A real-time multimedia message transmission method based on 5G network

Abstract

The present invention discloses a real-time multimedia message transmission method based on a 5G network, relates to the technical field of data transmission, and is used to improve the problem that some checksum algorithms cannot identify data duplication. The method comprises the following steps: detecting the transmission distance and the amount of transmitted data of a transmission channel, calculating the transmission data error rate by a grading method, and when the transmission data error rate is higher than a threshold, using a cumulative checksum algorithm to respectively calculate the checksum of the transmitted data when it is transmitted and received, and judging whether the transmission is erroneous by the checksum. When the checksum is consistent, obtaining the data source and data update frequency of the transmitted data, analyzing the degree of data duplication by fuzzy reasoning based on the data source and update frequency, and calculating the data duplication rate if the degree of data duplication is high. Different checksum algorithms are provided for users to choose according to the degree of data duplication, and judging whether a data duplication problem occurs according to the checksum algorithm. When the data is repeated, the data repetition rate is given to facilitate subsequent analysis and processing.

Description

Technical Field

[0001] The present invention relates to the field of data transmission technology, and more specifically, to a real-time multimedia message transmission method based on a 5G network. Background Art

[0002] Data transmission technology is the process of transferring data from one device or system to another. When applied to multimedia message transmission, data transmission technology makes the transmission of multimedia messages more efficient, convenient, secure and smooth, providing great convenience for modern life.

[0003] The existing technology has the following deficiencies:

[0004] When multimedia information is transmitted in a network channel, errors such as garbled characters or information duplication may occur. Most transmission mechanisms will calculate and checksum the outgoing information and the received information separately. When the checksum calculation results are inconsistent, it is determined that an error has occurred in the transmission of the multimedia information. However, when data duplication occurs in the multimedia information, some checksum algorithms can also obtain the same calculation results, resulting in problems such as the inability to identify data duplication in the multimedia information and data analysis errors. Summary of the Invention

[0005] In order to overcome the above-mentioned defects of the prior art, an embodiment of the present invention provides a real-time multimedia message transmission method based on a 5G network, which selects different checksum algorithms by analyzing the error rate and repetition rate of the transmitted data to solve the problems raised in the above-mentioned background technology.

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] A method for transmitting real-time multimedia messages based on a 5G network, comprising the following steps:

[0008] Step S1: collecting the transmission distance and transmission data volume of multiple transmission channels for pre-processing;

[0009] Step S2: setting an error threshold based on the pre-processed transmission distance and the amount of transmitted data and calculating the transmission data error rate. When the transmission data error rate exceeds the error threshold, a cumulative sum check algorithm is used to preliminarily determine whether a transmission error has occurred.

[0010] Step S3: When it is preliminarily determined that the transmission is error-free, the data source and update frequency of the transmitted data are collected, and the degree of data duplication is analyzed based on the data source and update frequency. If the degree of data duplication is high, the data duplication rate is calculated;

[0011] Step S4: Select a bitmap algorithm based on the degree of data duplication or apply the data duplication rate to the BLAKE2 algorithm to detect whether the transmitted data has data duplication problems.

[0012] In a preferred embodiment, in step S1, the transmission distance of the transmission channel cannot be directly obtained, and the system represents the result obtained by calculating the physical distance between the two transmission devices and the network signal strength where the two transmission devices are located and performing hierarchical summation; the amount of transmission data of the transmission channel is obtained by detecting the size of the storage space occupied by the transmission data in the system.

[0013] In a preferred embodiment, in step S1, the system sets up multiple groups of transmission equipment, detects the transmission distance and transmission data volume of each group of transmission channels respectively, and performs normalization processing to obtain multiple groups of transmission distance coefficients and transmission volume coefficients.

[0014] In a preferred embodiment, in step S2, the processed transmission distance coefficients are combined into a transmission distance data set, and the transmission volume coefficients are combined into a transmission volume data set. The specific steps for setting the error threshold are as follows:

[0015] Perform the same processing on the two data sets, use the data set as the analysis data set, divide the analysis data set into two parts of equal size, calculate the average value of the two data sets respectively and compare them, screen out the part with the larger average value as the new round of analysis data set, then divide the new round of analysis data set into two parts of equal size to calculate the average value, screen out the part with the smaller average value as the new round of analysis data set, alternately take the larger and smaller data sets and repeat the operation until the last data is left; the average value of the data obtained from the processing of the two data sets is set as the error threshold.

