CN118102318B - Data transmission system based on 5G technology - Google Patents

Abstract

The present invention discloses a data transmission system based on 5G technology, which relates to the technical field of wireless communication networks, and includes: a dynamic spectrum resource allocation module, a data reordering and encryption module, and an intelligent transmission control center; the dynamic spectrum resource allocation module adopts a spectrum dynamic allocation algorithm optimized for 5G networks, and the algorithm can adaptively manage and allocate spectrum resources based on the real-time load of the network, user needs and spectrum usage conditions; the data reordering and encryption module can intelligently adjust the processing order of the data packet according to its priority, size and destination; in addition, the module also adopts adaptive encryption technology; the intelligent transmission control center is the core of the system, and is responsible for comprehensively evaluating the operating results of the dynamic spectrum resource allocation module and the data reordering and encryption module; based on the results of these comprehensive evaluations, the intelligent transmission control center can take targeted adjustments, which significantly improves the performance and user experience of the 5G network.

Description

A data transmission system based on 5G technology

Technical Field

The present invention relates to the field of wireless communication network technology, and specifically to a data transmission system based on 5G technology.

Background technique

With the rapid development and widespread deployment of 5G technology, the demand for efficient and secure data transmission systems is growing. 5G networks promise to provide higher data transmission speeds, lower latency, and greater connection density than any previous mobile communication technology, which provides unlimited possibilities for various emerging applications such as augmented reality (AR), virtual reality (VR), self-driving cars, and Internet of Things (IoT) devices. However, these advantages also bring new challenges to network resource management, data security, and user experience optimization.

In existing technologies, spectrum resource management of 5G networks is usually relatively static and lacks the ability to dynamically adjust to real-time network load and user needs. This may lead to insufficient utilization of spectrum resources and network congestion, especially during periods of high user density or peak data demand. In addition, traditional data encryption technology may not meet the needs of 5G high-speed data flows, or affect the efficiency of data transmission while providing adequate security protection.

Summary of the invention

In order to solve the deficiencies mentioned in the above background technology, the purpose of the present invention is to provide a data transmission system based on 5G technology, which can improve the performance and user experience of 5G networks.

In the first aspect, the purpose of the present invention can be achieved by the following technical solution: A data transmission system based on 5G technology, comprising:

A dynamic spectrum resource allocation module, used to execute a spectrum dynamic allocation algorithm optimized for a 5G network, wherein the spectrum dynamic allocation algorithm adaptively manages and allocates 5G spectrum resources based on the load of the 5G network, user demand, and spectrum usage, outputs a first execution result, and sends the first execution result to an intelligent transmission control center;

A data reordering and encryption module, used to execute a data reordering algorithm and an adaptive encryption technology designed specifically for 5G data packets, wherein the data reordering algorithm intelligently reorders the 5G data packets according to the priority, size and destination of the 5G data packets, and the adaptive encryption technology dynamically selects an encryption strategy according to the characteristics of the 5G data, outputs a second execution result, and sends the second execution result to the intelligent transmission control center;

The intelligent transmission control center is used to perform a comprehensive evaluation based on the first execution result and the second execution result, as well as the real-time analysis of the 5G network status, to obtain a comprehensive evaluation result, and based on the comprehensive evaluation result, adjust the network traffic distribution, start priority adjustment and security reinforcement.

In combination with the first aspect, in some implementations of the first aspect, the system further includes: the dynamic spectrum resource allocation module executes a spectrum dynamic allocation algorithm optimized for a 5G network to perform management and allocation of spectrum resources based on a network status score, wherein the network status score calculation formula is as follows:

in, Represents the network load, which indicates the ratio of the spectrum resources currently in use in a specific area to the total available spectrum resources in the area; Represents service priority, which is used to indicate the weighted importance of various service types in a specific area; Represents the dynamic change degree of demand, indicating the changing trend of user demand in a specific area; and is the weight coefficient used to adjust and weight in the scoring process; and is the nonlinear adjustment coefficient used to adjust and The nonlinear effect of

Determine the spectrum resource requirement level according to the calculated network status score;

Dynamically adjust spectrum allocation based on determined spectrum resource demand levels.

In combination with the first aspect, in some implementations of the first aspect, the system further includes: the spectrum resource demand level includes low demand, medium demand and high demand.

In combination with the first aspect, in some implementations of the first aspect, the system further includes: a process for determining the spectrum resource requirement level:

When the calculated network status score is not greater than 0.3, the spectrum resource demand level is low demand;

When the calculated network status score is greater than 0.3 and not greater than 0.6, the spectrum resource demand level is medium demand;

When the calculated network status score is greater than 0.6, the spectrum resource demand level is high.

In combination with the first aspect, in some implementations of the first aspect, the system further includes: the process of dynamically adjusting spectrum allocation according to the determined spectrum resource demand level:

When it is determined that the spectrum resource demand level is low, retain the current spectrum allocation or reduce the current spectrum allocation by 5%;

When the spectrum resource demand level is determined to be medium demand, increase the current spectrum allocation by 10%;

When the spectrum resource demand level is determined to be high, the current spectrum allocation is increased by 20%.

In combination with the first aspect, in certain implementations of the first aspect, the system further includes: the data reordering and encryption module includes an execution unit for executing a data reordering algorithm and an encryption unit for implementing an adaptive encryption technology.

