Signal transmission optimization platform based on transmission array antenna

Abstract

The present application provides a signal transmission optimization platform based on a transmission array antenna, and relates to the field of signal transmission technology. The method includes: using the environmental spectrum information of the transmission array antenna as the input information of the spectrum identifier to obtain the spectrum identification result; issuing a signal transmission instruction; obtaining the target communication environment information; correcting the strategy fitness of the first working parameter strategy of the transmission array antenna to obtain the first target strategy fitness; if the fitness limit is not reached, obtaining the second working parameter strategy, and correcting and analyzing to obtain the second target strategy fitness; comparing and determining the optimal working parameter strategy, and performing signal transmission of the transmission array antenna. The present application can solve the technical problems of low signal transmission efficiency and unstable communication quality in the prior art of adjusting the working parameters of the transmission array antenna. Intelligent adjustment of the working parameters of the transmission array antenna is realized to achieve the technical effect of improving signal transmission efficiency and ensuring stable communication quality.

Description

Technical Field

[0001] The present application relates to the field of signal transmission technology, and in particular to a signal transmission optimization platform based on a transmission array antenna. Background Art

[0002] As a new type of antenna technology, transmission array antenna has attracted widespread attention for its flexibility and high efficiency. The transmission array antenna can dynamically adjust its working parameters according to different communication environments and requirements to achieve the best signal transmission effect. However, the traditional transmission array antenna working parameter adjustment method often relies on manual experience, which is not only time-consuming and labor-intensive, but also limited by the professional level of the operator. In addition, due to the complexity and variability of the wireless communication environment, the traditional adjustment method is difficult to adapt to various complex communication scenarios, resulting in low signal transmission efficiency and unstable communication quality.

[0003] In summary, the adjustment of working parameters of transmission array antennas in the prior art often relies on manual experience, which is difficult to adapt to various complex communication scenarios, and has technical problems such as low signal transmission efficiency and unstable communication quality. Summary of the invention

[0004] The purpose of this application is to provide a signal transmission optimization platform based on a transmission array antenna, so as to solve the technical problems in the prior art that the working parameter adjustment of the transmission array antenna relies on manual experience, is difficult to adapt to complex communication scenarios, has low signal transmission efficiency, and unstable communication quality.

[0005] In view of the above problems, the present application provides a signal transmission optimization platform based on a transmission array antenna.

[0006] In a first aspect, the present application provides a signal transmission optimization method based on a transmission array antenna, and the signal transmission optimization method based on the transmission array antenna is implemented by a signal transmission optimization platform based on the transmission array antenna, wherein the signal transmission optimization method based on the transmission array antenna includes: using the environmental spectrum information of the transmission array antenna as input information of a spectrum identifier to obtain a spectrum recognition result, wherein the spectrum identifier is an intelligent model trained based on the support vector machine principle; when the spectrum recognition result meets the signal transmission constraint, issuing a signal transmission instruction; reading a predetermined communication environment feature based on the signal transmission instruction, and collecting communication environment features of the transmission array antenna based on the predetermined communication environment feature to obtain target communication environment information; correcting the strategy fitness of a first working parameter strategy of the transmission array antenna in combination with the target communication environment information to obtain a first target strategy fitness; if the first target strategy fitness does not reach the fitness limit, obtaining a second working parameter strategy, and correcting and analyzing to obtain a second target strategy fitness of the second working parameter strategy; comparing the second target strategy fitness with the first target strategy fitness and determining an optimal working parameter strategy; under the signal transmission instruction, performing signal transmission of the transmission array antenna based on the optimal working parameter strategy.

[0007] In a second aspect, the present application further provides a signal transmission optimization platform based on a transmission array antenna, which is used to execute the signal transmission optimization method based on the transmission array antenna as described in the first aspect, wherein the signal transmission optimization platform based on the transmission array antenna includes: a spectrum recognition module, the spectrum recognition module is used to use the environmental spectrum information of the transmission array antenna as input information of a spectrum identifier to obtain a spectrum recognition result, and the spectrum identifier is an intelligent model trained based on the support vector machine principle; an instruction issuing module, the instruction issuing module is used to issue a signal transmission instruction when the spectrum recognition result meets the signal transmission constraint; an environment collection module, the environment collection module is used to read a predetermined communication environment feature based on the signal transmission instruction, and perform communication environment feature analysis on the transmission array antenna based on the predetermined communication environment feature. The invention relates to a method for collecting and collecting information to obtain target communication environment information; a fitness correction module, wherein the fitness correction module is used to perform strategy fitness correction on the first working parameter strategy of the transmission array antenna in combination with the target communication environment information to obtain the first target strategy fitness; a strategy adjustment module, wherein the strategy adjustment module is used to obtain the second working parameter strategy if the fitness of the first target strategy does not reach the fitness limit, and perform correction analysis to obtain the second target strategy fitness of the second working parameter strategy; a strategy comparison module, wherein the strategy comparison module is used to compare the fitness of the second target strategy with the fitness of the first target strategy and determine the optimal working parameter strategy; a transmission execution module, wherein the transmission execution module is used to perform signal transmission of the transmission array antenna based on the optimal working parameter strategy under the signal transmission instruction.

