Data processing method and system for near-field wireless transmission

Abstract

The present invention provides a data processing method and system for near-field wireless transmission, which relate to the field of wireless communication technology, and include obtaining spectrum characteristics and wireless environment characteristics of a short-range communication area; selecting at least one candidate channel according to the spectrum characteristics, and determining an optimal working channel according to the wireless environment characteristics; determining an initial channel coding strategy according to state characteristics of the optimal working channel, and adjusting the initial channel coding strategy based on the wireless environment characteristics to obtain the optimal channel coding strategy; inputting the wireless environment characteristics and the state characteristics of the optimal working channel into a pre-constructed modulation prediction model, and outputting an optimal signal modulation mode; and using the optimal channel coding strategy, the optimal signal modulation mode and the optimal working channel to perform data encoding, signal modulation and signal transmission in sequence for data to be transmitted. The present invention makes full use of environmental information to realize dynamic optimization of transmission strategies, thereby improving the reliability and efficiency of data transmission.

Description

Technical Field

[0001] The present invention relates to the field of wireless communication technology, and in particular to a data processing method and system for near-field wireless transmission. Background Art

[0002] With the rapid development of wireless communication technology, near-field wireless transmission technology has been widely used in many fields due to its high efficiency and convenience, such as mobile payment, smart home, Internet of Things communication, etc. However, in the process of near-field wireless transmission, the reliability and efficiency of data transmission are often affected by a variety of environmental factors, such as the occupancy of spectrum resources, the complexity of the wireless environment, and electromagnetic interference. Therefore, how to dynamically adjust the transmission strategy according to real-time environmental parameters to achieve the optimization of data transmission has become a key issue that needs to be solved in the current near-field wireless transmission technology.

[0003] Traditional near-field wireless transmission data processing methods mostly use fixed channels, coding strategies and modulation methods, and lack dynamic adaptability to environmental parameters. This method may perform well in relatively stable environments, but in complex and changing wireless environments, it often leads to problems such as low data transmission efficiency and increased bit error rate. Especially in scenarios with tight spectrum resources and severe electromagnetic interference, traditional fixed transmission strategies are even more difficult to meet the reliability and real-time requirements of data transmission.

[0004] Therefore, it is necessary to provide a data processing method and system for near-field wireless transmission to solve the above technical problems. Summary of the invention

[0005] To solve the above technical problems, the present invention provides a data processing method and system for near-field wireless transmission, which obtains the environmental parameters of the short-range communication area in real time, including spectrum characteristics and wireless environment characteristics, and dynamically selects the best working channel, determines the best channel coding strategy and the best signal modulation method according to these parameters. This method can make full use of environmental information and realize dynamic optimization of transmission strategy, thereby improving the reliability and efficiency of data transmission.

[0006] The present invention provides a data processing method for near-field wireless transmission, the method comprising the following steps:

[0007] Acquiring environmental parameters of a short-distance communication area, wherein the environmental parameters include spectrum characteristics and wireless environment characteristics of the short-distance communication area;

[0008] Selecting at least one candidate channel according to the spectrum characteristics, and determining the best working channel from the at least one candidate channel according to the wireless environment characteristics of the short-range communication area;

[0009] Determining an initial channel coding strategy according to the state characteristics of the optimal working channel, and adjusting the initial channel coding strategy based on the wireless environment characteristics of the short-range communication area to obtain an optimal channel coding strategy;

[0010] Inputting the wireless environment characteristics of the short-range communication area and the state characteristics of the optimal working channel into a pre-built modulation prediction model, and outputting the optimal signal modulation mode;

[0011] The optimal channel coding strategy, the optimal signal modulation method and the optimal working channel are used to perform data coding, signal modulation and signal transmission on the data to be transmitted in sequence.

[0012] Preferably, the obtaining of environmental parameters of the short-range communication area includes:

[0013] Collecting and analyzing spectrum characteristics in the short-range communication area, wherein the spectrum characteristics include available frequency bands, spectrum occupancy status, and signal interference intensity;

[0014] Measure and evaluate the wireless environment characteristics of the short-range communication area, wherein the wireless environment characteristics include the path loss value of the signal, the multipath effect parameter value of the signal, the degree of obstruction of the obstacle to the signal transmission path, and the interference intensity of the electromagnetic environment.

[0015] Preferably, the selecting at least one candidate channel according to the spectrum characteristics, and determining the best working channel from the at least one candidate channel according to the wireless environment characteristics of the short-range communication area, comprises:

[0016] Based on the available frequency bands, spectrum occupancy status and signal interference strength in the spectrum characteristics, a set of candidate channels that meet preset spectrum conditions are screened out, wherein the preset spectrum conditions are to determine whether the channel is available, whether the spectrum occupancy rate of the channel is lower than a preset occupancy rate threshold, and whether the signal interference strength of the channel is lower than a preset interference threshold;

[0017] According to a plurality of evaluation indicators determined by the wireless environment characteristics, an indicator evaluation is performed on the candidate channel set to obtain an evaluation result;

[0018] Based on the evaluation result of the wireless environment characteristics, the best working channel is determined from the candidate channel set by a weighted scoring method.

[0019] Preferably, the processing of the evaluation index includes:

[0020] Measuring and calculating a path loss value of each candidate channel, wherein the path loss value is negatively correlated with the channel score;

[0021] Analyzing a multipath effect parameter value of each candidate channel, wherein the multipath effect parameter value is negatively correlated with the channel score;

[0022] Using a geographic information system combined with a building layout map, the signal propagation path of each candidate channel is simulated, and the degree of obstruction of obstacles on the signal transmission path is evaluated, wherein the degree of obstruction is negatively correlated with the channel score;

[0023] The electromagnetic environment interference intensity of each candidate channel is monitored, wherein the electromagnetic environment interference intensity is negatively correlated with the channel score.

