A dynamic spectrum allocation based wireless communication network resource optimization system

Abstract

This invention relates to the field of wireless communication management technology, and in particular to a wireless communication network resource optimization system based on dynamic spectrum allocation. The system includes collecting basic network information of the wireless communication network, dividing the communication area time into several independent time periods, analyzing the stage information of each time period based on the collected basic network information, determining communication feature tags, identifying these tags, integrating independent time periods corresponding to the same tag, determining the corresponding frequency band, and combining this with key communication needs to obtain the preferred frequency band for that tag. Then, an inertial value set is constructed for the terminal user. Finally, the network adjustment module identifies the current time and determines the preferred frequency band, obtaining the user's current time period feature value based on the inertial value set, and completing real-time allocation based on the total bandwidth resources of the preferred frequency band. This invention dynamically matches the preferred frequency band to the current time, adapting to traffic fluctuations, achieving both flexible scheduling and compliance with regulatory requirements, and is applicable to diverse scenarios.

Description

Technical Field

[0001] This invention relates to the field of wireless communication management technology, and in particular to a wireless communication network resource optimization system based on dynamic spectrum allocation. Background Technology

[0002] With the growth of wireless services such as 5G, the number of users of wireless communication networks has surged, and the types of services have become more diversified and heterogeneous, leading to an ever-increasing demand for spectrum resources.

[0003] The prior art CN114641005A discloses a network resource management method and apparatus for dynamic spectrum sharing, which includes comparing and measuring interfered and uninterrupted time-frequency resources during network resource scheduling, and dynamically and finely scheduling time-frequency resources based on rate or dynamic frequency domain scheduling.

[0004] However, traditional wireless communication networks mostly adopt static spectrum allocation mechanisms, which result in low spectrum resource utilization. At the same time, when popular frequency bands are frequently congested due to concentrated user access, they cannot adapt to the dynamic fluctuations of service traffic and cannot meet the differentiated needs such as throughput of high-bandwidth services and battery life of low-power services. Summary of the Invention

[0005] The purpose of this invention is to solve the problems in the background art by proposing a wireless communication network resource optimization system based on dynamic spectrum allocation.

[0006] To achieve the above objectives, the present invention adopts the following technical solution:

[0007] A wireless communication network resource optimization system based on dynamic spectrum allocation includes:

[0008] The network information acquisition module is used to collect basic network information of wireless communication networks;

[0009] The feature processing module is used to divide the time of the communication area into several independent time periods, and then, based on the basic network information, collect and analyze the phase information in the independent time periods to determine the communication feature tags of the phase information.

[0010] The frequency band analysis module is used to identify communication feature tags, integrate the corresponding independent time periods of the same communication feature tags, determine the frequency bands that exist in the communication feature tags, and then determine the preferred frequency bands of the communication feature tags based on key communication needs.

[0011] The user analysis module is used to identify terminal users in the communication area, perform inertial analysis on the amount of data requested by terminal users, determine the representative value of the terminal user's request in each independent time period, and then determine the set of inertial values ​​of the terminal user based on the representative value of the request in each independent time period.

[0012] The network adjustment module is used to identify the current time and determine the preferred frequency band. At the same time, based on the inertial value set, it determines the current time period characteristic value of the terminal user. Then, based on the total bandwidth resource of the preferred frequency band and the current time period characteristic value of the terminal user, it allocates the total bandwidth resource of the preferred frequency band in real time.

[0013] As a further aspect of the present invention, the method for determining communication feature tags includes:

[0014] S1: Set the period time and unit time respectively, and divide the period time again according to the unit time to obtain several independent time periods. The period time and unit time are both time thresholds, and the period time is greater than the unit time.

[0015] Collect communication information within the communication area, divide the communication information into independent time periods, and obtain phase information;

[0016] S2: Sequentially mark the stage information as target information segments, and extract the running data from the target information segments respectively. The running data includes the number of users, user type and business type.