[0008] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0009] The spectrum recognition result of the environmental spectrum information of the transmission array antenna is obtained by a spectrum identifier trained based on the support vector machine principle. Then, when the spectrum recognition result meets the constraint conditions of signal transmission, a signal transmission instruction is issued. Then, the predetermined communication environment characteristics are read according to the signal transmission instruction, and these characteristics are used to collect the communication environment information of the transmission array antenna to obtain the target communication environment information. Thereafter, the target communication environment information is combined with the first working parameter strategy of the transmission array antenna to correct the strategy fitness and obtain the first target strategy fitness. If the first target strategy fitness does not reach the fitness limit, the system will obtain the second working parameter strategy and perform correction analysis on it to obtain the second target strategy fitness. Then, the first and second target strategy fitnesses are compared to determine the optimal working parameter strategy. Finally, under the guidance of the signal transmission instruction, the signal transmission of the transmission array antenna is carried out based on this optimal strategy. In general, the spectrum information is identified by the intelligent model, and the working parameters of the transmission array antenna are adjusted and optimized according to the communication environment characteristics, so as to finally achieve more efficient and accurate signal transmission. The technical goal of intelligent adjustment of the working parameters of the transmission array antenna is achieved, and the technical effect of improving signal transmission efficiency and ensuring stable communication quality is achieved.

[0010] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented according to the contents of the specification, and in order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are specifically cited below. It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present application, nor is it intended to limit the scope of the present application. Other features of the present application will become easy to understand through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] In order to more clearly illustrate the technical solutions in the present application or the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings in the following description are only exemplary, and for ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying any creative work.

[0012] Figure 1 A schematic diagram of the flow of the signal transmission optimization method based on the transmission array antenna of the present application;

[0013] Figure 2 This is a schematic diagram of the structure of the signal transmission optimization platform based on the transmission array antenna of this application.

[0014] Description of reference numerals:

[0015] Spectrum identification module 11, instruction issuing module 12, environment collection module 13, fitness correction module 14, strategy adjustment module 15, strategy comparison module 16, transmission execution module 17. DETAILED DESCRIPTION

[0016] This application provides a signal transmission optimization platform based on a transmission array antenna, which solves the technical problems in the prior art that the working parameter adjustment of the transmission array antenna often relies on manual experience, is difficult to adapt to various complex communication scenarios, and has low signal transmission efficiency and unstable communication quality. This application can realize the intelligent adjustment of the working parameters of the transmission array antenna, improve the signal transmission efficiency, and ensure stable communication quality.

[0017] Below, the technical solutions in the present application will be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all of the embodiments of the present application. It should be understood that the present application is not limited to the example embodiments described herein. Based on the embodiments of the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present application. It should also be noted that, for the convenience of description, only the parts related to the present application are shown in the accompanying drawings, rather than all of them.

[0018] Embodiment 1

[0019] Please refer to the attached Figure 1 The present application provides a signal transmission optimization method based on a transmission array antenna, wherein the method is applied to a signal transmission optimization platform based on a transmission array antenna, and the signal transmission optimization method based on a transmission array antenna specifically comprises the following steps:

[0020] Step 1: Using the environmental spectrum information of the transmission array antenna as input information of the spectrum identifier to obtain a spectrum recognition result. The spectrum identifier is an intelligent model trained based on the support vector machine principle.

