CN118102318A

CN118102318A - Data transmission system based on 5G technology

Info

Publication number: CN118102318A
Application number: CN202410487322.7A
Authority: CN
Inventors: 杨欣儒; 付章杰; 刘炳杉
Original assignee: Nanjing University of Information Science and Technology
Current assignee: Nanjing University of Information Science and Technology
Priority date: 2024-04-23
Filing date: 2024-04-23
Publication date: 2024-05-28
Anticipated expiration: 2044-04-23

Abstract

The invention discloses a data transmission system based on a 5G technology, which relates to the technical field of wireless communication networks and comprises the following components: the system comprises a dynamic spectrum resource allocation module, a data reordering and encrypting module and an intelligent transmission control center; the dynamic spectrum resource allocation module adopts a spectrum dynamic allocation algorithm optimized for the 5G network, the algorithm can adaptively manage and allocate spectrum resources based on real-time load, user demand and spectrum use condition of the network, the data reordering and encryption module can intelligently adjust the processing sequence according to the priority, the size and the destination of the data packet, in addition, the module also adopts an adaptive encryption technology, the intelligent transmission control center is the core of the system and is responsible for comprehensively evaluating the operation results of the dynamic spectrum resource allocation module and the data reordering and encryption module, and based on the comprehensive evaluation results, the intelligent transmission control center can adopt targeted adjustment, thereby remarkably improving the performance and user experience of the 5G network.

Description

Data transmission system based on 5G technology

Technical Field

The invention relates to the technical field of wireless communication networks, in particular to a data transmission system based on a 5G technology.

Background

With the rapid development and widespread deployment of 5G technology, there is an increasing demand for efficient, secure data transmission systems. The promise of 5G networks provides higher data transmission speeds, lower delays, and greater connection densities than any previous mobile communication technology, which provides unlimited possibilities for various emerging applications such as Augmented Reality (AR), virtual Reality (VR), autopilot, and internet of things (IoT) devices. However, these advantages simultaneously present new challenges for network resource management, data security, and user experience optimization.

In the prior art, spectrum resource management of a 5G network is generally static, and lacks dynamic adjustment capability for real-time network load and user requirements. This may lead to problems of under-utilization of spectrum resources and network congestion, especially during periods of intensive users or peak data demand. Furthermore, conventional data encryption techniques may not meet the requirements of 5G high-speed data streams or impact the efficiency of data transmission while providing adequate security protection.

Disclosure of Invention

In order to solve the above-mentioned shortcomings in the background art, the present invention aims to provide a data transmission system based on 5G technology, which can improve the performance and user experience of a 5G network.

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

the system comprises a dynamic spectrum resource allocation module, a first execution result and an intelligent transmission control center, wherein the dynamic spectrum resource allocation module is used for executing a spectrum dynamic allocation algorithm optimized for a 5G network, the spectrum dynamic allocation algorithm is used for adaptively managing and allocating 5G spectrum resources based on specific load, user demand and spectrum service condition of the 5G network, outputting and obtaining the first execution result, and sending the first execution result to the intelligent transmission control center;

The data reordering and encrypting module is used for executing a data reordering algorithm specially designed for the 5G data packet and an adaptive encrypting technology, wherein the data reordering algorithm intelligently reorders according to the priority, the size and the destination of the 5G data packet, the adaptive encrypting technology dynamically selects an encrypting strategy according to the characteristics of the 5G data, outputs a second executing result and sends the second executing result to the intelligent transmission control center;

The intelligent transmission control center is used for comprehensively evaluating according to the first execution result, the second execution result and the 5G network state analyzed in real time to obtain a comprehensive evaluation result, and adjusting network flow distribution, starting priority adjustment and safety reinforcement based on the comprehensive evaluation result.

With reference to the first aspect, in certain implementations of the first aspect, the system further includes: the dynamic spectrum resource allocation module executes a spectrum dynamic allocation algorithm optimized for the 5G network to execute management and allocation of spectrum resources based on a network state score, wherein the network state score calculation formula is as follows:

Wherein, Representing network load degree, representing the ratio of the spectrum resource currently in use in a specific area to the total available spectrum resource in the area; /(I)Representing service priorities for representing weighted importance of various service types within a particular area; /(I)Representing the dynamic change degree of the demand, and representing the change trend of the user demand in a specific area; /(I)And/>Is a weight coefficient for adjusting/>And/>Weights in the scoring process; /(I)And/>Is a nonlinear adjustment coefficient for adjustingAnd/>Is a nonlinear effect of (1);

determining a spectrum resource demand level according to the calculated network state score;

and dynamically adjusting spectrum allocation according to the determined spectrum resource demand level.

