CN117176301B - Digital cyclic sampling coding method and system for medium wave intelligent transmitter - Google Patents
Digital cyclic sampling coding method and system for medium wave intelligent transmitter Download PDFInfo
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Abstract
The application relates to the field of broadcast communication, in particular to a digital cyclic sampling coding method and system of a medium wave intelligent transmitter, wherein the method comprises the following steps: circularly sampling continuous information codes in the digitized data of the transmitter to obtain a minimum code distance curve of the information codes; calculating a segmentation coefficient according to the minimum code distance curve, and segmenting the information code to obtain a segmentation result; calculating an adaptive coefficient according to the segmentation coefficient; and according to the adaptive coefficients, performing cyclic encoding on segmented information codes matched with different encoders to generate codeword data with different codeword lengths. According to the method and the device, continuous information code data are analyzed, whether the current information code is used as a segmentation point or not is judged in real time, different encoders are selected for encoding the segmented information code data, and error correction capability of codewords is guaranteed while encoding efficiency and transmission efficiency are improved through parallel processing and a mode of selecting check codes with different lengths.
Description
Technical Field
The application relates to the field of broadcast communication, in particular to a digital cyclic sampling coding method and system for a medium wave intelligent transmitter.
Background
In modern communication systems, especially in the field of broadcast television, medium-wave intelligent transmitters are favored by wide users because of their wide coverage range and stable signal transmission quality. However, with rapid development of digitization and intelligent technology, requirements for digitization processing, control of display functions, and audio transmission efficiency of the medium-wave intelligent transmitter are also increasing.
Conventional mid-wave smart transmitters are typically operated by means of analog signal processing, which means that they may suffer from problems such as noise interference, signal attenuation, etc., thereby affecting their performance. To solve these problems, the prior art introduces DSP (Digital Signal Processor, digital signal processing) techniques to convert the original analog signal to a digital signal. But this approach may still be subject to transmission errors in the partially encoded data due to interference from various environmental factors during transmission. The existing cyclic code coding method has certain error correction capability in the digital coding transmission of a medium wave transmitter in the broadcasting field, thereby ensuring the accuracy of transmission input.
In the transmission coding of the digitized medium wave signal, binary data are coded, and corresponding binary check codes are required to be generated, wherein the check codes are used for detecting and correcting errors possibly occurring in the transmission process. Longer check codes tend to mean higher error correction capability, but increasing the error correction capability of encoded data by increasing the length of the check code, while at the same time, results in reduced encoding efficiency and transmission rate.
Disclosure of Invention
In order to improve coding efficiency and transmission efficiency and ensure error correction capability of code words, the application provides a digital cyclic sampling coding method and system of a medium wave intelligent transmitter.
In a first aspect, the present application provides a digital cyclic sampling coding method for a medium wave intelligent transmitter, which adopts the following technical scheme:
a digital cyclic sampling coding method of a medium wave intelligent transmitter comprises the following steps: circularly sampling continuous information codes in the digitized data of the transmitter to obtain a minimum code distance curve of the information codes; calculating a segmentation coefficient according to the minimum code distance curve, and segmenting the information code to obtain a segmentation result; calculating an adaptive coefficient according to the segmentation coefficient; and according to the adaptive coefficients, performing cyclic encoding on segmented information codes matched with different encoders to generate codeword data with different codeword lengths.
Optionally, the cyclic sampling is performed on the continuous information codes to obtain a minimum code distance curve of the information codes, which comprises the following steps: circularly sampling the information codes by using a multithreading mode to obtain code distances among the information codes; and calculating the minimum value of a plurality of code distances of each information code, and obtaining a minimum code distance curve of the information code.
Optionally, segmenting the information code, and obtaining the segmentation coefficients of multiple segments of the information code according to the minimum code distance curve, wherein the segmentation coefficients comprise the following steps: calculating check codes of a plurality of information codes according to a preset polynomial; generating a transmission error-free instruction in response to the check codes being identical; generating a transmission error instruction in response to the difference of the check codes; in response to the transmission error-free instruction, segment coefficients are calculated,obtaining a segmentation result, wherein the calculation formula is as follows:wherein->For the segmentation coefficient of the ith information code, the target interval is between the ith information code and the information code corresponding to the last segmentation point,/for the information code>A Gaussian function value of the number of information codes in the target interval, ">For the information entropy value of the code distance curve corresponding to all the information codes in the target interval,/for the information entropy value>The ratio of the minimum code distance value in the code distance curve corresponding to all the information codes in the target interval to the number of information code bits.
