Wireless transmission fault tolerance method and device based on cascade coding and dynamic interleaving

Abstract

The invention discloses a wireless transmission fault tolerance method and device based on cascade coding and dynamic interleaving, and mainly relates to the technical field of wireless transmission. Comprising the following steps: acquiring a transmission data set with priority labels at a sending end; performing data acquisition on the wireless transmission link based on a preset multi-dimensional channel state index to obtain a constructed channel state feature sequence; obtaining a signal burst risk assessment result; determining an error correction coding parameter and an interleaving parameter according to the signal burst risk assessment result; performing cascade error correction coding and adaptive interleaving to obtain interleaved data; and after the interleaving effect verification is passed, performing fault-tolerant wireless transmission on the interleaved data by using a wireless transmission link, and performing error correction decoding through a de-interleaver at a receiving end. The method has the advantages that the technical problems that in the prior art, under the complex wireless environment, the anti-interference capacity is poor, and data reliability and transmission efficiency are difficult to consider at the same time are solved, and the technical effect of improving wireless transmission fault-tolerant quality is achieved.

Description

Technical Field

[0001] This invention relates to the field of wireless transmission technology, and more specifically to a wireless transmission fault-tolerant method and apparatus based on concatenated coding and dynamic interleaving. Background Technology

[0002] With the development of medical electronics and wireless communication technologies, medical monitoring equipment is gradually becoming more portable and wearable. Typically, collected parameter data is transmitted in real-time to mobile terminals, gateway devices, or remote systems via wireless communication methods such as Bluetooth and Wi-Fi. Most existing wireless transmission links use fixed-frequency wireless communication methods, coupled with simple error correction or retransmission mechanisms to complete data transmission. Their system structure is relatively simple, with low power consumption and implementation cost, and therefore they are widely used in existing products.

[0003] However, in the process of implementing the technical solutions in the embodiments of the present invention, it was found that the above-mentioned technology has at least the following technical problems: In real-world applications, wireless transmission links are susceptible to factors such as human obstruction, electromagnetic interference, and transient switching of electrical appliances. Bit errors in wireless channels often exhibit a distinct burst characteristic, meaning that consecutive data bit errors occur within a short period of time.

[0004] Currently, commonly used error control methods mainly include Cyclic Redundancy Check (CRC) or simple forward error correction coding. Their main function is to detect or correct a small number of random bit errors, but they lack effective correction capabilities for long-term continuous burst errors generated in wireless channels. When burst interference occurs, multiple consecutive data bits or data blocks may be damaged simultaneously, making the entire data frame unrecoverable.

[0005] When transmitted data exhibits clear temporal continuity and structural characteristics, it becomes highly sensitive to continuous data errors. A sudden burst of errors can lead to the loss of critical feature information, thereby affecting subsequent data analysis.

[0006] Existing technologies typically fail to dynamically adjust error correction coding and interleaving strategies based on channel conditions, and also lack differentiated protection mechanisms for physiological data of different importance levels, making it difficult to simultaneously ensure data reliability and transmission efficiency in complex wireless environments. Summary of the Invention

[0007] This application provides a wireless transmission fault-tolerant method and apparatus based on concatenated coding and dynamic interleaving, which is used to address the technical problems in the prior art of poor anti-interference capability in complex wireless environments and difficulty in balancing data reliability and transmission efficiency.

[0008] In view of the above problems, this application provides a wireless transmission fault-tolerant method and apparatus based on concatenated coding and dynamic interleaving.

[0009] The first aspect of this application provides a wireless transmission fault-tolerant method based on concatenated coding and dynamic interleaving, the method comprising: The process involves: acquiring a set of transmission data with priority tags at the transmitting end, wherein the transmission data set includes a priority transmission data set and a regular transmission data set; collecting data from the wireless transmission link based on preset multi-dimensional channel state indicators to obtain a constructed channel state feature sequence, wherein the preset multi-dimensional channel state indicators include signal-to-noise ratio, received signal strength, instantaneous bit error rate, maximum bit error length, and number of retransmissions; performing a fast-slow interactive channel burst risk assessment on the channel state feature sequence to obtain a signal burst risk assessment result; determining error correction coding parameters and interleaving parameters based on the signal burst risk assessment result; using the error correction coding parameters to perform concatenated error correction coding on the priority transmission data set and the regular transmission data set, and then adaptively interleaving the encoded priority transmission coded data set and the regular transmission coded data set through an interleaver according to the interleaving parameters to obtain interleaved data; verifying the interleaving effect of the interleaved data; and, after the interleaving effect verification is passed, using the wireless transmission link to perform fault-tolerant wireless transmission of the interleaved data, and then performing error correction decoding through the deinterleaver at the receiving end.

[0010] In one possible implementation, a fast-slow interactive channel burst risk assessment is performed on the channel state feature sequence to obtain a signal burst risk assessment result. This includes: extracting data from the channel state feature sequence using both slow and fast timescales to obtain slow-timescale signal feature subsequences and fast-timescale signal feature subsequences; extracting features from the slow-timescale signal feature subsequences using a slow-timescale feature extraction unit to obtain slow-timescale risk features; extracting features from the fast-timescale signal feature subsequences using a fast-timescale feature extraction unit to obtain fast-timescale risk features; dynamically modulating the slow-timescale risk features using the fast-timescale risk features as weighting factors to obtain comprehensive signal burst risk features; and performing a risk assessment based on the comprehensive signal burst risk features to obtain a signal burst risk assessment result.

[0011] In one possible implementation, data extraction of the channel state feature sequence is performed using both slow and fast time scales to obtain slow-time-scale signal feature subsequences and fast-time-scale signal feature subsequences. This includes: constructing a feature fluctuation curve based on the channel state feature sequence, where the horizontal axis of the feature fluctuation curve represents time and the vertical axis represents channel state features; extracting the inflection point set of the feature fluctuation curve and calculating the interval between two adjacent inflection points to obtain a candidate time scale set; using the maximum value in the candidate time scale set as the fast time scale and the minimum value in the candidate time scale set as the slow time scale.

