5G-based data efficient transmission method, system and medium

Abstract

The present application provides a method, system, and medium for efficient data transmission based on 5G. The method comprises: obtaining data transmission demand data and data type characteristic data of a data transmission service, processing the data transmission demand data to obtain a data transmission demand level, allocating wireless resource blocks, obtaining wireless resource blocks for data transmission, obtaining state evaluation data of wireless channels, processing the state evaluation data to obtain wireless channel quality status, and finally, performing data transmission based on the wireless resource blocks for data transmission and the wireless channel quality status; the present application realizes dynamic optimal allocation of wireless resources and optimal wireless channel scheduling by evaluating data transmission demand and evaluating wireless channels for data transmission, thereby realizing efficient data transmission based on 5G.

Description

Technical Field

[0001] The present application relates to the field of mobile data communication technology, and more specifically, to a method, system, and medium for efficient data transmission based on 5G. Background Art

[0002] With its high bandwidth, low latency and large capacity, 5G technology has promoted the vigorous development of emerging applications such as autonomous driving, telemedicine, and industrial Internet. However, in terms of resource allocation in the traditional data transmission process, traditional 5G resource allocation methods mostly adopt fixed or semi-fixed strategies, which are difficult to meet the dynamic needs of diversified services. At the channel utilization level, wireless channels are time-varying and complex. The current 5G network's processing of channel status is mostly limited to real-time monitoring, and there is a lack of effective prediction of channel change trends. Therefore, the existing 5G data transmission methods have obvious defects in resource allocation and channel utilization, and are difficult to adapt to the complex and changing network environment and diversified business needs.

[0003] In response to the above problems, effective technical solutions are urgently needed. Summary of the Invention

[0004] The purpose of this application is to provide a 5G-based data efficient transmission method, system and medium, which can achieve dynamic optimal allocation of wireless resources and optimal wireless channel scheduling by evaluating data transmission requirements and evaluating data transmission wireless channels, thereby realizing efficient data transmission based on 5G.

[0005] This application also provides a 5G-based data efficient transmission method, comprising the following steps:

[0006] Obtaining data transmission demand data and data type characteristic data of the data transmission service;

[0007] Processing the data transmission requirement data to obtain a data transmission requirement level, and allocating wireless resource blocks to obtain wireless resource blocks for data transmission;

[0008] Obtain status evaluation data of wireless channels;

[0009] Processing the status evaluation data to obtain a wireless channel quality status;

[0010] Data transmission is performed according to the data transmission radio resource block and the radio channel quality status.

[0011] Optionally, in the 5G-based data efficient transmission method described in the present application, processing the data transmission requirement data to obtain the data transmission requirement level, and performing wireless resource block allocation to obtain the data transmission wireless resource block includes:

[0012] The data transmission requirement data includes the transmission data volume, flow requirement preset data and delay permission value;

[0013] Obtain the historical average data volume, historical traffic demand average data and historical delay permission average data within a preset time period;

[0014] Compare the transmission data volume, traffic demand preset data and delay tolerance value with the corresponding historical transmission data volume average, historical traffic demand average data and historical delay tolerance value to obtain the transmission data excess rate, traffic demand excess rate and delay tolerance rate;

[0015] Performing weighted sum processing on the transmission data excess rate, the flow demand excess rate and the delay tolerance rate to obtain a data transmission demand evaluation parameter;

[0016] Comparing the data transmission demand evaluation parameter with a preset data transmission demand evaluation threshold to obtain a data transmission demand level, including high demand, medium demand, or low demand;

[0017] Radio resource blocks are allocated according to the data transmission requirement level using a preset resource allocation method to obtain radio resource blocks for data transmission.

[0018] Optionally, in the 5G-based efficient data transmission method described in the present application, the processing according to the status evaluation data to obtain the wireless channel quality status includes:

[0019] The status evaluation data includes received signal strength, signal-to-noise ratio, channel fading coefficient, device moving speed and device moving direction characteristic data;

[0020] Inputting the received signal strength, signal-to-noise ratio, channel fading coefficient, device moving speed, and device moving direction characteristic data into a preset wireless channel quality evaluation model for processing to obtain wireless channel evaluation parameters;

[0021] The wireless channel evaluation parameter is compared with a preset wireless channel evaluation threshold to obtain a wireless channel quality status, including an excellent wireless channel or a poor wireless channel.

[0022] Optionally, the 5G-based efficient data transmission method described in this application further includes:

[0023] Compare the wireless channel evaluation parameters at different preset time points to obtain the wireless channel quality degradation rate;

[0024] Comparing the wireless channel quality degradation rate with a preset wireless channel quality attenuation threshold;

[0025] If the value is less than or equal to the preset wireless channel quality attenuation threshold, the wireless channel is determined to be normal;

[0026] If it is greater than a preset wireless channel quality attenuation threshold, it is determined that the wireless channel is about to become abnormal, and the data transmission service is scheduled.

[0027] Optionally, the 5G-based efficient data transmission method described in this application further includes:

[0028] Determining a data compression algorithm based on the data type characteristic data, including a lossless compression algorithm or a lossy compression algorithm;

[0029] The data to be transmitted of the data transmission service is compressed according to the data compression algorithm to obtain a compressed data packet.

[0030] Optionally, the 5G-based efficient data transmission method described in this application further includes:

[0031] Obtain data transmission application scenario information;

[0032] Querying a preset application scenario and network slice resource mapping table according to the data transmission application scenario information to obtain slice network resources, including bandwidth configuration data and flow control data;

[0033] Optimize the slice network resources according to the data transmission demand level by using a preset network resource optimization method to obtain slice network optimized resources;

[0034] Data transmission is performed based on the slice network optimized resources.