With reference to the first aspect, in certain implementations of the first aspect, the system further includes: the spectrum resource demand level includes a low demand, a medium demand, and a high demand.

With reference to the first aspect, in certain implementations of the first aspect, the system further includes: the determining process of the spectrum resource demand level comprises the following steps:

When the calculated network state score is not more than 0.3, the spectrum resource requirement level is low requirement;

When the calculated network state score is greater than 0.3 and not greater than 0.6, the spectrum resource requirement level is a medium requirement;

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

With reference to the first aspect, in certain implementations of the first aspect, the system further includes: the process of dynamically adjusting spectrum allocation according to the determined spectrum resource demand level comprises the following steps:

when the spectrum resource demand level is determined to be low demand, reserving the current spectrum allocation or reducing the current spectrum allocation by 5%;

when the spectrum resource requirement level is determined to be the medium requirement, increasing the current spectrum allocation by 10%;

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

With reference to the first aspect, in certain implementations of the first aspect, the system further includes: the data reordering and encrypting module comprises an executing unit for executing a data reordering algorithm and an encrypting unit for implementing an adaptive encrypting technique.

With reference to the first aspect, in certain implementations of the first aspect, the system further includes: the execution unit is used for:

calculating a composite score for a 5G packet according to the following formula ：

Wherein,、/>、/>And/>Is a weight coefficient; /(I)The urgency of the 5G data packet is determined according to the attribute or service requirement of the data packet; /(I)Is the maximum urgency value of the system definition,/>As a priority decay function,/>As a size sensitivity function,/>A flow regulating function for the destination;

And reordering according to the calculated comprehensive score of each 5G data packet.

With reference to the first aspect, in certain implementations of the first aspect, the system further includes: the priority decay functionThe method is realized by adopting the following formula:

Wherein, P is the priority of the 5G data packet, and is determined according to the type of the 5G data packet; t is the latency of the 5G packet in the queue; Is the attenuation coefficient;

Size sensitivity function The method is realized by adopting the following formula:

Wherein S is the size of the 5G data packet; is a threshold for the influence of the size of the 5G packet on the priority; c is the congestion level of the current network;

Destination traffic conditioning function The method is realized by adopting the following formula:

wherein D is a quantized value of the destination of the 5G packet, indicating the importance of the destination of the packet to network performance; n represents the current network traffic level, quantified as a percentage of network usage; Is a scaling factor used to balance the weight of network traffic on destination priority impact.

With reference to the first aspect, in certain implementations of the first aspect, the system further includes: the encryption unit is used for:

Identifying key features of the 5G data packet, the key features including data type, data sensitivity level, and urgency of data transmission;

Determining a proper encryption algorithm according to the identified key features;

The 5G data packet is encrypted using the determined encryption algorithm.

With reference to the first aspect, in certain implementations of the first aspect, the system further includes: the intelligent transmission control center is used for:

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

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

Monitoring network flow and load conditions, and recording total throughput, average delay and real-time congestion level of the network;

and adjusting network traffic distribution, starting priority adjustment and security reinforcement according to the spectrum allocation record, the detailed record of data processing, the total throughput of the network, the average delay and the real-time congestion level.

The invention has the beneficial effects that:

The system can adaptively manage and allocate the 5G spectrum resources according to the real-time network load, the user demand and the spectrum service condition through the dynamic spectrum resource allocation module. The dynamic allocation algorithm optimizes the utilization of spectrum resources, reduces resource idling and waste, enables the network to support more users and services, and simultaneously maintains high-speed data transmission rate. (2) The dynamic spectrum allocation mechanism can effectively cope with network load change, and the network bottleneck and congestion phenomenon can be avoided by intelligently allocating resources. The method not only improves the overall performance of the network, but also ensures that the user can still enjoy stable and reliable service under the condition of high demand. (3) The data reordering and encrypting module adopts an algorithm specially designed for the 5G data packet, performs intelligent reordering according to the characteristics of the data packet such as priority, size and destination, dynamically selects an encrypting strategy, and not only improves the efficiency of data transmission, but also ensures the data safety in the transmission process. This method is particularly suited for handling 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 strategies in time by comprehensively evaluating the running state of the network, such as adjusting network flow distribution, starting priority adjustment of data processing and enhancing security measures. This adaptive adjustment mechanism enables the network to flexibly cope with various situations, optimizing the user experience, especially when the network is highly loaded or security threatened.

Drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described, and it will be obvious to those skilled in the art that other drawings can be obtained according to these drawings without inventive effort;

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

Detailed Description

The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.

Embodiment one:

the following description is made of the relevant terms related to the embodiments of the present application:

as shown in fig. 1, a data transmission system based on a 5G technology includes:

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

A dynamic spectrum resource allocation module 101, configured to execute a spectrum dynamic allocation algorithm optimized for the 5G network, where the spectrum dynamic allocation algorithm adaptively manages and allocates 5G spectrum resources based on a specific load, a user demand, and a spectrum usage situation of the 5G network, so as to optimize 5G spectrum utilization and reduce 5G network congestion.

In the present embodiment, the dynamic spectrum resource allocation module 101 is specifically designed to cope with the challenges of spectrum management in 5G networks. The module adopts a frequency spectrum dynamic allocation algorithm which is specially optimized for the 5G network environment, and can be automatically adjusted according to the real-time load of the 5G network, the specific requirements of users and the current frequency spectrum use condition. The module is capable of dynamically managing and allocating 5G spectrum resources to ensure that at any given time, efficiency of spectrum usage is maximized while network congestion is significantly reduced or avoided.

Specifically, the operation of the dynamic spectrum resource allocation module 101 begins with continuously monitoring the state of the 5G network. This includes collecting data in real time regarding network load, user activity, and spectrum occupancy. Based on this information, the spectrum dynamic allocation algorithm analyzes the current network conditions, predicts future demand changes, and makes decisions based thereon to dynamically adjust spectrum allocation. This process takes into account a number of factors including, but not limited to, the geographic location of the user, the priority of the type of service, and other dynamic changes in the network.

In addition, the module is also capable of responding to feedback from the intelligent transmission control center 103. While the intelligent transmission control center 101 does not direct every operation of the dynamic spectrum resource allocation module 101, it provides valuable insight and advice by analyzing the operational results and status of the entire network. This includes adjusting spectrum allocation policies based on global network conditions to optimize overall network performance and user experience.

The dynamic spectrum resource allocation module 101 should have a high degree of configurability and flexibility to accommodate different network environments and requirements. When the module is implemented, algorithm parameters, such as a priority rule of spectrum allocation, a time window size of spectrum demand prediction and a speed of responding to network change, can be adjusted according to specific network architecture and user demands.

Still further, the dynamic spectrum resource allocation module performs spectrum resource management and allocation using a spectrum dynamic allocation algorithm based on a network status score, wherein the network status scoreCalculated according to the following equation 1:

Wherein, Representing network load degree, representing the ratio of the spectrum resource currently in use in a specific area to the total available spectrum resource in the area; /(I)Representing service priorities for representing weighted importance of various service types within a particular area; /(I)Representing the dynamic change degree of the demand, and representing the change trend of the user demand in a specific area; /(I)And/>Is a weight coefficient for adjusting/>And/>Weights in the scoring process; /(I)And/>Is a nonlinear adjustment coefficient for adjustingAnd/>Is a nonlinear effect of (1); determining a spectrum resource demand level according to the calculated network state score;

The network load, service priority and demand dynamic change are all measurement indexes aiming at specific areas. These indicators reflect the usage of the 5G network in the area, the importance of the service type and the trend of the user's demand. How these indices are calculated will be described in detail below.

Network load degreeIs calculated by (1):

The network load level represents the ratio of the spectrum resources currently being used in a particular region to the total available spectrum resources in that region. It is a direct indicator of how well the network is congested.

First, data about spectrum usage in a particular area needs to be collected. This includes the total amount of available spectrum resources (total spectrum resources) and the amount of spectrum resources currently being used (used spectrum resources) for that region.

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

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

This means that the network loading of this area is 0.7, or 70%.

Calculation of Service Priority (SPD):

Service priorities are calculated based on the importance or priority of different service types within a particular area. Different services (e.g., emergency communication, video streaming, data downloading, etc.) will be given different priority weights.

1. Defining priority weights: first, a priority weight is defined for each service type. Emergency services may be weighted highest, followed by video streaming, and then conventional data services, including data downloads.

2. Collecting service usage data: usage data for different service types within a particular area is collected.

3. Calculating service priority according to the following equation 3：

For example, if 40% of the resources are used by the video stream (service type priority weight of 0.8) in one area, 30% of the resources are used by the emergency service (service type priority weight of 1.0), and the remaining 30% of the resources are used by the normal data service (service type priority weight of 0.5), then:

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

Degree of demand dynamic changeIs calculated by (1):

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

1. Selecting a time window: a time window for the analysis is determined, for example comparing data for the same time period today and yesterday.