In combination with the first aspect, in some implementations of the first aspect, the system further includes: the execution unit is configured to:

The comprehensive score of 5G data packets is calculated according to the following formula: :

in, , , and is the weight coefficient; It is the urgency of the 5G data packet, which is determined based on the attributes of the data packet or the service requirements; is the maximum urgency value defined by the system, is the priority decay function, is the size sensitivity function, is the destination traffic regulation function;

Reordering is performed based on the calculated comprehensive score of each 5G data packet.

In combination with the first aspect, in some implementations of the first aspect, the system further includes: the priority decay function This is achieved using the following formula:

Among them, P is the priority of the 5G data packet, which is determined according to the type of the 5G data packet; T is the waiting time of the 5G data packet in the queue; is the attenuation coefficient;

Size Sensitivity Function This is achieved using the following formula:

Where S is the size of the 5G data packet; is the threshold of the impact of the size of 5G data packets on priority; C is the current network congestion level;

Destination Traffic Conditioning Function This is achieved using the following formula:

Where D is the quantified value of the destination of the 5G data packet, indicating the importance of the destination of the data packet to network performance; N represents the current network traffic level, quantified as a percentage of network utilization; It is an adjustment factor used to balance the weight of the impact of network traffic on destination priority.

In combination with the first aspect, in some implementations of the first aspect, the system further includes: the encryption unit is used to:

Identify key characteristics of 5G data packets, including data type, data sensitivity level, and urgency of data transmission;

Determine the appropriate encryption algorithm based on the identified key features;

Use a certain encryption algorithm to encrypt 5G data packets.

In combination with the first aspect, in some implementations of the first aspect, the system further includes: the intelligent transmission control center is used to:

receiving a spectrum allocation record of a dynamic spectrum resource allocation module, including an allocated spectrum bandwidth and an allocation success rate, wherein the spectrum allocation record is a first execution result;

Obtaining a detailed record of data processing from the data reordering and encryption module, wherein the detailed record of data processing includes a processing delay of a 5G data packet, an encryption algorithm selection, and an encryption success rate, and the detailed record of data processing is a second execution result;

Monitor network traffic and load, record the network's total throughput, average latency, and real-time congestion level;

According to the spectrum allocation records, detailed records of data processing, the total throughput of the network, the average delay, and the real-time congestion level, the network traffic distribution is adjusted, and priority adjustment and security reinforcement are initiated.

Beneficial effects of the present invention:

The present invention (1) uses a dynamic spectrum resource allocation module to adaptively manage and allocate 5G spectrum resources according to real-time network load, user demand and spectrum usage. This dynamic allocation algorithm optimizes the utilization of spectrum resources, reduces resource idleness and waste, and enables the network to support more users and services while maintaining a high data transmission rate. (2) The dynamic spectrum allocation mechanism can effectively respond to changes in network load and avoid network bottlenecks and congestion by intelligently allocating resources. This not only improves the overall performance of the network, but also ensures that users can still enjoy stable and reliable services under high demand conditions. (3) The data reordering and encryption module uses an algorithm designed specifically for 5G data packets, intelligently reorders data packets according to their characteristics such as priority, size and destination, and dynamically selects encryption strategies, which not only improves the efficiency of data transmission, but also ensures data security during transmission. This method is particularly suitable for processing large amounts of high-speed data streams while protecting user data from unauthorized access and attacks. (4) The intelligent transmission control center can adjust network policies in a timely manner by comprehensively evaluating the network operation status, such as adjusting network traffic distribution, starting data processing priority adjustment and strengthening security measures. This adaptive adjustment mechanism enables the network to flexibly respond to various situations and optimize the user experience, especially when the network load is high or security threats occur.

BRIEF DESCRIPTION OF THE DRAWINGS

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative work.

FIG. 1 is a schematic diagram of the system structure of the present invention.

Detailed ways

The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. 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 creative work are within the scope of protection of the present invention.

Embodiment 1:

The following is an introduction to the relevant terms involved in the embodiments of the present application:

As shown in FIG1 , a data transmission system based on 5G technology includes:

Dynamic spectrum resource allocation module 101, data reordering and encryption module 102 and intelligent transmission control center 103.

The dynamic spectrum resource allocation module 101 is used to execute a spectrum dynamic allocation algorithm optimized for the 5G network, wherein the spectrum dynamic allocation algorithm adaptively manages and allocates 5G spectrum resources based on the specific load, user demand and spectrum usage of the 5G network to optimize 5G spectrum utilization and reduce 5G network congestion.

In this embodiment, the dynamic spectrum resource allocation module 101 is specially designed to meet the challenges of spectrum management in 5G networks. The module adopts a spectrum dynamic allocation algorithm that is optimized specifically for the 5G network environment and can automatically adjust according to the real-time load of the 5G network, the specific needs of users, and the current spectrum usage. The module can dynamically manage and allocate 5G spectrum resources to ensure that at any given time, the spectrum usage efficiency can be maximized while significantly reducing or avoiding the occurrence of network congestion.

Specifically, the work of the dynamic spectrum resource allocation module 101 begins by continuously monitoring the status of the 5G network. This includes collecting data about network load, user activity, and spectrum occupancy in real time. Based on this information, the spectrum dynamic allocation algorithm analyzes the current network status, predicts future demand changes, and makes decisions accordingly to dynamically adjust spectrum allocation. This process takes into account a variety of factors, including but not limited to the user's geographic location, the priority of the service type, and other dynamic changes in the network.