Optionally, according to the segmentation coefficient, in calculating the adaptive coefficient, a calculation formula is as follows:wherein->For the i-th information code and the adaptive coefficients of the encoder corresponding to the target value +.>Representing the state of the relative peak of the segmentation coefficients of the ith information code,/>For target value, & lt + & gt>The segmentation coefficient corresponding to the ith information code.
Optionally, the method circularly samples continuous information codes in the digitized data of the transmitter to obtain a minimum code distance curve of the information codes, and further comprises the steps of: and adjusting the minimum code distance of the check codes in the digitized data and the length of the check codes.
Optionally, the adjusting the minimum code distance of the check code and the length of the check code includes the steps of: responding to the fact that the minimum code distance of the check code is larger than a preset code distance threshold value, reducing the order of a polynomial required for calculating the check code, reducing the value of the minimum code distance and increasing the length of the check code; and in response to the minimum code distance of the check code being smaller than or equal to the code distance threshold, increasing the order of a polynomial required for calculating the check code, increasing the value of the minimum code distance and reducing the length of the check code.
In a second aspect, the present application provides a digital cyclic sampling coding system of a medium wave intelligent transmitter, which adopts the following technical scheme:
a digital cyclic sampling coding system of a medium wave intelligent transmitter comprises: the system comprises a processor and a memory, wherein the memory stores computer program instructions which when executed by the processor realize the digital cyclic sampling coding method according to the medium wave intelligent transmitter.
The application has the following technical effects:
1. the method comprises the steps of collecting digital data of a medium wave transmitter, performing cyclic sampling by utilizing multiple threads, improving segmentation efficiency by parallel cyclic sampling, analyzing continuous information code data, enabling whether the current information code is used as a segmentation point or not to be judged in real time, and ensuring error correction capability of code words while improving coding efficiency and transmission efficiency by parallel processing and selecting check codes with different lengths.
2. Setting a plurality of encoders, selecting different encoders for encoding the segmented information code data, and encoding the segmented information code data by adopting different encoders to obtain data with different codeword lengths for the digital data information transmission of the medium wave intelligent transmitter.
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The above, as well as additional purposes, features, and advantages of exemplary embodiments of the present application will become readily apparent from the following detailed description when read in conjunction with the accompanying drawings. In the drawings, several embodiments of the present application are shown by way of example and not by way of limitation, and identical or corresponding reference numerals indicate identical or corresponding parts.
Fig. 1 is a flowchart of a method for steps S1-S4 in a digital cyclic sampling coding method of a medium wave intelligent transmitter according to an embodiment of the present application.
Fig. 2 is a flowchart of a method of steps S10-S12 in a digital cyclic sampling coding method of a medium wave intelligent transmitter according to an embodiment of the present application.
Fig. 3 is a flowchart of a method of steps S100-S101 in a digital cyclic sampling coding method of a medium wave intelligent transmitter according to an embodiment of the present application.
Fig. 4 is a flowchart of a method of steps S20-S23 in a digital cyclic sampling coding method of a medium wave intelligent transmitter according to an embodiment of the present application.
Detailed Description
The following description of the embodiments of the present application will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are some, but not all, of the embodiments of the present application. All other embodiments, which can be made by those skilled in the art based on the embodiments herein without making any inventive effort, are intended to be within the scope of the present application.
It should be understood that when the terms "first," "second," and the like are used in the claims, specification, and drawings of this application, they are used merely for distinguishing between different objects and not for describing a particular sequential order. The terms "comprises" and "comprising," when used in the specification and claims of this application, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
The embodiment of the application discloses a digital cyclic sampling coding method of a medium wave intelligent transmitter, which ensures that the coding transmission process of the digital data of the medium wave intelligent transmitter has certain error correction capability and ensures coding efficiency.
Data preparation: when the analog signal of the medium wave intelligent transmitter is digitally processed, in order to facilitate better visual control of the medium wave intelligent transmitter, the CPLD (Complex Programmable Logic Device ) +STM32 microcomputer control system is adopted to replace a display board, a control board and an instrument board, so that the control display function is more intelligent and more convenient, and the medium wave intelligent transmitter is intelligently controlled through the microcomputer control system.
