Communication module data transmission method, electronic equipment and storage medium

Abstract

The invention discloses a communication module data transmission method, electronic equipment and a storage medium. The communication module data transmission method mainly comprises the following steps: determining a target communication parameter of a communication module according to the electromagnetic interference intensity of an electromagnetic interference signal in spectrum data, a preset optimization strategy and a preset constraint condition; and controlling the communication module to perform data transmission according to the target communication parameters, the target communication parameters including a target spread spectrum factor, a target coding rate and target channel configuration, and the spectrum data being spectrum data of the communication module during data transmission. According to the technical scheme provided by the embodiment of the invention, the communication parameters of the communication module are adaptively adjusted according to the electromagnetic interference intensity of the electromagnetic interference signal in the frequency spectrum data of the communication module during data transmission, so that the anti-interference purpose is achieved, and the data transmission reliability of the communication module is improved.

Description

Technical Field

[0001] The present application relates to the field of mobile communication technology, and in particular to a communication module data transmission method, electronic equipment and storage medium. Background Art

[0002] In modern digital substations, communication modules are crucial for equipment status monitoring. These modules are widely used on key substation equipment such as transformers, circuit breakers, and switchgear. They collect critical operational data such as oil levels, bushing status, and partial discharge, providing data support for stable grid operation. However, due to the presence of numerous high-voltage electrical equipment, substations are typically subject to strong electromagnetic interference (EMI). This wide-spectrum EMI encompasses multiple frequency bands, from power frequency harmonics to high-frequency noise, spanning nearly the entire electromagnetic spectrum, posing a serious threat to the reliability of data transmission from communication modules. Summary of the Invention

[0003] An embodiment of the present application provides a communication module data transmission method, electronic device, and storage medium, which avoids the threat posed by electromagnetic interference to the reliability of data transmission of the communication module by electromagnetic interference by adaptively adjusting communication parameters according to the electromagnetic interference intensity of the electromagnetic interference signal in the spectrum data of the communication module during data transmission.

[0004] According to the first aspect of the present application, an embodiment of the present application provides a communication module data transmission method, including: determining the target communication parameters of the communication module based on the electromagnetic interference intensity of the electromagnetic interference signal in the spectrum data, a preset optimization strategy and preset constraints; according to the target communication parameters, controlling the communication module to perform data transmission; wherein the target communication parameters include: a target spreading factor, a target coding rate and a target channel configuration; the spectrum data is the spectrum data of the communication module during data transmission.

[0005] In some embodiments, the preset optimization strategy includes at least one of the following: when the electromagnetic interference intensity is greater than or equal to a first preset intensity threshold, adjusting the communication parameters of the communication module to adjust the data transmission accuracy of the communication module; when the electromagnetic interference intensity increases, adjusting the communication parameters of the communication module to adjust the data transmission accuracy of the communication module; when the electromagnetic interference intensity is less than a second preset intensity threshold, adjusting the communication parameters of the communication module to adjust the data transmission rate of the communication module; when the electromagnetic interference intensity decreases, adjusting the communication parameters of the communication module to adjust the data transmission rate of the communication module; wherein the communication parameters include: spreading factor, coding rate and channel configuration.

[0006] In some embodiments, the preset constraints include: parameter value constraints and data rate constraints; wherein the parameter value constraints include at least one of the following: the target spreading factor is within a first preset value range; the target coding rate is within a second preset value range; the target channel configuration is within a third preset value range; the data rate constraints include: a preset data transmission rate is greater than or equal to a preset rate threshold; the preset data transmission rate is related to the target spreading factor and the target coding rate.

[0007] In some embodiments, the target communication parameters of the communication module are determined based on the electromagnetic interference intensity of the electromagnetic interference signal in the spectrum data, a preset optimization strategy, and preset constraints, including: determining the predicted interference intensity of the electromagnetic interference intensity at the next moment based on the Kalman filtering algorithm; determining the target communication parameters of the communication module based on the predicted interference intensity, the preset optimization strategy, and the preset constraints.

[0008] In some embodiments, the Kalman filter algorithm is based on determining the predicted interference intensity of the electromagnetic interference intensity at the next moment, including: obtaining historical spectrum data of the communication module during data transmission within a preset time; obtaining a historical interference signal based on the historical spectrum data; determining the historical interference intensity of the historical interference signal based on the historical interference signal; and inputting the historical interference intensity into the Kalman filter algorithm to determine the predicted interference intensity.

[0009] In some embodiments, the method further includes: generating a communication parameter lookup table according to the preset optimization strategy and the preset constraint conditions; wherein the communication parameter lookup table is related to the electromagnetic interference intensity and the communication parameters of the communication module.

[0010] In some embodiments, determining the target communication parameters of the communication module based on the predicted interference intensity, the preset optimization strategy and the preset constraints includes: determining the target communication parameters corresponding to the predicted interference intensity based on the communication parameter lookup table.

[0011] In some embodiments, determining the target communication parameters of the communication module based on the predicted interference intensity, the preset optimization strategy and the preset constraints includes: obtaining the current electromagnetic interference intensity; obtaining the difference between the predicted interference intensity and the current electromagnetic interference intensity; determining the transition communication parameters of the communication module based on the difference, the preset optimization strategy and the preset constraints; and inputting the transition communication parameters into a preset dynamic adaptive optimization model to obtain the target communication parameters.

[0012] In some embodiments, the preset dynamic adaptive optimization model is: Wherein, R(SF[k],CR[k],Channel[k]|I[k]]) is the packet reception success rate at the kth moment; C(SF[k],CR[k],Channel[k],SF[k-1],CR[k-1],Channel[k-1]) is the parameter switching cost at the kth moment; λ is the balancing weight coefficient used to balance the packet reception success rate and the parameter switching cost.

[0013] In some embodiments, the transition communication parameters of the communication module are determined based on the difference, the preset optimization strategy and the preset constraints, including: if the difference is greater than or equal to 0, adjusting the communication parameters of the communication module multiple times according to the preset optimization strategy and the preset constraints, and determining multiple first transition communication parameters to adjust the data transmission accuracy of the communication module; if the difference is less than 0, adjusting the communication parameters of the communication module multiple times according to the preset optimization strategy and the preset constraints, and determining multiple second transition communication parameters to adjust the data transmission rate of the communication module.