In addition, the module is also able to respond to feedback from the intelligent transmission control center 103. Although the intelligent transmission control center 103 does not directly guide every operation of the dynamic spectrum resource allocation module 101, it provides valuable insights and suggestions by analyzing the operating results and status of the entire network. This includes adjusting the spectrum allocation strategy based on the global network status to optimize the overall network performance and user experience.

The dynamic spectrum resource allocation module 101 should be highly configurable and flexible to adapt to different network environments and requirements. When implementing this module, algorithm parameters such as the priority rules for spectrum allocation, the time window size for spectrum demand prediction, and the speed of responding to network changes can be adjusted according to the specific network architecture and user needs.

Furthermore, the dynamic spectrum resource allocation module uses a spectrum dynamic allocation algorithm based on network status scoring to perform spectrum resource management and allocation, wherein the network status scoring Calculated according to the following formula 1:

in, Represents the network load, which indicates the ratio of the spectrum resources currently in use in a specific area to the total available spectrum resources in the area; Represents service priority, which is used to indicate the weighted importance of various service types in a specific area; Represents the dynamic change degree of demand, indicating the changing trend of user demand in a specific area; and is the weight coefficient used to adjust and weight in the scoring process; and is the nonlinear adjustment coefficient used to adjust and The nonlinear impact of the network status is determined based on the calculated network status score.

Dynamically adjust spectrum allocation based on determined spectrum resource demand levels.

Network load, service priority, and demand dynamics are all metrics for a specific area. These metrics reflect the usage of 5G networks in the area, the importance of service types, and the changing trends of user demand. The following will explain in detail how to calculate these metrics.

Network load Calculation:

Network load indicates the ratio of spectrum resources currently in use in a specific area to the total available spectrum resources in the area. It is a direct indicator of network congestion.

First, data on spectrum usage in a specific region needs to be collected. This includes the total amount of spectrum resources available in the region (total spectrum resources) and the amount of spectrum resources currently in use (used spectrum resources).

Then, the network load is calculated according to the following formula 2: :

For example, if a region has a total spectrum resource of 100 MHz and 70 MHz is currently in use, then:

This means that the network load in this area is 0.7, or 70%.

Calculation of service priority degree (SPD):

Service priority is calculated based on the importance or priority of different service types within a specific area. Different services (such as emergency communications, video streaming, data downloading, etc.) will be given different priority weights.

1. Define priority weights: First, define a priority weight for each service type. Emergency services may have the highest weight, followed by video streaming, and then regular data services, which include data downloads.

2. Collect service usage data: Collect usage data of different service types in a specific area.

3. Calculate the service priority according to the following formula 3 :

For example, if video streaming (service type priority weight is 0.8) uses 40% of resources in a region, emergency services (service type priority weight is 1.0) use 30% of resources, and regular data services (service type priority weight is 0.5) use the remaining 30% of resources, then:

This means that the service priority for this area is 0.65.

Demand dynamics Calculation:

The dynamic change of demand reflects the rate of change of user demand within a certain period of time. This can be determined by comparing the network usage at two points in time.

1. Select the time window: Determine the time window for analysis, for example, compare the data of today and yesterday in the same time period.

2. Collect time point data: Collect network usage data at two time points.

3. Calculate the dynamic change degree of demand according to the following formula 4:

For example, if at this time yesterday, the network usage in a specific area was 50MHz, and at the same time today, the network usage in a specific area was 60MHz, then:

This means that the demand dynamics in this area is 0.2, or a 20% increase.

Assume that at a certain moment, the network load A high value indicates that the network is facing a large data transmission demand. It reflects the demand for high-priority services in the current services. Demand dynamic change degree Indicates the growth rate of demand in the near future.

by Introduced and parameters, the formula can more accurately adjust the impact of network load and service priority, making it have different sensitivities in different network conditions. This ensures that even when demand changes rapidly, the impact of dynamic changes in demand can be reasonably controlled to avoid excessive bias of spectrum resources in one direction due to temporary surges in demand.

Through this method, the dynamic spectrum resource allocation module 101 can respond to the real-time status and needs of the network more carefully and dynamically, providing a more complex and adaptable spectrum resource allocation strategy for the 5G network.

Determine the weight coefficient and And the nonlinear adjustment coefficient and Usually involves in-depth analysis of the network environment, service requirements, and historical data. The setting of these coefficients is intended to reflect the actual impact of different network parameters on the overall network performance, as well as the relative importance of these parameters. The following is a detailed explanation and method for determining these coefficients.

Determine the weight coefficient and At least one of the following methods can be used:

1. Historical data analysis: By analyzing historical network performance data, the network load can be evaluated ( ) and service priority ( ) on network performance (such as throughput, latency, etc.). If it is found that the network load has a more significant impact on performance, then Should be set higher than Higher and vice versa.

2. Expert opinion: The experience and knowledge of network operators and system designers are also important sources for determining weight coefficients. Their understanding of network operation can help set these coefficients to reflect the actual impact of different factors.

3. Optimization and simulation: By building a network model and performing simulation, you can try different weight combinations and observe which combination provides the best network performance. This method can help fine-tune the weight coefficients.

Determine the nonlinear adjustment coefficient and At least one of the following methods can be used:

1. Nonlinear impact analysis: The setting of nonlinear adjustment coefficients first requires analysis and For example, if the network load is close to the capacity limit, the negative impact on network performance may exceed the linear expectation, and a larger value to reflect this nonlinear effect.