[0016] In a preferred embodiment, in step S2, the system calculates the transmission distance coefficient and transmission volume coefficient of the transmission data to be tested and takes the average value as the transmission data error rate. When the transmission data error rate exceeds the error threshold, the system determines that the transmission data to be tested is prone to errors and uses the accumulation and verification algorithm to make an initial judgment on the transmission data.

[0017] In a preferred embodiment, in step S3, the data source obtains all data sources of the transmitted data by accessing the metadata field in the database table and records the number of data sources of the transmitted data; when obtaining the data update frequency, the data update frequency is reflected by recording the number of supplementary transmissions of the transmitted data by setting a time period.

[0018] In a preferred embodiment, in step S3, the specific steps of using fuzzy reasoning to analyze the degree of data duplication are as follows:

[0019] The number of data sources and the number of supplementary transmissions are defined as input variables and divided into fuzzy sets;

[0020] The degree of data duplication is defined as the output variable and divided into fuzzy sets;

[0021] Formulate fuzzy rules to describe the impact of the number of data sources and the number of supplementary transmissions on the degree of data duplication;

[0022] Perform fuzzy reasoning based on fuzzy rules to determine the degree of data duplication.

[0023] In a preferred embodiment, in step S3, when calculating the data repetition rate, the number of data sources of the transmitted data and the number of supplementary transmissions are summed to obtain a normalization parameter, which is then calculated using an exponential normalization formula based on the normalization parameter.

[0024] In a preferred embodiment, in step S4, when the data duplication degree is low, the system uses a bitmap algorithm to detect the transmitted data; when the data duplication degree is high, the system uses a BLAKE2 algorithm to detect the transmitted data;

[0025] If data duplication occurs in the transmitted data using the BLAKE2 algorithm, the data duplication rate of the transmitted data is given; if data duplication does not occur, the transmitted data is recorded.

[0026] The technical effects and advantages of the real-time multimedia message transmission method based on 5G network of the present invention are as follows:

[0027] The present invention analyzes the error rate of transmission data by detecting the transmission distance and the amount of transmission data of the transmission channel. When the error rate of transmission data is higher than a threshold, the cumulative sum checksum algorithm is used to respectively calculate the checksum of the transmission data when it is transmitted and received. A large amount of computing cost is saved by calculating the transmission data error rate and the cumulative sum checksum algorithm. Whether the transmission is erroneous is judged by the checksum. When the checksum is consistent, the data source and update frequency of the transmission data are collected. The data duplication degree is analyzed based on the data source and update frequency. If the data duplication degree is high, the data duplication rate is calculated. Different checksum algorithms are provided for users to choose according to the data duplication degree. Finally, the calculation result of the checksum algorithm is used to judge whether a data duplication problem occurs. By providing a suitable checksum algorithm, computing cost is saved, and the judgment accuracy is improved while also analyzing the transmission error type to facilitate subsequent accurate correction of the error. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 This is a schematic diagram of a real-time multimedia message transmission method based on a 5G network according to the present invention. DETAILED DESCRIPTION

[0029] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0030] The present invention analyzes the error rate of transmission data by detecting the transmission distance and the amount of transmission data of the transmission channel. When the error rate of transmission data is higher than a threshold, the cumulative sum checksum algorithm is used to respectively calculate the checksum of the transmission data when it is transmitted and received. Whether the transmission is erroneous is judged by the checksum. When the checksum is inconsistent, it is judged that an error occurs in the transmission data transmission. When the checksum is consistent, the data source and data update frequency of the transmission data are obtained. The data duplication degree is analyzed by fuzzy reasoning based on the data source and update frequency. If the data duplication degree is high, the data duplication rate is calculated. Different checksum algorithms are provided for users to choose according to the data duplication degree. Finally, whether a data duplication problem occurs is judged by the calculation result of the checksum algorithm. If the data is repeated, the data duplication rate is given to facilitate subsequent analysis and processing.