[0024] Preferably, the determining the best working channel from the candidate channel set by a weighted scoring method based on the evaluation result of the wireless environment characteristics comprises:

[0025] Pre-assign corresponding weight coefficients to each evaluation indicator;

[0026] For each candidate channel, its weighted score is calculated using the following formula:

[0027]

[0028] in, Indicates The weighted score of candidate channels, Indicates The path loss value of candidate channels, Indicates The multipath effect parameter value of the candidate channel, Indicates The blocking degree of candidate channels, Indicates The electromagnetic environment interference strength of the candidate channels, , , and Respectively represent the weight coefficients of path loss value, multipath effect parameter value, blocking degree and electromagnetic environment interference intensity;

[0029] The channel with the highest weighted score is selected from all candidate channels as the best working channel.

[0030] Preferably, determining the initial channel coding strategy according to the state characteristics of the optimal working channel, and adjusting the initial channel coding strategy based on the wireless environment characteristics of the short-range communication area to obtain the optimal channel coding strategy includes:

[0031] Based on the spectrum efficiency, bit error rate and signal stability of the optimal working channel, preliminarily selecting a combination of a coding rate and a coding length from a preset mapping table as an initial channel coding strategy, wherein the preset mapping table is pre-established based on an empirical relationship between channel state characteristics and coding parameters;

[0032] According to the path loss value, multipath effect parameter value, blocking degree and electromagnetic environment interference intensity, the coding rate and coding length of the initial channel coding strategy are adjusted to obtain the optimal channel coding strategy after the coding rate and coding length are adjusted.

[0033] Preferably, the coding rate and coding length are adjusted according to the following formula:

[0034]

[0035]

[0036] in, and are the encoding rates before and after adjustment, and are the encoding lengths before and after adjustment, , , and They are path loss value, multipath effect parameter value, blocking degree and electromagnetic environment interference intensity, and their values ​​are equal to , , and , , , and is the corresponding adjustment coefficient in the coding rate adjustment, , , and is the corresponding adjustment coefficient in the code length adjustment, , , and They are respectively the maximum allowable values ​​of path loss value, multipath effect parameter value, blocking degree and electromagnetic environment interference intensity.

[0037] Preferably, the step of inputting the wireless environment characteristics of the short-range communication area and the state characteristics of the optimal working channel into a pre-built modulation prediction model to output the optimal signal modulation mode includes:

[0038] The wireless environment characteristics and the state characteristics of the optimal working channel are taken as input vectors and input into a pre-built modulation prediction model. The modulation prediction model calculates the applicability score of each modulation mode according to the input vector, and selects the modulation mode with the highest score as the optimal signal modulation mode. The modulation prediction model is a machine learning model that learns the mapping relationship between the wireless environment characteristics and the channel state characteristics and the optimal signal modulation mode.

[0039] Preferably, the using the optimal channel coding strategy, the optimal signal modulation mode and the optimal working channel to sequentially perform data encoding, signal modulation and signal transmission on the data to be transmitted includes:

[0040] According to the determined optimal channel coding strategy, encoding processing is performed on the data to be sent;

[0041] Using the determined optimal signal modulation method, the encoded data is converted into a signal form suitable for transmission on the selected optimal working channel;

[0042] The modulated signal is sent to the receiving end through the optimal working channel.

[0043] The present invention also provides a data processing system for near-field wireless transmission, which is used to execute a data processing method for near-field wireless transmission. The system comprises:

[0044] An environmental parameter acquisition module, used to acquire environmental parameters of a short-distance communication area, wherein the environmental parameters include spectrum characteristics and wireless environment characteristics of the short-distance communication area;

[0045] A channel determination module, configured to select at least one candidate channel according to the spectrum characteristics, and determine the best working channel from the at least one candidate channel according to the wireless environment characteristics of the short-range communication area;

[0046] A strategy determination module, configured to determine an initial channel coding strategy according to the state characteristics of the optimal working channel, and adjust the initial channel coding strategy based on the wireless environment characteristics of the short-range communication area to obtain an optimal channel coding strategy;

[0047] A modulation mode determination module, used to input the wireless environment characteristics of the short-range communication area and the state characteristics of the optimal working channel into a pre-built modulation prediction model, and output an optimal signal modulation mode;

[0048] The sending module is used to use the optimal channel coding strategy, the optimal signal modulation method and the optimal working channel to perform data encoding, signal modulation and signal sending in sequence on the data to be sent.

[0049] Compared with the related art, the data processing method and system for near-field wireless transmission provided by the present invention have the following beneficial effects:

[0050] The present invention first collects and analyzes the spectrum characteristics in the short-distance communication area to screen out a set of candidate channels that meet the preset spectrum conditions. Then, in combination with the wireless environment characteristics, such as the path loss of the signal, the multipath effect parameters, the degree of obstruction of the signal transmission path by obstacles, and the interference intensity of the electromagnetic environment, the candidate channels are comprehensively evaluated to determine the best working channel. After determining the best working channel, the present invention further preliminarily selects the initial channel coding strategy according to the state characteristics of the channel, such as spectrum efficiency, bit error rate and signal stability, and adjusts the coding rate and coding length based on the wireless environment characteristics to obtain the best channel coding strategy. Finally, the wireless environment characteristics and the state characteristics of the best working channel are input into the pre-constructed modulation prediction model to output the best signal modulation mode. The best channel coding strategy, the best signal modulation mode and the best working channel are used to encode, modulate and send the data to be sent, thereby optimizing data transmission.