2. Parameter adjustment and testing: By adjusting and , and monitor how these adjustments affect the network state scoring function ( ) Based on the actual network conditions, the most suitable nonlinear adjustment coefficient can be found. This may require multiple rounds of testing and optimization.

3. Mathematical modeling and optimization algorithm: Use mathematical modeling methods to describe and The nonlinear characteristics of the network performance. Then, optimization algorithms (such as gradient descent) can be used to find the best and value that makes the model most accurately predict network performance.

4. Expert opinion: The experience and knowledge of network operators and system designers are also important sources for determining nonlinear adjustment coefficients. Their understanding of network operation can help set these coefficients to reflect the actual impact of different factors.

In practical applications, the process of determining these coefficients may require iteration and adjustment in order to maintain the accuracy and effectiveness of the scoring function in a changing network environment. In addition, as network technology develops and user behavior changes, these coefficients may need to be re-evaluated and adjusted regularly.

Furthermore, the spectrum resource demand level includes low demand, medium demand and high demand; and determining the spectrum resource demand level according to the calculated network status score includes:

When the calculated network status score is not greater than 0.3, the spectrum resource demand level is low demand;

When the calculated network status score is greater than 0.3 and not greater than 0.6, the spectrum resource demand level is medium demand;

When the calculated network status score is greater than 0.6, the spectrum resource demand level is high;

The dynamically adjusting spectrum allocation according to the determined spectrum resource demand level includes:

When it is determined that the spectrum resource demand level is low, retain the current spectrum allocation or reduce the current spectrum allocation by 5%;

When the spectrum resource demand level is determined to be medium demand, increase the current spectrum allocation by 10%;

When the spectrum resource demand level is determined to be high, the current spectrum allocation is increased by 20%.

For example, if the NSF value of area A is 0.55, it belongs to the "medium demand" range; the NSF value of area B is 0.75, it belongs to the "high demand" range. Adjust the decision model according to spectrum resources:

For region A, the spectrum resource allocation will be increased by 10%. If region A was originally allocated 100MHz of spectrum resources, it will now be increased to 110MHz.

For region B, the spectrum resource allocation will be increased by 20%. If region B was originally allocated 100MHz of spectrum resources, it will now be increased to 120MHz.

In this way, the spectrum dynamic allocation algorithm can dynamically adjust the spectrum allocation strategy in a quantitative way based on the NSF value calculated in real time, ensuring that the service types and user needs of different regions are more effectively met, while optimizing 5G spectrum utilization and reducing network congestion.

In summary, the dynamic spectrum resource allocation module 101 effectively optimizes the spectrum utilization of the 5G network through its algorithms and strategies, improving the efficiency of the network and user satisfaction. This dynamic and adaptive spectrum management method not only provides 5G network operators with powerful tools to cope with fluctuations and changes in network load, but also brings a more stable and high-quality service experience to end users.

The data reordering and encryption module 102 is used to execute a data reordering algorithm and an adaptive encryption technology designed specifically for 5G data packets, wherein the data reordering algorithm intelligently reorders the 5G data packets according to their priority, size and destination, and the adaptive encryption technology dynamically selects an encryption strategy according to the characteristics of the 5G data to ensure data security during transmission over the 5G network.

In the 5G data transmission system provided in this embodiment, the data reordering and encryption module 102 plays a vital role, aiming to enhance the efficiency and security of data transmission by intelligently processing data streams. This module includes two main functional parts: one part is responsible for reordering according to the characteristics of the data packet, and the other part applies adaptive encryption technology to ensure the security of data during transmission.

The data reordering process is based on the priority, size and destination of the 5G data packets. First, the system analyzes the incoming data packets and identifies these key attributes of each packet. For example, urgent voice call packets will be given high priority, while large non-urgent file transfers may be marked as low priority. In this way, the reordering algorithm ensures that high-priority data can be processed and forwarded faster to meet the needs of real-time or highly sensitive services.

Implementing this process requires developing an algorithm that can analyze and classify incoming packets in real time and sort them according to preset rules. This may involve building a priority queue where packets are inserted into the appropriate position based on their priority, size and destination for subsequent processing and transmission.

After the data is reordered, adaptive encryption technology is applied to these ordered data packets. This technology dynamically selects encryption strategies based on the characteristics of 5G data, which means that different types of data (such as text messages, video streaming, or file transfers) may apply different strengths or types of encryption methods. This adaptability not only enhances the security of the data, but also optimizes the efficiency of the encryption process - ensuring that more complex and computationally intensive encryption methods are used only when necessary.

To achieve this, a system needs to be designed that can evaluate the sensitivity and security requirements of data packets and select appropriate encryption algorithms accordingly. This may involve building an encryption policy database that contains recommended encryption methods for different data types and scenarios. The system will select the most suitable encryption policy from the database for application based on the attributes of the data packet, such as data type, destination and priority, as well as the current security status of the network.

Combining data reordering and adaptive encryption, the data reordering and encryption module 102 provides an efficient and secure channel for 5G data transmission. When deploying this module, it is necessary to ensure that the system can handle a large number of data packets in real time while maintaining sufficient flexibility and adaptability in selecting reordering rules and encryption strategies. In addition, the system design also needs to take into account the collaborative work with other parts of the network, such as the dynamic spectrum resource allocation module 101 and the intelligent transmission control center 103, to ensure that the performance and security of the entire network are optimized.

Through such design and implementation, the 5G data transmission system provided in this embodiment can provide users with powerful data protection while ensuring efficient data processing, meeting the dual requirements of modern communication networks for speed and security.