[0014] In some embodiments, inputting the transition communication parameters into a preset dynamic adaptive optimization model to obtain the target communication parameters includes: inputting multiple first transition communication parameters into the preset dynamic adaptive optimization model to determine multiple first objective function values; obtaining the maximum value of the first objective function, the maximum value of the first objective function being the maximum value among the multiple first objective function values; and determining the target communication parameter to be the first transition communication parameter corresponding to the maximum value of the first objective function.

[0015] In some embodiments, inputting the transition communication parameter into a preset dynamic adaptive optimization model to obtain the target communication parameter includes: inputting multiple second transition communication parameters into the preset dynamic adaptive optimization model to determine multiple second objective function values; obtaining the maximum value of the second objective function, the maximum value of the second objective function being the maximum value among the multiple second objective function values; and determining the target communication parameter as the second transition communication parameter corresponding to the maximum value of the second objective function.

[0016] In some embodiments, the method further comprises:

[0017] Acquire the spectrum data; acquire the electromagnetic interference signal according to the spectrum data; and determine the electromagnetic interference intensity of the electromagnetic interference signal according to the electromagnetic interference signal.

[0018] According to the second aspect of the present application, an embodiment of the present application also provides an electronic device, wherein a computer program or instruction is stored in the memory, and when the computer program or instruction is executed by the processor, the processor executes the steps in any one of the communication module data transmission methods provided in the embodiment of the present application.

[0019] According to the third aspect of the present application, an embodiment of the present application also provides a computer program product, including a computer program or instructions, which, when executed by a processor, implements the steps in any communication module data transmission method provided in the embodiment of the present application.

[0020] According to the fourth aspect of the present application, an embodiment of the present application also provides a computer-readable storage medium on which a computer program or instruction is stored, including a computer program or instruction, which, when executed by a processor, implements the steps in any communication module data transmission method provided in the embodiment of the present application.

[0021] The present application discloses a communication module data transmission method, electronic device and storage medium. The communication module data transmission method mainly includes: determining the target communication parameters of the communication module according to the electromagnetic interference intensity of the electromagnetic interference signal in the spectrum data, a preset optimization strategy and preset constraints; controlling the communication module to perform data transmission according to the target communication parameters, wherein the target communication parameters include: a target spreading factor, a target coding rate and a target channel configuration, and the spectrum data is the spectrum data of the communication module during data transmission. The technical solution provided in the embodiment of the present application adaptively adjusts the communication parameters of the communication module according to the electromagnetic interference intensity of the electromagnetic interference signal in the spectrum data of the communication module during data transmission, thereby achieving the purpose of anti-interference and improving the reliability of data transmission of the communication module. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative work.

[0023] Figure 1 A flow chart of a communication module data transmission method provided in an embodiment of the present application;

[0024] Figure 2 A flow chart of another communication module data transmission method provided in an embodiment of the present application;

[0025] Figure 3 A flow chart of another communication module data transmission method provided in an embodiment of the present application;

[0026] Figure 4 A flow chart of another communication module data transmission method provided in an embodiment of the present application;

[0027] Figure 5 This is a schematic structural diagram of an electronic device provided in some embodiments of the present application. DETAILED DESCRIPTION

[0028] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without making creative efforts shall fall within the scope of protection of the present invention.

[0029] In the following description, the specific embodiments of the present invention will be described with reference to steps and symbols performed by one or more computers, unless otherwise specified. Therefore, these steps and operations will be mentioned several times as being performed by a computer, and the computer execution referred to herein includes the operation of a computer processing unit by electronic signals representing data in a structured form. This operation converts the data or maintains it at a location in the computer's memory system, which can be reconfigured or otherwise change the operation of the computer in a manner familiar to testers in the field. The data structure in which the data is maintained is a physical location in the memory, which has specific characteristics defined by the data format. However, the principles of the present invention are described in the above text, which does not represent a limitation, and testers in the field will understand that the various steps and operations described below can also be implemented in hardware.

[0030] As used herein, the terms "module" or "unit" may be considered software objects executed on the computing system. The various components, modules, engines, and services described herein may be considered implementation objects on the computing system. While the devices and methods described herein are preferably implemented in software, they may also be implemented in hardware and remain within the scope of protection of the present invention.

[0031] It will be understood by those skilled in the art that, unless expressly stated otherwise, the singular forms "a", "an", "said" and "the" used herein may also include plural forms. It should be further understood that the term "comprising" used in the description of the present invention refers to the presence of the features, integers, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or groups thereof. It should be understood that when an element is "connected" or "coupled" to another element, it may be directly connected or coupled to the other element, or there may be intermediate elements. In addition, "connected" or "coupled" as used herein may include wireless connections or wireless couplings. The term "and / or" used herein includes all or any units and all combinations of one or more associated listed items.

[0032] Figure 1 This is a flow chart of a communication module data transmission method provided in an embodiment of the present application. Figure 1 The communication module data transmission method includes the following steps (step S100 and step S200):

[0033] Step S100: determining target communication parameters of the communication module based on the electromagnetic interference intensity of the electromagnetic interference signal in the spectrum data, a preset optimization strategy, and preset constraints; wherein the spectrum data is spectrum data of the communication module during data transmission;

[0034] Step S200: Controlling the communication module to perform data transmission according to target communication parameters; wherein the target communication parameters include: target spreading factor, target coding rate and target channel configuration.

[0035] In step S100, according to the electromagnetic interference intensity of the electromagnetic interference signal, in combination with the preset optimization strategy and the preset constraints, the communication parameters of the communication module are adjusted and optimized to obtain the optimal communication parameter combination as the target communication parameter to achieve the best data transmission effect. It should be understood that the electromagnetic interference intensity will affect the communication quality (such as bit error rate, transmission rate, etc.) of the communication module. In order to cope with the impact of the electromagnetic interference intensity on the communication quality, the communication parameters can be optimized and adjusted in combination with the preset optimization strategy and the preset constraints. For example, the preset optimization strategy can be to ensure the maximum transmission rate, minimum power consumption or maximization of anti-interference capability of the communication module data. For example, the preset constraints can be to ensure the maximum allowable bit error rate, maximum delay or minimum data transmission rate when the communication module transmits data. In the specific use process, the preset optimization strategy and the preset constraints can be reasonably selected according to the actual use scenario of the communication module to ensure that the communication module can meet the use requirements in the application scenario, and this application is not limited to this.