[0051] In summary, the data processing method for near-field wireless transmission proposed in the present invention effectively improves the reliability and efficiency of data transmission by acquiring environmental parameters in real time and dynamically adjusting the transmission strategy. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] Figure 1 A flowchart of a data processing method for near-field wireless transmission provided by the present invention;

[0053] Figure 2 A module structure diagram of a near-field wireless transmission data processing system provided by the present invention. DETAILED DESCRIPTION

[0054] The present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It is to be understood that the specific embodiments described herein are only used to explain the present invention, rather than to limit the present invention. It should also be noted that, for ease of description, only the parts related to the present invention, rather than all structures, are shown in the accompanying drawings. In addition, the embodiments of the present invention and the features in the embodiments may be combined with each other without conflict.

[0055] It should also be noted that, for ease of description, only the parts related to the present invention, but not all of the contents, are shown in the accompanying drawings. Before discussing the exemplary embodiments in more detail, it should be mentioned that some exemplary embodiments are described as processes or methods depicted as flow charts. Although the flow charts describe the operations (or steps) as sequential processes, many of the operations therein can be implemented in parallel, concurrently or simultaneously. In addition, the order of the operations can be rearranged. The process can be terminated when its operation is completed, but it can also have additional steps not included in the accompanying drawings. The process can correspond to methods, functions, procedures, subroutines, subprograms, etc.

[0056] Embodiment 1

[0057] The present invention provides a data processing method for near-field wireless transmission, referring to Figure 1 As shown, the method comprises the following steps:

[0058] S1: Acquire environmental parameters of a short-distance communication area, wherein the environmental parameters include spectrum characteristics and wireless environment characteristics of the short-distance communication area.

[0059] In the data processing method of near-field wireless transmission, obtaining the environmental parameters of the short-range communication area is a crucial first step. These environmental parameters include spectrum characteristics and wireless environment characteristics, which directly affect the channel selection, coding strategy and modulation method selection. Specifically, spectrum characteristics provide information about available frequency bands, spectrum occupancy status and signal interference strength, which is crucial for screening out suitable candidate channels. On the other hand, wireless environment characteristics such as path loss, multipath effect, obstacle blocking degree and electromagnetic interference strength help to evaluate the quality of each candidate channel, thereby determining the best working channel. By accurately obtaining this information, the reliability and efficiency of data transmission can be significantly improved.

[0060] Specifically, step S1 includes the following steps:

[0061] S11: Collect and analyze spectrum characteristics in the short-range communication area, where the spectrum characteristics include available frequency bands, spectrum occupancy status, and signal interference intensity.

[0062] In this embodiment, a spectrum analysis device (including but not limited to a spectrum analyzer or a software defined radio device) is used to scan the short-range communication area to collect spectrum data of all available frequency bands in the area. These data include the frequency range, bandwidth, current usage status of each frequency band, and whether there are interference signals. Subsequently, these spectrum data are analyzed to identify which frequency bands are unoccupied or only slightly occupied, and the signal interference strength of each frequency band is calculated. Based on these analysis results, a spectrum database is established to record detailed information of each frequency band, including spectrum occupancy and interference level.

[0063] In addition, frequency bands that meet the requirements will be screened out as candidate frequency bands based on preset spectrum conditions (spectrum occupancy rate is lower than a certain threshold, interference intensity is lower than a certain level).

[0064] By collecting and analyzing spectrum characteristics, frequency bands suitable for wireless transmission can be effectively identified, avoiding waste of spectrum resources and unnecessary interference. This not only improves spectrum utilization, but also provides a reliable basis for channel selection in subsequent steps. In addition, this method can adapt to dynamically changing spectrum environments, ensuring efficient data transmission even when spectrum usage changes.

[0065] S12: Measure and evaluate the wireless environment characteristics of the short-range communication area, wherein the wireless environment characteristics include the path loss value of the signal, the multipath effect parameter value of the signal, the degree of obstruction of the obstacle to the signal transmission path, and the interference intensity of the electromagnetic environment.

[0066] In this embodiment, in order to understand the characteristics of the wireless environment in the short-range communication area, a series of detailed measurements and evaluations are required. First, the path loss is evaluated by combining the wireless signal propagation model with actual measurements. The path loss value can be calculated by transmitting a test signal of known power and measuring the received signal strength at the receiving end. Secondly, multipath detection technology is used to analyze the multipath effect parameter value. By sending a specific detection signal and analyzing its reflection path, the specific parameters of the multipath effect are determined. In this application, the multipath effect parameter value is expressed by the root mean square delay spread value. For the evaluation of the degree of obstacle blocking, the geographic information system (GIS) and the building layout are combined to simulate the propagation path of the signal at different locations, identify possible physical obstacles and their impact on signal propagation. Finally, the electromagnetic environment monitoring equipment is used to detect the electromagnetic interference intensity, record the interference signal strength on each frequency band, and compare it with the standard interference threshold.

[0067] A comprehensive and accurate description of the wireless environment can be obtained through detailed measurement and evaluation of wireless environment characteristics. This not only helps to accurately evaluate the quality of each candidate channel, but also provides an important basis for subsequent weighted scoring and channel selection. In particular, for the common multipath effects and obstacle blocking problems in complex urban or industrial environments, this meticulous analysis method can significantly improve the stability and reliability of data transmission.