2. Time point data were collected: network usage data is collected at two points in time.

3. The demand dynamics are calculated according to the following equation 4:

for example, if the time of yesterday is 50MHz for a particular area and 60MHz for the same time of day, then:

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

Assume at some point that the network is loadedHigher, indicating that the network is facing greater data transmission demands. Service priority/>Reflecting the need for high priority services in the current service. Demand dynamic degree/>Indicating the rate of increase of demand in the near future.

By introduction ofAnd/>The formula can more accurately adjust the influence of network load degree and service priority degree so as to have different sensitivities under different network states. At the same time/>The method ensures that even under the condition that the demand rapidly changes, the influence of the dynamic change degree of the demand can be reasonably controlled, and the phenomenon that the spectrum resource excessively deviates to a certain aspect due to temporary demand surge is avoided.

In this way, the dynamic spectrum resource allocation module 101 can respond to the real-time state and requirement of the network more carefully and dynamically, and provides a more complex and adaptive spectrum resource allocation strategy for the 5G network.

Determining weight coefficientsAnd/>Nonlinear adjustment coefficient/>And/>It generally involves in-depth analysis of the network environment, service requirements, and historical data. The setting of these coefficients is intended to reflect the actual degree of impact of the different network parameters on the overall network performance, as well as the relative importance between these parameters. The following is a detailed explanation and method of determining these coefficients.

Determining weight coefficientsAnd/>At least one of the following modes may be employed:

1. historical data analysis: by analyzing the historical network performance data, the network load degree can be estimated ) And service priority (/ >)) Impact on network performance (e.g., throughput, delay, etc.). If the impact of network loading on performance is found to be more pronounced, then/>Should be set to be a ratio/>Higher and vice versa.

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

3. Optimizing and simulating: by building a network model and performing simulations, different combinations of weights can be tried and observed which combination can provide optimal network performance. This approach may help fine tune the weighting coefficients.

Determining nonlinear adjustment coefficientsAnd/>At least one of the following modes may be employed:

1. nonlinear impact analysis: the setting of the nonlinear adjustment coefficient first requires analysis And/>Is a non-linear influence of (c). For example, if the network loading approaches the capacity limit, its negative impact on network performance may exceed the linear expectation, where a larger/>Values reflect this nonlinear effect.

2. Parameter adjustment and test: by adjustingAnd/>And monitors how these adjustments affect the network state scoring function (/ >)) The most suitable nonlinear adjustment coefficient can be found for the reflection of the actual network conditions. This may require multiple rounds of testing and optimization.

3. Mathematical modeling and optimization algorithm: description using mathematical modeling methodAnd/>Nonlinear characteristics affecting network performance. An optimization algorithm (e.g., gradient descent) can then be used to find the best/>And/>Values such that the model most accurately predicts network performance.

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

In practice, 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. Furthermore, as network technology evolves and user behavior changes, these coefficients may need to be periodically re-evaluated and adjusted.

Still further, the spectrum resource demand level includes low demand, medium demand, and high demand; the determining the spectrum resource requirement level according to the calculated network state score comprises:

when the calculated network state score is greater than 0.6, the spectrum resource demand level is high demand;

The dynamically adjusting spectrum allocation according to the determined spectrum resource demand level comprises the following steps:

For example, if calculated, the NSF value for region a is 0.55, belonging to the "medium demand" interval; the NSF value of region B is 0.75, belonging to the "high demand" interval. Adjusting a decision model according to the spectrum resources:

for region a, the spectrum resource allocation will be increased by 10%. If region a were originally allocated 100MHz of spectrum resources, it would now increase to 110MHz.

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

In this way, the spectrum dynamic allocation algorithm can dynamically adjust the spectrum allocation strategy according to the calculated NSF value in real time by a quantization method, ensure to more effectively meet the service types and user requirements of different areas, and simultaneously optimize the 5G spectrum utilization rate and reduce network congestion.

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

The data reordering and encrypting module 102 is configured to execute a data reordering algorithm specifically designed for the 5G data packet, and an adaptive encrypting technique, where the data reordering algorithm intelligently reorders according to the priority, size and destination of the 5G data packet, and the adaptive encrypting technique dynamically selects an encrypting policy according to the characteristics of the 5G data, so as to ensure data security in the transmission process of the 5G network.