[0031] Embodiment, a real-time multimedia message transmission method based on 5G network, such as Figure 1 As shown, the following steps are included:

[0032] Step S1: collecting the transmission distance and transmission data volume of multiple transmission channels for pre-processing;

[0033] Step S2: setting an error threshold based on the pre-processed transmission distance and the amount of transmitted data and calculating the transmission data error rate. When the transmission data error rate exceeds the error threshold, a cumulative sum check algorithm is used to preliminarily determine whether a transmission error has occurred.

[0034] Step S3: When it is preliminarily determined that the transmission is error-free, the data source and update frequency of the transmitted data are collected, and the degree of data duplication is analyzed based on the data source and update frequency. If the degree of data duplication is high, the data duplication rate is calculated;

[0035] Step S4: Select a bitmap algorithm based on the degree of data duplication or apply the data duplication rate to the BLAKE 2 algorithm to detect whether data duplication occurs in the transmitted data.

[0036] The specific implementation is as follows:

[0037] In step S1, the transmission distance of the transmission channel cannot be obtained directly. The system obtains the address of the outgoing device and the address of the receiving device by connecting to the positioning system and calculates the physical distance between the two devices. It then opens a command line to prompt the user to enter a specified command to view the device network environment and receive the network signal strength entered by the user.

[0038] After determining the physical distance and receiving the network signal strength, the system uses a grading method to grade the physical distance and network signal, obtains the set value and sums it up, and uses the calculated result as the transmission distance coefficient of the transmission channel. The transmission distance coefficient reflects the transmission distance of the transmission channel.

[0039] The grading method uses data size for grading. For example, using physical distance in this example, the system calculates the physical distances between multiple groups of devices and assigns these data to percentage-based grading. Different grading coefficients are assigned to different levels of physical distance data. Once the physical distances between detected devices are calculated, the grading coefficient for that grading interval serves as a reference for subsequent analysis and processing. For example, if the percentage is set to 20%, the system will sort the calculated physical distances between multiple groups of devices from smallest to largest and divide them into five groups with a 20% percentage, each corresponding to a grading level. The grading coefficients for the five groups are then set to 0.3, 0.4, 0.5, 0.6, and 0.7, respectively, in the order of their grading. Similarly, network signal strength is pre-processed before calculating the transmission distance coefficient.

[0040] It should be explained that the percentage used in grading can be set according to actual conditions, and the setting of the level coefficient should satisfy the corresponding relationship of the parameters. The smaller the physical distance between the two devices or the greater the network signal strength, the smaller the transmission distance coefficient of the transmission channel. Therefore, when setting the level coefficient, the greater the physical distance, the greater the level coefficient, and the smaller the network signal strength, the greater the level coefficient.

[0041] The system detects the transmission data before it is transmitted to determine the size of the transmission data, that is, how much storage space the system occupies. After calculating the transmission distance coefficient of each group of devices, the system detects each group of transmission data and obtains the transmission data volume of each group. The calculation result of dividing the transmission data volume of each group by the maximum transmission data volume of all groups is used as the transmission volume coefficient.

[0042] It should be noted that in step S1, the number of collection combinations can be set in the system, and the system will obtain the calculation data corresponding to the number of collection combinations. For example, if the number of collection combinations is set to 10, the system will collect 10 groups of devices and calculate the transmission distance coefficient and transmission data volume of the transmission channel of each group of devices. In this example, there are two devices in each group, and the transmission data volume can be obtained by accessing the property page of viewing the transmission data.

[0043] In step S2, the system merges multiple transmission distance coefficients and transmission volume coefficients into a transmission distance data set and a transmission volume data set, and sets an error threshold based on the transmission distance data set and the transmission volume data set. The specific method for setting the error threshold is as follows:

[0044] The system uses the transmission distance data set as the analysis data set, randomly arranges the data in the analysis data set, counts the number of data in the analysis data set, divides the analysis data set into two parts with the same number of data, calculates the data averages in the two data sets respectively and compares them, and selects the part with the larger data average as the new round of analysis data set; the new round of analysis data set calculates the data averages in the two data sets in the same way, compares them, and selects the part with the smaller data average as the new round of analysis data set, alternately taking the data sets with the larger data average and the smaller data average as the analysis data set, and repeats the operation until only the last data is left in the analysis data set, that is, the last transmission distance coefficient, which is marked as a.

[0045] It should be explained that if the number of data in the analysis data set is an odd number, the median of the analysis data set will be eliminated before screening.