[0021] Specifically, the core of this step is to use the environmental spectrum information of the transmission array antenna to perform spectrum recognition. By inputting the environmental spectrum information collected by the transmission array antenna into the spectrum identifier trained based on the support vector machine principle, the spectrum can be effectively identified and analyzed. First, the spectrum information in the environment of the transmission array antenna is collected. Then this information is transmitted to the spectrum identifier as input data. Next, the spectrum identifier processes and analyzes the input spectrum information to obtain the spectrum identifier output recognition result. Among them, the recognition result refers to whether it is idle under the current spectrum information. By using the environmental spectrum information collected by the transmission array antenna and the spectrum identifier trained based on the support vector machine principle, the accuracy and efficiency of spectrum recognition can be effectively improved, which is of great significance for the rational use and management of spectrum resources.

[0022] Step 2: When the spectrum identification result meets the signal transmission constraint, a signal transmission instruction is issued.

[0023] Specifically, the core of this step is to control signal transmission according to the spectrum identification results. Its main purpose is to ensure that signal transmission is only carried out under certain constraints, thereby optimizing the efficiency and reliability of signal transmission. In this way, signal transmission in an unsuitable spectrum environment can be avoided, reducing the possibility of signal interference and transmission errors.

[0024] Step three: Reading predetermined communication environment characteristics based on the signal transmission instruction, and collecting communication environment characteristics of the transmission array antenna based on the predetermined communication environment characteristics to obtain target communication environment information.

[0025] Specifically, the core of this step is to use signal transmission instructions to guide the feature collection of the transmission array antenna in a specific communication environment. Its main purpose is to obtain specific information of the target communication environment by reading the predetermined communication environment features and operating the transmission array antenna based on these features. First, the predetermined communication environment features are read based on the issued signal transmission instructions. These features may include key parameters such as the frequency range, signal propagation characteristics, and interference level of the communication environment. Then, the transmission array antenna is configured and adjusted according to these predetermined features to adapt to the specific communication environment. In addition, the collected data is processed and analyzed to extract specific information of the target communication environment. Finally, through this communication environment feature collection mechanism based on signal transmission instructions, accurate perception and adaptation of the target communication environment are achieved, which not only improves the performance of the communication platform in a complex environment, but also enhances the stability and reliability of the communication.

[0026] Step 4: Correct the strategy fitness of the first working parameter strategy of the transmission array antenna in combination with the target communication environment information to obtain a first target strategy fitness.

[0027] Specifically, the core of this step is to correct the working parameter strategy of the transmission array antenna according to the target communication environment information to optimize its strategy adaptability. Its main purpose is to ensure that the transmission array antenna can adjust its working parameters according to the actual communication environment, thereby improving communication efficiency and signal quality.

[0028] Specifically, the target communication environment information collected previously, including key factors such as the frequency response and interference level of the communication environment, is first used to evaluate the first working parameter strategy of the transmission array antenna. Next, the strategy is adjusted as necessary based on the evaluation results to improve its adaptability, including the optimization of parameters such as the antenna's operating frequency, transmit power, and receiving sensitivity. In addition, the changing trend of the communication environment is considered to predict possible changes in demand in the future and further optimize the strategy adaptability. Finally, the first target strategy adaptability is obtained through this correction process, that is, the optimal working parameter configuration of the transmission array antenna in the current communication environment. Finally, this strategy adaptability correction mechanism is used to achieve a high degree of matching between the transmission array antenna's operating parameters and the actual communication environment, thereby significantly improving the performance and efficiency of the communication system. This dynamic adjustment capability enables the communication system to better cope with complex changes in the communication environment and ensure the continuity and stability of communication.

[0029] Step 5: If the fitness of the first target strategy does not reach the fitness limit, obtain the second working parameter strategy, and perform correction analysis to obtain the second target strategy fitness of the second working parameter strategy.

[0030] Specifically, the core of this step is to iteratively correct the working parameter strategy of the transmission array antenna until the predetermined fitness limit is reached. Its main purpose is to ensure that the working parameters of the transmission array antenna can adapt to the complex communication environment to the greatest extent, thereby optimizing the communication performance. Through this continuous correction process, the scheme aims to improve the adaptability and robustness of the communication system.