[0017] S3: First, extract the number of users Yh from the target information segment, and determine the load status based on the number of users Yh. The load status includes high load, medium load and low load.

[0018] S4: Obtain the running data in the target information segment, classify the running data according to user type to obtain user type 1, user type 2 and user type 3, count the quantity in each user type to determine the number of users accessing each user type, divide the number of users accessing each user type by the number of users Yh in the target information segment, and mark the calculation result as the user ratio coefficient, obtain the user ratio coefficient corresponding to each user type, identify the maximum value in the user ratio coefficient, and mark the user type corresponding to the maximum value as the key user information of the target information segment;

[0019] S5: Next, obtain the business type from the running data, process the business type according to the above method, obtain the business ratio coefficient of each business type, identify the maximum value among the business ratio coefficients, and mark the business type corresponding to the maximum value as key business information;

[0020] S6: Obtain the load status, key user information, and key service information of the target information segment, and recombine them to obtain the communication feature tag of the target information segment.

[0021] As a further aspect of the present invention, the user type refers to a classification based on the hardware attributes, power consumption level, and resource consumption capacity of the terminal device, including high-consumption terminal users, low-power terminal users, and professional terminal users. High-consumption terminal users refer to users whose hardware supports high data transmission and whose own power consumption tolerance is high. Low-power terminal users refer to users whose terminals rely on low-power operation and mainly transmit small amounts of data. Professional terminal users refer to users whose terminals carry critical business in specific industries and have extreme requirements for communication reliability or latency.

[0022] As a further aspect of the present invention, the service type refers to the classification based on the performance requirements and data characteristics of the communication services carried by the terminal, including eMBB services, uRLLC services, and mMTC services. Among them, eMBB services refer to consumer-grade communication services with "high data rate and large bandwidth transmission" as the core requirements, uRLLC services refer to industry-level key services with "extreme latency and extremely high reliability" as the core requirements, and mMTC services refer to Internet of Things services with "massive device access and low power consumption and small data transmission" as the core requirements.

[0023] As a further aspect of the present invention, the method for determining the load state includes:

[0024] Extract the basic network information of the communication area and set node thresholds Y1 and Y2. When Yh≤Y1, the load status in the target information segment is marked as low load. When Y1<Yh≤Y2, the load status is marked as medium load. When Yh>Y2, the load status is marked as high load. Where Y1<Y2.

[0025] As a further aspect of the present invention, user type 1, user type 2 and user type 3 correspond to high-consumption terminal users, low-energy-consumption terminal users and professional terminal users, respectively.

[0026] As a further aspect of the present invention, the method for determining the preferred frequency band includes:

[0027] Select a communication feature label b, obtain the independent time period corresponding to this communication feature label b, and mark it as the target analysis time period. Collect the network communication frequency bands that exist in the target analysis time period and mark them as frequency band i, i=1, 2, ..., and then obtain the standard operating parameters corresponding to the communication feature label b.

[0028] Let i=1, that is, obtain the communication operation parameter j in frequency band 1, where j represents different communication operation parameters, including operating power consumption, latency rate, transmission rate and error rate;

[0029] Using formula The communication operation parameter j is normalized to obtain the standardized operation parameter Dj. When the communication operation parameter j is the transmission rate, then... ;

[0030] Based on the key communication requirements of communication feature tag b, set corresponding parameter ratios for communication operation parameter j. Then use the calculation formula The frequency band operating coefficients FXi are obtained, where J represents the total number of communication operating parameters;

[0031] The remaining frequency bands i are then processed in the same way described above to determine the frequency band operating coefficient FXi for each frequency band i.

[0032] Obtain the band operation coefficient FXI of each frequency band i under the communication feature label b, compare the frequency band operation coefficient FXI, identify the maximum value of the frequency band operation coefficient FXI, and mark the network communication frequency band corresponding to the frequency band with the maximum value as the preferred frequency band of the communication feature label b.