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

The process of data reordering is based on the priority, size and destination of the 5G packets. First, the system analyzes the incoming packets to identify these key attributes for each packet. For example, urgent voice call packets may 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 more quickly, thus meeting the needs of real-time or high sensitivity services.

In carrying out this process, it is necessary to develop an algorithm that is capable of analyzing and classifying incoming packets in real time and ordering them according to preset rules. This may involve constructing a priority queue in which packets are inserted into appropriate locations for subsequent processing and transmission, depending on their priority, size and destination.

After data reordering, adaptive encryption techniques are applied to the ordered data packets. This technique dynamically selects encryption policies based on the characteristics of 5G data, meaning that different types of data (such as text messages, video streams, or file transfers) may apply different strengths or types of encryption methods. This adaptation not only enhances the security of the data, but also optimizes the efficiency of the encryption process-ensuring that more complex, computationally intensive encryption methods are used only when necessary.

To achieve this, it is necessary to design a system that can evaluate the sensitivity and security requirements of the data packets and select the appropriate encryption algorithm based thereon. This may involve building a database of encryption policies that contains recommended encryption methods for different data types and scenarios. The system will select the most appropriate encryption policy from the database to apply based on the attributes of the data packet, such as data type, destination and priority, and the security status of the current network.

Combining data reordering with adaptive encryption, the data reordering and encryption module 102 provides an efficient and secure path for 5G data transmission. When deploying this module, it is necessary to ensure that the system is able to process a large number of data packets in real time while maintaining sufficient flexibility and adaptability in selecting reordering rules and encryption policies. In addition, the system is designed to allow for cooperation 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 the design and implementation, the 5G data transmission system provided by the embodiment can provide powerful data protection for users while guaranteeing high-efficiency data processing, and meets the double requirements of modern communication networks on speed and safety.

Still further, the data reordering and encryption module comprises an execution unit for executing a data reordering algorithm, the execution unit being specifically configured to:

Calculating a composite score for a 5G packet according to equation 2 below ：

Wherein,、/>、/>And/>Are weight coefficients, which may be obtained from experimental data or from expert experience;

the urgency of the 5G data packet can be determined according to the attribute or service requirement of the data packet; /(I) Is the maximum urgency value defined by the system;

urgency is a key indicator for evaluating the transmission priority of data packets, especially in case of network congestion or limited resources. The following steps provide a framework for quantifying and implementing the determination of urgency.

The step of determining the urgency of the data packet comprises:

(1) Defining an emergency degree index: first, it is necessary to define what degree of urgency and how to quantify. The urgency may be determined based on factors such as the real-time requirements of the data packet, sensitivity to delay, quality of service (QoS) requirements, and the like. For example, real-time video or voice communications may have a high urgency, while email or ordinary data downloads may have a lower urgency.

(2) Identifying a packet attribute: the determination of the degree of urgency requires analysis of 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 typically contains QoS-related fields, such as a Differentiated Services Code Point (DSCP) field, that can be used to identify the priority and type of data flow.

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

(3) Quantifying the degree of urgency: based on the identified packet attributes, the urgency is measured as a specific value. This step may be performed in the following manner:

predefined urgency level: a set of urgency levels are predefined for different service types or QoS requirements and corresponding values are assigned. For example, the 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 current network conditions or real-time requirements of the data packet. For example, if the network congestion is severe, even ordinary data downloads may be given a high degree of urgency to ensure quality of service.

(4) And (3) carrying out emergency degree judgment: the incoming packets are analyzed and each packet is assigned an urgency value according to the criteria described above.

Through the above steps, the urgency level can be determined for the 5G data packet, so that priority management based on the urgency level is realized in the data reordering and encryption module. The method not only improves the utilization efficiency of network resources, but also ensures that the requirements of users on high-quality services can be met at key moments.

Priority decay functionThe implementation is as follows using equation 3:

Priority decay function Taking into account the priority and latency of 5G packets, it is ensured that high priority and/or longer latency packets are processed faster.

Wherein,Is the priority of the 5G data packet and is determined according to the type of the 5G data packet. Common types include, but are not limited to, emergency communications (e.g., emergency calls, alert signals), real-time services (e.g., voIP conversations, real-time video streaming), large data transmissions (e.g., file downloads, video uploads), and regular data transmissions (e.g., web browsing, email). Emergency communications may be given a value close to 1, whereas conventional data transmissions may be close to 0.;

T is the latency of the 5G packet in the queue; Is an attenuation coefficient, can be determined through experimental data or can be obtained through expert knowledge;

Size sensitivity function The implementation is as follows using equation 4:

Size sensitivity function The effect of the size of the data packet on its processing priority, and the feedback of the current network congestion level are taken into account by the logistic function.

