CN-121984622-A - Multifunctional signal modeling method, system, equipment and medium

CN121984622ACN 121984622 ACN121984622 ACN 121984622ACN-121984622-A

Abstract

The application provides a method, a system, equipment and a medium for modeling a multifunctional signal, wherein the method comprises the steps of generating binary keying information according to a function type of input data, configuring weighted fractional Fourier transform parameters for the function type according to the binary keying information, carrying out weighted fractional Fourier transform on the function type to obtain frequency domain signal parameters, constructing a weighted information cross entropy objective function, carrying out global optimization on the frequency domain signal parameters according to the weighted information cross entropy objective function to generate and transmit a mixed carrier signal, and carrying out inverse weighted fractional Fourier transform on the mixed carrier signal according to a frame type of the mixed carrier signal to obtain the multifunctional signal. The application adopts a flexible mixed carrier modulation frame of weighted fractional Fourier transform and weighted information cross entropy, and properly adjusts the weighted fractional Fourier transform parameters through global optimization, thereby realizing deep synergy and performance compromise of communication, perception and interference performance.

Inventors

HUANG CHONGWEN
HU YUQI
WANG DEZHI

Assignees

乾元国家实验室
浙江大学

Dates

Publication Date: 20260505
Application Date: 20260202

Claims (10)

1. A multi-functional signal modeling method based on weighted information cross entropy global optimization, the method comprising: Generating binary keying information according to the function type of input data, and configuring weighted fractional Fourier transform parameters for the function type according to the binary keying information; performing weighted fractional Fourier transform on the function type to obtain frequency domain signal parameters; Constructing a weighted information cross entropy objective function, and performing global optimization on the frequency domain signal parameters according to the weighted information cross entropy objective function to generate and transmit a mixed carrier signal; And performing inverse weighted fractional Fourier transform on the mixed carrier signal according to the frame type of the mixed carrier signal to obtain a multifunctional signal.
2. The method of claim 1, wherein generating binary keying information from a function type of input data and configuring weighted fractional fourier transform parameters for the function type based on the binary keying information comprises: separating input data into keying information and a payload, wherein the payload comprises a perception data frame and a communication data frame; And setting a weighted fractional Fourier transform parameter corresponding to the frame type of the effective data load according to the keying information.
3. The method of claim 2, wherein setting the weighted fractional fourier transform parameter corresponding to the frame type of the payload according to the keying information comprises: When the frame type of the effective data load is a perception data frame, generating the keying information as 0, and setting a weighted fraction Fourier transform parameter corresponding to the perception data frame as zero; And when the frame type of the effective data load is a communication data frame, generating the keying information as 1, and setting a weighted fraction Fourier transform parameter corresponding to the communication data frame as a non-zero value.
4. The method of claim 1, wherein the weighted-score fourier transform is expressed as Wherein, the method comprises the steps of, In the form of a time-domain discrete sequence, Is that Is a sequence of discrete fourier transforms of (c), Is that The sequence of the corresponding inversion is performed, Is that The sequence of the corresponding inversion is performed, Weighting coefficient Is defined as Is a weighted fractional fourier transform parameter.
5. The method of claim 1, wherein the weighted information cross entropy objective function is: Wherein, the method comprises the steps of, X represents a waveform of a multifunctional integrated signal, Representing the weighting coefficients of the communication signal, Representing the weighting coefficients of the perceived signal, Representing the weighting coefficients of the interfering signal, Representing the bandwidth of the communication signal, Representing the bandwidth of the perceived signal, Representing the bandwidth of the interfering signal, Representing a performance characterization of the normalized communication function, Representing a performance characterization of the normalized perceptual function, Representing a performance characterization of the normalized interference function, Representing the total bandwidth of the signal, Indicating a lower performance limit for the communication function, Representing the lower performance limit of the sensing function, Representing the lower performance limit of the interfering function.
6. The method of claim 1, wherein said performing an inverse weighted fractional fourier transform on said mixed carrier signal based on a frame type of said mixed carrier signal to obtain a multi-functional signal comprises: performing inverse weighted fractional Fourier transform on a received signal corresponding to the communication data frame to obtain a communication time domain frame; performing inverse weighted fractional Fourier transform on the received signals corresponding to the perception data frames to obtain perception time domain frames; Dividing the time-frequency diagram into N time-frequency units, wherein the energy duty ratio of each unit is The interference energy entropy is Wherein, the method comprises the steps of, Is the energy duty cycle of the ith time-frequency cell, Denoted as the first The interference energy of the individual time-frequency units, Representing the total interference energy of all time-frequency units.
7. The method of claim 1, wherein said performing an inverse weighted fractional fourier transform on said mixed carrier signal based on a frame type of said mixed carrier signal to obtain a multi-functional signal comprises: And performing matched filtering and calculating root mean square error of distance estimation on the perception time domain frame to measure the accuracy of the perception data frame.
8. A multi-functional signal modeling system based on weighted information cross entropy global optimization, the system comprising: the data analysis module is configured to generate binary keying information according to the function type of input data, and configure weighted fraction Fourier transform parameters for the function type according to the binary keying information; the carrier modulation and demodulation module is configured to perform weighted fractional Fourier transform on the function type to obtain frequency domain signal parameters, and perform inverse weighted fractional Fourier transform on the mixed carrier signal according to the frame type of the mixed carrier signal to obtain a multifunctional signal; And the global optimization module is configured to construct a weighted information cross entropy target function, globally optimize the frequency domain signal parameters according to the weighted information cross entropy target function, and generate and transmit a mixed carrier signal.
9. An electronic device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor implements the steps of the method of any one of claims 1 to 7 when the computer program is executed.
10. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1 to 7.