[0036] It should be understood that the electromagnetic interference intensity can be directly extracted from the electromagnetic interference signal in the spectrum data during the current data transmission process of the communication module and its intensity calculated in real time; it can also be combined with historical data to track and analyze the data transmission spectrum data of the communication module in different time periods over a period of time to evaluate its electromagnetic interference characteristics or trends; it can also be based on current and historical spectrum data and use an algorithm to predict the electromagnetic interference intensity at the next moment or in the future. In actual use, it can be selected as needed, as long as the communication module can obtain the optimal communication parameter combination that meets the current application scenario based on the electromagnetic interference intensity, combined with the preset optimization strategy and preset constraints. This application does not limit this.

[0037] In step S200, based on the target communication parameters determined in step S100, the communication parameters of the communication module are adjusted to the target communication parameters, and the target communication parameters are used to guide the communication module to perform data transmission. It should be understood that as the electromagnetic interference intensity changes over time, the determined target communication parameters will also change. The communication module will adaptively adjust the communication parameters to control the communication module's data transmission and achieve the purpose of anti-interference.

[0038] To sum up, the communication module data transmission method provided in the embodiment of the present application adaptively adjusts the communication parameters of the communication module according to the electromagnetic interference intensity of the electromagnetic interference signal in the spectrum data of the communication module during data transmission, thereby achieving the purpose of anti-interference, improving the reliability of data transmission of the communication module, and solving the problem that the communication module is easily affected by electromagnetic interference during data transmission, thereby reducing the reliability of data transmission.

[0039] In some embodiments, the above method further includes the following steps (steps S097 to S099):

[0040] Step S097: Acquire spectrum data;

[0041] Step S098: Acquire an electromagnetic interference signal according to the spectrum data;

[0042] Step S099: determining the electromagnetic interference intensity of the electromagnetic interference signal according to the electromagnetic interference signal.

[0043] In step S097 , spectrum data may be acquired through a spectrum analyzer, which may be configured to monitor electromagnetic spectrum information within a working frequency band of the communication module.

[0044] In step S098, the electromagnetic interference signal can be extracted from the spectrum data using filtering techniques, signal separation algorithms, and other methods. For example, the iterative adjustment function of the adaptive filter can be used to distinguish the electromagnetic interference signal from other useful signals in the spectrum data, thereby effectively extracting the electromagnetic interference signal.

[0045] In step S099, based on the extracted electromagnetic interference signal, its electromagnetic interference intensity is further calculated to quantify the interference degree, providing reliable data support for subsequent communication parameter optimization. In actual operation, the electromagnetic interference intensity can be calculated using a variety of methods. For example, the power spectral density (PSD), root mean square (RMS) or peak value of the electromagnetic interference signal are calculated to quantify the electromagnetic interference intensity of the electromagnetic interference signal.

[0046] To improve the accuracy of EMI intensity calculations, a method for averaging multiple measurements can be used. Specifically, multiple sets of spectrum data are collected continuously over a short period of time. EMI signal extraction and intensity calculation are performed on each set of spectrum data. The resulting EMI intensity values ​​are then statistically averaged to eliminate the effects of random noise and instantaneous fluctuations, resulting in a more reliable and accurate EMI intensity estimate.

[0047] The above steps not only effectively improve the accuracy of electromagnetic interference intensity identification but also provide a more reliable data foundation for subsequent optimization of communication parameters based on interference intensity. By reducing measurement errors and minimizing the impact of environmental factors on the results, the resulting electromagnetic interference intensity values ​​are more representative and stable, laying a solid foundation for optimizing the performance of communication modules and enhancing their anti-interference capabilities.

[0048] In some embodiments, the preset optimization strategy includes at least one of the following:

[0049] Strategy A: When the electromagnetic interference intensity is greater than or equal to a first preset intensity threshold, adjust the communication parameters of the communication module to adjust the data transmission accuracy of the communication module;

[0050] Strategy B: As the electromagnetic interference intensity increases, adjust the communication parameters of the communication module to adjust the data transmission accuracy of the communication module;

[0051] Strategy C: When the electromagnetic interference intensity is less than a second preset intensity threshold, adjusting the communication parameters of the communication module to adjust the data transmission rate of the communication module;

[0052] Strategy D: When the electromagnetic interference intensity decreases, adjust the communication parameters of the communication module to adjust the data transmission rate of the communication module; the communication parameters include: spreading factor, coding rate and channel configuration.

[0053] It should be understood that in high electromagnetic interference environments, priority is given to improving data transmission accuracy, while in low electromagnetic interference environments, priority is given to improving data transmission rate. The communication parameters of the communication module are adjusted based on this optimization goal. Communication parameters include spreading factor (SF), coding rate (CR), and channel configuration (Channel Configuration). Different communication parameters have different effects on data transmission. For example, SF determines the signal's spreading gain and anti-interference capability. A higher SF value can increase anti-interference capability, but will also reduce the data transmission rate accordingly. A higher CR provides better error correction capability, but will also occupy more bandwidth and reduce the effective data transmission rate. Rational allocation of channel resources can improve overall efficiency. Working channels are different channels within the operating frequency band allowed by the communication module. Channels with less interference can be selected for communication, avoiding frequency bands with more severe interference. When the interference environment changes, that is, when the electromagnetic interference intensity changes, the channel quality can be re-evaluated and switched to a better channel.