[0068] S2: Select at least one candidate channel according to the spectrum characteristics, and determine the best working channel from the at least one candidate channel according to the wireless environment characteristics of the short-range communication area.

[0069] In this application, this step directly affects the selection of subsequent coding strategies and modulation methods, and ultimately affects the quality and efficiency of data transmission. Specifically, by analyzing spectrum characteristics (such as available frequency bands, spectrum occupancy status, and signal interference strength), a set of candidate channels suitable for use can be screened out; and further combined with wireless environment characteristics (such as path loss, multipath effect, obstacle blocking degree, and electromagnetic interference strength), the quality of each candidate channel can be evaluated, thereby selecting the best working channel that best suits the current communication environment.

[0070] Specifically, step S2 includes the following steps:

[0071] S21: Based on the available frequency bands, spectrum occupancy status and signal interference strength in the spectrum characteristics, a set of candidate channels that meet preset spectrum conditions are screened out, wherein the preset spectrum conditions are to determine whether the channel is available, whether the spectrum occupancy of the channel is lower than a preset occupancy threshold, and whether the signal interference strength of the channel is lower than a preset interference threshold.

[0072] After obtaining the spectrum characteristics (including available frequency bands, spectrum occupancy status, and signal interference strength) in the short-range communication area, these data will be screened according to the preset spectrum conditions to determine the candidate channel set. The specific implementation steps are as follows:

[0073] Determine whether the channel is available: First, you need to confirm whether each frequency band complies with legal and technical specifications. For example, some frequency bands may be strictly regulated by national or regional radio regulatory agencies and may only be used under certain conditions. In addition, you also need to consider the technical specifications of the device and the range of supported frequency bands to ensure that the selected frequency band is compatible with the device.

[0074] Spectrum occupancy threshold: defines a maximum allowed spectrum occupancy, such as no more than 30%, to ensure that the selected frequency band has sufficient idle resources for transmission.

[0075] Signal interference strength threshold: Set a maximum allowable signal interference strength level, such as below -85 dBm, to ensure that signal quality is not affected by excessive external interference.

[0076] Based on the above set standards, all available frequency bands are preliminarily screened. This step mainly relies on the spectrum data collected previously, and the judgment is made by comparing the actual occupancy rate and interference intensity of each frequency band with the set threshold.

[0077] For those frequency bands whose spectrum occupancy is lower than the set occupancy threshold and whose signal interference strength is also lower than the set interference threshold, further check whether they comply with the requirements of laws, regulations and technical specifications. If a frequency band meets the standards in terms of spectrum occupancy and interference strength, but does not comply with local radio management regulations or is not supported by the device, then the frequency band should not be considered as an available channel.

[0078] Finally, the frequency bands that pass all the above checks are added to the candidate channel set. This set contains all the frequency bands that are most suitable for wireless transmission under the current conditions.

[0079] This method can effectively select the most suitable candidate channel set from a large number of available frequency bands, taking into account not only the spectrum occupancy rate and signal interference intensity, but also the requirements of laws, regulations and technical specifications, thus avoiding the waste of spectrum resources and unnecessary interference. This strategy not only improves spectrum utilization, but also provides a reliable basis for the selection of the best working channel in subsequent steps, and adapts to dynamically changing needs, ensuring efficient data transmission even when spectrum usage changes.

[0080] S22: performing an indicator evaluation on the candidate channel set according to a plurality of evaluation indicators determined by the wireless environment characteristics to obtain an evaluation result.

[0081] In this embodiment, in order to accurately evaluate the quality of each candidate channel, it is necessary to consider multiple evaluation indicators determined by multiple wireless environment characteristics. The specific steps are as follows:

[0082] Path loss assessment: Transmit a test signal of known power and measure the received signal strength at the receiving end to calculate the path loss value. The lower the path loss value, the shorter the signal propagation path and the smaller the signal attenuation.

[0083] Multipath effect parameter evaluation: Use multipath detection technology to send a specific detection signal and analyze its reflection path to determine the specific parameters of the multipath effect. In this embodiment, the root mean square delay spread (RMS Delay Spread) is selected as the key parameter of the multipath effect. The smaller the root mean square delay spread, the milder the multipath effect and the better the channel quality.

[0084] Obstacle blocking degree assessment: Combined with the Geographic Information System (GIS) and building layout diagrams, the signal propagation path at different locations is simulated to identify possible physical obstacles and their impact on signal propagation. The smaller the degree of obstacle blocking, the smoother the signal transmission path and the higher the channel quality.

[0085] Electromagnetic interference intensity monitoring: Use electromagnetic environment monitoring equipment to detect the interference signal intensity on each frequency band and compare it with the standard interference threshold. The lower the electromagnetic interference intensity, the less external interference the channel is subject to, and the better the channel quality.

[0086] For each evaluation indicator, a corresponding score is given according to its value. For example, the path loss value, multipath effect parameter value, obstacle blocking degree and electromagnetic interference intensity are all negatively correlated with the channel score, that is, the smaller these values ​​are, the higher the channel score is.

[0087] Detailed measurement and evaluation of wireless environment characteristics not only helps to accurately assess the quality of each candidate channel, but also provides an important basis for subsequent weighted scoring and channel selection.

[0088] S23: Based on the evaluation result of the wireless environment characteristics, determine the best working channel from the candidate channel set by a weighted scoring method.