[0035] Optionally, the 5G-based efficient data transmission method described in this application further includes:

[0036] Get the number of data packets to be transmitted by the data transmission party;

[0037] Comparing the number of packets to be transmitted with a preset threshold;

[0038] If it is greater than the preset threshold, the data packets to be transmitted are aggregated to obtain an aggregated data packet;

[0039] The aggregated data packets are used for data transmission.

[0040] In a second aspect, the present application provides a 5G-based data efficient transmission system, the system comprising: a memory and a processor, the memory comprising a program for a 5G-based data efficient transmission method, and the program for the 5G-based data efficient transmission method, when executed by the processor, implements the following steps:

[0041] Obtaining data transmission demand data and data type characteristic data of the data transmission service;

[0042] Processing the data transmission requirement data to obtain a data transmission requirement level, and allocating wireless resource blocks to obtain wireless resource blocks for data transmission;

[0043] Obtain status evaluation data of wireless channels;

[0044] Processing the status evaluation data to obtain a wireless channel quality status;

[0045] Data transmission is performed according to the data transmission radio resource block and the radio channel quality status.

[0046] Optionally, in the 5G-based data efficient transmission system described in the present application, the processing according to the data transmission requirement data to obtain the data transmission requirement level, and performing wireless resource block allocation to obtain the data transmission wireless resource block includes:

[0047] The data transmission requirement data includes the transmission data volume, flow requirement preset data and delay permission value;

[0048] Obtain the historical average data volume, historical traffic demand average data and historical delay permission average data within a preset time period;

[0049] Compare the transmission data volume, traffic demand preset data and delay tolerance value with the corresponding historical transmission data volume average, historical traffic demand average data and historical delay tolerance value to obtain the transmission data excess rate, traffic demand excess rate and delay tolerance rate;

[0050] Performing weighted sum processing on the transmission data excess rate, the flow demand excess rate and the delay tolerance rate to obtain a data transmission demand evaluation parameter;

[0051] Comparing the data transmission demand evaluation parameter with a preset data transmission demand evaluation threshold to obtain a data transmission demand level, including high demand, medium demand, or low demand;

[0052] Radio resource blocks are allocated according to the data transmission requirement level using a preset resource allocation method to obtain radio resource blocks for data transmission.

[0053] On the third aspect, the present application also provides a computer-readable storage medium, which stores a 5G-based data efficient transmission method program. When the 5G-based data efficient transmission method program is executed by a processor, the steps of the 5G-based data efficient transmission method as described in any one of the above items are implemented.

[0054] From the above, it can be seen that the 5G-based data efficient transmission method, system and medium provided in this application realize dynamic optimal allocation of wireless resources and optimal wireless channel scheduling by evaluating data transmission requirements and evaluating data transmission wireless channels, thereby realizing efficient data transmission based on 5G.

[0055] Other features and advantages of the present application will be described in the following description, and in part will become apparent from the description, or understood by practicing the embodiments of the present application. The objectives and other advantages of the present application can be achieved and obtained through the structures particularly pointed out in the written description and the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following is a brief introduction to the drawings required for use in the embodiments of the present application. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other relevant drawings can be obtained based on these drawings without creative work.

[0057] Figure 1 Flowchart of a 5G-based efficient data transmission method provided in an embodiment of the present application;

[0058] Figure 2 A flowchart of obtaining a wireless resource block for data transmission according to a 5G-based efficient data transmission method provided in an embodiment of the present application;

[0059] Figure 3 A flowchart of obtaining the wireless channel quality status of the 5G-based efficient data transmission method provided in an embodiment of the present application;

[0060] Figure 4 A high-level flowchart of methods according to various embodiments of the present application. DETAILED DESCRIPTION

[0061] The technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all of the embodiments. The components of the embodiments of the present application generally described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the application for protection, but merely represents the selected embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without making creative work fall within the scope of protection of the present application.

[0062] It should be noted that similar reference numerals and letters represent similar items in the following drawings. Therefore, once an item is defined in one drawing, it does not need to be further defined or explained in subsequent drawings. At the same time, in the description of this application, the terms "first", "second", etc. are only used to distinguish the description and should not be understood as indicating or implying relative importance.

[0063] Please refer to Figure 1 , Figure 1 Flowchart of a 5G-based efficient data transmission method in some embodiments of the present application. The 5G-based efficient data transmission method is used in terminal devices, such as computers, mobile phones, etc. The 5G-based efficient data transmission method includes the following steps:

[0064] S11. Acquire data transmission requirement data and data type characteristic data of the data transmission service;

[0065] S12. Processing the data transmission requirement data to obtain a data transmission requirement level, and allocating wireless resource blocks to obtain wireless resource blocks for data transmission;

[0066] S13, obtaining status evaluation data of the wireless channel;

[0067] S14. Processing the status evaluation data to obtain a wireless channel quality status;

[0068] S15. Perform data transmission according to the data transmission wireless resource block and wireless channel quality status.

[0069] It should be noted that in order to achieve efficient data transmission based on 5G network resources, a wireless resource allocation module is constructed on the 5G network base station side. The purpose is to reasonably allocate wireless resources according to the real-time monitored data transmission needs, improve resource utilization, and after determining the wireless resource allocation, evaluate and predict the quality of the wireless channel in real time. Based on the prediction of the channel status, forward-looking resource scheduling is performed to avoid data transmission interruption or rate reduction due to channel deterioration, and ensure the continuity and efficiency of data transmission.