Furthermore, the data reordering and encryption module includes an execution unit for executing a data reordering algorithm, wherein the execution unit is specifically used for:

The comprehensive score of 5G data packets is calculated according to the following formula: :

in, , , and are weight coefficients, which can be obtained through experimental data or based on expert experience;

It is the urgency of the 5G data packet, which can be determined based on the attributes of the data packet or the service requirements; is the maximum urgency value defined by the system;

Urgency is a key metric used to assess the priority of a packet's transmission, especially in situations of network congestion or limited resources. The following steps provide a framework for quantifying and implementing urgency decisions.

The steps to determine the urgency of a data packet include:

(1) Define urgency metrics: First, we need to define what urgency is and how to quantify it. Urgency can be determined based on factors such as the real-time requirements of data packets, sensitivity to delay, and quality of service (QoS) requirements. For example, real-time video or voice communication may have high urgency, while email or ordinary data downloads may have lower urgency.

(2) Identify data packet attributes: Determining the urgency requires analyzing the specific attributes of the data packet. These attributes may include:

Service type: such as VoIP, real-time video, instant messaging, file download, etc.

QoS parameters: The packet header usually contains QoS-related fields, such as the Differentiated Services Code Point (DSCP) field, which can be used to identify the priority and type of data flow.

Application Identification: In some cases, a data packet may contain specific application identification information, such as an API call for a specific application, which can be used to infer the urgency of the data packet.

(3) Quantify the urgency: Based on the identified packet attributes, quantify the urgency into a specific value. This step can be performed in the following ways:

Predefined urgency levels: A set of urgency levels are predefined for different service types or QoS requirements, and corresponding values are assigned. For example, urgency is divided into a range of 0 to 1, where 1 represents the highest urgency and 0 represents the lowest urgency.

Dynamic calculation: In some cases, the urgency may need to be dynamically calculated based on the current network status or the real-time requirements of the data packet. For example, if the network is severely congested, even ordinary data downloads may be given a higher urgency to ensure service quality.

(4) Implement urgency determination: Analyze incoming data packets and assign an urgency value to each packet based on the above criteria.

Through the above steps, the urgency of 5G data packets can be determined, so that priority management based on urgency can be implemented in the data reordering and encryption modules. This method not only improves the utilization efficiency of network resources, but also ensures that users' needs for high-quality services can be met at critical moments.

Priority decay function This is achieved using the following formula:

Priority decay function The priority and latency of 5G data packets are taken into account, ensuring that high priority and/or long latency data packets are processed faster.

in, is the priority of 5G data packets, which is determined by the type of 5G data packets. Common types include but are not limited to emergency communications (such as emergency calls, alarm signals), real-time services (such as VoIP calls, real-time video streaming), large data transmission (such as file downloads, video uploads), and regular data transmission (such as web browsing, email). Emergency communications can be assigned a value close to 1, while regular data transmission may be close to 0. ;

T is the waiting time of 5G data packets in the queue; is the attenuation coefficient, which can be determined from experimental data or obtained from expert knowledge;

Size Sensitivity Function This is achieved using the following formula:

Size Sensitivity Function The effect of packet size on its processing priority and the feedback of current network congestion level are considered through logistic function.

Where S is the size of the 5G data packet;

is the threshold value of the impact of the size of 5G data packets on priority;

C is the current network congestion level;

The following details how to determine the threshold value of the impact of packet size on priority. And the current network congestion level C.

is a key parameter used to differentiate between large packets that may have a greater impact on network performance and small packets that have a lesser impact. It is determined by:

1. Network performance analysis: First, we analyze historical data on the network’s performance to determine how different packet sizes affect network latency and throughput. In particular, we analyze the average size of packets when the network begins to show signs of congestion.

2. Quality of Service Requirements: Refer to the Quality of Service (QoS) requirements for different types of services. For example, real-time video streaming may have strict limits on the maximum delay of data packets, thus affecting Settings.

3. Experience: In many cases, The settings may also depend on the experience of the network administrator and the expected network usage. For example, if the network is mainly used for services such as instant messaging that transmit small data packets, Probably relatively small.

The network congestion level C is a dynamically changing indicator that reflects the current network resource usage and the data traffic level that the network can carry. Its determination methods include:

1. Real-time traffic monitoring: Assess the degree of network congestion by continuously monitoring the real-time network traffic and resource usage (such as bandwidth utilization, router queue length, etc.).

2. Congestion indicator calculation: Use specific algorithms or models, such as packet loss rate and round-trip time (RTT) increase in the TCP congestion control algorithm, to quantify the degree of network congestion. C can be set to a value between 0 (no congestion) and 1 (extreme congestion).

The above methods were used to determine and C, the data reordering and encryption module 102 can more intelligently adjust the priority according to the real-time network conditions and data packet characteristics to optimize the data transmission efficiency and responsiveness of the 5G network. For example, when the network congestion level C is high, the system may prioritize processing less than data packets to reduce network delays and improve throughput, thereby reasonably allocating network resources while ensuring service quality.

Destination Traffic Conditioning Function This is achieved using the following formula:

Where D is the quantitative value of the destination of the 5G data packet, indicating the importance of the destination of the data packet to the network performance;

Quantifying the destination D of 5G packets involves converting the importance of the destination into a measurable and comparable value. This quantification process needs to take into account the potential impact of the destination on network performance, including factors such as the urgency of packet transmission, quality of service requirements, and the network status of the destination node. The following is a framework for the quantification process, which is intended to provide technical personnel with guidance on how to achieve this goal.