[0012] In one possible implementation, determining error correction coding parameters and interleaving parameters based on the signal burst risk assessment results includes: retrieving a pre-constructed parameter mapping table based on the signal burst risk assessment results to obtain error correction coding parameters and basic interleaving parameters; routinely identifying the basic interleaving parameters; enhancing the basic interleaving parameters according to a preset enhancement threshold to obtain priority interleaving parameters, wherein the priority interleaving parameters have priority identifiers; and summarizing the basic interleaving parameters and priority interleaving parameters to obtain the interleaving parameters.

[0013] In one possible implementation, the concatenated error correction coding includes an inner code and an outer code; wherein the inner code is a convolutional code or a Turbo code, used to correct random error codes; and the outer code is a Reed-Solomon code, used to correct residual clustering error codes after the inner code is decoded.

[0014] In one possible implementation, verifying the interleaving effect of the interleaved data includes: before performing concatenated error correction coding at the transmitting end, establishing a source data logical index identifier for each coding unit to obtain a set of source data logical index identifiers, wherein each source data logical index identifier is used to characterize the relative position of the corresponding coding unit in the source data space, and is obtained by numbering the source data in chronological order; obtaining the interleaving space position recorded for each coding unit after interleaving to obtain a set of interleaving space positions; mapping the source data logical index identifier set to the interleaving space position set to construct an interleaving structure feature set; and verifying the interleaving effect of the interleaved data based on the interleaving structure feature set to obtain an interleaving effect verification result, wherein the interleaving effect verification result includes verification passed or verification failed.

[0015] In one possible implementation, the interleaving effect is verified based on the interleaving structure feature set to obtain an interleaving effect verification result, including: using the interleaving spatial location as an index, performing nearest neighbor aggregation on the interleaving structure feature set to obtain multiple aggregated interleaving structure feature sets; traversing the multiple aggregated interleaving structure feature sets and performing pairwise enumeration within each set to obtain multiple aggregated interleaving structure feature enumeration combination sets; using the source data logical index identifier as an index, performing set-based dispersion identification on the multiple aggregated interleaving structure feature enumeration combination sets to obtain a consolidation dispersion coefficient; and based on the consolidation dispersion coefficient, determining whether the coding units from adjacent positions still exhibit a clustered distribution in the interleaving space, and obtaining the interleaving effect verification result based on the determination result.

[0016] In one possible implementation, using the source data logical index identifier as an index, the multiple sets of aggregated and interwoven structural feature enumeration combinations are subjected to in-set dispersion identification to obtain an integrated dispersion coefficient. This includes: traversing the multiple sets of aggregated and interwoven structural feature enumeration combinations to identify differences in logical index identifiers of combined metadata, obtaining multiple sets of combined identifier differences; performing mean shift filtering on the multiple sets of combined identifier differences to determine multiple filtered combined identifier differences, and using the multiple filtered combined identifier differences as multiple in-set dispersion coefficients; determining multiple dispersion integration weights based on the number of combinations within each set in the multiple sets of aggregated and interwoven structural feature enumeration combinations; and performing weighted analysis on the multiple in-set dispersion coefficients based on the multiple dispersion integration weights to obtain the integrated dispersion coefficient.

[0017] In one possible implementation, based on the integration dispersion coefficient, it is determined whether the coding units from adjacent positions still exhibit a clustered distribution in the interleaving space, and the interleaving effect verification result is obtained based on the determination result, including: determining whether the integration dispersion coefficient is greater than or equal to a preset dispersion coefficient threshold; if yes, the interleaving effect verification result is verified as passed; if no, the interleaving effect verification result is verified as failed.

[0018] A second aspect of this application provides a wireless transmission fault-tolerant device based on concatenated coding and dynamic interleaving, the device comprising: A transmission data acquisition module is used to acquire a transmission data set with priority tags from the transmitting end, wherein the transmission data set includes a priority transmission data set and a regular transmission data set; a channel state feature sequence acquisition module is used to collect data from the wireless transmission link based on preset multi-dimensional channel state indicators to obtain a constructed channel state feature sequence, wherein the preset multi-dimensional channel state indicators include signal-to-noise ratio, received signal strength, instantaneous bit error rate, maximum bit error length, and retransmission count; a risk assessment module is used to perform fast and slow interactive channel burst risk assessment on the channel state feature sequence to obtain a signal burst risk assessment result; a parameter determination module... The system comprises a block for determining error correction coding parameters and interleaving parameters based on the signal burst risk assessment results; an interleaving data acquisition module for performing concatenated error correction coding on the priority transmission data set and the regular transmission data set using the error correction coding parameters, and adaptively interleaving the encoded priority transmission coded data set and the regular transmission coded data set through an interleaver according to the interleaving parameters to obtain interleaved data; and a fault-tolerant wireless transmission module for verifying the interleaving effect of the interleaved data. When the interleaving effect verification is successful, the interleaved data is transmitted wirelessly with fault tolerance using a wireless transmission link, and error correction decoding is performed by the deinterleaver at the receiving end.

[0019] One or more technical solutions provided in this application have at least the following technical effects or advantages: This application obtains a set of transmission data with priority tags at the transmitting end, including a priority transmission data set and a regular transmission data set; it collects data from the wireless transmission link based on preset multi-dimensional channel state indicators to obtain a constructed channel state feature sequence, where the preset multi-dimensional channel state indicators include signal-to-noise ratio, received signal strength, instantaneous bit error rate, maximum bit error length, and number of retransmissions; it performs a fast-slow interactive channel burst risk assessment on the channel state feature sequence to obtain a signal burst risk assessment result; it determines error correction coding parameters and interleaving parameters based on the signal burst risk assessment result; it uses the error correction coding parameters to perform concatenated error correction coding on the priority transmission data set and the regular transmission data set, and then adaptively interleaves the encoded priority transmission data set and the regular transmission data set according to the interleaving parameters through an interleaver to obtain interleaved data; it verifies the interleaving effect of the interleaved data, and when the interleaving effect verification is successful, it uses the wireless transmission link to perform fault-tolerant wireless transmission of the interleaved data, and performs error correction decoding through the deinterleaver at the receiving end. This achieves the technical effect of improving wireless transmission quality in complex wireless environments. Attached Figure Description

[0020] Appendix Figure 1 This is a schematic diagram of the wireless transmission fault tolerance method based on concatenated coding and dynamic interleaving provided in an embodiment of the present invention.