[0046] The same operation is performed on the transmission volume data set. The filtered transmission volume coefficient is marked as b. The average value of a and b is calculated and the calculation result is set as the error threshold. The system detects the current transmission data and calculates the transmission distance coefficient and transmission volume coefficient of the current transmission data. The average value of the transmission distance coefficient and transmission volume coefficient of the current transmission data is calculated as the transmission data error rate.

[0047] When the error rate of the transmitted data exceeds the error threshold, the system determines that the current transmitted data is prone to errors and uses the cumulative sum check algorithm to make an initial judgment on the transmitted data. The specific steps of the cumulative sum check algorithm for error detection of the transmitted data are as follows:

[0048] Initialization: Set a cumulative sum variable and set it to 0;

[0049] Accumulate: accumulate the values ​​of all data bytes in the transmitted data into the accumulated sum variable;

[0050] Modulo: Perform a modulo operation on the accumulated sum variable to obtain the checksum, the modulus is usually 256;

[0051] Send: Send the checksum and transmission data together to the receiver;

[0052] Receiving: The receiver receives the checksum and transmitted data;

[0053] Checksum: The receiver performs the same accumulation operation on the transmitted data and obtains a checksum modulo the operation.

[0054] Comparison: Compare the received checksum with the calculated checksum. If the two are the same, the initial judgment is passed; otherwise, the transmitted data is marked as erroneous data.

[0055] The system conducts initial error judgment on the transmitted data by analyzing the risk of errors in the transmitted data and using a simple accumulation and verification algorithm for the transmission information with a high error rate, which greatly saves the computing space and cost of the verification data and improves the transmission efficiency.

[0056] It should be noted that in the above accumulation process, the numerical value corresponding to the ASCII code of each data byte in the transmitted data is accumulated. The ASCII code is a character encoding standard used to represent characters as numbers so that computers can process and store information. For example, if the transmitted data is "He llo", the system will search for the ASCII codes of "H", "e", "l" and "o", which are 72, 101, 108 and 111 respectively. The accumulated sum variable is 0+72+101+108+108+111=500, and the modulo 256 is: 500%256=244, then the checksum is 244.

[0057] In step S3, when the transmitted data is not marked as erroneous data after the initial judgment, the data source and data update frequency of the transmitted data are collected. The more data sources of the transmitted data and the faster the data update frequency, the more likely data duplication events will occur and the higher the data duplication rate. If explanation is needed, the data duplication rate mentioned in this example means the probability of data duplication, not the degree of data duplication.

[0058] The data source can access the metadata field in the database table to obtain all data sources of the transmitted data and record the number of data sources of the transmitted data; the data update frequency can set a period of time as the analysis time, and record the number of supplementary transmissions of the transmitted data during the analysis time. The supplementary transmission data content is the updated or modified content of the transmitted data, and the number of supplementary transmissions can reflect the data update frequency.

[0059] Fuzzy reasoning is used to analyze the degree of data duplication and calculate the data duplication rate based on the data source and data update frequency. The number of data sources and the number of supplementary transmissions are defined as input variables and divided into different fuzzy sets.

[0060] For example, "Many", "Few" for the number of data sources, "Big", "Small" for the number of supplementary transmissions.

[0061] The data duplication degree is defined as the output variable and divided into different fuzzy sets, for example, “High” and “Low” for the data duplication degree.

[0062] Formulate a set of fuzzy rules to describe the impact of different input variables on the output variable, for example:

[0063] Mark the number of data sources as S, the number of supplementary transmissions as B, and the degree of data duplication as C to define

[0064] Ru l e1:IF(S is Many)AND(B is B ig)THEN(C is H i gh)

[0065] Ru l e1:IF(S is Few)AND(B is Sma ll)THEN(C is Low) ...

[0067] When the output result is "Low", it is judged that the data repetition degree is low, and the system provides the inverse code and algorithm to detect the transmitted data; when the output result is "High", it is judged that the data repetition degree is high, the system calculates the data repetition rate of the transmitted data and provides the BLAKE2 algorithm to detect the transmitted data.

[0068] The data repetition rate can be calculated using the exponential normalization formula: Where z is a normalization parameter, which can be obtained by summing the number of data sources and the number of supplementary transmissions of the transmitted data, F is the data repetition rate, and E is the natural base.