[0070] Please refer to Figure 2 , Figure 2 This is a flow chart of obtaining a data transmission wireless resource block for a 5G-based data efficient transmission method in some embodiments of the present application. According to an embodiment of the present invention, processing the data transmission demand data to obtain a data transmission demand level and allocating wireless resource blocks to obtain a data transmission wireless resource block includes:

[0071] S21, the data transmission requirement data includes the transmission data volume, the flow requirement preset data and the delay permission value;

[0072] S22. Obtain the historical average value of the amount of transmitted data, the historical average value of traffic demand, and the historical average value of delay permission within a preset time period;

[0073] S23, comparing the transmission data volume, traffic demand preset data, and delay tolerance value with the corresponding historical transmission data volume average, historical traffic demand average data, and historical delay tolerance average to obtain a transmission data excess rate, a traffic demand excess rate, and a delay tolerance rate;

[0074] S24, performing weighted sum processing on the transmission data excess rate, the flow demand excess rate, and the delay tolerance rate to obtain a data transmission demand evaluation parameter;

[0075] S25. Compare the data transmission demand evaluation parameter with a preset data transmission demand evaluation threshold to obtain a data transmission demand level, including high demand, medium demand, or low demand;

[0076] S26. Allocate wireless resource blocks according to the data transmission requirement level using a preset resource allocation method to obtain wireless resource blocks for data transmission.

[0077] It should be noted that in order to evaluate the data transmission demand, the transmission data volume, traffic demand preset data and delay tolerance value obtained by real-time monitoring are compared with the corresponding historical averages to obtain the corresponding transmission data exceedance rate, traffic demand exceedance rate and delay tolerance rate. Among them, the transmission data exceedance rate refers to the ratio of the difference between the transmission data volume and the historical transmission data volume average to the historical transmission data volume average. If it is a negative value, it is recorded as 0; the traffic demand exceedance rate refers to the ratio of the difference between the traffic demand preset data and the historical traffic demand average data to the historical traffic demand average data. If it is a negative value, it is recorded as 0; the delay tolerance rate refers to the ratio of the difference between the historical delay permission mean and the delay permission value to the historical delay permission mean. If it is a negative value, it is recorded as 0, that is, the minimum bit of the data transmission demand evaluation parameter is 0; then, the obtained transmission data excess rate, traffic demand excess rate and delay tolerance rate are weighted and summed to obtain the data transmission demand evaluation parameter. Finally, a threshold comparison is performed, and the data transmission demand level is determined according to the threshold range within which it falls, and wireless resources are allocated according to the preset method to ensure transmission efficiency.

[0078] Please refer to Figure 3 , Figure 3 This is a flow chart of obtaining the wireless channel quality status of a 5G-based data efficient transmission method in some embodiments of the present application. According to an embodiment of the present invention, the processing according to the status evaluation data to obtain the wireless channel quality status includes:

[0079] S31, the status evaluation data includes received signal strength, signal-to-noise ratio, channel fading coefficient, device moving speed and device moving direction characteristic data;

[0080] S32: Inputting the received signal strength, signal-to-noise ratio, channel fading coefficient, device moving speed, and device moving direction characteristic data into a preset wireless channel quality evaluation model for processing to obtain wireless channel evaluation parameters;

[0081] S33: performing a threshold comparison between the wireless channel evaluation parameter and a preset wireless channel evaluation threshold to obtain a wireless channel quality status, including an excellent wireless channel or a poor wireless channel.

[0082] It should be noted that the quality of the wireless channel determines the efficiency of wireless transmission. It is evaluated and predicted in real time through pre-trained models and threshold comparison. When it is predicted that the channel quality of a certain area will decline at a certain time, the data services to be transmitted by the data transmission users in the area will be intelligently scheduled to the superior channel to avoid data transmission interruption or rate reduction due to deterioration of channel quality, thereby achieving continuous and efficient data transmission. Among them, the device movement direction characteristic data represents the movement direction between the data transmission device and the base station. The preset wireless channel quality evaluation model is obtained by training by obtaining a large number of historical samples of signal strength, signal-to-noise ratio, channel fading coefficient, device movement speed and device movement direction characteristic data and corresponding wireless channel evaluation parameters, and the model is optimized according to the real-time prediction situation.

[0083] According to an embodiment of the present invention, the further embodiment includes:

[0084] Compare the wireless channel evaluation parameters at different preset time points to obtain the wireless channel quality degradation rate;

[0085] Comparing the wireless channel quality degradation rate with a preset wireless channel quality attenuation threshold;

[0086] If the value is less than or equal to the preset wireless channel quality attenuation threshold, the wireless channel is determined to be normal;

[0087] If it is greater than a preset wireless channel quality attenuation threshold, it is determined that the wireless channel is about to become abnormal, and the data transmission service is scheduled.

[0088] It should be noted that in order to prevent false alarms in channel prediction and improve the continuity and timeliness of channel quality monitoring, the wireless channel evaluation parameters at different time points are compared to obtain the wireless channel quality degradation rate. That is, the wireless channel evaluation parameters at the previous time point are subtracted from the wireless channel evaluation parameters at the next time point and then compared with the wireless channel evaluation parameters at the previous time point. Then, the threshold comparison is used to determine whether the wireless channel is about to become abnormal.

[0089] According to an embodiment of the present invention, the further embodiment includes:

[0090] Determining a data compression algorithm based on the data type characteristic data, including a lossless compression algorithm or a lossy compression algorithm;

[0091] The data to be transmitted of the data transmission service is compressed according to the data compression algorithm to obtain a compressed data packet.