[0031] Specifically, first evaluate whether the fitness of the first target strategy reaches the predetermined fitness limit. Among them, the fitness limit is a standard of system performance and is used to measure the effectiveness of the strategy. If the fitness of the first target strategy does not reach this limit, it means that the current strategy configuration is insufficient to meet the communication needs. At this time, the second working parameter strategy will be obtained, which may involve different configurations or adjustments to the antenna working parameters. Next, the second working parameter strategy is corrected and analyzed to evaluate its fitness in the current communication environment. This process is iterated multiple times according to the specific conditions of the communication environment, and the working parameter strategy is continuously adjusted and optimized until the optimal configuration is found. In this way, the strategy fitness can be gradually improved through continuous correction and optimization. Finally, fine adjustment of the operating parameters of the transmission array antenna is achieved to ensure the optimal performance of the communication system in various communication environments. This dynamic adaptability significantly improves the flexibility and reliability of the communication system, enabling it to effectively respond to complex communication challenges.

[0032] Step 6: Compare the fitness of the second target strategy with the fitness of the first target strategy and determine the optimal working parameter strategy.

[0033] Specifically, the core of this step is to compare the fitness of two different working parameter strategies and determine the optimal strategy. Its main purpose is to select the working parameter strategy that best suits the current communication environment by comparing the fitness of the first and second target strategies, thereby maximizing the performance and efficiency of the communication system. This comparison and selection process is a key step to ensure the adaptability and stability of the communication system. Specifically, the fitness of the second target strategy is first compared with the fitness of the first target strategy, which involves a detailed analysis of the performance of the two strategies in the same communication environment. Then, based on the comparison results, it is determined which strategy is better, and the strategy with higher fitness is selected as the optimal working parameter strategy. In addition, the long-term stability of the strategy and its versatility in different communication environments may also be considered. Finally, through this comparison and selection process, the working parameter strategy with the best performance in the current communication environment is determined. The performance of the communication system in a specific environment is improved, and the system's adaptability in the face of environmental changes is also enhanced. This dynamic adjustment and optimization mechanism ensures efficient operation and stable communication of the communication system.

[0034] Step 7: Under the signal transmission instruction, perform signal transmission of the transmission array antenna based on the optimal working parameter strategy.

[0035] Specifically, the core of this step is to use the determined optimal working parameter strategy to guide the signal transmission of the transmission array antenna. Its main purpose is to improve the efficiency and reliability of signal transmission by adopting optimized working parameters, ensure the optimal performance of the communication system in a specific communication environment, ensure the optimal performance of the communication system in various situations, and improve the reliability and efficiency of communication.

[0036] Further, it includes: forming an environmental spectrum training data set based on big data, and extracting a first training data set from the environmental spectrum training data set, wherein the first training data set includes first training spectrum information and a first training spectrum idle or not flag; based on the support vector machine principle, supervised learning and verification are performed on the first training spectrum information and the first training spectrum idle or not flag to obtain the spectrum identifier.

[0037] Specifically, big data is used to construct an environmental spectrum training dataset, and supervised learning is performed through the support vector machine principle to create a spectrum identifier that can identify the spectrum status. That is to say, by analyzing and learning a large amount of spectrum data, it is possible to effectively identify whether the spectrum is idle or not, thereby providing accurate spectrum information for signal transmission.

[0038] Specifically, first, an environmental spectrum training data set is established based on big data. This data set contains a large amount of spectrum information and whether these spectrums are idle or occupied. Then, a first training data set is extracted from this data set, which includes the first training spectrum information and the corresponding spectrum idle or not identification. Next, the first training data set is supervised learning using the support vector machine principle, where supervised learning is a machine learning method that trains the model with known input and output data so that it can predict new data. In addition, the learning results are tested to ensure the accuracy and reliability of the spectrum identifier. Finally, a spectrum identifier that can effectively identify the spectrum status is obtained through this training and testing process. This provides important spectrum information for the communication system, helps to optimize the use of spectrum resources, and improves communication efficiency and reliability.

[0039] Further, it includes: collecting frequency domain features of the environmental spectrum information to obtain first spectrum information; decomposing and analyzing the environmental frequency time series obtained by inverse Fourier transforming the environmental spectrum information to obtain component characteristic values ​​of the optimal component; using the component characteristic values ​​as second spectrum information, and combining with the first spectrum information to form the environmental spectrum information.