Defining the indicators of destination importance include;

1. Network topology role: Identify the role and status of the destination node in the network topology. For example, edge computing nodes, core network nodes, or cloud data centers may be given higher importance due to their key role in processing and distributing data.

2. Service type requirements: Consider the type of service associated with the destination. Specific services, such as real-time video streaming, online gaming, or emergency response systems, may require higher data transmission priority and lower latency, so the importance of the destination will be higher.

3. User experience impact: Evaluate the potential impact of a destination node failure or performance degradation on the end-user experience. The node with a greater impact on the user experience has a higher destination importance.

Quantification methods include:

1. Grading system: Establish a grading system to assign predefined importance levels to different destination types or categories. For example, importance can be divided into three levels: low, medium, and high, corresponding to values 0.3, 0.6, and 0.9 respectively.

2. Weight assignment: Assign weights to each importance indicator to reflect its contribution to the total importance of the destination. For example, network topology role may account for 50% of the total importance, service type demand 30%, and user experience impact 20%.

3. Calculate the comprehensive importance value: According to the different attributes of the destination and the assigned weights, calculate its comprehensive importance value D. For example, if a destination is an edge computing node (high importance), supports real-time video streaming (high demand) and has a great impact on user experience (high impact), it may obtain a quantitative value close to the highest.

N represents the current network traffic level, quantified as a percentage of network utilization;

It is an adjustment coefficient used to balance the weight of the impact of network traffic on destination priority, which can be obtained through experimental data or expert knowledge;

Reordering is performed based on the calculated comprehensive score of each 5G data packet. For example, the comprehensive score can be reordered from high to low.

Furthermore, the data reordering and encryption module includes an encryption unit for implementing an adaptive encryption technology, and the encryption unit is specifically used to:

Identify key characteristics of 5G data packets, including data type, data sensitivity level, and urgency of data transmission;

Determine the appropriate encryption algorithm based on the identified key features;

Use a certain encryption algorithm to encrypt 5G data packets.

In the data transmission system based on 5G technology provided in this embodiment, the data reordering and encryption module plays a vital role, especially the encryption unit, which uses adaptive encryption technology to ensure the security of data transmission. The core of this technology is to intelligently identify the key features of the data packet and select the most appropriate encryption algorithm for data encryption. This technology is described in detail below.

The encryption unit first needs to perform in-depth analysis of incoming 5G data packets to identify their key characteristics, which include:

Data Type: Data packets may contain various types of data, such as text, images, audio, or video. This step involves analyzing the contents or header information of the packet to determine the type of data it carries.

Data sensitivity level: Depending on the content and purpose of the data, data packets can be classified into different sensitivity levels such as public, sensitive or confidential. This usually requires pre-defined policies or rules, and possible content detection technology, to automatically determine the sensitivity of the data.

Urgency of data transmission: Some data packets, such as real-time communication or emergency response data, may have a higher urgency of transmission. The assessment of urgency may be based on the service type identification or other relevant indicators of the data packet.

Once the key characteristics of the data packet are identified, the encryption unit will then determine which encryption algorithm is most appropriate based on these characteristics. This process includes:

Establish an encryption algorithm library: First, you need to establish a library containing multiple encryption algorithms, each of which corresponds to a specific combination of data features.

Matching algorithm: By comparing the characteristics of the data packet with the applicable conditions of each algorithm in the algorithm library, the encryption unit selects the most matching algorithm. For example, for highly sensitive and urgent data, an algorithm with high encryption strength but moderate computational complexity may be selected.

Finally, the encryption unit will encrypt the 5G data packets using the selected encryption algorithm. This includes:

Generate keys: Generate the necessary encryption keys based on the selected encryption algorithm. This step may involve a key exchange protocol to ensure that both the sender and receiver of the data can share the key securely.

Perform encryption: Use the generated key and the determined algorithm to encrypt the data packet content to ensure that its content cannot be accessed or tampered with by unauthorized persons during transmission.

Key management: An effective key management strategy must also be implemented during the encryption process, including key updating, revocation, and storage, to prevent key leakage or abuse.

Through the above process, the encryption unit can provide highly customized security protection for each data packet in the 5G data transmission system. By intelligently identifying data features and dynamically selecting encryption algorithms, this adaptive encryption technology not only improves the security of data transmission, but also optimizes the efficiency and performance of the encryption process.

The intelligent transmission control center 103 is used to conduct a comprehensive evaluation based on the operating results of the dynamic spectrum resource allocation module, the data reordering and encryption module, and the real-time analysis of the 5G network status, user behavior and data characteristics; and based on the results of the comprehensive evaluation, adjust the network traffic distribution, start priority adjustment and security reinforcement.

In the data transmission system based on 5G technology, the intelligent transmission control center 103 plays a vital role. As the brain of the system, it is responsible for comprehensively evaluating the network status, user behavior, data characteristics and the operating results of other modules, and making intelligent decisions based on this to optimize network performance and security.

The main functions of the intelligent transmission control center 103 include collecting and analyzing data from the dynamic spectrum resource allocation module 101 and the data reordering and encryption module 102, and monitoring the network status and traffic distribution in real time. Based on this information, it can make accurate decisions and adjust the network configuration and resource allocation to achieve the optimal distribution of network traffic, optimize the priority sorting of data transmission, and enhance the security during data transmission.