[0092] It should be noted that using an effective data compression algorithm to compress data before data transmission can greatly improve transmission efficiency. Among them, lossless compression algorithms are suitable for data structures such as text, and lossy compression algorithms are suitable for images, audio and video.

[0093] According to an embodiment of the present invention, the further embodiment includes:

[0094] Obtain data transmission application scenario information;

[0095] Querying a preset application scenario and network slice resource mapping table according to the data transmission application scenario information to obtain slice network resources, including bandwidth configuration data and flow control data;

[0096] Optimize the slice network resources according to the data transmission demand level by using a preset network resource optimization method to obtain slice network optimized resources;

[0097] Data transmission is performed based on the slice network optimized resources.

[0098] It should be noted that large data packets are divided into multiple small data slices, and each data slice is assigned a sub-channel. Before data slicing, the data application scenarios should be understood to improve adaptability. For example, in autonomous driving and high-definition video streaming, the sliced ​​network resources are determined based on information queries for different application scenarios. Among them, the preset application scenarios and network slice resource mapping tables are pre-set by technical personnel in this field based on experience or specific applications, and can be dynamically adjusted to obtain bandwidth configuration data and flow control data, and then further optimized based on the data transmission demand level obtained by evaluation, which can further improve the efficiency of data transmission.

[0099] According to an embodiment of the present invention, the further embodiment includes:

[0100] Get the number of data packets to be transmitted by the data transmission party;

[0101] Comparing the number of packets to be transmitted with a preset threshold;

[0102] If it is greater than the preset threshold, the data packets to be transmitted are aggregated to obtain an aggregated data packet;

[0103] The aggregated data packets are used for data transmission.

[0104] It should be noted that the number of data packets transmitted by data transmission users each time is different. In order to optimize data transmission efficiency, the number of data packets is further evaluated after considering the data transmission size. Too many data packets will increase the number of message primitives processed for interaction between protocol layers, increase the system processor load, and reduce data transmission efficiency. Therefore, when the number of data packets to be transmitted is greater than the preset threshold, packet processing is performed to reduce the number of data packets, reduce protocol layer interactions, and reduce processor load. If it is not greater than the preset threshold, data transmission can be carried out normally.

[0105] Please refer to Figure 4 , Figure 4 This is a high-level flow chart of the methods of various embodiments of the present application, which can be used for efficient data transmission methods based on 5G. According to the embodiments of the present invention, the data transmission requirements and wireless channels are evaluated respectively, the data transmission requirement level and the wireless channel quality status are determined, the wireless resource block allocation is implemented, and the data transmission service is scheduled. At the same time, the data compression algorithm is determined according to the data type characteristic data, the slice network resources are determined according to the data transmission application scenario information, and it is determined whether the data packets to be transmitted need to be aggregated, so as to improve the adaptability of data transmission and ensure transmission efficiency.

[0106] It is worth mentioning that according to an embodiment of the present invention, the present invention further includes:

[0107] Obtain network status characteristic data of data transmission network nodes, including bandwidth utilization, delay data, packet loss rate and traffic load data;

[0108] Inputting the bandwidth utilization, delay data, packet loss rate and traffic load data into a preset network status evaluation model for processing to obtain a network status, including excellent network, good network or poor network;

[0109] The data transmission path is optimized according to the network status.

[0110] It should be noted that in order to dynamically monitor the network status of each node in data transmission and optimize the transmission path according to the network status, the real-time monitored bandwidth utilization, delay data, packet loss rate and traffic load data are input into the preset network status evaluation model for processing to obtain the network status. The preset network status evaluation model is trained by obtaining a large number of historical samples of bandwidth utilization, delay data, packet loss rate and traffic load data and the corresponding network status.

[0111] It is worth mentioning that according to an embodiment of the present invention, the present invention further includes:

[0112] Get the data packet to be transmitted;

[0113] Segmenting the data packet at a preset edge node to obtain data fragments;

[0114] The data segments are transmitted via preset sub-channels.

[0115] It should be noted that combining data transmission with edge computing, slicing the data packets to be transmitted by presetting edge nodes, and sinking computing and storage resources to the edge of the network can effectively reduce data transmission delays.

[0116] It is worth mentioning that according to an embodiment of the present invention, the present invention further includes:

[0117] Obtain the load status of the data transmission link, including overload or underload;

[0118] If the load state is light, data is transmitted via the 5G main link;

[0119] If the load state is overloaded, obtaining a bandwidth fluctuation value and a signal strength average value of the auxiliary link within a preset time period;

[0120] Inputting the bandwidth fluctuation value and the signal strength mean into a preset link stability evaluation model for processing to obtain link stability evaluation parameters;

[0121] If the link stability evaluation parameter is greater than or equal to a preset link stability evaluation threshold, the data to be transmitted is transmitted through the auxiliary link;

[0122] If it is less than the preset link stability assessment threshold, an early warning response is output.

[0123] It should be noted that the data transmission load is different at different time points and in different transmission areas. Technical personnel in this field can analyze and evaluate based on the resource occupancy rate, data transmission rate, transmission delay and packet loss rate of the main link. When the data transmission link is overloaded, seek assistance from an auxiliary link, such as Bluetooth and WiFi. Before transmitting data on the auxiliary link, the stability of the auxiliary link is evaluated by comparing the preset link stability evaluation model and the threshold. If it is greater than or equal to the preset link stability evaluation threshold, data diversion is performed, and the data to be transmitted is transmitted through the auxiliary link to reduce the burden on the 5G main link. The preset link stability evaluation model is obtained by training by obtaining the bandwidth fluctuation value and signal strength mean of a large number of historical samples and the corresponding link stability evaluation parameters.