[0054] The communication parameter combination is adjusted according to the preset optimization strategy to meet the data transmission requirements of the communication module. Specifically, if the electromagnetic interference intensity exceeds the first preset intensity threshold or shows an increasing trend (strategies A and B), the communication parameters can be adjusted with the improvement of data transmission accuracy as the optimization goal. Exemplarily, the spreading factor is increased to improve the anti-interference ability and receiving sensitivity of the signal, but at the same time the data transmission rate is reduced. Exemplarily, the coding rate is increased, the forward error correction redundancy is increased, and the reliability of data transmission is improved, but at the same time the data transmission rate is reduced. If the electromagnetic interference intensity is lower than the second preset intensity threshold or shows a weakening trend (strategies C and D), the communication parameters can be adjusted with the improvement of data transmission rate as the optimization goal. Exemplarily, the spreading factor is reduced and / or the coding rate is reduced to increase the data transmission rate.

[0055] It should be understood that the first preset intensity threshold and the second preset intensity threshold may be the same or different, and the first preset intensity threshold and the second preset intensity threshold may be set according to actual needs, which is not limited in this application.

[0056] Exemplarily, a data transmission accuracy threshold and a data transmission rate threshold can also be preset respectively. In the case of strategies A and B, the communication parameters of the communication module are adjusted to increase the data transmission accuracy from below the threshold to above the threshold; in the case of strategies C and D, the communication parameters of the communication module are adjusted to increase the data transmission rate from below the threshold to above the threshold.

[0057] The embodiments of the present application adjust the communication parameters of the communication module appropriately according to the magnitude of the electromagnetic interference intensity or the law of its dynamic change, with the goal of ensuring data transmission accuracy or data transmission rate, to achieve an optimal balance between data transmission accuracy and data transmission rate, so as to enhance the adaptability and reliability of the communication module in complex environments.

[0058] In some embodiments, the preset constraints include: parameter value constraints and data rate constraints; wherein the parameter value constraints include at least one of the following:

[0059] Condition A: The target spreading factor is within a first preset value range;

[0060] Condition B: The target coding rate is within the second preset value range;

[0061] Condition C: The target channel configuration is within the third preset value range.

[0062] The data rate constraint conditions include: a preset data transmission rate is greater than or equal to a preset rate threshold; and the preset data transmission rate is related to a target spreading factor and a target coding rate.

[0063] For example, the first preset value range is {SF7, SF8, SF9, SF 10 ,SF 11 ,SF 12}, where the larger the SF value is, the stronger the anti-interference ability is, from SF7 to SF 12 The second preset value range is {4 / 5, 4 / 6, 4 / 7, 4 / 8}, where CR represents data redundancy. The larger the denominator, the higher the data redundancy and the stronger the error correction capability. The third preset value range is {CH1, CH2, ..., CH n}, where n represents the total number of channel configurations. It should be understood that the above value range is only a specific example, and the preset value range can be appropriately expanded according to the actual use of the communication module. For example, the first preset value range is SF6 to SF 12 , the second preset value range is 4 / 4 to 4 / 10.

[0064] For example, based on the above-mentioned preset value range, the parameter value constraint condition may include at least one of the following, specifically expressed as:

[0065] Condition A1: SF[k]∈{SF7,SF8,SF9,SF 10 ,SF 11 ,SF 12};

[0066] Condition B1: CR[k]∈{4 / 5,4 / 6,4 / 7,4 / 8};

[0067] Condition C1: Channel[k]∈{CH1,CH2,…,CH n}.

[0068] Where SF[k] is the target spreading factor at time k, CR[k] is the target coding rate at time k, and Channel[k] is the target channel configuration at time k. When k = 0, SF[k], CR[k], and Channel[k] represent the initial spreading factor, coding rate, and channel configuration, respectively.

[0069] For example, the data rate constraint can be expressed as:

[0070] DataRate(SF[k],CR[k])≥DR min .

[0071] Where DataRate(SF[k],CR[k]) is the data transmission rate of the target spreading factor and target coding rate; DRmin is the minimum acceptable data rate threshold.

[0072] For example, when the interference increases, the SF is increased (eg, from SF7 to SF 12 ) to improve anti-interference capability; conversely, reducing SF increases data transmission rate. The selection of SF should meet condition A1.

[0073] For example, in a high-interference environment, the CR is increased (e.g., from 4 / 5 to 4 / 8) to enhance error correction capability; in a low-interference environment, the CR is reduced to optimize data transmission efficiency. The selection of the CR should meet condition B1.

[0074] For example, the quality of each available channel is regularly evaluated, and a channel with less interference is selected for communication. When a new interference source is detected, a better channel is switched to in a timely manner. The channel selection needs to meet condition C1.

[0075] The embodiments of this application can dynamically optimize the communication module's communication parameter settings based on preset constraints in different electromagnetic interference environments, improving the accuracy and rate of data transmission and enhancing the module's adaptability and reliability. In practical applications, flexible selection and adjustment of spreading factors, coding rates, and channel configurations, combined with intelligent detection and feedback mechanisms, can ensure that the communication module maintains efficient and reliable data transmission in various complex environments.

[0076] Figure 2 A flowchart of another communication module data transmission method provided in an embodiment of the present application.

[0077] See also Figure 2In some embodiments, the above step S100 includes the following steps (steps S110 and S120):

[0078] Step S110: determining the predicted interference intensity of the electromagnetic interference intensity at the next moment based on the Kalman filter algorithm;

[0079] Step S120: determining target communication parameters of the communication module according to the predicted interference intensity, the preset optimization strategy and the preset constraint conditions.

[0080] In step S110, a Kalman filter algorithm is used to predict the electromagnetic interference intensity of the electromagnetic interference signal at the next moment, thereby obtaining a predicted interference intensity. The Kalman filter algorithm can be used to predict the electromagnetic interference intensity at the next moment based on the current electromagnetic interference signal, or based on the electromagnetic interference intensity over a period of time, which is not limited in this application.

[0081] Of course, in order to more accurately predict the electromagnetic interference intensity at the next moment, the prediction can be based on the electromagnetic interference intensity over a period of time in the past, rather than relying solely on the current electromagnetic interference intensity. To this end, in some embodiments, the above step S110 includes the following steps (steps S111 to S114):

[0082] Step S111: Acquire historical spectrum data of the communication module during data transmission within a preset time;

[0083] Step S112: obtaining historical interference signals according to historical spectrum data;

[0084] Step S113: determining the historical interference intensity of the historical interference signal according to the historical interference signal;

[0085] Step S114: inputting the historical interference intensity into the Kalman filter algorithm to determine the predicted interference intensity.