[0040] Specifically, the core of this step is to comprehensively construct environmental spectrum information through frequency domain feature collection and time series decomposition analysis. Its main purpose is to more accurately describe and identify the spectrum state in the communication environment by integrating the frequency domain and time domain features of the spectrum information, so as to provide detailed information support for signal transmission and spectrum management. Specifically, firstly, the frequency domain features of the environmental spectrum information are collected, which involves analyzing the frequency distribution, signal strength and other characteristics of the spectrum to obtain the first spectrum information. Then, the environmental spectrum information is processed by inverse Fourier transform and converted into the environmental frequency time series. Next, the time series is decomposed and analyzed to identify the optimal component, wherein the optimal component represents the key feature in the spectrum, and the component characteristic value of the optimal component is used as the second spectrum information. Finally, the first spectrum information and the second spectrum information are combined to form a comprehensive environmental spectrum information. In this way, the spectrum information not only contains frequency domain features, but also time domain features, which provides richer data support for spectrum analysis and decision-making. The comprehensive construction of environmental spectrum information is achieved, which helps to improve the accuracy and effectiveness of spectrum analysis and provides an important basis for spectrum management and optimization of communication systems.

[0041] Further, it includes: decomposing the environmental frequency time series to obtain multiple components; introducing a component weight evaluation function to evaluate the multiple components in turn to obtain multiple weights; descending the multiple components based on the multiple weights to obtain a component descending list; extracting the first component in the component descending list, and using the first component as the optimal component, wherein the expression of the component weight evaluation function is as follows:

[0042] ;in, Characterizes the first of the multiple components The weight of the components, Characterizing the The characteristic information of the component, The total characteristic information amount characterizing the environment frequency time series, Represents the total number of components, Characterizing the The correlation coefficient value of the component and the environmental frequency time series, and are the first coefficient and the second coefficient respectively, and .

[0043] Specifically, by decomposing the environmental frequency time series, the importance of each component is evaluated, and the optimal component is selected from it. Its main purpose is to improve the accuracy and efficiency of spectrum analysis by identifying and utilizing the most representative components in the spectrum time series, thereby optimizing the performance of the communication system. First, the environmental frequency time series is decomposed to obtain multiple components, which represent different frequency components in the time series data. Then a component weight evaluation function is introduced to evaluate the importance of each component. This evaluation function may consider factors such as the energy and frequency characteristics of the component. Next, multiple components are evaluated in turn to obtain their respective weights, and the components are arranged in descending order based on these weights to form a descending component list. The components in this list are arranged from high to low in importance. Finally, the first component in the descending component list, that is, the component with the highest weight, is extracted and used as the optimal component. Among them, the expression of the component weight evaluation function is as follows:

[0044] ;in, Characterizes the first of the multiple components The weight of the components, Characterizing the The characteristic information of the component, The total characteristic information amount characterizing the environment frequency time series, Represents the total number of components, Characterizing the The correlation coefficient value of the component and the environmental frequency time series, and points are the first coefficient and the second coefficient respectively, and This optimal component represents the most critical feature in the ambient frequency time series, and the identification and utilization of the most representative component in the ambient frequency time series is realized.

[0045] Further, it includes: reading a predetermined working characteristic, the predetermined working characteristic including a first working characteristic identified by a first characteristic threshold; randomly obtaining a first parameter of the first working characteristic within the first characteristic threshold, and forming the first working parameter strategy based on the first parameter; wherein the predetermined working characteristic includes a unit phase, a unit amplitude, an operating frequency, a polarization state, and an impedance matching.

[0046] Specifically, the first working parameter strategy is created according to the predetermined working characteristics, and its main purpose is to construct a working parameter strategy suitable for the current communication environment by randomly selecting specific working characteristic parameters, so as to optimize the performance of the transmission array antenna. First, the predetermined working characteristics are read, and these characteristics include key parameters such as unit phase, unit amplitude, working frequency, polarization state and impedance matching. These parameters jointly determine the working performance of the transmission array antenna. Then, the first parameter of the first working characteristic is randomly obtained in the first characteristic threshold. For example, a specific phase value or amplitude value is randomly selected. Next, the first working parameter strategy is formed based on these randomly obtained first parameters. This strategy will guide the working mode of the transmission array antenna in a specific communication environment. In addition, since the parameters are randomly selected, this strategy construction method increases the diversity and adaptability of the strategy. Finally, through this parameter selection and strategy construction process based on the predetermined working characteristics, an initial working parameter configuration is provided for the transmission array antenna. Through this random selection and strategy construction method, the technical solution realizes the flexible configuration of the working parameters of the transmission array antenna. This provides the communication system with the ability to adapt to different communication environments and enhances the stability and reliability of communication.