[0021] Appendix Figure 2 This is a schematic diagram of the structure of a wireless transmission fault-tolerant device based on concatenated coding and dynamic interleaving provided in an embodiment of the present invention.

[0022] The labels shown in the attached diagram: Transmission data acquisition module 11, channel state feature sequence acquisition module 12, risk assessment module 13, parameter determination module 14, interleaved data acquisition module 15, and fault-tolerant wireless transmission module 16. Detailed Implementation

[0023] The present invention will be further illustrated below with reference to specific embodiments. It should be understood that these embodiments are for illustrative purposes only and are not intended to limit the scope of the invention. Furthermore, it should be understood that after reading the teachings of this invention, those skilled in the art can make various alterations or modifications to the invention, and these equivalent forms also fall within the scope defined by the appended claims. It should be noted that the terms "comprising" and "having" are intended to cover non-exclusive inclusion; for example, a process, method, apparatus, product, or server that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or modules not explicitly listed or inherent to these processes, methods, products, or devices.

[0024] Example 1, as shown in the appendix Figure 1 As shown, this application provides a wireless transmission fault-tolerant method based on concatenated coding and dynamic interleaving, wherein the method includes: A1: Obtain the set of transmission data with priority tags from the sending end, wherein the set of transmission data includes a priority transmission data set and a regular transmission data set; In one embodiment, the transmitting end refers to a medical monitoring device used to collect and transmit physiological parameter data, such as an electrocardiogram (ECG) monitor, a blood oxygen monitoring device, or a blood pressure monitoring terminal. The transmitted data set refers to the physiological data that has undergone basic acquisition and formatting processing and is to be transmitted by the transmitting end via a wireless link. Priority tags are identification information set to distinguish data of different importance, used to characterize the differences in transmission reliability requirements of corresponding data. For example, if the R-wave position information in the ECG waveform undergoes deeper interleaving and stronger forward error correction, while standard protection is used for waveform details, then the R-wave position information is priority transmission data, and the waveform details are regular transmission data.

[0025] Before framing, the application layer or presentation layer software / firmware at the sending end calls a priority tagging module. This module, based on signal processing algorithms such as real-time QRS detection or event triggers (e.g., outputting an alarm for blood oxygen saturation below a threshold), adds a priority tag header to each data packet or data block to be transmitted, for example, an ECG frame containing 256 sampling points. A data packet structure might be: [tag: 0x01 (indicating priority) | timestamp | data payload...]. Subsequently, the data packets are routed to different logical buffers according to the tags, forming two sets to be processed: the priority transmission data set and the regular transmission data set. These are then aggregated to obtain the transmission data set. This achieves the technical effect of providing input and operational objects for subsequent differentiated fault-tolerant protection.

[0026] A2: Data is collected from the wireless transmission link based on preset multi-dimensional channel state indicators to obtain a channel state feature sequence. The preset multi-dimensional channel state indicators include signal-to-noise ratio, received signal strength, instantaneous bit error rate, maximum bit error length, and number of retransmissions. It should be noted that multidimensional channel state indicators refer to a set of quantitative parameters obtained from different protocol layers such as the physical layer and data link layer, which can characterize the instantaneous quality and error modes of the wireless link from multiple perspectives. These parameters include signal-to-noise ratio, received signal strength, instantaneous bit error rate, maximum bit error length, and number of retransmissions.

[0027] At the transmitting end, the signal-to-noise ratio and received signal strength indication are periodically read from the physical layer driver, such as 10 times per second. Simultaneously, the instantaneous bit error rate, the maximum consecutive length of bit errors detected in the past cycle, and the number of retransmissions due to frame errors are read from the error statistics module of the data link layer. These values ​​are encapsulated into a feature vector with a precise timestamp. As data acquisition continues, the feature vector is arranged chronologically to obtain a channel state feature sequence containing multi-dimensional information.

[0028] A3: Perform fast and slow interactive channel burst risk assessment on the channel state feature sequence to obtain signal burst risk assessment results; Furthermore, a fast-slow interactive channel burst risk assessment is performed on the channel state feature sequence to obtain a signal burst risk assessment result. Step A3 in this embodiment of the application further includes: The channel state feature sequence is extracted using both slow and fast time scales to obtain slow-time-scale signal feature subsequences and fast-time-scale signal feature subsequences. The slow time-scale feature extraction unit is used to extract features from the feature subsequence of the slow time-scale signal to obtain slow time-scale risk features; The fast timescale feature extraction unit is used to extract features from the fast timescale signal feature subsequence to obtain fast timescale risk features; By using fast-timescale risk characteristics as weighting factors, slow-timescale risk characteristics are dynamically modulated to obtain comprehensive signal burst risk characteristics. Risk assessment is then conducted based on these comprehensive signal burst risk characteristics to obtain signal burst risk assessment results.

[0029] Furthermore, by invoking both slow and fast time scales to extract data from the channel state feature sequence, slow-time-scale signal feature subsequences and fast-time-scale signal feature subsequences are obtained. In this embodiment, step A3 further includes: A feature fluctuation curve is constructed based on the channel state feature sequence, wherein the horizontal axis of the feature fluctuation curve is time and the vertical axis is the channel state feature. Extract the set of inflection points of the characteristic fluctuation curve and count the time interval between two adjacent inflection points to obtain a set of candidate time scales; The maximum value in the candidate timescale set is taken as the fast timescale, and the minimum value in the candidate timescale set is taken as the slow timescale.

[0030] In one embodiment, the time scale refers to the length of the time window or the data sampling interval used when analyzing data. A slow time scale corresponds to a longer time window, such as several seconds to tens of seconds, used to capture slow-changing characteristics such as long-term trends in channel conditions and background noise levels. A fast time scale corresponds to a shorter time window, such as hundreds of milliseconds, used to capture rapid-changing characteristics such as instantaneous jitter and sudden interference in the channel.