[0086] To effectively predict the intensity of electromagnetic interference, it is first necessary to obtain historical spectrum data from the communication module during data transmission within a preset time period in step S111. For example, spectrum data from a past period of time, such as the previous day or week, is extracted from the communication module's historical records. This historical spectrum data includes spectrum data collected and stored by the communication module at different time points.

[0087] In step S112, the historical spectrum data acquired in step S111 is analyzed and processed to extract the electromagnetic interference signal therein to obtain the historical interference signal. Specifically, filtering technology or signal separation algorithm can be used to extract the historical interference signal from the historical spectrum data.

[0088] In step S113, a series of historical interference intensity data can be calculated based on methods such as power spectrum density and root mean square value. In step S114, the calculated historical interference intensity data can be input into the Kalman filter algorithm. It should be understood that Kalman filtering is a recursive algorithm based on time series information, which can effectively use historical data to establish a state transition model and predict future interference intensity. Exemplarily, the Kalman filter algorithm can be used to establish a prediction model of electromagnetic interference intensity over time based on the time series of historical interference intensity. The prediction model can fully consider the changing trend, periodicity and other potential influencing factors of the interference intensity. Use the established prediction model to predict the electromagnetic interference intensity at the next moment or within a period of time in the future.

[0089] The embodiment of the present application uses a Kalman filter algorithm based on historical spectrum data to accurately predict the electromagnetic interference intensity, overcoming the inaccuracy that may be caused by relying solely on current data.

[0090] In step S120, the communication parameters of the communication module are optimized in real time based on the predicted interference intensity. For example, when interference increases, the spreading factor is increased and the coding rate is increased to enhance anti-interference capabilities and data transmission accuracy; when interference decreases, the spreading factor is decreased and the coding rate is lowered to improve data transmission speed.

[0091] The embodiments of the present application update the prediction model and communication parameters in real time so that the communication module can maintain efficient and reliable communication transmission in a constantly changing electromagnetic environment, thereby improving the adaptability and performance of the overall communication system.

[0092] Figure 3 A flowchart of another communication module data transmission method provided in an embodiment of the present application.

[0093] See also Figure 3 In some embodiments, the above method further comprises the following steps:

[0094] Step S109: Generate a communication parameter lookup table according to a preset optimization strategy and preset constraints; wherein the communication parameter lookup table is related to the electromagnetic interference intensity and the communication parameters of the communication module.

[0095] It should be understood that the communication parameter lookup table records the optimal communication parameter combinations corresponding to different interference intensities.

[0096] Exemplarily, the electromagnetic interference intensity can be divided into several levels, each level corresponding to an interference intensity range. According to the preset optimization strategies A, B, C, and D and the preset constraint conditions, the communication parameters that need to be adjusted under different interference intensities are determined to ensure the data transmission rate or data transmission accuracy.

[0097] Exemplarily, the communication parameter lookup table can be represented in a table form, where the rows represent the electromagnetic interference intensity levels and the columns represent the communication parameters (SF, CR, channel configuration). According to the preset optimization strategies and the preset constraint conditions, the corresponding communication parameter values are filled in for each interference intensity level. For example, in the case of high interference, a larger SF (such as SF 12 ) and a higher coding rate (such as 4 / 8) are set, and a working channel with higher channel quality is preferentially selected; in the case of low interference, a smaller SF (such as SF7) and a lower coding rate (such as 4 / 5) are set, and a working channel with higher transmission efficiency can be selected.

[0098] Exemplarily, Table 1 is a communication parameter lookup table provided by an embodiment of the present application, as shown in the following table:

[0099] Table 1: Communication parameter lookup table

[0100] Electromagnetic interference intensity Spreading Factor (SF) Coding rate (CR) Channel Configuration Low <![CDATA[SF7]]> 4 / 5 <![CDATA[CH1]]> middle <![CDATA[SF9]]> 4 / 6 <![CDATA[CH2]]> high <![CDATA[SF 12 ]]> 4 / 8 <![CDATA[CH3]]>

[0101] It should be understood that Table 1 is only a specific example of a communication lookup table, and in actual use, the levels of electromagnetic interference intensity can be more finely divided according to needs, and the best communication parameter combination is matched for each electromagnetic interference intensity to meet the strong anti-interference effect of the communication module in the data transmission process. The present application does not specifically limit the communication parameter lookup table.

[0102] The embodiment of the present application can generate a comprehensive and effective communication parameter lookup table through the above steps, helping the communication module to automatically select the optimal communication parameter combination under different interference intensities, improving the adaptability and reliability of the system, and ensuring efficient and stable communication performance.

[0103] In some embodiments, the above step S120 includes the following step (step S121), as shown in Figure 3 .

[0104] Step S121: determining the target communication parameters corresponding to the predicted interference intensity according to the communication parameter lookup table.

[0105] The predicted interference intensity predicted using the Kalman filtering algorithm looks up the pre-generated communication parameter lookup table to obtain an entry matching the predicted interference intensity, from which the corresponding optimal communication parameter combination, i.e., the target communication parameters, are extracted.

[0106] The embodiments of the present application use a pre-generated lookup table and a table lookup method to determine the target communication parameters. This allows for rapid determination of the target communication parameters, avoiding complex real-time calculations. Furthermore, the low time complexity of the table lookup process ensures that the communication module can complete communication parameter optimization in a short period of time. Furthermore, the communication parameters in the lookup table are pre-generated based on a preset optimization strategy and preset constraints, ensuring that the optimal communication parameter combination is selected under varying interference intensities.

[0107] Figure 4 A flowchart of another communication module data transmission method provided in an embodiment of the present application.