[0047] Further, it includes: simulating the first working parameter strategy to obtain first simulation information, the first simulation information includes a first communication quality and a first communication efficiency; obtaining a first strategy fitness by weighted normalization of the first communication quality and the first communication efficiency; using the environmental impact index obtained by analyzing the predetermined communication environment characteristics as a fitness correction coefficient, and weighting the first strategy fitness to obtain the first target strategy fitness.

[0048] Further, it includes: the predetermined communication environment characteristics include channel conditions and interference levels.

[0049] Specifically, the fitness of the first working parameter strategy is evaluated through simulation experiments, and corrections are made in combination with the characteristics of the communication environment to obtain a more accurate target strategy fitness. Its main purpose is to optimize the working parameter strategy of the transmission array antenna by comprehensively considering environmental factors such as communication quality and communication efficiency, as well as channel conditions and interference levels, so as to improve the performance of the communication system in a specific environment.

[0050] First, the first working parameter strategy is simulated to simulate its performance in an actual communication environment. The simulation results include two key indicators: the first communication quality and the first communication efficiency. Then, these two indicators are weighted and normalized to obtain the first strategy fitness. Weighted normalization helps to convert indicators of different dimensions into comparable fitness values. Next, the predetermined communication environment characteristics are analyzed, including channel conditions and interference levels, which have an important impact on the performance of the communication system. In addition, the environmental impact index obtained by the analysis is used as a fitness correction coefficient to weight the first strategy fitness to obtain the first target strategy fitness. In this way, the evaluation of strategy fitness is more comprehensive, taking into account the actual impact of the communication environment. A detailed evaluation and optimization of the working parameter strategy of the transmission array antenna is achieved.

[0051] In summary, the signal transmission optimization method based on transmission array antenna provided in this application has the following technical effects:

[0052] The spectrum recognition result of the environmental spectrum information of the transmission array antenna is obtained by a spectrum identifier trained based on the support vector machine principle. Then, when the spectrum recognition result meets the constraint conditions of signal transmission, a signal transmission instruction is issued. Then, the predetermined communication environment characteristics are read according to the signal transmission instruction, and these characteristics are used to collect the communication environment information of the transmission array antenna to obtain the target communication environment information. Thereafter, the target communication environment information is combined with the first working parameter strategy of the transmission array antenna to correct the strategy fitness and obtain the first target strategy fitness. If the first target strategy fitness does not reach the fitness limit, the system will obtain the second working parameter strategy and perform correction analysis on it to obtain the second target strategy fitness. Then, the first and second target strategy fitnesses are compared to determine the optimal working parameter strategy. Finally, under the guidance of the signal transmission instruction, the signal transmission of the transmission array antenna is carried out based on this optimal strategy. In general, the spectrum information is identified by the intelligent model, and the working parameters of the transmission array antenna are adjusted and optimized according to the communication environment characteristics, so as to finally achieve more efficient and accurate signal transmission. The technical goal of intelligent adjustment of the working parameters of the transmission array antenna is achieved, and the technical effect of improving signal transmission efficiency and ensuring stable communication quality is achieved.

[0053] Embodiment 2

[0054] Based on the same inventive concept as the signal transmission optimization method based on the transmission array antenna in the aforementioned embodiment, the present application also provides a signal transmission optimization platform based on the transmission array antenna, see the attached Figure 2 , the signal transmission optimization platform based on transmission array antenna includes:

[0055] A spectrum identification module 11, the spectrum identification module 11 is used to use the environmental spectrum information of the transmission array antenna as the input information of the spectrum identifier to obtain the spectrum identification result, and the spectrum identifier is an intelligent model trained based on the support vector machine principle. An instruction issuing module 12, the instruction issuing module 12 is used to issue a signal transmission instruction when the spectrum identification result meets the signal transmission constraint. An environment collection module 13, the environment collection module 13 is used to read the predetermined communication environment characteristics based on the signal transmission instruction, and collect the communication environment characteristics of the transmission array antenna based on the predetermined communication environment characteristics to obtain the target communication environment information. A fitness correction module 14, the fitness correction module 14 is used to perform a strategy fitness correction on the first working parameter strategy of the transmission array antenna in combination with the target communication environment information to obtain the first target strategy fitness. A strategy adjustment module 15, the strategy adjustment module 15 is used to obtain the second working parameter strategy if the first target strategy fitness does not reach the fitness limit, and correct and analyze to obtain the second target strategy fitness of the second working parameter strategy. A strategy comparison module 16 is used to compare the fitness of the second target strategy with the fitness of the first target strategy and determine the optimal working parameter strategy. A transmission execution module 17 is used to perform signal transmission of the transmission array antenna based on the optimal working parameter strategy under the signal transmission instruction.