[0031] Based on the channel state feature sequence system, the characteristic fluctuation curves of the features changing over time are plotted. By finding the zero-crossing points of the first derivative of the curve or using inflection point detection algorithms, such as linear fitting based on a sliding window to determine the change in the slope sign, a set of inflection points of the curve is extracted. Each inflection point marks the moment when the signal operating state undergoes a significant change.

[0032] By calculating the time interval between adjacent inflection points, a candidate time scale set is obtained, such as 1.2s, 0.3s, 2.1s, and 0.5s. The maximum value of 2.1s is taken as the slow time scale, and the minimum value of 0.3s is taken as the fast time scale. Then, with window lengths of 2.1s and 0.3s respectively, a moving average or downsampling is performed on the original sequence to obtain the slow time scale signal feature subsequence and the fast time scale signal feature subsequence.

[0033] The feature extraction unit processes these two subsequences. For the slow-timescale subsequence, the 90th percentile of each feature is calculated over a longer period, such as the past 30 seconds. Statistical values ​​show that the maximum bit error length is less than 80 bits in 90% of cases, thus obtaining the slow-timescale risk feature, which characterizes the typical worst-case scenario that the channel may experience over a longer period. For the fast-timescale subsequence, its rapidly changing features, such as instantaneous jitter or sudden interference, are calculated within the current and recent fast-timescale periods. For example, if the peak value exceeds 100 bits in four of the last ten 0.3-second windows, this proportion is used as the fast-timescale risk feature, characterizing the current activity level of sudden errors.

[0034] Using fast-timescale risk characteristics as weighting factors, a weighting coefficient w = 1 + a * fast-timescale risk characteristics is defined, where 'a' is an adjustment factor. This coefficient is used to weight slow-timescale risk characteristics to obtain comprehensive signal burst risk characteristics. Finally, based on a pre-defined risk level table, such as: comprehensive characteristic value <50 bits for low risk, 50-150 bits for medium risk, and >150 bits for high risk, the signal burst risk assessment result is obtained.

[0035] By employing multi-scale analysis and interactive weighting, the time-varying characteristics of the channel, including slow-changing trends and rapid-changing impacts, are organically combined. This facilitates the differentiation between persistent mild interference and transient severe bursts, thereby enabling more accurate risk assessments. For instance, even if the current instantaneous bit error rate is not high, if the fast timescale shows abnormally active bursts (i.e., high weighting), the risk level will be increased.

[0036] A4: Determine the error correction coding parameters and interleaving parameters based on the signal burst risk assessment results; Furthermore, based on the signal burst risk assessment results, error correction coding parameters and interleaving parameters are determined. In this embodiment, step A4 further includes: Based on the signal burst risk assessment results, a pre-constructed parameter mapping table is retrieved to obtain error correction coding parameters and basic interleaving parameters; The basic interleaving parameters are conventionally labeled; the basic interleaving parameters are enhanced according to a preset enhancement threshold to obtain the preferred interleaving parameters, wherein the preferred interleaving parameters have a priority label; The interleaving parameters are obtained by summing the basic interleaving parameters and the preferred interleaving parameters.

[0037] Furthermore, the cascaded error correction code includes an inner code and an outer code; The inner code is a convolutional code or a Turbo code, used to correct random error codes; The outer code is a Reed-Solomon code, used to correct residual clustering errors after decoding the inner code.

[0038] It should be noted that the pre-constructed parameter mapping table is a lookup table pre-calibrated by those skilled in the art through theoretical analysis, simulation testing, and field experiments. It maps different signal burst risk assessment results to a set of optimal or suboptimal error correction coding parameters and basic interleaving parameters. Error correction coding parameters typically refer to the code rate of the inner and outer codes, i.e., the ratio of information bits to the total code length. The lower the code rate, the higher the redundancy and the stronger the error correction capability. Basic interleaving parameters mainly refer to the interleaving depth during the interleaving process, understood as the number of rows / columns of the interleaver, determining the degree to which data is scrambled and dispersed. The preset enhancement threshold is an amplification factor pre-set by those skilled in the art, used to generate stronger protection parameters for the priority data set on top of the basic interleaving parameters. The parameter mapping table is shown in Table 1.

[0039] Table 1 Parameter Mapping Table

[0040] Assuming the threshold rule is that the preferred data interleaving depth is 1.5 times the base interleaving depth, the preset enhancement threshold is 1.5. For example, when the base interleaving depth is 16 rows, the calculated preferred interleaving parameter is 24 rows, and this parameter is given a priority identifier. The interleaving parameter is obtained by summing the base interleaving parameter and the preferred interleaving parameter.

[0041] Meanwhile, during concatenated error correction coding, convolutional codes or Turbo codes are used for the inner code. These two code types exhibit excellent error correction performance close to the theoretical limit for randomly distributed bit errors in additive white Gaussian noise channels. The outer code uses Reed-Solomon codes, a non-binary block code specifically designed for burst errors or byte errors, which can effectively correct clusters of errors that may remain after decoding the inner code. For example, a (255, 223) Reed-Solomon code can correct 16-byte errors at any position within a codeword.

[0042] A5: Use the error correction coding parameters to perform concatenated error correction coding on the priority transmission data set and the regular transmission data set, and then use an interleaver to adaptively interleave the encoded priority transmission data set and the regular transmission data set according to the interleaving parameters to obtain interleaved data; It should be noted that during concatenated error correction coding, according to the error correction coding parameters, such as an inner code rate of 1 / 2 and an outer code rate of 0.8, two consecutive encoding operations are performed on the priority transmission data set and the regular transmission data set. First, the inner code encoder, such as a convolutional code encoder, processes the original data block, adding redundancy to correct random errors. Then, the outer code encoder, such as an RS encoder, re-encodes the entire data block after the inner code encoding, adding another layer of redundancy, specifically for correcting errors that cannot be handled by the inner code and that occur in clusters.

[0043] For example, when the original data packet from the regular transport data set is 200 bits, it is encoded using a convolutional code with an inner code rate of 1 / 2, resulting in an output of 400 bits. Then, these 400 bits are treated as a group of symbols using an RS code with an outer code rate of 0.8, for example, divided into 40 10-bit symbols for encoding. Assuming a 20% increase in redundancy, the final output is a 480-bit regular transport encoded data block. For priority transport data sets, due to their importance, more protective encoding parameters may be used, such as an inner code rate of 1 / 3 and an outer code rate of 0.7, generating a priority transport encoded data block with higher redundancy and a longer length.