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

is a threshold for the influence of the size of the 5G packet on the priority;

C is the congestion level of the current network;

how to determine the threshold of the packet size impact on priority is described in detail below And the congestion level C of the current network.

Is a key parameter for distinguishing between large packets that may have a greater impact on network performance and small packets that have a lesser impact. The determining method comprises the following steps:

1. Network performance analysis: firstly, by analyzing historical data of the performance of the network, the influence of data packets with different sizes on the network delay and throughput is determined. In particular, the average size of the packets at the beginning of the network showing signs of congestion is analyzed.

2. Quality of service requirements: with reference to quality of service (QoS) requirements for different types of services, for example, real-time video streaming may have a strict limitation on the maximum delay of data packets, thereby affectingIs set by the setting of (2).

3. Empirical values: in many cases the number of times that the number of time,The setting of (c) may also depend on the experience of the network administrator and the expected network usage. For example, if the network is primarily used for services that transport small data packets, such as instant messaging,May be relatively small.

The congestion degree C of the network is a dynamic index and reflects the current network resource use condition and the data traffic level which can be borne by the network. The determining method comprises the following steps:

1. And (3) monitoring the real-time flow: the congestion level of the network is assessed by continuously monitoring the real-time traffic and resource usage (e.g., bandwidth usage, router queue length, etc.) of the network.

2. And (3) calculating congestion indexes: the congestion level of the network is quantified using a specific algorithm or model, such as an index of packet loss rate, round Trip Time (RTT) increase, etc., in the TCP congestion control algorithm. C may be set to a value between 0 (no congestion) and 1 (extreme congestion).

Determined by comprehensive application of the above methodAnd C, the data reordering and encryption module 102 can more intelligently adjust priority based on real-time network conditions and packet characteristics to optimize data transmission efficiency and responsiveness of the 5G network. For example, when the network congestion level C is high, the system may prioritize less than/>To reduce network delay and to increase throughput, thereby ensuring quality of service while reasonably allocating network resources.

Destination traffic conditioning functionThe implementation is realized by adopting the following formula 5:

Wherein D is a quantized value of the destination of the 5G packet, indicating the importance of the destination of the packet to network performance;

Quantifying destination D of a 5G packet involves translating the importance of the destination into a measurable and comparable value. This quantization process takes into account the potential impact of the destination on network performance, including factors such as urgency of packet transmission, quality of service requirements, and network status of the target node. The following is a framework of the quantization process, which is intended to provide guidance to the person skilled in the art how to achieve this goal.

Defining destination importance indicators includes;

1. network topology roles: the role and role of the destination node in the network topology are identified. For example, edge computing nodes, core network nodes, or cloud data centers may be given higher importance due to their critical 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, and thus the importance of the destination may be higher.

3. User experience impact: the potential impact of a failure or performance degradation of the destination node on the end user experience is evaluated. The node with larger influence on the user experience has higher destination importance.

The quantization method comprises the following steps:

1. Grading system: a hierarchical system is established to assign predefined importance levels to different destination types or categories. For example, importance may be classified into three levels, low, medium, and high, corresponding to values of 0.3, 0.6, and 0.9, respectively.

2. Weight distribution: each importance index is assigned a weight reflecting its degree of contribution to the total importance of the destination. For example, network topology roles may account for 50% of total importance, service type requirements 30%, and user experience impact 20%.

3. Calculating a comprehensive importance value: based on the different attributes of the destination and the assigned weights, the comprehensive importance value D thereof is calculated. For example, if one destination is an edge computing node (high importance), supports real-time video streaming (high demand) and has a large impact on the user experience (high impact), it may get near the highest quantized value.

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

is an adjustment factor for balancing the weight of network traffic impact on destination priority, which can be obtained through experimental data acquisition or through expert knowledge;

and reordering according to the calculated comprehensive score of each 5G data packet. E.g., may reorder from high to low based on the composite score.

Still further, the data reordering and encryption module comprises an encryption unit for implementing an adaptive encryption technique, the encryption unit being specifically configured to:

The 5G data packet is encrypted using the determined encryption algorithm.