In order to reduce the problem of audio transmission loss and improve the index of the transmitter, the digital-to-analog conversion board and the audio input board are optimally designed, so that an ABS/EBD (Audio and Video Bridging Stream/Entertainment and Basic Support Services, audio and video bridging stream/entertainment and basic support service) digital audio interface, an analog interface and a digital-to-analog interface are converted and integrated into the same interface, and further more accurate digital data of the medium wave transmitter signal is obtained.
Specifically, after the digitized data of the medium wave intelligent transmitter is obtained, the data can be encoded by a cyclic code encoding method for transmission of the digitized data, and the larger the minimum code distance of the data after the cyclic code encoding is, the stronger the error correction capability of the cyclic code encoding is.
After the analog signals of the medium-wave intelligent transmitter are digitized, all the digitized data are binary coded for the convenience of transmission, and the design of a circuit is facilitated.
After binary encoding, the binary data digitized by the medium-wave intelligent transmitter at continuous moments can be obtained and used as transmitter digitized data, when the medium-wave intelligent transmitter carries out cyclic encoding transmission, the binary data is encoded, and binary check codes need to be generated, for example, in binary data 01011110, 0101 is an information code, and 1110 is a check code.
Referring to fig. 1, the digital cyclic sampling coding method of the medium wave intelligent transmitter of the present application includes steps S1 to S4, specifically as follows:
s1: and circularly sampling continuous information codes in the digitized data of the transmitter to obtain a minimum code distance curve of the information codes. Referring to fig. 2, step S1 includes steps S10 to S12, specifically as follows:
s10: and adjusting the minimum code distance of the check codes in the digitized data and the length of the check codes. Referring to fig. 3, step S10 includes steps S100 to S101, specifically as follows:
s100: and in response to the minimum code distance of the check code being greater than a preset code distance threshold, reducing the order of a polynomial required for calculating the check code, reducing the value of the minimum code distance and increasing the length of the check code.
S101: and in response to the minimum code distance of the check code being less than or equal to the code distance threshold, increasing the order of the polynomial required for calculating the check code, increasing the value of the minimum code distance and reducing the length of the check code.
In particular, in signal data transmission, since the length of the digitized binary data of the medium-wave intelligent transmitter is fixed, but the information codes at different moments are not consistent, so that the binary information codes are fixed in length but the error correction capability may not be the same after the check codes are added.
For binary information codes with larger minimum code distance, the binary information codes have stronger error correction capability, so that the order of polynomials required for calculating the check codes is reduced, the length of the check codes is reduced, the minimum code distance of the check codes is reduced, the error correction capability of the check codes is reduced, the minimum code distance of the binary information codes is larger, the coded data can still be ensured, the coded data is called codeword data, and certain error correction capability information is provided.
For binary code information codes with smaller minimum code distance, the binary code information codes have weaker error correction capability, and then the length of the check code is prolonged by improving the order of a polynomial required by calculating the check code, so that the minimum code distance of the check code is increased, the error correction capability of the check code is increased, and the encoded data is ensured to have certain error correction capability information.
S11: and circularly sampling the information codes by using a multithreading mode to obtain the code distance between the information codes.
S12: and calculating the minimum value of a plurality of code distances of each information code, and obtaining a minimum code distance curve of the information code.
Specifically, the method utilizes multithreading to circularly sample, obtains the minimum code distance corresponding to each information code in the fixed-length data segment, analyzes the minimum code distances corresponding to different information codes, namely analyzes the minimum value of a plurality of code distances, is used for information code segmentation, and has higher real-time coding efficiency through parallel processing.
In the subsequent step S2, the information code data needs to be segmented, and each segment needs to have an approximate minimum code distance, that is, the difference between the approximate values is smaller than a preset difference threshold. If the minimum code distance between the continuous information codes is calculated, the minimum code distance between the continuous information codes needs to be calculated in a crossing way, and the length of the segmentation is unknown, so that when a single information code is taken as a segmentation point, a large calculation amount can be caused to cause calculation congestion if the single information code is taken as a single thread, and therefore the multi-thread cyclic sampling is adopted in the method.