[0044] The encoded priority transmission data set and the regular transmission data set are fed into an interleaver. Internally, the interleaver maintains two logically independent interleaving matrices or employs two different interleaving algorithms, corresponding to the regular transmission data and the priority transmission data, respectively. For example, for regular transmission data, a 16-row block interleaving is used, writing 480 bits of data row-by-row into a 16x30 matrix. After filling, the data is read column-by-column, thus distributing the originally continuous data bits to positions at least 16 bit intervals apart on the transmission time axis. For transmission data, a 24-row block interleaving is used, which has a stronger dispersion effect. This yields the interleaved data.

[0045] For example, suppose a key byte in the priority data block, such as the value 0x55 representing the heart rate, has the binary 01010101 arranged consecutively in the original coded block. After 24 lines of deep interleaving, these 8 bits will be distributed across 24 different time slices that are far apart in the transmission frame.

[0046] A6: Verify the interleaving effect of the interleaved data. After the interleaving effect verification is passed, use the wireless transmission link to perform fault-tolerant wireless transmission of the interleaved data, and perform error correction and decoding through the deinterleaver at the receiving end.

[0047] Furthermore, to verify the interleaving effect of the interleaved data, step A6 of this embodiment further includes: Before performing concatenated error correction coding at the transmitting end, a source data logical index identifier is established for each coding unit to obtain a set of source data logical index identifiers. Each source data logical index identifier is used to characterize the relative position of the corresponding coding unit in the source data space, and is obtained by numbering the source data in chronological order. Obtain the interleaving space location of each coding unit recorded after interleaving, and obtain the set of interleaving space locations; Based on the mapping between the source data logical index identifier set and the interleaving spatial location set, an interleaving structure feature set is constructed; The interleaving effect is verified based on the interleaving structure feature set to obtain the interleaving effect verification result, wherein the interleaving effect verification result includes verification passed or verification failed.

[0048] It should be noted that the coding unit here refers to the smallest data granularity for concatenated coding operations, which can typically be an external codeword, such as an RS code block. The source data logical index identifier is a unique, ordered sequence number assigned to each coding unit, such as 1, 2, 3..., used to mark the unit's temporal order or logical position in the original data stream before encoding and interleaving. The interleaving spatial position refers to the new position number of each coding unit in the generated interleaved data stream after rearrangement by the interleaver, i.e., the transmission order. The interleaving structure feature set is a set of data pairs consisting of (source data logical index identifier, interleaving spatial position), which completely records the permutation or rearrangement process performed by the interleaver.

[0049] In one embodiment, an incremental logical index is appended to each coding unit before encoding. For example, there are 10 coding units, and their source data logical index identifier set is S = {1, 2, 3, ..., 10}. After encoding, these units are fed into an interleaver. During processing, the interleaver records the new position of each input unit in the output interleaved data stream. Assume that after interleaving, the set of interleaved spatial positions is P = {23, 5, 17, 9, 1, 30, 12, 4, 28, 16}, where the position number represents the time slice number in the final transmitted frame. Thus, the interleaved structure feature set F = {(1,23), (2,5), (3,17), (4,9), (5,1), (6,30), (7,12), (8,4), (9,28), (10,16)} can be constructed.

[0050] Next, the system analyzes whether logically adjacent units in the source data, such as indices 1 and 2, or 2 and 3, are also very close in position in the interleaving space. A dispersion threshold is preset by those skilled in the art, for example, requiring the average position difference to be greater than half the total number of units. If the calculation result meets the threshold, the interleaving verification is considered successful; otherwise, the verification fails, potentially triggering an alarm or requiring re-interleaving with alternative parameters.

[0051] Furthermore, based on the interlacing structure feature set, the interlacing effect of the interlacing data is verified to obtain the interlacing effect verification result. Step A6 of this embodiment further includes: Using the interlacing spatial location as an index, the set of interlacing structural features is aggregated to obtain multiple aggregated sets of interlacing structural features; By iterating through the multiple sets of aggregated and interwoven structural features, each set is enumerated pairwise to obtain a set of multiple enumerated combinations of aggregated and interwoven structural features. Using the source data logical index identifier as an index, the set of multiple aggregated and interwoven structural features is enumerated and combined to identify the dispersion within the set, and the integration dispersion coefficient is obtained. Based on the integration dispersion coefficient, it is determined whether the coding units from adjacent positions still exhibit a clustered distribution in the interleaving space, and the interleaving effect verification result is obtained based on the judgment result.

[0052] In one embodiment, the interleaving structure feature set is read and sorted according to the interleaving spatial position values. Then, according to a preset proximity determination rule—that is, if the absolute value of the difference between position numbers is less than or equal to a dynamic threshold—it is added to an aggregated interleaving structure feature set, thus obtaining multiple aggregated interleaving structure feature sets. Each aggregated interleaving structure feature set represents a data block that is temporally continuous or close to each other in the final transmitted frame.

[0053] Iterate through multiple aggregated-intertwined structural feature sets, generating pairwise enumeration combinations of all elements within each set, forming multiple sets of aggregated-intertwined structural feature enumeration combinations. For each aggregated-intertwined structural feature enumeration combination, calculate the absolute value of the difference between the source data logical index identifiers corresponding to its two elements. For a given aggregate set, its internal dispersion can be measured by calculating the statistical characteristics of all such index differences, such as the minimum, average, or proportion below a certain threshold.

[0054] Furthermore, using the source data logical index identifier as an index, the set of multiple aggregated interwoven structural feature enumeration combinations is used to identify the dispersion within the set, and the integration dispersion coefficient is obtained. Step A6 in this embodiment of the application also includes: Traverse the multiple aggregated and interwoven structural feature enumeration combination sets to perform combined metadata logical index identifier difference identification, and obtain multiple combined identifier difference sets; The mean shift filter is applied to the multiple sets of combined identifier differences to determine multiple filtered combined identifier differences, and the multiple filtered combined identifier differences are respectively used as the dispersion coefficients within the multiple sets. Based on the multiple aggregated and interwoven structural features, enumerate the combination quantity within each set in the combination set to determine multiple decentralized integration weights; The dispersion coefficients within the multiple sets are weighted and analyzed based on the multiple dispersion integration weights to obtain the integrated dispersion coefficients.