The implementation method includes the following steps:

1. Data collection and analysis: The intelligent transmission control center first needs to collect network operation data in real time, including but not limited to spectrum usage, data packet type and size, encryption status, network congestion, etc. In addition, it is also necessary to collect data on user behavior, such as data usage patterns, service quality requirements, etc., as well as real-time status information of the 5G network, such as signal strength, connection quality between nodes, etc.

2. Comprehensive evaluation: Through in-depth analysis and processing of the collected data, the intelligent transmission control center is able to conduct a comprehensive evaluation of the overall performance and security status of the current network. This process may involve complex data processing and analysis algorithms, such as machine learning models, to identify potential problems or optimization opportunities in the network.

3. Decision making: Based on the results of the comprehensive evaluation, the intelligent transmission control center will make a series of decisions, including adjusting the allocation strategy of spectrum resources, optimizing the reordering rules of data packets, and strengthening data encryption measures. These decisions are aimed at improving network performance and efficiency, reducing congestion, improving the security of data transmission, and improving the user's service experience.

By implementing the intelligent transmission control center 103, the 5G data transmission system can achieve higher network performance and security, meet the growing demand for data transmission, and provide users with better services. The design and implementation of this system demonstrates the great potential of 5G technology in intelligent network management and optimization.

Furthermore, the intelligent transmission control center is specifically used for:

Collecting spectrum allocation records of the dynamic spectrum resource allocation module 101, including allocated spectrum bandwidth and allocation success rate;

Obtain detailed records of data processing from the data reordering and encryption module 102, wherein the detailed records include processing delay of 5G data packets, encryption algorithm selection, and encryption success rate;

Monitor network traffic and load, and record the network's total throughput, average latency, and real-time congestion level;

According to the spectrum allocation records, detailed records of data processing, the total throughput of the network, the average delay, and the real-time congestion level, the network traffic distribution is adjusted, and priority adjustment and security reinforcement are initiated.

In the data transmission system based on 5G technology, the intelligent transmission control center plays a core role, responsible for integrating data from different modules, monitoring network status, and making intelligent decisions to optimize network performance and security. The process includes the following key steps, which are explained in detail below and provide examples.

1. Collect spectrum allocation records: The intelligent transmission control center first collects spectrum allocation records from the dynamic spectrum resource allocation module 101. These records include the spectrum bandwidth allocated to each service and user and the success rate of spectrum allocation, reflecting the efficiency of spectrum resource use and the effectiveness of allocation strategy.

2. Obtaining data processing records: At the same time, the control center also obtains detailed records of 5G data packet processing from the data reordering and encryption module 102, including the processing delay time of the data packet, the selected encryption algorithm and its success rate. This information helps to evaluate the performance of data flow processing and encryption operations.

3. Monitor network status: The control center continues to monitor the traffic and load of the entire network, including recording the total throughput, average latency, and real-time congestion level of the network. These indicators directly reflect the network's operating status and performance bottlenecks.

Based on the data collected above, the Intelligent Transport Control Center comprehensively evaluates the overall performance, security and user satisfaction of the network, and then makes corresponding adjustments based on the evaluation results to optimize the network. This may include adjusting network traffic distribution to alleviate congestion, adjusting the priority of data processing and encryption operations to improve efficiency, and strengthening data security measures to protect user data.

The following is an example:

Example 1: Congestion relief: If the intelligent transmission control center finds that the real-time congestion level in a certain area continues to rise, by analyzing the spectrum allocation records and network throughput, it may decide to reallocate spectrum resources, increase the bandwidth in the area, or adjust the routing of data flows to disperse the traffic, thereby alleviating congestion.

Example 2: Encryption strategy optimization: Based on detailed records of data processing, if the control center finds that the success rate of a certain encryption algorithm is lower than expected, it may choose another encryption algorithm to replace it, or adjust the priority of encryption operations to ensure the secure transmission of sensitive data.

Through these steps and examples, the intelligent transmission control center can effectively manage and optimize the 5G network, ensuring efficient and secure data transmission while improving user experience. This comprehensive evaluation and automatic adjustment mechanism is the key to achieving dynamic and intelligent network management, and provides solid technical support for the high-performance operation of 5G networks.

Based on the same inventive concept, the present invention also provides a computer device, which includes: one or more processors, and a memory for storing one or more computer programs; the program includes program instructions, and the processor is used to execute the program instructions stored in the memory. The processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. It is the computing core and control core of the terminal, which is used to implement one or more instructions, specifically used to load and execute one or more instructions in a computer storage medium to implement the above method.

It should be further explained that, based on the same inventive concept, the present invention also provides a computer storage medium, on which a computer program is stored, and the computer program is executed by the processor to execute the above method. The storage medium can adopt any combination of one or more computer-readable media. The computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium. The computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electrical, magnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples (non-exhaustive list) of computer-readable storage media include: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present invention, a computer-readable storage medium can be any tangible medium containing or storing a program, which can be used by an instruction execution system, device or device or used in combination with it.

In the description of this specification, the description with reference to the terms "one embodiment", "example", "specific example", etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present disclosure. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

The above shows and describes the basic principles, main features and advantages of the present disclosure. Those skilled in the art should understand that the present disclosure is not limited by the above embodiments, and the above embodiments and descriptions are only for explaining the principles of the present disclosure. Without departing from the spirit and scope of the present disclosure, the present disclosure may have various changes and improvements, and these changes and improvements all fall within the scope of the present disclosure to be protected.