[0069] It should be noted that the fuzzy set division can be adjusted based on the actual accuracy required. For example, while this example uses two fuzzy sets, it is actually possible to divide the number of data sources, the number of supplementary transmissions, and the degree of data duplication into three or more sets to more accurately assess the degree of data duplication. Furthermore, the number of data sources and the number of supplementary transmissions can be determined based on actual conditions by setting thresholds. For example, if the number of data sources exceeds 10, it can be marked as "Many", and if the number of supplementary transmissions exceeds 5, it can be marked as "Big", and so on. This will not be elaborated here.

[0070] In step S4, when the data duplication level is low, the system uses a bitmap algorithm to detect the transmitted data. The specific steps are as follows:

[0071] Initialize the bitmap: Create a bitmap array that stores the index address of each character in the transmitted data.

[0072] Traverse the array: When the transmission data is transmitted, traverse the order and index address corresponding to each character in the transmission data; after receiving the transmission data, traverse the transmission data again and compare it with the bitmap array. When the index address corresponding to the character in the transmission data is the same as the index address of the corresponding character in the bitmap array, the corresponding character is judged to be repeated and a duplicate label is marked.

[0073] Output result: Set a comparison threshold and count the ratio of repeated character labels to the total characters in the transmitted data. When the ratio exceeds the comparison threshold, the output result is set to 1 for output; otherwise, the output result is set to 0 for output.

[0074] When the output result is 1, the system sends a "data duplicate" prompt message to the user end; when the output result is 0, the system sends a "verification passed" prompt message to the user end.

[0075] When the data duplication level is high, the system uses the BLAKE2 algorithm to detect the transmitted data. The specific steps are as follows:

[0076] Initialization: define a 16-byte hash state tag as h;

[0077] Padding: Pad the transmitted data to make its length a multiple of 64 bytes. The padding method can add a byte 8 at the end of the data, and then add several zeros until the data length is a multiple of 64 bytes.

[0078] Compression: Divide the padded data into 64-byte blocks, each block as a group, use the G function to compress each group, mix the group data with the h state, and update the h state;

[0079] Output: After compressing all packets, the h state contains the final hash value. The 16 bytes in the h state are output to obtain a 128-bit hash value.

[0080] The system uses the BLAKE2 algorithm to calculate the hash value when transmitting and interpreting the transmitted data. When the two calculated hash values ​​are the same, the system sends a "data duplicate" prompt message to the user end. When the two calculated hash values ​​are different, the system sends a "verification passed" prompt message to the user end.

[0081] A mapping table is constructed based on the data repetition rate of the transmitted data and the hash value calculated by the BLAKE2 algorithm during transmission. The calculated hash value is used as the key and the data repetition rate is used as the value, and they are stored in a mapping table. When the transmitted data is received, its hash value is calculated again and the mapping table is queried. If the same hash value is found in the mapping table, it means that the data has appeared and the data repetition rate of the transmitted data can be obtained; if the same hash value is not found in the mapping table, the hash value and repetition rate of the transmitted data are recorded and added to the mapping table.

[0082] Selecting different algorithms to detect transmitted data according to the degree of data duplication greatly improves the accuracy and efficiency of data duplication analysis. Constructing a mapping table to record and store transmitted data facilitates subsequent analysis and processing of the transmitted data.

[0083] It should be noted that the bitmap algorithm is a common data structure and algorithm primarily used for efficient data storage and processing. It offers simplicity and high efficiency when analyzing data for duplication. The BLAKE2 algorithm is a cryptographic hash algorithm, an improvement on the original BLAKE algorithm. While the BLAKE2 algorithm requires more computation to detect duplicates in transmitted data, it offers higher accuracy. When padding, the BLAKE2 algorithm treats each character as a byte. For example, if the transmitted data is "He l lo," the system will pad the data with "He ll o80000...0" until the data reaches a multiple of 64 bytes. The G function involved in the compression step described above is a compression function that can perform different compression operations on data. Since the G function is a conventional technique, it will not be analyzed here.

[0084] The above embodiments may be implemented in whole or in part through software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments may be implemented in whole or in part in the form of a computer program product.

[0085] Those skilled in the art will appreciate that the modules and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application of the technical solution and the invention constraints. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0086] In addition, each functional module in each embodiment of the present application may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated into one module.