[0124] It is worth mentioning that according to an embodiment of the present invention, the present invention further includes:

[0125] Acquire real-time signal information of data transmission, perform data extraction, obtain the amplitude and phase values ​​of the interference signal, and generate a signal feature matrix;

[0126] Extracting features from the signal feature matrix to obtain interference signal feature data;

[0127] Inputting the interference signal characteristic data into a preset interference type prediction model for processing to obtain interference type characteristic data;

[0128] The interference signal is suppressed according to the interference type characteristic data in combination with a preset interference suppression algorithm.

[0129] It should be noted that during the data transmission process, the data transmission signal is monitored in real time, and the interference type is determined in combination with the deep learning model. Different interference signals should adopt different suppression measures to ensure the quality of data transmission. Interference signals such as adjacent channel interference and co-frequency interference, and suppression measures such as adaptive filtering and interference cancellation. Among them, the preset interference type prediction model is obtained by learning, training and optimizing a large number of signal samples containing various interference types.

[0130] The present invention also discloses a 5G-based data efficient transmission system, including a memory and a processor, wherein the memory includes a 5G-based data efficient transmission method program, and when the 5G-based data efficient transmission method program is executed by the processor, the following steps are implemented:

[0131] Obtaining data transmission demand data and data type characteristic data of the data transmission service;

[0132] Processing the data transmission requirement data to obtain a data transmission requirement level, and allocating wireless resource blocks to obtain wireless resource blocks for data transmission;

[0133] Obtain status evaluation data of wireless channels;

[0134] Processing the status evaluation data to obtain a wireless channel quality status;

[0135] Data transmission is performed according to the data transmission radio resource block and the radio channel quality status.

[0136] It should be noted that in order to achieve efficient data transmission based on 5G network resources, a wireless resource allocation module is constructed on the 5G network base station side. The purpose is to reasonably allocate wireless resources according to the real-time monitored data transmission needs, improve resource utilization, and after determining the wireless resource allocation, evaluate and predict the quality of the wireless channel in real time. Based on the prediction of the channel status, forward-looking resource scheduling is performed to avoid data transmission interruption or rate reduction due to channel deterioration, and ensure the continuity and efficiency of data transmission.

[0137] According to an embodiment of the present invention, the processing according to the data transmission requirement data to obtain the data transmission requirement level, and performing wireless resource block allocation to obtain the data transmission wireless resource block includes:

[0138] The data transmission requirement data includes the transmission data volume, flow requirement preset data and delay permission value;

[0139] Obtain the historical average data volume, historical traffic demand average data and historical delay permission average data within a preset time period;

[0140] Compare the transmission data volume, traffic demand preset data and delay tolerance value with the corresponding historical transmission data volume average, historical traffic demand average data and historical delay tolerance value to obtain the transmission data excess rate, traffic demand excess rate and delay tolerance rate;

[0141] Performing weighted sum processing on the transmission data excess rate, the flow demand excess rate and the delay tolerance rate to obtain a data transmission demand evaluation parameter;

[0142] Comparing the data transmission demand evaluation parameter with a preset data transmission demand evaluation threshold to obtain a data transmission demand level, including high demand, medium demand, or low demand;

[0143] Radio resource blocks are allocated according to the data transmission requirement level using a preset resource allocation method to obtain radio resource blocks for data transmission.

[0144] It should be noted that in order to evaluate the data transmission demand, the transmission data volume, traffic demand preset data and delay tolerance value obtained by real-time monitoring are compared with the corresponding historical averages to obtain the corresponding transmission data exceedance rate, traffic demand exceedance rate and delay tolerance rate. Among them, the transmission data exceedance rate refers to the ratio of the difference between the transmission data volume and the historical transmission data volume average to the historical transmission data volume average. If it is a negative value, it is recorded as 0; the traffic demand exceedance rate refers to the ratio of the difference between the traffic demand preset data and the historical traffic demand average data to the historical traffic demand average data. If it is a negative value, it is recorded as 0; the delay tolerance rate refers to the ratio of the difference between the historical delay permission mean and the delay permission value to the historical delay permission mean. If it is a negative value, it is recorded as 0, that is, the minimum bit of the data transmission demand evaluation parameter is 0; then, the obtained transmission data excess rate, traffic demand excess rate and delay tolerance rate are weighted and summed to obtain the data transmission demand evaluation parameter. Finally, a threshold comparison is performed, and the data transmission demand level is determined according to the threshold range within which it falls, and wireless resources are allocated according to the preset method to ensure transmission efficiency.

[0145] According to an embodiment of the present invention, the processing according to the status evaluation data to obtain the wireless channel quality status includes:

[0146] The status evaluation data includes received signal strength, signal-to-noise ratio, channel fading coefficient, device moving speed and device moving direction characteristic data;

[0147] Inputting the received signal strength, signal-to-noise ratio, channel fading coefficient, device moving speed, and device moving direction characteristic data into a preset wireless channel quality evaluation model for processing to obtain wireless channel evaluation parameters;

[0148] The wireless channel evaluation parameter is compared with a preset wireless channel evaluation threshold to obtain a wireless channel quality status, including an excellent wireless channel or a poor wireless channel.