[0089] In this embodiment, in order to determine the best working channel from the candidate channel set, a weighted scoring method is adopted. The specific steps are as follows:

[0090] Weight coefficient allocation: Pre-allocate corresponding weight coefficients for each evaluation indicator (path loss value, multipath effect parameter value, obstacle blocking degree and electromagnetic interference intensity). These weight coefficients can be manually adjusted according to the needs of actual application scenarios to balance the impact of different factors on channel quality.

[0091] Weighted score calculation: For each candidate channel, its weighted score is calculated using the following formula.

[0092]

[0093] in, Indicates The weighted score of candidate channels, Indicates The path loss value of candidate channels, Indicates The multipath effect parameter value of the candidate channel, Indicates The blocking degree of candidate channels, Indicates The electromagnetic environment interference strength of the candidate channels, , , and They respectively represent the weight coefficients of path loss value, multipath effect parameter value, blocking degree and electromagnetic environment interference intensity.

[0094] c. Select the channel with the highest weighted score from all candidate channels as the best working channel.

[0095] The weighted scoring method can comprehensively consider multiple wireless environment characteristic evaluation indicators and perform comprehensive scoring based on preset weight coefficients. This method can not only accurately evaluate the quality of each candidate channel, but also select the best working channel that best suits the current communication needs in a complex and changing wireless environment, thereby significantly improving the reliability and efficiency of data transmission.

[0096] S3: Determine an initial channel coding strategy according to the state characteristics of the optimal working channel, and adjust the initial channel coding strategy based on the wireless environment characteristics of the short-range communication area to obtain an optimal channel coding strategy.

[0097] After determining the best working channel, the next step is to formulate an initial channel coding strategy based on the state characteristics of the channel, and adjust this strategy according to the characteristics of the wireless environment in the short-range communication area to obtain the best channel coding strategy. The choice of channel coding strategy directly affects key performance indicators such as data transmission reliability, bit error rate and spectrum efficiency. By choosing a reasonable coding rate and coding length, the stability and efficiency of data transmission can be effectively improved, especially in a complex and changeable wireless environment.

[0098] Specifically, step S3 includes the following steps:

[0099] S31: Based on the spectrum efficiency, bit error rate and signal stability of the optimal working channel, a combination of coding rate and coding length is preliminarily selected from a preset mapping table as an initial channel coding strategy, wherein the preset mapping table is pre-established based on the empirical relationship between channel state characteristics and coding parameters.

[0100] In this embodiment, a set of initial coding rate and coding length is selected from a pre-established experience mapping table according to the state characteristics (spectral efficiency, bit error rate and signal stability) of the optimal working channel. This mapping table is usually constructed based on a large amount of experimental data and historical experience, and it records the optimal coding parameter combination under different channel conditions. For example, under the condition of high bit error rate but good spectrum efficiency, a lower coding rate and a longer coding length may be selected to enhance the error correction capability; while under the condition of low bit error rate and stable channel, a higher coding rate and a shorter coding length may be selected to improve the transmission efficiency.

[0101] Spectrum efficiency evaluation: Determine the appropriate coding rate by measuring the actual spectrum utilization of the optimal working channel, that is, the amount of data transmitted per unit bandwidth.

[0102] Bit error rate analysis: According to the bit error rate of the channel, select a code length that can provide sufficient error correction capability. If the bit error rate is high, it is necessary to add redundant information to ensure data integrity.

[0103] Signal stability considerations: Consider the signal stability of the channel, including its fluctuations over time. For channels with poor stability, more conservative coding strategies are usually required to cope with potential burst errors.

[0104] Based on the above analysis results, a matching coding rate and coding length combination is selected from a preset mapping table as an initial channel coding strategy.

[0105] This method can quickly find a relatively optimized set of initial settings from a large number of possible encoding parameter combinations, which not only improves design efficiency but also provides a basis for subsequent fine-tuning. In addition, the mapping table built based on experience and experimental data ensures that the selected strategy can achieve good performance in most cases.

[0106] S32: According to the path loss value, multipath effect parameter value, blocking degree and electromagnetic environment interference intensity, the coding rate and coding length of the initial channel coding strategy are adjusted to obtain the optimal channel coding strategy after the coding rate and coding length are adjusted.

[0107] In this embodiment, the following two formulas are used to dynamically adjust the coding rate and coding length to adapt to different wireless environment conditions. The coding rate is adjusted mainly to ensure that a certain transmission efficiency can be maintained in a harsh environment, while the coding length is adjusted to improve the reliability and anti-interference ability of data transmission. In this way, it is possible to better cope with complex wireless communication environments and optimize data transmission performance.

[0108] The coding rate and coding length are adjusted according to the following formula:

[0109]

[0110]

[0111] in, and are the encoding rates before and after adjustment, and are the encoding lengths before and after adjustment, , , and They are path loss value, multipath effect parameter value, blocking degree and electromagnetic environment interference intensity, and their values ​​are equal to , , and , , , and These coefficients are the corresponding adjustment coefficients in the coding rate adjustment. These coefficients determine the influence of each wireless environment feature on the coding rate. The values ​​of these coefficients are between 0 and 1, and are used to control the influence weight of each factor on the coding rate. , , and These coefficients are the corresponding adjustment coefficients in the code length adjustment. These coefficients determine the influence of each wireless environment characteristic on the code length. The values ​​of these coefficients are greater than 0 and are used to increase the code length to improve the reliability of data transmission. , , and They are the maximum allowable values ​​of path loss value, multipath effect parameter value, blocking degree and electromagnetic environment interference intensity. These maximum values ​​are used to normalize various wireless environment characteristics so that they are comparable in calculation.