Claims (3)

1. A data transmission system based on 5G technology, comprising: A dynamic spectrum resource allocation module, used to execute a spectrum dynamic allocation algorithm optimized for a 5G network, wherein the spectrum dynamic allocation algorithm adaptively manages and allocates 5G spectrum resources based on the load of the 5G network, user demand, and spectrum usage, outputs a first execution result, and sends the first execution result to an intelligent transmission control center; The dynamic spectrum resource allocation module executes a spectrum dynamic allocation algorithm optimized for 5G networks to manage and allocate spectrum resources based on a network status score, wherein the network status score NSF calculation formula is as follows: in, Represents the network load; Representative service priority; Represents the dynamic change of demand; and is the weight coefficient; and is the nonlinear adjustment coefficient; The network load Calculation: Calculation of service priority SPD: Demand dynamics Calculation: ; Determine the spectrum resource requirement level according to the calculated network status score; Dynamically adjust spectrum allocation based on determined spectrum resource demand levels; The spectrum resource demand levels include low demand, medium demand and high demand; The process of determining the spectrum resource requirement level: When the calculated network status score is not greater than 0.3, the spectrum resource demand level is low demand; When the calculated network status score is greater than 0.3 and not greater than 0.6, the spectrum resource demand level is medium demand; When the calculated network status score is greater than 0.6, the spectrum resource demand level is high; The process of dynamically adjusting spectrum allocation according to the determined spectrum resource demand level: When it is determined that the spectrum resource demand level is low, retain the current spectrum allocation or reduce the current spectrum allocation by 5%; When the spectrum resource demand level is determined to be medium demand, increase the current spectrum allocation by 10%; When the spectrum resource demand level is determined to be high, increase the current spectrum allocation by 20%; A data reordering and encryption module, used to execute a data reordering algorithm and an adaptive encryption technology designed specifically for 5G data packets, wherein the data reordering algorithm intelligently reorders the 5G data packets according to the priority, size and destination of the 5G data packets, and the adaptive encryption technology dynamically selects an encryption strategy according to the characteristics of the 5G data, outputs a second execution result, and sends the second execution result to the intelligent transmission control center; The data reordering and encryption module includes an execution unit for executing a data reordering algorithm and an encryption unit for implementing an adaptive encryption technique; The execution unit is used for: The comprehensive score of 5G data packets is calculated according to the following formula: : in, , , and is the weight coefficient; is the urgency of 5G data packets; is the maximum urgency value defined by the system, is the priority decay function, is the size sensitivity function, is the destination traffic regulation function; Steps to determine the urgency of a packet: Define urgency indicators: Urgency is determined based on the real-time requirements of the data packet, sensitivity to delay, and quality of service (QoS) requirements; Identify packet attributes: Determining urgency requires analyzing the attributes of the packet, including: Service type, QoS parameters, application identification; Quantifying urgency: Based on the identified packet attributes, the urgency is quantified into a numerical value. This step is performed in the following way: Predefined urgency levels: A set of urgency levels are predefined for different service types or QoS requirements, and corresponding values are assigned, dividing the urgency into a range of 0 to 1, where 1 represents the highest urgency and 0 represents the lowest urgency; Dynamic calculation: In some cases, the urgency needs to be dynamically calculated based on the current network status or the real-time requirements of the data packet. If the network is severely congested, even ordinary data downloads are given a high urgency to ensure service quality; Implement urgency determination: Analyze incoming packets and assign an urgency value to each packet based on the above criteria; Reorder the packets based on the calculated comprehensive score of each 5G data packet; The priority decay function This is achieved using the following formula: in, is the priority of the 5G data packet, which is determined according to the type of the 5G data packet; T is the waiting time of the 5G data packet in the queue; is the attenuation coefficient; Size Sensitivity Function This is achieved using the following formula: Where S is the size of the 5G data packet; is the threshold of the impact of the size of 5G data packets on priority; C is the current network congestion level; Destination Traffic Conditioning Function This is achieved using the following formula: Where D is the quantified value of the destination of the 5G data packet; N represents the current network traffic level, quantified as a percentage of network utilization; is the adjustment coefficient; The intelligent transmission control center is used to perform a comprehensive evaluation based on the first execution result and the second execution result, as well as the real-time analysis of the 5G network status, to obtain a comprehensive evaluation result, and based on the comprehensive evaluation result, adjust the network traffic distribution, start priority adjustment and security reinforcement. 2. A data transmission system based on 5G technology according to claim 1, characterized in that the encryption unit is used to: Identify key characteristics of 5G data packets, including data type, data sensitivity level, and urgency of data transmission; Determine the appropriate encryption algorithm based on the identified key features; Use a certain encryption algorithm to encrypt 5G data packets. 3. A data transmission system based on 5G technology according to claim 1, characterized in that the intelligent transmission control center is used to: receiving a spectrum allocation record from a dynamic spectrum resource allocation module, including an allocated spectrum bandwidth and an allocation success rate, wherein the spectrum allocation record is a first execution result; Obtaining a detailed record of data processing from the data reordering and encryption module, wherein the detailed record of data processing includes a processing delay of a 5G data packet, an encryption algorithm selection, and an encryption success rate, and the detailed record of data processing is a second execution result; Monitor network traffic and load, and record the network's total throughput, average latency, and real-time congestion level; According to the spectrum allocation records, detailed records of data processing, the total throughput of the network, the average delay, and the real-time congestion level, the network traffic distribution is adjusted, and priority adjustment and security reinforcement are initiated.