[0033] As a further aspect of the present invention, the method for determining the inertial numerical set includes:

[0034] Select any terminal user in the power supply area and collect the request data volume of this terminal user. Visualize the request data volume. In this embodiment, the visualization is set as a curve, that is, set time as the horizontal axis and request data volume as the vertical axis to establish a two-dimensional coordinate system. Mark the request data volume of the terminal user in the two-dimensional coordinate system in chronological order and perform linear fitting to obtain the curve.

[0035] The requested data volume is divided into independent time periods. The requested data volume in each independent time period is marked as a local data segment. Then, the mean of each local data segment is calculated, and the mean calculation result is marked as the representative value of the request in this independent time period.

[0036] According to the periodic time, the representative request values ​​in the independent time period are grouped, and the grouped representative request values ​​are then arranged in chronological order to obtain a set of values, where the periodic time corresponds one-to-one with the set of values.

[0037] Select the representative request value of the first position in all the numerical sets, and then use the mean processing method to calculate the mean of the representative request value of the first position. Mark the result as the time period feature value. Calculate the time period feature values ​​of all positions in the numerical set according to the above method, integrate the time period feature values ​​of all positions into a set, and then determine the inertial numerical set of this terminal user.

[0038] As a further aspect of the present invention, a method for real-time allocation of the total bandwidth resources of preferred frequency bands includes:

[0039] Collect real-time communication information, process the real-time communication information, determine the current communication feature tags, and then obtain the corresponding preferred frequency band based on the communication feature tags;

[0040] All terminal users are acquired, and based on the current time, the corresponding time period feature values ​​are extracted from the inertial value set. The time period feature values ​​of the terminal users are arranged in descending order to obtain the user sequence. Starting from the first user in the user sequence, the preferred frequency band is allocated first. After the channel allocation of the preferred frequency band is completed, the remaining terminal users in the user sequence are acquired and marked as low-power users.

[0041] Identify the total bandwidth resources of the preferred frequency band, calculate the bandwidth ratio occupied by the data requested by the allocated users, obtain the remaining bandwidth resources that can be carried at present, and select the low-power users whose data requested volume matches the remaining bandwidth resources without affecting the communication quality of the allocated users. Through time division multiplexing or frequency division multiplexing technology, the low-power users can share the remaining bandwidth resources of the preferred frequency band with the allocated users.

[0042] Compared with existing technologies, the advantages of this invention are:

[0043] This invention achieves precise matching between preferred frequency bands and service scenarios by finely dividing time periods and integrating time periods with the same communication characteristics through a frequency band analysis module. Simultaneously, the network adjustment module allocates resources based on real-time user inertial request data, and the user analysis module constructs a set of representative request values ​​for different time periods through inertial analysis of terminal user request data volume, enabling prediction of user resource needs. Based on this set and the bandwidth resources of the preferred frequency band, the network adjustment module achieves a reasonable allocation between users with high request volumes and those with low power consumption, ensuring both the throughput of high-bandwidth services and the reliability of low-latency services, while also meeting the battery life requirements of low-power terminals and considering the QoS indicators of various users. When determining preferred frequency bands, the frequency band analysis module matches them against a fixed compliant frequency band library defined by regulatory agencies, achieving flexible scheduling of dynamic spectrum while avoiding the risks of illegal frequency band use, thus demonstrating practical deployment feasibility. Attached Figure Description

[0044] Figure 1 This is a schematic diagram of the system structure of the present invention. Detailed Implementation

[0045] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments.

[0046] Reference Figure 1 A wireless communication network resource optimization system based on dynamic spectrum allocation includes a network information acquisition module, a feature processing module, a frequency band analysis module, a user analysis module, and a network adjustment module.

[0047] The network information acquisition module is used to collect basic network information of the wireless communication network, including network operating parameters and user operating parameters. Then, a one-way communication connection is established between the network information acquisition module and the feature processing module.