[0149] It should be noted that the quality of the wireless channel determines the efficiency of wireless transmission. It is evaluated and predicted in real time through pre-trained models and threshold comparison. When it is predicted that the channel quality of a certain area will decline at a certain time, the data services to be transmitted by the data transmission users in the area will be intelligently scheduled to the superior channel to avoid data transmission interruption or rate reduction due to deterioration of channel quality, thereby achieving continuous and efficient data transmission. Among them, the device movement direction characteristic data represents the movement direction between the data transmission device and the base station. The preset wireless channel quality evaluation model is obtained by training by obtaining a large number of historical samples of signal strength, signal-to-noise ratio, channel fading coefficient, device movement speed and device movement direction characteristic data and corresponding wireless channel evaluation parameters, and the model is optimized according to the real-time prediction situation.

[0150] According to an embodiment of the present invention, the further embodiment includes:

[0151] Compare the wireless channel evaluation parameters at different preset time points to obtain the wireless channel quality degradation rate;

[0152] Comparing the wireless channel quality degradation rate with a preset wireless channel quality attenuation threshold;

[0153] If the value is less than or equal to the preset wireless channel quality attenuation threshold, the wireless channel is determined to be normal;

[0154] If it is greater than a preset wireless channel quality attenuation threshold, it is determined that the wireless channel is about to become abnormal, and the data transmission service is scheduled.

[0155] It should be noted that in order to prevent false alarms in channel prediction and improve the continuity and timeliness of channel quality monitoring, the wireless channel evaluation parameters at different time points are compared to obtain the wireless channel quality degradation rate. That is, the wireless channel evaluation parameters at the previous time point are subtracted from the wireless channel evaluation parameters at the next time point and then compared with the wireless channel evaluation parameters at the previous time point. Then, the threshold comparison is used to determine whether the wireless channel is about to become abnormal.

[0156] According to an embodiment of the present invention, the further embodiment includes:

[0157] Determining a data compression algorithm based on the data type characteristic data, including a lossless compression algorithm or a lossy compression algorithm;

[0158] The data to be transmitted of the data transmission service is compressed according to the data compression algorithm to obtain a compressed data packet.

[0159] It should be noted that using an effective data compression algorithm to compress data before data transmission can greatly improve transmission efficiency. Among them, lossless compression algorithms are suitable for data structures such as text, and lossy compression algorithms are suitable for images, audio and video.

[0160] According to an embodiment of the present invention, the further embodiment includes:

[0161] Obtain data transmission application scenario information;

[0162] Querying a preset application scenario and network slice resource mapping table according to the data transmission application scenario information to obtain slice network resources, including bandwidth configuration data and flow control data;

[0163] Optimize the slice network resources according to the data transmission demand level by using a preset network resource optimization method to obtain slice network optimized resources;

[0164] Data transmission is performed based on the slice network optimized resources.

[0165] It should be noted that large data packets are divided into multiple small data slices, and each data slice is assigned a sub-channel. Before data slicing, the data application scenarios should be understood to improve adaptability. For example, in autonomous driving and high-definition video streaming, the sliced ​​network resources are determined based on information queries for different application scenarios. Among them, the preset application scenarios and network slice resource mapping tables are pre-set by technical personnel in this field based on experience or specific applications, and can be dynamically adjusted to obtain bandwidth configuration data and flow control data, and then further optimized based on the data transmission demand level obtained by evaluation, which can further improve the efficiency of data transmission.

[0166] According to an embodiment of the present invention, the further embodiment includes:

[0167] Get the number of data packets to be transmitted by the data transmission party;

[0168] Comparing the number of packets to be transmitted with a preset threshold;

[0169] If it is greater than the preset threshold, the data packets to be transmitted are aggregated to obtain an aggregated data packet;

[0170] The aggregated data packets are transmitted for data transmission.

[0171] It should be noted that the number of data packets transmitted by data transmission users each time is different. In order to optimize data transmission efficiency, the number of data packets is further evaluated after considering the data transmission size. Too many data packets will increase the number of message primitives processed for interaction between protocol layers, increase the system processor load, and reduce data transmission efficiency. Therefore, when the number of data packets to be transmitted is greater than the preset threshold, packet processing is performed to reduce the number of data packets, reduce protocol layer interactions, and reduce processor load. If it is not greater than the preset threshold, data transmission can be carried out normally.

[0172] According to an embodiment of the present invention, data transmission requirements and wireless channels are evaluated respectively, the data transmission requirement level and the wireless channel quality status are determined, wireless resource block allocation is implemented and data transmission services are scheduled. At the same time, the data compression algorithm is determined according to the data type characteristic data, the slice network resources are determined according to the data transmission application scenario information, and it is determined whether the data packets to be transmitted need to be aggregated, so as to improve the adaptability of data transmission and ensure transmission efficiency.

[0173] It is worth mentioning that according to an embodiment of the present invention, the present invention further includes:

[0174] Obtain network status characteristic data of data transmission network nodes, including bandwidth utilization, delay data, packet loss rate and traffic load data;

[0175] Inputting the bandwidth utilization, delay data, packet loss rate and traffic load data into a preset network status evaluation model for processing to obtain a network status, including excellent network, good network or poor network;

[0176] The data transmission path is optimized according to the network status.

[0177] It should be noted that in order to dynamically monitor the network status of each node in data transmission and optimize the transmission path according to the network status, the real-time monitored bandwidth utilization, delay data, packet loss rate and traffic load data are input into the preset network status evaluation model for processing to obtain the network status. The preset network status evaluation model is trained by obtaining a large number of historical samples of bandwidth utilization, delay data, packet loss rate and traffic load data and the corresponding network status.

[0178] It is worth mentioning that according to an embodiment of the present invention, the present invention further includes:

[0179] Get the data packet to be transmitted;

[0180] Segmenting the data packet at a preset edge node to obtain data fragments;

[0181] The data slices are transmitted through preset sub-channels.