In the data transmission system based on the 5G technology provided in this embodiment, the data reordering and encryption module plays a crucial role, especially the encryption unit therein, which adopts the adaptive encryption technology to ensure the security in the data transmission process. The key feature of the technology is that the key feature of the data packet is intelligently identified, and the most suitable encryption algorithm is selected to encrypt the data according to the key feature. This technique is described in detail below.

The encryption unit first needs to perform deep analysis on the incoming 5G packet to identify its key features, including:

data type: the data packets may contain various types of data such as text, pictures, audio or video. This step involves analysing the content or header information of the data packet to determine the type of data it carries.

Data sensitivity level: depending on the content and purpose of the data, the data packets may be classified as open, sensitive or confidential, among other different sensitivity levels. This typically requires predefined policies or rules, and possibly content detection techniques, 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 high degree of transmission urgency. The evaluation of the urgency may be based on a service type identification or other relevant indicator of the data packet.

Once the key features of the data packet are identified, the encryption unit then determines which encryption algorithm to use as best suited based on these features. This process includes:

establishing an encryption algorithm library: first, a library is created that contains a plurality of encryption algorithms, each algorithm corresponding to a particular combination of data features.

Matching algorithm: the encryption unit selects the best matching algorithm by comparing the characteristics of the data packet with the applicable conditions of each algorithm in the algorithm library. For example, for data of high sensitivity and urgency, it is possible to select an algorithm with high encryption strength but moderate computational complexity.

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

Generating a key: the necessary encryption key is generated according to the selected encryption algorithm. This step may involve a key exchange protocol to ensure that both the data sender and receiver can securely share the key.

Encryption is performed: the generated secret key and the determined algorithm are used for encrypting the content of the data packet, so that the content is ensured not to be accessed or tampered with by unauthorized in the transmission process.

Key management: effective key management policies, including updating, revocation and storage of keys, need to be implemented during encryption to prevent key leakage or misuse.

Through the above procedure, the encryption unit is able to provide highly customized security protection for each data packet in the 5G data transmission system. By intelligently identifying the data characteristics and dynamically selecting the encryption algorithm, the self-adaptive encryption technology not only improves the safety of data transmission, but also optimizes the efficiency and performance of the encryption process.

The intelligent transmission control center 103 is used for comprehensively evaluating the running results of the dynamic spectrum resource allocation module, the data reordering and encryption module, and the 5G network state, the user behavior and the data characteristics which are analyzed in real time; and based on the result of the comprehensive evaluation, adjusting network traffic distribution, starting priority adjustment and security reinforcement.

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

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 network status and traffic distribution in real time. Based on the information, the method can make accurate decisions, adjust network configuration and resource allocation to realize optimal distribution of network traffic, optimize priority ordering of data transmission and strengthen safety in the data transmission process.

The implementation method comprises the following steps:

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

2. Comprehensive evaluation: by performing in-depth analysis and processing on the collected data, the intelligent transmission control center can comprehensively evaluate the overall performance and the safety condition 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 result of the comprehensive evaluation, the intelligent transmission control center will make a series of decisions including adjusting the allocation policy of the spectrum resources, optimizing the reordering rules of the data packets, enhancing the data encryption measures, etc. These decisions aim to improve the performance and efficiency of the network, reduce congestion, improve the security of data transmission, and improve the service experience of the user.

By implementing the intelligent transmission control center 103,5G data transmission system, higher network performance and security can be realized, the increasing data transmission requirements are met, and better quality service is provided for users. The design and implementation of this system presents a great potential for 5G technology in intelligent network management and optimization.

Still further, the intelligent transmission control center is specifically configured to:

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

acquiring detailed records of data processing from the data reordering and encryption module 102, the detailed records including processing delay, encryption algorithm selection, and encryption success rate of the 5G data packet;

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

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

2. Acquiring a data processing record: at the same time, the control center will also obtain detailed records about the processing of the 5G packet from the data reordering and encryption module 102, including the processing delay time of the packet, the encryption algorithm selected and its success rate. This information helps to evaluate the performance of the data stream processing and encryption operations.

3. Monitoring the network state: the control center continues to monitor the traffic and load conditions throughout the network, including recording the overall throughput, average delay time, and real-time congestion level of the network. These metrics directly reflect the operating conditions and performance bottlenecks of the network.

According to the collected data, the intelligent transmission control center comprehensively evaluates the overall performance, the safety and the user satisfaction of the network, and then makes corresponding adjustment according to the evaluation result so as to optimize the network. This may include adjusting network traffic distribution to relieve congestion, adjusting the priority of data processing and encryption operations to increase efficiency, and enhancing data security measures to protect user data.