[0048] The feature processing module is used to analyze network communication resources in the communication area and determine communication feature tags for stage information. Specific analysis methods for these communication feature tags include:

[0049] S1: Set the periodic time and unit time respectively, and divide the periodic time again according to the unit time to obtain several independent time periods. The periodic time and unit time are both time thresholds, and the periodic time is greater than the unit time. In this embodiment, the periodic time is set to 1 natural day and the unit time is set to 1 hour.

[0050] Communication information within the communication area is collected, and then the communication information is divided into independent time periods to obtain stage information. The time axis of each stage information is a unit time, that is, there is a one-to-one correspondence between independent time periods and stage information.

[0051] S2: Randomly select a stage information and take it as an example. Mark this stage information as the target information segment and extract the operation data from the target information segment. The operation data includes the number of users, user types, and service types. Furthermore, user types refer to the classification based on the hardware attributes, power consumption levels, and resource consumption capabilities of terminal devices. These include high-power terminal users (users whose hardware supports high data transmission and has high power tolerance, such as 5G smartphones, laptops, or high-definition live streaming equipment), low-power terminal users (users whose terminals rely on low power consumption and mainly transmit small amounts of data, such as sensors, smart meters, and positioning terminals), and professional terminal users (terminals that carry critical business in specific industries and have extreme requirements for communication reliability or latency). The corresponding users include, for example, industrial control modules, vehicle networking OBU devices, and emergency communication terminals. The service type refers to the classification based on the performance requirements and data characteristics of the communication services carried by the terminal, including eMBB services, uRLLC services, and mMTC services. Among them, eMBB services refer to consumer-grade communication services with "high data rate and large bandwidth transmission" as the core requirement, such as high-definition video playback and large file download. uRLLC services refer to industry-level key services with "extreme latency and extremely high reliability" as the core requirement, such as industrial control commands and vehicle networking collision alarm signals. mMTC services refer to IoT services with "massive device access and low power consumption and small data transmission" as the core requirement, such as periodic data reporting of smart meters, status synchronization of urban street lights, and sensor data acquisition.

[0052] S3: First, extract the number of users Yh from the target information segment, and determine the load status based on the number of users Yh. The load status includes high load, medium load and low load.

[0053] Furthermore, methods for determining load status include:

[0054] Extract basic network information of the communication area and set node thresholds Y1 and Y2. When Yh≤Y1, the load status in the target information segment is marked as low load. When Y1<Yh≤Y2, the load status is marked as medium load. When Yh>Y2, the load status is marked as high load. Y1<Y2, and the specific values ​​of node thresholds Y1 and Y2 are set by those skilled in the art based on the basic network information.

[0055] S4: Obtain the running data in the target information segment, classify the running data according to user type to obtain user type 1, user type 2 and user type 3, count the quantity in each user type to determine the number of users accessing each user type, then divide the number of users accessing each user type by the number of users Yh in the target information segment, and mark the calculation result as the user ratio coefficient, obtain the user ratio coefficient corresponding to each user type, identify the maximum value in the user ratio coefficient, and mark the user type corresponding to the maximum value as the key user information of the target information segment;

[0056] It should be further explained that user type 1, user type 2 and user type 3 correspond to high-consumption terminal users, low-energy-consumption terminal users and professional terminal users, respectively.

[0057] S5: Next, obtain the business type from the running data, process the business type according to the above method, obtain the business ratio coefficient of each business type, identify the maximum value among the business ratio coefficients, and mark the business type corresponding to the maximum value as key business information;

[0058] S6: Obtain the load status, key user information, and key business information of the target information segment, and recombine them to obtain the communication feature tags of the target information segment;

[0059] The remaining stage information is sequentially marked as target information segments and processed according to the above method to determine the communication feature label of each stage information.