Specifically, the specific process of circularly sampling the continuous information code is as follows:
acquiring the ith information codeStarting the 1 st thread, calculating the code distance between the i information code and the (i+1) information code by using the 1 st thread>And calculates the code distance ++2 between the ith information code and the (i+2) th information code>And so on until the length is n, namely, calculating the code distance between the ith information code and the (i+n) th information code>。
Similarly, the (i+1) th information codeStarting the 2 nd thread, and calculating the code distance between the (i+1) th information code and the (i+2) th information code by using the thread>And calculates the code distance +.1 between the (i+1) th information code and the (i+3) th information code>And so on until the length of the interval information code is n, namely, the code distance between the (i+1) th information code and the (i+1+n) th information code is calculated. And thus n threads need to be started in total.
The first n information codes are coded according to the length of the check code corresponding to the coding requirement of the standard cyclic code, after the n information codes, each information code corresponds to n code distances, and then the minimum code distance is selected from the n code distances corresponding to each information code and is used as the minimum code distance of the information code and is recorded as。
Thus, for continuous information codes, a minimum code distance curve can be obtained.
S2: and calculating a segmentation coefficient according to the minimum code distance curve, and segmenting the information code to obtain a segmentation result. Referring to fig. 4, step S2 includes steps S20 to S23, specifically as follows:
s20: and calculating check codes of the plurality of information codes according to a preset polynomial.
S21: and generating a transmission error-free instruction in response to the check codes being identical.
S22: in response to the check code being different, a transmission error instruction is generated.
When the cyclic code is encoded, the check code calculation is carried out on different binary information codes according to a fixed polynomial, and then the preset decoding end carries out the check code calculation on the fixed polynomial, if the check codes are consistent, the current data transmission is considered to be correct, a transmission error-free instruction is generated, and otherwise, the transmission error is generated, and a transmission error instruction is generated.
After the minimum code distance curve corresponding to the continuous information code is obtained, the current information code needs to be segmented for cyclic code coding, and then the coded codeword data can be transmitted.
When the current information code is segmented, the coding efficiency is affected if more information data are accumulated and then segmented, and then the current information code data are selected to be acquired for real-time segmentation point judgment, and if the current information code data are segmented, the information code segmentation is performed.
Since the minimum code lengths in different sections are not consistent, and thus the check code lengths required by the different sections are also not consistent, the method selects a plurality of preset encoders, wherein each encoder corresponds to a polynomial with different orders and is used for generating check codes with different lengths when cyclic code encoding is performed.
Therefore, the segmented information code data can be subjected to parallel cyclic code coding, and the information transmission efficiency of the medium wave intelligent transmitter is improved.
Therefore, the acquisition process of the error correction coefficient corresponding to each piece of digitized data comprises the following steps: and obtaining the digitized corresponding segmentation coefficients of each information code according to the minimum code distance curve. And obtaining the self-adaptive coefficient of each digitalized information code according to the corresponding segmented coefficient of each digitalized information code. Specifically, the method includes steps S23 and S3:
s23: and responding to the transmission error-free instruction, calculating a segmentation coefficient, and obtaining a segmentation result.
If the number of the information codes in the current segment is too small or too large, the current information codes should not be segmentation points, when the number of the information codes is too large, the encoder is easy to idle, if the number of the information codes is too small, the encoder is frequently switched, and further the expected number length of the information codes is required to be determined according to specific implementation conditions and recorded as d, and the application d=10.
But the adjustment is needed according to the code distance curve change of the information codes in the segments during segmentation, so that the code distances in the segments finally separated are consistent, the minimum code distance is as large as possible, and the number of the information codes in the segments accords with the expected length. And further obtaining a segmentation coefficient corresponding to the current ith information code, wherein the calculation formula is as follows:
，
wherein,
setting the target interval between the ith information code and the information code corresponding to the last segmentation point.Is the segmentation coefficient of the i-th information code.
Is the gaussian function value of the number of information codes in the target interval.
For the information entropy value of the code distance curve corresponding to all the information codes in the target interval,/for the information entropy value>The ratio of the minimum code distance value in the code distance curve corresponding to all the information codes in the target interval to the number of information code bits.
In the calculationIn this case, the mean value of the gaussian function is set to d, the variance is set to 1, and the variance is a super-parameter, so that the practitioner can adjust the scene according to the implementation.