[0108] See also Figure 4 In some embodiments, the above step S120 includes the following steps (steps S125 to S128):

[0109] Step S125: obtaining the current electromagnetic interference intensity;

[0110] Step S126: obtaining the difference between the predicted interference intensity and the current electromagnetic interference intensity;

[0111] Step S127: Determine the transition communication parameters of the communication module based on the difference, the preset optimization strategy, and the preset constraints;

[0112] Step S128: Input the transition communication parameters into a preset dynamic adaptive optimization model to obtain target communication parameters.

[0113] In step S125, spectrum data currently transmitted by the communication module is acquired using a spectrum analyzer or other device, and the current electromagnetic interference intensity corresponding to the current electromagnetic interference signal is extracted, analyzed, and calculated. In step S126, the difference between the predicted interference intensity and the current electromagnetic interference intensity, obtained through prediction using a Kalman filter algorithm, is calculated. In step S127, the communication parameters of the communication module are adjusted based on the difference, a preset optimization strategy, and preset constraints. Multiple transitional communication parameters can be determined. In step S128, these multiple transitional communication parameters are input into a dynamic adaptive optimization model to determine the target communication parameters, i.e., the optimal communication parameters.

[0114] Specifically, in some embodiments, the preset dynamic adaptive optimization model is:

[0115]

[0116] Where R(SF[k],CR[k],Channel[k]|I[k]]) is the packet reception success rate at time k; C(SF[k],CR[k],Channel[k],SF[k-1],CR[k-1],Channel[k-1]) is the parameter switching cost at time k; λ is the balancing weight coefficient, which is used to balance the packet reception success rate and parameter switching cost.

[0117] I[k] is the electromagnetic interference intensity at the kth moment, i.e., the predicted interference intensity. Using polynomial regression or machine learning models (such as random forests or neural networks), based on SF[k], CR[k], Channel[k] at the kth moment and the predicted interference intensity I[k], calculate the packet reception success rate R(SF[k], CR[k], Channel[k]|I[k]]).

[0118] Calculate the switching cost C(SF[k],CR[k],Channel[k],SF[k-1],CR[k-1],Channel[k-1]) required to change the communication parameters SF[k-1],CR[k-1],Channel[k-1] at the previous time k-1 to the target communication parameters SF[k],CR[k],Channel[k] at the current time k. For example, the parameter switching cost can be defined as:

[0119]

[0120] Wherein, ΔSF(SF[k],SF[k-1]) is the spreading factor switching cost. When SF[k] is not equal to SF[k-1], ΔSF(SF[k],SF[k-1]) is 1, otherwise it is 0; ΔCR(CR[k],CR[k-1]) is the coding rate switching cost. When CR[k] is not equal to CR[k-1], ΔCR(CR[k],CR[k-1]) is 1, otherwise it is 0; ΔCH(Channel[k],Channel[k-1]) is the channel switching cost. When Channel[k] is not equal to Channel[k-1], ΔCH(Channel[k],Channel[k-1]) is 1, otherwise it is 0; α SF is the switching cost weight coefficient of the spreading factor; α CR is the coding rate switching cost weight coefficient; α CH is the channel switching cost weight coefficient.

[0121] By adjusting the λ value, the optimal balance between the packet reception success rate and the parameter switching cost can be found. A higher λ value indicates a greater emphasis on the packet reception success rate, while a lower λ value indicates a tendency to reduce the switching cost. At each time k, different communication parameter combinations can be tried to evaluate their packet reception success rate R and parameter switching cost C under the predicted interference intensity to obtain the optimal communication parameter combination. Furthermore, the embodiments of the present application can also utilize more efficient algorithms such as hill climbing algorithms and simulated annealing algorithms to optimize the search process and obtain the optimal communication parameter combination more quickly.

[0122] In some embodiments, the above step S128 includes the following steps (steps S1281 and S1282):

[0123] Step S1281: If the difference is greater than or equal to 0, adjust the communication parameters of the communication module multiple times according to a preset optimization strategy and preset constraints to determine multiple first transitional communication parameters to adjust the data transmission accuracy of the communication module;

[0124] Step S1282: If the difference is less than 0, adjust the communication parameters of the communication module multiple times according to the preset optimization strategy and the preset constraint conditions to determine multiple second transition communication parameters to adjust the data transmission rate of the communication module.

[0125] The difference between the predicted interference intensity and the current electromagnetic interference intensity is the key basis for judging whether the electromagnetic interference is increasing or decreasing.

[0126] If the difference is non-negative (i.e., greater than or equal to 0), the predicted interference intensity is higher than the current electromagnetic interference intensity, indicating that the communication module's interference is increasing. When interference increases, the preset optimization strategy focuses on improving the communication module's data transmission accuracy. Based on the preset constraints, the communication module's communication parameters can be adjusted multiple times within the permitted range to generate multiple possible first transition communication parameters.

[0127] If the difference is negative (i.e., less than 0), it indicates that the predicted interference intensity is lower than the current electromagnetic interference intensity, indicating that the interference in the communication module is decreasing. When interference decreases, the preset optimization strategy focuses on increasing the data transmission rate of the communication module. Based on the preset constraints, the communication module's communication parameters can be adjusted multiple times within the permitted range to generate multiple possible second transitional communication parameters.

[0128] Exemplarily, these first and second transitional communication parameter combinations can be generated using methods such as traversal, random search, or intelligent optimization algorithms. Traversal involves trying all possible parameter combinations one by one; random search involves randomly selecting parameter values ​​for combination; and intelligent optimization algorithms generate high-quality combinations through iteration and fitness evaluation. These methods can generate multiple communication parameter combinations during multiple adjustments of communication parameters, serving as input for a subsequent pre-set dynamic adaptive optimization model.

[0129] The embodiment of the present application determines whether the electromagnetic interference is increasing or decreasing by comparing the predicted interference intensity with the current electromagnetic interference intensity, and adjusts the communication parameters of the communication module multiple times based on the corresponding preset optimization strategy and preset constraints to obtain multiple communication parameter combinations, thereby providing data support for the subsequent acquisition of the optimal communication parameters, achieving the purpose of anti-interference, and improving the reliability of the communication module data transmission process.