[0056] Furthermore, the spectrum identification module 11 in the signal transmission optimization platform based on the transmission array antenna is also used to: establish an environmental spectrum training data set based on big data, and extract a first training data set from the environmental spectrum training data set, wherein the first training data set includes first training spectrum information and a first training spectrum idle or not flag; perform supervised learning and verification on the first training spectrum information and the first training spectrum idle or not flag based on the support vector machine principle to obtain the spectrum identifier.

[0057] Furthermore, the spectrum identification module 11 in the signal transmission optimization platform based on the transmission array antenna is also used to: collect frequency domain features of the environmental spectrum information to obtain first spectrum information; decompose and analyze the environmental frequency time series obtained by inverse Fourier transforming the environmental spectrum information to obtain component eigenvalues ​​of the optimal component; use the component eigenvalues ​​as second spectrum information, and combine them with the first spectrum information to form the environmental spectrum information.

[0058] Furthermore, the spectrum identification module 11 in the signal transmission optimization platform based on the transmission array antenna is also used to: decompose the environmental frequency time series to obtain multiple components; introduce a component weight evaluation function to evaluate the multiple components in turn to obtain multiple weights; descend the multiple components based on the multiple weights to obtain a component descending list; extract the first component in the component descending list, and use the first component as the optimal component, wherein the expression of the component weight evaluation function is as follows:

[0059] ;in, Characterizes the first of the multiple components The weight of the components, Characterizing the The characteristic information of the component, The total characteristic information amount characterizing the environment frequency time series, Represents the total number of components, Characterizing the The correlation coefficient value of the component and the environmental frequency time series, and are the first coefficient and the second coefficient respectively, and .

[0060] Furthermore, the fitness correction module 14 in the signal transmission optimization platform based on the transmission array antenna is also used to: read predetermined working characteristics, the predetermined working characteristics including a first working characteristic identified by a first characteristic threshold; randomly obtain a first parameter of the first working characteristic within the first characteristic threshold, and form the first working parameter strategy based on the first parameter; wherein the predetermined working characteristics include unit phase, unit amplitude, operating frequency, polarization state and impedance matching.

[0061] Furthermore, the fitness correction module 14 in the signal transmission optimization platform based on the transmission array antenna is also used to: simulate the first working parameter strategy to obtain first simulation information, the first simulation information including a first communication quality and a first communication efficiency; obtain a first strategy fitness by weighted normalization of the first communication quality and the first communication efficiency; use the environmental impact index obtained by analyzing the predetermined communication environment characteristics as a fitness correction coefficient, and weight the first strategy fitness to obtain the first target strategy fitness.

[0062] Furthermore, the fitness correction module 14 in the signal transmission optimization platform based on the transmission array antenna is also used for: the predetermined communication environment characteristics include channel conditions and interference levels.

[0063] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. Figure 1 The signal transmission optimization method based on the transmission array antenna and the specific examples in the first embodiment are also applicable to the signal transmission optimization platform based on the transmission array antenna in this embodiment. Through the above detailed description of the signal transmission optimization method based on the transmission array antenna, those skilled in the art can clearly understand the signal transmission optimization platform based on the transmission array antenna in this embodiment, so for the sake of brevity of the specification, it will not be described in detail here. For the system disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method part description.

[0064] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present application. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to the embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

[0065] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application belong to the scope of the present application and its equivalent technology, the present application is also intended to include these modifications and variations.