[0112] In this embodiment, the coding rate adjustment formula copes with poor wireless environment conditions (such as high path loss, strong multipath effect, severe obstacle blocking or high-intensity electromagnetic interference) by reducing the coding rate.

[0113] The impact of each wireless environment feature is normalized and multiplied by the corresponding adjustment coefficient, and then these effects are subtracted from 1 to obtain a correction factor. This correction factor is multiplied by the coding rate before adjustment to obtain the adjusted coding rate. If the impact of a wireless environment feature is large (for example, the path loss is very high), the item corresponding to the feature will be larger, resulting in a smaller correction factor, which ultimately reduces the coding rate. Conversely, if the wireless environment conditions are good, the correction factor is close to 1 and the coding rate remains almost unchanged.

[0114] The code length adjustment formula is to increase the reliability of data transmission by increasing the code length, especially in the case of poor wireless environment conditions (such as high path loss, strong multipath effect, severe obstacle blocking or high-intensity electromagnetic interference). The impact of each wireless environment feature is normalized and multiplied by the corresponding adjustment coefficient, and then added to 1 to obtain a correction factor. This correction factor is multiplied by the code length before adjustment to obtain the adjusted code length.

[0115] If a wireless environment feature has a greater impact (for example, the path loss is very high), the item corresponding to that feature will be larger, resulting in a larger correction factor, which will eventually increase the code length. Conversely, if the wireless environment conditions are good, the correction factor is close to 1 and the code length remains almost unchanged.

[0116] S4: Inputting the wireless environment characteristics of the short-range communication area and the state characteristics of the optimal working channel into a pre-built modulation prediction model, and outputting the optimal signal modulation mode.

[0117] Specifically, step S4 includes the following contents:

[0118] The wireless environment characteristics and the state characteristics of the optimal working channel are taken as input vectors and input into a pre-built modulation prediction model. The modulation prediction model calculates the applicability score of each modulation mode according to the input vector, and selects the modulation mode with the highest score as the optimal signal modulation mode. The modulation prediction model is a machine learning model that learns the mapping relationship between the wireless environment characteristics and the channel state characteristics and the optimal signal modulation mode.

[0119] In this embodiment, different wireless environment characteristics (such as path loss, multipath effect, obstacle blocking degree and electromagnetic interference intensity) and the state characteristics of the best working channel (such as spectrum efficiency, bit error rate and signal stability) will affect the selection of the most suitable modulation method. By using a machine learning model to predict the best signal modulation method, these characteristic information can be fully utilized to automatically select the modulation scheme that best suits the current communication conditions, thereby improving the performance of the overall system.

[0120] In order to determine the optimal signal modulation method, the collected wireless environment characteristics of the short-range communication area (including path loss value, multipath effect parameter value, obstacle blocking degree and electromagnetic interference intensity) and the state characteristics of the optimal working channel (such as spectrum efficiency, bit error rate and signal stability) are organized into an input vector and input into the pre-trained modulation prediction model.

[0121] The wireless environment characteristics and the state characteristics of the best working channel are used as input vectors. Each element represents the specific value of one of the above-mentioned characteristics.

[0122] The modulation prediction model is a machine learning model that is pre-trained based on a large amount of experimental data and historical experience. It can be, but is not limited to, a support vector machine (SVM), a neural network (NN), or other types of classifiers. The learning process of the model involves a large amount of performance data of various modulation methods under different conditions, with the goal of learning the mapping relationship between wireless environment characteristics and the optimal modulation method.

[0123] When the input vector is fed into the modulation prediction model, the model calculates a fitness score for each available modulation method. This score reflects the expected performance of a specific modulation method under given wireless environment conditions. For example, some modulation methods perform better in high bit error rate environments, while others are more stable in complex multipath environments.

[0124] According to the applicability scores of all modulation modes, the modulation mode with the highest score is selected as the optimal signal modulation mode, ensuring that the selected modulation mode can adapt to the current wireless communication environment to the greatest extent and provide the best data transmission performance.

[0125] S5: using the optimal channel coding strategy, the optimal signal modulation method and the optimal working channel to perform data encoding, signal modulation and signal transmission on the data to be transmitted in sequence.

[0126] After determining the best working channel and selecting the optimal coding strategy and modulation method, the next step is to apply these selections to the actual data transmission process. Specifically, the data to be transmitted needs to be encoded according to the best channel coding strategy, and the encoded data needs to be converted into a signal form suitable for transmission on the selected best working channel using the selected best signal modulation method, and finally the signal is sent to the receiving end through the best working channel. This process ensures that data can be transmitted efficiently and reliably in a complex wireless environment.

[0127] Specifically, step S5 includes the following steps:

[0128] S51: Encoding the data to be transmitted according to the determined optimal channel coding strategy.

[0129] In this embodiment, the original data to be transmitted is encoded according to the optimal channel coding strategy (including coding rate and coding length) determined in the previous step. The encoding process generally includes the following key steps:

[0130] Grouping and redundancy addition: The data to be sent is divided into multiple groups according to the code length requirements, and appropriate redundant information is added to each group. This step helps improve the reliability of data transmission, especially under high bit error rate or unstable channel conditions.

[0131] Error correction coding: Error correction coding technology (including but not limited to convolutional coding, Turbo coding and LDPC coding) is used to encode each group of data according to the set coding rate. The coding rate determines the ratio of original data to redundant information. A lower coding rate means higher redundancy and stronger error correction capability.