[0130] When the interference increases, multiple first transition communication parameters are determined, and based on a preset dynamic adaptive optimization model, the objective function values ​​corresponding to the various communication parameter combinations are compared, and the group with the largest objective function value is selected as the optimal communication parameter combination under the current electromagnetic environment. Specifically, in some embodiments, the above step S128 includes the following steps (steps S1283 to S1285):

[0131] Step S1283: inputting a plurality of first transition communication parameters into a preset dynamic adaptive optimization model to determine a plurality of first objective function values;

[0132] Step S1284: obtaining a maximum value of the first objective function, where the maximum value of the first objective function is the maximum value among multiple first objective function values;

[0133] Step S1285: Determine the target communication parameter as the first transition communication parameter corresponding to the maximum value of the first objective function.

[0134] When the interference weakens, multiple second transition communication parameters are determined, and based on a preset dynamic adaptive optimization model, the objective function values ​​corresponding to the various communication parameter combinations are compared, and the group with the largest objective function value is selected as the optimal communication parameter combination under the current electromagnetic environment. Specifically, in some embodiments, the above step S128 includes the following steps (steps S1286 to S1288):

[0135] Step S1286: inputting a plurality of second transition communication parameters into a preset dynamic adaptive optimization model to determine a plurality of second objective function values;

[0136] Step S1287: Obtain the maximum value of the second objective function, where the maximum value of the second objective function is the maximum value among the multiple second objective function values;

[0137] Step S1288: Determine the target communication parameter as the second transition communication parameter corresponding to the maximum value of the second objective function.

[0138] It should be understood that the preset dynamic adaptive optimization module is a pre-established model that, based on input communication parameters, predicts or evaluates the data transmission performance of the communication module under those communication parameter settings and outputs an objective function value. By comparing the objective function values ​​corresponding to all communication parameter combinations, the communication parameter combination that maximizes the objective function value can be found, which is the optimal communication parameter combination for the current electromagnetic environment.

[0139] Through the above steps, the strength of interference can be judged by the difference, and the target and communication parameters can be adaptively adjusted according to the strength of interference, thereby improving the data transmission reliability and efficiency of the communication module in complex electromagnetic environments.

[0140] The communication module data transmission method provided in the embodiment of the present application mainly includes: determining the target communication parameters of the communication module based on the electromagnetic interference intensity of the electromagnetic interference signal in the spectrum data, a preset optimization strategy, and preset constraints; and controlling the communication module to perform data transmission based on the target communication parameters, wherein the target communication parameters include: a target spreading factor, a target coding rate, and a target channel configuration, and the spectrum data is the spectrum data of the communication module during data transmission. The technical solution provided in the embodiment of the present application adaptively adjusts the communication parameters of the communication module based on the electromagnetic interference intensity of the electromagnetic interference signal in the spectrum data of the communication module during data transmission, thereby achieving the purpose of anti-interference, improving the reliability of data transmission of the communication module, and solving the problem that the communication module is easily affected by electromagnetic interference during data transmission, thereby reducing the reliability of data transmission.

[0141] Figure 5 This is a schematic structural diagram of an electronic device provided in some embodiments of the present application. Figure 5 The dotted line in a box indicates that the unit or module is optional. Figure 5 The electronic device 500 in the embodiment can be used to implement the method described in the above method embodiment. The electronic device 500 can be a chip, a terminal device or a server.

[0142] The electronic device 500 may include one or more processors 510. The processor 510 may support the electronic device 500 to implement the method described in the above method embodiment. The processor 510 may be a general-purpose processor or a special-purpose processor. For example, the processor may be a central processing unit (CPU). Alternatively, the processor may be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or the processor may be any conventional processor, etc.

[0143] The electronic device 500 may further include one or more memories 520. Computer programs are stored in the memories 520. The memories 520 may be independent of the processor 510 or integrated into the processor 510.

[0144] The electronic device 500 may further include a transceiver 530. The processor 510 may communicate with other devices or chips via the transceiver 530. For example, the processor 510 may transmit and receive data with other devices or chips via the transceiver 530.

[0145] The computer program in the memory 520 can be executed by the processor 510, causing the processor 510 to perform the following steps:

[0146] Determine target communication parameters of the communication module based on the electromagnetic interference intensity of the electromagnetic interference signal in the spectrum data, a preset optimization strategy, and preset constraints;

[0147] Control the communication module to transmit data according to the target communication parameters;

[0148] The target communication parameters include: target spreading factor, target coding rate and target channel configuration; the spectrum data is the spectrum data of the communication module during data transmission.

[0149] Those skilled in the art will appreciate that all or part of the steps in the various methods of the above embodiments may be accomplished by instructions, or by controlling related hardware through instructions. The instructions may be stored in a computer-readable storage medium and loaded and executed by a processor.

[0150] To this end, an embodiment of the present application provides a computer-readable storage medium having a computer program stored thereon, which is loaded by a processor to execute the steps described in the above method embodiment of the present application. For example, the computer program loaded by the processor may execute the following steps:

[0151] The target communication parameters of the communication module are determined based on the electromagnetic interference intensity of the electromagnetic interference signal in the spectrum data, the preset optimization strategy, and the preset constraints. Based on the target communication parameters, the communication module is controlled to perform data transmission. The target communication parameters include: a target spreading factor, a target coding rate, and a target channel configuration. The spectrum data is the spectrum data of the communication module during data transmission.

[0152] The specific implementation of the above operations / steps can be found in the previous embodiments and will not be repeated here.

[0153] The computer-readable storage medium may include a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, etc.

[0154] Since the computer program stored in the computer-readable storage medium can execute the steps in any of the above-mentioned method embodiments provided in the embodiments of the present application, the beneficial effects that can be achieved by the method described in any of the above-mentioned method embodiments can be achieved. Please refer to the previous embodiments for details and will not be repeated here.

[0155] The present application also provides a computer program product or computer program, which includes computer instructions stored in a computer-readable storage medium. A processor of an electronic device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the electronic device to perform the methods provided in various optional implementations of the above embodiments.

[0156] The above is a detailed introduction to a communication module data transmission method, electronic device and storage medium provided in the embodiments of the present application. Specific examples are used herein to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea; at the same time, for those skilled in the art, based on the ideas of the present invention, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as a limitation on the present invention.