[0087] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of this application. Therefore, the scope of protection of this application should be based on the scope of protection of the claims.

[0088] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A real-time multimedia message transmission method based on 5G network, characterized in that: The following steps are involved: Step S1: collecting the transmission distance and transmission data volume of multiple transmission channels for pre-processing; Step S2: setting an error threshold based on the pre-processed transmission distance and the amount of transmitted data and calculating the transmission data error rate. When the transmission data error rate exceeds the error threshold, a cumulative sum check algorithm is used to preliminarily determine whether a transmission error has occurred. Step S3: When it is preliminarily determined that the transmission is error-free, the data source and update frequency of the transmitted data are collected, and the degree of data duplication is analyzed based on the data source and update frequency. If the degree of data duplication is high, the data duplication rate is calculated; Step S4: Select a bitmap algorithm based on the degree of data duplication or apply the data duplication rate to the BLAKE2 algorithm to detect whether the transmitted data has data duplication problems; In step S2, the processed transmission distance coefficients are combined into a transmission distance data set, and the transmission volume coefficients are combined into a transmission volume data set. The specific steps for setting the error threshold are as follows: Perform the same processing on the two data sets, use the data set as the analysis data set, divide the analysis data set into two parts of equal size, calculate the average value of the two data sets respectively, and compare them. Filter out the part with the larger average value as the new round of analysis data set, then divide the new round of analysis data set into two parts of equal size to calculate the average value, and filter out the part with the smaller average value as the new round of analysis data set. Repeat the operation on the data set by alternating between taking the larger and smaller values ​​until the last data is left; set the average value of the data obtained from the processing of the two data sets as the error threshold; In step S3, when calculating the data repetition rate, the number of data sources of the transmitted data and the number of supplementary transmissions are summed to obtain a normalization parameter, and the exponential normalization formula is used to calculate the normalization parameter; In step S4, when the data duplication degree is low, the system uses the bitmap algorithm to detect the transmitted data; when the data duplication degree is high, the system uses the BLAKE2 algorithm to detect the transmitted data; If data duplication occurs in the transmitted data using the BLAKE2 algorithm, the data duplication rate of the transmitted data is given; if data duplication does not occur, the transmitted data is recorded.

2. The method for transmitting real-time multimedia messages based on a 5G network according to claim 1, wherein: In step S1, the transmission distance of the transmission channel cannot be obtained directly. The system calculates the physical distance between the two transmission devices and the network signal strength where the two transmission devices are located, and then performs a hierarchical summation to obtain the calculated result; the transmission data volume of the transmission channel is obtained by detecting the size of the storage space occupied by the transmission data in the system.

3. The method for transmitting real-time multimedia messages based on a 5G network according to claim 2, wherein: In step S1, the system sets up multiple groups of transmission equipment, detects the transmission distance and transmission data volume of each group of transmission channels respectively, and performs normalization processing to obtain multiple groups of transmission distance coefficients and transmission volume coefficients.

4. The method for transmitting real-time multimedia messages based on a 5G network according to claim 1, wherein: In step S2, the system calculates the transmission distance coefficient and transmission volume coefficient of the transmission data to be tested and takes the average value as the transmission data error rate. When the transmission data error rate exceeds the error threshold, the system determines that the transmission data to be tested is prone to errors and uses the accumulation and verification algorithm to make an initial judgment on the transmission data.

5. The method for real-time multimedia message transmission based on a 5G network according to claim 1, characterized in that: In step S3, the data source obtains all data sources of the transmitted data by accessing the metadata field in the database table and records the number of data sources of the transmitted data; when obtaining the data update frequency, the number of supplementary transmissions of the transmitted data is recorded by setting a time period to reflect the data update frequency.

6. The method for real-time multimedia message transmission based on a 5G network according to claim 4, characterized in that: In step S3, the specific steps of using fuzzy reasoning to analyze the degree of data duplication are as follows: The number of data sources and the number of supplementary transmissions are defined as input variables and divided into fuzzy sets; The degree of data duplication is defined as the output variable and divided into fuzzy sets; Formulate fuzzy rules to describe the impact of the number of data sources and the number of supplementary transmissions on the degree of data duplication; Perform fuzzy reasoning based on fuzzy rules to determine the degree of data duplication.

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