[0182] It should be noted that combining data transmission with edge computing, slicing the data packets to be transmitted by presetting edge nodes, and sinking computing and storage resources to the edge of the network can effectively reduce data transmission delays.

[0183] It is worth mentioning that according to an embodiment of the present invention, the present invention further includes:

[0184] Obtain the load status of the data transmission link, including overload or underload;

[0185] If the load state is light, data is transmitted via the 5G main link;

[0186] If the load state is overloaded, obtaining a bandwidth fluctuation value and a signal strength average value of the auxiliary link within a preset time period;

[0187] Inputting the bandwidth fluctuation value and the signal strength mean into a preset link stability evaluation model for processing to obtain link stability evaluation parameters;

[0188] If the link stability evaluation parameter is greater than or equal to a preset link stability evaluation threshold, the data to be transmitted is transmitted through the auxiliary link;

[0189] If it is less than the preset link stability assessment threshold, an early warning response is output.

[0190] It should be noted that the data transmission load is different at different time points and in different transmission areas. Technical personnel in this field can analyze and evaluate based on the resource occupancy rate, data transmission rate, transmission delay and packet loss rate of the main link. When the data transmission link is overloaded, seek assistance from an auxiliary link, such as Bluetooth and WiFi. Before transmitting data on the auxiliary link, the stability of the auxiliary link is evaluated by comparing the preset link stability evaluation model and the threshold. If it is greater than or equal to the preset link stability evaluation threshold, data diversion is performed, and the data to be transmitted is transmitted through the auxiliary link to reduce the burden on the 5G main link. The preset link stability evaluation model is obtained by training by obtaining the bandwidth fluctuation value and signal strength mean of a large number of historical samples and the corresponding link stability evaluation parameters.

[0191] It is worth mentioning that according to an embodiment of the present invention, the present invention further includes:

[0192] Acquire real-time signal information of data transmission, perform data extraction, obtain the amplitude and phase values ​​of the interference signal, and generate a signal feature matrix;

[0193] Extracting features from the signal feature matrix to obtain interference signal feature data;

[0194] Inputting the interference signal characteristic data into a preset interference type prediction model for processing to obtain interference type characteristic data;

[0195] The interference signal is suppressed according to the interference type characteristic data in combination with a preset interference suppression algorithm.

[0196] It should be noted that during the data transmission process, the data transmission signal is monitored in real time, and the interference type is determined in combination with the deep learning model. Different interference signals should adopt different suppression measures to ensure the quality of data transmission. Interference signals such as adjacent channel interference and co-frequency interference, and suppression measures such as adaptive filtering and interference cancellation. Among them, the preset interference type prediction model is obtained by learning, training and optimizing a large number of signal samples containing various interference types.

[0197] The third aspect of the present invention provides a readable storage medium, which stores a 5G-based data efficient transmission method program. When the 5G-based data efficient transmission method program is executed by a processor, the steps of the 5G-based data efficient transmission method as described in any one of the above items are implemented.

[0198] The 5G-based efficient data transmission method, system and medium disclosed in the present invention realize dynamic optimal allocation of wireless resources and optimal wireless channel scheduling by evaluating data transmission requirements and evaluating data transmission wireless channels, thereby realizing efficient data transmission based on 5G.

[0199] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are merely schematic. For example, the division of the units is merely a logical function division. In actual implementation, there may be other division methods, such as: multiple units or components can be combined, or can be integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the components shown or discussed can be through some interfaces, and the indirect coupling or communication connection of the devices or units can be electrical, mechanical or other forms.

[0200] The units described above as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units; they may be located in one place or distributed across multiple network units; some or all of the units may be selected according to actual needs to achieve the purpose of the scheme of this embodiment.

[0201] In addition, all functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may be separately used as a unit, or two or more units may be integrated into one unit; the above-mentioned integrated units may be implemented in the form of hardware or in the form of hardware plus software functional units.

[0202] Those skilled in the art will appreciate that all or part of the steps of the above-mentioned method embodiments may be implemented by hardware related to program instructions, and the aforementioned program may be stored in a readable storage medium. When the program is executed, the program executes the steps of the above-mentioned method embodiments. The aforementioned storage medium includes various media that can store program codes, such as mobile storage devices, read-only memories (ROMs), random access memories (RAMs), magnetic disks, or optical disks.

[0203] Alternatively, if the integrated units described above are implemented as software functional modules and sold or used as standalone products, they can also be stored on a readable storage medium. Based on this understanding, the technical solutions of the embodiments of the present invention, or the portion that contributes to the prior art, can be embodied in the form of a software product. This software product, stored on a storage medium, includes instructions for enabling a computer device (such as a personal computer, server, or network device) to execute all or part of the methods described in the various embodiments of the present invention. The aforementioned storage media include various media capable of storing program code, such as removable storage devices, ROM, RAM, magnetic disks, or optical disks.