[0060] Then, a one-way communication connection is established between the feature processing module and the frequency band analysis module, and the communication feature tags of the stage information are transmitted to the frequency band analysis module;

[0061] The frequency band analysis module receives and analyzes phase information and corresponding communication feature tags to determine the preferred frequency band for each independent time period. The specific methods for determining the preferred frequency band include:

[0062] Arbitrarily select a communication feature label b, obtain the independent time period corresponding to this communication feature label b, and mark it as the target analysis time period. Collect the network communication frequency bands that exist in the target analysis time period and mark them as frequency band i, i=1, 2, ..., and then obtain the standard operating parameters corresponding to the communication feature label b.

[0063] Let i=1, that is, obtain the communication operation parameter j in frequency band 1, where j represents different communication operation parameters. Furthermore, the communication operation parameters include operating power consumption, latency rate, transmission rate and error rate.

[0064] Using formula The communication operation parameter j is normalized to obtain the standardized operation processing parameter Dj. It should be further noted that when the communication operation parameter j is the transmission rate, then... ;

[0065] Based on the key communication requirements of communication feature tag b, set corresponding parameter ratios for communication operation parameter j. Then use the calculation formula The frequency band operating coefficients FXi are obtained, where J represents the total number of communication operating parameters;

[0066] It should be further explained that the parameter ratio The specific values ​​were obtained by those skilled in the art based on the key communication requirements of communication feature tag b and big data calculations;

[0067] The remaining frequency bands i are then processed in the same way described above to determine the frequency band operating coefficient FXi for each frequency band i.

[0068] Obtain the band operation coefficient FXI of each frequency band i under the communication feature label b, compare the band operation coefficient FXI, identify the maximum value of the band operation coefficient FXI, and mark the network communication frequency band corresponding to the frequency band i with the maximum value as the preferred frequency band of the communication feature label b;

[0069] The remaining communication feature tags are processed in accordance with the above method to determine the preferred frequency band for each communication feature tag;

[0070] Then, one-way communication connections are established between the frequency band analysis module and the user analysis module and the network conditioning module, respectively;

[0071] The user analysis module is used to perform inertial analysis on terminal users in the communication area to determine the set of inertial values ​​for each terminal user. The specific methods for determining the set of inertial values ​​include:

[0072] Select any terminal user in the power supply area and collect the request data volume of this terminal user. Visualize the request data volume. In this embodiment, the visualization is set as a curve, that is, set time as the horizontal axis and request data volume as the vertical axis to establish a two-dimensional coordinate system. Mark the request data volume of the terminal user in the two-dimensional coordinate system in chronological order and perform linear fitting to obtain the curve.

[0073] The requested data volume is divided into independent time periods. The requested data volume in each independent time period is marked as a local data segment. Then, the mean of each local data segment is calculated, and the mean calculation result is marked as the representative value of the request in this independent time period.

[0074] According to the periodic time, the representative request values ​​in the independent time period are grouped, and the grouped representative request values ​​are then arranged in chronological order to obtain a set of values, where the periodic time corresponds one-to-one with the set of values.

[0075] Select the representative value of the first position in all the numerical sets, and then use the mean processing method to calculate the mean of the representative value of the first position. Mark the result as the time period feature value. Calculate the time period feature values ​​of all positions in the numerical set according to the above method, integrate the time period feature values ​​of all positions into a set, and then determine the inertial numerical set of this terminal user.

[0076] The request data of all terminal users in the power supply area are processed in accordance with the above method to determine the inertial value set of each terminal user.

[0077] Then, a one-way communication connection is established between the user analysis module and the network regulation module, and the set of inertial values ​​of the end users is transmitted to the network regulation module;

[0078] The network adjustment module is used to identify the current time and collect real-time communication information. Then, it processes the real-time communication information, determines the current communication feature tag, and obtains the corresponding preferred frequency band based on the communication feature tag.

[0079] All terminal users are acquired, and based on the current time, the corresponding time period feature values ​​are extracted from the inertial value set. The time period feature values ​​of the terminal users are arranged in descending order to obtain the user sequence. Starting from the first user in the user sequence, the preferred frequency band is allocated first. After the channel allocation of the preferred frequency band is completed, the remaining terminal users in the user sequence are acquired and marked as low-power users.

