encrypted data, and parallel-to-serial conversion and digital-to-analog conversion are performed to complete the electro-optical conversion, which is then transmitted through optical fiber.

Images