Is 1. When the number of interval information codes between the ith information code and the information code corresponding to the last segmentation point is more close to d, the corresponding +.>The closer to the peak of the gaussian function. Since the peak values of the Gaussian functions under different variances are different, when the number of interval information codes between the ith information code and the information code corresponding to the last segmentation point is closer to d, the corresponding +.>The closer to the peak of the gaussian function, in this case, in order to make the peak 1, the gaussian function is multiplied by the inverse of the peak of the gaussian function to ensure that the value of the gaussian function is 1, i.e./1>Is 1.
The information entropy value of the code distance curve corresponding to all the information codes between the current ith information code and the information code corresponding to the last segmentation point is a measure for the degree of confusion. The larger the information entropy value is, the larger the disorder degree is, the larger the information quantity is, the more the information distance curve values corresponding to all the information codes between the ith information code and the information code corresponding to the last segmentation point are disordered, the more the information codes are not divided into the same segment, and therefore, in the case, the number of the information codes in the segment does not accord with the expected length, and the segmentation is also needed. And then (I)>The larger the value of (c) the less should it be broken into segments, the less suitable the ith information code is as a segmentation point, i.eThe smaller the value of (c) the more should be divided into segments, the more suitable the ith information code is as a segmentation point. For->The value pair +.>The value is adjusted so that +.>The smaller the value of +.>The larger the value of (i) the more suitable the i-th information code is as a segmentation point.
The ratio of the minimum code distance value in the code distance curve corresponding to all the information codes between the current ith information code and the information code corresponding to the last segmentation point to the number of information code bits is obtained.
The number of information code bits is denominator, and the code distance is consistent and not representative of the information codes, so that the minimum code distance value in the corresponding code distance curves of all the information codes in the section is obtained.
The larger the value is, the higher the error correction capability is, the more the information code in the current segment is always with a bit higher when the check code with equal length is used, if the error correction capability is high enough to be expected, the i-th information code can be segmented. And then (I)>The larger the value of (i) the more likely the ith information code is a segmentation point, +.>The larger the value of the code is, the more suitable the code is as a segmentation point at present, and then after the segmentation coefficients corresponding to the information codes are obtained, the segmentation of the corresponding information codes is completed, and a segmentation result is obtained.
And S3, calculating the self-adaptive coefficient according to the segmentation coefficient.
After the segmentation result is obtained, different encoders are allocated to the current segmented information codes to carry out cyclic code encoding for the digital data transmission of the medium wave intelligent transmitter.
When different encoders are selected, the different encoders correspond to polynomials with different orders, namely, the different encoders can generate check codes with different lengths, wherein the higher the order of the polynomials is, the longer the corresponding check code length is, the stronger the error correction capability is, and the coding transmission efficiency is lower.
In order to ensure the error correction capability of the code word data after the encoding of the information code data in each segment after the segmentation, the shorter check codes are adopted to carry out cyclic code encoding as far as possible, so that the encoding transmission efficiency is improved as far as possible while the error correction capability is ensured.
Further, the expected minimum code distance of the code word data in each segment is set so as to facilitate the matchingAnd comparing the minimum code distance in the measurement section, and performing ratio processing on the expected minimum code distance and the information code length to obtain an L value, wherein the information code length is denominator.
If the current ith information code is a segmentation point, the ith information code corresponds toThe larger the difference between the value and the L value is, the longer the check code is needed to ensure the corresponding order, the expected minimum code distance corresponds to an expected check code length, and the expected check code length set in the application is as follows: the two times of the information code length is added with 1, and the implementer can adjust according to specific implementation scenes.
Since the present application has multiple encoders, the L value is linearly decreased downward, and different encoders are selected to be decreased downward at intervals of 2 code distances, the present application requires a minimum code distance of 4, and the interval and the minimum code distance implementer can be adjusted according to the specific implementation scenario. Obtaining multi-stage decrementingWherein->The two code distances are different from each other,differ by two code distances, minimum +.>The corresponding code distance is 4. Calculate->The larger the absolute value of the difference value is with the absolute value of the difference value of different L, the more unsuitable the current ith information code is used as a segmentation point, the application takes the ith information code corresponding to the minimum value of the absolute value of the difference value as the segmentation point, and further calculates +.>The minimum value of the absolute value of the difference from the different L is taken as a target value and recorded asAs a reference to the currently selectable encoder. In selecting an encoder, if the current encoder is occupied, i.e. the current encoder is in encoding, no +.>Is skipped directly.