Claims

1. A communication module data transmission method, characterized in that: include: Determine target communication parameters of the communication module based on the electromagnetic interference intensity of the electromagnetic interference signal in the spectrum data, a preset optimization strategy, and preset constraints; controlling the communication module to perform data transmission according to the target communication parameters; The target communication parameters include: a target spreading factor, a target coding rate and a target channel configuration; and the spectrum data is the spectrum data of the communication module during data transmission.

2. The method according to claim 1, characterized in that The preset optimization strategy includes at least one of the following: When the electromagnetic interference intensity is greater than or equal to a first preset intensity threshold, adjusting the communication parameters of the communication module to adjust the data transmission accuracy of the communication module; When the electromagnetic interference intensity increases, adjusting the communication parameters of the communication module to adjust the data transmission accuracy of the communication module; When the electromagnetic interference intensity is less than a second preset intensity threshold, adjusting the communication parameters of the communication module to adjust the data transmission rate of the communication module; During the process of reducing the electromagnetic interference intensity, adjusting the communication parameters of the communication module to adjust the data transmission rate of the communication module; The communication parameters include: spreading factor, coding rate and channel configuration.

3. The method according to claim 1, characterized in that The preset constraints include: parameter value constraints and data rate constraints; The parameter value constraint condition includes at least one of the following: the target spreading factor is within a first preset value range; the target coding rate is within a second preset value range; the target channel configuration is within a third preset value range; The data rate constraint condition includes: a preset data transmission rate is greater than or equal to a preset rate threshold; and the preset data transmission rate is related to the target spreading factor and the target coding rate.

4. The method according to any one of claims 1 to 3, characterized in that The determining of target communication parameters of the communication module according to the electromagnetic interference intensity of the electromagnetic interference signal in the spectrum data, a preset optimization strategy, and preset constraints includes: Determining a predicted interference intensity of the electromagnetic interference intensity at a next moment based on a Kalman filter algorithm; The target communication parameters of the communication module are determined according to the predicted interference intensity, the preset optimization strategy and the preset constraint conditions.

5. The method according to claim 4, characterized in that The determining, based on the Kalman filter algorithm, the predicted interference intensity of the electromagnetic interference intensity at the next moment includes: Acquiring historical spectrum data of the communication module during data transmission within a preset time; Acquiring a historical interference signal according to the historical spectrum data; Determining, according to the historical interference signal, a historical interference intensity of the historical interference signal; The historical interference intensity is input into the Kalman filter algorithm to determine the predicted interference intensity.

6. The method according to claim 4, characterized in that The method further comprises: Generate a communication parameter lookup table according to the preset optimization strategy and the preset constraint conditions; The communication parameter lookup table is related to the electromagnetic interference intensity and the communication parameters of the communication module.

7. The method according to claim 6, characterized in that The determining the target communication parameters of the communication module according to the predicted interference intensity, the preset optimization strategy, and the preset constraint condition includes: The target communication parameter corresponding to the predicted interference intensity is determined according to the communication parameter lookup table.

8. The method according to claim 4, characterized in that The determining the target communication parameters of the communication module according to the predicted interference intensity, the preset optimization strategy, and the preset constraint condition includes: Get the current electromagnetic interference intensity; Obtaining a difference between the predicted interference intensity and the current electromagnetic interference intensity; determining a transition communication parameter of the communication module according to the difference, the preset optimization strategy, and the preset constraint condition; The transition communication parameters are input into a preset dynamic adaptive optimization model to obtain the target communication parameters.

9. The method according to claim 8, characterized in that The preset dynamic adaptive optimization model is: Wherein, R(SF[k],CR[k],Channel[k]|I[k]]) is the packet reception success rate at the kth moment; C(SF[k],CR[k],Channel[k],SF[k-1],CR[k-1],Channel[k-1]) is the parameter switching cost at the kth moment; λ is the balancing weight coefficient used to balance the packet reception success rate and the parameter switching cost.

10. The method according to claim 9, characterized in that The determining of the transition communication parameters of the communication module according to the difference, the preset optimization strategy, and the preset constraint condition includes: If the difference is greater than or equal to 0, adjusting the communication parameters of the communication module multiple times according to the preset optimization strategy and the preset constraint condition to determine multiple first transition communication parameters to adjust the data transmission accuracy of the communication module; If the difference is less than 0, the communication parameters of the communication module are adjusted multiple times according to the preset optimization strategy and the preset constraint conditions to determine multiple second transition communication parameters to adjust the data transmission rate of the communication module.

11. The method according to claim 10, characterized in that The step of inputting the transition communication parameters into a preset dynamic adaptive optimization model to obtain the target communication parameters includes: Inputting a plurality of the first transition communication parameters into the preset dynamic adaptive optimization model to determine a plurality of first objective function values; Obtaining a first objective function maximum value, where the first objective function maximum value is a maximum value among multiple first objective function values; The target communication parameter is determined to be the first transition communication parameter corresponding to the maximum value of the first objective function.

12. The method according to claim 10, characterized in that The step of inputting the transition communication parameters into a preset dynamic adaptive optimization model to obtain the target communication parameters includes: Inputting a plurality of the second transition communication parameters into the preset dynamic adaptive optimization model to determine a plurality of second objective function values; Obtaining a second objective function maximum value, where the second objective function maximum value is a maximum value among a plurality of second objective function values; The target communication parameter is determined to be the second transition communication parameter corresponding to the maximum value of the second objective function.

13. The method according to claim 1, wherein The method further comprises: Acquiring the spectrum data; Acquire the electromagnetic interference signal according to the spectrum data; The electromagnetic interference intensity of the electromagnetic interference signal is determined according to the electromagnetic interference signal.

14. An electronic device, characterized in that: It includes a memory and a processor, wherein the memory stores a computer program or instruction, and when the computer program or instruction is executed by the processor, the processor executes the steps in the communication module data transmission method according to any one of claims 1 to 13.

15. A computer-readable storage medium, characterized in that A computer program or instruction is stored thereon, and when the computer program or instruction is executed by a processor, the steps in the communication module data transmission method as described in any one of claims 1 to 13 are implemented.

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