Description

Multifunctional signal modeling method, system, equipment and medium Technical Field The application belongs to the technical field of wireless communication, and relates to a multifunctional signal modeling method, a system, equipment and a medium. Background Along with the deep fusion of 5G/6G and low-altitude economy, the integration of communication, perception, interference suppression and other multifunctional integration is realized in a single system, and the integration trend of improving the frequency spectrum efficiency and the system integration level is necessarily achieved. The unified bearing technology of the electromagnetic space multifunctional information aims at synchronously completing heterogeneous tasks such as data transmission, target detection and electronic countermeasure by sharing hardware, frequency spectrum and signal waveform, thereby remarkably reducing equipment complexity and deployment cost. However, the multi-function unified bearer faces fundamental challenges arising from the intrinsically conflicting functional requirements. For example, the function requirements contradict that the communication function needs to introduce randomness into the signal to carry information to ensure the data transmission capacity, the sensing function requires the signal to have certainty such as fixed frequency modulation characteristics to ensure the measurement accuracy of the target parameters, and the interference suppression function depends on the high uncertainty or deception of the signal to resist external interference. These mutually exclusive requirements form multidimensional conflicts in the time domain, the frequency domain and the information domain, which makes it difficult for a single waveform to meet the performance boundaries of all functions at the same time. In order to alleviate the contradiction, a cross-domain unified bearing frame is theoretically required to be constructed. As shown in fig. 1, an ideal integrated signal model essentially builds a synergistic mapping and regulation relationship among electromagnetic field, information domain and functional domain. Fig. 1 discloses that the multiplexing mechanism of electromagnetic field dimensions, the dynamic mapping mechanism of information and physical parameters and the cooperative regulation and control mechanism based on physical constraint are needed, and the multifunctional efficient unification can be realized in conflicting requirements. The prior art routes are mainly divided into two types, namely resource multiplexing-based and common waveform-based, but have obvious limitations. In the design based on resource multiplexing as shown in fig. 2, although the design realizes functional isolation through orthogonal coding, subspaces are difficult to be completely orthogonal due to electromagnetic field continuity and environmental scattering, inter-functional crosstalk is caused, and a static resource allocation mechanism of the design cannot realize depth coordination and dynamic adaptation as shown in fig. 3. The design based on the common waveform is limited by the inherent defect of the basic waveform, taking orthogonal frequency division multiplexing as an example, the fuzzy function formed by orthogonal frequency division multiplexing is shown in fig. 3, and has certain sensing potential, but in a high-speed moving scene, the Doppler shift can damage the orthogonality of subcarriers, so that the communication error rate is increased and the sensing precision is reduced, and the spectrum concentration characteristic is easily influenced by narrowband interference. Disclosure of Invention The application aims to provide a multifunctional signal modeling method, system, equipment and medium based on weighted information cross entropy global optimization, which are used for solving the interference problem of a dual-selectivity fading channel caused by multipath effect and Doppler frequency shift in a high-speed mobile environment. In a first aspect, the present application provides a method for modeling a multifunctional signal based on weighted information cross entropy global optimization, the method comprising: Generating binary keying information according to the function type of input data, and configuring weighted fractional Fourier transform parameters for the function type according to the binary keying information; performing weighted fractional Fourier transform on the function type to obtain frequency domain signal parameters; Constructing a weighted information cross entropy objective function, and performing global optimization on the frequency domain signal parameters according to the weighted information cross entropy objective function to generate and transmit a mixed carrier signal; And performing inverse weighted fractional Fourier transform on the mixed carrier signal according to the frame type of the mixed carrier signal to obtain a multifunctional signal. In one embodiment, th