Since the information code is continuous data, if only the ith information code is used as the final judgment basis, the situation of improper segmentation can occur, and further analysis is needed under the continuous information codeIf->In peak state +.>When the value of (2) is maximum, then it means that the reference of the current encoder can be selected if +.>Not in peak state or +.>When the value of (2) is not the maximum value, even +.>Is lower, the current encoder is not selected.
Obtaining the i information code and the corresponding encoder self-adaptive coefficient with the P value, wherein the calculation formula is as follows:
，
wherein,for the i-th information code and the adaptive coefficients of the encoder corresponding to the target value +.>Representing the state of the relative peak of the segmentation coefficients of the ith information code,/>For target value, & lt + & gt>The segmentation coefficient corresponding to the ith information code.
The calculation method of (1) is as follows: acquiring all information code correspondence between the current ith information code and the information code corresponding to the last segmentation point>The absolute value of the difference between the maximum value and the minimum value in the values is taken as a denominator, and all information codes between the current ith information code and the information code corresponding to the last segmentation point are +.>The absolute value of the difference of the minimum value in the values of (2) is taken as the numerator, and the ratio of the denominator and the numerator is taken as +.>。/>Representing the status of the relative peak of the segmentation coefficients corresponding to the ith information code,/and/or>The larger the value of (c) is, the more suitable the current ith information code is in peak state for segmentation, +.>Is set to 1.
For the segmentation factor corresponding to the ith information code,/-, for the information code>The larger the value of the (i) information code is, the smaller the code distance between the (i) information code and all the information codes corresponding to the last segmentation point is, the larger the code distance is, the length is proper, and the (i) information code can be used as the segmentation point.
Is->Minimum value of absolute value of difference from different L,>the smaller the value of (2) the more suitable the current ith information code is for the current encoder to use for cyclic code encoding, and thus it is necessary to map it negatively with exp (-x) function, so that +.>The smaller the value of exp (-x) the larger the value of exp (-x).
Currently, the method is thatIf the number is greater than the preset coefficient threshold, the ith information code is used as a segmentation point, if +.>And when the information code is smaller than or equal to the coefficient threshold value, the ith information code is not used as a segmentation point. Wherein the coefficient threshold is 1.5, which can be taken by the implementerAnd adjusting according to the specific implementation scene.
And S4, performing cyclic coding on segmented information codes matched with different encoders according to the adaptive coefficients to generate codeword data with different codeword lengths.
In order to adjust the error correction capability of cyclic codes for binary codes with different minimum code distances, the method sets a plurality of groups of polynomials with different orders for coding, and the existing codes are always fixed polynomials for coding, so that the lengths of check codes are consistent.
The method comprises the steps of setting a plurality of encoders, segmenting information codes, and encoding information code data of different segments by adopting different encoders after segmenting to obtain data with different codeword lengths for digital data information transmission of the medium wave intelligent transmitter.
When the segmentation of the information code data is completed, the information code with the smallest value is selectedAnd (3) performing cyclic code encoding by an encoder corresponding to the value, further obtaining codeword data of all data in the section after cyclic code encoding by cyclic sampling, and transmitting the codeword data to finish cyclic sampling encoding transmission of the digitized data of the medium wave intelligent transmitter. The cyclic code encoding process is known, and this scheme is not described in detail.
The method and the device improve the segmentation efficiency through parallel cyclic sampling, analyze continuous information code data, judge whether the current information code is used as a segmentation point in real time, select different encoders for encoding the segmented information code data, and process and select check codes with different lengths in parallel.
The embodiment of the application also discloses a digital cyclic sampling coding system of the medium wave intelligent transmitter, which comprises a processor and a memory, wherein the memory stores computer program instructions, and the digital cyclic sampling coding method of the medium wave intelligent transmitter is realized when the computer program instructions are executed by the processor.
The above system further comprises other components well known to those skilled in the art, such as a communication bus and a communication interface, the arrangement and function of which are known in the art and therefore are not described in detail herein.