Claims

1. A 5G-based data efficient transmission method, characterized in that: The following steps are involved: Obtaining data transmission demand data and data type characteristic data of the data transmission service; Processing the data transmission requirement data to obtain a data transmission requirement level, and allocating wireless resource blocks to obtain wireless resource blocks for data transmission; Obtain status evaluation data of wireless channels; Processing the status evaluation data to obtain a wireless channel quality status; Performing data transmission according to the data transmission wireless resource block and the wireless channel quality status; The processing according to the data transmission requirement data to obtain the data transmission requirement level, and performing wireless resource block allocation to obtain the data transmission wireless resource block includes: The data transmission requirement data includes the transmission data volume, flow requirement preset data and delay permission value; Obtain the historical average data volume, historical traffic demand average data and historical delay permission average data within a preset time period; Compare the transmission data volume, traffic demand preset data and delay tolerance value with the corresponding historical transmission data volume average, historical traffic demand average data and historical delay tolerance value to obtain the transmission data excess rate, traffic demand excess rate and delay tolerance rate; Performing weighted sum processing on the transmission data excess rate, the flow demand excess rate and the delay tolerance rate to obtain a data transmission demand evaluation parameter; Comparing the data transmission demand evaluation parameter with a preset data transmission demand evaluation threshold to obtain a data transmission demand level, including high demand, medium demand, or low demand; Allocating wireless resource blocks according to the data transmission demand level using a preset resource allocation method to obtain wireless resource blocks for data transmission; Also includes: Obtain data transmission application scenario information; Querying a preset application scenario and network slice resource mapping table according to the data transmission application scenario information to obtain slice network resources, including bandwidth configuration data and flow control data; Optimize the slice network resources according to the data transmission demand level by using a preset network resource optimization method to obtain slice network optimized resources; Optimizing resources for data transmission according to the slice network; Also includes: Get the number of data packets to be transmitted by the data transmission party; Comparing the number of packets to be transmitted with a preset threshold; If it is greater than the preset threshold, the data packets to be transmitted are aggregated to obtain an aggregated data packet; Transmitting the aggregated data packets for data transmission; Also includes: Get the data packet to be transmitted; Segmenting the data packet at a preset edge node to obtain data fragments; The data segments are transmitted through preset sub-channels.

2. The 5G-based data efficient transmission method according to claim 1, characterized in that: The processing according to the status evaluation data to obtain the wireless channel quality status includes: The status evaluation data includes received signal strength, signal-to-noise ratio, channel fading coefficient, device moving speed and device moving direction characteristic data; Inputting the received signal strength, signal-to-noise ratio, channel fading coefficient, device moving speed, and device moving direction characteristic data into a preset wireless channel quality evaluation model for processing to obtain wireless channel evaluation parameters; The wireless channel evaluation parameter is compared with a preset wireless channel evaluation threshold to obtain a wireless channel quality status, including an excellent wireless channel or a poor wireless channel.

3. The 5G-based data efficient transmission method according to claim 2, characterized in that: Also includes: Compare the wireless channel evaluation parameters at different preset time points to obtain the wireless channel quality degradation rate; Comparing the wireless channel quality degradation rate with a preset wireless channel quality attenuation threshold; If the value is less than or equal to the preset wireless channel quality attenuation threshold, the wireless channel is determined to be normal; If it is greater than a preset wireless channel quality attenuation threshold, it is determined that the wireless channel is about to become abnormal, and the data transmission service is scheduled.

4. The 5G-based data efficient transmission method according to claim 3, characterized in that: Also includes: Determining a data compression algorithm based on the data type characteristic data, including a lossless compression algorithm or a lossy compression algorithm; The data to be transmitted of the data transmission service is compressed according to the data compression algorithm to obtain a compressed data packet.

5. The 5G-based data efficient transmission system is characterized by: The system includes a memory and a processor, wherein the memory includes a program for a 5G-based data efficient transmission method, and when the 5G-based data efficient transmission method program is executed by the processor, the following steps are implemented: Obtaining data transmission demand data and data type characteristic data of the data transmission service; Processing the data transmission requirement data to obtain a data transmission requirement level, and allocating wireless resource blocks to obtain wireless resource blocks for data transmission; Obtain status evaluation data of wireless channels; Processing the status evaluation data to obtain a wireless channel quality status; Performing data transmission according to the data transmission wireless resource block and the wireless channel quality status; The processing according to the data transmission requirement data to obtain the data transmission requirement level, and performing wireless resource block allocation to obtain the data transmission wireless resource block includes: The data transmission requirement data includes the transmission data volume, flow requirement preset data and delay permission value; Obtain the historical average data volume, historical traffic demand average data and historical delay permission average data within a preset time period; Compare the transmission data volume, traffic demand preset data and delay tolerance value with the corresponding historical transmission data volume average, historical traffic demand average data and historical delay tolerance value to obtain the transmission data excess rate, traffic demand excess rate and delay tolerance rate; Performing weighted sum processing on the transmission data excess rate, the flow demand excess rate and the delay tolerance rate to obtain a data transmission demand evaluation parameter; Comparing the data transmission demand evaluation parameter with a preset data transmission demand evaluation threshold to obtain a data transmission demand level, including high demand, medium demand, or low demand; Allocating wireless resource blocks according to the data transmission demand level using a preset resource allocation method to obtain wireless resource blocks for data transmission; Also includes: Obtain data transmission application scenario information; Querying a preset application scenario and network slice resource mapping table according to the data transmission application scenario information to obtain slice network resources, including bandwidth configuration data and flow control data; Optimize the slice network resources according to the data transmission demand level by using a preset network resource optimization method to obtain slice network optimized resources; Optimizing resources for data transmission according to the slice network; Also includes: Get the number of data packets to be transmitted by the data transmission party; Comparing the number of packets to be transmitted with a preset threshold; If it is greater than the preset threshold, the data packets to be transmitted are aggregated to obtain an aggregated data packet; Transmitting the aggregated data packets for data transmission; Also includes: Get the data packet to be transmitted; Segmenting the data packet at a preset edge node to obtain data fragments; The data segments are transmitted through preset sub-channels.

6. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a 5G-based data efficient transmission method program. When the 5G-based data efficient transmission method program is executed by a processor, the steps of the 5G-based data efficient transmission method as described in any one of claims 1 to 4 are implemented.

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