[0055] Furthermore, based on the integration dispersion coefficient, it is determined whether the coding units from adjacent positions still exhibit a clustered distribution in the interleaving space, and the interleaving effect verification result is obtained based on the determination result. Step A6 of this embodiment further includes: Determine whether the integration dispersion coefficient is greater than or equal to a preset dispersion coefficient threshold. If so, the interleaving effect verification result is "verification passed". If not, the verification result for the interleaving effect is "verification failed".

[0056] Preferably, multiple aggregated interleaved structural feature enumeration combination sets are traversed, and arithmetic operations are performed on each binary combination within the set to calculate the absolute value of the difference between its two source data logical index identifiers, thereby generating an original combination identifier difference set for each aggregated set. The combination identifier difference set reflects the distance distribution of all data pairs in the original sequence within the neighborhood of that specific transmission time.

[0057] Subsequently, a mean-shift filtering algorithm is applied to multiple sets of combined identifier differences. This algorithm iteratively finds the maximum local data density, automatically identifies the main pattern of the difference distribution (i.e., the mode region), and filters out data points falling within this high-density region. Then, a central tendency statistic, such as the median or mean, is calculated from these filtered core data points and used as the filtered combined identifier differences for the aggregate set. This effectively eliminates the interference of a few outlier small differences, which may come from boundary data not fully dispersed by the interleaving algorithm, ensuring the robustness and representativeness of the obtained dispersion coefficient. The filtered differences are then used as the dispersion coefficient within the set.

[0058] Based on the number of binary combinations contained in each aggregation set, its corresponding dispersion integration weight is calculated through normalization. The weight is proportional to the number of combinations, so that aggregation-interleaved structure feature enumeration combination sets with larger data volume and thus occupying a longer continuous time in the transmission frame have a higher importance in the final evaluation.

[0059] Finally, a weighted analysis is performed, multiplying the dispersion coefficient within each aggregation set by its corresponding weight and summing the results to obtain the integrated dispersion coefficient. The integrated dispersion coefficient is a scalar value that integrates the data dispersion of all transmission neighborhoods in the entire interleaved data stream. Its value directly and quantitatively characterizes the interleaving scheme's ability to resist the common loss of original associated data due to transmission continuity.

[0060] The integration dispersion coefficient is compared with a preset dispersion coefficient threshold set by those skilled in the art. If the integration dispersion coefficient is greater than or equal to the preset dispersion coefficient threshold, the interleaving is deemed to have effectively dispersed the data, and the verification passes; otherwise, the interleaving effect is deemed poor, and the original adjacent data remains clustered in the transmission stream, and the verification fails. This achieves the technical effect of providing the sending end with accurate data basis for determining whether to continue transmission or readjust the interleaving strategy, thereby ensuring the inherent robustness of the final transmitted data in the face of sudden interference.

[0061] Example 2, based on the same inventive concept as the wireless transmission fault-tolerant method based on concatenated coding and dynamic interleaving in the foregoing examples, is as follows: Figure 2As shown, this application provides a wireless transmission fault-tolerant device based on concatenated coding and dynamic interleaving. The device and method embodiments in this application are based on the same inventive concept. The device includes: The data acquisition module 11 is used to acquire a set of transmission data with priority tags from the sending end, wherein the set of transmission data includes a priority transmission data set and a regular transmission data set. The channel state feature sequence acquisition module 12 is used to collect data from the wireless transmission link based on preset multi-dimensional channel state indicators to obtain a constructed channel state feature sequence. The preset multi-dimensional channel state indicators include signal-to-noise ratio, received signal strength, instantaneous bit error rate, maximum bit error length, and number of retransmissions. Risk assessment module 13 is used to perform fast and slow interactive channel burst risk assessment on the channel state feature sequence to obtain signal burst risk assessment results; Parameter determination module 14 is used to determine error correction coding parameters and interleaving parameters based on the signal burst risk assessment results; Interleaved data acquisition module 15 is used to perform concatenated error correction coding on the priority transmission data set and the regular transmission data set using the error correction coding parameters, and to adaptively interleave the encoded priority transmission coded data set and the regular transmission coded data set through an interleaver according to the interleaving parameters to obtain interleaved data; The fault-tolerant wireless transmission module 16 is used to verify the interleaving effect of the interleaved data. After the interleaving effect verification is passed, the interleaved data is transmitted wirelessly with fault tolerance using a wireless transmission link, and error correction and decoding are performed by the deinterleaver at the receiving end.

[0062] Furthermore, the risk assessment module 13 is used to perform the following steps: The channel state feature sequence is extracted using both slow and fast time scales to obtain slow-time-scale signal feature subsequences and fast-time-scale signal feature subsequences. The slow time-scale feature extraction unit is used to extract features from the feature subsequence of the slow time-scale signal to obtain slow time-scale risk features; The fast timescale feature extraction unit is used to extract features from the fast timescale signal feature subsequence to obtain fast timescale risk features; By using fast-timescale risk characteristics as weighting factors, slow-timescale risk characteristics are dynamically modulated to obtain comprehensive signal burst risk characteristics. Risk assessment is then conducted based on these comprehensive signal burst risk characteristics to obtain signal burst risk assessment results.

[0063] Furthermore, the risk assessment module 13 is used to perform the following steps: A feature fluctuation curve is constructed based on the channel state feature sequence, wherein the horizontal axis of the feature fluctuation curve is time and the vertical axis is the channel state feature. Extract the set of inflection points of the characteristic fluctuation curve and count the time interval between two adjacent inflection points to obtain a set of candidate time scales; The maximum value in the candidate timescale set is taken as the fast timescale, and the minimum value in the candidate timescale set is taken as the slow timescale.