In the context of this application, the foregoing memory may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. For example, the computer readable storage medium may be any suitable magnetic or magneto-optical storage medium, such as, for example, resistive random access memory RRAM (ResistiveRandomAccessMemory), dynamic random access memory DRAM (DynamicRandomAccessMemory), static random access memory SRAM (static random access memory), enhanced dynamic random access memory EDRAM (EnhancedDynamicRandomAccessMemory), high-bandwidth memory HBM (High-bandwidth memory), hybrid storage cube HMC (HybridMemoryCube), etc., or any other medium that may be used to store the desired information and that may be accessed by an application, a module, or both. Any such computer storage media may be part of, or accessible by, or connectable to, the device.
While various embodiments of the present application have been shown and described herein, it will be obvious to those skilled in the art that such embodiments are provided by way of example only. Many modifications, changes, and substitutions will now occur to those skilled in the art without departing from the spirit and spirit of the application. It should be understood that various alternatives to the embodiments of the present application described herein may be employed in practicing the application.
The foregoing are all preferred embodiments of the present application, and are not intended to limit the scope of the present application in any way, therefore: all equivalent changes in structure, shape and principle of this application should be covered in the protection scope of this application.
Claims (4)
1. The digital cyclic sampling coding method of the medium wave intelligent transmitter is characterized by comprising the following steps:
circularly sampling continuous information codes in the digitized data of the transmitter to obtain a minimum code distance curve of the information codes;
calculating a segmentation coefficient according to the minimum code distance curve, and segmenting the information code to obtain a segmentation result;
calculating an adaptive coefficient according to the segmentation coefficient;
according to the self-adaptive coefficient, circularly encoding the segmented information codes by matching with different encoders to generate codeword data with different codeword lengths;
according to the minimum code distance curve, calculating a segmentation coefficient, and segmenting an information code to obtain a segmentation result, wherein the method comprises the following steps:
calculating check codes of a plurality of information codes according to a preset polynomial;
generating a transmission error-free instruction in response to the check codes being identical;
generating a transmission error instruction in response to the difference of the check codes;
responding to the transmission error-free instruction, calculating a segmentation coefficient to obtain a segmentation result, wherein the calculation formula is as follows:
，
wherein,for the segmentation coefficient of the ith information code, the target interval is between the ith information code and the information code corresponding to the last segmentation point,/for the information code>A Gaussian function value of the number of information codes in the target interval, ">For the information entropy value of the code distance curve corresponding to all the information codes in the target interval,/for the information entropy value>For the ratio of the minimum code distance value in the code distance curve corresponding to all the information codes in the target interval to the number of information code bitsA value;
according to the segmentation coefficients, in the calculation of the self-adaptive coefficients, the calculation formula is as follows:
，
wherein,for the i-th information code and the adaptive coefficients of the encoder corresponding to the target value +.>Representing the state of the relative peak of the segmentation coefficients of the ith information code,/>For target value, & lt + & gt>The segmentation coefficient corresponding to the ith information code;
circularly sampling continuous information codes in the digitized data of the transmitter to obtain a minimum code distance curve of the information codes, and further comprising the steps of: and adjusting the minimum code distance of the check codes in the digitized data and the length of the check codes.
2. The method for digitally cyclically sampling and encoding a medium wave intelligent transmitter according to claim 1 wherein the step of cyclically sampling successive information codes to obtain a minimum code distance profile for the information codes comprises the steps of:
circularly sampling the information codes by using a multithreading mode to obtain code distances among the information codes;
and calculating the minimum value of a plurality of code distances of each information code, and obtaining a minimum code distance curve of the information code.
3. The method for digitally sampling and encoding a medium wave intelligent transmitter according to claim 1, wherein the adjusting of the minimum code distance of the check code and the length of the check code comprises the steps of:
responding to the fact that the minimum code distance of the check code is larger than a preset code distance threshold value, reducing the order of a polynomial required for calculating the check code, reducing the value of the minimum code distance and increasing the length of the check code;
and in response to the minimum code distance of the check code being smaller than or equal to the code distance threshold, increasing the order of a polynomial required for calculating the check code, increasing the value of the minimum code distance and reducing the length of the check code.
4. The digital cyclic sampling coding system of the medium wave intelligent transmitter is characterized by comprising the following components: a processor and a memory storing computer program instructions that when executed by the processor implement the medium wave intelligent transmitter digitized cyclical sampling encoding method of any one of claims 1-3.
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