Claims

1. A signal transmission optimization method based on a transmission array antenna, characterized in that: include: The environmental spectrum information of the transmission array antenna is used as input information of the spectrum identifier to obtain a spectrum recognition result, wherein the spectrum identifier is an intelligent model trained based on the support vector machine principle; When the spectrum identification result meets the signal transmission constraint, issuing a signal transmission instruction; Reading a predetermined communication environment feature based on the signal transmission instruction, and collecting communication environment features of the transmission array antenna based on the predetermined communication environment feature to obtain target communication environment information; performing strategy fitness correction on the first working parameter strategy of the transmission array antenna in combination with the target communication environment information to obtain a first target strategy fitness; If the fitness of the first target strategy does not reach the fitness limit, obtaining a second working parameter strategy, and correcting and analyzing to obtain a second target strategy fitness of the second working parameter strategy; Comparing the fitness of the second target strategy with the fitness of the first target strategy and determining an optimal working parameter strategy; Under the signal transmission instruction, performing signal transmission of the transmission array antenna based on the optimal working parameter strategy; The method further comprises: Collecting frequency domain features of the environmental spectrum information to obtain first spectrum information; Decomposing and analyzing the environmental frequency time series obtained by inverse Fourier transforming the environmental spectrum information to obtain component eigenvalues ​​of the optimal components; Using the component characteristic value as the second spectrum information, and combining it with the first spectrum information to form the environment spectrum information; The method further comprises: Decomposing the environmental frequency time series to obtain multiple components; Introducing a component weight evaluation function to sequentially evaluate the multiple components to obtain multiple weights; Based on the multiple weights, the multiple components are sorted in descending order to obtain a descending component list; Extract the first component in the descending list of components, and use the first component as the optimal component, wherein the expression of the component weight evaluation function is as follows: ； in, Characterizes the first of the multiple components The weight of the components, Characterizing the The characteristic information of the component, The total characteristic information amount characterizing the environment frequency time series, Represents the total number of components, Characterizing the The correlation coefficient value of the component and the environmental frequency time series, and are the first coefficient and the second coefficient respectively, and .

2. The signal transmission optimization method based on transmission array antenna according to claim 1, characterized in that: include: An environmental spectrum training data set is formed based on big data, and a first training data set is extracted from the environmental spectrum training data set, wherein the first training data set includes first training spectrum information and an indication of whether the first training spectrum is idle or not; The spectrum identifier is obtained by performing supervised learning and verification on the first training spectrum information and the identifier of whether the first training spectrum is idle or not based on the support vector machine principle.

3. The signal transmission optimization method based on transmission array antenna according to claim 1, characterized in that: include: Reading a predetermined operating characteristic, the predetermined operating characteristic comprising a first operating characteristic having an identifier of a first characteristic threshold; randomly acquiring a first parameter of the first operating feature within the first feature threshold, and forming the first operating parameter strategy based on the first parameter; The predetermined operating characteristics include unit phase, unit amplitude, operating frequency, polarization state and impedance matching.

4. The signal transmission optimization method based on transmission array antenna according to claim 1, characterized in that: include: Simulating the first working parameter strategy to obtain first simulation information, wherein the first simulation information includes a first communication quality and a first communication efficiency; Obtaining a first strategy fitness by weighting and normalizing the first communication quality and the first communication efficiency; The environmental impact index obtained by analyzing the predetermined communication environment characteristics is used as a fitness correction coefficient, and the first strategy fitness is weighted to obtain the first target strategy fitness.

5. The signal transmission optimization method based on transmission array antenna according to claim 4 is characterized in that: The predetermined communication environment characteristics include channel conditions and interference levels.

6. A signal transmission optimization platform based on transmission array antenna, characterized in that: The signal transmission optimization platform based on the transmission array antenna is used to perform the signal transmission optimization method based on the transmission array antenna according to any one of claims 1 to 5, comprising: A spectrum recognition module, wherein the spectrum recognition module is used to use the environmental spectrum information of the transmission array antenna as input information of a spectrum identifier to obtain a spectrum recognition result. The spectrum identifier is an intelligent model trained based on the support vector machine principle; An instruction issuing module, the instruction issuing module being used to issue a signal transmission instruction when the spectrum identification result meets the signal transmission constraint; An environment collection module, the environment collection module is used to read a predetermined communication environment feature based on the signal transmission instruction, and collect communication environment features of the transmission array antenna based on the predetermined communication environment feature to obtain target communication environment information; A fitness correction module, the fitness correction module is used to perform strategy fitness correction on the first working parameter strategy of the transmission array antenna in combination with the target communication environment information to obtain a first target strategy fitness; A strategy adjustment module, wherein if the first target strategy fitness does not reach the fitness limit, the strategy adjustment module is used to obtain a second working parameter strategy, and correct and analyze to obtain a second target strategy fitness of the second working parameter strategy; A strategy comparison module, the strategy comparison module is used to compare the fitness of the second target strategy with the fitness of the first target strategy and determine the optimal working parameter strategy; A transmission execution module, wherein the transmission execution module is used to perform signal transmission of the transmission array antenna based on the optimal working parameter strategy under the signal transmission instruction.

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