[0064] Furthermore, the parameter determination module 14 is used to perform the following steps: Based on the signal burst risk assessment results, a pre-constructed parameter mapping table is retrieved to obtain error correction coding parameters and basic interleaving parameters; The basic interleaving parameters are conventionally labeled; the basic interleaving parameters are enhanced according to a preset enhancement threshold to obtain the preferred interleaving parameters, wherein the preferred interleaving parameters have a priority label; The interleaving parameters are obtained by summing the basic interleaving parameters and the preferred interleaving parameters.

[0065] Furthermore, the cascaded error correction code includes an inner code and an outer code; The inner code is a convolutional code or a Turbo code, used to correct random error codes; The outer code is a Reed-Solomon code, used to correct residual clustering errors after decoding the inner code.

[0066] Furthermore, the fault-tolerant wireless transmission module 16 is used to perform the following steps: Before performing concatenated error correction coding at the transmitting end, a source data logical index identifier is established for each coding unit to obtain a set of source data logical index identifiers. Each source data logical index identifier is used to characterize the relative position of the corresponding coding unit in the source data space, and is obtained by numbering the source data in chronological order. Obtain the interleaving space location of each coding unit recorded after interleaving, and obtain the set of interleaving space locations; Based on the mapping between the source data logical index identifier set and the interleaving spatial location set, an interleaving structure feature set is constructed; The interleaving effect is verified based on the interleaving structure feature set to obtain the interleaving effect verification result, wherein the interleaving effect verification result includes verification passed or verification failed.

[0067] Furthermore, the fault-tolerant wireless transmission module 16 is used to perform the following steps: Using the interlacing spatial location as an index, the set of interlacing structural features is aggregated to obtain multiple aggregated sets of interlacing structural features; By iterating through the multiple sets of aggregated and interwoven structural features, each set is enumerated pairwise to obtain a set of multiple enumerated combinations of aggregated and interwoven structural features. Using the source data logical index identifier as an index, the set of multiple aggregated and interwoven structural features is enumerated and combined to identify the dispersion within the set, and the integration dispersion coefficient is obtained. Based on the integration dispersion coefficient, it is determined whether the coding units from adjacent positions still exhibit a clustered distribution in the interleaving space, and the interleaving effect verification result is obtained based on the judgment result.

[0068] Furthermore, the fault-tolerant wireless transmission module 16 is used to perform the following steps: Traverse the multiple aggregated and interwoven structural feature enumeration combination sets to perform combined metadata logical index identifier difference identification, and obtain multiple combined identifier difference sets; The mean shift filter is applied to the multiple sets of combined identifier differences to determine multiple filtered combined identifier differences, and the multiple filtered combined identifier differences are respectively used as the dispersion coefficients within the multiple sets. Based on the multiple aggregated and interwoven structural features, enumerate the combination quantity within each set in the combination set to determine multiple decentralized integration weights; The dispersion coefficients within the multiple sets are weighted and analyzed based on the multiple dispersion integration weights to obtain the integrated dispersion coefficients.

[0069] Furthermore, the fault-tolerant wireless transmission module 16 is used to perform the following steps: Determine whether the integration dispersion coefficient is greater than or equal to a preset dispersion coefficient threshold. If so, the interleaving effect verification result is "verification passed". If not, the verification result for the interleaving effect is "verification failed".

[0070] It should be noted that the order of the embodiments described above is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. Furthermore, the above description focuses on specific embodiments of this specification. Additionally, the processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired results. In some implementations, multitasking and parallel processing are possible or may be advantageous.

[0071] The above description is only a preferred embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

[0072] This specification and accompanying drawings are merely illustrative examples of this application and are intended to cover any and all modifications, variations, combinations, or equivalents within the scope of this application. Clearly, those skilled in the art can make various alterations and modifications to this application without departing from its scope. Therefore, if such modifications and modifications fall within the scope of this application and its equivalents, this application intends to include such modifications and modifications.

Claims

1. A wireless transmission fault-tolerant method based on concatenated coding and dynamic interleaving, characterized in that, The method includes: Obtain the transmission data set with priority tags from the sending end, wherein the transmission data set includes a priority transmission data set and a regular transmission data set; Data is collected from the wireless transmission link based on preset multidimensional channel state indicators to obtain a channel state feature sequence. The preset multidimensional channel state indicators include signal-to-noise ratio, received signal strength, instantaneous bit error rate, maximum bit error length, and number of retransmissions. The channel state feature sequence is subjected to fast and slow interactive channel burst risk assessment to obtain signal burst risk assessment results; The error correction coding parameters and interleaving parameters are determined based on the signal burst risk assessment results. The priority transmission data set and the regular transmission data set are concatenated with the error correction coding parameters, and the encoded priority transmission data set and the regular transmission data set are adaptively interleaved by an interleaver according to the interleaving parameters to obtain interleaved data; The interleaved data is subjected to interleaving effect verification. After the interleaving effect verification is passed, the interleaved data is transmitted wirelessly with fault tolerance using a wireless transmission link, and then the data is deinterleaved and decoded by the deinterleaver at the receiving end.

2. The wireless transmission fault-tolerant method based on concatenated coding and dynamic interleaving as described in claim 1, characterized in that, The channel state feature sequence is subjected to fast and slow interactive channel burst risk assessment to obtain signal burst risk assessment results, including: The channel state feature sequence is extracted using both slow and fast time scales to obtain slow-time-scale signal feature subsequences and fast-time-scale signal feature subsequences. The slow time-scale feature extraction unit is used to extract features from the feature subsequence of the slow time-scale signal to obtain slow time-scale risk features; The fast timescale feature extraction unit is used to extract features from the fast timescale signal feature subsequence to obtain fast timescale risk features; By using fast-timescale risk characteristics as weighting factors, slow-timescale risk characteristics are dynamically modulated to obtain comprehensive signal burst risk characteristics. Risk assessment is then conducted based on these comprehensive signal burst risk characteristics to obtain signal burst risk assessment results.