[0080] Next, the total bandwidth resources of the preferred frequency band are identified, the bandwidth ratio occupied by the data requested by the allocated users is calculated, and the remaining bandwidth resources that can be carried are obtained. Without affecting the communication quality of the allocated users, the low-power users whose data request volume matches the remaining bandwidth resources are selected. Through time division multiplexing (TDM) or frequency division multiplexing (FDM) technology, the low-power users and the allocated users can share the remaining bandwidth resources of the preferred frequency band, while ensuring that the communication indicators of both parties meet the preset standards. This further improves the resource utilization rate of the preferred frequency band and avoids the idle waste of frequency band resources.

[0081] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. A dynamic spectrum allocation based wireless communication network resource optimization system, characterized by include: The network information acquisition module is used to collect basic network information of wireless communication networks; The feature processing module is used to divide the time of the communication area into several independent time periods, and then, based on the basic network information, collect and analyze the phase information in the independent time periods to determine the communication feature tags of the phase information. The frequency band analysis module is used to receive phase information and corresponding communication feature tags, analyze them, and determine the preferred frequency band for each independent time period. Methods for determining preferred frequency bands include: Select a communication feature label b, obtain the independent time period corresponding to this communication feature label b, and mark it as the target analysis time period. Collect the network communication frequency bands that exist in the target analysis time period and mark them as frequency band i, i=1, 2, ..., and then obtain the standard operating parameters corresponding to the communication feature label b. Let i=1, that is, obtain the communication operation parameter j in frequency band 1, where j represents different communication operation parameters, including operating power consumption, latency rate, transmission rate and error rate; The communication running parameter j is normalized by using the formula , to obtain the standardized running processing parameter Dj. When the communication running parameter j is the transmission rate, at this time ; Based on the key communication requirements of communication feature tag b, set corresponding parameter ratios for communication operation parameter j. Then use the calculation formula The frequency band operating coefficients FXi are obtained, where J represents the total number of communication operating parameters; The remaining frequency bands i are then processed in the same way described above to determine the frequency band operating coefficient FXi for each frequency band i. Obtain the band operation coefficient FXI of each frequency band i under the communication feature label b, compare the band operation coefficient FXI, identify the maximum value of the band operation coefficient FXI, and mark the network communication frequency band corresponding to the frequency band i with the maximum value as the preferred frequency band of the communication feature label b; The user analysis module is used to identify terminal users in the communication area, perform inertial analysis on the amount of data requested by terminal users, determine the representative value of the terminal user's request in each independent time period, and then determine the set of inertial values ​​of the terminal user based on the representative value of the request in each independent time period. Methods for determining the set of inertial values ​​include: Select any terminal user in the power supply area and collect the request data volume of this terminal user. Visualize the request data volume by setting time as the horizontal axis and request data volume as the vertical axis to establish a two-dimensional coordinate system. Mark the request data volume of the terminal user in the two-dimensional coordinate system in chronological order and perform linear fitting to obtain a curve. The requested data volume is divided into independent time periods. The requested data volume in each independent time period is marked as a local data segment. Then, the mean of each local data segment is calculated, and the mean calculation result is marked as the representative value of the request in this independent time period. According to the periodic time, the representative request values ​​in the independent time period are grouped, and the grouped representative request values ​​are then arranged in chronological order to obtain a set of values, where the periodic time corresponds one-to-one with the set of values. Select the representative request value of the first position in all the numerical sets, and then use the mean processing method to calculate the mean of the representative request value of the first position. Mark the result as the time period feature value. Calculate the time period feature values ​​of all positions in the numerical set in the same way, integrate the time period feature values ​​of all positions into a set, and then determine the inertial numerical set of this terminal user. The network adjustment module is used to identify the current time and determine the preferred frequency band. At the same time, based on the inertial value set, it determines the current time period characteristic value of the terminal user. Then, based on the total bandwidth resource of the preferred frequency band and the current time period characteristic value of the terminal user, it allocates the total bandwidth resource of the preferred frequency band in real time.

2. The system of claim 1, wherein, Methods for determining communication feature tags include: S1: Set the period time and unit time respectively, and divide the period time again according to the unit time to obtain several independent time periods. The period time and unit time are both time thresholds, and the period time is greater than the unit time. Collect communication information within the communication area, divide the communication information into independent time periods, and obtain phase information; S2: Sequentially mark the stage information as target information segments, and extract the running data from the target information segments respectively. The running data includes the number of users, user type and business type. S3: First, extract the number of users Yh from the target information segment, and determine the load status based on the number of users Yh. The load status includes high load, medium load and low load. S4: Obtain the running data in the target information segment, classify the running data according to user type to obtain user type 1, user type 2 and user type 3, count the quantity in each user type to determine the number of users accessing each user type, divide the number of users accessing each user type by the number of users Yh in the target information segment, and mark the calculation result as the user ratio coefficient, obtain the user ratio coefficient corresponding to each user type, identify the maximum value in the user ratio coefficient, and mark the user type corresponding to the maximum value as the key user information of the target information segment; S5: Next, obtain the business type from the running data, process the business type according to the above method, obtain the business ratio coefficient of each business type, identify the maximum value among the business ratio coefficients, and mark the business type corresponding to the maximum value as key business information; S6: Obtain the load status, key user information, and key service information of the target information segment, and recombine them to obtain the communication feature tag of the target information segment.

3. A dynamic spectrum allocation based wireless communication network resource optimization system according to claim 2, wherein, User type refers to the classification based on the hardware attributes, power consumption level, and resource consumption capacity of terminal devices. It includes high-consumption terminal users, low-power terminal users, and professional terminal users. High-consumption terminal users refer to users whose hardware supports high data transmission and whose own power consumption tolerance is high. Low-power terminal users refer to users whose terminals rely on low power consumption and mainly transmit small amounts of data. Professional terminal users refer to users whose terminals carry critical business in specific industries and have extreme requirements for communication reliability or latency.

4. The system of claim 2, wherein, Service type refers to the classification based on the performance requirements and data characteristics of the communication services carried by the terminal, including eMBB services, uRLLC services, and mMTC services. Among them, eMBB services refer to consumer-grade communication services, uRLLC services refer to industry-level critical services, and mMTC services refer to Internet of Things (IoT) services.

5. The system of claim 2, wherein, Methods for determining load status include: Extract the basic network information of the communication area and set node thresholds Y1 and Y2. When Yh≤Y1, the load status in the target information segment is marked as low load. When Y1<Yh≤Y2, the load status is marked as medium load. When Yh>Y2, the load status is marked as high load. Where Y1<Y2.

6. The system of claim 2, wherein, User type 1, user type 2 and user type 3 correspond to high-consumption terminal users, low-energy-consumption terminal users and professional terminal users, respectively.

7. The system of claim 1, wherein, Methods for real-time allocation of total bandwidth resources in preferred frequency bands include: Collect real-time communication information, process the real-time communication information, determine the current communication feature tags, and then obtain the corresponding preferred frequency band based on the communication feature tags; All terminal users are acquired, and based on the current time, the corresponding time period feature values ​​are extracted from the inertial value set. The time period feature values ​​of the terminal users are arranged in descending order to obtain the user sequence. Starting from the first user in the user sequence, the preferred frequency band is allocated first. After the channel allocation of the preferred frequency band is completed, the remaining terminal users in the user sequence are acquired and marked as low-power users. Identify the total bandwidth resources of the preferred frequency band, calculate the bandwidth ratio occupied by the data requested by the allocated users, obtain the remaining bandwidth resources that can be carried at present, and select the low-power users whose data requested volume matches the remaining bandwidth resources without affecting the communication quality of the allocated users. Through time division multiplexing or frequency division multiplexing technology, the low-power users can share the remaining bandwidth resources of the preferred frequency band with the allocated users.

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