[0132] The above steps can generate optimized coded data streams, which have high robustness and can maintain good transmission quality in a complex and changeable wireless environment.

[0133] S52: Using the determined optimal signal modulation method, the encoded data is converted into a signal form suitable for transmission on the selected optimal working channel.

[0134] In this embodiment, after the data encoding is completed, it is necessary to convert the encoded data into a signal form suitable for transmission on the selected optimal working channel according to the optimal signal modulation method determined in the previous step. The specific steps are as follows:

[0135] Select the appropriate modulation scheme: According to the characteristics of the wireless environment and channel state, select the most appropriate modulation method from the pre-built modulation prediction model. The modulation methods include but are not limited to QPSK, 16-QAM, and 64-QAM. Different modulation methods have different trade-offs between bandwidth utilization and noise resistance.

[0136] Signal mapping: Map the encoded bit stream to the corresponding constellation point to form a complex baseband signal. For example, in QPSK modulation, every two bits are mapped to one constellation point; and in 16-QAM, every four bits are mapped to one constellation point.

[0137] Carrier modulation: The baseband signal is loaded onto a high-frequency carrier to form a radio frequency signal suitable for propagation in a wireless channel.

[0138] These steps can convert the encoded digital information into an analog signal form that can be transmitted on the selected optimal working channel, preparing for actual data transmission.

[0139] S53: Send the modulated signal to the receiving end through the best working channel.

[0140] In this embodiment, the last step is to send the modulated signal to the receiving end through the previously selected optimal working channel. The specific implementation includes:

[0141] The modulated RF signal is sent out using an antenna. In order to ensure that the receiving end can correctly demodulate the received signal, the transmitting end also needs to provide necessary synchronization information, including but not limited to the preamble or training sequence. This information helps the receiver lock the signal and accurately restore the original data.

[0142] Embodiment 2

[0143] The present invention also provides a data processing system for near-field wireless transmission, which is used to execute a data processing method for near-field wireless transmission. Figure 2 As shown, the system comprises:

[0144] The environmental parameter acquisition module 100 is used to acquire environmental parameters of a short-distance communication area, wherein the environmental parameters include spectrum characteristics and wireless environment characteristics of the short-distance communication area.

[0145] The channel determination module 200 is used to select at least one candidate channel according to the spectrum characteristics, and determine the best working channel from the at least one candidate channel according to the wireless environment characteristics of the short-range communication area.

[0146] The strategy determination module 300 is used to determine an initial channel coding strategy according to the state characteristics of the best working channel, and adjust the initial channel coding strategy based on the wireless environment characteristics of the short-range communication area to obtain the best channel coding strategy.

[0147] The modulation mode determination module 400 is used to input the wireless environment characteristics of the short-range communication area and the state characteristics of the optimal working channel into a pre-built modulation prediction model to output the optimal signal modulation mode.

[0148] The sending module 500 is used to use the optimal channel coding strategy, the optimal signal modulation method and the optimal working channel to perform data encoding, signal modulation and signal sending in sequence on the data to be sent.

[0149] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems) and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0150] A person skilled in the art may understand that all or part of the steps in the various methods of the above embodiments may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, the storage medium including a read-only memory (ROM), a random access memory (RAM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), a one-time programmable read-only memory (OTPROM), an electronically-erasable programmable read-only memory (EEPROM), a compact disc (CD-ROM) or other optical disc storage, magnetic disk storage, magnetic tape storage, or any other computer-readable medium that can be used to carry or store data.

[0151] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

Claims

1. A data processing method for near-field wireless transmission, characterized in that: The method comprises the following steps: Acquiring environmental parameters of a short-distance communication area, wherein the environmental parameters include spectrum characteristics and wireless environment characteristics of the short-distance communication area; Specifically, the acquisition of environmental parameters includes: Collecting and analyzing spectrum characteristics including available frequency bands, spectrum occupancy status, and signal interference strength within the short-range communication area; Measuring and evaluating wireless environment characteristics including path loss value of signals, multipath effect parameter value of signals, degree of obstruction of obstacles on signal transmission path, and interference intensity of electromagnetic environment in the short-range communication area; Selecting at least one candidate channel according to the spectrum characteristics, and determining the best working channel from the at least one candidate channel according to the wireless environment characteristics of the short-range communication area; Determining an initial channel coding strategy according to the state characteristics of the optimal working channel, and adjusting the initial channel coding strategy based on the wireless environment characteristics of the short-range communication area to obtain an optimal channel coding strategy; Inputting the wireless environment characteristics of the short-range communication area and the state characteristics of the optimal working channel into a pre-built modulation prediction model, and outputting the optimal signal modulation mode; The optimal channel coding strategy, the optimal signal modulation method and the optimal working channel are used to perform data coding, signal modulation and signal transmission on the data to be transmitted in sequence.

2. A data processing method for near-field wireless transmission according to claim 1, characterized in that: The selecting at least one candidate channel according to the spectrum characteristics, and determining the best working channel from the at least one candidate channel according to the wireless environment characteristics of the short-range communication area, comprises: Based on the available frequency bands, spectrum occupancy status and signal interference strength in the spectrum characteristics, a set of candidate channels that meet preset spectrum conditions are screened out, wherein the preset spectrum conditions are to determine whether the channel is available, whether the spectrum occupancy rate of the channel is lower than a preset occupancy rate threshold, and whether the signal interference strength of the channel is lower than a preset interference threshold; According to a plurality of evaluation indicators determined by the wireless environment characteristics, an indicator evaluation is performed on the candidate channel set to obtain an evaluation result; Based on the evaluation result of the wireless environment characteristics, the best working channel is determined from the candidate channel set by a weighted scoring method.