The following is an example illustration:

Example 1: congestion relief: if the intelligent transmission control center finds that the real-time congestion level of a certain area continuously rises, by analyzing the spectrum allocation record and the network throughput, it may decide to reallocate the spectrum resources, increase the bandwidth of the area, or adjust the route of the data flow to disperse the traffic, thereby alleviating the congestion.

Example 2: encryption policy optimization: based on the detailed record of data processing, if the control center finds that the success rate of one encryption algorithm is lower than expected, another encryption algorithm may be selected to replace or adjust the priority of encryption operation, so as to ensure the safe transmission of sensitive data.

Through the steps and the examples, the intelligent transmission control center can effectively manage and optimize the 5G network, ensure efficient and safe data transmission and improve user experience. The comprehensive evaluation and automatic adjustment mechanism is a key for realizing dynamic and intelligent network management, and provides solid technical support for high-performance operation of the 5G network.

Based on the same inventive concept, the present invention also provides a computer apparatus comprising: one or more processors, and memory for storing one or more computer programs; the program includes program instructions and the processor is configured to execute the program instructions stored in the memory. The processor may be a central processing unit (Central Processing Unit, CPU), but may also be other general purpose processor, digital signal processor (DIGITAL SIGNAL Processor, DSP), application specific integrated circuit (Application SpecificIntegrated Circuit, ASIC), field-Programmable gate array (Field-Programmable GATEARRAY, FPGA) or other Programmable logic device, discrete gate or transistor logic device, discrete hardware components, etc., that are the computational core and control core of the terminal for implementing one or more instructions, particularly for loading and executing one or more instructions within a computer storage medium to implement the methods described above.

It should be further noted that, based on the same inventive concept, the present invention also provides a computer storage medium having a computer program stored thereon, which when executed by a processor performs the above method. The storage media may take the form of any combination of one or more computer-readable media. The computer readable medium may 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 electronic, magnetic, optical, electrical, magnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples (a non-exhaustive list) of the computer-readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, 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 disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.

In the description of the present specification, the descriptions of the terms "one embodiment," "example," "specific example," and the like, mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present disclosure. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiments or examples. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.

The foregoing has shown and described the basic principles, principal features, and advantages of the present disclosure. It will be understood by those skilled in the art that the present disclosure is not limited to the embodiments described above, which have been described in the foregoing and description merely illustrates the principles of the disclosure, and that various changes and modifications may be made therein without departing from the spirit and scope of the disclosure, which is defined in the appended claims.

Claims

1. A data transmission system based on 5G technology, comprising:

2. The data transmission system according to claim 1, wherein the dynamic spectrum resource allocation module performs 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 NSF is calculated as follows:

Wherein, Representing the network load degree; /(I)Representing service priority; /(I)Representing the dynamic change degree of the demand; /(I)AndIs a weight coefficient; /(I)And/>Is a nonlinear adjustment coefficient;

3. The data transmission system according to claim 2, wherein the spectrum resource requirement level includes a low requirement, a medium requirement and a high requirement.

4. A data transmission system based on 5G technology according to claim 3, wherein the determining of the spectrum resource requirement level is:

5. A data transmission system based on 5G technology according to claim 2, wherein the process of dynamically adjusting the spectrum allocation according to the determined spectrum resource requirement level:

6. The data transmission system based on 5G technology according to claim 1, wherein the data reordering and encryption module comprises an execution unit for executing a data reordering algorithm and an encryption unit for implementing an adaptive encryption technology.

7. The data transmission system according to claim 6, wherein the execution unit is configured to:

Wherein,、/>、/>And/>Is a weight coefficient; /(I)Is the urgency of the 5G packet; /(I)Is the maximum urgency value of the system definition,/>As a priority decay function,/>As a size sensitivity function,/>A flow regulating function for the destination;

8. The data transmission system based on 5G technology as claimed in claim 7, wherein the priority decay functionThe method is realized by adopting the following formula:

Wherein, Is the priority of the 5G data packet, and is determined according to the type of the 5G data packet; t is the latency of the 5G packet in the queue; /(I)Is the attenuation coefficient;

Wherein D is a quantized value of a destination of the 5G packet; n represents the current network traffic level, quantified as a percentage of network usage; For adjusting the coefficients.

9. The data transmission system according to claim 6, wherein the encryption unit is configured to:

The 5G data packet is encrypted using the determined encryption algorithm.

10. The data transmission system based on the 5G technology according to claim 1, wherein the intelligent transmission control center is configured to: