Optimization method and system for access of RedCap terminal to 5G network

Abstract

The invention relates to the technical field of wireless communication optimization, in particular to an optimization method and system for accessing a RedCap terminal to a 5G network, and the method comprises the steps: collecting data from the RedCap terminal, extracting frequency spectrum state information in the process of accessing the terminal to the 5G network, dividing channel states into a plurality of channel state categories, calculating the transition probability between the channel states, and generating a dynamic transition probability matrix. According to the method, data are collected from a RedCap terminal, frequency spectrum state information is extracted, channel states are classified innovatively, and a dynamic transition probability matrix construction method is combined, so that the change rule of the channel states is effectively described. Through frequency statistics and co-occurrence relation analysis of channel state categories, channel allocation is more accurate, and a channel allocation strategy can be adjusted according to dynamic changes, so that flexibility and high efficiency of resource scheduling are enhanced.

Description

Technical Field

[0001] The present invention relates to the technical field of wireless communication optimization, and in particular, to an optimization method and system for RedCap terminals to access the 5G network. Background Art

[0002] The technical field of wireless communication optimization involves improving the performance of wireless communication networks and the efficiency of resource utilization, covering aspects such as network planning, signal transmission optimization, spectrum resource management, and device access control. The purpose of this field is to enhance the stability, coverage, transmission rate, and user experience of wireless networks through technical means, and it is widely applied in 4G and 5G to meet the increasing data transmission requirements and the number of device accesses.

[0003] Among them, the optimization method for RedCap terminals to access the 5G network mainly studies how to improve the access efficiency and communication performance of lightweight terminals (such as RedCap devices) in the 5G network environment. This method aims to solve problems such as insufficient resource allocation, signal interference, and transmission delay that lightweight terminals may face in high-density network scenarios, thereby enhancing the practical application effect of RedCap devices in fields such as the Internet of Things and industrial automation.

[0004] Existing technologies are difficult to effectively characterize the changing characteristics of the channel state in high-density network scenarios. The classification and dynamic transfer characteristics of channel types have not been deeply studied, resulting in the difficulty of flexible channel resource allocation to cope with the dynamic changes of signal interference and network load. For example, when the signal interference in the network changes frequently, existing technologies often cannot accurately predict the future distribution of the channel state, resulting in the lag of resource allocation. In the resource matching process, existing technologies are difficult to consider signal strength and interference probability together, and it is easy to assign incorrect priorities in scenarios with low interference but insufficient signal strength, thus affecting communication quality. In terms of the matching between spectrum blocks and load, existing technologies have insufficient optimization of path allocation and lack of effective balance of path length and resource weight, which easily leads to a decrease in resource utilization efficiency. For example, in multi-task scenarios, existing methods may choose long paths with low resource weight, resulting in resource waste. In task access management, existing technologies have limited real-time adjustment ability for channels and cannot dynamically optimize the resource distribution of the main control channel and the auxiliary channel in the case of uneven task distribution, which easily causes unreasonable bandwidth allocation and increased task processing delay fluctuations. Summary of the Invention

[0005] To solve the technical problems existing in the prior art, embodiments of the present invention provide an optimization method and system for RedCap terminals to access the 5G network. The technical solutions are as follows: An optimization method for RedCap terminals to access the 5G network includes the following steps: S1: Collect data from the RedCap terminal, extract the spectrum status information during the process of the terminal accessing the 5G network, divide the channel status into several channel status categories, calculate the transition probabilities between the channel statuses, and generate a dynamic transition probability matrix; S2: Based on the data in the dynamic transition probability matrix, select the channel with the lowest interference probability and the highest signal strength when the RedCap terminal accesses the 5G network as the target channel, and generate a channel priority allocation result; S3: Based on the channel priority allocation result, extract the spectrum block and load distribution requirements therefrom, optimize the allocation path between the spectrum block and the load distribution, divide multiple priority queues, and associate the priority queues with the resource information in the allocation path to generate a cross-layer priority matching result; S4: Based on the cross-layer priority matching result, monitor the access status of the terminal tasks, perform real-time analysis on the signal strength and interference probability in the task access status, and make real-time adjustments to the task distribution of the main control channel and the auxiliary channel according to the analysis results to generate a hierarchical access result of the main control and auxiliary channels; S5: Based on the hierarchical access result of the main control and auxiliary channels, classify the priority segments according to the delay sensitivity and throughput requirements, and generate an optimized result of dynamic bandwidth allocation by dynamically optimizing the bandwidth resource allocation of the priority segments.

[0006] The improvements of the present invention are as follows. The dynamic transition probability matrix includes the transition probabilities of the channel status categories, the signal strength ranges corresponding to the channel status categories, and the interference probability ranges corresponding to the channel status categories. The channel priority allocation result includes the target channel number, the channel priority sorting, and the available time window corresponding to the channel. The cross-layer priority matching result includes the priority queue classification, the optimized parameters of the resource allocation path, and the relevance information of the load distribution to the channel. The hierarchical access result of the main control and auxiliary channels includes the task distribution status of the main control channel, the task distribution status of the auxiliary channel, and the real-time channel load balancing parameters. The optimized result of dynamic bandwidth allocation includes the bandwidth allocation ratio of the priority segments, the dynamic bandwidth adjustment parameters, and the resource allocation status information of the priority segments.

[0007] The improvements of the present invention are as follows. The specific steps of collecting data from the RedCap terminal, extracting the spectrum status information during the process of the terminal accessing the 5G network, dividing the channel status into several channel status categories, calculating the transition probabilities between the channel statuses, and generating a dynamic transition probability matrix are as follows: S101: Based on the RedCap terminal signal strength, interference probability, and occupancy data, according to the acquisition standard of the channel status information, group the signal strength data and label the strength levels, and divide the data ranges of the interference probability and occupancy data to generate a channel status classification data set; S102: Based on the channel state classification data set, statistically analyze the occurrence frequency of each channel state category, sort the category frequencies in descending order of proportion, and statistically analyze the co-occurrence relationship between each channel state category to generate a channel state category statistical list; S103: According to the time series order of the channel state category statistical list, calculate the transition probability from each channel state category to other categories, and dynamically adjust it through the combined weight of signal strength, interference probability, and occupancy to generate a dynamic transition probability matrix.

[0008] The present invention is improved in that for calculating the transition probability from each channel state category to other categories, the formula is used: ; Obtain the transition probability from category i to category j ; where, is the actual occurrence times of category i transitioning to category j, is the total number of times category i transitions to all categories, is the signal strength normalization value of category i, and the calculation formula is: , is the signal strength of category i, and are the maximum and minimum signal strengths among all categories.

[0009] The present invention is improved in that based on the data in the dynamic transition probability matrix, the specific steps for selecting the channel with the lowest interference probability and the highest signal strength as the target channel when the RedCap terminal accesses the 5G network to generate the channel priority allocation result are as follows: S201: Based on the dynamic transition probability matrix, combined with the channel state data at the current moment, calculate the channel state distribution probability corresponding to each future time step, extract and record the channel state probabilities of each time step to generate a channel state prediction distribution list; S202: Based on the channel state prediction distribution list, screen the channel states of future time steps according to the condition that the signal strength value is in the upper limit range and the interference probability value is in the lower limit range to generate a channel state preferred distribution list; S203: Based on the channel state preferred distribution list, combined with the resource allocation requirements of the RedCap terminal, establish a corresponding relationship according to the channel priority order and the terminal requirements to generate a channel priority allocation result.

[0010] The present invention is improved in that for calculating the channel state distribution probability corresponding to each future time step, the formula is used: ; Obtain the next moment of the time step Channel state Probability distribution of ; Wherein is the time step Channel state Probability distribution of is an element in the dynamic transition probability matrix, indicating that the channel state transitions to the next channel state Probability of is the total number of channel states.

[0011] The present invention is improved as follows: Based on the channel priority allocation result, extract the spectrum block and load distribution requirements therefrom, optimize the allocation path between the spectrum block and the load distribution, and divide multiple priority queues, associate the priority queues with the resource information in the allocation path, and generate the cross-layer priority matching result. The specific steps are as follows: S301: Based on the channel priority allocation result, extract the distribution information of the spectrum block and the load demand information and analyze their adaptability, set the edge weight between the two according to the value of the adaptability, and generate a spectrum block and load edge weight class list; S302: Based on the spectrum block and load edge weight class list, perform a combined analysis on all spectrum block allocation paths, screen the allocation path with the shortest path length and the highest total weight value, and generate an optimal resource allocation path; S303: Based on the optimal resource allocation path, divide multiple priority queues according to the corresponding relationship between the spectrum block and the load in the allocation path, associate the priority queues with the resource allocation information in the path, and generate a cross-layer priority matching result.

[0012] The present invention is improved as follows: Based on the cross-layer priority matching result, monitor the access status of the terminal task, perform real-time analysis on the signal strength and interference probability in the task access status, and perform real-time adjustment on the task distribution of the main control channel and the auxiliary channel according to the analysis result, and generate the main control and auxiliary channel hierarchical access result. The specific steps are as follows: S401: Based on the cross-layer priority matching result, extract the resource allocation information for the terminal to access the 5G network, monitor the access status of the terminal task in real time, analyze the signal strength and interference probability of the accessed task, and determine whether it exceeds the preset signal strength range, and generate a task access status analysis result; S402: Based on the analysis result of the task access status, reassign the tasks with signal strength lower than the preset signal strength range or interference probability higher than the preset signal strength range to the auxiliary channel, maintain the tasks within the preset signal strength range on the primary control channel, record the task distribution of the primary control channel and the auxiliary channel, and generate a distribution table of the primary control and auxiliary channels; S403: Based on the distribution table of the primary control and auxiliary channels, adjust the real-time load conditions of the primary control channel and the auxiliary channel, re-establish hierarchical access and perform initialization allocation of corresponding resources, and generate a hierarchical access result of the primary control and auxiliary channels.

[0013] The improvement of the present invention is that, based on the hierarchical access result of the primary control and auxiliary channels, classify the priority segments according to the delay sensitivity and throughput requirements, and dynamically optimize the bandwidth resource allocation of the priority segments. The specific steps for generating the optimized result of dynamic bandwidth allocation are as follows: S501: Based on the hierarchical access result of the primary control and auxiliary channels, extract the priority segment data of the hierarchical access RedCap terminals, classify the priority segments according to the numerical intervals of the delay sensitivity and throughput requirements, and generate a priority segment classification result; S502: Based on the priority segment classification result, compare the actual values of the delay sensitivity and throughput requirements of the priority segments with the preset delay threshold range and throughput requirement standard, and perform refined adjustment of the corresponding bandwidth resources according to the comparison result to generate a bandwidth allocation list for the priority segments; S503: Based on the bandwidth allocation list of the priority segments, combined with the real-time network load monitoring data, dynamically adjust the segmented allocation parameters of each priority segment according to the load conditions, optimize the allocation ratio and growth rate of the bandwidth resources, and generate an optimized result of dynamic bandwidth allocation.

[0014] An optimization system for RedCap terminals to access the 5G network, the system includes: The channel status analysis module extracts channel status information based on the RedCap terminal spectrum status data, classifies the channel status categories, counts the category frequencies and transition relationships, calculates the channel status transition probability, and generates a dynamic transition probability matrix; The channel preference and allocation module selects the target channel with the lowest interference probability and the highest signal strength based on the dynamic transition probability matrix, calculates the fitness of the spectrum block and the load distribution, optimizes the allocation path, divides the priority queue and associates the resource information, and generates a cross-layer priority matching result; The task access optimization module monitors the task access status based on the cross-layer priority matching result, analyzes the signal strength and interference probability, adjusts the tasks beyond the range to the auxiliary channel, optimizes the task distribution of the primary control and auxiliary channels, and generates a hierarchical access result of the primary control and auxiliary channels; The bandwidth dynamic allocation module dynamically adjusts the bandwidth allocation strategy based on the hierarchical access results of the primary and auxiliary channels, classifies priority segments according to delay sensitivity and throughput requirements, optimizes the segmented allocation parameters in combination with the real-time load, and generates an optimized result of bandwidth dynamic allocation.

[0015] The beneficial effects brought by the technical solutions provided in the embodiments of the present invention at least include: By collecting data from RedCap terminals and extracting spectrum status information, the channel status is innovatively classified, and combined with the method of constructing a dynamic transition probability matrix, the change law of the channel status is effectively characterized. The frequency statistics and co-occurrence relationship analysis of channel status categories make channel allocation more accurate, and can adjust the channel allocation strategy according to dynamic changes, thereby enhancing the flexibility and efficiency of resource scheduling. In the process of channel resource allocation, using the upper and lower limit conditions of signal strength and interference probability, combined with dynamic probability to predict the future channel status distribution, the generation of the optimal distribution is completed, and at the same time, it is matched with the terminal requirements to form a priority allocation strategy, significantly improving the utilization efficiency of channel resources and reducing the interference impact. In the optimization of spectrum block and load allocation, the optimal resource allocation path is selected through fitness analysis and path optimization, further improving the resource allocation efficiency and load balancing ability. In task access management, based on real-time monitoring of signal strength and interference probability, the task distribution of the primary channel and the auxiliary channel is dynamically adjusted, and at the same time, the bandwidth allocation is optimized in combination with delay sensitivity and throughput requirements, realizing the dynamic adjustment and hierarchical management of bandwidth resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0017] Figure 1 It is the flowchart of the method of the present invention; Figure 2 It is the schematic diagram of the detailed process of step S1 of the present invention; Figure 3 It is the schematic diagram of the detailed process of step S2 of the present invention; Figure 4 It is the schematic diagram of the detailed process of step S3 of the present invention; Figure 5 It is the schematic diagram of the detailed process of step S4 of the present invention; Figure 6 It is the schematic diagram of the detailed process of step S5 of the present invention; Figure 7 It is the system module diagram of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0018] The technical solution of the present invention is described below in conjunction with the accompanying drawings.

[0019] In the embodiments of the present invention, words such as "exemplarily" and "for example" are used to indicate examples, illustrations, or explanations. Any embodiment or design described as an "exemplary" in the present invention should not be interpreted as being preferred or advantageous over other embodiments or designs. Rather, the use of the word "exemplary" is intended to present concepts in a concrete manner. Furthermore, in the embodiments of the present invention, "and / or" can mean both or either of the two.

[0020] In the embodiments of the present invention, sometimes a subscript such as W1 may be written as a non-subscript such as W1. When the difference is not emphasized, the meanings to be expressed are the same.

[0021] In order to make the technical problems, technical solutions and advantages to be solved by the present invention more clear, a detailed description will be given below with reference to the accompanying drawings and specific embodiments.

[0022] See also Figure 1 , an embodiment of the present invention provides an optimization method for a RedCap terminal to access a 5G network, comprising the following steps: S1: Collect data from RedCap terminals, extract spectrum status information when the terminals access the 5G network, divide the channel status into several channel state categories, calculate the transition probability between channel states, and generate a dynamic transition probability matrix; S2: Based on the data in the dynamic transition probability matrix, the channel with the lowest interference probability and the highest signal strength when the RedCap terminal accesses the 5G network is selected as the target channel, and the channel priority allocation result is generated; S3: Based on the channel priority allocation results, spectrum blocks and load distribution requirements are extracted, the allocation path between the spectrum blocks and load distribution is optimized, multiple priority queues are divided, and the priority queues are associated with the resource information in the allocation path to generate cross-layer priority matching results. S4: Based on the cross-layer priority matching results, monitor the access status of terminal tasks, perform real-time analysis of the signal strength and interference probability of the task access status, adjust the task distribution of the primary and secondary channels in real time based on the analysis results, and generate the hierarchical access results of the primary and secondary channels; S5: Based on the hierarchical access results of the primary and secondary channels, the priority segments are classified according to delay sensitivity and throughput requirements. By dynamically optimizing the bandwidth resource allocation of the priority segments, the bandwidth dynamic allocation optimization results are generated.

[0023] The dynamic transition probability matrix includes the transition probabilities of channel state categories, the signal strength ranges corresponding to the channel state categories, and the interference probability ranges corresponding to the channel state categories. The channel priority allocation result includes the target channel number, the channel priority ranking, and the available time window corresponding to the channel. The cross-layer priority matching result includes the priority queue classification, the resource allocation path optimization parameters, and the correlation information of the load distribution to the channel. The hierarchical access result of the primary and secondary channels includes the task distribution status of the primary channel, the task distribution status of the secondary channel, and the real-time channel load balancing parameters. The bandwidth dynamic allocation optimization result includes the bandwidth allocation ratio of the priority segments, the bandwidth dynamic adjustment parameters, and the resource allocation status information of the priority segments.

[0024] Please refer to Figure 2 , collect data from RedCap terminals, extract the spectrum state information during the process of the terminals accessing the 5G network, divide the channel states into several channel state categories, calculate the transition probabilities between the channel states, and the specific steps for generating the dynamic transition probability matrix are as follows: S101: Based on the RedCap terminal signal strength, interference probability, and occupancy data, according to the acquisition standard of channel state information, group the signal strength data and label the strength levels, and divide the data ranges of the interference probability and occupancy data to generate a channel state classification data set; First, collect the signal strength sample data. Based on actual tests, obtain multiple signal strength sample values. For example, the signal strengths measured during terminal access in the test environment are 40, 60, 80, 90, etc. Then calculate the distribution range of the signal strength samples, divide the intervals through distribution statistical methods. For example, use the quantile method to divide the signal strength into weak signals, medium signals, and strong signals, corresponding to the intervals 0 - 50, 50 - 75, and 75 - 100 respectively. Subsequently, divide the interference probability data. By monitoring the environmental interference situation, obtain the probability values of interference events. For example, the probabilities of interference are 10%, 30%, and 60% respectively, corresponding to the interference levels of low, medium, and high. Finally, process the occupancy data. By monitoring the channel occupancy rate when the terminal is connected, obtain the occupancy rate intervals. For example, the occupancy rates within the statistical time period are 20%, 50%, and 80% respectively, corresponding to low occupancy, medium occupancy, and high occupancy. Combining the above classification methods, generate a channel state classification data set including signal strength grouping, interference probability levels, and occupancy levels.

[0025] S102: Based on the channel state classification data set, statistically analyze the occurrence frequencies of each channel state category, sort the category frequencies according to the proportion from high to low, and statistically analyze the co-occurrence relationships between each channel state category to generate a channel state category statistical list; Record the names and frequencies of all channel state categories as basic data. By parsing the channel state data in the time series and using the frequency statistics method, obtain the occurrence times of each category. For example, within a one-hour sampling period, the occurrence times of channel states 1, 2, and 3 are 30, 20, and 10 times respectively. Subsequently, convert the occurrence frequencies into percentage form. For example, the occurrence frequency of category 1 is 50%, category 2 is 33.3%, and category 3 is 16.7%. Sort them in descending order of frequency. Then calculate the co-occurrence relationship between channel state categories, and perform correlation analysis on the channel state data through the co-occurrence matrix. The construction method of the co-occurrence matrix is to record the consecutive occurrence frequencies of any two channel states in the time series. For example, the consecutive co-occurrence times of category 1 and category 2 are 10 times, and the co-occurrence times of category 1 and category 3 are 5 times. Finally, generate a frequency and co-occurrence relationship list of channel state categories based on these statistical results.

[0026] S103: Calculate the transition probability from each channel state category to other categories in the order of the time series, and dynamically adjust it through the combined weights of signal strength, interference probability, and occupancy to generate a dynamic transition probability matrix; For calculating the transition probability from each channel state category to other categories, use the formula: ; Obtain the transition probability from category i to category j ; where, is the actual occurrence times of category i transitioning to category j, statistically based on the time series data. The specific statistical method is to traverse adjacent data pairs in the time series. For example, if the time series is [1, 2, 1, 3], the number of times category 1 transitions to category 2 is 1, and the number of times category 2 transitions to category 1 is 0. is the total number of times category i transitions to all categories, obtained by accumulating the frequencies of category i transitioning to other categories in the time series. For example, the total number of times category 1 transitions to category 2 and category 3 is ; is the signal strength normalization value of category i, reflecting the relative strength of the signal strength corresponding to category i and the signal strengths of all categories. The normalization processing method is: ; is the signal strength of category i, obtained by measuring the signal power when the RedCap terminal accesses through the monitoring device. For example, the signal strength of category 1 measured by the signal receiver is 70 dBm, category 2 is 50 dBm, and category 3 is 90 dBm. and are the maximum and minimum signal strengths among all categories, respectively obtained through statistical analysis of the time series data.

[0027] Collect channel state category time series data. For example, a certain time series is [1, 2, 1, 3, 2, 1]. Record the number of transitions from category 1 to 2, 1 to 3, 2 to 1, 2 to 3, etc. respectively. According to the sequence statistics, it is obtained that: At the same time, record the signal strength range corresponding to each category. For example, the signal strength of category 1 is 70 dBm, the signal strength of category 2 is 50 dBm, the signal strength of category 3 is 90 dBm. The maximum signal strength is 90 dBm, and the minimum signal strength is 50 dBm. Calculate the signal strength normalization value of each category according to the formula: ; Substitute the signal strength normalization value into the improved transition probability formula. For example, the transition probability from category 1 to category 2 is: ; The transition probability from category 1 to category 3 is: ; Finally, organize all the transition probabilities into a dynamic transition probability matrix. For example: ; The results show that each value in the matrix represents the probability relationship of a certain category transferring to other categories. For example, 0.666 in the matrix represents the probability that category 1 transfers to category 2 is 0.666. Combining with historical signal strength data can verify the accuracy of the calculation results. For example, comparing the actual signal strength measurement values of category 1 and category 2, the results show that the transfer probability of the category with stronger signal is relatively larger. This dynamic transition probability matrix can dynamically adjust and optimize the calculation results by combining the normalization value of signal strength, improve the channel resource allocation efficiency of RedCap terminals accessing the 5G network, enhance the access stability, and thus provide a reliable reference basis for network optimization.

[0028] Please refer to Figure 3 , based on the data in the dynamic transition probability matrix, select the channel with the lowest interference probability and the highest signal strength as the target channel when the RedCap terminal accesses the 5G network. The specific steps to generate the channel priority allocation result are as follows: S201: Based on the dynamic transition probability matrix, combined with the channel state data at the current moment, calculate the channel state distribution probability corresponding to each future time step, extract and record the channel state probability of each time step, and generate a channel state prediction distribution list; For calculating the channel state distribution probability corresponding to each future time step, use the formula: ; Obtain the probability distribution of the next moment of the channel state at time step ; in, is the time step Channel Status The probability distribution of the channel state at the current moment The probability value is directly collected based on the current channel state statistics. For example, it is obtained by recording the number of times the channel state appears in a time window and normalizing it. Assuming that the time window is 10 seconds and the number of times states 1, 2, and 3 appear is 6, 3, and 1, the probability distribution is , is an element in the dynamic transition probability matrix, representing the channel state Transition to the next channel state The probability of is the total number of channel states, representing the full range of channel states.

[0029] Dynamic transition probability matrix Based on the above statistical analysis, for example, the matrix is: ; Current moment The channel state probability distribution For vectors, for example: ; Calculate time steps state The distribution probability of: ; Enter the value: ; Calculate time steps state The distribution probability of: ; Enter the value: ; Calculate time steps state The distribution probability of: ; Enter the value: ; Finally, the time step The channel state probability distribution vector is: ; The results show that by calculating the dynamic transition probability matrix, the distribution probability of the channel state at future moments can be predicted. For example, the predicted probability of state 1 is 0.45. Comparing with the historical state distribution can verify the accuracy of the transition matrix, and this prediction result provides an important basis for subsequent channel allocation optimization.

[0030] S202: Based on the predicted distribution list of channel states, screen the channel states at future time steps according to the condition that the signal strength value is within the upper limit range and the interference probability value is within the lower limit range, and generate a preferred distribution list of channel states. Extract the signal strength values and interference probability values corresponding to each future time step through the predicted distribution list of channel states. The specific operations include extracting the signal strength and interference probability parameters of each channel state from the predicted distribution data. For example, the signal strength data at future moments are recorded as 60 dBm, 80 dBm, and 95 dBm, and the interference probabilities are 20%, 5%, and 10% respectively. Compare and screen each channel state item by item according to the set conditions, mark the channel states with a signal strength higher than 75 dBm and an interference probability lower than 10% as preferred channels, and further check the occupancy data to verify the availability of the channel states. For example, eliminate the channel states with a channel occupancy rate higher than 80%, and screen out the channel states with a signal strength within the range, an interference probability within the range, and an occupancy rate meeting the conditions. Finally, generate a preferred distribution list of channel states.

[0031] S203: Based on the preferred distribution list of channel states, combined with the resource allocation requirements of RedCap terminals, establish a corresponding relationship according to the priority order of channels and terminal requirements, and generate the channel priority allocation result. Combined with the resource allocation requirements of RedCap terminals, extract the parameter data of terminal resource requirements, such as bandwidth requirements, latency requirements, and access signal strength, etc. The specific operation is to compare the actual values of RedCap terminal resource requirements with the preferred distribution of channel states one by one. For example, the bandwidth required by the terminal is 50 Mbps, and the latency requirement is less than 20 ms. Obtain the bandwidth and latency data of the preferred channels as 60 Mbps and 15 ms respectively. Align these channel state parameters with the terminal requirements, and sort according to the channel priority order. For example, preferentially allocate the channel states that meet the requirements and sort them from high to low according to the performance parameters of bandwidth and latency, and establish the corresponding relationship between terminal requirements and channel states in turn. Finally, form the channel priority allocation result and record the relevant parameters for subsequent verification and optimization.

[0032] Please refer to Figure 4 , based on the channel priority allocation result, extract the spectrum block and load distribution requirements therefrom, optimize the allocation path between the spectrum block and the load distribution, and divide multiple priority queues, associate the priority queues with the resource information in the allocation path, and the specific steps to generate the cross-layer priority matching result are as follows: S301: Based on the channel priority allocation result, extract the distribution information and load demand information of the spectrum blocks, analyze their adaptability, set the edge weights between the two according to the value of the adaptability, and generate a list of spectrum block and load edge weight classes; Record information such as the center frequency, bandwidth, and occupancy duration of each spectrum block through a monitoring device. For example, the center frequency of the spectrum block is 2.4 GHz, the bandwidth is 20 MHz, and the occupancy duration is 5 ms. At the same time, obtain the information of the load demand, including the bandwidth demand, data transmission delay, and load size. For example, the load bandwidth demand is 15 MHz, the data transmission delay is 3 ms, and the load size is 5 MB. Conduct an adaptability analysis on the two sets of information. Obtain the adaptability parameters by comparing the difference value between the bandwidth of the spectrum block and the load bandwidth demand and the overlap degree between the occupancy duration and the load transmission duration. Set the edge weights between the spectrum block and the load according to the value of the adaptability. Organize the edge weight values of each spectrum block and the load into a list of edge weight classes, and record the adaptation information and weight values for subsequent path analysis.

[0033] S302: Based on the list of spectrum block and load edge weight classes, conduct a combined analysis of the allocation paths for all spectrum blocks, screen the allocation path with the shortest path length and the highest total weight value, and generate an optimal resource allocation path; Take the spectrum block numbers in the list and their corresponding edge weight values, combine the paths of all spectrum blocks through the path analysis method in graph theory. For example, use the shortest path analysis method to traverse the paths of different spectrum block combinations, record the length and total weight value of each path, define the path length as the number of spectrum blocks in the path, and define the total weight value as the sum of all edge weight values in the path. For example, path 1 contains spectrum blocks 1, 3, and 5, the path length is 3, and the total weight value is 8.5. Path 2 contains spectrum blocks 2 and 4, the path length is 2, and the total weight value is 7.2. Sort all paths according to the conditions of the shortest path length and the highest total weight value, screen out path 2 as the optimal resource allocation path, and record the path as the sequence of spectrum block numbers for subsequent operations.

[0034] S303: Based on the optimal resource allocation path, divide multiple priority queues according to the corresponding relationship between the spectrum blocks and the load in the allocation path, associate the priority queues with the resource allocation information in the path, and generate a cross-layer priority matching result; According to the correspondence between the spectrum blocks and the load in the path, obtain parameters such as the weight value, bandwidth, and delay of each spectrum block. Sort the weight values in descending order and divide them into multiple priority queues. For example, the high-priority queue contains spectrum blocks with weight values of 6.5 and 5.8, and the low-priority queue contains spectrum blocks with weight values of 3.5 and 2.8. Associate the spectrum blocks in the priority queues with the load requirements. By screening the bandwidth requirements, delay requirements, and size of the load, allocate the high-priority queue to the load with higher bandwidth requirements and lower delay requirements, and allocate the low-priority queue to the load with lower bandwidth and delay requirements. Associate the final priority queue with the spectrum blocks of the resource allocation path to form a cross-layer priority matching result for subsequent spectrum resource allocation and optimization operations.

[0035] Please refer to Figure 5 , based on the cross-layer priority matching result, monitor the access status of the terminal tasks, perform real-time analysis on the signal strength and interference probability in the task access status, and make real-time adjustments to the task distribution between the primary control channel and the auxiliary channel according to the analysis results. The specific steps for generating the hierarchical access result of the primary control and auxiliary channels are as follows: S401: Based on the cross-layer priority matching result, extract the resource allocation information for the terminal to access the 5G network, monitor the access status of the terminal tasks in real time, analyze the signal strength and interference probability of the accessed tasks, determine whether it exceeds the preset signal strength range, and generate an analysis result of the task access status; Extract the resource allocation information for the terminal to access the 5G network, monitor the access status of the terminal tasks in real time, analyze the signal strength and interference probability of the accessed tasks. By recording the real-time signal strength and interference probability data of the terminal access, such as the signal strength is -75dBm and the interference probability is 20%, compare the signal strength with the preset signal range (such as -80dBm to -50dBm), and at the same time analyze whether the interference probability exceeds the set threshold (such as 10%). Determine whether the task access status is within the normal range, record the data points of the signal strength and interference probability, and analyze the reasons for exceeding the range, such as counting the number of tasks exceeding the range, the exceeding amplitude, and its impact on the task access quality, and generate an analysis result of the task access status, including the status classification (normal or abnormal) of the accessed tasks and their signal interference characteristics.

[0036] S402: Based on the analysis result of the task access status, reallocate the tasks with signal strength lower than the preset signal strength range or interference probability higher than the preset signal strength range to the auxiliary channel, maintain the tasks within the preset signal strength range on the primary control channel, record the task distribution between the primary control channel and the auxiliary channel, and generate a distribution table of the primary control and auxiliary channels; Tasks with signal strength below the preset signal strength range or interference probability higher than the preset threshold are reassigned to the auxiliary channel, and tasks within the preset signal strength range are maintained on the primary control channel. The channel allocation information is recorded through a real-time allocation table. First, tasks that meet the conditions of signal strength and interference probability are screened out and assigned to the primary control channel. For example, Task A has a signal strength of -65 dBm and an interference probability of 8%, and it is assigned to the primary control channel. At the same time, tasks with signal strength below the range or interference probability higher than the threshold are screened out. For example, Task B has a signal strength of -85 dBm or an interference probability of 15%, and it is assigned to the auxiliary channel. The task distribution information of the primary control channel and the auxiliary channel is recorded, including the task number, signal strength, interference probability, and the assigned channel number, to generate a task distribution table for the primary control and auxiliary channels, which serves as the basic data for subsequent channel resource allocation.

[0037] S403: Based on the distribution table of the primary control and auxiliary channels, adjust the real-time load conditions of the primary control channel and the auxiliary channel, re-establish hierarchical access, and perform initial allocation of corresponding resources to generate the hierarchical access result of the primary control and auxiliary channels; Adjust the real-time load conditions of the primary control channel and the auxiliary channel. Combining the task distribution information and the channel load statistical data, re-establish the channel architecture of hierarchical access, and divide the channel load information into three levels: high, medium, and low. Among them, the high-load channel corresponds to the channel with the number of tasks exceeding 80% and the bandwidth utilization rate exceeding 75%. The medium-load channel corresponds to the channel with the number of tasks between 50% - 80% and the bandwidth utilization rate between 50% - 75%. The low-load channel corresponds to the channel with the number of tasks below 50% and the bandwidth utilization rate below 50%. Adjust the load of the auxiliary channel to balance the task distribution. At the same time, perform initial allocation of channel resources according to the principle of hierarchical access. For example, the high-load channel is allocated more bandwidth resources, the medium-load channel is allocated medium bandwidth resources, and the low-load channel is allocated the least bandwidth resources. Record the load tasks and resource allocation information of each layer of access channels to generate the hierarchical access result of the primary control and auxiliary channels.

[0038] Please refer to Figure 6 , based on the hierarchical access result of the primary control and auxiliary channels, classify the priority segments according to the delay sensitivity and throughput requirements. The specific steps for dynamically optimizing the bandwidth resource allocation of the priority segments to generate the optimized result of bandwidth dynamic allocation are as follows: S501: Based on the hierarchical access result of the primary control and auxiliary channels, extract the priority segment data of the hierarchical access RedCap terminals, classify the priority segments according to the numerical intervals of delay sensitivity and throughput requirements, and generate the priority segment classification result; Extract the priority segment data of the hierarchical access RedCap terminal, analyze the delay sensitivity and throughput requirements in the priority segment, record the actual delay value and throughput requirement value of each priority segment. For example, the delay values are 5ms, 15ms, and 50ms respectively, and the throughput requirements are 100Mbps, 50Mbps, and 10Mbps respectively. Divide the delay sensitivity into three intervals: high, medium, and low. Among them, high delay sensitivity corresponds to a delay value less than 10ms, medium delay sensitivity corresponds to a delay value between 10ms and 30ms, and low delay sensitivity corresponds to a delay value greater than 30ms. At the same time, divide the throughput requirement into three intervals: high, medium, and low. Among them, high throughput requirement corresponds to a throughput greater than 75Mbps, medium throughput requirement corresponds to a throughput between 25Mbps and 75Mbps, and low throughput requirement corresponds to a throughput less than 25Mbps. Classify the priority segment data according to the above interval criteria, and record the classification results for subsequent resource allocation optimization analysis to generate the priority segment classification result.

[0039] S502: Based on the priority segment classification result, compare the actual values of the delay sensitivity and throughput requirement of the priority segment with the preset delay threshold range and throughput requirement standard, and make corresponding refined adjustments to the bandwidth resources according to the comparison results to generate the priority segment bandwidth allocation list; Compare the actual values of the delay sensitivity and throughput requirement of the priority segment with the preset delay threshold range and throughput requirement standard, extract the actual delay value and throughput requirement value of each priority segment. For example, record the priority segment with a delay of 8ms and a throughput requirement of 90Mbps, and compare it with the preset high delay sensitivity threshold (less than 10ms) and high throughput requirement standard (greater than 75Mbps). Confirm that this priority segment meets the high-priority classification, and further allocate bandwidth resources. Allocate resources through the bandwidth adjustment rule. For example, the higher the delay sensitivity of the priority segment, the more bandwidth resources are allocated. For example, the high-priority segment is allocated 50MHz bandwidth, the medium-priority segment is allocated 30MHz bandwidth, and the low-priority segment is allocated 20MHz bandwidth to generate the priority segment bandwidth allocation list for dynamic resource optimization adjustment.

[0040] S503: Based on the priority segment bandwidth allocation list, combined with the real-time network load monitoring data, dynamically adjust the segmented allocation parameters of each priority segment according to the load situation, optimize the allocation ratio and growth rate of the bandwidth resources, and generate the bandwidth dynamic allocation optimization result; Combined with real-time network load monitoring data, extract the current network load parameters. For example, the network load rate is 70%, and the number of tasks in the priority segments is 10 tasks in the high-priority segment, 20 tasks in the medium-priority segment, and 15 tasks in the low-priority segment. Dynamically adjust the segmentation allocation parameters for each priority segment according to the load situation. For example, in the case of high load, reduce the bandwidth allocation of the low-priority segment to 10 MHz, and at the same time increase the bandwidth allocation of the high-priority segment to 60 MHz. Adjust the bandwidth allocation ratio for each priority segment according to the real-time load change, record the bandwidth allocation growth rate for each priority segment. For example, the bandwidth allocation growth rate of the high-priority segment is 10 Mbps / s, the bandwidth allocation growth rate of the medium-priority segment is 5 Mbps / s, and the bandwidth allocation growth rate of the low-priority segment is 0 Mbps / s. Finally, generate an optimized result for dynamic bandwidth allocation for subsequent implementation of network resource management and bandwidth allocation adjustment.

[0041] Please refer to Figure 7 , an optimization system for RedCap terminals to access 5G networks. The system includes: The channel state analysis module extracts channel state information based on the RedCap terminal spectrum state data, classifies the channel state categories, counts the category frequencies and transition relationships, calculates the channel state transition probability, and generates a dynamic transition probability matrix; The channel preference and allocation module selects the target channel with the lowest interference probability and the highest signal strength based on the dynamic transition probability matrix, calculates the adaptability of the spectrum block to the load distribution, optimizes the allocation path, divides the priority queue and associates the resource information, and generates a cross-layer priority matching result; The task access optimization module monitors the task access status based on the cross-layer priority matching result, analyzes the signal strength and interference probability, adjusts the tasks outside the range to the auxiliary channel, optimizes the task distribution between the main control channel and the auxiliary channel, and generates a hierarchical access result for the main control channel and the auxiliary channel; The bandwidth dynamic allocation module classifies the priority segments according to the delay sensitivity and throughput requirements based on the hierarchical access result of the main control channel and the auxiliary channel, dynamically adjusts the bandwidth allocation strategy, combines the real-time load to optimize the segmentation allocation parameters, and generates an optimized result for dynamic bandwidth allocation.

[0042] It should be understood that the term "and / or" in this article is merely a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist simultaneously, and B exists alone. Among them, A and B can be singular or plural. In addition, the character " / " in this article generally represents an "or" relationship between the front and back associated objects, but it may also represent an "and / or" relationship, which can be specifically understood by referring to the context.

[0043] In the present invention, "at least one" means one or more, and "a plurality" means two or more. "At least one of the following" or similar expressions refer to any combination of these items, including any combination of single item (s) or plural item (s). For example, at least one of a, b, or c can represent: a, b, c, a - b, a - c, b - c, or a - b - c, where a, b, and c can be single or multiple.

[0044] It should be understood that in various embodiments of the present invention, the sequence numbers of the above - mentioned processes do not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present invention.

[0045] Those of ordinary skill in the art can realize that the units and algorithm steps of each example described in combination with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered as exceeding the scope of the present invention.

[0046] Those skilled in the art can clearly understand that for the convenience and conciseness of description, the specific working processes of the devices, apparatuses, and units described above can refer to the corresponding processes in the foregoing method embodiments, and will not be described herein again.

[0047] In several embodiments provided by the present invention, it should be understood that the disclosed devices, apparatuses, and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the units is only a logical function division. In actual implementation, there can be other division methods. For example, multiple units or components can be combined or integrated into another device, or some features can be ignored or not executed. Another point is that the displayed or discussed couplings or direct couplings or communication connections to each other can be through some interfaces. The indirect couplings or communication connections of the devices or units can be in electrical, mechanical, or other forms.

[0048] The units described as separate components may or may not be physically separated. The components displayed as units may or may not be physical units, that is, they can be located in one place, or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0049] In addition, in each embodiment of the present invention, each functional unit can be integrated into a processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit.

[0050] If the above-mentioned function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or a part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in each embodiment of the present invention. The foregoing storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical discs that can store program codes.

[0051] The above is only the specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention can easily think of changes or substitutions, which should all be covered by the protection scope of the present invention. Therefore, the protection scope of the present invention should be subject to the protection scope of the claims.

Claims

1. An optimization method for a RedCap terminal to access a 5G network, characterized in that, The steps include: Collect data from RedCap terminals, extract spectrum status information during the process of the terminals accessing the 5G network, divide the channel status into several channel status categories, calculate the transition probabilities between channel statuses, and generate a dynamic transition probability matrix; Based on the data in the dynamic transition probability matrix, select the channel with the lowest interference probability and the highest signal strength when the RedCap terminal accesses the 5G network as the target channel, and generate a channel priority allocation result; Based on the channel priority allocation result, extract the spectrum blocks and load distribution requirements therefrom, optimize the allocation path between the spectrum blocks and the load distribution, divide multiple priority queues, and associate the priority queues with the resource information in the allocation path to generate a cross-layer priority matching result; Based on the cross-layer priority matching result, monitor the access status of the terminal tasks, perform real-time analysis on the signal strength and interference probability in the task access status, and perform real-time adjustment on the task distribution of the main control channel and the auxiliary channel according to the analysis result to generate a hierarchical access result of the main control and auxiliary channels; Based on the hierarchical access result of the main control and auxiliary channels, classify the priority segments according to the delay sensitivity and throughput requirements, and generate an optimized result of dynamic bandwidth allocation by dynamically optimizing the bandwidth resource allocation of the priority segments.

2. The optimized method for a RedCap terminal to access a 5G network according to claim 1, wherein: The dynamic transition probability matrix includes the transition probabilities of channel status categories, the signal strength ranges corresponding to the channel status categories, and the interference probability ranges corresponding to the channel status categories. The channel priority allocation result includes the target channel number, the channel priority ranking, and the available time window corresponding to the channel. The cross-layer priority matching result includes the priority queue classification, the optimized parameters of the resource allocation path, and the correlation information of the load distribution to the channel. The hierarchical access result of the main control and auxiliary channels includes the task distribution status of the main control channel, the task distribution status of the auxiliary channel, and the real-time channel load balancing parameters. The optimized result of dynamic bandwidth allocation includes the bandwidth allocation ratio of the priority segments, the dynamic adjustment parameters of the bandwidth, and the resource allocation status information of the priority segments.

3. The optimized method for a RedCap terminal to access a 5G network according to claim 1, characterized in that: The specific steps of collecting data from RedCap terminals, extracting spectrum status information during the process of the terminals accessing the 5G network, dividing the channel status into several channel status categories, calculating the transition probabilities between channel statuses, and generating a dynamic transition probability matrix are as follows: Based on the RedCap terminal signal strength, interference probability, and occupancy data, group the signal strength data and label the strength levels according to the acquisition standard of the channel status information, and divide the data ranges of the interference probability and occupancy data to generate a channel status classification data set; Based on the channel status classification data set, perform statistical analysis on the occurrence frequencies of each channel status category, sort the category frequencies according to the proportion from high to low, and perform statistical analysis on the co-occurrence relationships between each channel status category to generate a channel status category statistical list; According to the time series order of the channel status category statistical list, calculate the transition probabilities from each channel status category to other categories, and perform dynamic adjustment through the combined weights of the signal strength, interference probability, and occupancy to generate a dynamic transition probability matrix.

4. The optimized method for a RedCap terminal to access a 5G network according to claim 3, characterized in that: For calculating the transition probability from each channel state category to other categories, the formula is used: ； Obtain the transition probability from class i to class j ; Among them, is the actual occurrence times of the transfer from category i to category j, is the total number of times the transfer from category i to all categories, is the signal strength normalization value of category i, and the calculation formula is: , is the signal strength of category i, and are the maximum and minimum values of the signal strength among all categories.

5. The optimization method for a RedCap terminal to access a 5G network according to claim 1, wherein: Based on the data in the dynamic transition probability matrix, the specific steps for selecting the channel with the lowest interference probability and the highest signal strength when the RedCap terminal accesses the 5G network as the target channel and generating the channel priority allocation result are as follows: Based on the dynamic transition probability matrix and combined with the channel state data at the current moment, calculate the channel state distribution probability corresponding to each future time step, extract and record the channel state probability of each time step, and generate a channel state prediction distribution list; Based on the channel state prediction distribution list, screen the channel states of future time steps according to the condition that the signal strength value is within the upper limit range and the interference probability value is within the lower limit range, and generate a channel state preferred distribution list; Based on the channel state preferred distribution list, combined with the resource allocation requirements of the RedCap terminal, establish a corresponding relationship according to the priority order of the channels and the terminal requirements, and generate a channel priority allocation result.

6. The optimization method for a RedCap terminal to access a 5G network according to claim 5, characterized in that: For calculating the channel state distribution probability corresponding to each future time step, the formula is used: ； Obtain the next moment of the time step Channel state Probability distribution of ; wherein, is the time step is the probability distribution of the channel state , and is an element in the dynamic transition probability matrix, representing the probability that the channel state transitions to the next channel state , and is the total number of channel states.

7. The optimization method for a RedCap terminal to access a 5G network according to claim 1, wherein: Based on the channel priority allocation result, extract the spectrum block and load distribution requirements therefrom, optimize the allocation path between the spectrum block and the load distribution, and divide multiple priority queues, and associate the priority queues with the resource information in the allocation path, and the specific steps for generating the cross-layer priority matching result are as follows: Based on the channel priority allocation result, extract the distribution information of the spectrum block and the load demand information and analyze their adaptability, and set the edge weight between the two according to the value of the adaptability, and generate a spectrum block and load edge weight class list; Based on the spectrum block and load edge weight class list, conduct a combined analysis of all spectrum block allocation paths, screen the allocation path with the shortest path length and the highest total weight value, and generate an optimal resource allocation path; Based on the optimal resource allocation path, divide multiple priority queues according to the corresponding relationship between the spectrum block and the load in the allocation path, and associate the priority queues with the resource allocation information in the path, and generate a cross-layer priority matching result.

8. The optimization method for a RedCap terminal to access a 5G network according to claim 1, characterized in that: Based on the cross-layer priority matching result, monitor the access status of the terminal task, conduct real-time analysis of the signal strength and interference probability in the task access status, and make real-time adjustments to the task distribution of the main control channel and the auxiliary channel according to the analysis result, and the specific steps for generating the hierarchical access result of the main control and auxiliary channels are as follows: Based on the cross-layer priority matching result, extract the resource allocation information for the terminal to access the 5G network, monitor the access status of the terminal task in real time, analyze the signal strength and interference probability of the accessed task, and determine whether it exceeds the preset signal strength range, and generate a task access status analysis result; Based on the task access status analysis result, reallocate the tasks with signal strength lower than the preset signal strength range or interference probability higher than the preset signal strength range to the auxiliary channel, maintain the tasks within the preset signal strength range on the main control channel, record the task distribution of the main control channel and the auxiliary channel, and generate a main control and auxiliary channel distribution table; Based on the master and auxiliary channel distribution table, adjust the real-time load conditions of the master channel and the auxiliary channel, re-establish hierarchical access and perform initialization allocation of corresponding resources, and generate the hierarchical access result of the master and auxiliary channels.

9. The optimization method for a RedCap terminal to access a 5G network according to claim 1, wherein: Based on the hierarchical access result of the master and auxiliary channels, classify the priority segments according to delay sensitivity and throughput requirements, and dynamically optimize the bandwidth resource allocation for the priority segments. The specific steps for generating the optimized result of dynamic bandwidth allocation are as follows: Based on the hierarchical access result of the master and auxiliary channels, extract the priority segment data of the hierarchical access RedCap terminals, classify the priority segments according to the numerical intervals of delay sensitivity and throughput requirements, and generate the priority segment classification result; Based on the priority segment classification result, compare the actual values of the delay sensitivity and throughput requirements of the priority segments with the preset delay threshold range and throughput requirement standard, and perform refined adjustment of the corresponding bandwidth resources according to the comparison result to generate the priority segment bandwidth allocation list; Based on the priority segment bandwidth allocation list, combine the real-time network load monitoring data, dynamically adjust the segmentation allocation parameters of each priority segment according to the load conditions, optimize the allocation ratio and growth rate of the bandwidth resources, and generate the optimized result of dynamic bandwidth allocation.

10. An optimization system for a RedCap terminal to access a 5G network, characterized in that, Execute according to the optimized method for RedCap terminals to access the 5G network described in any one of claims 1-9. The system includes: The channel state analysis module extracts channel state information based on the RedCap terminal spectrum state data, divides the channel state categories, counts the category frequencies and transition relationships, calculates the channel state transition probability, and generates a dynamic transition probability matrix; The channel selection and allocation module selects the target channel with the lowest interference probability and the highest signal strength based on the dynamic transition probability matrix, calculates the fitness of the spectrum block and the load distribution, optimizes the allocation path, divides the priority queue and associates the resource information, and generates the cross-layer priority matching result; The task access optimization module monitors the task access status based on the cross-layer priority matching result, analyzes the signal strength and interference probability, adjusts the tasks outside the range to the auxiliary channel, optimizes the task distribution of the master and auxiliary channels, and generates the hierarchical access result of the master and auxiliary channels; The dynamic bandwidth allocation module classifies the priority segments according to delay sensitivity and throughput requirements based on the hierarchical access result of the master and auxiliary channels, dynamically adjusts the bandwidth allocation strategy, combines the real-time load to optimize the segmentation allocation parameters, and generates the optimized result of dynamic bandwidth allocation.

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