3. The data processing method for near-field wireless transmission according to claim 2, characterized in that: The obtaining of the wireless environment characteristics includes: Measuring and calculating a path loss value of each candidate channel, wherein the path loss value is negatively correlated with the channel score; Analyzing a multipath effect parameter value of each candidate channel, wherein the multipath effect parameter value is negatively correlated with the channel score; Using a geographic information system combined with a building layout map, the signal propagation path of each candidate channel is simulated, and the degree of obstruction of the signal propagation path by obstacles is evaluated, wherein the degree of obstruction is negatively correlated with the channel score; The electromagnetic environment interference intensity of each candidate channel is monitored, wherein the electromagnetic environment interference intensity is negatively correlated with the channel score.

4. The data processing method for near-field wireless transmission according to claim 3, characterized in that: The step of determining the best working channel from the candidate channel set by a weighted scoring method based on the evaluation result of the wireless environment characteristics comprises: Pre-assign corresponding weight coefficients to each evaluation indicator; For each candidate channel, its weighted score is calculated using the following formula: in, Indicates The weighted score of candidate channels, Indicates The path loss value of candidate channels, Indicates The multipath effect parameter value of the candidate channel, Indicates The blocking degree of candidate channels, Indicates The electromagnetic environment interference strength of the candidate channels, , , and Respectively represent the weight coefficients of path loss value, multipath effect parameter value, blocking degree and electromagnetic environment interference intensity; The channel with the highest weighted score is selected from all candidate channels as the best working channel.

5. The method for processing data of near-field wireless transmission according to claim 4, characterized in that: The determining of the initial channel coding strategy according to the state characteristics of the best working channel, and adjusting the initial channel coding strategy based on the wireless environment characteristics of the short-range communication area to obtain the best channel coding strategy includes: Based on the spectrum efficiency, bit error rate and signal stability of the optimal working channel, preliminarily selecting a combination of a coding rate and a coding length from a preset mapping table as an initial channel coding strategy, wherein the preset mapping table is pre-established based on an empirical relationship between channel state characteristics and coding parameters; According to the path loss value, multipath effect parameter value, blocking degree and electromagnetic environment interference intensity, the coding rate and coding length of the initial channel coding strategy are adjusted to obtain the optimal channel coding strategy after the coding rate and coding length are adjusted.

6. A data processing method for near-field wireless transmission according to claim 5, characterized in that: The coding rate and coding length are adjusted according to the following formula: in, and are the coding rates before and after adjustment, and are the encoding lengths before and after adjustment, , , and They are path loss value, multipath effect parameter value, blocking degree and electromagnetic environment interference intensity, and their values ​​are equal to , , and , , , and is the corresponding adjustment coefficient in the coding rate adjustment, , , and is the corresponding adjustment coefficient in the code length adjustment, , , and They are respectively the maximum allowable values ​​of path loss value, multipath effect parameter value, blocking degree and electromagnetic environment interference intensity.

7. A data processing method for near-field wireless transmission according to claim 6, characterized in that: The step of inputting the wireless environment characteristics of the short-range communication area and the state characteristics of the optimal working channel into a pre-built modulation prediction model to output an optimal signal modulation mode includes: The wireless environment characteristics and the state characteristics of the optimal working channel are taken as input vectors and input into a pre-built modulation prediction model. The modulation prediction model calculates the applicability score of each modulation mode according to the input vector, and selects the modulation mode with the highest score as the optimal signal modulation mode. The modulation prediction model is a machine learning model that learns the mapping relationship between the wireless environment characteristics and the channel state characteristics and the optimal signal modulation mode.

8. The method for processing data of near-field wireless transmission according to claim 7, characterized in that: The using the optimal channel coding strategy, the optimal signal modulation mode and the optimal working channel to sequentially perform data coding, signal modulation and signal transmission on the data to be transmitted includes: According to the determined optimal channel coding strategy, encoding processing is performed on the data to be sent; Using the determined optimal signal modulation method, the encoded data is converted into a signal form suitable for transmission on the selected optimal working channel; The modulated signal is sent to the receiving end through the optimal working channel.

9. A data processing system for near-field wireless transmission, used to execute a data processing method for near-field wireless transmission according to any one of claims 1 to 8, characterized in that: The system comprises: An environmental parameter acquisition module, used to acquire environmental parameters of a short-distance communication area, wherein the environmental parameters include spectrum characteristics and wireless environment characteristics of the short-distance communication area; A channel determination module, configured to select at least one candidate channel according to the spectrum characteristics, and determine the best working channel from the at least one candidate channel according to the wireless environment characteristics of the short-range communication area; A strategy determination module, configured to determine an initial channel coding strategy according to the state characteristics of the optimal working channel, and adjust the initial channel coding strategy based on the wireless environment characteristics of the short-range communication area to obtain an optimal channel coding strategy; A modulation mode determination module, used to input the wireless environment characteristics of the short-range communication area and the state characteristics of the optimal working channel into a pre-built modulation prediction model, and output an optimal signal modulation mode; The sending module is used to use the optimal channel coding strategy, the optimal signal modulation method and the optimal working channel to perform data encoding, signal modulation and signal sending in sequence on the data to be sent.

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