3. The wireless transmission fault-tolerant method based on concatenated coding and dynamic interleaving as described in claim 2, characterized in that, Data extraction is performed on the channel state feature sequence using both slow and fast time scales to obtain slow-time-scale signal feature subsequences and fast-time-scale signal feature subsequences, including: A feature fluctuation curve is constructed based on the channel state feature sequence, wherein the horizontal axis of the feature fluctuation curve is time and the vertical axis is the channel state feature. Extract the set of inflection points of the characteristic fluctuation curve and count the time interval between two adjacent inflection points to obtain a set of candidate time scales; The maximum value in the candidate timescale set is taken as the fast timescale, and the minimum value in the candidate timescale set is taken as the slow timescale.

4. The wireless transmission fault-tolerant method based on concatenated coding and dynamic interleaving as described in claim 1, characterized in that, Based on the signal burst risk assessment results, error correction coding parameters and interleaving parameters are determined, including: Based on the signal burst risk assessment results, a pre-constructed parameter mapping table is retrieved to obtain error correction coding parameters and basic interleaving parameters; The basic interleaving parameters are conventionally labeled; the basic interleaving parameters are enhanced according to a preset enhancement threshold to obtain the preferred interleaving parameters, wherein the preferred interleaving parameters have a priority label; The interleaving parameters are obtained by summing the basic interleaving parameters and the preferred interleaving parameters.

5. The wireless transmission fault-tolerant method based on concatenated coding and dynamic interleaving as described in claim 1, characterized in that, The cascaded error correction code includes an inner code and an outer code; The inner code is a convolutional code or a Turbo code, used to correct random error codes; The outer code is a Reed-Solomon code, used to correct residual clustering errors after decoding the inner code.

6. The wireless transmission fault-tolerant method based on concatenated coding and dynamic interleaving as described in claim 1, characterized in that, Verification of the interleaving effect of the interleaved data includes: Before performing concatenated error correction coding at the transmitting end, a source data logical index identifier is established for each coding unit to obtain a set of source data logical index identifiers. Each source data logical index identifier is used to characterize the relative position of the corresponding coding unit in the source data space, and is obtained by numbering the source data in chronological order. Obtain the interleaving space location of each coding unit recorded after interleaving, and obtain the set of interleaving space locations; Based on the mapping between the source data logical index identifier set and the interleaving spatial location set, an interleaving structure feature set is constructed; The interleaving effect is verified based on the interleaving structure feature set to obtain the interleaving effect verification result, wherein the interleaving effect verification result includes verification passed or verification failed.

7. The wireless transmission fault-tolerant method based on concatenated coding and dynamic interleaving as described in claim 6, characterized in that, Based on the set of interleaved structural features, the interleaved data is subjected to interleaving effect verification to obtain interleaving effect verification results, including: Using the interlacing spatial location as an index, the set of interlacing structural features is aggregated to obtain multiple aggregated sets of interlacing structural features; By iterating through the multiple sets of aggregated and interwoven structural features, each set is enumerated pairwise to obtain a set of multiple enumerated combinations of aggregated and interwoven structural features. Using the source data logical index identifier as an index, the set of multiple aggregated and interwoven structural features is enumerated and combined to identify the dispersion within the set, and the integration dispersion coefficient is obtained. Based on the integration dispersion coefficient, it is determined whether the coding units from adjacent positions still exhibit a clustered distribution in the interleaving space, and the interleaving effect verification result is obtained based on the judgment result.

8. The wireless transmission fault-tolerant method based on concatenated coding and dynamic interleaving as described in claim 7, characterized in that, Using the source data logical index identifier as an index, the set of multiple aggregated and interwoven structural features is enumerated and combined to identify the dispersion within the set, and the integration dispersion coefficient is obtained, including: Traverse the multiple aggregated and interwoven structural feature enumeration combination sets to perform combined metadata logical index identifier difference identification, and obtain multiple combined identifier difference sets; The mean shift filter is applied to the multiple sets of combined identifier differences to determine multiple filtered combined identifier differences, and the multiple filtered combined identifier differences are respectively used as the dispersion coefficients within the multiple sets. Based on the multiple aggregated and interwoven structural features, enumerate the combination quantity within each set in the combination set to determine multiple decentralized integration weights; The dispersion coefficients within the multiple sets are weighted and analyzed based on the multiple dispersion integration weights to obtain the integrated dispersion coefficients.

9. The wireless transmission fault-tolerant method based on concatenated coding and dynamic interleaving as described in claim 7, characterized in that, Based on the integration dispersion coefficient, it is determined whether coding units from adjacent positions still exhibit a clustered distribution in the interleaving space. Based on the determination result, the interleaving effect verification result is obtained, including: Determine whether the integration dispersion coefficient is greater than or equal to a preset dispersion coefficient threshold. If so, the interleaving effect verification result is "verification passed". If not, the verification result for the interleaving effect is "verification failed".

10. A wireless transmission fault-tolerant device based on concatenated coding and dynamic interleaving, characterized in that, The apparatus is used to implement the wireless transmission fault-tolerant method based on concatenated coding and dynamic interleaving as described in any one of claims 1-9, and the apparatus comprises: The data acquisition module is used to acquire a set of transmission data with priority tags from the sending end, wherein the transmission data set includes a priority transmission data set and a regular transmission data set; The channel state feature sequence acquisition module is used to collect data from the wireless transmission link based on preset multi-dimensional channel state indicators to obtain a constructed channel state feature sequence. The preset multi-dimensional channel state indicators include signal-to-noise ratio, received signal strength, instantaneous bit error rate, maximum bit error length, and number of retransmissions. The risk assessment module is used to perform fast and slow interactive channel burst risk assessment on the channel state feature sequence to obtain signal burst risk assessment results. The parameter determination module is used to determine error correction coding parameters and interleaving parameters based on the signal burst risk assessment results. The interleaved data acquisition module is used to perform concatenated error correction coding on the priority transmission data set and the regular transmission data set using the error correction coding parameters, and to adaptively interleave the encoded priority transmission coded data set and the regular transmission coded data set through an interleaver according to the interleaving parameters to obtain interleaved data; The fault-tolerant wireless transmission module is used to verify the interleaving effect of the interleaved data. After the interleaving effect verification is passed, the interleaved data is transmitted wirelessly with fault tolerance using a wireless transmission link, and error correction and decoding are performed by the deinterleaver at the receiving end.

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